The capability of ERS-1 SAR precision data to discriminate between crop types for land cover inventory purposes at the earliest stage in the growing season was assessed using a field-based classification. The objectives were tested for an agriculturalregion in the Netherlands, where twelve crop types are found. Fourteen ERS-1 SAR images were available for this area, covering the 1992 growing season (May to November). The field-based classification yielded an overall classification accuracy of 80% with the optimal data set. The stage at which the crop types could be assessed depended on the crop. Cereals could be discriminated in May, potatoes and rape-seed in May and June
Methods based on Sentinel-1 data were developed to monitor crops and fields to facilitate the distri...
Multitemporal X- and C-band E-SAR data from 8 dates and three ERS-1 images between May 20 and July 3...
Classification of crops and other land cover types is an important application of both optical/infra...
A possible output of the European project ReSeDA is to use the very complete available data base cov...
The current paper investigates the potential contribution of ENVISAT wide swath (WS) images for disc...
This paper assessed the use of optical and SAR imagery for crop identification in an operational con...
International audienceMore and more remote sensing data corresponding to various wavelength domains ...
Multitemporal E-SAR CVV 95 dates) and ERS-1 images (3 dates) between May 20 and July 14, 1992 were i...
Timely availability of crop acreage estimation is crucial for maintaining economic and ecological su...
Reliable early-season crop classification provides necessary input for storage planning, logistics o...
Accurate crop type maps are vital for agricultural monitoring and sustainable land management. When...
Multi-temporal classification of agricultural crops using Sentinel-1 Abstract This diploma thesis ai...
This study integrated multi-temporal, multispectral optical and L-band synthetic aperture radar (SAR...
High temporal and spatial resolution optical image time series have been proven efficient for crop t...
This paper reports on an investigation aimed at evaluating the performance of a neural-network based...
Methods based on Sentinel-1 data were developed to monitor crops and fields to facilitate the distri...
Multitemporal X- and C-band E-SAR data from 8 dates and three ERS-1 images between May 20 and July 3...
Classification of crops and other land cover types is an important application of both optical/infra...
A possible output of the European project ReSeDA is to use the very complete available data base cov...
The current paper investigates the potential contribution of ENVISAT wide swath (WS) images for disc...
This paper assessed the use of optical and SAR imagery for crop identification in an operational con...
International audienceMore and more remote sensing data corresponding to various wavelength domains ...
Multitemporal E-SAR CVV 95 dates) and ERS-1 images (3 dates) between May 20 and July 14, 1992 were i...
Timely availability of crop acreage estimation is crucial for maintaining economic and ecological su...
Reliable early-season crop classification provides necessary input for storage planning, logistics o...
Accurate crop type maps are vital for agricultural monitoring and sustainable land management. When...
Multi-temporal classification of agricultural crops using Sentinel-1 Abstract This diploma thesis ai...
This study integrated multi-temporal, multispectral optical and L-band synthetic aperture radar (SAR...
High temporal and spatial resolution optical image time series have been proven efficient for crop t...
This paper reports on an investigation aimed at evaluating the performance of a neural-network based...
Methods based on Sentinel-1 data were developed to monitor crops and fields to facilitate the distri...
Multitemporal X- and C-band E-SAR data from 8 dates and three ERS-1 images between May 20 and July 3...
Classification of crops and other land cover types is an important application of both optical/infra...