This work is an effort to share Geographical Information System: Georeferencing, digitization and map making steps through QGIS 2.0.1
Georeferencing
Digitization of Topographical sheet
Point
Line
Area
Bihar Map
District Headquarters
Railway of Bihar
District Boundaries
Thematic Maps (Literacy & Sex Ratio)
This presentation is about the raster and vector data in GIS which is important and costly as well, through the presentation we will learn about both type of data.
This presentation is about the raster and vector data in GIS which is important and costly as well, through the presentation we will learn about both type of data.
Digital Elevation Model (DEM) is the digital representation of the land surface elevation with respect to any reference datum. DEM is frequently used to refer to any digital representation of a topographic surface. DEM is the simplest form of digital representation of topography. GIS applications depend mainly on DEMs, today.
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.
When you georeference your raster data, you define its location using map coordinates and assign the coordinate system of the map frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with your other geographic data. The georeferencing tools on the Georeference tab allows you to georeference any raster dataset.
In general, there are four steps to georeference your data:
Add the raster dataset that you want to align with your projected data.
Use the Georeference tab to create control points, to connect your raster to known positions in the map
Review the control points and the errors
Save the georeferencing result, when you are satisfied with the alignment.
This is most benificial for the First year Engineering students.This presentation consists of videos and many applications of GIS. The processes and the other parts of GIS is also nicely explained.
Types of Platforms
1. Airbrone Platforms
2. Spacebrone Platforms
Platforms are Vital Role in remote sensing data acquisition
Necessary to correct the position the remote sensors that collect data from the objects of interest
Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data.
Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link.
Finally, the georeferenced raster file can be exported for further usage.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Digital Elevation Model (DEM) is the digital representation of the land surface elevation with respect to any reference datum. DEM is frequently used to refer to any digital representation of a topographic surface. DEM is the simplest form of digital representation of topography. GIS applications depend mainly on DEMs, today.
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.
When you georeference your raster data, you define its location using map coordinates and assign the coordinate system of the map frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with your other geographic data. The georeferencing tools on the Georeference tab allows you to georeference any raster dataset.
In general, there are four steps to georeference your data:
Add the raster dataset that you want to align with your projected data.
Use the Georeference tab to create control points, to connect your raster to known positions in the map
Review the control points and the errors
Save the georeferencing result, when you are satisfied with the alignment.
This is most benificial for the First year Engineering students.This presentation consists of videos and many applications of GIS. The processes and the other parts of GIS is also nicely explained.
Types of Platforms
1. Airbrone Platforms
2. Spacebrone Platforms
Platforms are Vital Role in remote sensing data acquisition
Necessary to correct the position the remote sensors that collect data from the objects of interest
Raster data is commonly obtained by scanning maps or collecting aerial photographs and satellite images. Scanned map datasets don't normally contain spatial reference information (either embedded in the file or as a separate file). With aerial photography and satellite imagery, sometimes the location information delivered with them is inadequate, and the data does not align properly with other data one has. Thus, to use some raster datasets in conjunction with other spatial data, we need to align or georeference them to a map coordinate system. A map coordinate system is defined using a map projection (a method by which the curved surface of the earth is portrayed on a flat surface). Georeferencing a raster data defines its location using map coordinates and assigns the coordinate system of the data frame. Georeferencing raster data allows it to be viewed, queried, and analyzed with other geographic data.
Generally, we georeference raster data using existing spatial data (target data)—such as georeferenced rasters or a vector feature class—that resides in the desired map coordinate system. The process involves identifying a series of ground control points—known x,y coordinates—that link locations on the raster dataset with locations in the spatially referenced data (target data). Control points are locations that can be accurately identified on the raster dataset and in real-world coordinates. Many different types of features can be used as identifiable locations, such as road or stream intersections, the mouth of a stream, rock outcrops, the end of a jetty of land, the corner of an established field, street corners, or the intersection of two hedgerows. The control points are used to build a polynomial transformation that will shift the raster dataset from its existing location to the spatially correct location. The connection between one control point on the raster dataset (the from point) and the corresponding control point on the aligned target data (the to point) is a link.
Finally, the georeferenced raster file can be exported for further usage.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Terra formation control or how to move mountainsijcga
The new Uplift Model of terrain generation is generalized here and provides new possibilities for terra
formation control unlike previous fractal terrain generation methods. With the Uplift Model fine-grained
editing is possible allowing the designer to move mountains and small hills to more suitable locations
creating gaps or valleys or deep bays rather than only being able to accept the positions dictated by the
algorithm itself. Coupled with this is a compressed file storage format considerably smaller in size that the
traditional height field or height map storage requirements.
Introduction
GIS Stands for - Geographic Information
System
G + IS
(Geography) + (Information System)
Geography is the science that Studies the land
feature, inhabitants, and the phenomena of
Earth.
Information system – A way of manipulating the
information digitally (Using computer or digital
Device).
This presentation focuses on Creation of image to image georeferencing in Arcgis of a particular area
A geographic information system (GIS) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data.
Prepared as part of the IT for Business Intelligence course of MBA @VGSOM, IIT Kharagpur. The tutorial describes how to create an interactive map using the open source software QGIS.
