Agriculture risk estimation: An aid for farmers who are risking life and limb for the food security of the nation
Agricultural production is subjected to many uncertainties. Hazards and unforeseen extreme climatic events increase the risk of agriculture production. Many risks directly affect farmers’ production decisions and welfare. Being an agrarian country, 48.9% of the Indian population directly or indirectly depends on agriculture (Economic Survey 2014-15)1. A total of 12,602 farming sector persons (8,007 farmers/cultivators; 4,595 agricultural laborers) has committed suicides during 2015, accounting for 9.4% of total suicides victims (1,33,623) in the country (National Crime Records Bureau statistics, 2015)2.
Agriculture yield is influenced by the Land-atmosphere interactions. In spite of their importance, the representation or modeling of these interactions in the existing weather and climate models are constrained because of the involvement of a complex set of process that is difficult to be monitored. Agro-hydrological parameters are the variables that vary with land-atmosphere interactions yet will retain the memory of the anomalies happened in past. Agro-hydrological (A-H) parameters (such as soil moisture, evapotranspiration, and NDVI) due to its inherent memory can hence be used in modeling L-AI to predict the risk associated in agriculture production. Dynamic forecasting of agriculture yield is possible by ensembling A-H variables with a machine learning algorithm. With the emergence of satellite sensors, A-H parameters can be monitored with much ease. Agriculture risk and related issues should be tackled from a policy-making and governance angle. Agriculture risk estimation may help decision-makers and stakeholders to take appropriate steps or formulate policies to eradicate or reduce the impacts of agricultural risk and thus safeguarding the life and interests of the farmers.
Satyukt analytics an expert in microwave remote sensing can estimate and predict the risk involved in agriculture production using high resolution,multi-satellite estimated Agrohydrological parameters and machine learning.
Satyukt Analytics salutes the farmers and acknowledges the contributions made by them in the path of poverty eradication.
