Showing posts with the label RS Analysis


Remote sensing is used for change detection and analysis of different earth surface features; it includes both man-made and natural features. These features can be combined in a one thematic map, which can be named as land use/land cover map. Features which are selected to include in land use/land cover map largely depends upon the objective of work/project as well as satellite image selected for project/study. As spatial and spectral propertiesof satellite image plays significant role in acquiring satellite image based on project/study objective. In this change detection analysis, multi date satellite images need to use and satellite image should have same season/acquiring date and month. Based on satellite image selection using spatial and spectral properties, level of classification is decided for land use/land cove map.Level of classification can be understood with this example in below figure- Figure 1 Classification Level for Land use/Land Cover Map These satellite image will be p…

Remote Sensing and GIS for Spatial Analysis- A Scenario Based Analysis Approach

Remote Sensing process is very significant to keep watch on earth surface features including both man-made and natural. Satellite image acquired and processed in image processing software to create spatial data. These spatial data can be further used as input data in different mathematical models to analyze the change and to find trends in future for policy planning and implementation.GIS software also used to create input data and those spatial data can further integrated in models to analyze current as well as future scenario. GIS has many functions and tools which can be employ to find the impact in that area as well as to analysis impact of neighborhood or vice versa.  In this scenario analysis, the urban area has been re-simulated for 2015 and 2025 by including commercial and industrial areas proposed in the 2025 land use plan. The aim of this analysis is to ascertain the impacts of commercial and industrial areas on urban change. The variable proximity to commercial and industri…

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…

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…

Remote Sensing Application for Coastal Studies

In this article remote sensing application is used for mapping of physical feature of coastal ecosystem. Coral reefs are mapped using satellite images. Coral reefs are described as live coral, dead coral and coral in bleaching condition.  Need of Coral Mapping Coral reefs are the foundation and primary structure of highly productive and diverse marine ecosystem. This is the reason, Coral reefs are called the “rainforests of the sea,” Corals grow in shallow water close to the shore and thrive within a limited range of temperature, salinity and turbidity. These ecologically and economically important marine habitats have been significantly degraded and destroyed by human and natural disturbance such as global warming or rise in sea surface temperature. When the environmental conditions that the coral requires are altered, the stress placed on the coral often causes bleaching. Decline in the density of zooxanthellae leads to coral bleaching. Large-scale bleaching is predominantly triggere…

Advantages of Multi Spectral Satellite Images

Advantages of Multi Spectral/Band Satellite ImagesRemote Sensing sensors record earth's reflectance in different wavelength and these received reflectance value are processed to create separate image for each wavelength. The reflectance value stored for different wavelength in different layers, which are also called bands present in that satellite images
Multi band images also known as multi spectral satellite images. Multi band image simply define, when more than one band/spectrum and at least three wavelength data recorded by sensor to create composite of satellite images. A sensor can record several wavelength simultaneously and it is completely depend upon sensor characteristics and capabilities.
As it is already studied that sensor can record earth surface feature in different wavelength from visible spectrum to infrared spectrum.The reflectance recorded from different wavelength can be converted in to satellite image. in general three wavelength from visible i.e. blue wave …

Advantages of Multi date/Temporal Images

Multi Date Images and their AdvantagesRemote Sensing process become more applicable by using temporal/multi date satellite images. Remote sensing system is developed to acquire satellite images of earth surface feature in repetitive mode. This repetition of satellite may vary with satellite to satellite,  it may be form few hours to days. 
Multi date images mean satellite image/aerial photographs captured by sensor on different dates but belongs to same location or area covered by that sensor. These multi date images are very useful and advantageous in remote sensing to find out changes with time in natural as well as man-made features. Change detection analysis is important process in which multi date satellite image employed for analysis. 
Multi date images also called as multi temporal images. As it is understood that satellite are ideals for monitoring changes of earth surface feature over time. The repeat cycles of satellite around the earth are measured either in days or weeks. Th…