干旱地区遥感生态指数的改进——以乌兰布和沙漠为例

doi:10.13287/j.1001-9332.202011.011

应用生态学报 ›› 2020, Vol. 31 ›› Issue (11): 3795-3804.doi: 10.13287/j.1001-9332.202011.011

干旱地区遥感生态指数的改进——以乌兰布和沙漠为例

王杰¹, 马佳丽¹, 解斐斐^2*, 徐锡杰³

¹内蒙古大学生态与环境学院, 呼和浩特 010021;
²山东科技大学测绘科学与工程学院, 山东青岛 266590;
³中国科学院大学资源与环境学院, 北京 100190

收稿日期:2020-06-08 接受日期:2020-08-13 出版日期:2020-11-15 发布日期:2021-06-10
通讯作者: * E-mail: xff@sdust.edu.cn
作者简介:王杰, 女, 1995年生, 硕士研究生。主要从事生态环境遥感研究。E-mail: 31815035@mail.imu.edu.cn
基金资助:
城市空间信息工程北京市重点实验室项目(2019209)和山东省高等学校科技计划项目(J18KA214)资助

Improvement of remote sensing ecological index in arid regions: Taking Ulan Buh Desert as an example

WANG Jie¹, MA Jia-li¹, XIE Fei-fei^2*, XU Xi-jie³

¹School of Ecology and Environment, Inner Mongolia University, Hohhot 010021, China;
²College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, Shandong, China;
³College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China

Received:2020-06-08 Accepted:2020-08-13 Online:2020-11-15 Published:2021-06-10
Contact: * E-mail: xff@sdust.edu.cn
Supported by:
the Fund of Beijing Key Laboratory of Urban Spatial Information Engineering (2019209) and the Project of Shandong Province Higher Educational Science and Technology Program (J18KA214).

摘要/Abstract

摘要： 干旱区以荒漠为主要背景,生态环境脆弱,极易受到自然和人为因素的影响。为了定量评价干旱区生态环境质量,基于遥感生态指数(RSEI),针对干旱区对其进行改进,构建了干旱遥感生态指数(ARSEI),该指数耦合了绿度、湿度、盐度、热度以及土地退化度信息。利用ARSEI和RSEI对乌兰布和沙漠2000—2019年生态环境质量进行动态监测和评价,分析两者的差别及在干旱区的适用性。同时分析乌兰布和沙漠生态环境质量时空变化特征及原因。结果表明: ARSEI比RSEI对干旱区生态环境质量具有更好的适用性,ARSEI增强了土地利用类型变化在生态环境质量评价中的作用。2000—2019年,乌兰布和沙漠生态环境质量整体上为差。等级为优、良、中的部分主要分布在沙漠北部,等级为差的部分主要集中在戈壁和沙地处,较差主要在低覆盖度植被区。2000—2019年,乌兰布和沙漠生态环境质量总体变好,沙漠北部城镇或农场生态环境质量变化复杂,变差和变好交替分布。生态农业和沙产业对生态环境质量有明显的改善作用,这是乌兰布和沙漠生态环境质量变化的主要原因。

关键词: 生态环境质量, 干旱遥感生态指数, 遥感动态监测, 主成分分析, 乌兰布和沙漠

Abstract: The arid area is mainly composed of desert, with fragile eco-environment and being extremely vulnerable to the influence of natural and human perturbations. Based on the remote sen-sing ecological index (RSEI), the arid remote sensing ecological index (ARSEI) was formed to improve the remote sensing ecological index for arid area, which was coupled with the information of greenness, humidity, salinity, heat and land degradation to quantitatively evaluate the eco-environment quality. We used ARSEI and RSEI to dynamically monitor and evaluate the eco-environment quality of Ulan Buh Desert from 2000 to 2019, and analyzed their differences and their applicability in arid area. We further examined the characteristics and reasons of the temporal and spatial variations of the eco-environment quality of Ulan Buh Desert. The results showed that the ARSEI index had better applicability to the eco-environment quality in arid area than the RSEI, and it enhanced the role of land use changes in the ecological environment quality assessment. From 2000 to 2019, the overall eco-environmental quality of Ulan Buh Desert was worse. The parts under better, good, and medium grades were mainly distributed in the northern region, the parts with worse grades were mainly concentrated in the gobi and sandy land, and the poor ones were mainly located in area with low coverage vegetation. From 2000 to 2019, the overall quality of the eco-environment in the Ulan Buh Desert were becoming better. Meanwhile, the eco-environment quality of towns and farms in the northern part of the desert changed complexly, with deterioration and improvement alternately distributed. The main reason for the changes in the eco-environment of Ulan Buh Desert was the positive effects of ecological agriculture and sand industry.

