This document provides an introduction and literature review for a project on extracting roads from satellite imagery using semi-automatic methods. It discusses the objectives of preparing a road network for 16 wards in Thiruvananthapuram Corporation by digitizing roads from satellite images using GIS, identifying missing roads with GPS, and measuring road widths with EDM. It reviews common road extraction methods and the software used, including ERDAS Imagine for image processing and ArcGIS for digitization and database management.
Land use land cover mapping for smart village using gisSumit Yeole
This document summarizes a presentation on land use and land cover mapping for a smart village in India using GIS. The objectives were to understand GIS and remote sensing technologies and their applications in precision agriculture. The presenter described collecting satellite imagery, classifying land use types, and mapping them for the village of Kundewadi to identify agriculture, settlements, vegetation, water bodies and other land types. Pie charts showed the results, which found people primarily used the land for agriculture and suggested ways to improve wastewater, groundwater, solid waste management and increase agriculture land and trees.
The Presentation gives the overview of the process necessary for accomplishing the task for the preparation of Ground water movements and identification carried out by Rajiv gandhi national drinking water mission project.
This document summarizes a report on using GIS and remote sensing for natural resource mapping and management. It was prepared by Kamal Abdurahman for his supervisor at Koya University. The report describes using satellite imagery to map geology, vegetation, soils, and land use/land cover in a region of the Middle East. Imagery was analyzed using GIS software to extract spatial information on natural resources for sustainable management and decision making. Field verification involved collecting GPS points to validate mapped resources. Final maps of the study area's geology, soils, vegetation and land use were produced at a scale of 1:25,000.
Geodesy is the science of measuring and representing the Earth, including its gravity field. It has applications in monitoring climate change, natural hazards, volcanoes, water resources, soil moisture, glaciers, and landslides using space-based technologies like GNSS, altimetry, and gravity missions. Some key technologies are GPS, GLONASS, altimetry missions like TOPEX and JASON-1, and gravity missions like GRACE and CHAMP. Geodesy has its origins in ancient Greece and has evolved into a modern discipline using satellites to study Earth systems and processes.
This document provides an agenda and introduction to OpenStreetMap (OSM). It outlines OSM as a collaborative project to create a free map of the world. The agenda covers introductions to OSM, editing tools, data collection tools, and hands-on mapping. It discusses OSM's history, statistics, the Humanitarian OSM Team, and examples of OSM's use in crisis response and developing countries. It also outlines how to download data, edit maps, and use OSM data in various applications.
Application of gis and remote sensing in modern transport systemSabhapathy Civil
This document discusses various technologies used in intelligent transportation systems, including remote sensing, geographic information systems, and applications like advanced public transport systems, advanced traffic management systems, and advanced traveler information systems. It provides examples of intelligent transportation system implementations in India, describing components like traffic management, electronic toll collection, traveler information, and route guidance. It also outlines the benefits of intelligent transportation systems in improving traffic flow, easing congestion and driver frustration, and monitoring environmental and road conditions.
identification of ground water potential zones using gis and remote sensingtp jayamohan
This document summarizes a study that mapped groundwater potential zones in the Muvattupuzha block of Kerala, India using GIS and remote sensing. Key factors like geology, geomorphology, lineaments, drainage density, rainfall, land use, slope and soils were analyzed as layers in GIS. Weighted overlay analysis was used to delineate excellent, moderate and poor groundwater potential zones. Validation with field data found good correlation. The study aims to aid groundwater development and management to address water scarcity in the region.
This document provides an overview of geographical information systems (GIS). It discusses the history of GIS, how GIS captures and analyzes spatial data, and examples of GIS applications. The document also outlines the key components of a GIS, including technologies used, and envisions the future scope of GIS with increased integration of data over time.
Land use land cover mapping for smart village using gisSumit Yeole
This document summarizes a presentation on land use and land cover mapping for a smart village in India using GIS. The objectives were to understand GIS and remote sensing technologies and their applications in precision agriculture. The presenter described collecting satellite imagery, classifying land use types, and mapping them for the village of Kundewadi to identify agriculture, settlements, vegetation, water bodies and other land types. Pie charts showed the results, which found people primarily used the land for agriculture and suggested ways to improve wastewater, groundwater, solid waste management and increase agriculture land and trees.
The Presentation gives the overview of the process necessary for accomplishing the task for the preparation of Ground water movements and identification carried out by Rajiv gandhi national drinking water mission project.
This document summarizes a report on using GIS and remote sensing for natural resource mapping and management. It was prepared by Kamal Abdurahman for his supervisor at Koya University. The report describes using satellite imagery to map geology, vegetation, soils, and land use/land cover in a region of the Middle East. Imagery was analyzed using GIS software to extract spatial information on natural resources for sustainable management and decision making. Field verification involved collecting GPS points to validate mapped resources. Final maps of the study area's geology, soils, vegetation and land use were produced at a scale of 1:25,000.
Geodesy is the science of measuring and representing the Earth, including its gravity field. It has applications in monitoring climate change, natural hazards, volcanoes, water resources, soil moisture, glaciers, and landslides using space-based technologies like GNSS, altimetry, and gravity missions. Some key technologies are GPS, GLONASS, altimetry missions like TOPEX and JASON-1, and gravity missions like GRACE and CHAMP. Geodesy has its origins in ancient Greece and has evolved into a modern discipline using satellites to study Earth systems and processes.
This document provides an agenda and introduction to OpenStreetMap (OSM). It outlines OSM as a collaborative project to create a free map of the world. The agenda covers introductions to OSM, editing tools, data collection tools, and hands-on mapping. It discusses OSM's history, statistics, the Humanitarian OSM Team, and examples of OSM's use in crisis response and developing countries. It also outlines how to download data, edit maps, and use OSM data in various applications.
Application of gis and remote sensing in modern transport systemSabhapathy Civil
This document discusses various technologies used in intelligent transportation systems, including remote sensing, geographic information systems, and applications like advanced public transport systems, advanced traffic management systems, and advanced traveler information systems. It provides examples of intelligent transportation system implementations in India, describing components like traffic management, electronic toll collection, traveler information, and route guidance. It also outlines the benefits of intelligent transportation systems in improving traffic flow, easing congestion and driver frustration, and monitoring environmental and road conditions.
identification of ground water potential zones using gis and remote sensingtp jayamohan
This document summarizes a study that mapped groundwater potential zones in the Muvattupuzha block of Kerala, India using GIS and remote sensing. Key factors like geology, geomorphology, lineaments, drainage density, rainfall, land use, slope and soils were analyzed as layers in GIS. Weighted overlay analysis was used to delineate excellent, moderate and poor groundwater potential zones. Validation with field data found good correlation. The study aims to aid groundwater development and management to address water scarcity in the region.
This document provides an overview of geographical information systems (GIS). It discusses the history of GIS, how GIS captures and analyzes spatial data, and examples of GIS applications. The document also outlines the key components of a GIS, including technologies used, and envisions the future scope of GIS with increased integration of data over time.
This document discusses key principles of map design including selection of colors, symbols, labeling, and overall layout. It emphasizes that while there are scientific rules of map design, there is also an artistic element. The document outlines topics to be covered such as map scale and generalization, symbolization, choropleth mapping, use of color, and labeling. It provides guidelines for map elements like titles, legends, and orientation indicators. It also discusses classification schemes, issues with choropleth maps, effective use of color, and best practices for labeling and typography. Ethical practices of map design to avoid deception are highlighted.
LAND USE /LAND COVER CLASSIFICATION AND CHANGE DETECTION USING GEOGRAPHICAL I...IAEME Publication
Land use and land cover change has become a central component in current strategies for managing natural resources and monitoring environmental changes. Geographical information system and image processing techniques used for the analysis of land use/land cover and change detection of Sukhana Basin of Aurangabad District, Maharashtra state. The tools used ArcGIS10.1 and ERDAS IMAGINE9.1, landsat images of 1996, 2003and 2014. From land use / land cover change detection it is found that during 1996-2014, water bodies cover have loss of 4 Sq. Km. Barren land have 146 Sq.Km. loss and forest area with 96 Sq.Km. loss. It is found that urbanization area has gain of 51 Sq.Km. and agricultural land cover also have gain of 195 Sq.Km.
Understanding Coordinate Systems and Projections for ArcGISJohn Schaeffer
Everything you need to know to work with coordinate systems and projecting data in ArcGIS. The presentation starts by explaining the terminology, and then discusses the details you need to know to actually work successfully with coordinate systems, use the proper projections, and geographic transformations. This is a very practical look at a complex subject.
This summarizes a document about change detection techniques in remote sensing for analyzing land use and land cover changes. Remote sensing using aerial photographs and satellite imagery allows efficient monitoring of land cover changes compared to traditional field surveys. Change detection involves identifying transformations of land cover types over time and space using multi-temporal remote sensing data. Common techniques include comparing imagery from Landsat, QuickBird and other satellite sensors to detect changes in agriculture, deforestation, urban growth and other human and natural impacts on the earth's surface.
Groundwater is water located beneath the Earth's surface that saturates pores and fractures in rock and soil. It is the largest supply of fresh water available for human use. Groundwater occurs naturally and is replenished through precipitation, though the amount that can be accessed through wells varies significantly between locations. It is stored in porous geologic formations called aquifers and can be confined by layers of impermeable rock. Wells are constructed to access groundwater from aquifers, with casing, screens, grout and gravel packs used to properly construct the well. Groundwater can become contaminated if wells are improperly built or toxic materials leak into the ground near a well.
