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Remote Sensing Applications for Agriculture and Crop Modelling

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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,

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Keywords

  • ?13C
  • Á Trous algorithm
  • agricultural land-cover
  • AquaCrop
  • big data technology
  • canopy temperature depression
  • Climate Change
  • conservation agriculture
  • control variables
  • crop growth model
  • crop inventory
  • crop modeling
  • crop modelling
  • crop production
  • crop residue management
  • crop simulation model
  • crop type mapping
  • Cropsim-CERES Wheat
  • cultivars
  • Data assimilation
  • decision support system for agrotechnology transfer (DSSAT)
  • Disease
  • droplet drift
  • durum wheat
  • dynamic model
  • EPIC model
  • FAPAR
  • flat-fan atomizer
  • fractional cover
  • generalized model
  • Geography
  • GIS
  • grain yield
  • habitat assessment
  • hydroponic
  • hyperspectral data
  • hyperspectral sensor
  • Integrated Administration and Control System
  • Irrigation
  • Land use change
  • large cardamom
  • leaf area index
  • leaf nitrogen concentration
  • Machine learning
  • management zone
  • multi-spectral
  • n/a
  • NDVI
  • Nitrogen
  • nitrogen nutrition index
  • Plant
  • precision agriculture
  • Precision farming
  • prediction modeling
  • protein content
  • proximal sensing
  • relative frequencies
  • Remote sensing
  • RGB images
  • satellite
  • satellite images
  • Sentinel-2
  • Sentinel-2 satellite imagery
  • septoria tritici blotch
  • simulation analysis
  • Soil
  • soil organic carbon
  • soil stoichiometry
  • sorghum biomass
  • SPAD
  • spatial variability
  • species modelling
  • spectral simulation
  • spectral-weight variations in fused images
  • Tarim Basin
  • temporal variability
  • UAV
  • UAV chemical application
  • variable rate technology
  • vegetable monitoring
  • vegetation index
  • vegetation indices
  • wheat
  • yield
  • yield estimation
  • yield mapping
  • yield monitoring

Links

DOI: 10.3390/books978-3-03928-227-2

Editions

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