Landslide_Mapping_Sri lanka
•Download as PPT, PDF•
0 likes•203 views
This document presents a landslide susceptibility map created for Sri Lanka using a bivariate statistical method. Six factors that influence landslide susceptibility are identified: lithology, soil type, landuse, slope, aspect, and curvature. GIS software is used to generate weighted maps for each factor based on statistical analysis of landslide occurrences. These weighted maps are then combined through map algebra to create a final landslide hazard susceptibility map for Sri Lanka. The workflow involves data preparation steps like rasterization of vector data, reclassification of aspect, slope and curvature, followed by zonal statistics analysis and calculation of weight values to produce individual weighted maps for each factor, which are then summed to obtain the final susceptibility map.
Report
Share
Report
Share
Recommended
Remote sensing & GIS
This presentation gives an idea of how remote sensing and GIS are used practically through an example.
Projections
This document discusses map projections and their use in GIS. It begins by explaining that map projections are needed to portray the spherical Earth on a flat surface, and that coordinate reference systems define the relationship between projected maps and real-world locations. It then discusses different types of map projections, including their advantages and disadvantages. Specifically, it covers conformal, equal-distance, and equal-area projections. It also discusses terminology like datum, spheroid, and false northing/easting values. Finally, it provides guidance on choosing a suitable projection and properly assigning projections in GIS projects.
Dem analaysis and catchment delineation using GIS
This presentation describes how a GIS can be used to derive DEM derivatives and delineate catchments and streams
Potentiel3.0 hydro
1. The document outlines a multi-step process involving data preparation, community mapping, focus groups, flood simulations, and community validation and decision making.
2. Key steps include data preparation with local mapping parties, UAV flights and imagery collection, focus groups to identify issues, initial flood simulations, and revisions based on community feedback.
3. Examples are given of community decision making, such as organizing to clean wastewater canals at the neighborhood level and removing advertising boards claiming credit for local work.
Remote sensing analysis
http://www.fao.org/globalsoilpartnership
This Presentation was made during the Digital Soil Mapping training that took place in Amman - Jordan from 29 November - 7 December 2015, and it presents the Remote sense analysis
© FAO: http://www.fao.org
Machine learning and Satellite Images
We use the Georeferenced results of the 2010 Census in Mexico to train machine learning algorithms to detect growth in cities and contribute new information to estimate the total population.
Lect 10 & 11 coordinate systems
1) The document discusses coordinate systems used in GIS, specifically geographic and projected coordinate systems.
2) The basic coordinate system used to represent locations on Earth is latitude and longitude, which form a geographic grid.
3) Projected coordinate systems like UTM transform latitude and longitude coordinates into plane coordinates for use in GIS.
Integrating eo with official statistics using machine learning in mexico geo ...
Integrating eo with official statistics using machine learning in mexico geo ...Abel Alejandro Coronado Iruegas
Sharing the experience and results of using georeferenced 2010 Census data in Mexico and EO to train algorithms in order to detect urban growth and generate useful information for estimating population for non-census years.Recommended
Remote sensing & GIS
This presentation gives an idea of how remote sensing and GIS are used practically through an example.
Projections
This document discusses map projections and their use in GIS. It begins by explaining that map projections are needed to portray the spherical Earth on a flat surface, and that coordinate reference systems define the relationship between projected maps and real-world locations. It then discusses different types of map projections, including their advantages and disadvantages. Specifically, it covers conformal, equal-distance, and equal-area projections. It also discusses terminology like datum, spheroid, and false northing/easting values. Finally, it provides guidance on choosing a suitable projection and properly assigning projections in GIS projects.
Dem analaysis and catchment delineation using GIS
This presentation describes how a GIS can be used to derive DEM derivatives and delineate catchments and streams
Potentiel3.0 hydro
1. The document outlines a multi-step process involving data preparation, community mapping, focus groups, flood simulations, and community validation and decision making.
2. Key steps include data preparation with local mapping parties, UAV flights and imagery collection, focus groups to identify issues, initial flood simulations, and revisions based on community feedback.
3. Examples are given of community decision making, such as organizing to clean wastewater canals at the neighborhood level and removing advertising boards claiming credit for local work.
Remote sensing analysis
http://www.fao.org/globalsoilpartnership
This Presentation was made during the Digital Soil Mapping training that took place in Amman - Jordan from 29 November - 7 December 2015, and it presents the Remote sense analysis
© FAO: http://www.fao.org
Machine learning and Satellite Images
We use the Georeferenced results of the 2010 Census in Mexico to train machine learning algorithms to detect growth in cities and contribute new information to estimate the total population.
Lect 10 & 11 coordinate systems
1) The document discusses coordinate systems used in GIS, specifically geographic and projected coordinate systems.
2) The basic coordinate system used to represent locations on Earth is latitude and longitude, which form a geographic grid.
3) Projected coordinate systems like UTM transform latitude and longitude coordinates into plane coordinates for use in GIS.
Integrating eo with official statistics using machine learning in mexico geo ...
Integrating eo with official statistics using machine learning in mexico geo ...Abel Alejandro Coronado Iruegas
Sharing the experience and results of using georeferenced 2010 Census data in Mexico and EO to train algorithms in order to detect urban growth and generate useful information for estimating population for non-census years.GIS fundamentals - raster
This document discusses raster data in GIS. Raster data represents geographic information as a grid of cells or pixels organized into a matrix of rows and columns. Each cell contains a value representing information such as elevation, vegetation index, or land use class. Raster data can represent data as integers, floats, or other data types and comes in various resolutions, with higher resolution providing more detail. Rasters can be single band (one value per cell) or multiband (multiple values per cell representing different wavelengths). Examples of raster data sources include remote sensing imagery, digital elevation models, and land cover maps.
