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remote sensong analysis
This report summarizes the analysis of satellite imagery for an area in India located at 29° 58' N 78°10 E. Three methods of remote sensing analysis were used: visual interpretation, digital analysis with Erdas Imagine, and classification of land features. Key findings include identification of urban areas, water bodies, vegetation/crops, and man-made structures. Crop analysis identified rice and wheat fields and estimated harvest amounts. River pollution analysis used reflectance values. Road construction needs were assessed using spatial and surface profiling tools. The study area and different land categories were delineated. Changes over time were observed using Landsat images from 1999 to 2003. Remote sensing allowed efficient land use planning and modeling of the terrain.
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remote sensong analysis
- 1. Analysis of satellite imagery Basedon remote sensing Submitted to- Bindi mam Submitted by – Mayank singh sakla
- 2. Introduction Remote sensing ismethod which is used to get information about any object without coming in contact with it. data analysis is done by 2 methods 1.visual interpretation 2.Digital techniques we are using Erdas imagine as a tool to analysis images.
- 3. Objective The object ofthis report is data analysis of remotely sensed images and understanding End utilisation process. The aim consists of following study – Analysis of urban feature Analysis of water body Analysis of man-made feature Analysis of vegetation (crop) or land feature
- 4. Geographical location(lat/lon) 29°58' N 78°10 E Humidity Above 55% except winter (25%) MSL 300 METER Wind velocity 15 km/hour approx. Vegetation Northeast of city ( Rajaji national park) Urban (UA certified) 19 lacs approx. (2011) Annual temperature variation 4 to 40 degree Celsius Area 14 km square Study area Source-SOI MAP map
- 5. Data used Data usedhere are generated after correcting error. Data are in standardized format, so that it allows analyze. Data obtained from satellite S. No. Sensor name Spatial resolution Spectral band 1 LISS III 23.5 M 3 2 AWIFS 54 M 4 3 LANDSAT(L4-5TM) 30 M 7
- 6. Methodology SLECTION OF AREA DATADOWNLOAD BY PUBLIC DOMAIN WEBSITE BHUVAN EARTH EXPLORER/USGS IRS SERIES LISS III AWIFS LANDSAT(L4-5TM) USE OF ERDAS AS TOOL( .img) Interpreter utility stack Data preparation mosaic Perform task and analysis
- 7. Thematic map generation Toolused histogram By supervised and unsupervised work Here This figure will help in unique map generation of vegetation.
- 8. Crop analysis Age ofcrop / health can be identified by LUT value. Government uses this for deciding base value
- 9. • Age ofcrop can be identified by look up table value it is fully based on reflectance amount by leave of crop . • Area under histogram of this area can be used to estimate quantity of crop. • In digital technique Band 3 (LISS III) is very useful in vegetation study. • Calibrated scale is use by client to measure quantity . • calculation of ratio vegetation index (RVI)
- 10. Continuation….. • Normalized differentvegetation index (NDVI) calculation. It is high in NIR than red band. Rain fall 1054 mm annual Soil type sandy Sown area 118.4 ha Kharif crop rice Rabi crop wheat Source:- agricoop.nic.in
- 11. Ganga river pollution Toolused inquire cursor / LUT value According to reflectance value we may estimate the quantity of turbidity in river water.
- 12. Survey of RoadWork Tool used spatial profile tool Estimation of cutting and filling for road construction
- 13. Terrain modeling Tool used surface profile According to elevation profile we may Generate digital elevation model.
- 14. National park analysis NAME-Rajaji national park some part In meters TYPE – dense forest ORIGINALLY= Area of park cover under this image is only 6.29% of total area which is 820 kmsq.
- 15. Category distribution By assigningunique identification We may demarcate different feature Like Urban Water body vegetation
- 16. Wasteland management LANDSAT 1999LANDSAT 2003 The located place is of no use since many years so we can use it like for tourist accommodation
- 17. Climate change Source–LANDSAT4-5TM 1 APRIL1999 2 JANUARY 1999 FIG. Changes can be see in hilly region according to temporal variation
- 18. conclusion • Crop analysiscan be made efficient by applied remote sensing • River cleaning project can be achieved • Surveying of area can be made efficient like profile leveling • Optimize use of land can be achieved • Modeling(Terrain modeling) can be done • Cartographic map can be made according to remote sensing data.
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