Can weed distribution maps be developed from remote sensed reflectance data? When are the appropriate times to collect these data during the season? What wavebands can be used to distinguish weedy from weed- free areas? This research examined if and when reflectance could be used to distinguish between weed-free and weed-infested (mixed species) areas in soybean and to determine the most useful wavebands to separate crop, weed, and soil reflectance differences. Treatments in the two-year study included no vegetation (bare soil), weed-free soybean, and weed-infested soybean and, in one year, 80% corn residue cover. Reflectance was measured at several sampling times from May through September in 2001 and 2002 using a hand-held multispectral r...
Crop disease detection with remote sensing is a challenging area that can have significant economic ...
Graduation date: 1983Spectral patterns of three brush species under the influence of herbicide treat...
161 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2000.Unsupervised clustering of co...
Weed distribution maps can be developed from remotely sensed reflectance data if collected at approp...
Remote sensing may provide the information required to identify weed management zones. The objective...
In this article, the potential of multi-spectral airborne remote sensing is evaluated for the detect...
This paper analyses the potential and limitations of airborne remote sensing systems for detecting c...
Field studies were conducted in 2016 and 2017 to determine if multispectral imagery collected from a...
This study investigated the possibility of using data, acquired from airborne multi-spectral or hyp...
MSc. (Geography)Growing concerns with regards to the environmental and economic impacts related to t...
Weed species occur in non-uniform Patches across agricultural fields with the amount of patchiness d...
Wheat, Triticum durum L, is a major cereal crop in Spain with over five million ha grown a...
Weed control is commonly performed by applying selective herbicides homogeneously over entire agricu...
This paper analyses the potential and limitations of airborne remote sensing systems for detecting c...
Among the poorly studied factors affecting the spectral reflectivity of crops and, consequently, the...
Crop disease detection with remote sensing is a challenging area that can have significant economic ...
Graduation date: 1983Spectral patterns of three brush species under the influence of herbicide treat...
161 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2000.Unsupervised clustering of co...
Weed distribution maps can be developed from remotely sensed reflectance data if collected at approp...
Remote sensing may provide the information required to identify weed management zones. The objective...
In this article, the potential of multi-spectral airborne remote sensing is evaluated for the detect...
This paper analyses the potential and limitations of airborne remote sensing systems for detecting c...
Field studies were conducted in 2016 and 2017 to determine if multispectral imagery collected from a...
This study investigated the possibility of using data, acquired from airborne multi-spectral or hyp...
MSc. (Geography)Growing concerns with regards to the environmental and economic impacts related to t...
Weed species occur in non-uniform Patches across agricultural fields with the amount of patchiness d...
Wheat, Triticum durum L, is a major cereal crop in Spain with over five million ha grown a...
Weed control is commonly performed by applying selective herbicides homogeneously over entire agricu...
This paper analyses the potential and limitations of airborne remote sensing systems for detecting c...
Among the poorly studied factors affecting the spectral reflectivity of crops and, consequently, the...
Crop disease detection with remote sensing is a challenging area that can have significant economic ...
Graduation date: 1983Spectral patterns of three brush species under the influence of herbicide treat...
161 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2000.Unsupervised clustering of co...