Google Earth Engine平台下秦岭地区植被覆盖时空变化分析

doi:10.13474/j.cnki.11-2246.2022.0140

测绘通报 ›› 2022, Vol. 0 ›› Issue (5): 49-55.doi: 10.13474/j.cnki.11-2246.2022.0140

Google Earth Engine平台下秦岭地区植被覆盖时空变化分析

赵侃^1,2, 师芸^1,2, 牛敏杰^1,2

1. 西安科技大学测绘科学与技术学院, 陕西西安 710054;
2. 自然资源部煤炭资源勘察与综合利用重点实验室, 陕西西安 710021

收稿日期:2021-07-20 修回日期:2022-01-20 发布日期:2022-06-08
通讯作者: 师芸。E-mail:shiyun0908@hotmail.com
作者简介:赵侃(1997-),男,硕士生,主要研究方向为环境遥感。E-mail:19210061015@stu.xust.edu.cn
基金资助:
国家自然科学基金(41674013;41874012)

Research on the temporal and spatial changes of vegetation coverage in Qinling mountains based on Google Earth Engine platform

ZHAO Kan^1,2, SHI Yun^1,2, NIU Minjie^1,2

1. College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China;
2. Key Laboratory of Coal Resources Exploration and Comprehensive Utilization, Ministry of Land and Resources, Xi'an 710021, China

Received:2021-07-20 Revised:2022-01-20 Published:2022-06-08

摘要/Abstract

摘要： 秦岭地区植被覆盖动态变化对其生态环境有重要影响。本文利用Google Earth Engine云平台,选取1986—2019年Landsat TM/OLI地表反射率数据,结合像元二分模型估算秦岭地区植被覆盖度(FVC);通过年际变化斜率、变异系数、Hurst指数等评价指标,对FVC的时空变化、稳定性和持续性变化进行分析。此外,探究FVC与气温、降雨的耦合关系,并分析土地利用变化对FVC的影响。结果表明:34年间,秦岭地区FVC整体上呈现良好的状况,中高等及以上植被覆盖区达73.11%;FVC由1986年的62.86%增长到2019年的70.01%,植被活动在不断增强;FVC的变异系数均值为0.34,标准差为0.45,其稳定性与其空间分布呈高度自相关性;秦岭地区的植被覆盖变化受气候变化和人为因素的共同影响。

关键词: Google Earth Engine云平台, 秦岭, 植被覆盖度, 时空变化

Abstract: The dynamic change of vegetation cover in Qinling mountains has an important impact on its ecological environment. Based on the Google Earth Engine cloud platform, this paper selects the Landsat TM/OLI surface reflectance data from 1986 to 2019, combines with the dimidiate pixel model to estimate the fractional vegetation cover (FVC) in Qinling mountains. The spatiotemporal variation, stability and persistence of FVC are analyzed by using the slope of interannual variation, coefficient of variation and Hurst index. In addition, the coupling relationship between FVC and temperature and rainfall is explored,and the impact of land use change on FVC is analyzed. The results shows that:during the 34 years, FVC in Qinling region is in a good condition, with 73.11% vegetation coverage of medium, high and above; FVC will increase from 62.86% in 1986 to 70.01% in 2019, and vegetation activity will continue to increase; the mean coefficient of variation of FVC is 0.34, the standard deviation is 0.45, and its stability is highly autocorrelated with its spatial distribution; vegetation cover change in Qinling mountains is affected by climate change and human factors.

Key words: GEE cloud platform, Qinling mountains, fractional vegetation cover, temporal and spatial changes

中图分类号:

P237

赵侃, 师芸, 牛敏杰. Google Earth Engine平台下秦岭地区植被覆盖时空变化分析[J]. 测绘通报, 2022, 0(5): 49-55.

ZHAO Kan, SHI Yun, NIU Minjie. Research on the temporal and spatial changes of vegetation coverage in Qinling mountains based on Google Earth Engine platform[J]. Bulletin of Surveying and Mapping, 2022, 0(5): 49-55.

