Extraction of Vegetation Cover and Optimization of Vegetation Indices in a Desert Hinterland Oasis

Wang Ning; Zhou Mingtong; Wei Xuan; Guo Yuchuan

doi:10.13961/j.cnki.stbctb.2022.06.025

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Extraction of Vegetation Cover and Optimization of Vegetation Indices in a Desert Hinterland Oasis

- Extraction of Vegetation Cover and Optimization of Vegetation Indices in a Desert Hinterland Oasis
- Bulletin of Soiland Water Conservation Vol. 42, Issue 6, Pages: 197-205(2022)
- 作者机构：
  
  1. 新疆大学地理与遥感科学学院,新疆,乌鲁木齐,830017
  2. 绿洲生态教育部重点实验室,新疆,乌鲁木齐,830017
- 作者简介：
- 基金信息：
- DOI：10.13961/j.cnki.stbctb.2022.06.025
  CLC： Q948;TP79
- Published：2022
- 稿件说明：
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Wang Ning, Zhou Mingtong, Wei Xuan, et al. Extraction of Vegetation Cover and Optimization of Vegetation Indices in a Desert Hinterland Oasis[J]. Bulletin of Soiland Water Conservation, 2022, 42(6): 197-205.
DOI：

Wang Ning, Zhou Mingtong, Wei Xuan, et al. Extraction of Vegetation Cover and Optimization of Vegetation Indices in a Desert Hinterland Oasis[J]. Bulletin of Soiland Water Conservation, 2022, 42(6): 197-205. DOI： 10.13961/j.cnki.stbctb.2022.06.025.

摘要

[目的] 对沙漠腹地绿洲植被覆盖度提取及植被指数优选进行分析和研究，为该区选取最优植被指数反演极端干旱区绿洲植被覆盖状况提供科学依据。 [方法] 选取塔克拉玛干沙漠腹地达里雅布依绿洲天然植被作为研究对象，以无人机航拍样地影像获取的植被覆盖度为基准，采用Sentinel-2B卫星影像提取多种典型植被指数，运用回归统计方法建立植被指数-植被覆盖度统计模型，在卫星像元尺度上确定反演干旱绿洲覆盖度的最优植被指数。 [结果] ①利用Image J软件提取样方植被覆盖度精度较高，总体精度可达88.67%。 ②土壤调节型植被指数(SAVI，MSAVI)在标准回归系数、确定系数评价指标中表现良好，指示极端干旱区天然植被覆盖变化有较好的适用性。 [结论] 在极端干旱区，Image J提取稀疏植被效果较好，SAVI，MSAVI更适合绿洲植被覆盖变化研究。

Abstract

[Objective] The extraction of vegetation cover and optimization of vegetation indices in desert hinterland oasis were analyzed and studied in order to providing scientific basis for select the optimal vegetation indices to invert the vegetation cover status of extreme arid zone oasis. [Methods] Natural vegetation cover data from the Dariyabui Oasis in the hinterland of the Taklamakan Desert were obtained from UAV aerial photography sample images and used as the benchmark. A variety of typical vegetation indices were extracted from Sentinel-2B satellite images

and a vegetation index-vegetation cover statistical model was established using regression statistics to determine the optimal vegetation index for inversion to quantify arid oasis vegetation cover at the satellite image element scale. [Results] ① The accuracy of vegetation cover of the extracted samples using Image J software was high

and the overall accuracy reached 88.67%. ② The soil-regulated vegetation indices (SAVI

MSAVI) performed well as shown by standard regression coefficients and coefficients of determination

and had good applicability in reflecting natural vegetation cover changes in extreme arid zones. [Conclusion] In an extreme arid zone

Image J software did well in extracting sparse vegetation cover

and SAVI and MSAVI are the more suitable vegetation indices for oasis vegetation cover change studies.

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