Key words: ecological environment quality, arid remote-sensing ecological index, remote sensing dynamic monitoring, principal component analysis, Ulan Buh Desert

王杰, 马佳丽, 解斐斐, 徐锡杰. 干旱地区遥感生态指数的改进——以乌兰布和沙漠为例[J]. 应用生态学报, 2020, 31(11): 3795-3804.

WANG Jie, MA Jia-li, XIE Fei-fei, XU Xi-jie. Improvement of remote sensing ecological index in arid regions: Taking Ulan Buh Desert as an example[J]. Chinese Journal of Applied Ecology, 2020, 31(11): 3795-3804.

参考文献

[1] 布日古德, 塔娜, 达来. 干旱半干旱地区生态环境问题及修复. 山东工业技术, 2017(13): 287 [Bu R-G-D, Ta N, Da L. Ecological environment problems and restoration in arid and semi-arid areas. Shandong Industrial Technology, 2017(13): 287]
[2] 孙权, 张显峰, 江淼. 干旱区生态环境敏感参量遥感反演与评价系统研究. 北京大学学报:自然科学版, 2011, 47(6): 1073-1080 [Sun Q, Zhang X-F, Jiang M. Eco-environmental variables estimation from remotely sensed data and eco-environmental assessment: Models and system. Acta Scientiarum Naturalium Universitatis Pekinensis, 2011, 47(6): 1073-1080]
[3] 彭建, 党威雄, 刘焱序, 等. 景观生态风险评价研究进展与展望. 地理学报, 2015, 70(4): 664-677 [Peng J, Dang W-X, Liu Y-X, et al. Review on landscape ecological risk assessment. Acta Geographica Sinica, 2015, 70(4): 664-677]
[4] 周玲美, 王世航. 内蒙古杭锦旗生态环境时空变化的遥感监测与评价. 应用生态学报, 2020, 31(6): 1999-2006 [Zhou L-M, Wang S-H. Remote sensing monitoring and evaluation of spatial and temporal changes of ecological environment in Hangjin Banner, Inner Mongolia, China. Chinese Journal of Applied Ecology, 2020, 31(6): 1999-2006]
[5] 生态环境部. 生态环境状况评价技术规范: HJ 192—2015. 北京: 中国环境科学出版社, 2015 [Ministry of Ecology and Environment of the People's Republic of China. Technical Criterion for Ecosystem Status Evaluation: HJ 192-2015. Beijing: China Environmental Science Press, 2015]
[6] 中国气象局. 生态质量气象评价方法. 北京: 中国气象局, 2007 [China Meteorological Administration. Meteorological Assessment Method of Ecological Qualities. Beijing: China Meteorological Administration, 2007]
[7] 徐涵秋. 城市遥感生态指数的创建及其应用. 生态学报, 2013, 33(24): 7853-7862 [Xu H-Q. A remote sensing urban ecological index and its application. Acta Ecologica Sinica, 2013, 33(24): 7853-7862]
[8] Shi Z, Li H. Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation. Environmental Monitoring and Assessment, 2007, 128: 217-229
[9] 蒋超亮, 吴玲, 刘丹, 等. 干旱荒漠区生态环境质量遥感动态监测——以古尔班通古特沙漠为例. 应用生态学报, 2019, 30(3): 877-883 [Jiang C-L, Wu L, Liu D, et al. Dynamic monitoring of eco-environmental quality in arid desert area by remote sensing: Taking the Gurbantunggut Desert, China as an example. Chinese Journal of Applied Ecology, 2019, 30(3): 877-883]
[10] 李清云, 杨勇强, 王振锡, 等. 基于TM数据的阿克苏市生态环境质量指数RSEI动态变化分析. 西南农业学报, 2019, 32(7): 1646-1651 [Li Q-Y, Yang Y-Q, Wang Z-X, et al. Dynamic change analysis of remote sensing ecological index in Aksu based on TM data ana-lysis. Southwest China Journal of Agricultural Sciences, 2019, 32(7): 1646-1651]
