Remote Sensing Applications for Agriculture and Crop Modelling

Remote Sensing Applications for Agriculture and Crop Modelling
Author :
Publisher : MDPI
Total Pages : 308
Release :
ISBN-10 : 9783039282265
ISBN-13 : 3039282263
Rating : 4/5 (65 Downloads)

Book Synopsis Remote Sensing Applications for Agriculture and Crop Modelling by : Piero Toscano

Download or read book Remote Sensing Applications for Agriculture and Crop Modelling written by Piero Toscano and published by MDPI. This book was released on 2020-02-13 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Crop models and remote sensing techniques have been combined and applied in agriculture and crop estimation on local and regional scales, or worldwide, based on the simultaneous development of crop models and remote sensing. The literature shows that many new remote sensing sensors and valuable methods have been developed for the retrieval of canopy state variables and soil properties from remote sensing data for assimilating the retrieved variables into crop models. At the same time, remote sensing has been used in a staggering number of applications for agriculture. This book sets the context for remote sensing and modelling for agricultural systems as a mean to minimize the environmental impact, while increasing production and productivity. The eighteen papers published in this Special Issue, although not representative of all the work carried out in the field of Remote Sensing for agriculture and crop modeling, provide insight into the diversity and the complexity of developments of RS applications in agriculture. Five thematic focuses have emerged from the published papers: yield estimation, land cover mapping, soil nutrient balance, time-specific management zone delineation and the use of UAV as agricultural aerial sprayers. All contributions exploited the use of remote sensing data from different platforms (UAV, Sentinel, Landsat, QuickBird, CBERS, MODIS, WorldView), their assimilation into crop models (DSSAT, AQUACROP, EPIC, DELPHI) or on the synergy of Remote Sensing and modeling, applied to cardamom, wheat, tomato, sorghum, rice, sugarcane and olive. The intended audience is researchers and postgraduate students, as well as those outside academia in policy and practice.


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