Similar to Geographical Information System (GIS) Georeferencing and Digitization, Bihar Thematic Map making (20)
Migration Profile of Odisha with focus on BhubaneswarKamlesh Kumar
Migration is one the most important demographic component to determine the size, growth and structure of population of a particular region, besides fertility and mortality. For a large country like India, the study of movement of population in different parts of the country helps in understanding the dynamics of the society and societal change better. Bhubaneswar is one of the magnets for migrants in east India attributing to its exponential growth rates. This is an attempt to map the migration pattern in the city and the state.
Population Projection of Khordha District, ODISHA 2021-51Kamlesh Kumar
Work is based on Walter Isard's methods in a simplistic manner.
1. ARITHMATICAL INCREASE METHOD OF PROJECTION
2. GEOMETRIC INCREASE METHOD
3. INCREMENTAL INCREASE METHOD
DEMOGRAPHIC PROFILE OF CONTINENTAL ODISHAKamlesh Kumar
Although the state is endowed with vast natural resources it has remained on the bottom of the developmental chart of the nation. With such a reserve of natural resources and human resource potential, it is like a hibernating beast which must awake for good. Stealing the limelight of the most favourable smart city, the capital is growing like never before along with a few more cities. Yet the state remains mostly rural and lagging in most aspects except for the coastal regions. My analysis is that the state has not been given its due attention in planning which is the reason for its present backwardness.
‘Fashion’ is a notoriously difficult term to pin down, and it is extremely doubtful whether it is possible to come up with necessary and sufficient conditions for something justifiably to be called ‘fashionable’. Generally speaking, we can distinguish between two main categories in our notion of fashion: one that fashion refers to clothing or that fashion is a general mechanism, logic or ideology that, among other things, applies to the area of clothing.
Adam Smith , who was among the first philosophers to give fashion a central role in his anthropology, claims that fashion applies first and foremost to areas in which taste is
a central concept. This applies in particular to clothes and furniture, but also to music, poetry and architecture. Immanuel Kant provides a description of fashion that focuses on general changes in human lifestyles: ‘All fashions are, by their very concept, mutable ways of living.’
However, trends die quickly and with that comes waste. Clothing produced by fast fashion brands are oftentimes made from cheap materials, like polyester and acrylic, and not built to last: The average American throws away 80 pounds of clothing every year. We’ve been conditioned to believe that buying a garment and wearing it once is justifiable. It’s not. Due to the growing demand in the fast fashion industry, we see a vast overproduction of clothing; for example, the Copenhagen Fashion Summit reports that fashion is responsible for 92 million tons of solid waste dumped in landfills each year. This cultural shift on how we consume clothing is leaving a huge mark on the planet. Fashion has become much more than representation and being covered.
COMMUNAL HARMONY: PUNJABI & TIBETANS IN DELHIKamlesh Kumar
LANDSCAPE AS TEXT
Delhi, the majestic, cosmopolitan, sprawling capital of the nation viewed as one of the global nodes bustling with life in haste. It has maintained its identity as a pluralistic amalgamation with myriads of ethno-religious groups and minority communities. Such is the very famous, our own ‘little Tibet’- Majnu Ka Tila situated at a stone’s throw from the Delhi University North Campus. Officially known as Aruna Nagar Colony is the universal gathering place
for Tibetans living around Delhi and a transit point for the people of the trans-Himalayan range and conversely a gateway to Tibet for the Indians and foreign tourists alike as the capital city enjoys a status of a flourishing educational and political hub.
Tall buildings on either side make the narrow alley so dark it’s as if the sun never makes it here. Shops on either side sell only exotic Tibetan jewellery, Buddhist artefacts and crockery. In this labyrinth of a colony, the stalls are full of copies of branded shoes and clothes, reflecting the latest in fashion trends across Asia. Many of the tiny outlets sell Buddhist curios and Tibetan literature. Ahead, the alley opens into a bright courtyard facing the monastery. Old ladies sit in the sun, making fresh momos and laphing, pancakes rolled with chilli paste. Besides MKT is a Foodie's paradise, the eateries here are not only popular for its momos, but one can also enjoy authentic Tibetan, Chinese and Korean delicacies along with the yummiest of the English pastries.
Majnu Ka Tila not only is limited to Tibetan community but constituted by the Punjabi community as well which has a historical context.
The area provides a microcosm of diversified India where there is invisible transition and diffusion of identity, culture of distinct communities and Indianisation of Tibetan lifestyle.
For instance, many Tibetans who cannot afford the rising rents of the Tibetan enclave (due to hotels and tourist activities) are forced to live in the Punjabi Basti where renting an apartment is cheaper comparatively. Living in Punjabi zone is seen influencing a cultural and identity loss. To diffuse with the Punjabi population is perceived as a risk “of identity loss”, and forgetting your Tibetan culture. These frontiers are mental, social and religious. Nonetheless, the ethnic groups interacting and sharing a space is a matter of pride as community harmony.
An overlay operation is much more than a simple merging of linework; all the attributes of the features taking part in the overlay are carried through. In general, there are two methods for performing overlay analysis—feature overlay (overlaying points, lines, or polygons) and raster overlay. Some types of overlay analysis lend themselves to one or the other of these methods. Overlay analysis to find locations meeting certain criteria is often best done using raster overlay (although you can do it with feature data). Of course, this also depends on whether your data is already stored as features or raster. It may be worthwhile to convert the data from one format to the other to perform the analysis.
