GIS & Remote Sensing

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…

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/Band Satellite ImagesMulti 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 depends simultaneously and it is depend on 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 length, green wavelength and red wave length, whereas infrared can be further defined as near infrared, mid infrared, far infrared and thermal infrared. So it can be simply explained as capability of sensor to sense reflectance in to different wave lengths to create multi band or multi spectral images. For example L…

Multi Date Images and their AdvantagesMulti date images mean satellite image/aerial photographs captured by sensor on different dates but same location or area covered by sensor for that satellite images/aerial photographs. These multi date images are very useful and advantageous 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. This repeat cycle also termed as temporal characteristics of satellite. By this every satellite has its own repeat period for any specific area by which multi date images created and used for monitoring changes on earth surface. It can be understand by the example, suppose if someone wants to …

Introduction to Digital Image ProcessingDigital Image Processing is the implementation of mathematical methods and algorithm on digital images for correcting, improving, analyzing and creating information. Nowadays remote sensing data are available digitally therefore process performed on these image also defined as digital image processing. Digital image processing is combination of processes in which different techniques deployed for editing, manipulation of digital images using image processing software. It is important to understand that the main aim of this processing is to extract information from satellite image, which are not readily available in satellite image, such as built up area, water body etc. To process satellite image digitally, the remote sensing data (i.e. satellite images/aerial photographs) must be recorded and facilitate only in digital form. Instead of digital satellite images, other requirements of image processing are computer system with appropriate hardware,…

Image Interpretation ElementsAs discussed in last article about image interpretation and also defined image interpretation elements/keys. Elements/Keys are below- Figure-Use of Elements/Keys for Image Interpretation SizeShapeShadowTone/ColorTexturePatternHeight & depthSiteAssociationColorColor is primary element and convenient to identify and recognize earth surface feature on multi band satellite image. Color images can be obtained by combination of three bands and two type of combinations can be prepared, first Natural Color composite (NCC) and the second one is False color composite (FCC). In both type of combination color may vary for the same feature, such as vegetation appears green in NCC whereas it will appear red in FCC. Figure- Color variation in FCC and NCC
ToneIt refers to the average brightness of an area or, in the case of color imagery, to the dominant color of the region. It depends on the nature of the surface and illumination. Smooth surfaces behave like specular refl…

Image interpretation The main objective of image interpretation is to create information in the form of thematic maps. A thematic map can be prepared by categorizing all pixels of the image into classes or themes to generate map from the remote sensing data. One can take different theme based on field of study, for example one can create Landuse/land cover map based on mapping different categories such as water, forest, rangeland, urban etc.Mapping and quantification of surface water bodies/ water resources.Geological map based on identification of landforms, rock types, folds, faults and fractures.Urban change detection maps using multi date remote sensing data.
Below steps followed for Image Interpretation- Classification                Assign objects to classes
               Detection, recognition, identification.                Interpreter confidence is ranked as possible, probable Measurement               Uses image scale to derive measurements such as length with distance and volume
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