Monitoring Droughts and Impacts on Crop Yield in Ukraine from Weather and Satellite Data

Adamenko, T.; Прокопенко, А. Г.

doi:10.1007/978-90-481-9618-0_1

Cited by 11 publications

(10 citation statements)

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“…We used a subtractive model for visualization, where the primary factors are illustrated with a pure color and the overlapping areas of influence are depicted by the intersection of colors. Although the studies have discussed the impact of climatic variation on land surface changes [33,55,56], very few of them have focused on the impact of environmental factors on land surface trends in Ukraine as opposed to management and land tenure factors [1][2][3][4][5][6][7][8]. Our results show that the changes in land surface can be partially explained by the combination of thermal and water conditions.…”

Section: Factors Of Land Surface Dynamics In Ukrainementioning

confidence: 75%

“…In addition, the scale compatibility was another issue, as the datasets might be not representative for an 8 km grid [53]. To overcome this, we compared our results with the results of the previous studies [1,[4][5][6][7][8][9] and investigated the validity of the results by local experts. …”

Section: Trends Of Ndvi Seriesmentioning

confidence: 99%

“…Since the late 1990s and early 2000s, due to the economic recovery, the re-cultivation of formerly abandoned land emerged [5]. The last period (2003-2013) was also associated with strong environmental impacts (i.e., droughts and extreme weather conditions) [8,27].…”

Section: Characteristics Of the Main Time Periods Of The Trend Shiftsmentioning

confidence: 99%

“…In winter, permanent snow cover occurs almost everywhere in the country. One of the key features of the climate of Ukraine are the droughts which in recent years have increased frequency and affect large areas [8,27,29].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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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.

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Section: Factors Of Land Surface Dynamics In Ukrainementioning

confidence: 75%

Section: Trends Of Ndvi Seriesmentioning

confidence: 99%

Section: Characteristics Of the Main Time Periods Of The Trend Shiftsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2016

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“…The climate of Ukraine has the same trends as the climate of the entire Earth; however, the warming rate is above the global average. This is the main feature of the heterogeneity of climate change in Ukraine (Adamenko, 2017; Adamenko and Prokopenko, 2011). The climate change trend in Ukraine is not linearly growing after 1970-1980 ( Fig.…”

Section: Introductionmentioning

confidence: 94%

The Typicality of Hydrothermal Conditions of the Forest Steppe and Their Influence on the Productivity of Crops

Butenko

Litvinov

Borys

et al. 2020

EREM

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Analysis of changes in hydrothermal conditions of growing crops in the forest steppe zone of Ukraine over a period of 2004–2016 showed that by the average monthly air temperature more than a half of the years under study and by rainfall nearly a third of the researched period differed significantly from the average long-term value and were close to extreme weather. Statistical analysis of long-term indicators of the air temperature regime is evidence of a steady trend towards an increase in average annual air temperature with significant fluctuations in indices in separate periods from 7.9 ± 2.9 to 10.0 ± 2.5oС and a decrease in the amount and instability of natural moisture entry. The influence of weather conditions on the formation of productivity of spiked cereals (winter and spring wheat, spring barley) and maize was assessed at the current agrometeorological risks in the forest steppe of Ukraine. Based on the correlation-regression analysis, mathematical models were created that reproduce the dependence of grain yields upon the complex weather conditions of the growing season, the impact of which reached 60–70%. The conditions of eight years (2006–2008, 2011–2014 and 2016), when the hydrothermal index for the vegetation period was 1.13–1.76, turned out to be optimal by hydrothermal indicators to harvest maize yield at 5.83–9.47 t/ha. However, the years of 2005, 2009–2010 and 2015 were unfavorable as they received precipitation by 120 mm lower than a norm or 36% of the norm. The rainfall by 37–61% lower than a norm in June–July and grain yield 3.12–6.51 t/ha were also characteristic of the years mentioned above.

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New Remote Sensing Vegetation Health Technology

Kogan

2022

Remote Sensing Land Surface Changes

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Monitoring Droughts and Impacts on Crop Yield in Ukraine from Weather and Satellite Data

Cited by 11 publications

References 0 publications

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

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

The Typicality of Hydrothermal Conditions of the Forest Steppe and Their Influence on the Productivity of Crops

New Remote Sensing Vegetation Health Technology

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