长白山自然保护区生态环境质量的遥感评价

doi:10.18306/dlkxjz.2016.10.010

Abstract

Abstract:

The well-being of the human race is closely related to the ecological environment. In the past few decades, indicators retrieved from remote sensing data have been increasingly more widely applied to ecological environment evaluation for their advantages of spatial visualization, and remote sensing technology offers important reference to regional ecological environment management, improvement, and development planning by quickly assessing regional ecological environment quality. Remote sensing ecological index (RSEI), constructed by four indicators including green degree, humidity degree, heat degree, and dry degree retrieved from remote sensing images, can reflect ecological environment status. RSEI is based on real-time remote sensing images and accordingly more capable of quick evaluation of temporal and spatial changes of ecological environment quality. In this article, Landsat5 TM images from 1995 and 2007 and Landsat8 OLI images from 2015 were used as data source to retrieve values of the four indicators to construct the RSEI by the principal component analysis method, and Changbai Mountain Nature Reserve ecological environment quality from 1995 to 2015 was evaluated using the RSEI. The result shows: (1) The green degree and humidity degree have an positive effect on promoting the ecological environment quality of the region while the heat degree and dry degree have a restraining effect on the regional ecological environment quality, and the humidity degree is more significant than the other three indicators. (2) In this region, the proportion of excellent and good RSEI classes accounted for 49.5%, 66.5%, and 76.2% of the total area in 1995, 2007, and 2015. Meanwhile, the degenerated, unchanged, and improved RSEI classes were 3.9%, 55.6%, and 40.5% of the total area respectively, indicating that the overall ecological environment quality has gradually improved. To some extent this is attributed to the Natural Forest Resources Protection Project and a series of ecological conservation measures taken in the Changbai Mountain Nature Reserve area. Although the overall ecological environment quality of the study area has gradually improved, the ecological environment quality around Tianchi has declined. This area has a relatively fragile ecological environment and suffers from high intensity of tourism activities. The decline in ecological environment quality may be attributed to the increasingly intense tourism activities. (3) The stepwise regression analysis results show that each of the selected indicators is key to indicating the ecological environment quality, and the model prediction result reveals that the control of barren and dry surfaces is a critical step for improving the ecological environment quality.

Key words: ecological environment quality, remote sensing ecological index, principal component analysis, Changbai Mountain Nature Reserve

Shiyuan WANG, Xuexia ZHANG, Tong ZHU, Wei YANG, Jingyao ZHAO. Assessment of ecological environment quality in the Changbai Mountain Nature Reserve based on remote sensing technology[J].PROGRESS IN GEOGRAPHY, 2016, 35(10): 1269-1278.

