Spatio-Temporal Patterns of Drought and Impact on Vegetation in North and West Africa Based on Multi-Satellite Data
Studying the significant impacts of drought on vegetation is crucial to understand its dynamics and interrelationships with precipitation, soil moisture, and temperature. In North and West Africa regions, the effects of drought on vegetation have not been clearly stated. Therefore, the present study...
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| Format: | Article |
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MDPI AG
2020-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/23/3869 |
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| author | Malak Henchiri Qi Liu Bouajila Essifi Tehseen Javed Sha Zhang Yun Bai Jiahua Zhang |
| author_facet | Malak Henchiri Qi Liu Bouajila Essifi Tehseen Javed Sha Zhang Yun Bai Jiahua Zhang |
| author_sort | Malak Henchiri |
| collection | DOAJ |
| description | Studying the significant impacts of drought on vegetation is crucial to understand its dynamics and interrelationships with precipitation, soil moisture, and temperature. In North and West Africa regions, the effects of drought on vegetation have not been clearly stated. Therefore, the present study aims to bring out the drought fluctuations within various types of Land Cover (LC) (Grasslands, Croplands, Savannas, and Forest) in North and West Africa regions. The drought characteristics were evaluated by analyzing the monthly Self-Calibrating Palmer Drought Severity Index (scPDSI) in different timescale from 2002 to 2018. Then, the frequency of droughts was examined over the same period. The results have revealed two groups of years (dry years and normal years), based on drought intensity. The selected years were used to compare the shifting between vegetation and desert. The Vegetation Condition Index (VCI), the Temperature Condition Index (TCI), the Precipitation Condition Index (PCI), and the Soil Moisture Condition Index (SMCI) were also used to investigate the spatiotemporal variation of drought and to determine which LC class was more vulnerable to drought risk. Our results revealed that Grasslands and Croplands in the West region, and Grasslands, Croplands, and Savannas in the North region are more sensitive to drought. A higher correlation was observed among the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Tropical Rainfall Measuring Mission (TRMM), and Soil Moisture (SM). Our findings suggested that NDVI, TRMM, and SM are more suitable for monitoring drought over the study area and have a reliable accuracy (R<sup>2</sup> > 0.70) concerning drought prediction. The outcomes of the current research could, explicitly, contribute progressively towards improving specific drought mitigation strategies and disaster risk reduction at regional and national levels. |
| first_indexed | 2024-03-10T14:34:04Z |
| format | Article |
| id | doaj.art-7ca2ae71368b4ef2be73651f33550d22 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T14:34:04Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-7ca2ae71368b4ef2be73651f33550d222023-11-20T22:20:53ZengMDPI AGRemote Sensing2072-42922020-11-011223386910.3390/rs12233869Spatio-Temporal Patterns of Drought and Impact on Vegetation in North and West Africa Based on Multi-Satellite DataMalak Henchiri0Qi Liu1Bouajila Essifi2Tehseen Javed3Sha Zhang4Yun Bai5Jiahua Zhang6School of Automation, Qingdao University, Qingdao 266071, ChinaCollege of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing 100049, ChinaLaboratory of Eremology and Combating Desertification, Institut des Regions Arides (IRA), Medenine 4119, TunisiaSchool of Automation, Qingdao University, Qingdao 266071, ChinaSchool of Automation, Qingdao University, Qingdao 266071, ChinaSchool of Automation, Qingdao University, Qingdao 266071, ChinaRemote Sensing Information and Digital Earth Center, School of Computer Science and Technology, Qingdao University, Qingdao 266071, ChinaStudying the significant impacts of drought on vegetation is crucial to understand its dynamics and interrelationships with precipitation, soil moisture, and temperature. In North and West Africa regions, the effects of drought on vegetation have not been clearly stated. Therefore, the present study aims to bring out the drought fluctuations within various types of Land Cover (LC) (Grasslands, Croplands, Savannas, and Forest) in North and West Africa regions. The drought characteristics were evaluated by analyzing the monthly Self-Calibrating Palmer Drought Severity Index (scPDSI) in different timescale from 2002 to 2018. Then, the frequency of droughts was examined over the same period. The results have revealed two groups of years (dry years and normal years), based on drought intensity. The selected years were used to compare the shifting between vegetation and desert. The Vegetation Condition Index (VCI), the Temperature Condition Index (TCI), the Precipitation Condition Index (PCI), and the Soil Moisture Condition Index (SMCI) were also used to investigate the spatiotemporal variation of drought and to determine which LC class was more vulnerable to drought risk. Our results revealed that Grasslands and Croplands in the West region, and Grasslands, Croplands, and Savannas in the North region are more sensitive to drought. A higher correlation was observed among the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Tropical Rainfall Measuring Mission (TRMM), and Soil Moisture (SM). Our findings suggested that NDVI, TRMM, and SM are more suitable for monitoring drought over the study area and have a reliable accuracy (R<sup>2</sup> > 0.70) concerning drought prediction. The outcomes of the current research could, explicitly, contribute progressively towards improving specific drought mitigation strategies and disaster risk reduction at regional and national levels.https://www.mdpi.com/2072-4292/12/23/3869Drought IndicesNorth and West AfricashiftingSpatiotemporal VariationsVegetation Response |
| spellingShingle | Malak Henchiri Qi Liu Bouajila Essifi Tehseen Javed Sha Zhang Yun Bai Jiahua Zhang Spatio-Temporal Patterns of Drought and Impact on Vegetation in North and West Africa Based on Multi-Satellite Data Remote Sensing Drought Indices North and West Africa shifting Spatiotemporal Variations Vegetation Response |
| title | Spatio-Temporal Patterns of Drought and Impact on Vegetation in North and West Africa Based on Multi-Satellite Data |
| title_full | Spatio-Temporal Patterns of Drought and Impact on Vegetation in North and West Africa Based on Multi-Satellite Data |
| title_fullStr | Spatio-Temporal Patterns of Drought and Impact on Vegetation in North and West Africa Based on Multi-Satellite Data |
| title_full_unstemmed | Spatio-Temporal Patterns of Drought and Impact on Vegetation in North and West Africa Based on Multi-Satellite Data |
| title_short | Spatio-Temporal Patterns of Drought and Impact on Vegetation in North and West Africa Based on Multi-Satellite Data |
| title_sort | spatio temporal patterns of drought and impact on vegetation in north and west africa based on multi satellite data |
| topic | Drought Indices North and West Africa shifting Spatiotemporal Variations Vegetation Response |
| url | https://www.mdpi.com/2072-4292/12/23/3869 |
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