参考文献

[1] ZHOU Zhaoqiang, DING Yibo, SHI Haiyun, et al. Analysis and prediction of vegetation dynamic changes in China:past, present and future[J]. Ecological Indicators, 2020, 117:106642.
[2] 邓晨晖,白红英,高山,等.秦岭植被覆盖时空变化及其对气候变化与人类活动的双重响应[J].自然资源学报, 2018, 33(3):425-438.
[3] MU Xihan, ZHAO Tian, RUAN Gaiyan, et al. High spatial resolution and high temporal frequency (30-m/15-day) fractional vegetation cover estimation over China using multiple remote sensing datasets:method development and validation[J]. Journal of Meteorological Research, 2021, 35(1):128-147.
[4] 魏石磊,翟亮,桑会勇,等.像元分解模型的植被覆盖度遥感估算[J].测绘科学, 2016, 41(1):139-143.
[5] WU Donghai, WU Hao, ZHAO Xiang, et al. Evaluation of Spatiotemporal Variations of Global Fractional Vegetation Cover Based on Gimms Ndvi Data From 1982 to 2011[J]. Remote Sensing, 2014, 6(5):4217-4239.
[6] AMANI M, GHORBANIAN A, AHMADI S A, et al. Google earth engine cloud computing platform for remote sensing big data applications:a comprehensive review[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13:5326-5350.
[7] 唐志光,邓刚,李少为,等.基于Google Earth Engine的湖南省近30年不透水面时空变化研究[J].地理与地理信息科学, 2020, 36(2):41-46.
[8] HANSEN M C,POTAPOV P V,MOORE R, et al. High-resolution global maps of 21st-century forest cover change[J]. Science, 2013, 342(6160):850-853.
[9] CHEN B,XIAO X,LI X, et al. A mangrove forest map of China in 2015:analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform[J]. Isprs Journal of Photogrammetry and Remote Sensing, 2017, 131:104-120.
[10] 齐贵增,白红英,孟清,等. 1959-2018年秦岭南北春季气候时空变化特征[J].干旱区研究, 2019, 36(5):1079-1091.
[11] 崔晓临.秦岭地区土地利用/覆被变化及水热环境响应[D].西安:西北大学, 2013.
[12] 赵婷,白红英,邓晨晖,等. 2000-2016年秦岭山地植被覆盖变化地形分异效应[J].生态学报, 2019, 39(12):4499-4509.
[13] 孙华,白红英,张清雨,等.秦岭南北地区植被覆盖对区域环境变化的响应[J].环境科学学报, 2009, 29(12):2635-2641.
[14] 李宇宸,张军,薛宇飞,等.基于Google Earth Engine的中老缅交界区橡胶林分布遥感提取[J].农业工程学报, 2020, 36(8):174-181.
[15] 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.
[16] 张滔,唐宏.基于Google Earth Engine的京津冀2001-2015年植被覆盖变化与城镇扩张研究[J].遥感技术与应用, 2018, 33(4):593-599.
[17] 刘海,黄跃飞,郑粮.气候与人类活动对丹江口水源区植被覆盖变化的影响[J].农业工程学报, 2020, 36(6):97-105.
[18] 张成才,娄洋,李颖,等.基于像元二分模型的伏牛山地区植被覆盖度变化[J].水土保持研究, 2020, 27(3):301-307.
[19] 江田汉,邓莲堂. Hurst指数估计中存在的若干问题:以在气候变化研究中的应用为例[J].地理科学, 2004,24(2):177-182.
[20] 郭永强,王乃江,褚晓升,等.基于Google Earth Engine分析黄土高原植被覆盖变化及原因[J].中国环境科学, 2019, 39(11):4804-4811.

Google Earth Engine平台下秦岭地区植被覆盖时空变化分析

Research on the temporal and spatial changes of vegetation coverage in Qinling mountains based on Google Earth Engine platform

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	杨俊, 刘灵辉. 加权全极化SAR图像分类下的功能区土地时空变化特征提取[J]. 测绘通报, 2022, 0(7): 138-142,153.
[2]	王丽蒙, 王加胜, 杨昆, 王志敏, 粟凡婕, 陈鑫亚. 1990—2019年石漠化区耕地时空特征及成因分析——以富源县为例[J]. 测绘通报, 2022, 0(4): 77-82.
[3]	柳絮, 张宁, 徐晓天, 安超, 许士翔, 李程. 基于多源空间数据与空地协同的植被覆盖度估算——以东亚干草草原为例[J]. 测绘通报, 2022, 0(1): 39-43,55.
[4]	高照忠, 魏海霞, 黄铁兰. 粤港澳大湾区土地覆盖及景观格局时空变化分析[J]. 测绘通报, 2021, 0(5): 25-29.
[5]	王树祥, 韩留生, 杨骥, 李勇, 赵倩, 刘杨晓月, 吴昊. 一种改进的融合多指标荒漠化等级分类方法[J]. 测绘通报, 2021, 0(4): 8-12.
[6]	李广超, 赵海盟, 伍毅, 杨彬, 李丽和, 张洪, 杨泉光, 陈伟. 2000-2016年广西防城金花茶自然保护区关键生态环境参数时空变化[J]. 测绘通报, 2021, 0(2): 13-17.
[7]	陈伟, 王哲, 赵海盟, 李丽和, 张学鹏, 李广超. 利用线性融合方法进行金花茶自然保护区植被覆盖度时空变化研究[J]. 测绘通报, 2021, 0(11): 1-6.
[8]	石振武, 李驰. 黑龙江省呼玛至十八站公路路域生存环境质量评估[J]. 测绘通报, 2021, 0(11): 106-109,114.
[9]	胡洁, 姜成桢, 杨勇, 何晓锋, 李凯. 黑河中下游植被覆盖度变化遥感监测[J]. 测绘通报, 2021, 0(10): 34-38.
[10]	邵亚奎, 王蕾, 朱长明, 方晖, 张新, 黄端, 陶莉. GEE云平台支持下的西天山森林遥感监测与时空变化分析[J]. 测绘通报, 2020, 0(8): 13-17.
[11]	宋晓春, 刘兴科, 孙玮婕. 黑河流域MODIS气溶胶产品时空对比分析[J]. 测绘通报, 2020, 0(7): 64-69.
[12]	江杉, 王益澄, 马仁锋. 中国东海叶绿素浓度变化分析及其海水温度响应[J]. 测绘通报, 2020, 0(6): 39-44.
[13]	谭远模, 谢思梅, 谢荣安. 土地利用时空变化与城市化发展分析[J]. 测绘通报, 2020, 0(4): 139-142,146.
[14]	王科雯, 李晶, 王瑞国, 付晓. 胜利矿区植被覆盖度时序变化的空间异质性监测[J]. 测绘通报, 2020, 0(11): 1-6.
[15]	李晶, 崔绿园, 闫萧萧, 杨震, 董金玮, 邓晓娟. 草原矿区长时序植被覆盖度变化趋势对比分析[J]. 测绘通报, 2019, 0(8): 130-134,157.