Spatial and temporal change characteristics of vegetation coverage in Erhai Lake basin during 1988—2018

doi:10.6046/gtzyyg.2020283

Abstract
Figures/Tables
References
Related Articles
Metrics

Download: PDF(3584 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

As an important indicator reflecting the surface ecological environment, vegetation is widely used in the study of regional resources and environmental carrying capacity. Taking Erhai Lake basin as an example and based on the Google Earth Engine remote sensing big data cloud computing platform, the authors obtained the annual maximum normalized difference vegetation index (NDVI) value of Erhai Lake basin in 1988—2018 by using nearly 455 Landsat series images with 30 m resolution. The pixel binary model was used for quantitative estimation of fractional vegetation cover (FVC), and the spatial-temporal change characteristics of FVC in Erhai Lake basin were comprehensively analyzed through the linear regression model. Additionally, the internal relationship between FVC and geological lithology was investigated. The results are as follows: (1) From 1988 to 2018, the vegetation coverage of Erhai Lake basin showed a trend of continuous fluctuation growth, with a growth rate of 0.38%/a. (2) The basin was dominated by high vegetation coverage, of which 82.54% of the regional vegetation coverage continued to be improved, whereas the area of continuous degradation accounted for only 3.27%, which was mainly distributed in the area with significant urbanization. (3) the FVC varied in different types of lithological areas, among which the highest was metamorphic rock, and the lowest was dolomite and volcanic rock.

Keywords Google Earth Engine Erhai Lake basin fractional vegetation cover pixel binary model temporal and spatial changes analysis

ZTFLH:

TP79

Corresponding Authors: GUO Zhaocheng E-mail: chch1223@126.com;guozc@agrs.cn

Issue Date: 21 July 2021

	Service

	E-mail this article
	E-mail Alert
	RSS
	Articles by authors

	Hong CHEN
	Zhaocheng GUO
	Peng HE

Cite this article:

Hong CHEN,Zhaocheng GUO,Peng HE. Spatial and temporal change characteristics of vegetation coverage in Erhai Lake basin during 1988—2018[J]. Remote Sensing for Land & Resources, 2021, 33(2): 116-123.

URL:

https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020283 OR https://www.gtzyyg.com/EN/Y2021/V33/I2/116

Fig.1 Satellite image of Erhai Lake basin

Tab.1 Distribution of Landsat series images in Erhai Lake basin(1988—2018)(景)

Fig.2 Spatial distribution corresponding to different lithologic types in Erhai Lake basin

Fig.3 Inter-annual variations of FVC over Erhai Lake basin during 1988—2018

Fig.4 FVC Inter-annual change trend of FVC in Erhai Basic (1988—2018)

Fig.5 Comparison of the FVC distribution at Erhai Lake basin in four periods (1988—2018)

Tab.2 Vegetation coverage area and rate of different levels of FVC in Erhai Basin from 1988 to 2018

Fig.6 Changes of FVC values corresponding to different lithologic types in Erhai Lake basin

