Application Of Remote Sensing & GIS for Effective Agricultural Management By Dr Jibanananda Roy Consultant, SkyMap Global

Introduction Agricultural Practices And Effect On Man And Environment Unplanned Agricultural Practices Overuse of Natural Resources Unscientific Use of Chemicals & Fertilizers Man made and Natural Changes in Environment & Ecology Biodiversity

Introduction Agricultural Practices And Effect On Man And Environment Degradation of Land and Environment Reduction in Crop Yield Environmental Pollution Human Health Hazard Natural Disasters

REQUIREMENT Sustainable Agricultural Management Plan Region Specific Management Plan Effective Use of Technology Long Term Management Plan Awareness Among Stakeholders Analysis Of Social, Political, Infrastructural And Financial Issues Preservation Of Natural System

TECHNOLOGY Availability And Use Satellite Remote Sensing Data – Multispectral & Hyperspectral – SAR – Digital Terrain Model – Derived Data Weather – Historical And Predictive Software And Systems Periodic Monitoring And Corrective Action Human Experts

OBJECTIVE Propose methodologies for continuous crop health monitoring and yield prediction using satellite images, field survey data and ancillary information Analysis of historical data and field survey using Remote Sensing to develop a model for crop yield prediction. Productivity analysis of different crops with respect to other similar areas or historical data. Identification of parameters for productivity. Agricultural zoning. A sustainable development plan.

Data Analysis During Last 30 Years Several Effective Models Have Been Developed And Implemented Models Are Case Specfic – Regional, Agriculture Type Direct Models Integration Of Field Survey Issues Of All Stakeholders Multi-criteria Decision Support System

SCALE Large Contiguous Area With Similar Crop Mixed Cultivation – Orchard, Vegetables, Horticulture Single Crop Vs Multiple Crops Periodicity Of Crop Yield

Standard Models Normalized Difference Vegetation Index (NDVI) Other Band Ratios Leaf Area Index (LAI) Spectral Signature – Crop Health & Crop Yield Band Combinations Fusion Of Multiple Satellite Data

Advanced Models Models Based On Narrow Band Hyperspectral Satellite Data Use Of Red Edge Band With NIR – Crop Type Delineation – Crop Health Monitoring – Crop Yield Estimation

Use Of SAR Data Crop Type Analysis Based On Texture Estimation Of Soil Moisture – Crop Type Delineation – Crop Health Monitoring – Crop Yield Estimation

Mixed Cultivation Smaller Area With Different Type Of Crops High Crop Yield At Specific Areas Low Yield In Several Areas – Individual Plot Level Management Plan – No Macroscopic Plan – Bad Water Management – High Pollution – Land Degradation, Soil Erosion – Bad Disaster Management During Flood and Other Natural Calamities – Ineffective Use Of Satellite Data – Awareness

Issues With Satellite Data Not Viable For Small Land Holdings And Mixed Cultivation May Not Be Effective For Pest Attack Information Due To Inherent Delay In Providing Data Limitation Of Predictive Model Development Data Degradation Due To Atmospheric Disturbances

Effective Use Of Satellite Data Analysis Of Large Area Model Development With Field Collection Of Spectral Parameters Effective Use Of SAR Data Fusion Or Mixed Mode Analysis Of Coarse And High Resolution Data Continuous Data Collection, Analysis and Notification Refinement Of Model Based On Past Data Infrastructure Development Plan for Storage And Delivery

CONCLUSION Agricultural Zoning Based On Natural Factors Satellite Data Can Be Effectively Used By Analyzing Large Agricultural Zone. Field Survey For Model Development By Analyzing Spectral Characteristics. Development Of Better Water Management Plan Continuous Monitoring And Model Refinement Development Of Rule Based System Analyzing Multiple Factors Using GIS and Rule Based Software.

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