File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher

임정호

Im, Jungho
Intelligent Remote sensing and geospatial Information Science Lab.
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

Full metadata record

DC Field Value Language
dc.citation.startPage 112145 -
dc.citation.title REMOTE SENSING OF ENVIRONMENT -
dc.citation.volume 252 -
dc.contributor.author Son, Bokyung -
dc.contributor.author Park, Sumin -
dc.contributor.author Im, Jungho -
dc.contributor.author Park, Seohui -
dc.contributor.author Ke, Yinghai -
dc.contributor.author Quackenbush, Lindi J. -
dc.date.accessioned 2023-12-21T16:36:21Z -
dc.date.available 2023-12-21T16:36:21Z -
dc.date.created 2021-02-03 -
dc.date.issued 2021-01 -
dc.description.abstract In this research, a new drought monitoring approach with an adaptive index-Vector Projection Analysis (VPA) and Vector Projection Index of Drought (VPID)- was developed that considers multiple drought indicators in various climate zones across the Contiguous United States (CONUS) and East Asia. A major advantage of VPA is that it uses multiple dependent variables (i.e., surface-based drought indices) and multiple independent variables (i.e., satellite-derived drought factors) to capture varied climate and environmental characteristics. Therefore, the VPA-based indices can be adopted for different drought types (i.e., meteorological, agricultural and hydrological droughts) depending on the user's selection of drought factors and indices. In VPA, the weights of each drought factor are generated through correlations (r) between each dependent variable and a satellite-derived drought factor that is obtained from the new generation sensor systems, Visible Infrared Imaging Radiometer Suite (VIIRS) and Global Precipitation Mission (GPM). Three schemes of VPID with different combinations of variables focused on integrated-, short-, and long-term drought (VPIDinte, VPIDshort, and VPIDlong, respectively) were evaluated over the CONUS and East Asia. All three schemes showed good agreement with surface-based drought indices resulting in averaged r (from 0.42 to 0.68) across both study areas. While VPIDshort or VPIDlong were more correlated with short (1-3 months) or long (9-12 months) term surface-based drought indices, VPIDinte provided a more generalized (i.e., integrated from 1 to 12 months) index that is suitable for varied drought conditions. The spatial distributions of drought from VPIDs agreed with United States Drought Monitor (USDM) data and Emergency Events Database across East Asia for both extreme drought and normal conditions. In particular, the drought areas of VPIDinte corresponded with the USDM results with r = 0.83 and root mean square error = 9.4%. Crop yield trends were also consistent with the VPIDs results in most years for both study areas. The proposed approach, VPA and VPID, can be adopted for any region with different combinations of surface-based drought indices and satellite-derived drought factors. -
dc.identifier.bibliographicCitation REMOTE SENSING OF ENVIRONMENT, v.252, pp.112145 -
dc.identifier.doi 10.1016/j.rse.2020.112145 -
dc.identifier.issn 0034-4257 -
dc.identifier.scopusid 2-s2.0-85094326677 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/49924 -
dc.identifier.url https://www.sciencedirect.com/science/article/pii/S0034425720305186?via%3Dihub -
dc.identifier.wosid 000595876800002 -
dc.language 영어 -
dc.publisher ELSEVIER SCIENCE INC -
dc.title A new drought monitoring approach: Vector Projection Analysis (VPA) -
dc.type Article -
dc.description.isOpenAccess FALSE -
dc.relation.journalWebOfScienceCategory Environmental Sciences; Remote Sensing; Imaging Science & Photographic Technology -
dc.relation.journalResearchArea Environmental Sciences & Ecology; Remote Sensing; Imaging Science & Photographic Technology -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Drought indices -
dc.subject.keywordAuthor Vector Projection Analysis -
dc.subject.keywordAuthor Vector Projection Index of Drought -
dc.subject.keywordAuthor VIIRS -
dc.subject.keywordAuthor GPM -
dc.subject.keywordAuthor CONUS -
dc.subject.keywordAuthor East Asia -
dc.subject.keywordPlus MULTISENSOR INTEGRATED INDEX -
dc.subject.keywordPlus AGRICULTURAL DROUGHT -
dc.subject.keywordPlus SOIL-MOISTURE -
dc.subject.keywordPlus METEOROLOGICAL DROUGHT -
dc.subject.keywordPlus HYDROLOGICAL DROUGHT -
dc.subject.keywordPlus POTENTIAL EVAPOTRANSPIRATION -
dc.subject.keywordPlus VEGETATION HEALTH -
dc.subject.keywordPlus RESPONSE INDEX -
dc.subject.keywordPlus PRECIPITATION -
dc.subject.keywordPlus IMPACT -

qrcode

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