Weighted Overlay
Overlays several raster files using a common measurement scale and weights each according to its importance.
The weighted overlay table allows the calculation of a multiple criteria analysis between several raster files.
Raster- The raster of the criteria being weighted.
Influence- The influence of the raster compared to the other criteria as a percentage of 100.
Field- The field of the criteria raster to use for weighting.
Remap- The scaled weights for the criterion.
In addition to numerical values for the scaled weights in Remap, the following options are available:
Restricted- Assigns the restricted value (the minimum value of the evaluation scale set, minus one) to cells in the output, regardless of whether other input raster files have a different scale value set for that cell.
No data - Assigns No Data to cells in the output, regardless of whether other input raster files have a different scale value set for that cell.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
In the context of remote sensing, change detection refers to the process of identifying differences in the state of land features by observing them at different times. This process can be accomplished either manually (i.e., by hand) or with the aid of remote sensing software. Manual interpretation of change from satellite images or aerial photos involves an observer or analyst defining areas of interest and comparing them between images from two dates. This may be accomplished either on-screen (such as in a GIS) or on paper. When analyzing aerial photographs, a stereoscope which allows for two spatially-overlapping photos to be displayed in 3D, can aid photo interpretation. Manual image interpretation works well when assessing change between discrete classes (forest openings, land use and land cover maps) or when changes are large (e.g., heavy mechanized maneuver damage, engineering training impacts). Manual image interpretation is also an option when trying to determine change using images or photos from different sources (comparing historic aerial photographs to current satellite imagery).
Automated methods of remote sensing change detection usually are of two forms: post-classification change detection and image differencing using band ratios. In post-classification change detection, the images from each time period are classified using the same classification scheme into a number of discrete categories like land cover types. The two (or more) classifications are compared and the area that is classified the same or different is tallied. With image differencing, a band ratio such as NDVI is constructed from each input image, and the difference is taken between the band ratios of different times. In the case of differencing NDVI images, positive output values may indicate an increase in vegetation, negative values a decrease in vegetation, and values near zero no change. With either post-classification or image differencing change detection, it is necessary to specify a threshold below which differences between the two images is considered to be non-significant. The specification of thresholds is critical to the results of change detection analysis and usually must be found through an iterative process.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Accuracy assessment is an important part of any classification project. It compares the classified image to another data source that is considered to be accurate or ground truth data. Ground truth can be collected in the field; however, this is time consuming and expensive. Ground truth data can also be derived from interpreting high-resolution imagery, existing classified imagery, or GIS data layers.
The most common way to assess the accuracy of a classified map is to create a set of random points from the ground truth data and compare that to the classified data in a confusion matrix. Although this is a two-step process, you may need to compare the results of different classification methods or training sites, or you may not have ground truth data and are relying on the same imagery that you used to create the classification. To accommodate these other workflows, this process uses three geoprocessing tools: Create Accuracy Assessment Points, Update Accuracy Assessment Points, and Compute Confusion Matrix.
Thresholding
Thresholding is the process of identifying the pixels in a classified image that are the most likely to be classified incorrectly. These pixels are put into another class (usually class 0). These pixels are identified statistically, based upon the distance measures
that were used in the classification decision rule.
Accuracy Assessment : Error Matrix
Accuracy assessment is a general term for comparing the classification to geographical data that are assumed
to be true, in order to determine the accuracy of the classification process. Usually, the assumed-true data are derived from ground truth data. It is usually not practical to ground truth or otherwise test every pixel of a classified image. Therefore, a set of reference pixels is usually used. Reference pixels are points on the classified image for which actual data are (or will be) known. The reference pixels are randomly selected.
Overall accuracy: Overall accuracy is used to indicate the accuracy of whole classification (i.e. number of correctly classifier pixels divided by the total number of pixels in the error matrix)
User’s accuracy(commission error): User’s accuracy is regarded as the probability that a pixel classified on map actually represents that
class on the ground or reference data
Producer’s accuracy(omission error): Producer’s accuracy represents the probability of reference pixel being correctly classified
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
The objective of image classification is to classify each pixel into only one class (crisp or hard classification) or to associate the pixel with many classes (fuzzy or soft classification). The classification techniques may be categorized either on the basis of training process (supervised and unsupervised) or on the basis of theoretical model (parametric and non-parametric).
Unsupervised classification is where the groupings of pixels with common characteristics are based on the software analysis of an image without the user providing sample classes. The computer uses techniques to determine which pixels are related and groups them into classes. The user can specify which algorism the software will use and the desired number of output classes but otherwise does not aid in the classification process. However, the user must have knowledge of the area being classified when the groupings of pixels with common characteristics produced by the computer have to be related to actual features on the ground (such as waterbodies, developed areas, forests, etc.).
