基于Landsat和Sentinel-2卫星图像的中分辨率动态生境指数

IF 8.7 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES Ecological Indicators Pub Date : 2025-04-01 Epub Date: 2025-03-18 DOI:10.1016/j.ecolind.2025.113367
Elena Razenkova , Katarzyna E. Lewińska , Akash Anand , He Yin , Laura S. Farwell , Anna M. Pidgeon , Patrick Hostert , Nicholas C. Coops , Volker C. Radeloff
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引用次数: 0

摘要

生物多样性科学需要有效的工具来预测物种多样性在多个时空尺度上的模式。动态生境指数(DHIs)是一种遥感指数,它以一种与生物多样性评估生态相关的方式总结了地上植被的生产力。现有的全球DHIs来源于1公里分辨率的MODIS,可以很好地预测大尺度上的物种丰富度,但与许多物种感知其栖息地的粒度相比,该分辨率是粗糙的。有了Sentinel-2和Landsat数据更精细的空间分辨率,再加上Landsat更长的数据记录,就有可能在更长的时间内以更精细的粒度跟踪植被的潜在变化及其对生物多样性的影响。在此,我们的主要目标是在美国连续的10 m Sentinel-2、30 m Landsat和250 m MODIS数据中获得DHIs,并在两个空间范围内比较所有DHIs,并评估这些DHIs预测25个国家生态观测站网络陆地站点鸟类物种丰富度的能力。此外,我们获得了1991-2000年的Landsat DHIs,并研究了它们在2011-2020年间的变化情况。我们发现Sentinel-2、Landsat和MODIS DHIs在生态区域汇总时高度相关(Spearman相关范围为0.89 ~ 0.99),表明它们之间具有良好的一致性,并且我们能够克服Sentinel-2和Landsat较低的时间分辨率。Sentinel-2和Landsat DHIs在模拟所有鸟类种群的物种丰富度方面优于MODIS,在线性回归模型中解释了高达49%的草地分支变异。此外,中分辨率DHIs (10-30 m分辨率)比MODIS DHIs更能捕获空间异质性。从1991-2000年到2011-2020年,Landsat DHIs发生了相当大的变化,例如西海岸、山脉和南部地区的累积DHI增加,但中西部地区的累积DHI降低。我们为美国周边地区新导出的DHIs在生物多样性科学和保护方面具有很大的应用潜力。
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Medium-resolution Dynamic Habitat Indices from Landsat and Sentinel-2 satellite imagery
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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来源期刊
Ecological Indicators
Ecological Indicators 环境科学-环境科学
CiteScore
11.80
自引率
8.70%
发文量
1163
审稿时长
78 days
期刊介绍: The ultimate aim of Ecological Indicators is to integrate the monitoring and assessment of ecological and environmental indicators with management practices. The journal provides a forum for the discussion of the applied scientific development and review of traditional indicator approaches as well as for theoretical, modelling and quantitative applications such as index development. Research into the following areas will be published. • All aspects of ecological and environmental indicators and indices. • New indicators, and new approaches and methods for indicator development, testing and use. • Development and modelling of indices, e.g. application of indicator suites across multiple scales and resources. • Analysis and research of resource, system- and scale-specific indicators. • Methods for integration of social and other valuation metrics for the production of scientifically rigorous and politically-relevant assessments using indicator-based monitoring and assessment programs. • How research indicators can be transformed into direct application for management purposes. • Broader assessment objectives and methods, e.g. biodiversity, biological integrity, and sustainability, through the use of indicators. • Resource-specific indicators such as landscape, agroecosystems, forests, wetlands, etc.
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