Use of Multispectral Airborne Images to Improve In-Season Nitrogen Management, Predict Grain Yield and Estimate Economic Return of Maize in Irrigated High Yielding Environments.
Ángel MaresmaJaume LloverasJosé A. Martínez-CasasnovasPublished in: Remote. Sens. (2018)
Keyphrases
- multispectral
- remotely sensed
- image data
- satellite images
- multispectral images
- hyperspectral
- remote sensing
- image analysis
- multi band
- remotely sensed images
- hyperspectral images
- multispectral satellite images
- change detection
- hyperspectral data
- remote sensing images
- spectral bands
- high spatial resolution
- land cover
- spatial resolution
- remote sensing data
- infrared
- visible spectrum
- spectral characteristics
- multispectral imaging
- high resolution satellite images
- remote sensing imagery
- hyperspectral imagery
- satellite imagery
- machine learning
- water resources
- spectral images
- land cover classification
- illumination conditions
- segmentation algorithm
- image registration
- high resolution
- input image
- edge detection
- target detection
- image classification
- infrared images