Supervised classification is based on the idea that a user can select sample pixels in an image that are representative of specific classes and then direct the image processing software to use these training sites as references for the classification of all other pixels in the image. Input classes are selected based on the knowledge of the user. The user also sets the bounds for how similar other pixels must be to group them together. These bounds are often set based on the spectral characteristics of the input classes (AOI), plus or minus a certain increment (often based on “brightness” or strength of reflection in specific spectral bands). The user also designates the number of classes that the image is classified into.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Interpolation is the process of using points with known values to estimate values at other unknown points. It can be used to predict unknown values for any geographic point data, such as elevation, rainfall, noise levels, atmospheric components and so on.
The Inverse Distance Weighting (IDW) assumes each input point to have a local influence that diminishes with distance. It assumes that closer things are more alike than those that are farther apart. It weights the points closer to the processing cell greater than those further away. A specified number of points, or all points within a specified radius can be used to determine the output value of each location. To predict a value for any unmeasured location, IDW will use the measured values surrounding the prediction location. Those measured values closest to the prediction location will have more influence on the predicted value than those farther away.
Spline estimates values using a mathematical function that minimizes overall surface curvature, resulting in a smooth surface that passes exactly through the input points. This method is best for gently varying surfaces, such as elevation, water table heights, or pollution concentrations. A Regularized method creates a smooth, gradually changing surface with values that may lie outside the sample data range.
Kriging is a geostatistical interpolation technique that considers both the distance and the degree of variation between known data points when estimating values in unknown areas. Kriging assumes that the distance or direction between sample points reflects a spatial correlation that can be used to explain variation in the surface. The Kriging tool fits a mathematical function to a specified number of points, or all points within a specified radius, to determine the output value for each location. Kriging is a multistep process; it includes exploratory statistical analysis of the data, variogram modeling, creating the surface, and (optionally) exploring a variance surface. Kriging is most appropriate when you know there is a spatially correlated distance or directional bias in the data. It is often used in soil science and geology.
Trend is a statistical method that finds the surface that fits the sample points using a least-square regression fit. It fits one polynomial equation to the entire surface. This results in a surface that minimizes surface variance in relation to the input values. The surface is constructed so that for every input point, the total of the differences between the actual values and the estimated values (i.e., the variance) will be as small as possible.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
With increasing use of remote sensing, the need for crispier, accurate and enhanced precision has deemed to the improvement in the spectral and spatial resolution of remotely sensed imagery. For most of the systems, panchromatic images typically have higher resolution, while multispectral images offer information in several spectral channels. Resolution merge (also called pan-sharpening) allows us to combine advantages of both kinds of images by merging them into one.
The resolution merge or pan sharpening is the technique used to obtain high resolution multi-spectral images. The color information is collected from the coarse resolution satellite data and the intensity from the high resolution satellite data.
The main constraint is to preserve the spectral information for aspects like land use. Saving theimage from distortion of the spectral characteristics is important in the merged dataset.
The most common techniques for spatial enhancement of low-resolution imagery combining high and low resolution data can be used are: Intensity-Hue-Saturation, Principal Component, Multiplicative and Brovey Transform.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Remote Sensing: Normalized Difference Vegetation Index (NDVI)Kamlesh Kumar
The Normalized Difference Vegetation Index (NDVI) is a numerical indicator that uses the visible and near-infrared (NIR) bands of the electromagnetic spectrum to analyze whether the target (image) being observed contains green vegetation or not. Healthy vegetation (chlorophyll) reflects more near-infrared (NIR) and green light compared to other wavelengths. But it absorbs more red and blue light. This is why our eyes see vegetation as the colour green. If we could see near-infrared, then it would be strong for vegetation too.
It is basically measured through the use of Intensity, Hue and saturation of an image and through pixels as well.
The density of vegetation (NDVI) at a certain point on the image is equal to the difference in the intensities of reflected light in the red and infrared range divided by the sum of these intensities.
푁퐷푉퐼=((푁퐼푅−푅퐸퐷))/((푁퐼푅+푅퐸퐷))
The result of this formula generates a value between -1 and +1. If you have low reflectance (low values) in the red band and high reflectance in the NIR, this will yield a high NDVI value. And vice versa.
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.
The advantage of digital imagery is that it allows us to manipulate the digital pixel values in the image. Even after the radiometric corrections image may still not be optimized for visual interpretation. An image 'enhancement' is basically anything that makes it easier or better to visually interpret. An enhancement is performed for a specific application as well. This enhancement may be inappropriate for another purpose, which would demand a different type of enhancement.
Filtering is used to enhance the appearance of an image. Spatial filters are designed to highlight or suppress specific features in an image based on their spatial frequency. ‘Rough’ textured areas of an image, where the changes in tone are abrupt, have high spatial frequencies, while ‘smooth’ areas with little variation have low spatial frequencies. A common filtering procedure involves moving a ‘matrix' of a few pixels in dimension (ie. 3x3, 5x5, etc.) over each pixel in the image, using mathematical calculation and replacing the central pixel with the new value.
A low-pass filter is designed to emphasize larger, homogeneous areas of similar tone and reduce the smaller detail in an image. Thus, low-pass filters generally serve to smooth the appearance of an image. In some cases, like 'low-pass filtering', the enhanced image can actually look worse than the original, but such an enhancement was likely performed to help the interpreter see low spatial frequency features among the usual high frequency clutter found in an image. High-pass filters do the opposite and serve to sharpen the appearance of fine detail in an image. Directional, or edge detection filters are designed to highlight linear features, such as roads or field boundaries. These filters can also be designed to enhance features which are oriented in specific directions.