This document discusses flood mapping and summarizes the key inputs and processes. It notes that more accurate flood maps are needed and describes using precipitation data, rainfall-runoff models, hydraulic models, and terrain data to create flood maps. Issues with importing data and a lack of ArcGIS 10 support are mentioned. Future work on real-time flood mapping by interpolating water surface elevations from stage data is also discussed.
Groundwater Data Requirement and AnalysisC. P. Kumar
The document discusses groundwater data requirements, acquisition, processing, and analysis. It outlines the types of physical and hydrological data needed for groundwater studies, including maps, cross-sections, and time-series data on water levels, quality, pumping, and other factors. Key points covered include establishing monitoring networks, validating data, preparing hydrographs, water table maps, and other tools to characterize the groundwater system and identify issues like contamination or over-pumping. Statistical methods for interpolating hydrological variables from point data across regions are also summarized.
Application of RS and GIS in Groundwater Prospects ZonationVishwanath Awati
This document discusses using remote sensing and GIS techniques to map groundwater prospects zones. It presents a case study of applying these methods in Bata Valley, Himachal Pradesh, India. The methodology involves developing thematic maps of factors like geology, land use, and water levels. These maps are then overlaid and analyzed in GIS to identify zones of good, moderate, or poor groundwater potential. The study concludes these techniques can effectively map groundwater prospects and inform management plans.
This document provides an introduction to the fundamentals of remote sensing. It defines remote sensing as acquiring information about the Earth's surface without direct contact, using sensors to detect reflected or emitted energy. It describes the basic components of the remote sensing process, including an energy source, interactions with the atmosphere and target, sensor recording, data transmission and processing, analysis and interpretation, and application of results. It discusses electromagnetic radiation, the electromagnetic spectrum, and how different wavelengths interact with and are affected by the atmosphere through scattering and absorption mechanisms before reaching the target. The key atmospheric windows used for remote sensing correspond to the visible, infrared and microwave portions of the spectrum.
Landsat was a joint NASA/USGS satellite program designed to systematically acquire global land surface images. Landsat 1 was launched in 1972 as the first satellite dedicated to observing Earth's land areas. Subsequent Landsat satellites carried improved sensors with higher spatial, spectral, and radiometric resolutions. Landsat provides repetitive coverage of the entire global land mass with images useful for mapping and monitoring land use change over time.
Ambiguity in Geophysics,Gravity,Magnetic,EM,MT
Error reduction by Available applications
Geosoft,Euler,Anaylitical,Equpotential,Spectral, Principal Components
This document discusses geo-referencing raster data. It defines geo-referencing as aligning raster data to real-world coordinates so it can be viewed and analyzed with other geographic data. There are two main types of geo-referencing: absolute, which aligns raster to maps or coordinates, and relative, which aligns raster to other geo-referenced raster. The document outlines the geo-referencing process, including selecting ground control points, performing transformations, and interpreting error metrics to evaluate accuracy.
This document discusses the definition, nature, and scope of cartography. It can be summarized as follows:
1) Cartography is the science and art of making maps. It combines elements of geography, earth science, and communication to graphically portray spatial information about the earth or other celestial bodies.
2) Cartography relies on techniques from fields like surveying, remote sensing, and geography to collect and generalize data, which is then designed and constructed into maps to convey messages and facts to users.
3) Advances in technology like satellites, computers, and the internet have significantly impacted cartographic processes by providing new data sources, analysis tools, and modes of map production and sharing. However, traditional
This document provides an outline for a presentation on geospatial technologies including remote sensing, GPS, mapping, surveying, and GIS. It begins with an introduction to the geomatic umbrella and defines key geospatial concepts. It then discusses remote sensing platforms and sensors, and provides examples of agricultural and forestry applications. It also summarizes GPS systems and applications. The document defines mapping and surveying and provides examples. It concludes with an overview of GIS hardware, software, data, and functions and discusses example applications in emergency management, petroleum management, and utilities.
It is a presentation made on the actual work done on site for the selection of construction site for the dam,it can be used as well for other site suitability.
Geo-referencing is GIS based spatial analysis technique which is discussed in this presentation.For video you can see following link:
https://www.youtube.com/watch?v=h559lOsvOU8&feature=youtu.be&fbclid=IwAR3PB9YB4i86zrYyzxbiz_g2-4_ujowdO1gfm4Lz5E3vGf56Fn5DAzeUA_8
Map to Image Georeferencing using ERDAS softwareSwetha A
The document provides steps to georeference a satellite image using ERDAS software. It involves opening the image and a georeferenced toposheet in separate viewers, selecting ground control points that match features in both, and using a polynomial geometric model to resample the image. At least 4 GCPs should be selected to georeference the image, which can then be verified using swipe and transparency tools to check the alignment of features.
This document provides an overview of key concepts in GIS including shapefiles, grids, rasters, vectors, DEM, TIN, coordinate systems, and common file formats. It discusses the differences between raster and vector data, and explains that shapefiles are commonly used to store vector data while grids are used for raster data. DEM and TIN are introduced as methods for representing elevation data. The document also covers projected and unprojected coordinate systems and provides examples of coordinate systems. Common file formats for both raster and vector data are listed.
Remote Sensing: Principal Component AnalysisKamlesh Kumar
Principal components analysis is a orthogonal transformational technique (preserving the symmetry between vectors and angles) to reveal new set of data arguably better from the original data set and better capture the essential information as well. It happens often that some variables are highly correlated with a lot of duplication. Instead of discarding the redundant data, principal components analysis condenses the info. in inter-correlated variables into a few variables, called principal components.
The main idea of Principal Component Analysis (PCA) is to reduce the dimensionality of a data set consisting of many variables correlated with each other, either heavily or lightly, while retaining the variation present in the dataset, up to the maximum extent.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Types of roads can be classified based on speed and accessibility. The main types discussed are:
1) Freeways have strict rules - they are multi-lane divided roads with no stops or cross traffic and limited access for pedestrians and bicycles. Entrance and exit ramps allow vehicles to safely merge or exit at freeway speeds.
2) Major highways have high speeds like freeways but may have turning lanes and traffic lights or interchanges. Access is partially limited.
3) Minor highways connect residential areas or rural areas and can have divided or undivided lanes with possible stops.
Local streets provide access to properties with full access and slow speeds while collectors and arterials have increasing
The document proposes a monorail system for Trivandrum, Kerala to address traffic issues. It discusses monorail technology, advantages for Trivandrum including affordable cost and minimal land use. A market study identifies potential routes connecting major business hubs and residential areas. A phased project plan from 2010-2020 is proposed, with the first phase connecting Vikas Bhavan to Technopark. Financing options including PPP models are suggested. Next steps include a feasibility study and detailed project report to start Phase I construction by mid-2010.
This document discusses key principles of map design including selection of colors, symbols, labeling, and overall layout. It emphasizes that while there are scientific rules of map design, there is also an artistic element. The document outlines topics to be covered such as map scale and generalization, symbolization, choropleth mapping, use of color, and labeling. It provides guidelines for map elements like titles, legends, and orientation indicators. It also discusses classification schemes, issues with choropleth maps, effective use of color, and best practices for labeling and typography. Ethical practices of map design to avoid deception are highlighted.
LAND USE /LAND COVER CLASSIFICATION AND CHANGE DETECTION USING GEOGRAPHICAL I...IAEME Publication
Land use and land cover change has become a central component in current strategies for managing natural resources and monitoring environmental changes. Geographical information system and image processing techniques used for the analysis of land use/land cover and change detection of Sukhana Basin of Aurangabad District, Maharashtra state. The tools used ArcGIS10.1 and ERDAS IMAGINE9.1, landsat images of 1996, 2003and 2014. From land use / land cover change detection it is found that during 1996-2014, water bodies cover have loss of 4 Sq. Km. Barren land have 146 Sq.Km. loss and forest area with 96 Sq.Km. loss. It is found that urbanization area has gain of 51 Sq.Km. and agricultural land cover also have gain of 195 Sq.Km.
Understanding Coordinate Systems and Projections for ArcGISJohn Schaeffer
Everything you need to know to work with coordinate systems and projecting data in ArcGIS. The presentation starts by explaining the terminology, and then discusses the details you need to know to actually work successfully with coordinate systems, use the proper projections, and geographic transformations. This is a very practical look at a complex subject.
This summarizes a document about change detection techniques in remote sensing for analyzing land use and land cover changes. Remote sensing using aerial photographs and satellite imagery allows efficient monitoring of land cover changes compared to traditional field surveys. Change detection involves identifying transformations of land cover types over time and space using multi-temporal remote sensing data. Common techniques include comparing imagery from Landsat, QuickBird and other satellite sensors to detect changes in agriculture, deforestation, urban growth and other human and natural impacts on the earth's surface.
Groundwater is water located beneath the Earth's surface that saturates pores and fractures in rock and soil. It is the largest supply of fresh water available for human use. Groundwater occurs naturally and is replenished through precipitation, though the amount that can be accessed through wells varies significantly between locations. It is stored in porous geologic formations called aquifers and can be confined by layers of impermeable rock. Wells are constructed to access groundwater from aquifers, with casing, screens, grout and gravel packs used to properly construct the well. Groundwater can become contaminated if wells are improperly built or toxic materials leak into the ground near a well.
This document discusses flood mapping and summarizes the key inputs and processes. It notes that more accurate flood maps are needed and describes using precipitation data, rainfall-runoff models, hydraulic models, and terrain data to create flood maps. Issues with importing data and a lack of ArcGIS 10 support are mentioned. Future work on real-time flood mapping by interpolating water surface elevations from stage data is also discussed.
