Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103824
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorMainland Development Office-
dc.creatorWang, Zen_US
dc.creatorWang, Zen_US
dc.creatorXiong, Jen_US
dc.creatorHe, Wen_US
dc.creatorYong, Zen_US
dc.creatorWang, Xen_US
dc.date.accessioned2024-01-10T02:38:56Z-
dc.date.available2024-01-10T02:38:56Z-
dc.identifier.urihttp://hdl.handle.net/10397/103824-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Wang, Z., Wang, Z., Xiong, J., He, W., Yong, Z., & Wang, X. (2022). Responses of the Remote Sensing Drought Index with Soil Information to Meteorological and Agricultural Droughts in Southeastern Tibet. Remote Sensing, 14(23), 6125.is available at https://doi.org/10.3390/rs14236125.en_US
dc.subjectDrought monitoringen_US
dc.subjectTVMPDIen_US
dc.subjectSoil moistureen_US
dc.subjectMeteorological droughten_US
dc.subjectAgricultural droughten_US
dc.subjectSoutheastern Tibeten_US
dc.titleResponses of the remote sensing drought index with soil information to meteorological and agricultural droughts in southeastern Tibeten_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume14en_US
dc.identifier.issue23en_US
dc.identifier.doi10.3390/rs14236125en_US
dcterms.abstractThe Temperature-Vegetation-Precipitation-Drought Index (TVPDI) has a good performance in drought monitoring in China. However, different regions have different responses to droughts due to terrain differences. In southeastern Tibet, the drought monitoring capacity of some drought indices without soil information has to be assessed on account of the poor sensitivity between temperature and soil humidity. Therefore, soil moisture was added to calculate a new drought index based on TVPDI in southeastern Tibet, named the Temperature-Vegetation-Soil-Moisture-Precipitation-Drought Index (TVMPDI). Then, the TVMPDI was validated by using the Standardized Precipitation Evapotranspiration Index (SPEI) and other remote sensing drought indices, including the Vegetation Health Index (VHI) and Scale Drought Conditions Index (SDCI), during the growing seasons of 2003-2018. The Standardized Precipitation Index (SPI) and SPEI were used to represent meteorological drought and Gross Primary Productivity (GPP) was used to represent agricultural drought. The relation between TVMPDI and these drought indices was compared. Finally, the time trends of TVMPDI were also analyzed. The relation coefficients of TVMPDI and SPEI were above 0.5. The correlations between TVMPDI and drought indices, including the Vegetation Health Index (VHI) and Scale Drought Conditions Index (SDCI), also had a good performance. The correlation between the meteorological drought indices (SPI and SPEI) and TVMPDI were not as good as for the TVPDI, but the temporal correlation between the TVMPDI and GPP was greater than that between the TVPDI and GPP. This indicates that the TVMPDI is more suitable for monitoring agricultural drought than the TVPDI. In addition, historical drought monitoring had values that were consistent with those of the actual situation. The trend of the TVMPDI showed that drought in the study area was alleviated from 2003 to 2018. Furthermore, GPP was negatively correlated with SPEI (r = -0.4) and positively correlated with Soil Moisture (SM) drought index (TVMPDI, SMCI) (r = 0.4) in the eastern part of the study area, which suggests that SM, rather than precipitation, could promote the growth of vegetation in the region. A correct understanding of the role of soil information in drought comprehensive indices may monitor meteorological drought and agricultural drought more accurately.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationRemote sensing, Dec. 2022, v. 14, no. 23, 6125en_US
dcterms.isPartOfRemote sensingen_US
dcterms.issued2022-12-
dc.identifier.isiWOS:000896538600001-
dc.identifier.scopus2-s2.0-85143761521-
dc.identifier.eissn2072-4292en_US
dc.identifier.artn6125en_US
dc.description.validate202401 bcvc-
dc.description.oaVersion of Recorden_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextKey R & D project of Sichuan Science and Technology Department; Science and Technology Project of Xizang Autonomous Region; Strategic Priority Research Program of the Chinese Academy of Sciences; National Key R&D Program of Chinaen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
remotesensing-14-06125-v2.pdf6.58 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

99
Last Week
5
Last month
Citations as of Nov 9, 2025

Downloads

73
Citations as of Nov 9, 2025

SCOPUSTM   
Citations

9
Citations as of Dec 19, 2025

WEB OF SCIENCETM
Citations

9
Citations as of Dec 18, 2025

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.