Medium-resolution Dynamic Habitat Indices from Landsat and Sentinel-2 satellite imagery

被引:0
|
作者
Razenkova, Elena [1 ]
Lewinska, Katarzyna E. [1 ,2 ]
Anand, Akash [1 ]
Yin, He [3 ]
Farwell, Laura S. [1 ,4 ]
Pidgeon, Anna M. [1 ]
Hostert, Patrick [2 ,5 ]
Coops, Nicholas C. [6 ]
Radeloff, Volker C. [1 ]
机构
[1] Univ Wisconsin Madison, Dept Forest & Wildlife Ecol, SILVIS Lab, 1630 Linden Dr, Madison, WI 53706 USA
[2] Humboldt Univ, Geog Dept, Unter Linden 6, D-10099 Berlin, Germany
[3] Kent State Univ, Dept Geog, 325 S Lincoln St, Kent, OH USA
[4] Pacific Birds Habitat Joint Venture, Portland, OR 97215 USA
[5] Humboldt Univ, Integrat Res Inst Transformat Human Environm Syst, Unter Linden 6, D-10099 Berlin, Germany
[6] Univ British Columbia, Dept Forest Resources Management, Integrated Remote Sensing Studio, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
关键词
Biodiversity; Productivity; Species distribution modeling; Global change; Grain; Scales; SPECIES RICHNESS; ECOLOGICAL APPLICATIONS; SPATIAL-PATTERNS; COVER CHANGE; ENERGY; MODIS; PRODUCTIVITY; PREDICTORS; NDVI; BIODIVERSITY;
D O I
10.1016/j.ecolind.2025.113367
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Biodiversity science requires effective tools to predict patterns of species diversity at multiple temporal and spatial scales. The Dynamic Habitat Indices (DHIs) are remotely sensed indices that summarize aboveground vegetation productivity in a way that is ecologically relevant for biodiversity assessments. Existing global DHIs, derived from MODIS at 1-km resolution, predict species richness at broad scales well, but that resolution is coarse relative to the grain at which many species perceive their habitat. With the much finer spatial resolution of Sentinel-2 and Landsat data, plus Landsat's longer data record, it is possible to track potential changes of vegetation and its impacts on biodiversity at a finer grain over longer periods. Here, our main goals were to derive the DHIs from 10-m Sentinel-2, 30-m Landsat, and 250-m MODIS data for the conterminous US and compare all DHIs at two spatial extents, and to evaluate the ability of these DHIs to predict bird species richness in 25 National Ecological Observatory Network terrestrial sites. In addition, we derived the Landsat DHIs for 1991-2000 and investigated how they changed by 2011-2020. We found that the Sentinel-2, Landsat, and MODIS DHIs were highly correlated when summarized by ecoregion (Spearman correlation ranging from 0.89 to 0.99), indicating good agreement between them and that we were able to overcome the lower temporal resolution of Sentinel-2 and Landsat. Sentinel-2 and Landsat DHIs outperformed MODIS in modeling species richness for all bird guilds, explaining up to 49% of variance of grassland affiliates in linear regression models. Furthermore medium-resolution DHIs (10-30 m resolution) captured spatial heterogeneity much better than MODIS DHIs. We observed considerable changes in Landsat DHIs from 1991-2000 to 2011-2020, such as increased cumulative DHI along the West Coast, in mountain ranges, and in the South, but lower cumulative DHI in the Midwest. Our newly derived DHIs for the conterminous US have great potential for use in biodiversity science and conservation.
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页数:14
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