Abstract
One of the key elements influencing crop production across the globe is abiotic stress. Early detection and corrective action in this regard can help to lessen the effects of stresses on crop growth and output. Recent advances in remote sensing hold a vital role in the early identification of abiotic stress across a broader area with less involvement of money, time, and labour. Remote sensing technology has become an indispensable tool in the field of agriculture, particularly for detecting abiotic stress in plants. This paper reviews the application of remote sensing techniques for the assessment of abiotic stress factors such as drought, flood, salinity, and nutrient deficiency. Furthermore, the review explores the critical aspects of data acquisition, processing, and analysis, underscoring the importance of machine learning and artificial intelligence techniques in enhancing the accuracy of stress detection.
Published Version
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