[11] Jing Y, Zhang F, He Y, et al. Assessment of spatial and temporal variation of ecological environment quality in Ebinur Lake Wetland National Nature Reserve, Xinjiang, China. Ecological Indicators, 2020, 110: 10.1016/j.ecolind.2019.105874
[12] Hu XS, Xu HQ. A new remote sensing index for asses-sing the spatial heterogeneity in urban ecological quality: A case from Fuzhou City, China. Ecological Indicators, 2018, 89: 11-21
[13] 王凤歌. 乌兰布和沙漠生态系统服务时空动态与权衡分析. 硕士论文. 呼和浩特: 内蒙古大学, 2019 [Wang F-G. Spatiao-Temporal Dynamics and Trade-Offs Analysis of Ecosystem Services in Ulan Buh Desert. Master Thesis. Hohhot: Inner Mongolia University, 2019]
[14] 贾宝全, 陈利军, 杨维西, 等. 乌兰布和沙漠地区土地利用动态变化分析. 干旱区研究, 2007, 24(5): 610-617 [Jia B-Q, Chen L-J, Yang W-X, et al. Ana-lysis on the dynamic land use change in the Ulan Buh Desert Region. Arid Zone Research, 2007, 24(5): 610-617]
[15] 韩永光, 任昱, 张秋良. 乌兰布和沙漠绿洲沙产业(农业)开发的环境风险与保护对策研究. 干旱区资源与环境, 2012, 26(11): 25-30 [Han Y-G, Ren Y, Zhang Q-L. Environmental risks of deserticulture deve-lopment in Ulan Buh Desert Oasis and the countermea-sures. Journal of Arid Land Resources and Environment, 2012, 26(11): 25-30]
[16] 徐浩杰. 亚洲中部干旱区植被变化及其影响因素(2000—2012). 硕士论文. 兰州: 兰州大学, 2014 [Xu H-J. Variations of Vegetation and Its Influence Factors in the Arid Region of the Central Asia from 2000 to 2012. Master Thesis. Lanzhou: Lanzhou University, 2014]
[17] 樊自立, 马英杰, 王让会, 等. 干旱区内陆河流域生态系统类型及其整治途径——以新疆为例. 中国沙漠, 2000, 20(4): 393-396 [Fan Z-L, Ma Y-J, Wang R-H, et al. Ecosystem types in the continental river watershed of arid area and the managemental approaches: A case study in Xinjiang of China. Journal of Desert Research, 2000, 20(4): 393-396]
[18] 周可法, 张清, 陈曦, 等. 中亚干旱区生态环境变化的特点和趋势. 中国科学: 地球科学, 2006, 36(suppl.2): 133-139 [Zhou K-F, Zhang Q, Chen X, et al. Characteristics and trends of ecological environment changes in the arid regions of central Asia. Science in China Series D: Earth Sciences, 2006, 36(suppl.2): 133-139]
[19] 马全林, 张德奎, 袁宏波, 等. 乌兰布和沙漠植被数量分类及环境解释. 干旱区资源与环境, 2019, 33(9): 160-167 [Ma Q-L, Zhang D-K, Yuan H-B, et al. Numerical classification and environmental interpretation of desert vegetation in the Ulan Buh Desert. Journal of Arid Land Resources and Environment, 2019, 33(9): 160-167]
[20] 徐涵秋. 区域生态环境变化的遥感评价指数. 中国环境科学, 2013, 33(5): 889-897 [Xu H-Q. A remote sensing index for assessment of regional ecological changes. China Environmental Science, 2013, 33(5): 889-897]
[21] Du H, Xue X, Wang T. Estimation of the quantity of aeolian saltation sediments blown into the Yellow River from the Ulanbuh Desert, China. Journal of Arid Land, 2013, 6: 205-218
[22] 齐亚霄, 张飞, 陈瑞, 等. 2001—2015年天山北坡植被覆盖动态变化研究. 生态学报, 2020, 40(11): 3677-3687 [Qi Y-X, Zhang F, Chen R, et al. Vegetation coverage dynamics in northern slope of Tianshan Mountains from 2001 to 2015. Acta Ecologica Sinica, 2020, 40(11): 3677-3687]
[23] Mo K, Chen Q, Chen C, et al. Spatiotemporal variation of correlation between vegetation cover and precipitation in an arid mountain-oasis river basin in northwest China. Journal of Hydrology, 2019, 574: 138-147