Understanding Coordinate Systems and Projections for ArcGIS
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.
POSTER_BUSTOS
The Sky view factor (SVF) represents the fraction of visible sky from a location and is used to estimate the urban heat island effect, energy balance, and thermal comfort. This document describes an online GIS tool that calculates SVF values based on building footprints, heights, and observer locations. The tool divides the hemisphere into slices, calculates elevation angles and distances to buildings to determine the fraction of sky obstructed at each observer point. Calculated SVF values are uploaded to ArcGIS Online to share maps of SVF distributions for urban planning and analysis of different design proposals.
Remotesensingandgisapplications
This document contains exam questions for a Remote Sensing and GIS Applications course. It includes 8 questions related to topics like remote sensing systems, GIS components and data structures, photogrammetry, natural disasters, and watershed drainage patterns. Students are instructed to answer 5 of the 8 questions, which vary in length from short answer to longer explanations and include diagrams/flowcharts. Key remote sensing and GIS concepts covered include raster vs vector data, active vs passive systems, interpolation methods, and using the technologies for applications like flood mapping and groundwater analysis.
Unit 3: figures
This document contains 14 figures related to glacial dynamics in Greenland. The figures show:
1) A map of Greenland with four study sites circled
2) Average air temperatures over Greenland from 2001-2010, showing 2010 was anomalously warm
3) Snowmelt data for Greenland calculated from satellite imagery
4) Maps of ice velocity for several Greenland glaciers from 2000-2001 and 2008-2009
5) A surface elevation change map of Greenland from satellite altimetry data
6) Time series graphs of ice elevation change at four study sites from satellite and airborne altimetry
7) A time series graph of ice mass changes in Greenland from 2002-2012 based on
07 a70110 remotesensingandgisapplications
This document contains exam questions for a Remote Sensing and GIS Applications course. It includes questions about rainfall-runoff relationships and models, scanner systems for remote sensing, key aspects of making effective maps from geospatial data, GIS workflow processes and cognitive models, disadvantages of remotely sensed data and physics concepts related to electromagnetic radiation, and questions about photogrammetry applications, raster data models, and comparing aerial photographs to topographic maps.
Map design in GIS
This document provides an overview of map design using GIS software. It discusses important elements to include in maps such as titles, legends, scale bars, and north arrows. It also covers choosing appropriate symbology for different map features, file formats, and resolutions for different map outputs. The document is intended to teach learners how to design effective maps using GIS software.
Geographic Information Systems (April – 2016) [Question Paper | CBSGS: 75:25 ...
Geographic Information Systems (April – 2016) [Question Paper | CBSGS: 75:25 ...Mumbai B.Sc.IT Study
Geographic Information Systems (April – 2016) [Question Paper | CBSGS: 75:25 Pattern]
april - 2017, april - 2016, april - 2015, april - 2014, april - 2013, october - 2017, october - 2016, october - 2015, october - 2014, may - 2016, may - 2017, december - 2017, 75:25 pattern, 60:40 pattern, revised course, old course, mumbai bscit study, mumbai university, bscit semester vi, bscit question paper, old question paper, previous year question paper, semester vi question paper, question paper, CBSGS, IDOL, kamal t, internet technology, digital signals and systems, data warehousing, ipr and cyber laws, project management, geographic information systemOSM Buildings - Buildings in space, sun in time
The document discusses calculating the position of the sun and projecting shadows from buildings onto maps using OpenStreetMap data. It provides code to calculate the sun's position based on date, latitude and longitude, as well as code to project a shadow of a standard length and direction from that sun position. The integration of these calculations allows rendering building shadows on web maps. Optimizations are discussed such as using the same shadow vector for all points and avoiding shadows casting on other objects.
Mst 1 question paper(bt401) cse
This document contains a mid-semester examination for the subject of Engineering Mathematics - III. The exam contains 4 questions worth a total of 28 marks. Question 1 has two parts that involve finding real roots of equations using the Regula Falsi and Newton-Raphson methods. Question 2 has two parts involving Newton's interpolation formula and Newton's divided difference formula. Question 3 has two parts, one requiring finding a cubic polynomial and the other evaluating a definite integral using different numerical methods. Question 4 has two parts involving solving equations using Crout's method and Gauss-Jacobi method.
3D Watershed Celebes
This document outlines the steps to derive watersheds in Central Celebes, Indonesia from SRTM data using 3D modeling software and ArcGIS tools:
1) Load and preprocess SRTM data to create a DEM raster, including cropping, filling blanks, converting projections, and saving as a GeoTIFF.
2) Perform terrain analysis in ArcGIS to calculate flow direction, flow accumulation, stream definition, stream segmentation, and catchment grid delineation using the ArcHydro tools.
3) View the resulting watersheds and hydrological networks in 3D in ArcScene by setting the appropriate layer properties and vertical exaggeration.
Floodplain Modeling with LiDAR-Derived Terrain
The document discusses the process of creating a terrain model and delineating floodplains from LiDAR data using ArcGIS and HEC-GeoRAS/HEC-RAS software. Key steps include building a terrain from LiDAR point clouds, breaklines and other feature classes, converting the terrain to a raster, using HEC-GeoRAS to generate cross-section geometry from the raster for hydraulic modeling in HEC-RAS, and mapping floodplains back in GIS from HEC-RAS results. Issues like missing LiDAR data or incorrect elevations may require additional field surveying.