THIS PRESENTATION IS TO HELP YOU PERFORM THE TASK STEP BY STEP.
Mountainous regions occupy one-fourth of the world’s terrestrial surface, most rich in diverse landscapes and hold on to the biodiversity and cultural diversity along with supporting 10% of humankind with their direct life support base. Most mountainous regions have been at the far periphery of mainstream societal concerns for a long time. Remote, relatively inaccessible, they were generally pictured as difficulty, unyielding and unprofitable environments. Very less have focused attention on mountainous people and cultures, primitive religion, marginal survival, unusual adaptation to very high altitude, fraternal polyandry to obliterate informed communication and more meaningful analysis in practical sense. Early research concentrated mainly on specialised studies with little cross disciplinary endeavour. During the last few decades there have been spasmodic accounts of the highland and lowland mainly induced by events of great economic or political significance and due to the degradation of highlands which are potential threats to subjacent lowland population centre. Recent developments, expanding highland research and awareness spread by institutions and governments have shone a new ray of light towards the bright future. However, increased awareness with political advocacy must be pursued further.
Water is hydrosphere is made up of all the water on Earth. This includes all of the rivers, lakes, streams, oceans, groundwater, polar ice caps, glaciers and moisture in the air (like rain and snow). The hydrosphere is found on the surface of Earth, but also extends down several miles below, as well as several miles up into the atmosphere. So, there is a need for study of water as a scarce resource.
WHAT IS HYDROLOGICAL CYCLE
SYSTEM APPROACH IN HYDROLOGY
HYDROLOGIC INPUT & OUTPUT
VARIATION IN HYDROLOGICAL CYCLE
COMPONENTS
EVAPORATION
EVAPOTRANSPIRATION
PRECIPITATION
INTERCEPTION
INFILTRATION
GROUND WATER
RUN-OFF
HUMAN IMPACT
EARTH SURFACE
CLIMATE CHANGE
ATMOSPHERIC POLLUTION
MULTI PURPOSE PROJECTS
WATER WITHDRAWAL
MANAGEMENT AND CONTROL
An assessment on the temperate ecosystem with the following sub headings:
Geological evolution: Location and Extent
Atmospheric changes
Hydrological Changes
Land Degradation
Biodiversity Loss
Challenges to Human Community
Geosystem Approach: El Nino Southern Oscillation EffectsKamlesh Kumar
Earth system as a whole is very complex and dynamic, for that matter we prepare models to represent the functioning linkages and processes for better understanding. However, the geo-systems can not be summed up in just one model. Hence, we use system analysis approach, if we see Earth as a giant system, there're many sub-systems for better comprehension representing only a particular component of the system.
Here, I've tried to cover the geo-system approach siting a globe affecting example of the El Nino Southern Oscillation (ENSO) phenomena.
This report is detailed study of the research conducted in Kirori Mal College. The basic objective of this report is to get a tough insight in the use of research techniques. Geography, being a field science, a geographical enquiry always need to been supplemented through well planned Research. Research is an essential component of geographic enquire. It is a basic procedure to understand the earth as a home of humankind. Disaster management is an inseparable part of the discipline especially which deals with the study of natural phenomena. This research focuses upon the FIRE safety plan of the institution. It is carried out through observation, sketching, measurement, interviews, etc. The Research facilitate the collection of local level information that is not available through secondary sources.
In this report, various methodologies have been employed such as my, measurement and interviewing, photographing, examining, the collection and gathering of information at different corners of the institution and later, tabulating and computing them is an important part of the field work.
Furthermore, the research report has been prepared in concise form alongside with maps and diagrams for giving visual impressions. Moreover, it contains all the details of the procedures followed, methods, tools and techniques employed.
Disaster Prevention & Preparedness: Earthquake in NepalKamlesh Kumar
This report is detailed study of the field survey conducted in Kathmandu and Sindhupalchowk in Nepal on the earthquake disaster. The basic objective of this report is to get a tough insight in the use of field techniques regarding disaster management. Geography deals with human interaction with nature. This phenomenon can be better understood through field studies. Geography, being a field science, a geographical enquiry always need to be supplemented through well planned field surveys. Field is an essential component of geographic enquire. It is a basic procedure to understand the earth as a home of humankind. It is carried out through observation, sketching, measurement, interviews, etc. Field work takes the children out of the class and enables them to better understand the subject by visiting the areas practically giving an insight into the social, cultural and economic lives of the people. This also adds up the advantage of visiting the grass root levels of the society and ameliorative comprehension of the GLOCAL lives. It also has instilled various research making techniques in the budding geographers and shaping their thinking perspectives. The field surveys facilitate the collection of local level information that is not available through secondary sources.
In this report, various methodologies have been employed such as mapping, digitization, measurement and interviewing (questionnaires designing), the collection and gathering of information at the local level by conducting primary surveys and later, tabulating and computing them is an important part of the field survey.
