Remote sensing evaluation of eco-environmental quality in Chengde City from 2013 to 2022
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摘要: 【研究目的】生态环境是人类赖以生存发展的基础，利用遥感技术对承德市生态环境质量和状况进行评价及分析，为承德市生态环境保护和治理提供科学依据和技术支持。【研究方法】本研究基于Landsat系列遥感影像，利用ENVI 软件计算得到反映生态环境的绿度、湿度、干度和热度四个指标，并采用主成分分析法构建遥感生态指数模型，对承德市生态环境质量进行评价。【研究结果】通过利用2013年、2016年、2019年和2022年四期承德市遥感影像计算的四个指标构建遥感生态指数模型，并对其进一步分析，结果表明：（1）使用主成分分析结果中的第一主成分指标来构建RSEI模型，代表绿度的NDVI和代表湿度的WET对生态环境质量起到正面作用，代表干度的NDBSI和代表热度的LST 对生态环境质量起到负面作用；（2）2013—2022 年，承德市RSEI 均值由0.625 上升至0.640，生态环境质量总体呈现上升趋势，生态环境得到基本改善；（3）2013—2022 年，承德市生态环境变差的面积为2 405.562 3 km2，约占总面积的6.07%；不变的面积为28 769.067 km2，约占总面积的75.54%；变好的面积为8 483.188 5 km2，约占总面积的21.39%。【结论】在2013 至2022 年的十年间，承德市的生态环境质量总体上呈现出显著的初步改善趋势。本次研究可为承德市区域环境保护工作提供可参考的依据。
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关键词:
- 生态环境 /
- 遥感影像 /
- 遥感生态指数(RSEI) /
- 主成分分析 /
- 承德市
Abstract: This paper is the result of ecological environment.[Objective] Ecological environment is the foundation for the survival and development of human beings. Remote sensing technology is used to evaluate and analyze the quality and status of the ecological environment in Chengde City provides scientific basis and technical support for the protection and governance of the ecological environment in Chengde City. [Methods]This study is based on Landsat series remote sensing images, and uses ENVI software to calculate four indicators reflecting the ecological environment: greenness, wetness, dryness, and heat. In addition, the principal component analysis method is used to construct a remote sensing ecological index model to evaluate the ecological environment quality of Chengde City. [Results] The remote sensing ecological index model was constructed by using four indicators calculated from remote sensing images of Chengde City in 2013, 2016, 2019, and 2022, and further analyzed, showing that:(1)The first principal component index in the principal component analysis was used to construct the RSEI model. NDVI (representing greenness) and WET (representing wetness) had a positive effect on the ecological environment quality, while NDBSI (representing dryness) and LST(representing heat) had a negative effect on the ecological environment quality. (2) From 2013 to 2022, the average RSEI value of Chengde City increased from 0.625 to 0.640, and the ecological environment quality showed an overall upward trend, and the ecological environment was basically improved. (3) From 2013 to 2022, the area of ecological environment deterioration in Chengde city is 2 405.562 3 km2, accounting for about 6.07%of the total area; The unchanged area is 28 769.067 km2, accounting for 75.54%of the total area.The improved area is 8 483.1885 km2, accounting for 21.39% of the total area. [Conclusions] From 2013 to 2022, the overall ecological environment quality of Chengde City has shown a significant initial improvement trend. This study can provide a reference basis for regional environmental protection work in Chengde City. -
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[1] 陈创,聂平静,黄凤寸,等.2024.基于RSEI 改进模型的生态环境质量评价及驱动机制研究:以湖南省桃江县为例[J]. 水土保持通报,44(03):159-170.
[2] 陈丽红,刘普幸,花亚萍.2021.基于RSEI的疏勒河流域生态质量综合评价及其成因分析[J].土壤通报,52(01):25-33.
[3] 程志峰,何祺胜.2019.基于RSEI 的苏锡常城市群生态环境遥感评价[J].遥感技术与应用,34(03):531-539.
[4] 崔阳,孙洪泉,夏积德.2024.杨凌区1990-2020 年生态环境时空演变分析[J].地理空间信息,22(06):43-47.
[5] 郭超凡,马点明,袁玥,等.2024.基于RSEI 的交通枢纽城市生态环境质量动态评价:以郑州市为例[J].云南大学学报(自然科学版),46(05):896-906.
[6] 杭鑫,罗晓春,曹云,等.2020.基于RSEI 模型的生态质量评估及城镇化影响:以南京市为例[J].应用生态学报,31(01):219-229.