MySQL Spatial Extensions - Boston MySQL Meetup April 2005
This document summarizes Andrew Collins' April 4th, 2005 presentation on MySQL Spatial Extensions. It outlines the OpenGIS Simple Features Specification geometry class hierarchy and spatial data model. It also describes some basic and spatial analysis methods defined in the specification, noting that MySQL implements some but not all methods. The document references additional OpenGIS specifications and the JTS Topology Suite library.
Bayesian Hilbert Maps for Dynamic Continuous Occupancy Mapping
Hilbert mapping is an efficient technique for building continuous
occupancy maps from depth sensors such as LiDAR in static environments.
However, to make the map adaptable to dynamic environments, its parameters
need to be learned automatically. In this paper, we take a variational Bayesian
approach to this problem, thus eliminating the regularization term typically ad-
justed heuristically. We extend the proposed model to learn long-term occupancy
maps in dynamic environments in a sequential fashion, demonstrating the power
of kernel methods to capture abstract nonlinear patterns and Bayesian learning
to construct sophisticated models. Experiments conducted in environments
with moving vehicles show that the proposed approach has a significant speed
improvement over the state-of-the-art techniques and maintain a similar or
better accuracy. We also discuss the robustness against occlusions and various
theoretical and empirical aspects of building long-term dynamic occupancy maps.
3D Analyst - Lake Lorelindu by GRASS
This document describes using the open source GIS software GRASS to calculate the volume of Lore Lindu Lake in Central Sulawesi, Indonesia. It details the steps taken, which include importing polygon and depth point data, creating a bathymetry map using inverse distance weighted interpolation, generating contour and slope maps, viewing the results in 3D, and calculating the lake volume as 143449194.374 cubic meters using the r.volume command. The document concludes that GRASS provides an accessible and flexible way to perform this hydrological analysis and 3D volume calculation.
FOSS4G in Europe; Italy and the Politecnico de Milano
Maria Antonia Brovelli, Carolina Arias Muñoz, Marco Minghini, Giorgio Zamboni.
https://drive.google.com/file/d/0B3xWOhmJOx-_am5Ld3c4dnFPUUE/view
https://www.youtube.com/watch?v=dQ-EdwoPMVQ&feature=youtu.be
e-SOTER Regional pilot platform as EU contribution to a Global Soil Observing...
The document discusses testing the e-SOTER approach for soil mapping in Morocco. The e-SOTER method aims to standardize soil data collection and mapping across countries. For Morocco, the project involved characterizing landforms and parent materials from remote sensing data, correlating local soil classifications to international standards, and mapping soils at large and medium scales. Field validation found 56% accuracy for medium-scale mapping. While e-SOTER provides a framework, it has some limitations for processes like decarbonation in semi-arid areas. Overall, the project helped build soil mapping capacity in Morocco and established a database to inform projects on climate change, erosion, and land use.
Geographic Information Systems (April – 2017) [Question Paper | CBSGS: 75:25 ...
Geographic Information Systems (April – 2017) [Question Paper | CBSGS: 75:25 ...Mumbai B.Sc.IT Study
Geographic Information Systems (April – 2017) [Question Paper | CBSGS: 75:25 Pattern]
april - 2017, april - 2016, april - 2015, april - 2014, april - 2013, october - 2017, october - 2016, october - 2015, october - 2014, may - 2016, may - 2017, december - 2017, 75:25 pattern, 60:40 pattern, revised course, old course, mumbai bscit study, mumbai university, bscit semester vi, bscit question paper, old question paper, previous year question paper, semester vi question paper, question paper, CBSGS, IDOL, kamal t, internet technology, digital signals and systems, data warehousing, ipr and cyber laws, project management, geographic information systemGeneral Introduction to ROC Curves
ROC curves are used to evaluate machine learning algorithms and visualize the tradeoff between true positives and false positives. An ROC curve plots the true positive rate against the false positive rate for different discrimination thresholds. The area under the ROC curve (AUC) provides a single measure of performance, with higher values indicating better classification. While ROC curves are commonly used, precision-recall curves may provide a better evaluation for some applications by focusing on precision and recall rather than false positives.
Landslide
This document discusses landslides, including their causes, types, effects, indicators, prevention, and safety measures. It defines landslides as the downward movement of soil, rock, and vegetation under gravity. Key points include that landslides occur when resisting forces are less than driving forces, and can be triggered by heavy rainfall, earthquakes, erosion, deforestation, and human activities like excavation. The document outlines common landslide types and describes their impacts, such as damage to infrastructure, loss of life, and secondary hazards like flooding. It provides guidance on landslide hazard mapping, mitigation strategies, and safety precautions during landslide events.
Landslide ppt
it is my presentation on a natural disaster LANDSLIDE.
If u want to download it email me abhimanyu24@in.com
GIS-3D Analysis of Susceptibility Landslide Disaster in Upstream Area of Jene...
