Changes in the grasslands of the Caucasus based on Cumulative Endmember Fractions from the full 1987–2019 Landsat record

Grasslands are important for global biodiversity, food security, and climate change analyses, which makes mapping and monitoring of vegetation changes in grasslands necessary to better understand, sustainably manage, and protect these ecosystems. However, grassland vegetation monitoring at spatial a...

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Autores principales:	Katarzyna Ewa Lewińska, Johanna Buchner, Benjamin Bleyhl, Patrick Hostert, He Yin, Tobias Kuemmerle, Volker C. Radeloff
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Time series analysis Rangelands Spectral mixture analysis (SMA) LandTrendr Degradation Google earth engine Physical geography GB3-5030 Science Q
Acceso en línea:	https://doaj.org/article/2d193dccf5434ba5bb1f33abac9ab5be
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spelling	oai:doaj.org-article:2d193dccf5434ba5bb1f33abac9ab5be2021-11-14T04:35:34ZChanges in the grasslands of the Caucasus based on Cumulative Endmember Fractions from the full 1987–2019 Landsat record2666-017210.1016/j.srs.2021.100035https://doaj.org/article/2d193dccf5434ba5bb1f33abac9ab5be2021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666017221000225https://doaj.org/toc/2666-0172Grasslands are important for global biodiversity, food security, and climate change analyses, which makes mapping and monitoring of vegetation changes in grasslands necessary to better understand, sustainably manage, and protect these ecosystems. However, grassland vegetation monitoring at spatial and temporal resolution relevant to land management (e.g., ca. 30-m, and at least annually over long time periods) is challenging due to complex spatio-temporal pattern of changes and often limited data availability. Here we assess both short- and long-term changes in grassland vegetation cover from 1987 to 2019 across the Caucasus ecoregion at 30-m resolution based on Cumulative Endmember Fractions (i.e., annual sums of monthly ground cover fractions) derived from the full Landsat record, and temporal segmentation with LandTrendr. Our approach combines the benefits of physically-based analyses, missing data prediction, annual aggregations, and adaptive identification of changes in the time-series. We analyzed changes in vegetation fraction cover to infer the location, timing, and magnitude of vegetation change episodes of any length, quantified shifts among all ground cover fractions (i.e., green vegetation, non-photosynthetic vegetation, soil, and shade), and identified change pathways (i.e., green vegetation loss, desiccation, dry vegetation loss, revegetation green fraction, greening, or revegetation dry fraction). We found widespread long-term positive changes in grassland vegetation (32.7% of grasslands), especially in the early 2000s, but negative changes pathways were most common before the year 2000. We found little association between changes in green vegetation and meteorological conditions, and varied relationships with livestock populations. However, we also found strong spatial heterogeneity in vegetation dynamics among neighboring fields and pastures, demonstrating capability of our approach for grassland management at local levels. Our results provide a detailed assessment of grassland vegetation change in the Caucasus Ecoregion, and present an approach to map changes in grasslands even where availability of Landsat data is limited.Katarzyna Ewa LewińskaJohanna BuchnerBenjamin BleyhlPatrick HostertHe YinTobias KuemmerleVolker C. RadeloffElsevierarticleTime series analysisRangelandsSpectral mixture analysis (SMA)LandTrendrDegradationGoogle earth enginePhysical geographyGB3-5030ScienceQENScience of Remote Sensing, Vol 4, Iss , Pp 100035- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Time series analysis Rangelands Spectral mixture analysis (SMA) LandTrendr Degradation Google earth engine Physical geography GB3-5030 Science Q
spellingShingle	Time series analysis Rangelands Spectral mixture analysis (SMA) LandTrendr Degradation Google earth engine Physical geography GB3-5030 Science Q Katarzyna Ewa Lewińska Johanna Buchner Benjamin Bleyhl Patrick Hostert He Yin Tobias Kuemmerle Volker C. Radeloff Changes in the grasslands of the Caucasus based on Cumulative Endmember Fractions from the full 1987–2019 Landsat record
description	Grasslands are important for global biodiversity, food security, and climate change analyses, which makes mapping and monitoring of vegetation changes in grasslands necessary to better understand, sustainably manage, and protect these ecosystems. However, grassland vegetation monitoring at spatial and temporal resolution relevant to land management (e.g., ca. 30-m, and at least annually over long time periods) is challenging due to complex spatio-temporal pattern of changes and often limited data availability. Here we assess both short- and long-term changes in grassland vegetation cover from 1987 to 2019 across the Caucasus ecoregion at 30-m resolution based on Cumulative Endmember Fractions (i.e., annual sums of monthly ground cover fractions) derived from the full Landsat record, and temporal segmentation with LandTrendr. Our approach combines the benefits of physically-based analyses, missing data prediction, annual aggregations, and adaptive identification of changes in the time-series. We analyzed changes in vegetation fraction cover to infer the location, timing, and magnitude of vegetation change episodes of any length, quantified shifts among all ground cover fractions (i.e., green vegetation, non-photosynthetic vegetation, soil, and shade), and identified change pathways (i.e., green vegetation loss, desiccation, dry vegetation loss, revegetation green fraction, greening, or revegetation dry fraction). We found widespread long-term positive changes in grassland vegetation (32.7% of grasslands), especially in the early 2000s, but negative changes pathways were most common before the year 2000. We found little association between changes in green vegetation and meteorological conditions, and varied relationships with livestock populations. However, we also found strong spatial heterogeneity in vegetation dynamics among neighboring fields and pastures, demonstrating capability of our approach for grassland management at local levels. Our results provide a detailed assessment of grassland vegetation change in the Caucasus Ecoregion, and present an approach to map changes in grasslands even where availability of Landsat data is limited.
format	article
author	Katarzyna Ewa Lewińska Johanna Buchner Benjamin Bleyhl Patrick Hostert He Yin Tobias Kuemmerle Volker C. Radeloff
author_facet	Katarzyna Ewa Lewińska Johanna Buchner Benjamin Bleyhl Patrick Hostert He Yin Tobias Kuemmerle Volker C. Radeloff
author_sort	Katarzyna Ewa Lewińska
title	Changes in the grasslands of the Caucasus based on Cumulative Endmember Fractions from the full 1987–2019 Landsat record
title_short	Changes in the grasslands of the Caucasus based on Cumulative Endmember Fractions from the full 1987–2019 Landsat record
title_full	Changes in the grasslands of the Caucasus based on Cumulative Endmember Fractions from the full 1987–2019 Landsat record
title_fullStr	Changes in the grasslands of the Caucasus based on Cumulative Endmember Fractions from the full 1987–2019 Landsat record
title_full_unstemmed	Changes in the grasslands of the Caucasus based on Cumulative Endmember Fractions from the full 1987–2019 Landsat record
title_sort	changes in the grasslands of the caucasus based on cumulative endmember fractions from the full 1987–2019 landsat record
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/2d193dccf5434ba5bb1f33abac9ab5be
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Changes in the grasslands of the Caucasus based on Cumulative Endmember Fractions from the full 1987–2019 Landsat record

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