ORCID Profile
0000-0003-3038-9531
Current Organisation
University of Leipzig
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Springer Science and Business Media LLC
Date: 13-05-2021
DOI: 10.1038/S41559-021-01451-X
Abstract: Monitoring global bio ersity from space through remotely sensing geospatial patterns has high potential to add to our knowledge acquired by field observation. Although a framework of essential bio ersity variables (EBVs) is emerging for monitoring bio ersity, its poor alignment with remote sensing products hinders interpolation between field observations. This study compiles a comprehensive, prioritized list of remote sensing bio ersity products that can further improve the monitoring of geospatial bio ersity patterns, enhancing the EBV framework and its applicability. The ecosystem structure and ecosystem function EBV classes, which capture the biological effects of disturbance as well as habitat structure, are shown by an expert review process to be the most relevant, feasible, accurate and mature for direct monitoring of bio ersity from satellites. Bio ersity products that require satellite remote sensing of a finer resolution that is still under development are given lower priority (for ex le, for the EBV class species traits). Some EBVs are not directly measurable by remote sensing from space, specifically the EBV class genetic composition. Linking remote sensing products to EBVs will accelerate product generation, improving reporting on the state of bio ersity from local to global scales.
Publisher: Springer Science and Business Media LLC
Date: 25-10-2021
Publisher: Wiley
Date: 10-08-2017
DOI: 10.1002/RSE2.59
Publisher: Elsevier BV
Date: 10-2015
Publisher: Wiley
Date: 18-05-2012
Publisher: Wiley
Date: 08-2018
Abstract: Human activities exert stress on and create disturbances to ecosystems, decreasing their ersity, resilience and ultimately the health of ecosystems and their vegetation. In environments with rapid changes in vegetation health (VH), progress is needed when it comes to monitoring these changes and underlying causes. There are different approaches to monitoring VH such as in situ species approaches and the remote‐sensing approach. Here we provide an overview of in situ species approaches, that is, the biological, the phylogenetic, and the morphological species concept, as well as an overview of the remote‐sensing spectral trait/spectral trait variations concept to monitor the status of VH as well as processes of stress, disturbances, and resource limitations affecting VH. The approaches are compared with regard to their suitability for monitoring VH, and their advantages, disadvantages, potential, and requirements for being linked are discussed. No single approach is sufficient to monitor the complexity and multidimensionality of VH over the short to long term and on local to global scales. Rather, every approach has its pros and cons, making it all the more necessary to link approaches. In this paper, we present a framework and list crucial requirements for coupling approaches and integrating additional monitoring elements to form a multisource vegetation health monitoring network (MUSO‐VH‐MN). When it comes to linking the different approaches, data, information, models or platforms in a MUSO‐VH‐MN, big data with its complexity and syntactic and semantic heterogeneity and the lack of standardized approaches and VH protocols pose the greatest challenge. Therefore, Data Science with the elements of (a) digitalization, (b) semantification, (c) ontologization, (d) standardization, (e) Open Science, as well as (f) open and easy analyzing tools for assessing VH are important requirements for monitoring, linking, analyzing, and forecasting complex and multidimensional changes in VH.
Publisher: Springer Science and Business Media LLC
Date: 24-05-2021
Publisher: Springer Science and Business Media LLC
Date: 19-07-2021
Publisher: Wiley
Date: 06-2020
DOI: 10.1111/ECOG.04960
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Pedro J. Leitão.