[1]	Jong R D, Bruin S D, Wit A D, et al. Analysis of monotonic greening and browning trends from global NDVI time-series[J]. Remote Sensing of Environment, 2011, 115(2):692-702. doi: 10.1016/j.rse.2010.10.011 url: https://linkinghub.elsevier.com/retrieve/pii/S0034425710003160
[2]	Gitelson A A, Kaufman Y J, Stark R, et al. Novel algorithms for remote estimation of vegetation fraction[J]. Remote Sensing of Environment, 2002, 80(1):76-87. doi: 10.1016/S0034-4257(01)00289-9 url: https://linkinghub.elsevier.com/retrieve/pii/S0034425701002899
[3]	贾坤, 姚云军, 魏香琴, 等. 植被覆盖度遥感估算研究进展[J]. 地球科学进展, 2013, 28(7):774-782.
[3]	Jia K, Yao Y J, Wei X Q, et al. A review on fractional vegetation cover estimation using remote sensing[J]. Advances in Earth Science, 2013, 28(7):774-782.
[4]	Voorde T V D, Vlaeminck J, Canters F. Comparing different approaches for mapping urban vegetation cover from Landsat ETM+ data:A case study on Brussels[J]. Sensors, 2008, 8(6):3880-3902. pmid: 27879914
[5]	Zhang X, Liao C, Li J, et al. Fractional vegetation cover estimation in arid and semi-arid environments using HJ-1 satellite hyperspectral data[J]. International Journal of Applied Earth Observation and Geoinformation, 2013, 21(1):506-512. doi: 10.1016/j.jag.2012.07.003 url: https://linkinghub.elsevier.com/retrieve/pii/S0303243412001419
[6]	李苗苗, 吴炳方, 颜长珍, 等. 密云水库上游植被覆盖度的遥感估算[J]. 资源科学, 2004, 26(4):153-159.
[6]	Li M M, Wu B F, Yan C Z, et al. Estimation of vegetation fraction in the upper basin of Miyun reservoir by remote sensing[J]. Resource Science, 2004, 26(4):153-159.
[7]	陈效逑, 王恒. 1982—2003年内蒙古植被带和植被覆盖度的时空变化[J]. 地理学报, 2009, 64(1):84-94.
[7]	Chen X Q, Wang H. Spatial and temporal variations of vegetation belts and vegetation cover degrees in inner Mongolia from 1982 to 2003[J]. Acta Geographica Sinica, 2009, 64(1):84-94.
[8]	刘宪锋, 朱秀芳, 潘耀忠, 等. 1982—2012年中国植被覆盖时空变化特征[J]. 生态学报, 2015, 35(16):59-70.
[8]	Liu X F, Zhu X F, Pan Y Z, et al. Spatiotemporal changes in vegetation coverage in China during 1982—2012[J]. Acta Ecologica Sinica, 2015, 35(16):59-70.
[9]	刘宪锋, 潘耀忠, 朱秀芳, 等. 2000—2014年秦巴山区植被覆盖时空变化特征及其归因[J]. 地理学报, 2015, 70(5):705-716. doi: 10.11821/dlxb201505003
[9]	Liu X F, Pan Y Z, Zhu X F, et al. Spatiotemporal variation of vegetation coverage in Qinling-Daba Mountains in relation to environmental factors[J]. Acta Geographica Sinica, 2015, 70(5):705-716.
[10]	郑朝菊, 曾源, 赵玉金, 等. 近15年中国西南地区植被覆盖度动态变化[J]. 国土资源遥感, 2017, 29(3):128-136.doi: 10.6046/gtzyyg.2017.03.19. doi: 10.6046/gtzyyg.2017.03.19
[10]	Zheng Z J, Zeng Y, Zhao Y J, et al. Monitoring and dynamic analysis of fractional vegetation cover in southwestern China over the past 15 years based on MODIS data[J]. Remote Sensing for Land and Resources, 2017, 29(3):128-136.doi: 10.6046/gtzyyg.2017.03.19. doi: 10.6046/gtzyyg.2017.03.19
[11]	房世波, 谭凯炎, 刘建栋, 等. 鄂尔多斯植被盖度分布与环境因素的关系[J]. 植物生态学报, 2009, 33(1):30-38.
[11]	Fang S B, Tan K Y, Liu J D, et al. Vegetation cover and its relationship with environmental factors at different scales in the Ordos region of China[J]. Chinese Journal of Plant Ecology, 2009, 33(1):30-38.
