Accurate and faster estimation of crop area is a great utility in the farming process as it helps in estimating crop production in advance of the harvest. As Indian agriculture is mainly characterized by fragmentation and land holdings whose size is less than 1 ha a much finer spatial resolution is necessary. The required spatiotemporal resolution of the satellite products used in the study is obtained by integrating multi-sensor data with an algorithm developed at Satyukt analytics, as most of the satellite products have compromised spatial or temporal resolution.

Crop acreage is the determining factor in crop production as it is helpful in determining the national or regional food demand and supply balance. Satyukt Analytics Pvt Ltd has developed an innovative methodology based on the Dynamic time warping algorithm to estimate the temporal signatures of the area. Each crop has a phenological cycle that is relevant for space-time classification. Remote sensing satellites overpass a particular place at regular intervals, and thus their data can be recorded as a three-dimensional array in space-time. Spectral signatures of the area under study are also calculated as different crops exhibit significant variability due to several factors like climate, soil, farming practices. These signatures are used to estimate the different crop types for each of the pixel (spatial resolution of 30 m) of satellite data. The crops grown over time at a particular place can be analyzed and identified accurately and thereby area covered by individual crops can be calculated with much ease. The model is calibrated using 60% of the field data samples, whereas the remaining is used for validation of the results.