Contribution of Remote Sensing on Crop Models: A Review
AbstractCrop growth models simulate the relationship between plants and the environment to predict the expected yield for applications such as crop management and agronomic decision making, as well as to study the potential impacts of climate change on food security. A major limitation of crop growth models is the lack of spatial information on the actual conditions of each field or region. Remote sensing can provide the missing spatial information required by crop models for improved yield prediction. This paper reviews the most recent information about remote sensing data and their contribution to crop growth models. It reviews the main types, applications, limitations and advantages of remote sensing data and crop models. It examines the main methods by which remote sensing data and crop growth models can be combined. As the spatial resolution of most remote sensing data varies from sub-meter to 1 km, the issue of selecting the appropriate scale is examined in conjunction with their temporal resolution. The expected future trends are discussed, considering the new and planned remote sensing platforms, emergent applications of crop models and their expected improvement to incorporate automatically the increasingly available remotely sensed products. View Full-Text
Share & Cite This Article
Kasampalis, D.A.; Alexandridis, T.K.; Deva, C.; Challinor, A.; Moshou, D.; Zalidis, G. Contribution of Remote Sensing on Crop Models: A Review. J. Imaging 2018, 4, 52.
Kasampalis DA, Alexandridis TK, Deva C, Challinor A, Moshou D, Zalidis G. Contribution of Remote Sensing on Crop Models: A Review. Journal of Imaging. 2018; 4(4):52.Chicago/Turabian Style
Kasampalis, Dimitrios A.; Alexandridis, Thomas K.; Deva, Chetan; Challinor, Andrew; Moshou, Dimitrios; Zalidis, Georgios. 2018. "Contribution of Remote Sensing on Crop Models: A Review." J. Imaging 4, no. 4: 52.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.