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Case study of remote sensing in agriculture

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Case study of remote sensing in agriculture
Case study of remote sensing in agriculture
Case study of remote sensing in agriculture
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This article presents the use of the Normalized Differences Vegetation Index NDVI time series based change detection method for agriculture phenology monitoring. Geographic Information System GIS technology is becoming an essential tool to combing multiple maps and information from different sources as satellite, field and socio-economic data. This research work was the procedure by pre-processing, signal filtering and interpolation of monthly NDVI time series that represent a complete crop phonological cycle. We divided whole agriculture area into five part according to NDVI Values such as no agriculture, low agriculture, medium agriculture, high agriculture and very high agriculture area. The simulation results show that the NDVI is highly useful in detecting the surface feature of the area, which is extremely beneficial for sustainable development of agriculture and decision making.
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A Case Study of Using Remote Sensing Data and GIS for Land Management; Catalca Region

Over the past decade, the number of Earth observation satellites increased by several orders of magnitude and the spectral and spatial resolution of data they collect improved. Multispectral remote sensing technology is widely used in agriculture and is appropriate for vegetation analysis Polder and van der Heijden ; Sabins Vegetation has characteristic spectra, often showing characteristic absorption maxima or minima at particular wavelengths. Most vegetation indices are based on the sharp increase in reflectance from vegetation that occurs around nm the red-edge , a change that is characteristic of green vegetation and not found for most other natural surfaces that show relatively slow changes of reflectance with wavelength over this region Jones and Vaughan
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To browse Academia. Skip to main content. Log In Sign Up. Download Free PDF. Remote Sensing in Agriculture.
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