Groundwater Data Requirement and AnalysisC. P. Kumar
The document discusses groundwater data requirements, acquisition, processing, and analysis. It outlines the types of physical and hydrological data needed for groundwater studies, including maps, cross-sections, and time-series data on water levels, quality, pumping, and other factors. Key points covered include establishing monitoring networks, validating data, preparing hydrographs, water table maps, and other tools to characterize the groundwater system and identify issues like contamination or over-pumping. Statistical methods for interpolating hydrological variables from point data across regions are also summarized.
Application of RS and GIS in Groundwater Prospects ZonationVishwanath Awati
This document discusses using remote sensing and GIS techniques to map groundwater prospects zones. It presents a case study of applying these methods in Bata Valley, Himachal Pradesh, India. The methodology involves developing thematic maps of factors like geology, land use, and water levels. These maps are then overlaid and analyzed in GIS to identify zones of good, moderate, or poor groundwater potential. The study concludes these techniques can effectively map groundwater prospects and inform management plans.
This document provides an introduction to the fundamentals of remote sensing. It defines remote sensing as acquiring information about the Earth's surface without direct contact, using sensors to detect reflected or emitted energy. It describes the basic components of the remote sensing process, including an energy source, interactions with the atmosphere and target, sensor recording, data transmission and processing, analysis and interpretation, and application of results. It discusses electromagnetic radiation, the electromagnetic spectrum, and how different wavelengths interact with and are affected by the atmosphere through scattering and absorption mechanisms before reaching the target. The key atmospheric windows used for remote sensing correspond to the visible, infrared and microwave portions of the spectrum.
Landsat was a joint NASA/USGS satellite program designed to systematically acquire global land surface images. Landsat 1 was launched in 1972 as the first satellite dedicated to observing Earth's land areas. Subsequent Landsat satellites carried improved sensors with higher spatial, spectral, and radiometric resolutions. Landsat provides repetitive coverage of the entire global land mass with images useful for mapping and monitoring land use change over time.
Ambiguity in Geophysics,Gravity,Magnetic,EM,MT
Error reduction by Available applications
Geosoft,Euler,Anaylitical,Equpotential,Spectral, Principal Components
This document discusses geo-referencing raster data. It defines geo-referencing as aligning raster data to real-world coordinates so it can be viewed and analyzed with other geographic data. There are two main types of geo-referencing: absolute, which aligns raster to maps or coordinates, and relative, which aligns raster to other geo-referenced raster. The document outlines the geo-referencing process, including selecting ground control points, performing transformations, and interpreting error metrics to evaluate accuracy.
This document discusses the definition, nature, and scope of cartography. It can be summarized as follows:
1) Cartography is the science and art of making maps. It combines elements of geography, earth science, and communication to graphically portray spatial information about the earth or other celestial bodies.
2) Cartography relies on techniques from fields like surveying, remote sensing, and geography to collect and generalize data, which is then designed and constructed into maps to convey messages and facts to users.
3) Advances in technology like satellites, computers, and the internet have significantly impacted cartographic processes by providing new data sources, analysis tools, and modes of map production and sharing. However, traditional
This document provides an outline for a presentation on geospatial technologies including remote sensing, GPS, mapping, surveying, and GIS. It begins with an introduction to the geomatic umbrella and defines key geospatial concepts. It then discusses remote sensing platforms and sensors, and provides examples of agricultural and forestry applications. It also summarizes GPS systems and applications. The document defines mapping and surveying and provides examples. It concludes with an overview of GIS hardware, software, data, and functions and discusses example applications in emergency management, petroleum management, and utilities.
It is a presentation made on the actual work done on site for the selection of construction site for the dam,it can be used as well for other site suitability.
Geo-referencing is GIS based spatial analysis technique which is discussed in this presentation.For video you can see following link:
https://www.youtube.com/watch?v=h559lOsvOU8&feature=youtu.be&fbclid=IwAR3PB9YB4i86zrYyzxbiz_g2-4_ujowdO1gfm4Lz5E3vGf56Fn5DAzeUA_8
Map to Image Georeferencing using ERDAS softwareSwetha A
The document provides steps to georeference a satellite image using ERDAS software. It involves opening the image and a georeferenced toposheet in separate viewers, selecting ground control points that match features in both, and using a polynomial geometric model to resample the image. At least 4 GCPs should be selected to georeference the image, which can then be verified using swipe and transparency tools to check the alignment of features.
This document provides an overview of key concepts in GIS including shapefiles, grids, rasters, vectors, DEM, TIN, coordinate systems, and common file formats. It discusses the differences between raster and vector data, and explains that shapefiles are commonly used to store vector data while grids are used for raster data. DEM and TIN are introduced as methods for representing elevation data. The document also covers projected and unprojected coordinate systems and provides examples of coordinate systems. Common file formats for both raster and vector data are listed.
Remote Sensing: Principal Component AnalysisKamlesh Kumar
Principal components analysis is a orthogonal transformational technique (preserving the symmetry between vectors and angles) to reveal new set of data arguably better from the original data set and better capture the essential information as well. It happens often that some variables are highly correlated with a lot of duplication. Instead of discarding the redundant data, principal components analysis condenses the info. in inter-correlated variables into a few variables, called principal components.
The main idea of Principal Component Analysis (PCA) is to reduce the dimensionality of a data set consisting of many variables correlated with each other, either heavily or lightly, while retaining the variation present in the dataset, up to the maximum extent.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Types of roads can be classified based on speed and accessibility. The main types discussed are:
1) Freeways have strict rules - they are multi-lane divided roads with no stops or cross traffic and limited access for pedestrians and bicycles. Entrance and exit ramps allow vehicles to safely merge or exit at freeway speeds.
2) Major highways have high speeds like freeways but may have turning lanes and traffic lights or interchanges. Access is partially limited.
3) Minor highways connect residential areas or rural areas and can have divided or undivided lanes with possible stops.
Local streets provide access to properties with full access and slow speeds while collectors and arterials have increasing
The document proposes a monorail system for Trivandrum, Kerala to address traffic issues. It discusses monorail technology, advantages for Trivandrum including affordable cost and minimal land use. A market study identifies potential routes connecting major business hubs and residential areas. A phased project plan from 2010-2020 is proposed, with the first phase connecting Vikas Bhavan to Technopark. Financing options including PPP models are suggested. Next steps include a feasibility study and detailed project report to start Phase I construction by mid-2010.
Evaluation of operational efficiency of urban road network using travel time ...eSAT Journals
This document evaluates the operational efficiency of an urban road network in Tiruchirappalli, India using travel time reliability measures. Traffic volume and travel times were collected using video data from 8-10 AM on various roads. Average travel times, 95th percentile travel times, and buffer time indexes were calculated to assess reliability. Non-motorized vehicles were found to most impact reliability on one road. A relationship between buffer time index and traffic volume was developed. Finally, a travel time model was created and validated based on length, speed, and volume.
A Security Model for Virtual Infrastructure in the CloudEditor IJCATR
1) The document proposes a new security model called the cloud protection system for virtual infrastructure in cloud computing.
2) The model aims to increase security in the cloud by more accurately monitoring virtual machines and cloud infrastructure components to detect threats like denial of service attacks.
3) The key components of the proposed model include monitoring core cloud components and middleware, detecting any unauthorized changes, and prioritizing packet processing to avoid dropping important packets during denial of service attacks.
Abstract Traffic congestion on city road networks is one of the main issues to be addressed by today’s traffic management schemes. The frequent traffic jams at major junctions call for an efficient traffic management system in place. The image sequences from a camera are analyzed using edge detection technique, object counting method and queue length estimation to obtain the most efficient technique. Subsequently, the number of vehicles at the intersection is evaluated and traffic is efficiently managed. The paper also proposes to implement a real-time emergency vehicle detection system. In case an emergency vehicle is detected, the lane is given priority over all the others. Using image-processing operations to calculate traffic density is cost effective as cameras are cheaper and affordable devices compared to any other devices such as sensors. Keywords: Edge detection, Object counting, vehicle queue length, traffic management, image processing.
The document is a draft concession agreement for an annuity-based infrastructure project. It outlines the key terms of the agreement between the National Highways Authority of India (NHAI) and a concessionaire for the Panagarh-Palsit Project, including definitions, grant of concession, project site details, obligations of both parties, annuity payment structure, change in law, force majeure, defaults and termination provisions. The schedules provide further details on the project scope, site conditions, performance security, annuity payment schedule and other technical requirements.
This document discusses road network development and management. It covers topics such as providing access through road networks, finding objective indicators to measure performance, improving existing road networks by reducing travel time delays, accidents, and vehicle operation costs. It also discusses generating income through road tolls and taxes to finance construction and maintenance costs. The main objectives for road authorities are to provide access, improve financial feasibility, expand networks to connect isolated areas, and reduce environmental impacts.
Academic Presentation On Review Of Road NetworkKamal Rumah
This document discusses road networks and their analysis. It begins with an introduction and historical overview of roads. It then describes the hierarchy of road networks, including arterial, collector and local roads. The document analyzes road network patterns using techniques like graph theory. It also discusses the current and future operation of road networks, including the potential for connected and autonomous vehicles. It concludes that advanced technologies will deliver benefits by managing road networks better to support economic growth and innovation.
This document summarizes integrated water resources management (IWRM) in Asia. It discusses IWRM as a process that brings stakeholders together to increase water security through locally appropriate solutions. It provides examples of progress, including IWRM being reflected in policies and the creation of river basin organizations. Promising results are noted, such as performance benchmarking and investment roadmaps. The document stresses the importance of partnerships and boundary-spanning leadership to generate and share knowledge to co-create solutions across boundaries.
