Remote Sensing and GIS Spatial Analysis-Scenario Analysis based on Land use Plan and Policies

This article is in continuation of last article in which remote sensing and GIS used for spatial analysis to assess and prospects of future scenario in urban change. In the below article another case is discussed in which effectiveness of proposed plan of 2025 for city is assessed using remote sensing and GIS based spatial analysis process.Through remote sensing, one can acquire satellite image of different periods or multi date as well as from high resolution to medium resolution and also combination of bands or multi spectral or panchromatic band. In current there are many choices are available related to acquiring of satellite images. This may help user to create spatial data from high resolution to medium resolution as per need and also for different periods like from last 10 or 20 years to ascertain the change and trend of urban sprawl. The basic and important steps of digital image processing such as layer stacking, subset, mosaic, enhancement, interpretation and classification

Remote Sensing and GIS Spatial Analysis-Scenario Based Analysis of Future Urban Sprawl

Remote Sensing data or images can be used to assess past trends and current status of natural as well as man-made features on earth surface. Satellite imagescan be acquired based on need and using image characteristic/properties such as Spatial, temporal and spectral resolutions to create spatial data in the form of land use/land covermaps. GIS is used to create other spatial data such as road network, proximity to central business district etc. The spatial data can be created in both raster and vector format including non-spatial data in the form of attributes for scenario based analysis. These data can also convert from raster to vector and vice versa as per need using image processing and GIS software.These spatial data can be integrated to assess the changes in future based on some specific condition and constraints. As GIS allow to incorporating mathematical and simulation models, it is become easy to use these spatial data for assessment based on certain condition, which can be …

Remote Sensing and GIS for Urban Sprawl Projection/Prediction

Urban sprawl, an outcome of socioeconomic development and population under certain conditions, is continuously increasing. It becomes a major issue facing by many metropolitan cities of developing and developed countries. Urban sprawl is often took as scattered suburban development that create and increase several issues-  Stress on basic amenities  Traffic problems,  Reduce local resources, and  No more open space  It is important to appropriately illustrate urban sprawl in order to prepare a complete understanding of the causes and effects of urban sprawl processes. Urban sprawl is often assessed and characterized based on major socio-economic factors such as  Growth in Population  Transportation/Commuting Costs Employment Shifts  Revenue Generation in City  Commercial Development Status Urban sprawl, in most cases associated with poor land use plan and economic development and activities. 
This above approach based on socio-economic factors cannot effectively identify the influences of urban…

GIS Spatial Analysis-Land Use Mix Spatial Data

IntroductionGIS is a versatile tool and can be used for variety of application as well as creation of spatial data. It can be used to create elevation data, population density, water quality, urban density, air quality etc. and at the same time these data can be spatially represented. The advantage of GIS spatial data, that it can be analyzed to assess the impact on neighborhood or surrounding environment. GIS has various functions,spatial data in both formats such as raster and vector.Here in this article GIS is used to create distribution of commercial and industrial activity within the city to find out the impact on travel demand. For this a spatial data named land use mix created using GIS spatial analytical tool.Land use mix index is used to ascertain the level of commercial activity in each ward of Jaipur city. This indicator is very important to know the level of commercial and industrial activities (in the form of At present, there is no available data source that provides the…

Buffer Analysis Using QGIS

IntroductionGIS provide many tools for understanding and analysis of spatial data base. GIS has capabilities to analyze feature itself as well as its surrounding area and impact of surrounding area on that earth feature. GIS functions play significant role in the data creation, edit, manipulation and analysis. There are ‘n’ number of function available in GIS based on mathematical, statistical and spatial approach such proximity analysis, buffer analysis, spatial analysis etc. 
Buffer analysis is used to delineate areas in proximity to geographic spatial feature. In this a buffer is generated around that existing geographic feature by using distance parameters and this buffer area is used to identify and analyze spatial features comes into that buffer area or outside that buffer area. 
In the buffer analysis a buffer area of specified distance from geographic feature is created then this buffer area can be used to specify the spatial features fall in that buffer area and features are be…

Interpolation Process of Spatial Data in GIS Environment using QGIS

Introduction Continuous spatial data is very important in many applications for spatial analysis. So for such analysis, acquiring continuous spatial data is very difficult, costly and usually takes very long time for study area. In case, if one needs to collect/create continuous data then field sampling and observations is very common practice, such as water sampling for quality analysis. But during this field sampling process, it is nearly impossible to collect data from each and every spot of field, usually samples collected at certain distance. So this distance gap/interval between two samples/more samples is not possible to cover as well as very tedious and time consuming. In this case, some representative samples such as water samples from all well locations or pollution parameters from air monitoring stations will be collected and interpolation method is deployed to create continuous layer. Accuracy of interpolated spatial data depends upon the quantity and spatial distribution …

Digital Image Processing-Introduction to Image Classification

IntroductionClassification is a simple process to categorize or sorting of data based on defined categories or criteria. Such as students in class can be categorized based on marks obtained in maths- number of student below 40%, number of students between 40-60%, number of students between 60-80% and number of students having more than 80%. So based on this criteria student can be categorized or sort in to four different class/category. This is a very simple and basic approach of classification to understand behavior of data in quantitative and qualitative both ways. 
This classification approach is used to classify satellite image. in the satellite image classification process, images are classified based on categorization and classification of pixel values present in satellite image. The pixel value present in each pixel is also called DN values (Digital Number), which is representation of reflectance values received by sensor of earth surface feature. It is already explained in prev…

Application GIS and Remote Sensing in Wetland Mapping-Case Study

Remote Sensing and GIS in Wetland MappingWetland mapping provides useful and important information for assessment of water resources and also for conservation and management of wetland. Remote Sensing and GIS techniques have huge potential for mapping, monitoring and assessment of wetland resources. There are better options to the users for wetland mapping, due to advancement in remote sensing and GIS technologies. As variety of remote sensing images are available with better and finder spatial and temporal resolution. As well as stereo satellite images are also available for effective and accurate mapping and estimation. These high resolution and stereo images can be used to wetland database and integrated with GIS for further analysis such as change simulation, scenario based predictions for better planning and monitoring.  Wetland Mapping Process through Remotely Sensed Images In the study the wetlands of Rajasthan falling in different ecological regions ranging from humid to hot ar…

Remote Sensing Application in Wetland Mapping

Inland Wetland Environment Wetlands refer to lowlands covered with shallow and sometimes temporary or intermittent waters. Wetlands include marshes, swamps, bogs, wet meadows, potholes, shallow lakes and ponds. However deep lakes, reservoir and permanent waters of streams are not considered as Wetlands. Hence we can say wetlands are transitional lands between terrestrial and aquatic systems where the water table is usually at or near the surface.  Importance of wetlands Wetlands posses a great ecological significance in terms of, net primary production, micro-climatic control, ground water recharge and habitat to large number of flora and fauna. It also plays a vital role in nutrient recycling and storage as well as biodiversity conservation. Wetlands help to retain water during dry periods, thus keeping the water table high and relatively stable. Threats to wetlands Rapidly expanding human population, large scale changes in land use, different development projects and improper use of w…