Furthermore, the field study report has been prepared in concise form alongside with maps and diagrams for giving visual impressions. Moreover, it contains all the details of the procedures followed, methods, tools and techniques employed and the modern technology of navigation, satellite connections, GIS software have been very helpful in the pre-field drills.
The report has the following headings and sub-headings:
Introduction
Study area
Transit: Table & Maps
Disaster scenario of Nepal
Earthquake: Timeline
Causes
Impact
Who is helping Nepal?
Reconstruction and Rehabilitation Status
Objectives & Methodology
Literature review
Data representation and Analysis
Findings and Suggestions
Conclusions
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
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Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
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It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
2. CONTENTS
Exercise 1- Scanned Image of the Topographical sheet
Exercise 2- Georeferenced Image of the Topographical sheet
Digitization of Topographical sheet
Exercise 3 - Point
Exercise 4 - Line
Exercise 5 - Area
Bihar Map
Exercise 6- Scanned Image of the Map
Exercise 7- Georeferenced image of the Map
Digitization of Map
Exercise 8 - District Headquarters
Exercise 9 - Railway of Bihar
Exercise 10 - District Boundaries
Thematic Maps
Exercise 11 - Literacy
Exercise 12 - Sex Ratio
Annexure
4. EXERCISE- 2
GEOREFERENCING
Introduction
Georeferencing is a process of establishing a mathematical relationship between the image coordinate
system and the real world spatial coordinate system. This mathematical relationship can be assigned by any
one of the transformation settings, viz. Polynomial order 1, 2 or 3, Linear, Projective and Thin Plate Spline
etc. Polynomial order 2 is the most widely used transformation in Georeferencing. Recently Thin Plate
Spline gaining popularity due its ability of incorporating the local deformations in the data, this is very
useful when we are dealing with low resolution data. However, in this practical we are using traditional
polynomial order 2 transformation to perform georeferencing/rectification of the Toposheet.
In this exercise, we will use a topographic Map of Uttar Pradesh. This map is in the Universal Transverse
Mercator(UTM) projection based on WGS 84 Datum.
1. First, we open Quantum GIS (QGIS) via the Start menu. (Start → All Programs → QGIS Dufour →
QGIS Desktop 2.0.1)
2. We then open QGIS Georeferencer via the menu bar. (Raster → Georeferencer → Georeferencer).
3. The Georeferencer is in the form of a window with two parts to it. The upper part is called as 'Main
Work Space' dedicated to display the Raster Map to be georeferenced and it allows the user to input the
geographic or projected coordinates of control points. The lower part, titled 'GCP table', is where the
Ground Control Point data and residuals will be displayed.
4. Add the toposheet to the Georeferencer by clicking on the 'Open Raster' button or from the File menu
(File → Open Raster).
5. You will then be presented with a popup window, navigate to the data folder in which the 'toposheet.tif'
file is kept. Click on the drop-down menu right to the 'File name' and select '[GDAL] GeoTIFF'. Now
select the ‘toposheet.tif’ and click ‘Open’.
6. You will then be presented with the 'Coordinate Reference System Selector' window, from which we
will select the 'WGS 84' under Coordinate reference system of the world section.
7. To georeference an image we use Ground Control Points (GCPs). GCP is a location on the earth's
surface with known coordinates on both earth and Toposheet/ imagery, i.e., geographic and pixel
coordinates respectively. In this we use graticule intersections as GCPs.
8. To start adding GCPs to our map, we first zoom to a corner of the map where we can easily identify the
intersection of the latitude and longitude. Use the scroll wheel of the mouse to zoom in and out of the map.
Use the 'Pan' Button when needed.
9. To add a GCP click on the 'Add point' button, or go via the menu (Edit → Add Point). The mouse will
transform into a '+' sign, which we use to click on the centre of the intersection. Use 'View tool' when
needed.
5. 10. A window 'Enter map coordinates' will pop up where we enter the coordinates of the point which we
take from the map. Always enter 'Longitude or Easting' in X field and 'Latitude or Northing' in Y field. Use
'space bar' in the key board to separate the Degree value from Minutes value and then click ‘OK’.
11. In this exercise we are using the 'Polynomial 2' transformation to georeference the image. For the
'Polynomial 2' transformation we will require minimum 6+1(for check) i.e., 7 GCPs or more GCPs on the
map. Therefore, we need to mark at least 7 GCPs. The GCPs locations should be spread out as much as
possible and they should not be co-linear at the same time they should enclose our whole area. Use the
above procedure to mark six more control points.
12. We now set the spatial reference settings for the toposheet by clicking on the 'Transformation Settings'
button. The 'Transformation Settings' window pops up in which we will enter the spatial information of our
map.
13. Click on the 'Transformation type' drop-down menu and select 'Polynomial 2'. This means we will be
using a second order polynomial transformation.
14. Click on the button next to ‘Output Raster'. A dialogue box will appear in which we enter the name of
our output file. It is recommended to include the name of the original file in this file for example
'Toposheet_WGS84_georef.tif ', This helps us to keep track of our work.
15. ‘Check’ the check box 'Load in QGIS when done' and 'Use 0 for transparency when needed', leave the
reset of the values as default and click 'OK'.
16. After Click 'OK', the last column 'residual [pixels]' displays some values. These are the error values
associated with the GCPs. An error value of 1 or less would be satisfactory.
