Comparative evaluation of drought indices for monitoring drought based on remote sensing data
Many indices are used to monitor drought events. However, different indices have different data requirements and applications. Hence, evaluating their applicability will help to characterize drought events and refine the development of effective drought indices. We constructed different drought indi...
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| Veröffentlicht in: | Environmental science and pollution research international 2021-04, Vol.28 (16), p.20408-20425 |
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| creator | Wei, Wei Zhang, Jing Zhou, Liang Xie, Binbin Zhou, Junju Li, Chuanhua |
| description | Many indices are used to monitor drought events. However, different indices have different data requirements and applications. Hence, evaluating their applicability will help to characterize drought events and refine the development of effective drought indices. We constructed different drought indices based on multisource remote sensing data and comprehensively evaluated and compared their applicability for drought monitoring throughout China. The characteristics of drought events in 2009 and 2011 were compared using various drought indices. The different time scales of the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Index (SPI) were used to evaluate remote sensing drought indices in different regions. Single drought indices, including the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data, the Precipitation Condition Index (PCI) derived from Tropical Rainfall Measurement Mission (TRMM) data, and the TCI and Soil Moisture Condition Index (SMCI) derived from Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) data, as well as combined drought indices, including the Microwave Integrated Drought Index (MIDI), Optimized Vegetation Drought Index (OVDI), Optimized Meteorological Drought Index (OMDI), Scale Drought Conditions Index (SDCI), and Synthesized Drought Index (SDI), were analyzed and compared to evaluate their applicability. The results showed that different drought indices have specific characteristics under different land use types in China. The VCI and TCI can better monitor long-term drought conditions, but they have a weak correlation with the in situ drought index in forestland and grassland areas. The correlation of SPI-1 with the PCI is higher than that with other single indices, which indicates that the PCI is a good short-term drought index. The SMCI has a better correlation with the short-term in situ drought index, but it is not conducive to drought monitoring in areas such as densely forested land and grassland. The correlations of the in situ drought index with the combined drought indices (the MIDI, OVDI, OMDI, SDCI, and SDI) are better than those with the single drought indices. |
| doi_str_mv | 10.1007/s11356-020-12120-0 |
| format | Article |
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However, different indices have different data requirements and applications. Hence, evaluating their applicability will help to characterize drought events and refine the development of effective drought indices. We constructed different drought indices based on multisource remote sensing data and comprehensively evaluated and compared their applicability for drought monitoring throughout China. The characteristics of drought events in 2009 and 2011 were compared using various drought indices. The different time scales of the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Index (SPI) were used to evaluate remote sensing drought indices in different regions. Single drought indices, including the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data, the Precipitation Condition Index (PCI) derived from Tropical Rainfall Measurement Mission (TRMM) data, and the TCI and Soil Moisture Condition Index (SMCI) derived from Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) data, as well as combined drought indices, including the Microwave Integrated Drought Index (MIDI), Optimized Vegetation Drought Index (OVDI), Optimized Meteorological Drought Index (OMDI), Scale Drought Conditions Index (SDCI), and Synthesized Drought Index (SDI), were analyzed and compared to evaluate their applicability. The results showed that different drought indices have specific characteristics under different land use types in China. The VCI and TCI can better monitor long-term drought conditions, but they have a weak correlation with the in situ drought index in forestland and grassland areas. The correlation of SPI-1 with the PCI is higher than that with other single indices, which indicates that the PCI is a good short-term drought index. The SMCI has a better correlation with the short-term in situ drought index, but it is not conducive to drought monitoring in areas such as densely forested land and grassland. The correlations of the in situ drought index with the combined drought indices (the MIDI, OVDI, OMDI, SDCI, and SDI) are better than those with the single drought indices.</description><identifier>ISSN: 0944-1344</identifier><identifier>EISSN: 1614-7499</identifier><identifier>DOI: 10.1007/s11356-020-12120-0</identifier><identifier>PMID: 33405156</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Aquatic Pollution ; Atmospheric Protection/Air Quality Control/Air Pollution ; China ; Correlation ; Drought ; Drought index ; Earth and Environmental Science ; Earth Observing System (EOS) ; Ecotoxicology ; Environment ; Environmental Chemistry ; Environmental Health ; Environmental monitoring ; Environmental science ; Evaluation ; forest land ; Grasslands ; Land use ; Precipitation ; Rain ; Rainfall ; Rainfall measurement ; Remote monitoring ; Remote sensing ; Research Article ; Soil conditions ; Soil moisture ; soil water ; Spectroradiometers ; Standardized precipitation index ; temperature ; Vegetation ; Waste Water Technology ; Water Management ; Water Pollution Control</subject><ispartof>Environmental science and pollution research international, 2021-04, Vol.28 (16), p.20408-20425</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021</rights><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c466t-91b28d73714135d18ff91f8d71d78203d25d9a14b80ebb2b082ac0a74318bdc73</citedby><cites>FETCH-LOGICAL-c466t-91b28d73714135d18ff91f8d71d78203d25d9a14b80ebb2b082ac0a74318bdc73</cites><orcidid>0000-0003-4918-8713</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11356-020-12120-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11356-020-12120-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33405156$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wei, Wei</creatorcontrib><creatorcontrib>Zhang, Jing</creatorcontrib><creatorcontrib>Zhou, Liang</creatorcontrib><creatorcontrib>Xie, Binbin</creatorcontrib><creatorcontrib>Zhou, Junju</creatorcontrib><creatorcontrib>Li, Chuanhua</creatorcontrib><title>Comparative evaluation of drought indices for monitoring drought