Volcanic eruptions can have immediate and long-term effects on the surrounding land, air, and water. Immediate effects include lava flows, volcanic ash, mudflows, pyroclastic flows, landslides, and steam explosions. Long-term effects involve continued mudflows over time, crater collapse, hardened lava forming new rock layers, and ash helping to build new landscapes. Eruptions release gases like sulfur dioxide and carbon dioxide into the air, and can produce acid rain by releasing acids. They also affect water by creating hot springs, geysers, fumaroles, and deep sea vents.
The document discusses road networks, including their functions and components. It reviews literature on road network concepts and Vision 2040, which outlines expectations for reliable, environmentally-friendly, and accessible road infrastructure. The document also examines road network operations, traffic management, and the role of road networks in social and economic development.
The document discusses road networks, including their origins, patterns, hierarchy, design, control and analysis. It notes that road networks developed from the need for transportation and consist of nodes, links and control facilities. The hierarchy categorizes roads by function and includes arterial, collector and local roads. Modern techniques for analyzing networks include connectivity analysis and considering accessibility impacts on urban areas.
India has one of the largest road networks in the world spanning over 4.6 million kilometers. The network consists of national highways, state highways, major district roads, and rural roads. While India has made significant improvements in expanding and modernizing its road infrastructure in recent decades, issues around maintenance, expansion, safety, and congestion persist due to the large size and usage of the network. Future plans aim to continue enhancing the network through the addition of more expressways and improving rural connectivity.
This document provides information on navigation maps including road network coverage in India, road types, and other transportation features. It details that the maps cover 658 cities in India with road network data on over 22 million km of roads, including 69,825 km of national highways. The maps also include railway coverage of 65,762 km of track. Road types classified include expressways, dual carriageways, roundabouts, and slip roads. Additional information covered includes road class, traffic flow, route numbers, and other transportation layers like railways and waterways.
Logistics Infrastructure slideshow explains the current mode of transport in India and . It also discussed about the future requirements and opportunities in Logistic Infra.
India has several advantages that make its logistics industry poised for growth, such as a large, young population and strong GDP growth. Currently logistics costs account for 13% of GDP, compared to 8.7% in the US, representing significant potential for cost reduction. The government is taking initiatives to improve infrastructure like roads, railways, ports and airports in order to improve efficiency and reduce costs. While the logistics industry is large and growing, it remains fragmented and faces challenges around lack of organization, outdated practices, and underdeveloped infrastructure and technology.
Disruptions on Road Networks: Impact on traffic characteristicsJumpingJaq
This document summarizes a study that investigated the impact of short-term disruptions on traffic characteristics. The study analyzed travel time and traffic volume data from five pairs of parallel routes during peak periods, comparing scenarios with and without incidents. Key findings were that average travel times remained similar, but travel time volatility increased under incident conditions. Traffic volumes shifted slightly between routes when incidents occurred, indicating adaptive route choice behavior. The study highlights the need for transport models to account for disrupted traffic conditions and adaptive user equilibrium.
This document discusses India's infrastructure development and policy. It outlines the current state of India's infrastructure, including poor road conditions and electricity shortages. It also identifies factors impeding development, such as a poor judicial system and corruption. The document then covers India's efforts to develop various infrastructure sectors like power, ports, and roads through public-private partnerships and privatization. It concludes by noting that if private investment in infrastructure continues, India can expect to sustain its high economic growth.
This document summarizes a study that evaluated the accuracy of GPS and automatic level instruments for topographic surveying. The study collected elevation data using both instruments at points in a study area in Iraq. The data was input into GIS software to create contour maps and digital elevation models (DEMs) from each dataset. The accuracy of the DEMs was then evaluated and compared. The results showed the effect that the source data, DEM resolution, and ground control point distribution had on accuracy. This allowed the study to assess the relative accuracy and effectiveness of GPS versus automatic leveling for topographic data collection and DEM generation.
This document summarizes a study that evaluated the accuracy of GPS and automatic level instruments for topographic surveying. Researchers collected elevation data for 25 points in the study area using both a GPS receiver and an automatic level. They then used ArcGIS to create contour maps and digital elevation models from each dataset. The results showed that the GPS data had lower standard deviation and was therefore more accurate than the automatic level data. However, automatic leveling remains a cost-effective method for small study areas. The integration of GPS and GIS techniques allows for efficient processing and analysis of spatial data to produce high accuracy topographic maps and DEMs.
This document summarizes a study that used remote sensing and GIS techniques to produce a digital land use map of the Technical Institute of Anbar in Iraq. Satellite imagery and attribute data were collected and digitized in ArcGIS to create vector data layers representing land use classes. The final digital map identified destroyed buildings, service buildings, green areas, sports facilities, and unused land. It found that 20% of the institute's area contained structures while 80% was unused land. The digital map and geographic database produced can serve as a basis for future studies of the Technical Institute of Anbar.
This document summarizes a study that used remote sensing and GIS techniques to produce a digital land use map of the Technical Institute of Anbar in Iraq. Satellite imagery and attribute data were collected and digitized in ArcGIS to create vector data layers representing land use classes. The final digital map identified destroyed buildings, service buildings, green areas, sports facilities, and unused land. It found that 20% of the institute's area contained structures while 80% was unused land. The digital map and geographic database produced can serve as a basis for future studies of the Technical Institute of Anbar.
Performance of Phase Congruency and Linear Feature Extraction for Satellite I...IOSR Journals
This document summarizes research on extracting linear features from satellite images. It introduces using a phase congruency and linear feature extraction model combined with an adaptive smoothing algorithm. The paper aims to evaluate the advantages and limitations of this approach when applied to satellite image feature extraction. It also describes other common feature extraction methods, such as using mathematical morphology operations like dilation and erosion. Overall, the document reviews techniques for automated linear feature extraction from satellite imagery.
Perhaps the most important component of a GIS is in the part of data used in GIS. The data for GIS can be derived from various sources. A wide variety of data sources exist for both spatial and attribute data.
A Geographic Information System (GIS) is a computer system for capturing, storing, analyzing and managing data and associated attributes which are spatially referenced to Earth. GIS integrates common database operations with tools for visualizing and analyzing geographic data. Key components of a GIS include hardware, software, data, people and methods. GIS draws upon techniques from fields such as cartography, remote sensing, photogrammetry, surveying and statistics. Spatial data in GIS can be represented using vector or raster data models. Vector models represent geographic features as points, lines and polygons while raster models divide space into a grid of cells. GIS performs functions such as inputting data, map making, data manipulation, file management, querying
Environment Impact Assessment Using Remote Sensingshubham shama
This document provides an overview of using remote sensing and GIS for environmental impact assessments. It discusses how satellite imagery allows for large area coverage in short time periods and how GIS enables spatial analysis and modeling. Examples are given of assessing impacts of projects like dams by computing command areas and changes over time. Both active sensors like radar and lidar, and passive sensors like radiometers are outlined. The advantages of remote sensing for environmental monitoring and assessing rapidly changing phenomena are highlighted.
This document summarizes a study that used GIS techniques to design a ring road for Erode District in Tamil Nadu, India. The study aimed to establish the shortest path for the road network to minimize traffic in the city and provide better transportation. GIS was used to survey the area, create contour maps and 3D models, evaluate different route alignments, and estimate cut and fill volumes. Raster analysis incorporated terrain information to determine the lowest cost route. The resulting ring road design was a 22 km route around Erode City connecting major roads to improve traffic flow and economic growth while reducing environmental pollution.
IJRET-V1I1P3 - Remotely Sensed Images in using Automatic Road Map CompilationISAR Publications
High Resolution satellite Imagery is an important source for road network extraction for
roads database creation, refinement and updating. Various sources of imagery are known for their
differences in spectral, spatial, radioactive and temporal characteristics and thus are suitable for
different purposes of vegetation mapping. A number of shape descriptors are computed to reduce
the misclassification between road and other spectrally similar objects. The detected road segments
are further refined using morphological operations to form final road network, which is then
evaluated for its completeness, correctness and quality. The proposed methodology has been tested
on updating on road extraction from remotely-sensed imagery.
This project involves updating the geographic information system (GIS) database and maps for the existing electricity distribution network in Muzaffarabad, Pakistan. The network was originally developed in 2006 but has not been updated since 2010. The project will update the digital database and maps to reflect current infrastructure by collecting data on transformers, poles, conductors, and consumers. This updated GIS database will help improve planning, implementation, and operation of the electricity network by providing accurate spatial and non-spatial utility data to support decision making. The specific area of focus will be the 11kV City-4 feeder network within the 132kV Muzaffarabad grid.
This document summarizes geospatial applications in civil engineering. It discusses how remote sensing and GIS techniques can be used for site investigations, terrain mapping and analysis, water resources engineering, town planning and urban development, transportation network analysis, and landslide studies. Specific applications are described, including using drones for site investigations, terrain analysis tools like slope and aspect maps, watershed and hydrologic modeling, and urban planning. Data sources, tools, and workflows are also outlined.
GIS Application Used in Urban Planning In IndiaIRJET Journal
This document discusses how geographic information systems (GIS) are used for urban planning in India. It provides an overview of GIS, describing it as a system for capturing, storing, analyzing, and managing spatially referenced data. GIS allows users to create maps, perform spatial queries and analysis, and visualize and model information. The document outlines how GIS is used in various aspects of urban planning like infrastructure development, transportation planning, and monitoring of health, sanitation, and other city services. It provides examples of how GIS aids in tasks like feasibility studies, land use planning, and public participation in the planning process. Overall, the document illustrates how Indian planners leverage GIS technologies to effectively plan and manage urban development.