The assessment of landslide hazard and risk has become a topic of major interest for both geoscientists and engineering professionals as well as for local communities and administrations in many parts of the world. Recently, Geographic Information Systems (GIS), with their excellent spatial data processing capacity, have attracted great attention in natural disaster assessment. In this paper, an assessment of landslide hazard at Upper Area of Jeneberang Watershed has been studied using GIS technology. By simulating the potential landslide according the minimum safety factor value using GIS, it can be expected that great contribution as a basic decision making for many prevention works before future landslide occurs at upstream area of Jeneberang River Watershead, South Sulawesi, Indonesia
More Related Content
What's hot
GIS fundamentals - raster
This document discusses raster data in GIS. Raster data represents geographic information as a grid of cells or pixels organized into a matrix of rows and columns. Each cell contains a value representing information such as elevation, vegetation index, or land use class. Raster data can represent data as integers, floats, or other data types and comes in various resolutions, with higher resolution providing more detail. Rasters can be single band (one value per cell) or multiband (multiple values per cell representing different wavelengths). Examples of raster data sources include remote sensing imagery, digital elevation models, and land cover maps.
Understanding Coordinate Systems and Projections for ArcGIS
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.
POSTER_BUSTOS
The Sky view factor (SVF) represents the fraction of visible sky from a location and is used to estimate the urban heat island effect, energy balance, and thermal comfort. This document describes an online GIS tool that calculates SVF values based on building footprints, heights, and observer locations. The tool divides the hemisphere into slices, calculates elevation angles and distances to buildings to determine the fraction of sky obstructed at each observer point. Calculated SVF values are uploaded to ArcGIS Online to share maps of SVF distributions for urban planning and analysis of different design proposals.
Remotesensingandgisapplications
This document contains exam questions for a Remote Sensing and GIS Applications course. It includes 8 questions related to topics like remote sensing systems, GIS components and data structures, photogrammetry, natural disasters, and watershed drainage patterns. Students are instructed to answer 5 of the 8 questions, which vary in length from short answer to longer explanations and include diagrams/flowcharts. Key remote sensing and GIS concepts covered include raster vs vector data, active vs passive systems, interpolation methods, and using the technologies for applications like flood mapping and groundwater analysis.
Unit 3: figures
This document contains 14 figures related to glacial dynamics in Greenland. The figures show:
1) A map of Greenland with four study sites circled
2) Average air temperatures over Greenland from 2001-2010, showing 2010 was anomalously warm
3) Snowmelt data for Greenland calculated from satellite imagery
4) Maps of ice velocity for several Greenland glaciers from 2000-2001 and 2008-2009
5) A surface elevation change map of Greenland from satellite altimetry data
6) Time series graphs of ice elevation change at four study sites from satellite and airborne altimetry
7) A time series graph of ice mass changes in Greenland from 2002-2012 based on
07 a70110 remotesensingandgisapplications
This document contains exam questions for a Remote Sensing and GIS Applications course. It includes questions about rainfall-runoff relationships and models, scanner systems for remote sensing, key aspects of making effective maps from geospatial data, GIS workflow processes and cognitive models, disadvantages of remotely sensed data and physics concepts related to electromagnetic radiation, and questions about photogrammetry applications, raster data models, and comparing aerial photographs to topographic maps.
Map design in GIS
This document provides an overview of map design using GIS software. It discusses important elements to include in maps such as titles, legends, scale bars, and north arrows. It also covers choosing appropriate symbology for different map features, file formats, and resolutions for different map outputs. The document is intended to teach learners how to design effective maps using GIS software.
Geographic Information Systems (April – 2016) [Question Paper | CBSGS: 75:25 ...
Geographic Information Systems (April – 2016) [Question Paper | CBSGS: 75:25 ...Mumbai B.Sc.IT Study
Geographic Information Systems (April – 2016) [Question Paper | CBSGS: 75:25 Pattern]
april - 2017, april - 2016, april - 2015, april - 2014, april - 2013, october - 2017, october - 2016, october - 2015, october - 2014, may - 2016, may - 2017, december - 2017, 75:25 pattern, 60:40 pattern, revised course, old course, mumbai bscit study, mumbai university, bscit semester vi, bscit question paper, old question paper, previous year question paper, semester vi question paper, question paper, CBSGS, IDOL, kamal t, internet technology, digital signals and systems, data warehousing, ipr and cyber laws, project management, geographic information systemOSM Buildings - Buildings in space, sun in time
The document discusses calculating the position of the sun and projecting shadows from buildings onto maps using OpenStreetMap data. It provides code to calculate the sun's position based on date, latitude and longitude, as well as code to project a shadow of a standard length and direction from that sun position. The integration of these calculations allows rendering building shadows on web maps. Optimizations are discussed such as using the same shadow vector for all points and avoiding shadows casting on other objects.
Mst 1 question paper(bt401) cse
This document contains a mid-semester examination for the subject of Engineering Mathematics - III. The exam contains 4 questions worth a total of 28 marks. Question 1 has two parts that involve finding real roots of equations using the Regula Falsi and Newton-Raphson methods. Question 2 has two parts involving Newton's interpolation formula and Newton's divided difference formula. Question 3 has two parts, one requiring finding a cubic polynomial and the other evaluating a definite integral using different numerical methods. Question 4 has two parts involving solving equations using Crout's method and Gauss-Jacobi method.
3D Watershed Celebes
This document outlines the steps to derive watersheds in Central Celebes, Indonesia from SRTM data using 3D modeling software and ArcGIS tools:
1) Load and preprocess SRTM data to create a DEM raster, including cropping, filling blanks, converting projections, and saving as a GeoTIFF.
2) Perform terrain analysis in ArcGIS to calculate flow direction, flow accumulation, stream definition, stream segmentation, and catchment grid delineation using the ArcHydro tools.
3) View the resulting watersheds and hydrological networks in 3D in ArcScene by setting the appropriate layer properties and vertical exaggeration.
