Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013

Ukraine has experienced immense environmental and institutional changes during the last three decades. We have conducted this study to analyze important land surface dynamics and to assess processes underlying the changes. This research was conducted in two consecutive steps. To analyze monotonic ch...

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Main Authors: Gohar Ghazaryan, Olena Dubovyk, Nataliia Kussul, Gunter Menz
Format: Article
Language:English
Published: MDPI AG 2016-07-01
Series:Remote Sensing
Subjects:
Online Access:http://www.mdpi.com/2072-4292/8/8/617
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spelling doaj-80198b000cbe4620b9ea251960249bb72020-11-25T00:34:26ZengMDPI AGRemote Sensing2072-42922016-07-018861710.3390/rs8080617rs8080617Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013Gohar Ghazaryan0Olena Dubovyk1Nataliia Kussul2Gunter Menz3Center for Remote Sensing of Land Surfaces (ZFL), University of Bonn, Walter-Flex-Str. 3, 53113 Bonn, GermanyCenter for Remote Sensing of Land Surfaces (ZFL), University of Bonn, Walter-Flex-Str. 3, 53113 Bonn, GermanySpace Research Institute of National Academy of Sciences of Ukraine and State Space Agency of Ukraine, Glushkov Ave, 40, Building 4/1, 03680 Kyiv, UkraineCenter for Remote Sensing of Land Surfaces (ZFL), University of Bonn, Walter-Flex-Str. 3, 53113 Bonn, GermanyUkraine has experienced immense environmental and institutional changes during the last three decades. We have conducted this study to analyze important land surface dynamics and to assess processes underlying the changes. This research was conducted in two consecutive steps. To analyze monotonic changes we first applied a Mann–Kendall trend analysis of the Normalized Difference Vegetation Index (NDVI3g) time series. Gradual and abrupt changes were studied by fitting a seasonal trend model and detecting the breakpoints. Secondly, essential environmental factors were used to quantify their possible relationships with land surface changes. These factors included soil moisture as well as gridded air temperature and precipitation data. This was done using partial rank correlation analysis based on annually aggregated time-series. Our results demonstrate that positive NDVI trends characterize approximately one-third of Ukraine’s land surface, located in the northern and western areas of the country. Negative trends occurred less frequently, covering less than 2% of the area and are distributed irregularly across the country. Monotonic trends were rarely found; shifting trends were identified with a greater frequency. Trend shifts were seen to occur with an increased frequency following the period of the 2000s. We determined that land surface dynamics and climate variability are functionally interdependent; however, the relative influence of the drivers varies in different locations. Among the factors analyzed, the air temperature variable explains the largest portion of NDVI variability. High air temperature/NDVI correlation coefficients (r = 0.36 − 0.77) are observed over the entire country. The soil moisture content is of significant influence in the eastern portion of Ukraine (r = 0.68); precipitation (r = 0.65) was most influential in the central regions of the country. These results increase our understanding of ecosystem responses to climatic changes and anthropogenic activities.http://www.mdpi.com/2072-4292/8/8/617trend analysisland cover changeAVHRREastern Europe
collection DOAJ
language English
format Article
sources DOAJ
author Gohar Ghazaryan
Olena Dubovyk
Nataliia Kussul
Gunter Menz
spellingShingle Gohar Ghazaryan
Olena Dubovyk
Nataliia Kussul
Gunter Menz
Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013
Remote Sensing
trend analysis
land cover change
AVHRR
Eastern Europe
author_facet Gohar Ghazaryan
Olena Dubovyk
Nataliia Kussul
Gunter Menz
author_sort Gohar Ghazaryan
title Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013
title_short Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013
title_full Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013
title_fullStr Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013
title_full_unstemmed Towards an Improved Environmental Understanding of Land Surface Dynamics in Ukraine Based on Multi-Source Remote Sensing Time-Series Datasets from 1982 to 2013
title_sort towards an improved environmental understanding of land surface dynamics in ukraine based on multi-source remote sensing time-series datasets from 1982 to 2013
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2016-07-01
description Ukraine has experienced immense environmental and institutional changes during the last three decades. We have conducted this study to analyze important land surface dynamics and to assess processes underlying the changes. This research was conducted in two consecutive steps. To analyze monotonic changes we first applied a Mann–Kendall trend analysis of the Normalized Difference Vegetation Index (NDVI3g) time series. Gradual and abrupt changes were studied by fitting a seasonal trend model and detecting the breakpoints. Secondly, essential environmental factors were used to quantify their possible relationships with land surface changes. These factors included soil moisture as well as gridded air temperature and precipitation data. This was done using partial rank correlation analysis based on annually aggregated time-series. Our results demonstrate that positive NDVI trends characterize approximately one-third of Ukraine’s land surface, located in the northern and western areas of the country. Negative trends occurred less frequently, covering less than 2% of the area and are distributed irregularly across the country. Monotonic trends were rarely found; shifting trends were identified with a greater frequency. Trend shifts were seen to occur with an increased frequency following the period of the 2000s. We determined that land surface dynamics and climate variability are functionally interdependent; however, the relative influence of the drivers varies in different locations. Among the factors analyzed, the air temperature variable explains the largest portion of NDVI variability. High air temperature/NDVI correlation coefficients (r = 0.36 − 0.77) are observed over the entire country. The soil moisture content is of significant influence in the eastern portion of Ukraine (r = 0.68); precipitation (r = 0.65) was most influential in the central regions of the country. These results increase our understanding of ecosystem responses to climatic changes and anthropogenic activities.
topic trend analysis
land cover change
AVHRR
Eastern Europe
url http://www.mdpi.com/2072-4292/8/8/617
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AT nataliiakussul towardsanimprovedenvironmentalunderstandingoflandsurfacedynamicsinukrainebasedonmultisourceremotesensingtimeseriesdatasetsfrom1982to2013
AT guntermenz towardsanimprovedenvironmentalunderstandingoflandsurfacedynamicsinukrainebasedonmultisourceremotesensingtimeseriesdatasetsfrom1982to2013
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