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Remote Sensing and GIS Application in Hydro geological Mapp

“Remote sensing and GIS in hydrogeological mapping and water quality modeling”

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Remote Sensing and GIS Application in Hydro geological Mapp

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  1. SBL GSS Division Remote Sensing and GIS Application in Hydro geological Mapping and Water Quality Modeling By Venugopalan Nair

  2. Outline Introduction Remote Sensing System Electro Magnetic Spectrum Digital Image Processing Radiometric corrections Geometric corrections Thematic mapping Hydro geological Mapping Water Quality Modeling- A Case Study

  3. Self Introduction Name: Venugopalan Nair Education: M.Sc. (Applied Geology), Barkatullah University, Bhopal, India M.Tech (Remote Sensing), Bharathidasan University, Trichy, India M.Tech (Hydrology), IIT, Roorkee, India Experience: 15 Years + in GIS National Geophysical Research Institute GB Pant Institute ofHimalayan Environment and Development Defense Terrain Research Lab Central Ground Water Board RMSI SBL

  4. Self Introduction • Venugopalan Nair, Senior Manager, SBL has delivered a lecture on “Remote sensing and GIS in hydrogeological mapping and water quality modeling” for a training course on sustainable development and management of ground water resources, conducted by Central Ground Water Board, Rajiv Gandhi National Ground Water Training and Research Institute, River Development and Ganga Rejuvenation, Ministry of water Resources, Government of India • In the lecture, Mr.Nair has explained the basics of remote sensing technology to participants from agricultural, soil conservation, Cochin University of Science and Technology, and many other departments constantly works for sustainable development. The presentation explained how this useful technology and implement in agriculture, land resource utilization, water conservation and ground water quality modeling. The enthusiastic participants made many queries in their respective domain and updated themselves about this technology.

  5. Remote Sensing System

  6. Electro Magnetic Spectrum

  7. Energy Interactions

  8. Energy Interactions

  9. Resolutions in Remote Sensing Resolutions in RResolutions in Remote Sensihjhjkhkngdfwefrefrte3trer3434ererwemote Sensing Spatial Resolution Spectral Resolution Radiometric Resolution Temporal Resolution

  10. Spatial Resolutions LISS IV Image Spatial Resolution 5.8m Land sat Image Spatial Resolution 30m

  11. Spectral Resolution

  12. Characteristics of commonly used bands

  13. Radiometric Resolutions

  14. Temporal Resolution

  15. Sample Satellite Image

  16. Satellite Image Procurement Sun Angle Nadir angle STD/Ortho ready

  17. Digital Image Processing Radiometric Corrections Geometric Corrections Image classification

  18. Digital Image Processing PIXEL

  19. Image Enhancement

  20. GIS Services – Geo Referencing Using Feature matching Using DGPS points Using reference coordinates /grid

  21. Pan Sharpening/Resolution Merging

  22. Mosaicking

  23. Colour balancing

  24. Tiling

  25. Digital Elevation Models

  26. Digital Elevation Models

  27. Ortho rectification

  28. Classification Supervised classification Unsupervised classification Hybrid classification

  29. Supervised Classification Training site identification Spectral signature collection Statistical analysis Classification Methods Process running

  30. Supervised Classification

  31. Supervised Classification • Advantages • Analyst has control over the selected classes tailored to the purpose • Has specific classes of known identity • Does not have to match spectral categories on the final map with informational categories of interest • Can detect serious errors in classification if training areas are misclassified

  32. Supervised Classification • Disadvantages • Analyst imposes a classification (may not be natural) • Training data are usually tied to informational categories and not spectral properties • Remember diversity • Training data selected may not be representative • Selection of training data may be time consuming and expensive • May not be able to recognize special or unique categories because they are not known or small

  33. Unsupervised Classification Algorithm based Inbuilt methods

  34. Unsupervised Classification • Advantages • Requires no prior knowledge of the region • Human error is minimized • Unique classes are recognized as distinct units • Disadvantages • Classes do not necessarily match informational categories of interest • Limited control of classes and identities • Spectral properties of classes can change with time

  35. Unsupervised Classification

  36. Feature Extraction

  37. Thematic mapping

  38. Land Use Land Cover Mapping Activities • Input image collection • Geo referencing • LULC schema preparation • Image classification • Topology corrections • Field verification • Post field updation • Final LULC map compilation

  39. PICTORIAL REPRESENTATION OF GROUND WATER QUALITY DETERIORATION

  40. STUDY AREA • LOCATION

  41. STUDY AREA GEOLOGY SIWALIC FORMATIONS INDO-GANGETIC ALLUVIUM BHABAR TARAI ALLUVIAL PLAINS

  42. STUDY AREA HYDRO-GEOLOGY

  43. STUDY AREA HYDRO-GEOLOGY CROSS SECTION ALONG GANESHPUR – SHIKARPUR CROSS SECTION ALONG MANAKPUR - JWALAPUR

  44. 9 Ratings Weight 3 × 5 6 × 4 5 × 3 5 × 2 6 × 1 4 × 5 × 3 132 IAWQ MODEL THROUGH GIS

  45. AQUIFER WATER QUALITY INDEX ADVANTAGES OF AWQI METHOD • THE METHOD HAS A LOW COST OF APPLICATION • APPLIED IN EXTENSIVE REGIONS • RELATIVELY FEW, EASY TO COLLECT, AND COMMON DATA IS REQUIRED • SEVERAL PARAMETERS AND THEIR INTERRELATIONSHIP DECREASE THE PROBABILITY OF IGNORING SOME IMPORTANT PARAMETERS • RESTRICT THE EFFECT OF AN INCIDENTAL ERROR • ENHANCE THE STATISTICAL ACCURACY OF THE MODEL • OTHER SPECIALIZED METHODS WOULD REQUIRE SPECIFIC PARAMETERS.

  46. DRASTIC MODEL DISADVANTAGES OF DRASTIC METHOD • SO MANY VARIABLES ARE FACTORED INTO THE FINAL INDEX THAT CRITICAL PARAMETERS IN GROUND WATER CONTAMINATION MAY BE SUBDUED BY OTHER PARAMETERS THAT HAVE NO BEARING ON GROUND WATER POLLUTION. • THE SELECTION OF THE PARAMETERS IS BASED ON QUALITATIVE JUDGMENT AND NOT QUANTITATIVE STUDIES.

  47. GROUND WATER QUALITY MODALITY OF GROUND WATER SAMPLE COLLECTION • PRE FIELD PREPARATIONS • PURGING OF THE WELLS • SAMPLE COLLECTION • FIELD ANALYSIS • pH • ELECTRICAL CONDUCTANCE • TEMPERATURE • STORAGE • LABORATORY ANALYSIS

  48. GROUND WATER QUALITY LABORATORY ANALYSIS

  49. GROUND WATER QUALITY LABORATORY ANALYSIS

  50. GROUND WATER QUALITY DISTRIBUTION OF pH AND TDS

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