17. Double check and adjust the GCP locations if the value is greater than 1. To adjust a point, click on the
'Move GCP Point' button, and then click and drag the point to the desired location. Use 'Delete Point'
button to delete an erroneous GCP. We can also enable and disable the GCPs by using check boxes under
'on/off' column in 'GCP Table'.
18. Once the error is around or below 1, click the 'Start Georeferencing' Button. The processing will take at
about 2 minutes. The georeferenced image will be found at the location specified for the 'Output File' in
step 15. You can also notice, the output file loaded in QGIS canvas.
6. 19. It is useful to save the GCPs for later use if the georeferencing needs to be done again, or if corrections
are required. To save them, click on the 'Save GCPs as' button. In the pop up window enter an appropriate
name for the GCP file, preferably the same as that of the image. This file can be loaded later on by clicking
on the 'Load GCP points' button in 'Georeferencer' window after adding toposheet, and selecting it from the
pop up window.
7. DIGITIZATION
Introduction
Digitization is the process of converting analog data into digital data sets. In GIS context
digitization refers to creating vector datasets viz., point, line or polygon from raster datasets. It is a
way of tracing/recording geographic features in vector format from georeferenced images or maps.
With the help of digitization, we can create different set of layers Viz. Rivers, roads, schools, ward
boundaries and building blocks from a single map; this process is known as Vectorization. Vector
data is easy to edit, update and is more accurate as compared to raster data. Vector data is more
efficient for GIS analysis. Due to these reasons Vectorization is the first step in many GIS projects.
However, it is a time-consuming process and needs a lot of attention to prevent introduction of
errors in the datasets. Vector data is mainly of three types
- Point: It consists of single points having (X, Y) coordinates, for example lamp posts, bus stops
and postbox positions etc.
- Line: It consists a series of (X, Y) coordinates in a sequence (from start node to end node with a
number of vertices joining these two nodes). For example, roads, power lines, ward boundaries and
contours etc.
- Polygon: It is a series of (X, Y) coordinates in a sequence closing a figure where first and last
points are the same. For example, lakes, building blocks, village blocks, ward areas and forests etc.
In this exercise we will use the output of ‘IGET_GIS_003: Georeferencing a Toposheet tutorial’ as
our input.
Open the raster layer of georeferenced toposheet of IGET_GIS_003 tutorial in the map canvas
of Quantum GIS via, ‘Main menu bar → Layer → Add Raster Layer’ or else directly click on icon
from the toolbar → browse and select the georeferenced raster layer in tutorial data → Click on
‘Open’ in the popup window.
8. EXERCISE- 3
Point Layer Creation
1.To create new point layer, go to main menu bar in QGIS interface and select ‘Layer’! ‘New’!
‘New Shapefile Layer’.
2. Now the ‘New vector Layer’ window will popup. Select ‘Type’ as ‘Point’ as we are interested in
creating a point layer.
3. Specify CRS same as original layer, i.e., as ‘EPSG:4326 - WGS 84’. To do this click on
‘Specify CRS’! Select the ‘WGS 84’ under Coordinate reference system of the world! Click on
‘OK’
4. We can add new required attribute fields to the vector layer that we have created. For example,
if we are creating point vector layer of all temples we can add ‘Name’ of the temple as new field
and ‘intake capacity’, ‘Address’ etc. as other fields.
5. For Each New attribute added, an appropriate name, type of the variable (like text, whole
number, decimal number and date) and width must be selected. Click on ‘Add to attribute List’ and
the attribute will be added to the list.
6. Once the required attributes are added, click on ‘OK’.
7. Now you will be presented with ‘Save As’ window, save the file in appropriate drive with
appropriate name for example: temple up.shp. Once the layer is saved it opens as point data layer
under map legend.
8. To start digitization, we have to enable the editing mode of the corresponding vector layer.
Right click on temple up.shp’ point layer and click on ‘Toggle Editing’
9.You will notice a pencil symbol on left side of the layer name. This tells you that the layer is
ready for editing.
10. Zoom into the toposheet where temples are present, the symbol of hospital in the given
toposheet is. Click on Add feature icon from digitizing toolbar.
11. Place the pointer at the center of the feature of interest and click.
12.You will be presented with an ‘Attributes’ window. Fill the required attribute information like
‘id’, ‘Name’ and ‘Intake_Cap’ (Intake Capacity), ‘Address’. Click ‘OK’.
9. 13. The point will be created with the specified attributes at the specified location. Now open the
attribute table of temple up.shp’ by right clicking on the temple layer and selecting ‘Open Attribute
Table’. If you want to change any details, then simply select the attribute by double click and edit
it. For example, change the number of visitors from 1000 to 1200.
14. Similarly digitize the other temples in the toposheet. Click on ‘Save Layer Edits’
icon in ‘Digitizing’ tool bar, to save the edits. After saving click once again on the toggle button to
stop editing. This will save the point layer along with its attributes.
15. Go to attribute table of temple up.shp’ to check if the attributes are added properly or not. If not
properly added, edit them as described in step 13.
10. B) Point layer Layout
I. To get the layout of the Temple point layer, go to ‘Project’ → New Print Composer, then fill the
‘Composer title box’.
