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were, to follow up, control and foil any conspiracy by external or internal dissidents against the military and governmental institutions. On top of that, surveying the over all counter offensive movements be it public or military and curbing such activities is also...
NY (Iverson et al. unpublished data). In 2016 and 2017, Iverson et al. documented plant species richness and abundance at 144 sites across the most common habitat types (N = 22) in the surveyed region that span across the broader classes of forest, agriculture...
The water streams were grouped into 5 classes by equal intervals and then scored within a MEDALUS framework classification as the following: from 0.3 to 2.5 the assigned value with the assigned value of 2.0; from 2.5 to 4.7 with the assigned value of 1.6; from 4.7 to 6.9 with the assigned...
(Kelly and Holub2008; Meek et al.2019). The theft of camera traps not only results in data loss but limits the financial viability of surveying wildlife in urban areas. We took some precautionary measures including using camouflage to hide cameras, placing cameras off-trail and below eye-...
The low area of wetlands in 1987 and the high conversion rate of wetlands into other LULC classes could be explained by the fact that heavy crown cover hides wetlands in the satellite images. Baker et al. [79] argued that Landsat imagery is often unable to distinguish between a feature’s...
Reflectance values corresponding to the various land use/cover classes were used to create their respective spectral signatures which were then used to perform the classification. The land cover categories are: closed forest, open forest, small-scale agriculture, mechanized (large scale) agriculture, ...
(e.g., the summer near-infrared (NIR-S) band), topographic factors (e.g., the digital elevation model (DEM)), and spectral indices (e.g., the summer resident ratio index (RRI-S)) significantly contribute to the accuracy of each ensemble learning classifier. Using feature-optimized ...
As shown in Figure 4, the natural breakpoint method classifies X, Y and Z into four classes (lowest, lower, higher and highest, corresponding to the numbers 1, 2, 3 and 4). The higher value indicates a higher risk to the cultivated land. To enhance homogeneity and reduce intra-group ...
The data-related geographic can be divided into many classes, according to their sources and format, such as raster dataset, shape file, textual information, and voice [1]. Locality description, which is a common form of voice, conveys considerable spatial information and can be derived from ...