Topographic Information System as a Tool for Environmental Management, a Case...iosrjce
IOSR Journal of Environmental Science, Toxicology and Food Technology (IOSR-JESTFT) multidisciplinary peer-reviewed Journal with reputable academics and experts as board member. IOSR-JESTFT is designed for the prompt publication of peer-reviewed articles in all areas of subject. The journal articles will be accessed freely online.
The document discusses the application of remote sensing and geographical information systems (GIS) in civil engineering. It provides definitions of remote sensing as remotely sensing objects on Earth and GIS as a system to capture, store, analyze and present geographically referenced data. The document outlines some basic concepts of GIS including its origins from technologies like computer-aided cartography and databases. It also discusses data types in GIS like spatial data, attributes and different data models. Common software, functional elements and applications of GIS in areas like facilities management and environmental planning are summarized as well.
Quantitative analysis of Mouza map image to estimate land area using zooming ...TELKOMNIKA JOURNAL
The document presents a quantitative analysis of mouza map images to estimate land area using zooming and Canny edge detection techniques. It discusses how mouza maps are currently used to record land measurements in Bangladesh but manual estimation is time-consuming. The proposed system first zooms in on mouza map images using curvature interpolation. It then segments the selected area using Canny edge detection and calculates the area from extracted features. Compared to field measurements, the system achieved 89.8% accuracy, allowing land administrators to more efficiently provide area information to landowners.
Geographic Information System for Bachelor in Agriculture EngineeringDinesh Bishwakarma
This document discusses the application of geographic information systems (GIS) and remote sensing in agriculture. It defines GIS as a system used to input, store, retrieve, manipulate, analyze and output geospatial data to support decision making. The key components of GIS are described as hardware, software, data, people, and methods. Remote sensing is defined as the non-contact recording of electromagnetic spectrum information using sensors from platforms like aircraft or satellites, and analyzing the data using image processing. Common applications of remote sensing and GIS in agriculture include crop mapping and monitoring, soil analysis, and precision farming.
This document provides an introduction to Geographic Information Systems (GIS) including definitions, components, and applications. It defines GIS as having three integrated parts: geographic, information, and systems. GIS combines hardware, software, data, people, and methods to capture, store, analyze, and display spatial data. Key applications of GIS include navigation, natural resource management, and environmental planning. The document also outlines the basic functions of GIS including capturing, storing, querying, analyzing, displaying, and presenting geographic data.
A geographic information system (GIS) allows users to capture, store, manipulate, analyze, manage and display spatial or geographical data. GIS integrates hardware, software and data to visualize relationships within mapped information. Key components include hardware, GIS software, data and people. There are two main data types - raster, which stores cell-based data like images, and vector, which represents discrete features using points, lines and polygons. GIS has evolved significantly since the 1960s and is now widely used across various fields and applications.
Similar to PREPARATION OF ROAD NETWORK FROM SATELLITE IMAGERY (20)
Use PyCharm for remote debugging of WSL on a Windo cf5c162d672e4e58b4dde5d797...shadow0702a
This document serves as a comprehensive step-by-step guide on how to effectively use PyCharm for remote debugging of the Windows Subsystem for Linux (WSL) on a local Windows machine. It meticulously outlines several critical steps in the process, starting with the crucial task of enabling permissions, followed by the installation and configuration of WSL.
The guide then proceeds to explain how to set up the SSH service within the WSL environment, an integral part of the process. Alongside this, it also provides detailed instructions on how to modify the inbound rules of the Windows firewall to facilitate the process, ensuring that there are no connectivity issues that could potentially hinder the debugging process.
The document further emphasizes on the importance of checking the connection between the Windows and WSL environments, providing instructions on how to ensure that the connection is optimal and ready for remote debugging.
It also offers an in-depth guide on how to configure the WSL interpreter and files within the PyCharm environment. This is essential for ensuring that the debugging process is set up correctly and that the program can be run effectively within the WSL terminal.
Additionally, the document provides guidance on how to set up breakpoints for debugging, a fundamental aspect of the debugging process which allows the developer to stop the execution of their code at certain points and inspect their program at those stages.
Finally, the document concludes by providing a link to a reference blog. This blog offers additional information and guidance on configuring the remote Python interpreter in PyCharm, providing the reader with a well-rounded understanding of the process.
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
An improved modulation technique suitable for a three level flying capacitor ...
PREPARATION OF ROAD NETWORK FROM SATELLITE IMAGERY
1. 1
CHAPTER 1
INTRODUCTION
1.1 GENERAL
Preparation of maps has been one of the challenging areas in surveying. The
conventional methods are to go to area directly and take measurements, level etc and
plot the map. This requires large human resources and consumes time and money.
Also accuracy of this map is susceptible to human and many instruments involved.
But in the present days we cannot afford time. Also Map revision is traditionally a
manual task especially when maps are updated on the basis of aerial images and
existing map data. For this reason, maps are typically out of date. For example, it has
been reported that, for a number of reasons, the revision lag-time for topographic
maps from the United States Geological Survey (USGS) is more than 23 years. To
overcome these types of difficulties methods of extraction of road network from
satellite image plays an important role.
The different methods of road extraction from satellite image includes the
Automatic method (J. B. Mena 2005) and Semi-automatic method (Jun Zhou 2006) of
road extraction. In automatic method the human computer interaction is very low or it
is said to be done with pure mathematical algorithms by the computer, whereas in the
semi-automatic method there is human interaction also along with the help of
computer. In semiautomatic road extraction, a road in the image is delineated using its
geometric and photometric properties with the initial positions provided by an
operator.
While microcomputer made their first appearance three decades ago, it is only
in the last 15 years they have become "seriously useable" machines. This situation has
occurred as the consequence of a series of developments which includes: faster
processing facility, large capacity, high performance and relatively inexpensive hard
discs; high resolution colour monitors; CD-ROM players becoming near universal;
and availability of inexpensive, high quality colour output devices and colour
scanners. These hardware technology changes have gone in parallel with changes in
better data conversion, software for scanners, better software for image manipulation
and storage, and improvements in database management system.
2. 2
The innovation and development in computer, communication and software is
contributing towards the growth of information technology. The net result of these
changes is that it is now relatively easy to create, store, retrieve, and analyze large
quantities of spatial and non-spatial data of urban and transportation system. A related
change is the rapid development of spatial information technologies such as Remote
Sensing (RS), Global Positioning System (GPS) and Geographical Information
System (GIS).This made the process like road network generation, map revision,
flood mapping, urban change detection, etc. easy as compared to the conventional
methods to the same.
Road tracking methods make assumptions about road characteristics like, roads are
elongated, road surfaces are usually homogeneous, there is adequate contrast between
road and adjacent areas, roads may not be elongated at crossings, bridges, and ramps,
road surfaces may be built from various materials that cause radiometric changes,
ground objects such as trees, houses, vehicles and shadows may occlude the road
surface and may strongly influence the road appearance, road surfaces may not have
adequate contrast with adjacent areas because of road texture, lighting conditions, and
weather conditions, the resolution of satellite images can have a significant impact on
computer vision algorithms.
One problem with these systems is that such assumptions are pre-defined and
fixed whereas image road features vary considerably. Such properties cannot be
completely predicted and they constitute the main source of problems with fully
automated systems. One solution to this problem is to adopt a semiautomatic
approach that retains the ‘‘the human in the loop” where computer vision algorithms
are used to assist humans performing these tasks.
The report briefly explains the preparation of road from satellite imagery by
the semi automatic method which includes the process like geo-referencing,
mosaicing, haze reduction, noise removal, image enhancements like contrast
stretching, filtering, and edge enhancement by using software ERDAS Imagine and
extraction of selected area and digitizing done in Arc GIS. Also uses EDM for width
measurement of roads at junctions and handheld GPS for non visible roads in the
satellite image.
3. 3
1.2 OBJECTIVES
The main objectives of the project is extraction of roads from satellite images of the
selected 16 wards of Thiruvananthapuram Corporation, preparation of road network
which include digitization of road network using GIS, identification of missing road
using hand held GPS and road width measurement using EDM.
4. 4
CHAPTER 2
LITERATURE REVIEW
2.1 GENERAL
The Road extraction from remotely sensed imagery has been an active
research area in map preparation for over two decades. During the past 20 years, a
number of semi-automatic and automatic methods and algorithms for road extraction
have been developed. Conventional methods of road extraction usually consist of
three main steps, road finding, road tracking, and road linking. In road finding, local
properties of the image are tested and road candidates are found using certain criteria.
The detected road candidates are then traced to form road segments. The separated
road segments are finally linked to generate a road network using geometric
constraints. In semiautomatic road extraction, a road in the image is delineated using
its geometric and photometric properties with the initial positions provided by an
operator. These methods use local geometric constraints for road tracking and linking.
Because the global structure of the road network is not considered, wrong segments
are unavoidable, and occlusions such as trees, shadows, surface anomalies, and road
width change can cause the tracking to be lost.
2.2 REMOTE SENSING
Remote sensing is the science and to some extent art of obtaining information
about an object, area, or phenomenon through the analysis of data acquired by a
device that is not in contact with the object, area, or phenomenon under
investigations. This is done by sensing and recording the reflected or emitted energy
and processing, analyzing, and applying that information. The advent of Remote
Sensing through space borne and air-borne platforms and sensors has opened new
vistas for modern, scientific surveying of earth’s natural resources. Remote sensing
data is the name given to any data where information about a location is collected
remotely, i.e. from a different location, such as collecting information about the
ground surface from inside an aircraft.
