Crop yield estimation using different remote sensing data: literature review

Abstract

The climatic conditions and many other environmental factors have an impact on the crop growth stage and then on crop yield. The evaluation of seasonal crop production requires simultaneously monitoring crop yield conditions and early evaluation of significantly reduced production caused by unexpected disasters. Early detection of stunted crop growth can help prevent a disaster or help plan to prevent its occurrence or spread. On the other side, Farmlands cover a wide area of the planet’s surface, so the use of advanced technologies (for example, remote sensing) is very important to minimize the cost of monitoring, and eliminate the wasting of natural resources. Nowadays, the different satellite types such as Landsat, Sentinel, MODIS, and, Spot lead to variations in remote sensing data in spatial, temporal, radiometric, and spectral resolution. This is done to obtain many indices to utilize in crop management and the environmental effect. This review paper presents many studies to clarify three main tasks. Firstly, present the importance of using different types of remote sensing data depending on the reason for use. Secondly, the most famous indices have been used in many studies for different purposes to obtain accurate crop management, such as Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST). Lastly, conclude the review by presenting the potential of the various remote sensing data and the importance of many indices that are helpful for crop and environmental factors monitoring.