Integrated Use of Satellite Remote Sensing, Artificial Neural Networks, Field Spectroscopy, and GIS in Estimating Crucial Soil Parameters in Terms of Soil Erosion.
Dimitrios D. AlexakisEvdokia TapoglouAnthi-Eirini K. VozinakiIoannis K. TsanisPublished in: Remote. Sens. (2019)
Keyphrases
- remote sensing
- soil erosion
- landsat tm
- artificial neural networks
- change detection
- remote sensing image processing
- multispectral
- digital image analysis
- remote sensing images
- natural environment
- image analysis
- remote sensing imagery
- satellite images
- high resolution
- image processing
- spectral data
- satellite imagery
- high spatial resolution
- hyperspectral
- remotely sensed
- environmental sciences
- geographical information systems
- remote sensing data
- qualitative evaluation
- image fusion
- satellite data
- land cover
- multi spectral images
- remotely sensed images
- earth observation
- remotely sensed data
- automatic image registration
- infrared
- neural network
- remote sensed images
- multispectral images
- hyperspectral data
- hyperspectral imagery
- hyperspectral images
- pattern recognition
- high quality