5. 5
2.3 ERDAS Imagine 8.6
ERDAS IMAGINE is an image processing software with raster graphics editor
capabilities designed by ERDAS, Inc. for geospatial applications. ERDAS IMAGINE
is aimed primarily at geospatial raster data processing and allows the user to prepare,
display and enhance digital images for mapping use in GIS or in C ADD software. It
is a toolbox allowing the user to perform numerous operations on an image and
generate an answer to specific geographical questions. By manipulating imagery data
values and positions, it is possible to see features that would not normally be visible
and to locate geo-positions of features that would otherwise be graphical. The level of
brightness or reflectance of light from the surfaces in the image can be helpful with
vegetation analysis, prospecting for minerals etc. Other usage examples include linear
feature extraction, generation of processing work flows ("spatial models" in ERDAS
IMAGINE), import/export of data for a wide variety of formats, ortho-rectification,
mosaicing of imagery, stereo and automatic feature extraction of map data from
imagery.
The digital Image Processing done in ERDAS includes:
• Preprocessing
Geometric correction
Radiometric correction
Haze reduction
Noise removal
• Image enhancement
Contrast stretching
Filtering
Edge enhancement
2.4 ArcGIS
In the highly dynamic and complex world 'information' has become a critical
resource for effective and efficient management of organisation. Information
Technology in its various forms is enabling organizations to churn raw data into
meaningful information for effective decision making. One such form of Information
Technology (IT) is Geographic Information System (GIS). It is described as: “An
organized collection of computer hardware, software, geographic data and personnel
6. 6
designed to efficiently capture, store, update, manipulate, analyze, and display all
forms of geographically referenced information”. According to this definition, GIS
includes not only computing capability and data, but also manages the users, and
organizations within which they function and institutional relationships that govern
their management and use of information. GIS system design and implementation
planning are not a separate process. They must occur in conjunctions with one
another.
ArcGIS is a suite consisting of a group of geographic information system
(GIS) software products produced by Esri.
ArcGIS is a system for working with maps and geographic information. It is
used for: creating and using maps; compiling geographic data; analyzing mapped
information; sharing and discovering geographic information; using maps and
geographic information in a range of applications; and managing geographic
information in a database.
The system provides an infrastructure for making maps and geographic
information available throughout an organization, across a community, and openly on
the Web.
7. 7
2.4.1 Conceptualization of GIS
Conceptually, a GIS can be envisioned as a stacked set of map layers, where
each layer is aligned or registered to all other layers. Typically, each layer will contain
a unique geographic theme or data type. The GIS database stores both the spatial data
(where something occurs) and the attribute data (characteristics of the spatial data) for
all of the features shown on each layer. These themes may include, for example,
topography, soils, land-use, cadastral (land ownership) information, or infrastructure
such as roads, Traffic Analysis Zones (TAZ), pipelines, power lines, or sewer
networks. Figure 1 gives a schematic view of geographic layer system in GIS. By
sharing mutual geography, all layers in the GIS can be combined or overlaid in any
user-specified combination.
Fig. 1 Mapping layers of GIS
2.5 GLOBAL POSITIONING SYSTEM (GPS)
Global Positioning System (GPS) has tremendous potential for better transport
management/planning. Traffic management, emergency services (fire service,
accident relief, ambulance service, policing, etc.), are the few areas where GPS can
8. 8
play significant role due to its capability to provide near accurate location (latitude,
longitude, altitude) and other details. Traffic routing, movement of vehicles, VIP
movement, taxi service, fleet management for passenger and cargo services etc.
becomes easier by using GPS receivers on vehicles. Use of GPS along with GIS
database of the city can help to perform the above tasks more effectively. GPS is also
very useful in creating accurate spatial databases. Global positioning system is an
earth-orbiting Satellite based system that provides signals anywhere on or above
earth, 24 hours a day, round the year, and irrespective of weather, and that can be used
to determine precise time and the position of a GPS receiver in three dimensions. This
technology is increasingly used as input for GIS particularly for precise positioning of
geo-spatial data and for collection of data from the field. One major advantage is its
capability of forming a powerful building block in an integrated system. GPS together
with a co-ordinate system and GIS produces a map and the map facilitates navigation.
GPS is rapidly becoming an important tool to the GIS and Remote sensing industries.
2.5.1 Concept of GPS
GPS consists of a constellation of radio navigation satellite and a ground
control segment. It manages satellite operation and users with specialized receivers
who use the satellite data to satisfy a broad range of positioning requirements. In
brief, following are the key features of GPS:-
1. The basis of GPS is ‘triangulation’ more precisely trilateration from satellites
2. A GPS receiver measures distance using the travel time of radio signals.
3. To measure travel time GPS needs very accurate timing that is achieved with some
techniques.
4. Along with distance, one needs to know exactly where the satellites are in space.
5. Finally one must correct for any delays, the signal experience as it travels through
the atmosphere.
The whole idea behind GPS is to use satellites in space as reference points for
location here on earth. By very accurately measuring the distances from at least three
satellites, we can ‘triangulate’ our position anywhere on the earth by resection
method.
9. 9
CHAPTER 3
METHODOLOGY
3.1 GENERAL
Methodology used for linear feature extraction can be used for the extraction
of road network from satellite imaginary. Suitable area can be selected from
Thiruvananthapuram Corporation and high resolution Cartosat image can be
collected. A shapefile of the study area will be created using ArcGIS and the image
can be cut using the shapefile. The image can be processed according to the algorithm
using ERDAS IMAGINE software. The processed image is digitized in ArcGIS and a
map of road network can be prepared.
3.2 SELECTION OF AREA
Suitable area for the project is selected from the Thiruvananthapuram
corporation map considering the availability of high resolution satellite image
(Cartosat image, 2.5m). 16 wards were selected.
Fig. 2 Ward Map of Trivandrum Corporation
10. 10
3.3 DATA AND MATERIALS
The data collection includes the collection of satellite images having sufficient
spatial resolution, GPS data using hand held GPS for jointing the missing links of
roads with the road network extracted from satellite imagery, width of road at
junctions using EDM. The processing of the data for the extraction of road network
from satellite imagery and further corrections using the additional data collected by
GPS and EDM requires software like ERDAS IMAGINE and ArcGIS.
SATELLITE IMAGES
The road map preparation requires high resolution satellite images otherwise
the roads may not be visible in the processed image. In the Department of Civil
Engineering the available images were (a) IRS LISS III which is having a spatial
resolution of 23m, (b) Panchromatic which is having a spatial resolution of 5.8m, (c)
Cartosat which is having a special resolution of 2.5m, (d) LISS IV which is having a
spatial resolution of 5.8m. Cartosat images containing the selected area were collected
from Department of Civil Engineering as it is having a high spatial resolution of 2.5m
comparing to the available satellite images.
GPS
Roads having smaller width are not able to digitize in ArcGIS. Those roads
can be plotted using hand held GPS. The hand held GPS (Magellan) having an
accuracy of 5m is collected from the Department Of Civil Engineering.
EDM
The edges of the roads having low width cannot be visible from the satellite image,
the width of the roads are to be measured and an average value is to be assigned at the
junctions to each roads meeting at the junction these are to be measured by using
EDM.
ERDAS IMAGINE
The pre processing operations like geo-referencing, mosaicing, haze reduction, noise
removal, image enhancements like contrast stretching, filtering, and edge
enhancement are to be done in ERDAS IMAGINE software.
11. 11
ArcGIS
The processes like extraction of the selected 16 wards from the satellite image and the
digitising of the extracted roads are to be done in ArcGIS software.
3.4 EXTRACTION OF ROAD
The road networks may not be clearly visible in the satellite image in the raw form
thus it is to be processed and enhanced to get the road network clearly. This include
the Pre-processing like Geo-referencing, Mosaicing of image, Shapefile preparation,
Extraction of selected area, Haze Reduction, Noise Removal and also Image
Enhancement like Contrast Stretching, Filtering and Edge Enhancement.
3.4.1 Pre-processing of images
Pre-processing refers to the image rectification and restoration procedures.
This is the initial step done in data processing.
In their raw form, as received from imaging sensors mounted on satellite
platforms, remotely-sensed data generally contain flaws or deficiencies. The
correction of deficiencies and the removal of flaws present in the data are termed pre-
processing because, quite logically, such operations are carried out before the data are
used for a particular purpose. Despite the fact that some corrections are carried out at
the ground receiving station, there is often still a need on the user’s part for some
further pre-processing. The subject is thus considered here before methods of image
enhancement and analysis are examined. It is difficult to decide what should be
included under the heading of ‘pre-processing’, since the definition of what is, or is
not, a deficiency in the data depends to a considerable extent on the use to which
those data are to be put. If, for instance, a detailed map of the distribution of particular
vegetation types is required then the geometrical distortion present in an uncorrected
remotely-sensed image will be considered to be a significant deficiency. On the other
hand, if the purpose of the study is to establish the presence or absence of a particular
class of land use (such as irrigated areas in an arid region) then a visual analysis of a
suitably-processed false-colour image will suffice and, because the study is concerned
with determining the presence or absence of a particular land use type rather than its
precise location, the geometrical distortions in the image will be seen as being of
secondary importance. A second example will show the nature of the problem .An
attempt to estimate reflectance of a specific target from remotely-sensed data will be
12. 12
hindered, if not completely prevented, by the effects of interactions between the
incoming and outgoing electromagnetic radiation and the constituents of the
atmosphere. Correction of the imagery for atmospheric effects will, in this instance,
be considered to be an essential part of data pre-processing whereas, in some other
case (for example, discrimination between land-cover types in an area at a particular
point in time), the investigator will be interested in relative, rather than absolute, pixel
values and thus atmospheric correction would be unnecessary. Measurements of
change over time using multi-temporal image sets will, in the case of optical imagery,
require correction for atmospheric variability, and it will also be necessary to register
the images forming the multi-temporal sequence to a common geographical
coordinate system. In addition, corrections for changes in sensor calibrations will be
needed to ensure that like is compared with like.
