Indoor plants were observed over a period of 18 days and stressed due to a lack of sunlight or water. Wild sedge photographed on the forest floor at close range and with a difficult capture setup produced results comparable to published ...
1.3 Spectral Signatures The spatial resolution of satellite remote-sensing systems is too low to identify many objects by their shape or spatial detail. In some cases, it is possible to identify such objects by spectral measurements. There has, therefore, been great interest in measuring the spect...
Our primary research objective was to compare spectral recovery metrics to field measurements of post-fire vegetation dynamics in mixed conifer forests burned at a high severity in the Blue Mountains, USA. We conducted top-down (spectral recovery metrics as input variables) and bottom-up (field me...
To many, green signifies nature – plants, trees, and forests. It’s the same in remote sensing. The green portion covers the reflectance peak from leaf surfaces (hence the color green that we see). This also means the spectral reflectance is low in the blue and red regions of the spect...
Spectral Signatures of Photosynthesis. Ⅰ. Review of Earth Organisms Why do plants reflect in the green and have a "red edge" in the red, and should extrasolar photosynthesis be the same? We provide (1) a brief review of how... NANCY Y. KIANG,JANET SIEFERT,GOVINDJEE,... - 《Astrobiolo...
The measured above-surface spectra demonstrated typical spectral signatures of complex turbid coastal water, with two peaks within green and red bands and relatively high reflectance within red and near-infrared bands. Due to the high concentrations of the riverine discharged TSM, remote sensing ...
Spectral signature transform based approach: In this approach we consider the methods that apply some mathematical transformation on the original target spectral signature to develop an elaborated set of target signatures [83], [120], [84], [85]. • Spectral signature variant based approach: In...
spectral signatures give some insights into different surface processes, e.g., vegetation states9, urban expansion5,10, fires, and burned areas11,12. However, often one has to combine specific spectral regions of interest (i.e., spectral bands) in order to reduce unwanted (i.e., confounding...
Spectral signatures of healthy and diseased grapevine leaves were measured with a non-imaging spectro-radiometer at two infection severity levels. The most discriminating wavelengths were selected by a genetic algorithm (GA) feature selection tool, the Spectral Disease Indices (SDIs) are designed by ...
As discussed inSection 2.2, for image processing,spectral features, especially color indices, are valuable and effective for vegetation segmentation. For plants with different leaf colors, spectral features are effective for discrimination between them. But for plants with similar color, spectral features...