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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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 |
work_keys_str_mv |
AT goharghazaryan towardsanimprovedenvironmentalunderstandingoflandsurfacedynamicsinukrainebasedonmultisourceremotesensingtimeseriesdatasetsfrom1982to2013 AT olenadubovyk towardsanimprovedenvironmentalunderstandingoflandsurfacedynamicsinukrainebasedonmultisourceremotesensingtimeseriesdatasetsfrom1982to2013 AT nataliiakussul towardsanimprovedenvironmentalunderstandingoflandsurfacedynamicsinukrainebasedonmultisourceremotesensingtimeseriesdatasetsfrom1982to2013 AT guntermenz towardsanimprovedenvironmentalunderstandingoflandsurfacedynamicsinukrainebasedonmultisourceremotesensingtimeseriesdatasetsfrom1982to2013 |
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