Because of the difficulty of deciding what should be included under the
heading of pre-processing methods, an arbitrary choice has been made. Correction for
geometric, radiometric and atmospheric deficiencies, and the removal of data errors or
flaws, is covered here despite the fact that not all of these operations will necessarily
be applied in all cases. This point should be borne in mind by the reader. It should not
be assumed that the list of topics covered in this topic constitutes a menu to be
followed in each and every application. The pre-processing techniques discussed in
the following sections should, rather, be seen as being applicable in certain
circumstances and in particular cases. The investigator should decide which pre-
processing techniques are relevant on the basis of the nature of the information to be
extracted from the remotely-sensed data.
The pre-processing procedure is done as follows:
Geo-referencing:
Geo-referencing is the process of aligning spatial data (layers that are shape
files: polygons, points, etc.) to an image file such as an historical map, satellite image,
or aerial photograph. Toposheet of the study area is to be geo-referenced adopting
Projected Coordinate System, UTM, Zone 43N. With respect to the geo-referenced
toposheet the four satellite imagery are to be geo-referenced in ERDAS IMAGINE.
13. 13
Mosaicing of image:
The selected area containing the 16 wards were distributed in two cartosat
images. The Cartosat images are to be mosaiced to make a single image. This is to be
done in ERDAS Imagine.
From data preparation menu by using mosaic tool the two geo-referenced
Cartosat images are to be mosaiced to a single image.
Shapefile preparation:
Shapefiles spatially describe geometries, points, polylines, and polygons.
These, for example, could represent water wells, rivers or road network, and lakes or
boundaries, respectively. The following procedure is done to prepare shapefile.
From the ArcCatalog a personal Geo-database was created in that a new
feature class was added with the specifications like polygonal feature, projected
coordinate system as required for the shapefile. Then using the edit tool bar the
boundary of the selected wards is traced and saved. This export to ERDAS
IMAGINE and the area is to be extracted.
Extraction of selected area:
The selected area containing the 16 wards of the Trivandrum Corporation is to
be extracted from the mosaiced Cartosat image, by preparing the shapefile of the area
in ArcGIS and cutting the area from Cartosat image in ERDAS IMAGINE.
Table 1 Selected Wards
Ward No. Ward Name Ward No. Ward Name
17 Pattom 29 Vazhuthacaud
22 Sasthamangalam 30 Kanilampara
23 Kowdiyar 43 Valyashala
24 Kuravankonam 44 Jagathy
25 Kanchankode 81 Thampanoor
26 Kununkuzhi 82 Vanchiyoor
27 Palayam 83 Sreekandeshwaram
28 Thycaud 94 Kannammoola
14. 14
Haze Reduction:
Haze compensation procedure is designed to minimize the influence of path
radiance effects. One means of haze compensation in multispectral data is to observe
the radiance recorded over target areas of essentially zero reflectance. For example,
the reflectance of deep clear water is essentially zero in the near-infrared region of the
spectrum. Therefore any signal observed over such an area represents the path
radiance, and this value can be subtracted from all pixels in the band.
Noise Removal:
Image noise is any unwanted disturbance in image data that is due to
limitation in the sensing, signal digitization or data recording process. The potential
sources of noise range from periodic drift or malfunction of a detector, to electronic
interference between sensor components to intermittent "hiccups" in the data
transmission and recording sequence. Noise can either degrade or totally mask the
true radiometric information content of a digital image. The objective of noise
removal is to restore an image close an approximation of the original scene as
possible.
3.4.2 Image Enhancement
The procedures applied to image data in order to more effectively display or
record the data for subsequent visual interpretation. Normally, image enhancement
involves techniques for increasing the visual distinctions between features in a scene.
The, objective is to create a new” images from the original image data in order to
increase the amount of information that can be visually interpreted from the data. The
enhanced images can be displayed interactively on a monitor or they can be recorded
in a hardcopy format, either in black and white or in color. There are no simple rules
for producing the single “best" image for a particular application. Often several
enhancements made from the same “raw” image are necessary.
The various image enhancements done to the imagery in ERDAS IMAGINE
includes:
15. 15
Contrast Stretching:
Contrast stretching (often called normalization) is a simple image
enhancement technique that attempts to improve the contrast in an image by
`stretching' the range of intensity values it contains to span a desired range of values,
e.g. the full range of pixel values that the image type concerned allows. It differs from
the more sophisticated histogram equalization in that it can only apply a linear scaling
function to the image pixel values. As a result the `enhancement' is less harsh.
The intent of contrast stretching is to expand the narrow range of brightness
values typically present in an input image over a wider range of grey values. The
result is an output image that is designed to accentuate the contrast between features
of interest to the image analyst.
Contrast Stretching is to be done such that the required features will be more
clearly visible in the satellite images. The breakpoint of each band of the image is to
be adjusted in the ERDAS IMAGINE so that roads are more clearly visible. For each
band of multi-spectral images the breakpoints are to be adjusted and check whether
the roads are visible. The resultant image will give a better idea of location of roads in
the images.
Filtering:
Spatial filters emphasize or deemphasize image data of various spectral
frequencies. Spatial frequency refers to the “roughness” of the tonal variations
occurring in an image. Image areas of high spatial frequency are tonally rough. That is
gray levels in these areas change abruptly over a relatively small number of pixels
(e.g. across roads or field borders). “Smooth” image areas are those of low spatial
frequency, where gray levels vary only gradually over a relatively large number of
pixels (e.g. large agricultural fields or water bodies)
Low pass filters are designed to emphasize low frequency features (large area
changes in brightness) and deemphasize the high frequency components of an image
(local detail). A simple low pass filter may be implemented by passing a moving
window throughout an original image and creating a second image whose DN at each
pixel corresponds to the local average within the moving window at each of its
positions in the original image. Low pass filtering is done in ERDAS IMAGINE by
16. 16
passing a moving a 3x3 pixel window throughout the original image and a low
frequency image is obtained. The low frequency image obtained after low pass filter
is smooth or blurred so that the original image details are blurred.
High pass filters do just the reverse of low pass filter. They emphasize the
detailed high frequency components of an image and deemphasize the more general
low frequency information. A simple high pass filter may be implemented by
subtracting a low pass filtered image (pixel by pixel) from the original, unprocessed
image. The high frequency image obtained after high pass filtering will have a high
contrast and gives a better idea of roads. The image will be sharpened and it roads
will be more clear.
Edge Enhancement:
In Edge enhancement it enhances the edge contrast of an image. It is typically
implemented in three steps:
• A high frequency component image is produced containing the edge
information. The Kernel size used to produce this image is chosen
based on the roughness of the image. “Rough” image suggest small
filter sizes (e.g. 3x3 pixels), whereas large sizes (9x9 pixels) are used
with “smooth” images.
• All or a fraction of the gray level in each pixel of the original scene is
added back to the high frequency component image.
• The composite image is contrast stretched. This result in an image
containing local contrast enhancement of high frequency features that
also preserves the low frequency brightness information contained in
the scene.
In ERDAS IMAGINE, the high frequency image is passed through a Kernel of
size 3x3 and a high frequency image is produced containing the edge information.
The composite image is then contrast stretched. This image is a high frequency
sharpened image. The edges of roads will be clearer in these images. This image
clearly gives the details of roads in the study area for their extraction. This road
details are then digitized in Arc GIS.
17. 17
3.5 DIGITIZING OF EXTRACTED ROADS
The processed image is to be loaded in ArcGIS for the extraction of roads. The
roads are digitized by visual interpretation and saved as corresponding feature class
for each image. A road passing through an area with uniformly distributed vegetation,
like paddy field becomes prominent due to their different reflection characteristics.
The areas where there is a very good background contrast then the road section
throughout and edges of the road can be identified clearly.
3.6 PLOTTING OF MISSING ROADS USING GPS
Roads having smaller width are not able to digitize in ArcGIS. Those roads
can be plotted using hand held GPS. The readings, latitudes and longitudes, of roads
are to be taken manually by field investigation and need to be added to the missing
links manually.
3.7 ROAD WIDTH MEASUREMENT USING EDM
Generally the width of the road is same from junction to junction. Even though
there are slight variations but we are assuming it to be uniform. The widths of
extracted roads are to be measured using Electronic Distance Meter (EDM) at various
locations and the average value is assigned as the uniform value.
18. 18
CHAPTER 4
DATA PROCESSING
4.1 SATELLITE IMAGES OF STUDY AREA
Cartosat images containing the selected area (Cartosat 547354 & 547355)
were collected from Geo-informatics lab as it is having a high spacial resolution of
2.5m comparing to the available satellite images.
