A high-precision oasis dataset for China from remote sensing images.

Jingwu Lin, Dongwei Gui, Yunfei Liu, Qi Liu, Siyuan Zhang, Chuang Liu
Author Information
  1. Jingwu Lin: State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China.
  2. Dongwei Gui: State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China. guidwei@ms.xjb.ac.cn.
  3. Yunfei Liu: State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China.
  4. Qi Liu: State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China.
  5. Siyuan Zhang: State Key Laboratory of Desert and Oasis Ecology, Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China.
  6. Chuang Liu: Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China. liuchuang@igsnrr.ac.cn.

Abstract

High-resolution oasis maps are imperative for understanding ecological and socio-economic development of arid regions. However, due to the late establishment and relatively niche nature of the oasis discipline, there are no high-precision datasets related to oases in the world to date. To fill this gap, detailed visual interpretation of remote sensing images on Google Earth Professional or Sentinel-2 was conducted in summer 2020, and for the first time, a high-precision dataset of China's oases (abbreviation HDCO) with a resolution of 1 meter was constructed. HDCO comprises 1,466 oases with a total area of 277,375.56 km. The kappa coefficient for this dataset validated by the field survey was 0.8686 and the AUC value for the ROC curve was 0.935. In addition, information on the geographic coordinates, climatic conditions, major landforms, and hydrological features of each oasis was added to the attribute table of the dataset. This dataset enables researchers to quantitatively monitor location and area of oases, fosters exploration of the relationship between oases and human under climate change and urbanization.

References

  1. Sci Data. 2022 Aug 25;9(1):519 [PMID: 36008422]
  2. Biochem Med (Zagreb). 2012;22(3):276-82 [PMID: 23092060]
  3. Environ Monit Assess. 2016 Jan;188(1):35 [PMID: 26676411]
  4. Science. 2020 Feb 14;367(6479):787-790 [PMID: 32054762]
  5. Sci Rep. 2020 May 26;10(1):8672 [PMID: 32457337]
  6. Sci Rep. 2016 Oct 14;6:35418 [PMID: 27739500]
  7. Nature. 2021 Apr;592(7856):E28 [PMID: 33854242]
  8. Sci Rep. 2020 Oct 19;10(1):17708 [PMID: 33077843]
  9. Sci Rep. 2023 Nov 8;13(1):19424 [PMID: 37940666]
  10. Sci Rep. 2017 Aug 10;7(1):7723 [PMID: 28798390]

Grants

  1. 42171042/National Natural Science Foundation of China (National Science Foundation of China)

Word Cloud

Created with Highcharts 10.0.0oasesdatasetoasishigh-precisionremotesensingimagesHDCO1area0High-resolutionmapsimperativeunderstandingecologicalsocio-economicdevelopmentaridregionsHoweverduelateestablishmentrelativelynichenaturedisciplinedatasetsrelatedworlddatefillgapdetailedvisualinterpretationGoogleEarthProfessionalSentinel-2conductedsummer2020firsttimeChina'sabbreviationresolutionmeterconstructedcomprises466total27737556 kmkappacoefficientvalidatedfieldsurvey8686AUCvalueROCcurve935additioninformationgeographiccoordinatesclimaticconditionsmajorlandformshydrologicalfeaturesaddedattributetableenablesresearchersquantitativelymonitorlocationfostersexplorationrelationshiphumanclimatechangeurbanizationChina

Similar Articles

Cited By