Towards an improved environmental understanding of land surface dynamics in ukraine based on multi-source remote sensing time-series datasets from 1982 to 2013

17Citations
Citations of this article
49Readers
Mendeley users who have this article in their library.

Abstract

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.

Cite

CITATION STYLE

APA

Ghazaryan, G., Dubovyk, O., Kussul, N., & Menz, G. (2016). 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, 8(8). https://doi.org/10.3390/rs8080617

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free