Drought Risk Assessment in Cultivated Areas of Central Asia Using MODIS Time-Series Data
Drought is one of the most damaging environmental hazards and a naturally occurring phenomenon in Central Asia that is accompanied by crucial consequences for the agriculture sector. This research aimed at understanding the nature and extent of drought over the cropland regions of Central Asia with...
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description | Drought is one of the most damaging environmental hazards and a naturally occurring phenomenon in Central Asia that is accompanied by crucial consequences for the agriculture sector. This research aimed at understanding the nature and extent of drought over the cropland regions of Central Asia with the help of spatiotemporal information from the region. We assessed drought occurrence using the vegetation health index (VHI). An algorithm was developed to reduce the noise of heterogeneous land surfaces by adjusting the vegetation index and brightness temperature. The vegetation condition index (VCI) and temperature condition index (TCI) were calculated using Moderate Resolution Imaging Spectroradiometer (MODIS) products for the growing season (April–September) from 2000 to 2015. The intense drought years were identified and a drought map (drought probability occurrence) was generated. The findings of this research indicated regional heterogeneity in the cropland areas having experienced droughts, observed through spatiotemporal variations. Some of the rain-fed and irrigated croplands of Kazakhstan demonstrated a higher vulnerability to annual drought occurrences and climate change impacts, while other cropland regions were found to be more resistant to such changes. The development of policy tools is required to support informed decision-making and planning processes to adapt to the occurrence of droughts. This could be achieved by the timely assessment, monitoring, and evaluation of the spatiotemporal distribution trends and variabilities of drought occurrences in this region. The results from this study focus on the spatiotemporal variations in drought to reveal the bigger picture in order to better understand the regional capacity for sustainable land management and agricultural activities within a changing environment. |
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This research aimed at understanding the nature and extent of drought over the cropland regions of Central Asia with the help of spatiotemporal information from the region. We assessed drought occurrence using the vegetation health index (VHI). An algorithm was developed to reduce the noise of heterogeneous land surfaces by adjusting the vegetation index and brightness temperature. The vegetation condition index (VCI) and temperature condition index (TCI) were calculated using Moderate Resolution Imaging Spectroradiometer (MODIS) products for the growing season (April–September) from 2000 to 2015. The intense drought years were identified and a drought map (drought probability occurrence) was generated. The findings of this research indicated regional heterogeneity in the cropland areas having experienced droughts, observed through spatiotemporal variations. Some of the rain-fed and irrigated croplands of Kazakhstan demonstrated a higher vulnerability to annual drought occurrences and climate change impacts, while other cropland regions were found to be more resistant to such changes. The development of policy tools is required to support informed decision-making and planning processes to adapt to the occurrence of droughts. This could be achieved by the timely assessment, monitoring, and evaluation of the spatiotemporal distribution trends and variabilities of drought occurrences in this region. The results from this study focus on the spatiotemporal variations in drought to reveal the bigger picture in order to better understand the regional capacity for sustainable land management and agricultural activities within a changing environment.</description><identifier>ISSN: 2073-4441</identifier><identifier>EISSN: 2073-4441</identifier><identifier>DOI: 10.3390/w12061738</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Agricultural land ; Agricultural management ; Agricultural research ; Agriculture ; Asia ; Brightness temperature ; Changing environments ; Climate change ; Datasets ; Decision making ; Drought ; Droughts ; Electronic data processing ; Environmental aspects ; Environmental hazards ; Environmental management ; Environmental risk ; Heterogeneity ; Land management ; Methods ; MODIS ; Noise reduction ; Precipitation ; Productivity ; Remote sensing ; Risk assessment ; Seasons ; Spatial distribution ; Spectroradiometer ; Spectroradiometers ; Studies ; Sustainable agriculture ; Temporal distribution ; Tillage ; Time-series analysis ; Vegetation ; Water shortages ; Wheat</subject><ispartof>Water (Basel), 2020-06, Vol.12 (6), p.1738</ispartof><rights>COPYRIGHT 2020 MDPI AG</rights><rights>2020. This work is licensed under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c331t-53c021dd571085de6a70ea13ded5664d3aa43e42b948b9f757ed5ea10ec7bc773</citedby><cites>FETCH-LOGICAL-c331t-53c021dd571085de6a70ea13ded5664d3aa43e42b948b9f757ed5ea10ec7bc773</cites><orcidid>0000-0002-2430-8072 ; 0000-0001-9735-7265 ; 0000-0003-2082-6160</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Aitekeyeva, Nurgul</creatorcontrib><creatorcontrib>Li, Xinwu</creatorcontrib><creatorcontrib>Guo, Huadong</creatorcontrib><creatorcontrib>Wu, Wenjin</creatorcontrib><creatorcontrib>Shirazi, Zeeshan</creatorcontrib><creatorcontrib>Ilyas, Sana</creatorcontrib><creatorcontrib>Yegizbayeva, Asset</creatorcontrib><creatorcontrib>Hategekimana, Yves</creatorcontrib><title>Drought Risk Assessment in Cultivated Areas of Central Asia Using MODIS Time-Series Data</title><title>Water (Basel)</title><description>Drought is one of the most damaging environmental hazards and a naturally occurring phenomenon in Central Asia that is accompanied by crucial consequences for the agriculture sector. This research aimed at understanding the nature and extent of drought over the cropland regions of Central Asia with the help of spatiotemporal information from the region. We assessed drought occurrence using the vegetation health index (VHI). An algorithm was developed to reduce the noise of heterogeneous land surfaces by adjusting the vegetation index