Remote sensing information is extremely useful for monitoring drought over large areas as it can offer detailed and frequent

observations Several satellite-derived vegetation indices, such as the Normalized Difference Vegetation Index (NDVI),

Vegetation Condition Index (VCI), and Temperature Condition Index (TCI), have been developed to monitor drought from

local to global scales. These indices help assess drought-related vegetation stress and are often validated against ground

observations.

Proposed satellite based Agromet Products

• In-season monitoring of crop area

• LST PRODUCT

• Daily Surface Insolation product

• Surface Soil Wetness Index (SWI)

• Evapotranspiration using surface energy balance

• Monthly estimates of PET from VHRR insolation and WRF forecast

• Delineation of alarm zones to alert farmers

• Development of methodology for forecasting spatial crop age / phenology

• Development and validation of Crop Water Requirement Satisfaction Index (WRSI)

• Development of SPI from satellite rainfall

• Development of operational demand-based irrigation scheduling

• Development of Digital agro-climatic atlas for improved crop planning

• Development of methodology for tracking major pests and diseases

Remote sensing information is extremely useful for monitoring drought over large areas as it can offer detailed and frequent

observations Several satellite-derived vegetation indices, such as the Normalized Difference Vegetation Index (NDVI),

Vegetation Condition Index (VCI), and Temperature Condition Index (TCI), have been developed to monitor drought from

local to global scales. These indices help assess drought-related vegetation stress and are often validated against ground

observations.

Satellite data is increasingly utilized for weather monitoring, leading to more frequent use of microwave and radar

technology to gauge soil moisture and rainfall. This improved approach provides crucially accurate information for effective

drought-monitoring.

Advances in satellite technology have enabled the estimation of key drought-related variables, including:

• Land Surface Temperature (LST)

• Evapotranspiration (ET)

• Soil Moisture

• Precipitation