Journal
ECOGRAPHY
Volume 44, Issue 3, Pages 414-426Publisher
WILEY
DOI: 10.1111/ecog.05266
Keywords
biodiversity indices; data management; hyperspectral; LiDAR; spectral indices; structural indices
Categories
Funding
- DFG Priority Program 1374 'Infrastructure-Biodiversity-Exploratories' [NA 783/6-2]
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Monitoring biodiversity and its changes over space and time is a key challenge for ecological research. Remote sensing data has been proven to be a powerful complement to field work, and the RSDB serves as an integrative solution for storing and processing various types of remote sensing data, providing over 200 biodiversity-related indices for ecological studies.
Monitoring biodiversity and its change over space and time is a key challenge for ecological research. Utilizing remote sensing data in ecological research has been shown to be a powerful complement to labor-intensive field work to derive area-wide biodiversity indices, which can also capture larger spatiotemporal areas. However, preprocessing different types of remote sensing data for specific studies often requires extensive computational skills as the algorithms for creating final data products are scattered across the literature. Our remote sensing database (RSDB, <>) serves as an integrative storage, management and processing solution for several types of remote sensing data. Transparent data processing capabilities for more than 200 biodiversity-related indices are included and can be used to calculate ready-to-use data products for a variety of ecological studies. These data products, for example, leaf area, vertical distribution of biomass and foliage height derived from light detection and ranging (LiDAR) point clouds, are individually calculated for user-specified study areas and can serve as proxies for ecological variables, such as the availability of resources or habitat heterogeneity. The primary RSDB user interface is web browser based on management, exploration, visualization and product processing capabilities. The RSDB stores data in layers that are discoverable by textual metadata and mapping on overview maps. Individual data layers can be explored using interactive maps and 3-D visualizations. We additionally provide a seamless connection of the RSDB's functionality with the R environment through our accompanying R package for scripting and advanced processing tasks. We designed the RSDB to be an easily accessible solution for on-demand processing of comprehensive biodiversity indices. To date, the RSDB has been used and tested in several studies, and we are convinced that it will continue to facilitate biodiversity monitoring via its application to ecological research.
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