Floodplain Modeling with LiDAR-Derived Terrain
The document discusses the process of creating a terrain model and delineating floodplains from LiDAR data using ArcGIS and HEC-GeoRAS/HEC-RAS software. Key steps include building a terrain from LiDAR point clouds, breaklines and other feature classes, converting the terrain to a raster, using HEC-GeoRAS to generate cross-section geometry from the raster for hydraulic modeling in HEC-RAS, and mapping floodplains back in GIS from HEC-RAS results. Issues like missing LiDAR data or incorrect elevations may require additional field surveying.
MySQL Spatial Extensions - Boston MySQL Meetup April 2005
This document summarizes Andrew Collins' April 4th, 2005 presentation on MySQL Spatial Extensions. It outlines the OpenGIS Simple Features Specification geometry class hierarchy and spatial data model. It also describes some basic and spatial analysis methods defined in the specification, noting that MySQL implements some but not all methods. The document references additional OpenGIS specifications and the JTS Topology Suite library.
Bayesian Hilbert Maps for Dynamic Continuous Occupancy Mapping
Hilbert mapping is an efficient technique for building continuous
occupancy maps from depth sensors such as LiDAR in static environments.
However, to make the map adaptable to dynamic environments, its parameters
need to be learned automatically. In this paper, we take a variational Bayesian
approach to this problem, thus eliminating the regularization term typically ad-
justed heuristically. We extend the proposed model to learn long-term occupancy
maps in dynamic environments in a sequential fashion, demonstrating the power
of kernel methods to capture abstract nonlinear patterns and Bayesian learning
to construct sophisticated models. Experiments conducted in environments
with moving vehicles show that the proposed approach has a significant speed
improvement over the state-of-the-art techniques and maintain a similar or
better accuracy. We also discuss the robustness against occlusions and various
theoretical and empirical aspects of building long-term dynamic occupancy maps.
3D Analyst - Lake Lorelindu by GRASS
This document describes using the open source GIS software GRASS to calculate the volume of Lore Lindu Lake in Central Sulawesi, Indonesia. It details the steps taken, which include importing polygon and depth point data, creating a bathymetry map using inverse distance weighted interpolation, generating contour and slope maps, viewing the results in 3D, and calculating the lake volume as 143449194.374 cubic meters using the r.volume command. The document concludes that GRASS provides an accessible and flexible way to perform this hydrological analysis and 3D volume calculation.
FOSS4G in Europe; Italy and the Politecnico de Milano
Maria Antonia Brovelli, Carolina Arias Muñoz, Marco Minghini, Giorgio Zamboni.
https://drive.google.com/file/d/0B3xWOhmJOx-_am5Ld3c4dnFPUUE/view
https://www.youtube.com/watch?v=dQ-EdwoPMVQ&feature=youtu.be
e-SOTER Regional pilot platform as EU contribution to a Global Soil Observing...
The document discusses testing the e-SOTER approach for soil mapping in Morocco. The e-SOTER method aims to standardize soil data collection and mapping across countries. For Morocco, the project involved characterizing landforms and parent materials from remote sensing data, correlating local soil classifications to international standards, and mapping soils at large and medium scales. Field validation found 56% accuracy for medium-scale mapping. While e-SOTER provides a framework, it has some limitations for processes like decarbonation in semi-arid areas. Overall, the project helped build soil mapping capacity in Morocco and established a database to inform projects on climate change, erosion, and land use.
Geographic Information Systems (April – 2017) [Question Paper | CBSGS: 75:25 ...
Geographic Information Systems (April – 2017) [Question Paper | CBSGS: 75:25 ...Mumbai B.Sc.IT Study
Geographic Information Systems (April – 2017) [Question Paper | CBSGS: 75:25 Pattern]
april - 2017, april - 2016, april - 2015, april - 2014, april - 2013, october - 2017, october - 2016, october - 2015, october - 2014, may - 2016, may - 2017, december - 2017, 75:25 pattern, 60:40 pattern, revised course, old course, mumbai bscit study, mumbai university, bscit semester vi, bscit question paper, old question paper, previous year question paper, semester vi question paper, question paper, CBSGS, IDOL, kamal t, internet technology, digital signals and systems, data warehousing, ipr and cyber laws, project management, geographic information systemWhat's hot (18)
Understanding Coordinate Systems and Projections for ArcGIS
Understanding Coordinate Systems and Projections for ArcGIS
Geographic Information Systems (April – 2016) [Question Paper | CBSGS: 75:25 ...
Geographic Information Systems (April – 2016) [Question Paper | CBSGS: 75:25 ...
MySQL Spatial Extensions - Boston MySQL Meetup April 2005
MySQL Spatial Extensions - Boston MySQL Meetup April 2005
Bayesian Hilbert Maps for Dynamic Continuous Occupancy Mapping
Bayesian Hilbert Maps for Dynamic Continuous Occupancy Mapping
FOSS4G in Europe; Italy and the Politecnico de Milano
FOSS4G in Europe; Italy and the Politecnico de Milano
e-SOTER Regional pilot platform as EU contribution to a Global Soil Observing...
e-SOTER Regional pilot platform as EU contribution to a Global Soil Observing...
Geographic Information Systems (April – 2017) [Question Paper | CBSGS: 75:25 ...
Geographic Information Systems (April – 2017) [Question Paper | CBSGS: 75:25 ...
Viewers also liked
General Introduction to ROC Curves
ROC curves are used to evaluate machine learning algorithms and visualize the tradeoff between true positives and false positives. An ROC curve plots the true positive rate against the false positive rate for different discrimination thresholds. The area under the ROC curve (AUC) provides a single measure of performance, with higher values indicating better classification. While ROC curves are commonly used, precision-recall curves may provide a better evaluation for some applications by focusing on precision and recall rather than false positives.
Landslide
This document discusses landslides, including their causes, types, effects, indicators, prevention, and safety measures. It defines landslides as the downward movement of soil, rock, and vegetation under gravity. Key points include that landslides occur when resisting forces are less than driving forces, and can be triggered by heavy rainfall, earthquakes, erosion, deforestation, and human activities like excavation. The document outlines common landslide types and describes their impacts, such as damage to infrastructure, loss of life, and secondary hazards like flooding. It provides guidance on landslide hazard mapping, mitigation strategies, and safety precautions during landslide events.
Landslide ppt
it is my presentation on a natural disaster LANDSLIDE.
If u want to download it email me abhimanyu24@in.com
GIS-3D Analysis of Susceptibility Landslide Disaster in Upstream Area of Jene...
The assessment of landslide hazard and risk has become a topic of major interest for both geoscientists and engineering professionals as well as for local communities and administrations in many parts of the world. Recently, Geographic Information Systems (GIS), with their excellent spatial data processing capacity, have attracted great attention in natural disaster assessment. In this paper, an assessment of landslide hazard at Upper Area of Jeneberang Watershed has been studied using GIS technology. By simulating the potential landslide according the minimum safety factor value using GIS, it can be expected that great contribution as a basic decision making for many prevention works before future landslide occurs at upstream area of Jeneberang River Watershead, South Sulawesi, Indonesia
Tyresoil Retaining Wall (Adopting a low cost Landslide Mitigation Method)
A low cost landslide method for mitigating landslide risk, in an urban community. Initiative operationalized through a Framework Agreement between the National Disaster Office of Jamaica the General Counsel of Martinique.
Marjanović, M: Advanced Landslide Assessment of the Halenkovice Experimental ...
This presentation summarizes advanced landslide assessment methods applied at the Halenkovice experimental site in the Czech Republic. A variety of data collection and modeling methods were used, including field surveys, remote sensing, statistical analyses, and machine learning techniques like support vector machines. The results show improved accuracy over earlier regression models, though further refinements are still needed, like increasing the number of folds in model optimization and exploring multi-class scenarios. Overall, the study demonstrates the promise of comprehensive, multi-method landslide assessments for informing land use planning and hazard management.
Viewers also liked (6)
GIS-3D Analysis of Susceptibility Landslide Disaster in Upstream Area of Jene...
GIS-3D Analysis of Susceptibility Landslide Disaster in Upstream Area of Jene...
Tyresoil Retaining Wall (Adopting a low cost Landslide Mitigation Method)
Tyresoil Retaining Wall (Adopting a low cost Landslide Mitigation Method)
Marjanović, M: Advanced Landslide Assessment of the Halenkovice Experimental ...
Marjanović, M: Advanced Landslide Assessment of the Halenkovice Experimental ...
Similar to Landslide_Mapping_Sri lanka
m tech syllabus
This document provides information on the course structure and syllabus for an M.Tech in Geomatics program offered by the Survey Training Institute in collaboration with Jawaharlal Nehru Technological University.
The program is spread over 4 semesters. Each semester is approximately 20-21 weeks with classes typically 4 sessions per day of around 100 minutes each. There are normally 15 theory and 4 laboratory sessions per week.
The syllabus covers subjects in the areas of surveying, geodesy, photogrammetry, remote sensing, GIS, and cartography. Some example subjects listed are topographical surveying and mapping, introduction to geodesy, elements of photogrammetry, and remote sensing
Paregiani
The document discusses an automated method for classifying earth surfaces to assess landslide susceptibility using topographic data. It examines different geomorphometric classification approaches and parameters to distinguish landscape types related to landslides. The study tests supervised and unsupervised classification methods, compares results, and develops an integrated method using slope gradient, convexity and texture that identifies terrain features correlated with past landslide events. The automated integrated classification approach provides a useful tool for landslide susceptibility analysis at a territorial scale.
Advances in Agricultural remote sensings
This document summarizes a 3-part training program on crop mapping using synthetic aperture radar (SAR) and optical remote sensing. The training will cover crop classification using time series of polarimetric SAR data, monitoring crop growth through SAR-derived crop structural parameters, and classifying crop types using time series optical and radar data. Attendees will learn how to analyze satellite image time series from sensors like Sentinel-1 and Sentinel-2 for applications like crop monitoring. The training objectives are to understand polarimetric SAR for crop assessment and using multitemporal SAR and optical data for crop monitoring and classification.
Data Processing Using IRS Satellite Imagery for Disaster Monitoring (Case Stu...
This content shows IRS specification (Indian satellite), color composition, NDVI calculation, extracting damaged areas and comparison of Landsat-8 and IRS for the case study of earthquake in Indonesia.
Slope Modeling & Terrain Analysis (EPAN09)
The document summarizes a project to create an accurate slope model for Jefferson County, West Virginia using Light Detection and Ranging (LiDAR) data. Field measurements of slope were taken at 34 locations and compared to slope models derived from 10-meter, 3-meter, and 1-meter digital elevation models. The 1-meter LiDAR data was found to most accurately represent the terrain with a higher R2 value and finer detail. The created slope model using this data could potentially be used for planning purposes when combined with other data layers.
