Application of GIS using NDVI and LST estimation to measure climate variability-induced drought risk assessment in Ethiopia
The contribution of this paper is to assess the drought patterns using the Land Surface Temperature (LST) estimation index and examine the correlation between the Normalized Difference Vegetation Index (NDVI). The main objective was to evaluate the spatiotemporal variation in agricultural drought pa...
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| Format: | Article |
| Language: | English |
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IWA Publishing
2023-07-01
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| Series: | Journal of Water and Climate Change |
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| Online Access: | http://jwcc.iwaponline.com/content/14/7/2479 |
| _version_ | 1797202777240240128 |
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| author | Fikiru Temesgen Gelata Han Jiqin Samerawit Chaka Gemeda Birhan Wubishet Asefa |
| author_facet | Fikiru Temesgen Gelata Han Jiqin Samerawit Chaka Gemeda Birhan Wubishet Asefa |
| author_sort | Fikiru Temesgen Gelata |
| collection | DOAJ |
| description | The contribution of this paper is to assess the drought patterns using the Land Surface Temperature (LST) estimation index and examine the correlation between the Normalized Difference Vegetation Index (NDVI). The main objective was to evaluate the spatiotemporal variation in agricultural drought patterns and severity in order to estimate and measure climate variability. According to the study's findings, the region experienced mild to severe meteorological drought periods 15–18 times over the study period. The majority of these periods (62.72%) were classified as mild drought (unusual dry circumstances), which usually only showed a slight departure from the distribution of rainfall that is close to normal. According to the findings, cropping seasons from 2013 to 2022 saw an increase in agricultural dryness and a decrease in grain yield, with varying degrees of severity in different geographic locations. Based on the result, the major difficulties and challenges identified were the shortage of drinking water, and impacts on air quality, and food and nutrition. Accordingly, agricultural drought risk mapping can be utilized to mitigate the risk associated with drought on agricultural productivity and guide decision-making processes in drought monitoring.
HIGHLIGHTS
Droughts, which are typically associated with high temperatures and low moisture levels, have become increasingly common and critical concerns for all parties involved.;
The unique characterizations for the vegetative area which has an effect on many socioeconomics provided by the remote-sensing-based indices for evaluating the state of vegetation include biomass and growth status.; |
| first_indexed | 2024-03-12T15:26:13Z |
| format | Article |
| id | doaj.art-f19a8033a7b843039236d285c10001cd |
| institution | Directory Open Access Journal |
| issn | 2040-2244 2408-9354 |
| language | English |
| last_indexed | 2024-04-24T08:08:50Z |
| publishDate | 2023-07-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Journal of Water and Climate Change |
| spelling | doaj.art-f19a8033a7b843039236d285c10001cd2024-04-17T08:30:37ZengIWA PublishingJournal of Water and Climate Change2040-22442408-93542023-07-011472479248910.2166/wcc.2023.154154Application of GIS using NDVI and LST estimation to measure climate variability-induced drought risk assessment in EthiopiaFikiru Temesgen Gelata0Han Jiqin1Samerawit Chaka Gemeda2Birhan Wubishet Asefa3 College of Economics and Management, Nanjing Agricultural University, 210095, Nanjing, Jiangsu, China College of Economics and Management, Nanjing Agricultural University, 210095, Nanjing, Jiangsu, China Department of Agricultural Economics, Ambo University, 19, Ambo, Ethiopia Pan African University of Water and Energy Science, including climate change (PAUWES), Tlemcen, Algeria The contribution of this paper is to assess the drought patterns using the Land Surface Temperature (LST) estimation index and examine the correlation between the Normalized Difference Vegetation Index (NDVI). The main objective was to evaluate the spatiotemporal variation in agricultural drought patterns and severity in order to estimate and measure climate variability. According to the study's findings, the region experienced mild to severe meteorological drought periods 15–18 times over the study period. The majority of these periods (62.72%) were classified as mild drought (unusual dry circumstances), which usually only showed a slight departure from the distribution of rainfall that is close to normal. According to the findings, cropping seasons from 2013 to 2022 saw an increase in agricultural dryness and a decrease in grain yield, with varying degrees of severity in different geographic locations. Based on the result, the major difficulties and challenges identified were the shortage of drinking water, and impacts on air quality, and food and nutrition. Accordingly, agricultural drought risk mapping can be utilized to mitigate the risk associated with drought on agricultural productivity and guide decision-making processes in drought monitoring. HIGHLIGHTS Droughts, which are typically associated with high temperatures and low moisture levels, have become increasingly common and critical concerns for all parties involved.; The unique characterizations for the vegetative area which has an effect on many socioeconomics provided by the remote-sensing-based indices for evaluating the state of vegetation include biomass and growth status.;http://jwcc.iwaponline.com/content/14/7/2479climatedroughtgislstndvistudy areas |
| spellingShingle | Fikiru Temesgen Gelata Han Jiqin Samerawit Chaka Gemeda Birhan Wubishet Asefa Application of GIS using NDVI and LST estimation to measure climate variability-induced drought risk assessment in Ethiopia Journal of Water and Climate Change climate drought gis lst ndvi study areas |
| title | Application of GIS using NDVI and LST estimation to measure climate variability-induced drought risk assessment in Ethiopia |
| title_full | Application of GIS using NDVI and LST estimation to measure climate variability-induced drought risk assessment in Ethiopia |
| title_fullStr | Application of GIS using NDVI and LST estimation to measure climate variability-induced drought risk assessment in Ethiopia |
| title_full_unstemmed | Application of GIS using NDVI and LST estimation to measure climate variability-induced drought risk assessment in Ethiopia |
| title_short | Application of GIS using NDVI and LST estimation to measure climate variability-induced drought risk assessment in Ethiopia |
| title_sort | application of gis using ndvi and lst estimation to measure climate variability induced drought risk assessment in ethiopia |
| topic | climate drought gis lst ndvi study areas |
| url | http://jwcc.iwaponline.com/content/14/7/2479 |
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