II. Then the Composer window will appear. Go to layout drop down menu, select ‘Add Map’ and
draw a box in the space below to get the selected layer layout.
III. Then through the available options, add ‘scale’ and ‘legend’ to the layout and make changes if
required.
11. EXERCISE- 4
Line Layer creation:
A) Line is basically used to represent any linear network such as road, railways and drainage etc.
1. To create line layer, go to ‘Layer’ ! ‘New’ ! ‘New Shapefile Layer’. The ‘New vector Layer’
window will open up. Select ‘Type’ as ‘Line’ as we are interested in creating Line layer of roads
and Specify CRS as ‘EPSG: 4326 – WGS 84’.
2. Add required attributes, for example ‘Name’ as shown in above figure and click ‘OK’. ‘Save
As’ window will open up. Browse to an appropriate location and give an appropriate name for
example ‘Drainage-UP’ ! click on ‘Save’.
3. The layer is created and will be listed in Map legend. Right click on layer, click on ‘Toggle
Editing’ or click on icon from ‘Digitizing’ toolbar.
4. Zoom into the toposheet where river are seen. Click on ‘Add feature’ icon from ‘Digitizing’
toolbar.
5. Now trace cursor along the middle of the road by using left mouse button to insert vertices when
you think the road changes its profile, this means you have to insert more vertices while digitizing
bends to get smooth curve. When you reach a junction or at the end of the road click on the right
mouse button to stop. Now ‘Attributes’ window will open, fill in the appropriate attributes for
example Name is ‘Left bank Yamuna’ and click ‘OK’.
6. Snapping tolerance can be set manually. Go to ‘Settings’ ! ‘snapping Options’.
7. Check the box to the left side of river layer and set ‘Mode’ to ‘vertex and segment’. Specify
tolerance as ‘5’ pixels. Check on ‘Enable topological editing’. And click ‘OK’
8. So by use of the snapping tool it is possible to get an accurate intersection of roads. Once you
finish digitizing all roads in the toposheet save the edits and stop editing by clicking on ‘Toggle
editing’ button. Now the road network along with its attributes will be saved.
12. B) Line layer Layout
I. To get the layout of the Temple point layer, go to ‘Project’ → New Print Composer, then fill the
‘Composer title box’.
II. Then the Composer window
will appear. Go to layout drop
down menu, select ‘Add Map’
and draw a box in the space
below to get the selected layer
layout.
III. Then through the available
options, add ‘scale’ and
‘legend’ to the layout and make
changes if required.
13. EXERCISE- 5
Polygon Layer creation:
A) Polygon is basically used to demarcate areas such as administrative parcels, forests, buildup areas and
water bodies etc.
1. To create Polygon layer, go to ‘Layer’! ‘New’! ‘New Shapefile Layer’. The ‘New vector Layer’ window
will open up. Select ‘Type’ as ‘Polygon’ and Specify CRS as ‘EPSG: 4326 – WGS 84’.
2. Add required attributes for example ‘Name’ and click ‘OK’. ‘Save As’ window will open up, save the
file at appropriate location, for example ‘Settlements.
3. The layer will be created and listed under Map Legend. Right click on layer! click on ‘Toggle Editing’.
4. Zoom into the toposheet where Settlements are located. Click on ‘Add feature’ icon from digitizing
toolbar.
5. Make sure that the snapping option for Settlement layer and also other required layers consisting of the
features that are following their boundary is also enabled.
6. Start digitizing the reserve forest polygons by using left mouse button to insert vertices and right mouse
button to finish. Once you finish digitizing all reserve forest areas, save edits and de-select the ‘Toggle
editing’ button.
7. Now digitize the other features to prepare a Map. The Toposheet given to you in the supplied data set
was prepared by using QGIS. You have to digitize all the vector feature layers in this tutorial to create a
map in cartography tutorial.
14. B) Polygon layer Layout
I. To get the layout of the Temple point layer, go to ‘Project’ → New Print Composer, then fill the
‘Composer title box’.
II. Then the Composer window will appear. Go to layout drop down menu, select ‘Add Map’ and
draw a box in the space below to get the selected layer layout.
III. Then through the available options, add ‘scale’ and ‘legend’ to the layout and make changes if
required.
22. THEMATIC MAP
Introduction
A Thematic map is a map that emphasizes a particular theme or special topic such as the sex
ratio, literacy rate in an area. They are different from general reference maps because they
do not just show natural features like rivers, cities, political subdivisions and highways.
Instead, if these items are on a thematic map, they are simply used as reference points to
enhance one’s understanding of the map's theme and purpose. They provide specific
information about particular locations and spatial patterns.
In this exercise, we made thematic map of Bihar showing sex ratio and literacy rate with the
help of digitization.
Procedure
1. We took the data for literacy and sex ratio of each district of Bihar from the 2011 census.
This data was divided into 4 class intervals.
2. Then, separate layers were created for each interval using polygon feature and districts
falling in each of these class intervals were marked.
3. Next a separate shade was assigned to each category starting from dense shade for those
having highest value to lighter shade showing districts having lower value.
4. Once digitization of all layers is done, the layer edits were saved and the Toggle editing
button was deselected.