(untitled) (International Association of Biologicals and Computational Digest, 2023)
Agriculture plays a central role in safeguarding the region’s food supply and achieving the second UN Sustainable Development Goal of zero hunger by 2030. However, the agriculture sector faces challenges from changing consumer demand, demographics, inefficient value chains, climate change and water shortage. Climate change is already impacting significantly on agriculture and food production in developing countries. Agriculture has been able to keep up with the rising demand for food and other agricultural goods because of the development of new farming techniques throughout the previous century. Natural resources will undoubtedly be further stressed as result of rising food demand, population growth, income levels, etc. New methods and approaches should be able to meet future food demands while maintaining or lowering agriculture’s environmental imprint as the detrimental effects of agriculture on the environment become more widely acknowledged. The application of remote sensing in agriculture can aid the evolution of agricultural practices that face different types of challenges by providing information related to crop status at different scales all through the season. Making educated management decisions with the help of emerging technologies including geospatial technology, the Internet of Things (IoT), Big Data analysis, and artificial intelligence (AI). To maximize agricultural inputs, boot agricultural production, and decrease input losses, precision agriculture (PA) uses a variety of such technologies. Over the past few decades, there has been a sharp expansion in the use of remote sensing technology for PA (precision agriculture). It is crucial to investigate and design an easy-to-use yet dependable workflow for the real-time use of remote sensing in PA (precision agriculture) 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 (precision agriculture) applications is likely to result from the development of accurate yet simple-to-use, user-friendly systems.