Geographic Information System unit 1
This document outlines the syllabus for a course on Geographic Information Systems (GIS). It is divided into 5 units that cover fundamentals of GIS, spatial data models, data input and topology, data analysis, and applications of GIS. The objectives of the course are to introduce students to the basic concepts of GIS and provide an understanding of spatial data structures, management processes, and analysis tools.
Fundamentals of GIS
This document outlines the syllabus for a course on Geographic Information Systems (GIS). The course is divided into 5 units that cover fundamentals of GIS, spatial data models, data input and topology, data analysis, and applications of GIS. The objectives are to introduce GIS fundamentals and processes of data management, analysis, and output. Students will learn about spatial data structures, data quality standards, and tools for data input, analysis, and management. The course aims to provide knowledge of GIS concepts and techniques.
GIS_FDP_Final.pdf
This document provides an overview of geospatial technology and geographic information systems (GIS). It discusses how GIS integrates data from GPS and remote sensing to store, analyze and manage spatial data referenced to locations on Earth. The key aspects covered include GIS data models using vector and raster formats, representing terrain as digital terrain models (DTMs), performing analysis like overlay operations and neighborhood functions, and calculating slopes and aspects from elevation data. GIS is presented as a versatile system for solving real-world problems by linking thematic data layers based on their geographic coordinates.
Application of Modern Geographical Tools & Techniques in Planning and Develo...
1. The document discusses the application of modern geographical tools and techniques such as GIS, remote sensing, and geostatistics in planning and development projects to ensure they are economically feasible, socially acceptable, and environmentally sustainable.
2. Key aspects discussed include creating robust spatial and non-spatial databases, classifying and regionalizing areas using composite indices to identify problem areas, and applying tools of geoinformatics like GPS, remote sensing, and GIS for data acquisition, analysis, and geovisualization to extract geographical information.
3. Modern geographical techniques are crucial for resource appraisal, management, and development by identifying issues, deficit areas, and informing the strategies and inputs of planners and managers.
CL#21-0488.pdf
1) The document describes a new methodology for identifying landslides using synthetic aperture radar (SAR) data on the Google Earth Engine platform.
2) It applies the methodology to map landslides triggered by heavy rainfall in Hiroshima, Japan in 2018, achieving good detection results by combining pre- and post-event SAR images and a digital elevation model.
3) The study finds that using more SAR images and data from multiple satellite flyovers improves landslide identification accuracy, and that rapid landslide mapping is possible within a week of an event.
SEG_2022_Presentation_16633576222324.pdf
The document discusses the importance of creating coherent geologic maps for mineral exploration through field mapping and the use of geographic information systems (GIS). Key points include:
- Professional quality geologic maps produced by field mapping are important tools that contain information used to make exploration decisions.
- GIS allows for integration of field data, geochemical data, geophysical surveys, and drill holes to perform spatial analysis and generate derivative maps useful for exploration.
- Underlying unseen data that contributes to coherent digital geologic maps includes lithology, structures, mineralization, geochemistry, and geophysics.
Remote Sensing Data Acquisition,Scanning/Imaging systems
full of concepts about RS data acquisition scanning and imaging systems. Best for students of remote sensing. in this presentation we briefly explained the concept of scanning in remote sensing.
Landuse Landcover mapping and Comparative analysis of deM from TerraSAR-X and...
LULC map using SAR GRD data and Comparative analysis of DEM prepared using TerraSAR-X and Sentinel-1A
1.pptx
Introduction to various GIS software, google earth. Intro types, types of maps, map projections and hands on to Q GIS software. Introduction to latitude longitude system, shape file generation, geo referencing and digitization.
GIS Introduction.ppt
This document provides an introduction to Geographic Information Systems (GIS) and geographic data sources. It defines what GIS is, explains why GIS is unique in its ability to handle spatial data and show connections between spatially proximate activities. It describes how GIS works using the layer approach to integrate spatial and attribute data. The document outlines different types of spatial data like raster and vector formats. It discusses various GIS functions such as measurement, analysis of single and multiple objects, and creating new objects through operations like overlay and buffering. Finally, it provides examples of sources of spatial data, attributes, and an exercise for students to find appropriate online geographic datasets for research topics.
Surface Analysis in GIS
This document help you to prepare Triangulation Network (TIN), Hillshade Map, Slope map, interpolation and Digital Elevation Model (DEM) in a area and how to interpret them.
Introduction of GIS & Remote Sensing (RS)
- Geographic Information Systems (GIS) is a computer-based tool that allows users to create, analyze, and display spatial information. GIS integrates many types of data to provide insights.
- GIS is used widely by international organizations, private industry, and government for applications like transportation planning, environmental analysis, and disaster management. It stores geographic data in layers that can be linked by location.
- Remote sensing involves collecting information about an area from a distance, such as via satellite or aerial imagery. High resolution sensors are commonly used to create accurate base maps and infrastructure data. Remote sensing data is extracted and digitized in GIS to build geographic databases.
Review of Digital Soil Mapping steps
The document outlines the key steps for digital soil mapping (DSM) which includes 1) deciding on the mapping focus and study area, 2) identifying and collecting relevant soil and environmental data, and 3) organizing and preprocessing the data. It then discusses 4) choosing appropriate GIS, terrain modeling, and image processing tools to analyze the data and 5) systematically applying the tools while documenting the process. The final steps involve 6) assessing the accuracy of the soil maps produced and 7) reporting the results.
