Prospects for Drought Detection and Monitoring Using Long-Term Vegetation Indices Series from Satellite Data in Kazakhstan DOI Creative Commons
Irina Vitkovskaya, M. Batyrbayeva,

Nurmaganbet Berdigulov

et al.

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2225 - 2225

Published: Dec. 19, 2024

The rainfed cereal growing regions of Northern Kazakhstan experience significant yield fluctuations due to dependence on weather conditions. Early detection and monitoring droughts is crucial for effective mitigation strategies in this region. This study emphasises the following objectives: (1) description current vegetation condition with a possible separation short-term effects (2) analysing trends changes their directionality quantification. Terra MODIS satellite images from 2000 2023 are used. Differential indices—Normalised Difference Vegetation Index (NDVI) Condition (VCI)—are used determine characteristics each season. A key component comparison NDVI values historical maximum, minimum, average identify early indicators drought. deviations multiyear norms VCI below 0.3 visually reflect changing conditions influenced by seasonal patterns. results show that algorithm effectively detects signs drought through observed values, showing trend towards increasing frequency intensity Kazakhstan. was particularly detecting severe seasons advance, as case June 2010 May 2012, thus supporting recognition onset. Integrated (IVI) (IVCI) time series integrated assessments, temporal cover, determining these changes, ranking season series. Areas high probability based low IVCI mapped. present value remote sensing tool monitoring, offering timely spatially detailed information vulnerable areas. approach provides critical agricultural planning, environmental management policy making, especially arid semi-arid regions. importance data accurate forecasting suggests methodology can be adapted other drought-sensitive Emphasising socio-economic benefits, using reduce material losses facilitate targeted responses.

Language: Английский

Satellite-Based Soil Moisture Estimation and Evaluation of Agricultural Drought Risk in the Tana Sub-Basin, Upper Blue Nile River Basin, Ethiopia DOI

Habtamu Abay Eshetie,

Dejena Sahlu,

Tena Alamirew Agumasie

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Understanding Drought: Agricultural and Socioeconomic Effects in Tekeze Watershed, Northern Ethiopia DOI

Yonas Tesfay,

Simachew Bantigegn,

Mehretie Belay

et al.

Earth Systems and Environment, Journal Year: 2025, Volume and Issue: unknown

Published: April 15, 2025

Language: Английский

Citations

0
Evaluation of standardized precipitation evapotranspiration drought index and soil moisture in the Nile River Basin using google earth engine cloud computing approach DOI
Birara Gebeyhu Reta

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(5)

Published: May 1, 2025

Language: Английский

Citations

0
Assessment of the impacts of climate change on drought intensity and frequency using SPI and SPEI in the Southern Pre-Balkash region, Kazakhstan DOI Creative Commons

Alimkulov Sayat,

Makhmudova Lyazzat,

Talipova Elmira

et al.

Watershed Ecology and the Environment, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 1, 2024

Language: Английский

Citations

2
Prospects for Drought Detection and Monitoring Using Long-Term Vegetation Indices Series from Satellite Data in Kazakhstan DOI Creative Commons
Irina Vitkovskaya, M. Batyrbayeva,

Nurmaganbet Berdigulov

et al.

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2225 - 2225

Published: Dec. 19, 2024

The rainfed cereal growing regions of Northern Kazakhstan experience significant yield fluctuations due to dependence on weather conditions. Early detection and monitoring droughts is crucial for effective mitigation strategies in this region. This study emphasises the following objectives: (1) description current vegetation condition with a possible separation short-term effects (2) analysing trends changes their directionality quantification. Terra MODIS satellite images from 2000 2023 are used. Differential indices—Normalised Difference Vegetation Index (NDVI) Condition (VCI)—are used determine characteristics each season. A key component comparison NDVI values historical maximum, minimum, average identify early indicators drought. deviations multiyear norms VCI below 0.3 visually reflect changing conditions influenced by seasonal patterns. results show that algorithm effectively detects signs drought through observed values, showing trend towards increasing frequency intensity Kazakhstan. was particularly detecting severe seasons advance, as case June 2010 May 2012, thus supporting recognition onset. Integrated (IVI) (IVCI) time series integrated assessments, temporal cover, determining these changes, ranking season series. Areas high probability based low IVCI mapped. present value remote sensing tool monitoring, offering timely spatially detailed information vulnerable areas. approach provides critical agricultural planning, environmental management policy making, especially arid semi-arid regions. importance data accurate forecasting suggests methodology can be adapted other drought-sensitive Emphasising socio-economic benefits, using reduce material losses facilitate targeted responses.

Language: Английский

Citations

1