Modeling the spatial distribution of above-ground carbon in Mexican coniferous forests using remote sensing and a geostatistical approach.
Jose Mauricio Galeana-PizañaAlejandra López-CalocaPenélope López-QuirozJosé Luis Silván-CárdenasStephane CouturierPublished in: Int. J. Appl. Earth Obs. Geoinformation (2014)
Keyphrases
- remote sensing
- spatial distribution
- land cover
- spatial autocorrelation
- change detection
- multispectral
- spatial information
- remote sensing images
- satellite images
- image analysis
- image fusion
- high resolution
- hyperspectral
- image processing
- remote sensing data
- earth observation
- remote sensing imagery
- weather prediction
- automatic image registration
- satellite imagery
- spatial distance
- satellite data
- remotely sensed
- multi spectral images
- high spatial resolution
- remotely sensed imagery
- hyperspectral imaging
- digital image analysis
- remotely sensed images
- hyperspectral remote sensing
- climate change
- remotely sensed data
- earth science
- geographical information systems
- remote sensed images
- feature extraction
- hyperspectral images
- grain size
- computer vision
- hyperspectral imagery