Fig. 3 Cartosat Images (2.5m)
4.2 PRE-PROCESSING OF IMAGES
In their raw form, as received from imaging sensors mounted on satellite
platforms, remotely-sensed data generally contain flaws or deficiencies. The
correction of deficiencies and the removal of flaws present in the data are termed pre-
processing because, quite logically, such operations are carried out before the data are
used for a particular purpose.
Pre-processing refers to the image rectification and restoration procedures. This is the
initial step done in data processing.
Geo-referencing:
Geo-referencing of toposheet of the study area is done and the projection
system adopted is Projected Coordinate System, UTM, Zone 43N. With respect to the
geo-referenced toposheet the four satellite imagery were geo-referenced in ERDAS
IMAGINE.
19. 19
Fig. 4 Geo-referenced Images
Mosaicing of image:
The selected area containing the 16 wards were distributed in two Cartosat
images. The Cartosat images are mosaiced to make a single image. This is done in
ERDAS Imagine.
From data preparation menu by using mosaic tool the two geo-referenced Cartosat
images are mosaiced to a single image.
Fig. 5 Mosaiced Image
Shapefile preparation:
From the Arc Catalog a personal Geo-database was created in that a new feature
class was added with the specifications like polygonal feature, projected coordinate
system as required for the shapefile. Then using the edit tool bar the boundary of the
20. 20
selected wards is traced and saved. This is exported to ERDAS IMAGINE and the
area is extracted.
Fig. 6 Shape File of the Selected Area
Extraction of selected area:
The selected area containing the 16 wards of the Trivandrum Corporation is
extracted(area 25sq km) from the mosaiced Cartosat image, by preparing the shapefile
of the area in ArcGIS and cutting the area from Cartosat image in ERDAS IMAGINE.
Fig.7 Extracted Image
Haze Reduction:
Haze reduction is done in ERDAS IMAGINE. The resultant images obtained after
haze reduction is shown in the fig.5. For convenience haze correction routines are
21. 21
often applied uniformly throughout a scene. The raw image will be enhanced in
contrast but the image will be blurred.
Fig. 8 Haze Reduced Image
Noise Removal:
Image noise is any unwanted disturbance in image data that is due to
limitation in the sensing, signal digitization or data recording process.The objective of
noise removal is to restore an image close an approximation of the original scene as
possible. There was not much noise in the raw data so there was not much difference
in the image obtained after noise reduction.
Fig. 9 Noise Removed Image
22. 22
4.3 IMAGE ENHANCEMENT
The procedures applied to image data in order to more effectively display or
record the data for subsequent visual interpretation. Normally, image enhancement
involves techniques for increasing the visual distinctions between features in a scene.
Contrast Stretching
Contrast Stretching is done such that the required features will be more clearly
visible in the satellite images. The breakpoint of each band of the image is adjusted in
the ERDAS IMAGINE so that roads are more clearly visible. For each band of multi-
spectral images the breakpoints are adjusted and checked whether the roads are
visible. The resultant image will gives a better idea of location of roads in the images.
Fig. 10 Contrast Stretched Image
High-pass Filtering
A simple high pass filter may be implemented by subtracting a low pass
filtered image (pixel by pixel) from the original, unprocessed image. The high
frequency image obtained after high pass filtering will have a high contrast and gives
a better idea of roads. The image will be sharpened and it roads will be more clear.
23. 23
Fig. 11 High-pass Filtered Image
Edge Enhancement
In ERDAS IMAGINE, the high frequency image is passed through a Kernel of
size 3x3 and a high frequency image is produced containing the edge information.
The composite image is then contrast stretched. This image is a high frequency
sharpened image. The edges of roads will be clearer in these images. This image
clearly gives the details of roads in the study area for their extraction. This road
details are then digitized in Arc GIS.
Fig. 12 Edge Enhanced Image
24. 24
4.4 DIGITISING OF ENHANCED IMAGES
The processed image is then loaded in ArcGIS for the extraction of roads. The
roads are digitized by visual interpretation and saved as corresponding feature class
for each image. A road passing through an area with uniformly distributed vegetation,
like paddy field becomes prominent due to their different reflection characteristics.
The areas where there is a very good background contrast then the road section
throughout and edges of the road can be identified clearly. From the selected 16 wards
of Trivandrum corporation 75km length of road is digitised.
Fig. 13 Digitised Road Map
25. 25
CHAPTER 5
MAP REVISION BY FIELD DATA
The missing road networks from the satellite image due to various reasons like
the resolution of image, canopy cover, single band image, narrow width of roads etc,
are to be incorporated to the digitised road map by using collected GPS and EDM
data of the corresponding roads in ArcGIS.
5.1 GPS DATA
Roads having smaller width were not able to digitize in ArcGIS. Those roads
can be plotted using hand held GPS. The readings, latitudes and longitudes, of roads
were taken manually by field investigation and need to be added to the missing links
manually.
Table 2 GPS Coordinates of Missing Roads
LOCATION LAT LONG
Pattom 76°56´34´´ 8°31´1´´
76°56´38´´ 8°31´1´´
76°56´38´´ 8°31´5´´
76°56´38´´ 8°31´8´´
76°56´42´´ 8°31´8´´
76°56´42´´ 8°31´5´´
76°56´46´´ 8°31´5´´
76°56´46´´ 8°31´1´´
76°56´42´´ 8°31´1´´
76°56´42´´ 8°30´58´´
76°56´42´´ 8°30´54´´
26. 26
5.2 EDM DATA
The widths of extracted roads are to be measured using Electronic Distance
Meter (EDM) at various locations and the average value is assigned as the uniform
value.
Table 3 Road Widths at Junctions
Junction Road Width (m)
Plamood Manchadivila 6.5
Plamood to PMG (One Way) 7
PMG to Plamood (One Way) 8
Varambasseri 5.5
Pattom 14
PMG Barton Hill 9
Museum 15
Palayam 17
Museum Vellayambalam 15
Nanthancode 7
Palayam 13.5
PMG 15
Vellayambalam Museum 15
Thiruvananthaapuram –
Thenmala
15
Shasthamangalam 18
Peroorkada 14.55
27. 27
Palayam Statue 18.5
PMG 18.5
Bakery Fly Over 21
Kerala University 23
Peroorkada Ambalamukku 13.5
Main Central 15
Kesavadasapuram Ulloor 10
Main Central 15
Pattom 14
Ayurveda College Statue 15
East Fort 15
LMS PMG 18
Palayam 14
Vellayambalam 15
Kawdiar Peroorkada 13.5
Pattom 13
Vellayambalam 13.5
Pattom Kesavadasapuram 14
Kawdiar 13
PMG 14
Medical College 7
28. 28
Kerala University General Hospital 13
Bakery Junction 21
VJT Hall 10
PMG 6
General Hoapital Vanchiyoor 10
MG 8
Pattoor 14
Patoor Palayam-Airport 14
Kanammoola Palam 5
Pallimukku Palayam-Airport 14
Kanammoola Palam 5
Kanammoola SBI Medical College 7
PMG 6.5
Statue Ambujavilasam 6
Press 7
30. 30
CHAPTER 6
CONCLUSION
The road map preparation using conventional methods is a tedious and time
consuming task. As the transportation facilities in the developed as well as developing
countries change at very faster rate new methods of road map preparation that make
use of the information technology is need of the time. Road extraction from satellite
image can play an important role in the map revision processes. The software like
ERDAS Imagine and Arc GIS, and Geospatial data collection instruments like GPS,
and EDM helps in the extraction of road network of an area from a satellite image
which can be used to update maps at a faster rate.
The main advantage of the approach used for the preparation of road network
using satellite imagery and other geospatial data collection mechanisms is easiness of
the work and the reduced time. Software like ERDAS Imagine saves a lot of time in
the map making process as it provides a great help in the rectification and restoration
of satellite images and further enhancement process of the image for the delineation
of the linear features like road network of an area. A geographic information system
has the power to incorporate different thematic layers of geo-spatial data and integrate
it with the non spatial data. A GIS based road network, as prepared in this work, will
facilitate further manipulation and easy updating. It can also be used for the decision
makers by employing a suitable analysis with the data.
The accuracy of the work is mainly determined by the resolution of the
satellite image used. The available high resolution image in the Department of Civil
Engineering was Cartosat image with a spatial resolution of 2.5m which was a single
band image. The results show that the width of the roads that can be extracted from
the satellite image has a relation to the spatial resolution of the data. In the present
work roads having width smaller than 5m, which is two times the spatial resolution of
the image, could not be identified in the extraction process.
Road map preparation using satellite images can eliminate a lot errors
associated with the conventional map making using field survey, especially the
inherent errors associated with the conventional plotting can be eliminated by
automatic extraction and further digitising in GIS.
31. 31
REFERENCE
1. Ana Paula Camargo (2001). “The Uses of GPS in Civil Engineering as a Tool
for Monitoring Structural Oscillations of Bridges”
2. Heng Lia, Zhen Chenb, Liang Yonga, Stephen C.W. Kongc (2004).
“Application of integrated GPS and GIS technology for reducing construction
waste and improving construction efficiency”
3. Jun Zhou, Walter F. Bischof Terry and Caelli (2006). “Road tracking in aerial
images based on human–computer interaction and Bayesian filtering”
4. Karthika (2011). “Effect of spatial and spectral resolution on the extraction of
road network”
5. Lillesand T. M., Kiefer R. W., John Wiley and sons (1979). “Remote sensing
and image interpretation”
6. Mena J.B., Malpica J.A. (2005). “An automatic method for road extraction in
rural and semi-urban areas starting from high resolution satellite imagery”
7. Paul M. Mather (2000). “Computer Processing of Remotely-Sensed Images
An Introduction”