Understanding the forest cover dynamics and its health status using GIS-based analytical hierarchy process

Correction: Miletić et al. Quantifying Forest Cover Loss as a Response to Drought and Dieback of Norway Spruce and Evaluating Sensitivity of Various Vegetation Indices Using Remote Sensing. Forests 2024, 15, 662

“…For example, Typical VIs are well known for assessing photosynthetic activity, forest health status, and detecting forest stressors such as pest outbreaks [43,51,55,[93][94][95][96]. On the other hand, Water VIs primarily provide a quantitative measure of water content in various tree species, early detection of water stress, and assessment of drought impacts on forested areas [48,51,52,57,[96][97][98][99]. Tasseled Cap (TC) transformation components are selected as they compress multispectral data into a few bands associated with physical scene characteristics with minimal information loss [100], thus sharing or having greater sensitivity in detecting various vegetation properties of both Typical VIs and Water VIs [42,101,102].…”

“…Regardless, the application of VIs has not demonstrated any significant use in forest-themed studies in Serbia. Past studies in Serbia have mainly focused on spatial and temporal forest cover mapping [57][58][59][60][61][62][63], mapping of illegal logging effects [64,65], and mapping of wildfire effects [66,67]. An exception is the research of Jovanović and Milanović [68], in which the health status of beech forests was evaluated using VIs, more precisely the NDVI.…”

“…To the following: By utilizing the spectral reflectance characteristics of plants, gathered via various imaging techniques, and combining reflectance from specific spectral wavelengths (bands) [53], VIs make the large-scale analysis of forest vegetation inexpensive and reliable. As proven by many studies [43,45,[54][55][56][57], VIs have also been found to be very sensitive in forecasting conifer health status, as they can signal drought stress and pest outbreaks, facilitating timely interventions in forest management and thus reducing the adverse effects of such disturbances. Therefore, the non-invasive approach and efficiency of VIs in forest health monitoring, which is made possible using high temporal frequency and spatially explicit satellite data, can provide insights into current and future forest health status over largescale forested areas.…”

“…Therefore, the non-invasive approach and efficiency of VIs in forest health monitoring, which is made possible using high temporal frequency and spatially explicit satellite data, can provide insights into current and future forest health status over largescale forested areas. For example, various VIs have been applied in forest health monitoring, and the most common ones are the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), the Transformed Vegetation Index (TVI), the Normalized Difference Moisture Index (NDMI), the Disease Water Stress Index (DSWI), Tasseled Cap Wetness (TCW), and Tasseled Cap Greenness (TCG) [38,39,[45][46][47][48]54,[57][58][59][60]. Despite their high accuracy, other conventional methods require constant, time-consuming, and cost-ineffective monitoring service, thus indicating the utter importance and innovativeness of remote sensing-produced VIs in monitoring forest health status over large-scale forested areas.…”

Determination of Logistics Distribution Centers: A Combination of Spatial Analysis and Analytical Hierarchy Process

“…When the CR value approaches zero, it indicates that the pairwise comparisons are highly consistent (an example of such a result is the calculation of the sub-criteria rainfall (CR = 0.000)). However, if the CR value is too high, it indicates that the calculations are inconsistent and a recalculation is necessary [67][68][69]. Fundamentally, the AHP method has advantages in terms of its usage.…”