The Recent Applications of Remote sensing in Agriculture-A Review

Remote sensing is becoming a crucial technology in current agricultural practices, with several uses and benefits for farmers, researchers and policymakers. Crop monitoring and management are the principal applications of remote sensing in agriculture. Remote sensing allows for the rapid and precise diagnosis of crop health, growth and yield estimation by evaluating data received from satellites or airborne platforms. This data assists farmers in optimising irrigation, fertilization, pest and disease control measures, resulting in better resource allocation, enhanced productivity and lower environmental consequences. The identification and mapping of crop diseases and pests is a key application. Remote sensing may detect minute differences in plant physiology, such as chlorophyll content changes, which may signal the presence of diseases or pest infestations. Initial identification allows for focused treatments such as precision pesticide application, disease avoidance and crop loss reduction. Precision agriculture relies heavily on remote sensing. Farmers may produce precise field maps that delineate differences in soil qualities, nutrient levels, and moisture content by integrating satellite photography, GPS navigation systems and computer algorithms. This data enables site-specific management, allowing farmers to deploy resources precisely where they are required, optimising inputs, lowering costs and minimising environmental consequences. Remote sensing makes land-use planning and monitoring easier. It can assist in identifying potential agricultural sites, assessing land degradation and tracking changes in land cover and land use trends over time. Policymakers can use this data to make informed decisions about land management, sustainable agriculture practices and conservation activities. It helps with agricultural water resource management. It is feasible to monitor water availability, assess irrigation demands and identify locations vulnerable to drought or water stress by studying satellite data. This information allows for more efficient water distribution, reducing water waste and improving water-use efficiency in agricultural activities. Remote sensing has numerous uses in agriculture, revolutionizing old farming practices. Keywords: Artificial intelligence, precision agriculture, remote sensing, satellites, spectral reflectance, sustainability