Emerging hot spot analysis to indicate forest conservation priorities and efficacy on regional to continental scales: a study of forest change in Selva Maya 2000–2020

Abstract

Despite the importance of preserving contiguous tropical forest areas to maintain biodiversity and terrestrial carbon stocks, methodological challenges continue to hinder broad-scale analysis of threats to these forests. Emerging Hot Spot Analysis (EHSA) is a spatial-statistical method that conveys complex information about the temporal dynamics of deforestation across a range of moderate to coarse spatial scales. Using Global Forest Change (GFC) data as inputs, EHSA produces spatially comprehensive, gridded outputs that represent a standardized, reproduceable way to instantiate contiguous forest tracts as spatial objects. Doing so allows aggregation of other GFC-derived values and analysis of alternative geographic configurations besides sub-national jurisdictions or protected areas, which can limit observation of finer scale variations. This paper illustrates the method’s utility to comprehensively characterize the magnitude and temporality of pressures facing the Selva Maya, a transboundary forest region with extensive areas under conservation that covers portions of Mexico, Guatemala, and Belize.

Spatio temporal variation of urban multi-scale carbon emissions and its influencing factors based on night light data:-A case study of Pearl River Delta urban agglomeration

“…Then, Mann-Kendall was used to evaluate time series changes of Getis-Ord Gi* at each location to calculate Z-score. At the end, 17 models including 8 hot spot, 8 cold spot, and non-signi cant models were formed [32]. This analysi s can sensitively identify the spatiotemporal variations of hot or cold spots and supplement Moran's I index in spatio-temporal terms [33].…”

Spatio-Temporal Dynamics and Driving Forces of Multi-Scale Emissions Based on Nighttime Light Data: A Case Study of the Pearl River Delta Urban Agglomeration

“…Then, the Mann-Kendall test was used to evaluate time-series changes in Getis-Ord Gi* at each location to calculate the Z-score. At the end, 17 models including 8 hot-spot, 8 cold-spot, and non-significant models were formed [49]. This analysis can sensitively identify the spatio-temporal variations of hot or cold spots and supplement Moran's I index in spatio-temporal terms [50].…”

A Conceptual Framework for Modeling Spatiotemporal Dynamics of Diesel Attenuation Capacity: A Case Study across Namyangju, South Korea

“…The emerging hot spot analysis (EHSA) tool in ArcGIS, developed by ESRI, provided a robust statistical assessment that simultaneously gives back the spatial and temporal hot and cold spot trend [15]. Even though EHSA has been applied in disease outbreaks [16,17], accident occurrence [18], flooding and drought [19][20][21], forest loss [22], and conservation monitoring [23,24], its application in soil vulnerability especially on vadose zone AC has not been recorded. Therefore, incorporating EHSA into the vulnerability study will provide a new way to assess and understand the dynamics of soil SD, AC, or other general vulnerability assessments.…”