Kasampalis, DA, Alexandridis, TK, Deva, C et al. (3 more authors) (2018) Contribution of Remote Sensing on Crop Models: A Review. Journal of Imaging, 4 (4). 52. ISSN 2313-433X
Abstract
Crop 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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license http://creativecommons.org/licenses/by/4.0/). |
Keywords: | crop models; earth observation; fusion; yield production; crop yield; vegetarian indices; spatio-temporal scale |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds) |
Funding Information: | Funder Grant number EU - European Union 774652 |
Depositing User: | Symplectic Publications |
Date Deposited: | 13 Apr 2018 09:26 |
Last Modified: | 16 Apr 2018 07:32 |
Status: | Published |
Publisher: | MDPI |
Identification Number: | 10.3390/jimaging4040052 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:129580 |