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刘朔, 杨建勇, 蔡凡隆. 基于Landsat 8的若尔盖县沙化监测区NDVI植被覆盖变化特征分析[J]. 四川林业科技, 2022, 43(1): 50−56. DOI: 10.12172/202104200001
引用本文: 刘朔, 杨建勇, 蔡凡隆. 基于Landsat 8的若尔盖县沙化监测区NDVI植被覆盖变化特征分析[J]. 四川林业科技, 2022, 43(1): 50−56. DOI: 10.12172/202104200001
LIU S, YANG J Y, CAI F L. Analysis of NDVI vegetation cover change characteristics in desertification monitoring areas of Zoige county based on landsat 8[J]. Journal of Sichuan Forestry Science and Technology, 2022, 43(1): 50−56. DOI: 10.12172/202104200001
Citation: LIU S, YANG J Y, CAI F L. Analysis of NDVI vegetation cover change characteristics in desertification monitoring areas of Zoige county based on landsat 8[J]. Journal of Sichuan Forestry Science and Technology, 2022, 43(1): 50−56. DOI: 10.12172/202104200001

基于Landsat 8的若尔盖县沙化监测区NDVI植被覆盖变化特征分析

Analysis of NDVI Vegetation Cover Change Characteristics in Desertification Monitoring Areas of Zoige County Based on Landsat 8

  • 摘要: 以若尔盖县第五次沙化监测图斑区为研究区,采用2013年、2015年、2017年3个年度10月初的 Landsat 8影像提取NDVI,通过像元二分模型反演植被覆盖度(FC),再将NDVI和FC进行分级后,进行各级别的面积转移矩阵分析,同时也与沙化程度进行相关性分析。研究表明:(1)NDVI和FC从2013年、2015年、2017年都呈显著增加趋势,NDVI中位数值从2013年的0.4775,增加到2015年0.5374,至2017年达0.5921;FC中位数值从2013年的0.5305,增加到2015年0.5971,至2017年达0.6578。(2)NDVI和FC各级别的面积转移矩阵中,具体转化方向一致,主要是向高植被方向转化,表现为:中等级向较高等级转化;较低等级向中等级转化;低等级向较低等级转化。(3)NDVI 及FC等级与研究区2015年监测的沙化程度均呈显著正相关,说明本次NDVI 及植被覆盖度重分类等级的划分基本符合研究区沙化植被覆盖度现状,研究方法及结果可为沙化监测提供数据和技术支撑。

     

    Abstract: In this paper, the fifth desertification monitoring area in Zoige county was selected as the research area, and the NDVI was extracted from Landsat 8 images in early October of 2013, 2015 and 2017. The vegetation coverage (FC) was inversed by the dimidiate pixel model. After classifying the NDVI and FC, the area transfer matrix of each level was analyzed, and the correlation analysis between NDVI , FC and the desertification degree was also analyzed. The results showed that: (1) The NDVI and FC showed a significant increasing trend from 2013, 2015 and 2017, with the median value of NDVI increasing from 0.4775 in 2013 to 0.5374 in 2015 and reaching 0.5921 in 2017; the median value of FC increased from 0.5305 in 2013 to 0.5971 in 2015 and reached 0.6578 in 2017. (2) In the area transfer matrix of NDVI and FC levels, the specific transformation direction was the same, mainly to the direction of higher vegetation, which was shown as: the medium level to the higher level; the lower grade to the medium grade; the low level to the lower level. (3) The NDVI and FC levels were significantly positively correlated with the desertification degree monitored in 2015, indicating that the classification of NDVI and vegetation coverage reclassification grades was basically in line with the current situation of desertification vegetation coverage in the study area. The research methods and results could provide data and technical support for desertification monitoring.

     

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