[12]	Amiri R, Weng Q, Alimohammadi A, et al. Spatial-temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area,Iran[J]. Remote Sensing of Environment, 2009, 113(12):2606-2617. doi: 10.1016/j.rse.2009.07.021 url: https://linkinghub.elsevier.com/retrieve/pii/S0034425709002405
[13]	张晓东, 刘湘南, 赵志鹏, 等. 基于像元二分法的盐池县植被覆盖度与地质灾害点时空格局分析[J]. 国土资源遥感, 2018, 30(2):195-201.doi: 10.6046/gtzyyg.2018.02.26. doi: 10.6046/gtzyyg.2018.02.26
[13]	Zhang X D, Liu X N, Zhao Z P, et al, Spatial-temporal pattern analysis of the vegetation coverage and geological hazards in Yanchi county based on dimidiate pixel model[J]. Remote Sensing for Land and Resources, 2018, 30(2):195-201.doi: 10.6046/gtzyyg.2018.02.26. doi: 10.6046/gtzyyg.2018.02.26
[14]	高雁, 刘蜀鄂, 雷琳. 洱海流域植被覆盖度遥感估算与变化分析[J]. 林业调查规划, 2011, 36(6):10-12.
[14]	Gao Y, Liu S E, Lei L. RS estimation of vegetation coverage and change analysis in Erhai basin[J]. Forest Inventory and Planning, 2011, 36(6):10-12.
[15]	裴杰, 牛铮, 王力, 等. 基于Google Earth Engine云平台的植被覆盖度变化长时间序列遥感监测[J]. 中国岩溶, 2018, 37(4):136-144.
[15]	Pei J, Niu Z, Wang L, et al, Monitoring to variations of vegetation cover using long-term time series remote sensing data on the Google Earth Engine cloud platform[J]. Carsologica Sinica, 2018, 37(4):136-144.
[16]	Busetto L, Meroni M, Colombo R. Combining medium and coarse spatial resolution satellite data to improve the estimation of sub-pixel NDVI time series[J]. Remote Sensing of Environment, 2008, 112(1):118-131. doi: 10.1016/j.rse.2007.04.004 url: https://linkinghub.elsevier.com/retrieve/pii/S0034425707001563
[17]	Leprieur C, Verstraete M M, Pinty B. Evaluation of the performance of various vegetation indices to retrieve vegetation cover from AVHRR data[J]. Remote Sensing Reviews, 1994, 10(4):265-284. doi: 10.1080/02757259409532250 url: http://www.tandfonline.com/doi/abs/10.1080/02757259409532250
[18]	李苗苗. 植被覆盖度的遥感估算方法研究[D]. 北京:中国科学院研究生院(遥感应用研究所), 2003.
[18]	Li M M. The method of vegetation fraction estimation by remote sensing[D]. Beijing:Graduate School of Chinese Academy of Sciences(Institute of Remote Sensing Applications), 2003.
[19]	Stow D, Daeschner S, Hope A, et al. Variability of the seasonally integrated normalized difference vegetation index across the north slope of Alaska in the 1990s[J]. International Journal of Applied Earth Observation and Geoinformation, 2003, 24(5):1111-1117.
[20]	席冬梅, 邓卫东, 高宏光, 等. 云南省主要地质背景区土壤理化性质及矿物质元素丰度分析[J]. 土壤, 2008, 40(1):114-120.
[20]	Xi D M, Deng W D, Gao H G, et al. Physico-chemical properties of rocks and soils and abundances of minerals in main geological background areas in Yunnan province[J]. Soils, 2008, 40(1):114-120.
[21]	章明奎, 姚玉才, 邱志腾, 等. 中国南方碳酸盐岩发育土壤的成土特点与系统分类[J]. 浙江大学学报(农业与生命科学版), 2019, 45(1):60-71.
[21]	Zhang M K, Yao Y C, Qiu Z T, et al. Pedogenetic characteristics and taxonomic classification of soils developed from carbonate rocks in the south of China[J]. Journal of Zhejiang University(Agriculture and Life Sciences), 2019, 45(1):60-71.
[22]	徐烨, 邓艳, 曹建华, 等. 云南小江流域不同土地利用类型土壤微量元素的对比分析[J]. 中国岩溶, 2018, 37(5):116-124.
[22]	Xu Y, Deng Y, Cao J H, et al. Comparative analysis of soil trace elements in different land use types in Xiaojiang river basin,Yunnan[J]. Carsologica Sinica, 2018, 37(5):116-124.

