Time Series Crop Analysis Using Multispectral Remote Sensing

The combination of enhanced access to remotely sensed imagery and time series data together with the growing availability of artificial intelligence algorithms, has substantially broadened the community of users engaged in processing and analyzing earth observations over time. This will be particularly beneficial for the application of sustainable agricultural performance and for monitoring crops intermittently. The primary objective of this study is to design a methodology to be utilized in the analysis of crop dynamics based on Sentinel-2 multispectral remote sensing imagery. In this work, an algorithm is devised using Google Earth Engine (GEE) to illustrate cropping patterns and to map cropping intensity in the drought regions in Prakasam of Andhra Pradesh, India. This study focuses on understanding the cropping patterns for the years 2019–2023. This detection effort is used to analyze the impact of socio-ecological intervention carried out.