based on remote sensing data</title><title>Environmental science and pollution research international</title><addtitle>Environ Sci Pollut Res</addtitle><addtitle>Environ Sci Pollut Res Int</addtitle><description>Many indices are used to monitor drought events. However, different indices have different data requirements and applications. Hence, evaluating their applicability will help to characterize drought events and refine the development of effective drought indices. We constructed different drought indices based on multisource remote sensing data and comprehensively evaluated and compared their applicability for drought monitoring throughout China. The characteristics of drought events in 2009 and 2011 were compared using various drought indices. The different time scales of the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Index (SPI) were used to evaluate remote sensing drought indices in different regions. Single drought indices, including the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data, the Precipitation Condition Index (PCI) derived from Tropical Rainfall Measurement Mission (TRMM) data, and the TCI and Soil Moisture Condition Index (SMCI) derived from Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) data, as well as combined drought indices, including the Microwave Integrated Drought Index (MIDI), Optimized Vegetation Drought Index (OVDI), Optimized Meteorological Drought Index (OMDI), Scale Drought Conditions Index (SDCI), and Synthesized Drought Index (SDI), were analyzed and compared to evaluate their applicability. The results showed that different drought indices have specific characteristics under different land use types in China. The VCI and TCI can better monitor long-term drought conditions, but they have a weak correlation with the in situ drought index in forestland and grassland areas. The correlation of SPI-1 with the PCI is higher than that with other single indices, which indicates that the PCI is a good short-term drought index. The SMCI has a better correlation with the short-term in situ drought index, but it is not conducive to drought monitoring in areas such as densely forested land and grassland. The correlations of the in situ drought index with the combined drought indices (the MIDI, OVDI, OMDI, SDCI, and SDI) are better than those with the single drought indices.</description><subject>Aquatic Pollution</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>China</subject><subject>Correlation</subject><subject>Drought</subject><subject>Drought index</subject><subject>Earth and Environmental Science</subject><subject>Earth Observing System (EOS)</subject><subject>Ecotoxicology</subject><subject>Environment</subject><subject>Environmental Chemistry</subject><subject>Environmental Health</subject><subject>Environmental monitoring</subject><subject>Environmental science</subject><subject>Evaluation</subject><subject>forest land</subject><subject>Grasslands</subject><subject>Land use</subject><subject>Precipitation</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Rainfall measurement</subject><subject>Remote monitoring</subject><subject>Remote sensing</subject><subject>Research Article</subject><subject>Soil conditions</subject><subject>Soil moisture</subject><subject>soil water</subject><subject>Spectroradiometers</subject><subject>Standardized precipitation index</subject><subject>temperature</subject><subject>Vegetation</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution 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Int</addtitle><date>2021-04-01</date><risdate>2021</risdate><volume>28</volume><issue>16</issue><spage>20408</spage><epage>20425</epage><pages>20408-20425</pages><issn>0944-1344</issn><eissn>1614-7499</eissn><abstract>Many indices are used to monitor drought events. However, different indices have different data requirements and applications. Hence, evaluating their applicability will help to characterize drought events and refine the development of effective drought indices. We constructed different drought indices based on multisource remote sensing data and comprehensively evaluated and compared their applicability for drought monitoring throughout China. The characteristics of drought events in 2009 and 2011 were compared using various drought indices. The different time scales of the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Index (SPI) were used to evaluate remote sensing drought indices in different regions. Single drought indices, including the Vegetation Condition Index (VCI), the Temperature Condition Index (TCI) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) data, the Precipitation Condition Index (PCI) derived from Tropical Rainfall Measurement Mission (TRMM) data, and the TCI and Soil Moisture Condition Index (SMCI) derived from Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) data, as well as combined drought indices, including the Microwave Integrated Drought Index (MIDI), Optimized Vegetation Drought Index (OVDI), Optimized Meteorological Drought Index (OMDI), Scale Drought Conditions Index (SDCI), and Synthesized Drought Index (SDI), were analyzed and compared to evaluate their applicability. The results showed that different drought indices have specific characteristics under different land use types in China. The VCI and TCI can better monitor long-term drought conditions, but they have a weak correlation with the in situ drought index in forestland and grassland areas. The correlation of SPI-1 with the PCI is higher than that with other single indices, which indicates that the PCI is a good short-term drought index. The SMCI has a better correlation with the short-term in situ drought index, but it is not conducive to drought monitoring in areas such as densely forested land and grassland. The correlations of the in situ drought index with the combined drought indices (the MIDI, OVDI, OMDI, SDCI, and SDI) are better than those with the single drought indices.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>33405156</pmid><doi>10.1007/s11356-020-12120-0</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0003-4918-8713</orcidid></addata></record> |
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| subjects | Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution China Correlation Drought Drought index Earth and Environmental Science Earth Observing System (EOS) Ecotoxicology Environment Environmental Chemistry Environmental Health Environmental monitoring Environmental science Evaluation forest land Grasslands Land use Precipitation Rain Rainfall Rainfall measurement Remote monitoring Remote sensing Research Article Soil conditions Soil moisture soil water Spectroradiometers Standardized precipitation index temperature Vegetation Waste Water Technology Water Management Water Pollution Control |
| title | Comparative evaluation of drought indices for monitoring drought based on remote sensing data |
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