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AP 640 REMOTE SENSING IN AGRICULTURE                                                                                  (2L+1P) III
(Pre-requisite: AP-140)

Objective
  To impart knowledge about the remote Sensing techniques and their applications in agriculture.

Theory

UNIT I
  Scope of remote sensing in agriculture, sensors and platforms, data availability for agricultural remote sensing.

UNIT II
  Spectral characteristics of soils, differentiation and identification of soils, spectroscopy of soils, soil parameters by hyperspectral remote sensing, soil survey and resource mapping.

UNIT III
  Interaction of EM radiation with plant components and crop canopies, spectral signatures, spectral and hyper-spectral indices, crop identification and acreage estimation, crop growth monitoring and yield modeling.

UNIT IV
  Infra red thermometry, crop abiotic and biotic stress differentiation and assessment, retrieval of crop biophysical parameters – empirical and radiative transfer approach, advanced digital image processing and classification techniques for crops.

UNIT V
  and use/ land cover mapping, land planning with reference to different agro eco-regions, land degradation process and their evaluation by remote sensing.

UNIT VI
  Role of remote sensing in water resource development and management, identification of ground water potential zones, generation of different thematic maps for integrated watershed management; utility of SAR data for crop inventory, salinity mapping, soil moisture mapping, flood assessment and management by remote sensing.

UNIT VII
  Precision farming principles - VRT, Modern techniques and machines.

Practical
  Use of Infrared thermometry and spectral data for crop stress monitoring, Hyperspectral data for soil and crop characterization, Computation of Spectral Indices for Soil and Vegetation, Processing of microwave Remote Sensing Data, Salinity mapping from remote sensing data, Pre-processing of time series satellite data, Crop discrimination and acreage estimation, Crop yield modeling from satellite data, Land use land cover classification and change detection

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