[24] Baig MHA, Zhang L, Shuai T, et al. Derivation of a tasselled cap transformation based on Landsat 8 at-sate-llite reflectance. Remote Sensing Letters, 2014, 5: 423-431
[25] Wen X, Ming Y, Gao Y, et al. Dynamic monitoring and analysis of ecological quality of Pingtan comprehensive experimental zone, a new type of Sea Island City, based on RSEI. Sustainability, 2020, 12: 21-35
[26] 刘杰. 湘中南红壤地区土壤质量特征与退化红壤的肥力调控技术研究. 博士论文. 长沙: 湖南农业大学, 2010 [Liu J. Red Soil Quality Characteristics and Fertility Ameliorating Measures in Central-south Hunan Province. PhD Thesis. Changsha: Hunan Agricultural University, 2010]
[27] Nishikawa H, Yasuda I. Long-term variability of winter mixed layer depth and temperature along the Kuroshio jet in a high-resolution ocean general circulation model. Journal of Oceanography, 2011, 67: 503-518
[28] 卞正富, 于昊辰, 侯竟, 等. 西部重点煤矿区土地退化的影响因素及其评估. 煤炭学报, 2020, 45(1): 338-350 [Bian Z-F, Yu H-C, Hou J, et al. Influencing factors and evaluation of land degradation of 12 coal mine areas in West China. Journal of China Coal Society, 2020, 45(1): 338-350]
[29] 陈彬, 俞炜炜, 陈光程, 等. 滨海湿地生态修复若干问题探讨. 应用海洋学学报, 2019, 38(4): 464-473 [Chen B, Yu W-W, Chen G-C, et al. Coastal wetland restoration: An overview. Journal of Applied Oceanography, 2019, 38(4): 464-473]
[30] 肖泱, 吕洪德. 潍坊市生态环境状况动态变化研究. 环境科学与管理, 2017, 42(4): 156-159 [Xiao Y, Lyu H-D. Study on ecosystem status dynamic changes in Weifang. Environmental Science and Management, 2017, 42(4): 156-159]
[31] 马劲松, 刘晓峰, 左天惠. 南京市土地利用强度指数异质性研究. 测绘科学, 2010, 35(4): 49-51 [Ma J-S, Liu X-F, Zuo T-H. Study on spatial heterogeneity of land use intensity in Nanjing. Science of Surveying and Mapping, 2010, 35(4): 49-51]
[32] 姜宛贝. 干旱区土地退化遥感监测方法研究. 博士论文. 北京: 中国农业大学, 2017 [Jiang W-B. Study of Land Degradation Remote Sensing Monitoring Method in the Arid Region. PhD Thesis. Beijing: China Agricul-tural University, 2017]
[33] 吴文婕. 石羊河流域绿洲水土资源利用生态风险评价研究——以武威市为例. 硕士论文. 兰州: 西北师范大学, 2012 [Wu W-J. Comprehensive Evaluation on Soil-Water Utilization Ecological Risk of Oasis: A Case Study of Wuwei City in Shiyang River Basin. Master Thesis. Lanzhou: Northwest Normal University, 2012]
[34] 冯娟, 丁建丽, 杨爱霞, 等. 干旱区土壤盐渍化信息遥感建模. 干旱地区农业研究, 2018, 36(1): 266-273 [Feng J, Ding J-L, Yang A-X, et al. Remote sen-sing modeling of soil salinization information in arid areas. Agricultural Research in the Arid Areas, 2018, 36(1): 266-273]
[35] 王葆芳, 贾宝全, 杨晓晖, 等. 干旱区土地利用方式对沙漠化土地恢复能力的评价. 生态学报, 2002, 22(12): 2030-2035 [Wang B-F, Jia B-Q, Yang X-H, et al. Effects of land-use types on restoration of desertified land in arid zone of China. Acta Ecologica Sinica, 2002, 22(12): 2030-2035]
[36] 郑凯. 气候变化和人类活动对祖厉河流域植被覆盖的影响. 博士论文. 兰州: 兰州大学, 2019 [Zheng K. Impacts of Climate Change and Human Activities on Vegetation Cover in the Zuli River Basin. PhD Thesis. Lanzhou: Lanzhou University, 2019]