Geographic information system(GIS) and its applications in agriculture
This document presents a seminar on geographic information systems (GIS) given by Nalla Anthony Kiranmai. The seminar discusses the principles, components, functions, applications and advantages of GIS. It covers topics such as the linkage between remote sensing and GIS, vector vs raster data representation, spatial data analysis functions including overlays and buffers, and applications of GIS in fields like agriculture, land suitability analysis, and groundwater assessment. The seminar aims to provide an introduction to GIS concepts and demonstrate how GIS can be used as an integrated technology for spatial analysis and decision support.
Introduction_GIS.pptx
This document provides an introduction to geographic information systems (GIS) including definitions, common hardware, software, and data types used in GIS. It discusses the open source software QGIS compared to the commercial software ArcGIS and covers vector and raster data layers, layer attributes, styles, and visualization of spatial data in GIS. Common data sources introduced include topographic maps, nautical charts, satellite imagery, and aerial photography.
Similar to Landslide_Mapping_Sri lanka (20)
Data Processing Using IRS Satellite Imagery for Disaster Monitoring (Case Stu...
Data Processing Using IRS Satellite Imagery for Disaster Monitoring (Case Stu...
Application of Modern Geographical Tools & Techniques in Planning and Develo...
Application of Modern Geographical Tools & Techniques in Planning and Develo...
Remote Sensing Data Acquisition,Scanning/Imaging systems
Remote Sensing Data Acquisition,Scanning/Imaging systems
Landuse Landcover mapping and Comparative analysis of deM from TerraSAR-X and...
Landuse Landcover mapping and Comparative analysis of deM from TerraSAR-X and...
Geographic information system(GIS) and its applications in agriculture
Geographic information system(GIS) and its applications in agriculture
Landslide_Mapping_Sri lanka
- 1. LANDSLIDE SUCCEPTIBILITY MAP (Case of study SRILANKA) Presented by Rashid Javed Meenat Allah Saleem February 24, 2012
- 2. Bivariate statistical method 1. Landslide rupture 2. Relevant factors (parameters) for the prediction of landslide : - Lithology - Slope - Landuse - Aspect - Soiltype - Curvature Statistical Map
- 3. Statistical Analysis Map 3. Weight value for each factor : - Dens. clas : Landslide density within parameter class - Density map : Landslide density within entire map - N pixel (Si) : Number of pixels, which contain landslides per parameter class - N pixel (Ni): Total number of pixels in a parameter class
- 4. Statistical Analysis Map Six weight value maps will be calculated: 1. lithology weight map 2. Soil type weight map 3. Landuse weight map 4. Slope weight map 5. Aspect weight map 6. Curvature weight map Hazard succeptibility map
- 5. Data Available • Soil map • Contour lines(10m intervals) • Land use map • Landslide rupture map • Reference coordinate system for Srilanka: Central Meridian, False Northing Latitude of origin, Scale factor, false northings and false eastings are 200,000meters, • Used Software : ArcGIS 10
- 6. Work Flow 1.Created a file geodatabase(arcGIS 10) 2.Assigned the given coordinate system to our geodatabase, 3.Imported our features( all shapefiles) 4. Rasterisation of our feature Landslide rupture (define the extent of our raster by using mask) 5. Generated TIN from contour lines 6.TIN to Ratser(GRID): define cell size and mask
- 7. Continue….. 7.Reclassification : Aspect, slope and curvature 8. Rasterization : lithology, landuse and soil type features ( polygon to raster) 9. Zonal tables ( zonal statistics as table) 10.Join tables to corresponding classes 11. Calculate six weight value maps 12. Hazard susceptibility map(sum up all weight value maps) (Map algebra i.e. Raster Calculator)
- 8. 1.Creataion File Geodatabase • Assigned the given coordinate system and projection • Imported all our features
- 9. 2.Rasterization:LandSide Rupture Feature •Cell size : 20m • Assign the extent of our raster •by using given mask feature •Total number of pixel (2752)
- 10. 3.Generation Aspect Slope and Curvature 1. TIN from Contour lines (3D Analyst tools TIN management) 2. TIN to Raster(GRID) (3D Analyst tools from TIN TIN to Raster)
- 11. Continue…. Spatial analyst tools (Aspect, slope and curvature) Aspect Slope Curvature All these rasters do not have values ( no Attribute tables, floating rasters)
- 12. 4.Rasterization:Lithology Landuse and Soil Polygon Raster Soiltype : 4 classes Lithology : 3 classes Landuse : 21 classes
- 13. 5.Reclassification Spatial analyst tools Reclass Reclassify Aspect 5 classes are made
- 14. Continue….. Slope 5 classes Curvature 5 classes
- 16. Reclassification of LanduseRaster Landuse 4 classes
- 17. 6.Zonal Tables Spatial analyst tools Zonal Zonal statistics as table •We want to calculate the number of pixels of landslide that fall in each class of our raster slope, • Repeated the same process is done for 5 remaining Rasters
- 18. 7.Join Tables to Correspond Rasters • Join tables of each raster to its corresponding zonal statistic table, • Total number of pixels of that raster in each zonal statistic table, • Use “Field calculator”, added a new field of weight in our table
- 19. 8.Field Calculator Calculate the weight values by introducing the given formula in field calculator
- 20. 9.Calculate Six Weight Value Maps e.g. Aspect -ve values mean Low Risk Area +ve values mean High Risk Area
- 21. 10.Weight Maps Aspect weight map Slope weight map
- 22. Continue….. Curvature weight map Soiltype weight map
- 23. Continue…. Lithology weight map Landuse weight map
- 25. Thank you for your attention.
- 26. 26 QUESTIONS???