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Multivariate analysis of land surface dynamics in Central Asia: patterns of trends and drivers under a changing climate

Üreyen, Soner und Klein, Igor und Eisfelder, Christina und Künzer, Claudia (2024) Multivariate analysis of land surface dynamics in Central Asia: patterns of trends and drivers under a changing climate. GIScience and Remote Sensing, 61 (1), Seiten 1-24. Taylor & Francis. doi: 10.1080/15481603.2024.2364461. ISSN 1548-1603.

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Offizielle URL: https://www.tandfonline.com/doi/full/10.1080/15481603.2024.2364461?src=exp-la

Kurzfassung

With temperatures in Central Asia (CA) increasing more than the global average, this region is one of the global hotspots affected by climate change. CA is mostly characterized by arid climate, which is why available water resources are of paramount importance for the societies, economies, and the environment. In this regard, quantifying changes on the land surface and controlling factors that influence land surface dynamics are of great interest to improve our understanding of climate change impacts in this region. Hence, this study analyzes multivariate time series covering climatic, hydrological and Earth observation (EO)-based land surface variables. The used EO time series characterize the land surface and include data on the normalized difference vegetation index (NDVI), surface water area (SWA), and snow cover area (SCA) between December 2002 to November 2021. To analyze these time series, we employ trend analyses and a causal discovery algorithm. Both analyses were carried out at multiple spatial and temporal scales. The results show that NDVI trends were mostly significantly negative in the Northwest and positive in the Northeast of CA in summer. In summer and autumn, the percentage of significant negative NDVI trends outweighed the positive trends. For SWA, the detected trends were mostly significant negative throughout all scales. Significant negative trends were retrieved for SCA across all seasons, except for autumn regionally. Particularly the Tian Shan and Pamir mountains show significant declines of SCA in winter and spring. The causal analyses revealed that the NDVI is mostly controlled by water availability in summer. In spring and autumn, temperature is the leading driver on the NDVI. Likewise, temperature is found to largely control SWA in spring and autumn. SCA is mostly negatively coupled to temperature during spring and autumn. A positive coupling between SCA and precipitation is identified in winter.

elib-URL des Eintrags:https://elib.dlr.de/204770/
Dokumentart:Zeitschriftenbeitrag
Titel:Multivariate analysis of land surface dynamics in Central Asia: patterns of trends and drivers under a changing climate
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Üreyen, SonerSoner.Uereyen (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Klein, IgorIgor.Klein (at) dlr.dehttps://orcid.org/0000-0003-0113-8637NICHT SPEZIFIZIERT
Eisfelder, ChristinaChristina.Eisfelder (at) dlr.dehttps://orcid.org/0000-0002-6790-6953NICHT SPEZIFIZIERT
Künzer, ClaudiaClaudia.Kuenzer (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:13 Juni 2024
Erschienen in:GIScience and Remote Sensing
Referierte Publikation:Ja
Open Access:Ja
Gold Open Access:Ja
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:61
DOI:10.1080/15481603.2024.2364461
Seitenbereich:Seiten 1-24
Verlag:Taylor & Francis
ISSN:1548-1603
Status:veröffentlicht
Stichwörter:Multivariate time series; vegetation; surface water area; snow cover area; trends and causality
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Fernerkundung u. Geoforschung
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Deutsches Fernerkundungsdatenzentrum > Dynamik der Landoberfläche
Hinterlegt von: Üreyen, Soner
Hinterlegt am:22 Jul 2024 11:41
Letzte Änderung:22 Jul 2024 11:41

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