干旱地区遥感生态指数的改进——以乌兰布和沙漠为例

Improvement of remote sensing ecological index in arid regions: Taking Ulan Buh Desert as an example

PDF (PC)

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]	王清韵, 周丁扬, 安萍莉, 姜广辉. 自然保护地政策对区域生态环境质量的影响——以三江源地区为例 [J]. 应用生态学报, 2023, 34(5): 1349-1359.
[2]	杜箫宇, 吕飞南, 王春雨, 宇振荣. 基于MSPA-Conefor-MCR的县域尺度生态网络构建——以延庆区为例 [J]. 应用生态学报, 2023, 34(4): 1073-1082.
[3]	岳奕帆, 陈国鹏, 王立, 杨钧, 杨克彤. 基于Google Earth Engine云平台的甘肃舟曲县生态环境质量动态监测与评价 [J]. 应用生态学报, 2022, 33(6): 1608-1614.
[4]	马玉诏, 党红凯, 李科江, 郑春莲, 曹彩云, 张俊鹏, 李全起. 咸水灌溉对冬小麦籽粒品质特性和产量的影响 [J]. 应用生态学报, 2022, 33(4): 1063-1068.
[5]	蒋丛泽, 受娜, 高玮, 马仁诗, 沈禹颖, 杨宪龙. 青藏高原东北缘不同土地利用类型土壤质量综合评价 [J]. 应用生态学报, 2022, 33(12): 3279-3286.
[6]	南生祥, 魏伟, 刘春芳, 周俊菊. 土地利用变化的生态环境效应及其时空演变特征——以河西走廊为例 [J]. 应用生态学报, 2022, 33(11): 3055-3064.
[7]	曹琪琪, 肖辉杰, 刘涛, 孙景宽, 夏江宝, 王栋, 辛智鸣, 贺文君, 赵丹丹, 黄文文. 乌兰布和沙漠东北部不同耕作年限农田土壤有机碳密度及其影响因素 [J]. 应用生态学报, 2022, 33(10): 2628-2634.
[8]	黄进, 陈金华, 张方敏. 基于主成分分析的安徽省冬小麦气候灾损风险的时空演变 [J]. 应用生态学报, 2021, 32(9): 3185-3194.
[9]	宫彬彬, 吴晓蕾, 张斌, 陈一卓, 边鑫宇, 纪日翟, 高洪波. 草莓种苗壮苗指数模型的构建与质量评价 [J]. 应用生态学报, 2021, 32(8): 2809-2817.
[10]	文广超, 孙世奎, 李兴, 谢洪波. 可鲁克湖流域生态环境质量诊断 [J]. 应用生态学报, 2021, 32(8): 2906-2914.
[11]	杨亮洁, 张小鸿, 潘竟虎, 杨永春. 成渝城市群城镇化与生态环境耦合协调及交互影响 [J]. 应用生态学报, 2021, 32(3): 993-1004.
[12]	徐超, 王明田, 杨再强, 韩玮, 郑盛华. 高温对温室草莓光合生理特性的影响及胁迫等级构建 [J]. 应用生态学报, 2021, 32(1): 231-240.
[13]	周玲美, 王世航. 内蒙古杭锦旗生态环境时空变化的遥感监测与评价 [J]. 应用生态学报, 2020, 31(6): 1999-2006.
[14]	李娜, 韩晓增, 盛明, 龙静泓. 东北黑土成土母质培肥过程中土壤肥力变化特征 [J]. 应用生态学报, 2020, 31(4): 1155-1162.
[15]	朱泓, 王金亮, 程峰, 邓欢, 张恩伟, 李应鑫. 滇中湖泊流域生态环境质量监测与评价 [J]. 应用生态学报, 2020, 31(4): 1289-1297.