and brightness temperature. The vegetation condition index (VCI) and temperature condition index (TCI) were calculated using Moderate Resolution Imaging Spectroradiometer (MODIS) products for the growing season (April–September) from 2000 to 2015. The intense drought years were identified and a drought map (drought probability occurrence) was generated. The findings of this research indicated regional heterogeneity in the cropland areas having experienced droughts, observed through spatiotemporal variations. Some of the rain-fed and irrigated croplands of Kazakhstan demonstrated a higher vulnerability to annual drought occurrences and climate change impacts, while other cropland regions were found to be more resistant to such changes. The development of policy tools is required to support informed decision-making and planning processes to adapt to the occurrence of droughts. This could be achieved by the timely assessment, monitoring, and evaluation of the spatiotemporal distribution trends and variabilities of drought occurrences in this region. 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Li, Xinwu ; Guo, Huadong ; Wu, Wenjin ; Shirazi, Zeeshan ; Ilyas, Sana ; Yegizbayeva, Asset ; Hategekimana, Yves</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-53c021dd571085de6a70ea13ded5664d3aa43e42b948b9f757ed5ea10ec7bc773</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Agricultural land</topic><topic>Agricultural management</topic><topic>Agricultural research</topic><topic>Agriculture</topic><topic>Asia</topic><topic>Brightness temperature</topic><topic>Changing environments</topic><topic>Climate change</topic><topic>Datasets</topic><topic>Decision making</topic><topic>Drought</topic><topic>Droughts</topic><topic>Electronic data processing</topic><topic>Environmental aspects</topic><topic>Environmental hazards</topic><topic>Environmental management</topic><topic>Environmental risk</topic><topic>Heterogeneity</topic><topic>Land management</topic><topic>Methods</topic><topic>MODIS</topic><topic>Noise reduction</topic><topic>Precipitation</topic><topic>Productivity</topic><topic>Remote sensing</topic><topic>Risk assessment</topic><topic>Seasons</topic><topic>Spatial distribution</topic><topic>Spectroradiometer</topic><topic>Spectroradiometers</topic><topic>Studies</topic><topic>Sustainable agriculture</topic><topic>Temporal distribution</topic><topic>Tillage</topic><topic>Time-series analysis</topic><topic>Vegetation</topic><topic>Water shortages</topic><topic>Wheat</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aitekeyeva, Nurgul</creatorcontrib><creatorcontrib>Li, Xinwu</creatorcontrib><creatorcontrib>Guo, Huadong</creatorcontrib><creatorcontrib>Wu, Wenjin</creatorcontrib><creatorcontrib>Shirazi, Zeeshan</creatorcontrib><creatorcontrib>Ilyas, Sana</creatorcontrib><creatorcontrib>Yegizbayeva, Asset</creatorcontrib><creatorcontrib>Hategekimana, Yves</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Water (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Aitekeyeva, Nurgul</au><au>Li, Xinwu</au><au>Guo, Huadong</au><au>Wu, Wenjin</au><au>Shirazi, Zeeshan</au><au>Ilyas, Sana</au><au>Yegizbayeva, Asset</au><au>Hategekimana, Yves</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Drought Risk Assessment in Cultivated Areas of Central Asia Using MODIS Time-Series Data</atitle><jtitle>Water (Basel)</jtitle><date>2020-06-01</date><risdate>2020</risdate><volume>12</volume><issue>6</issue><spage>1738</spage><pages>1738-</pages><issn>2073-4441</issn><eissn>2073-4441</eissn><abstract>Drought is one of the most damaging environmental hazards and a naturally occurring phenomenon in Central Asia that is accompanied by crucial consequences for the agriculture sector. This research aimed at understanding the nature and extent of drought over the cropland regions of Central Asia with the help of spatiotemporal information from the region. We assessed drought occurrence using the vegetation health index (VHI). An algorithm was developed to reduce the noise of heterogeneous land surfaces by adjusting the vegetation index and brightness temperature. The vegetation condition index (VCI) and temperature condition index (TCI) were calculated using Moderate Resolution Imaging Spectroradiometer (MODIS) products for the growing season (April–September) from 2000 to 2015. The intense drought years were identified and a drought map (drought probability occurrence) was generated. The findings of this research indicated regional heterogeneity in the cropland areas having experienced droughts, observed through spatiotemporal variations. Some of the rain-fed and irrigated croplands of Kazakhstan demonstrated a higher vulnerability to annual drought occurrences and climate change impacts, while other cropland regions were found to be more resistant to such changes. The development of policy tools is required to support informed decision-making and planning processes to adapt to the occurrence of droughts. This could be achieved by the timely assessment, monitoring, and evaluation of the spatiotemporal distribution trends and variabilities of drought occurrences in this region. The results from this study focus on the spatiotemporal variations in drought to reveal the bigger picture in order to better understand the regional capacity for sustainable land management and agricultural activities within a changing environment.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/w12061738</doi><orcidid>https://orcid.org/0000-0002-2430-8072</orcidid><orcidid>https://orcid.org/0000-0001-9735-7265</orcidid><orcidid>https://orcid.org/0000-0003-2082-6160</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Agricultural land Agricultural management Agricultural research Agriculture Asia Brightness temperature Changing environments Climate change Datasets Decision making Drought Droughts Electronic data processing Environmental aspects Environmental hazards Environmental management Environmental risk Heterogeneity Land management Methods MODIS Noise reduction Precipitation Productivity Remote sensing Risk assessment Seasons Spatial distribution Spectroradiometer Spectroradiometers Studies Sustainable agriculture Temporal distribution Tillage Time-series analysis Vegetation Water shortages Wheat |
title | Drought Risk Assessment in Cultivated Areas of Central Asia Using MODIS Time-Series Data |
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