[7] 郝灿,陈义忠,高田源,等.2023.基于生态足迹理论的承德市水资源利用均衡性及影响因素[J].河北工业大学学报,52(05):85-96.
[8] 何盈利,尤南山,崔耀平,等.2021.2000 年来中国生态状况时空变化格局[J].自然资源学报,36(05):1176-1185.
[9] 黄垒,李磊,王威.2023.基于GIS 的华北地区自然资源综合评价区划研究[J].华北地质,46(4):83-88.
[10] 李博伦,遆超普,颜晓元.2016.Landsat 8 陆地成像仪影像的缨帽变换推导[J].测绘科学,(04):102-107.
[11] 李尧,袁红,罗建松,等.2021.基于RSEI 模型的生态环境质量评价研究[J].测绘与空间地理信息,(04):117-119+124.
[12] 吕大伟,蔡海生,张学玲,等.2021.基于遥感生态指数的弋阳县生态安全格局构建及优化[J].农业现代化研究,(03):545-556.
[13] 农兰萍,王金亮.2020.基于RSEI 模型的昆明市生态环境质量动态监测[J].生态学杂志,(06):2042-2050.
[14] 施智勇,胡晓婷,谢慧黎,等.2023.基于RSEI的生态环境质量评价及驱动力分析--以闽江流域(福州段)为例[J].测绘通报,(02):28-33.
[15] 宋慧敏,薛亮.2016.基于遥感生态指数模型的渭南市生态环境质量动态监测与分析[J].应用生态学报,27(12):3913-3919.
[16] 王丽春,焦黎,来风兵,等.2019.基于遥感生态指数的新疆玛纳斯湖湿地生态变化评价[J].生态学报,39(08):2963-2972.
[17] 王妍妍,张霞,尚国琲.2022.2013-2020 年北京市植被覆盖时空变化特征分析[J].河北地质大学学报,45(01):99-105.
[18] 徐涵秋.2013a.区域生态环境变化的遥感评价指数[J].中国环境科学,33(05):889-897.
[19] 徐涵秋.2013b.水土流失区生态变化的遥感评估[J].农业工程学报,29(07):91-97+294.
[20] 许新国.2023.承德市乡村旅游发展区域特征与区划研究[J].河北旅游职业学院学报,28(04):12-18.
[21] 杨惠麟,张存波,赵祺.2024.基于RSEI模型的成都市生态环境遥感评价[J].科学技术创新,(08):38-41.
[22] 杨江燕,吴田,潘肖燕,等.2019.基于遥感生态指数的雄安新区生态质量评估[J].应用生态学报,30(01):277-284.
[23] 叶博文,孙标,赵云靓,等. 2024. 2000-2022 年内蒙古生境质量时空演变及驱动力分析[J/OL].环境科学.
[24] 章程焱,杨少康,董晓华,等.2023.基于RSEI 指数的长江上游流域生态环境质量时空演变及影响因子研究[J].水土保持研究,30(01):356-363.
[25] 张晓山,张旺锋,高新宇,等.2023.基于RSEI 的张掖市甘州区生态环境质量动态评估[J].人民黄河,45(02):114-120.
[26] 张志军,陈楚,王琳,等.2023.天津北部山区典型地质灾害遥感监测应用[J].华北地质,46(4):76-82.
[27] 赵娜,王冰,王子昊,等.2024.基于遥感生态指数的内蒙古生态环境质量时空演化及生态管理分区[J/OL].环境科学.
[28] 朱贞榕.2017.基于遥感生态指数(RSEI)的南昌市生态环境质量评价[D].东华理工大学.
[29] Chander G, Markham B L, Helder D L. 2009.Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors [J]. Remote Sensing of Environment, 113:893-903.
[30] Crist E P.1985.A TM tasseled cap equivalent transformation for reflectance factor data.Remote Sensing of Environment, 17(3):01-306.
[31] Huang C, Wylie B, Yang L, et al. 2002.Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance. International Journal of Remote Sensing, 23(8):1741-1748.
[32] NASA.Landsat 7 Science Data Users Handbook [EB/OL].http://landsathandbook.gsfc.nasa.gov, 2012-09-05.
[33] Nichol J. 2005.Remote sensing of urban heat islands by day and night [J]. Photogrammetric Engineering and Remote Sensing, 71(6):613-621.
[34] Rikimaru A, Roy P S, Miyatake S. 2002.Tropical forest cover density mapping[J].Tropical Ecology, 43(1):39-47.
[35] Xu H Q. 2008. A new index for delineating built-up land features in satellite imagery[J]. International Journal of Remote Sensing, 29(14):4269-4276.
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