Remote sensing for site selection in vegetation survey along a successional gradient in post-industrial vegetation.

ABSTRACT: Vegetation characteristics are an important proxy to measure the outcome of ecological restoration and monitor vegetation changes. Similarly, the classification of remotely sensed images is a prerequisite for many field ecological studies. We have a limited understanding of how the remote sensing approach can be utilized to classify spontaneous vegetation in post-industrial spoil heaps that dominate urban areas. We aimed to assess whether an objective a priori classification of vegetation using remotely sensed data allows for ecologically interpretable division. We hypothesized that remote sensing-based vegetation clusters will differ in alpha diversity, species, and functional composition; thereby providing ecologically interpretable division of study sites for further analyses. We acquir

SUBMITTER: Anibaba QA 

PROVIDER: S-EPMC11349488 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature