TY  - BOOK
AU  - Toscano, Piero
AB  - 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,
DO  - 10.3390/books978-3-03928-227-2
ID  - OAPEN ID: 44748
KW  - nitrogen nutrition index
KW  - n/a
KW  - soil organic carbon
KW  - yield estimation
KW  - hyperspectral sensor
KW  - crop modeling
KW  - crop residue management
KW  - land use change
KW  - flat-fan atomizer
KW  - vegetation index
KW  - septoria tritici blotch
KW  - crop simulation model
KW  - temporal variability
KW  - spectral-weight variations in fused images
KW  - plant
KW  - EPIC model
KW  - large cardamom
KW  - crop inventory
KW  - proximal sensing
KW  - sorghum biomass
KW  - soil
KW  - UAV
KW  - Integrated Administration and Control System
KW  - canopy temperature depression
KW  - fractional cover
KW  - Cropsim-CERES Wheat
KW  - hyperspectral data
KW  - yield
KW  - wheat
KW  - precision farming
KW  - SPAD
KW  - AquaCrop
KW  - prediction modeling
KW  - spectral simulation
KW  - leaf nitrogen concentration
KW  - machine learning
KW  - crop production
KW  - protein content
KW  - Á Trous algorithm
KW  - spatial variability
KW  - variable rate technology
KW  - crop type mapping
KW  - Tarim Basin
KW  - leaf area index
KW  - management zone
KW  - irrigation
KW  - multi-spectral
KW  - agricultural land-cover
KW  - crop modelling
KW  - dynamic model
KW  - satellite images
KW  - climate change
KW  - control variables
KW  - generalized model
KW  - Sentinel-2 satellite imagery
KW  - vegetation indices
KW  - vegetable monitoring
KW  - Sentinel-2
KW  - remote sensing
KW  - cultivars
KW  - crop growth model
KW  - yield monitoring
KW  - big data technology
KW  - conservation agriculture
KW  - GIS
KW  - fAPAR
KW  - droplet drift
KW  - simulation analysis
KW  - durum wheat
KW  - hydroponic
KW  - grain yield
KW  - Leaf Area Index
KW  - NDVI
KW  - precision agriculture
KW  - relative frequencies
KW  - soil stoichiometry
KW  - habitat assessment
KW  - data assimilation
KW  - satellite
KW  - species modelling
KW  - ?13C
KW  - disease
KW  - nitrogen
KW  - yield mapping
KW  - UAV chemical application
KW  - RGB images
KW  - decision support system for agrotechnology transfer (DSSAT)
L1  - https://mdpi.com/books/pdfview/book/2023
LA  - English
LK  - https://directory.doabooks.org/handle/20.500.12854/58167
PB  - MDPI - Multidisciplinary Digital Publishing Institute
PY  - 2020
SN  - 9783039282265
SN  - 9783039282272
TI  - Remote Sensing Applications for Agriculture and Crop Modellingnull
ER  - 
