Vol. 12, Issue 2 (2023)

Author(s):
Akash Barela, Sunny Thakur, Surbhi Pachori, Shivangi Rahangdale, Vinod Kumar Goyal, Sumit Kakade and MK Shrivastava

Abstract:
Agriculture meets humanity's most fundamental needs: food and fibre. New farming practices introduced during the last century (for example, during the Green Revolution) have helped agriculture keep up with rising demand for food and other agricultural goods. However, increased food consumption, a growing population, and rising income levels are all projected to place extra strain on natural resources. With an increasing awareness of agriculture's negative environmental implications, new techniques and approaches should be able to fulfil future food demands while preserving or lowering agriculture's environmental imprint. Emerging technologies such as geospatial technology, the Internet of Things (IoT), Big Data analysis, and artificial intelligence (AI) might be used to make more educated crop management decisions. The use of remote sensing technologies for PA has grown substantially over the last few decades. The unprecedented availability of high resolution (spatial, spectral, and temporal) satellite imagery has encouraged the use of remote sensing in a wide range of PA applications, including crop monitoring, irrigation control, fertilizer application, disease and pest management, and yield prediction. We present an overview of remote sensing systems, methodologies, and vegetation indices, as well as their recent (2015-2020) applications in PA in this study. Remote sensing-based PA technologies, such as variable fertilizer rate application technology in Green Seeker and Crop Circle, are already in use in commercial agriculture. Unmanned aerial vehicles (UAVs) have grown in popularity over the last decade due to their low cost and flexibility in acquiring high-resolution (cm-scale) photographs. At the same time, academics are investigating cutting-edge data storage and processing methods like cloud computing and machine learning due to the accessibility of a significant volume of satellite data. It is crucial to investigate and design an easy-to-use but dependable workflow for the real-time use of remote sensing in PA given the complexity of image processing and the quantity of technical knowledge and skill required. Wider usage of remote sensing technologies in commercial and non-commercial PA applications is anticipated to arise from the development of accurate yet simple-to-use, user-friendly systems.