[1]	YU Sen, JIA Mingming, CHEN Gao, LU Yingying, LI Yi, ZHANG Bochun, LU Chunyan, LI Huiying. A study of the disturbance to mangrove forests in Dongzhaigang, Hainan based on LandTrendr[J]. Remote Sensing for Natural Resources, 2023, 35(2): 42-49.
[2]	ZHU Lin, HUANG Yuling, YANG Gang, SUN Weiwei, CHEN Chao, HUANG Ke. Information extraction and spatio-temporal evolution analysis of the coastline in Hangzhou Bay based on Google Earth Engine and remote sensing technology[J]. Remote Sensing for Natural Resources, 2023, 35(2): 50-60.
[3]	CHEN Huixin, CHEN Chao, ZHANG Zili, WANG Liyan, LIANG Jintao. A remote sensing information extraction method for intertidal zones based on Google Earth Engine[J]. Remote Sensing for Natural Resources, 2022, 34(4): 60-67.
[4]	LI Yi, CHENG Lina, LU Yingying, ZHANG Bochun, YU Sen, JIA Mingming. A study on the changes in coastal tidal flats in the Laizhou Bay based on MSIC and OTSU[J]. Remote Sensing for Natural Resources, 2022, 34(4): 68-75.
[5]	ZHU Qi, GUO Huadong, ZHANG Lu, LIANG Dong, LIU Xuting, WAN Xiangxing. Classification of tropical natural forests in Hainan Island based on multi-temporal Landsat8 remote sensing images[J]. Remote Sensing for Natural Resources, 2022, 34(2): 215-223.
[6]	LUO Hongjian, MING Dongping, XU Lu. Time series calculation of remote sensing ecological index based on GEE[J]. Remote Sensing for Natural Resources, 2022, 34(2): 271-277.
[7]	FANG Mengyang, LIU Xiaohuang, KONG Fanquan, LI Mingzhe, PEI Xiaolong. A method for creating annual land cover data based on Google Earth Engine: A case study of the Yellow River basin[J]. Remote Sensing for Natural Resources, 2022, 34(1): 135-141.
[8]	ZHENG Xiucheng, ZHOU Bin, LEI Hui, HUANG Qiyu, YE Haolin. Extraction and spatio-temporal change analysis of the tidal flat in Cixi section of Hangzhou Bay based on Google Earth Engine[J]. Remote Sensing for Natural Resources, 2022, 34(1): 18-26.
[9]	YAO Jinxi, ZHANG Zhi, ZHANG Kun. An analysis of the characteristics, causes, and trends of spatio-temporal changes in vegetation in the Nuomuhong alluvial fan based on Google Earth Engine[J]. Remote Sensing for Natural Resources, 2022, 34(1): 249-256.
[10]	LAI Peiyu, HUANG Jing, HAN Xujun, MA Mingguo. An analysis of impacts from water impoundment in Three Gorges Dam Project on surface water in Chongqing area base on Google Earth Engine[J]. Remote Sensing for Natural Resources, 2021, 33(4): 227-234.
[11]	LIU Yongmei, FAN Hongjian, GE Xinghua, LIU Jianhong, WANG Lei. Estimation accuracy of fractional vegetation cover based on normalized difference vegetation index and UAV hyperspectral images[J]. Remote Sensing for Natural Resources, 2021, 33(3): 11-17.
[12]	YE Wantong, CHEN Yihong, LU Yinhao, Wu Penghai. Spatio-temporal variation of land surface temperature and land cover responses in different seasons in Shengjin Lake wetland during 2000—2019 based on Google Earth Engine[J]. Remote Sensing for Land & Resources, 2021, 33(2): 228-236.
[13]	MOU Xiaoli, LI He, HUANG Chong, LIU Qingsheng, LIU Gaohuan. Application progress of Google Earth Engine in land use and land cover remote sensing information extraction[J]. Remote Sensing for Land & Resources, 2021, 33(2): 1-10.
[14]	ZHANG Chengcai, LUO Weiran, DOU Xiaonan, WANG Jinxin. Research on the method of using Landsat8 data to improve FCD model[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(4): 33-38.
[15]	ZHENG Zhaoju, ZENG Yuan, ZHAO Yujin, ZHAO Dan, WU Bingfang. Monitoring and dynamic analysis of fractional vegetation cover in southwestern China over the past 15 years based on MODIS data[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(3): 128-136.

Viewed

Full text

Abstract

Cited

Shared

Discussed