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References 36

[1]	丁雨賝, 冯长春, 王利伟. 2016. 山地区域土地生态红线划定方法与实证研究: 以重庆市涪陵区义和镇为例[J]. 地理科学进展, 35(7): 851-859.
	[Ding Y C, Feng C C, Wang L W.2016. Determination of ecological red line of mountainous areas: A case study of Yihe Town in Chongqing Municipality[J]. Progress in Geography, 35(7): 851-859.]
[2]	傅伯杰, 刘宇. 2014. 国际生态系统观测研究计划及启示[J]. 地理科学进展, 33(7): 893-902. doi: 10.11820/dlkxjz.2014.07.004
	[Fu B J, Liu Y.2014. Global ecosystem observation and research programs: Evolution and insights for future development[J]. Progress in Geography, 33(7): 893-902.] doi: 10.11820/dlkxjz.2014.07.004
[3]	高科. 2012. 自然保护区旅游活动生态负效应研究: 以吉林长白山自然保护区为例[J]. 西北农林科技大学学报: 社会科学版, 12(4): 86-91. doi: 10.3969/j.issn.1009-9107.2012.04.016
	[Gao K.2012. On ecologically negative impacts of tourism activities in nature reserve: A case study of Jilin Changbai Mountain Nature Reserve[J]. Journal of Northwest A & F University: Social Science Edition, 12(4): 86-91.] doi: 10.3969/j.issn.1009-9107.2012.04.016
[4]	侯光雷, 张洪岩, 郭聃, 等. 2012. 长白山区植被生长季NDVI时空变化及其对气候因子敏感性[J]. 地理科学进展, 31(3): 285-292. doi: 10.11820/dlkxjz.2012.03.003
	[Hou G L, Zhang H Y, Guo D, et al.2012. Spatial-temporal variation of NDVI in the growing season and its sensitivity to climatic factors in Changbai Mountains[J]. Progress in Geography, 31(3): 285-292.] doi: 10.11820/dlkxjz.2012.03.003
[5]	李粉玲, 常庆瑞, 申健, 等. 2015. 黄土高原沟壑区生态环境状况遥感动态监测: 以陕西省富县为例[J]. 应用生态学报, 26(12): 3811-3817.
	[Li F L, Chang Q R, Shen J, et al.2015. Dynamic monitoring of ecological environment in loess hilly and gully region of Loess Plateau based on remote sensing: A case study on Fuxian County in Shaanxi Province, Northwest China[J]. Chinese Journal of Applied Ecology, 26(12): 3811-3817.]
[6]	李国伟, 赵伟, 魏亚伟, 等. 2015. 天然林资源保护工程对长白山林区森林生态系统服务功能的影响[J]. 生态学报, 35(4): 984-992. doi: 10.5846/stxb201304240799
	[Li G W, Zhao W, Wei Y W, et al.2015. Evaluation on the influence of natural forest protection program on forest ecosystem service function in Changbai Mountain[J]. Acta Ecologica Sinica, 35(4): 984-992.] doi: 10.5846/stxb201304240799
[7]	李秀民. 2014. 延边林区天保工程实施效果评价体系的构建与实证研究[D]. 哈尔滨: 东北林业大学.
	[Li X M.2014. Study on demonstration and construction of NFPP effect evaluation system in Yanbian forest region[D]. Harbin, China: Northeast Forestry University.]
[8]	刘志锋. 2010. 基于多源遥感数据的长白山地区植被动态变化研究[D]. 延吉: 延边大学.
	[Liu Z F.2010. Study on the dynamic Change of vegetation in the Changbai Mountain area based on multi-source remote sensing data[D]. Yanji, China: Yanbian University.]
[9]	柳菲. 2012. 地表比辐射率遥感反演方法研究[D]. 武汉: 湖北大学.
	[Liu F.2012. Researching of remote sensing inversion method on land surface emissivity[D]. Wuhan, China: Hubei University.]
[10]	南颖, 刘志锋, 朱卫红, 等. 2011. 长白山的台风灾区范围及植被恢复动态: 基于遥感技术的研究[J]. 自然灾害学报, 20(6): 131-139.
	[Nan Y, Liu Z F, Zhu W H, et al.2011. Range of typhoon-stricken area and trend of vegetation restoration in Changbai Mountain: RS-based research[J]. Journal of Natural Disasters, 20(6): 131-139.]
[11]	牛丽君, 梁宇, 王绍先, 等. 2013. 长白山自然保护区风灾区植被恢复评价[J]. 生态学杂志, 32(9): 2375-2381.
	[Niu L J, Liang Y, Wang S X, et al.2013. Evaluation of vegetation restoration in wind disaster area in Changbai Mountains Nature Reverse, Northeast China[J]. Chinese Journal of Ecology, 32(9): 2375-2381.]
[12]	戚涛. 2007. 基于遥感的区域植被生态环境质量综合评价研究[D]. 武汉: 华中科技大学.
	[Qi T.2007. The study of regional vegetation ecological environment quality integrative evaluation based-on remote sensing[D]. Wuhan, China: Huazhong University of Science and Technology.]
[13]	宋军伟, 张友静, 李鑫川, 等. 2016. 基于GF-1与Landsat-8影像的土地覆盖分类比较[J]. 地理科学进展, 35(2): 255-263.
	[Song J W, Zhang Y J, Li X C, et al.2016. Comparison between GF-1 and Landsat-8 images in land cover classification[J]. Progress in Geography, 35(2): 255-263.]
[14]	覃志豪, 李文娟, 徐斌, 等. 2004. 利用Landsat TM6反演地表温度所需地表辐射率参数的估计方法[J]. 海洋科学进展, 22(S1): 129-137. doi: 10.3969/j.issn.1671-6647.2004.z1.022
	[Qin Z H, Li W J, Xu B, et al.2004. Estimation method of land surface emissivity for retrieving land surface temperature from Landsat TM6 data[J]. Advances in Marine Science, 22(Sl): 129-137.] doi: 10.3969/j.issn.1671-6647.2004.z1.022
[15]	吴丹丹, 蔡运龙. 2009. 中国生态恢复效果评价研究综述[J]. 地理科学进展, 28(4): 622-628. doi: 10.11820/dlkxjz.2009.04.020
	[Wu D D, Cai Y L.2009. Evaluation of ecological restoration effects in China: A review[J]. Progress in Geography, 28(4): 622-628.] doi: 10.11820/dlkxjz.2009.04.020
[16]	徐涵秋. 2013a. 城市遥感生态指数的创建及其应用[J]. 生态学报, 33(24): 7853-7862. doi: 10.5846/stxb201208301223
	[Xu H Q.2013a. A remote sensing urban ecological index and its application[J]. Acta Ecologica Sinica, 33(24): 7853-7862.] doi: 10.5846/stxb201208301223
[17]	徐涵秋. 2013b. 区域生态环境变化的遥感评价指数[J]. 中国环境科学, 33(5): 889-897. doi: 10.3969/j.issn.1000-6923.2013.05.019
	[Xu H Q.2013b. A remote sensing index for assessment of regional ecological changes[J]. China Environmental Science, 33(5): 889-897.] doi: 10.3969/j.issn.1000-6923.2013.05.019
[18]	徐一中. 2014. 长白山西坡苔原带退化土地的生态管理[D]. 长春: 东北师范大学.
	[Xu Y Z.2014. Ecological management of degraded land in the tundra of Changbai Mountain western slope[D]. Changchun, China: Northeast Normal University.]
[19]	姚尧, 王世新, 周艺, 等. 2012. 生态环境状况指数模型在全国生态环境质量评价中的应用[J]. 遥感信息, 27(3): 93-98. doi: 10.3969/j.issn.1000-3177.2012.03.016
	[Yao Y, Wang S X, Zhou Y, et al.2012. The application of ecological environment index model on the national evaluation of ecological environment quality[J]. Remote Sensing Information, 27(3): 93-98.] doi: 10.3969/j.issn.1000-3177.2012.03.016
[20]	张建亮, 刘方正, 崔国发. 2016. 长白山国家级自然保护区植被时空变化及其驱动因子[J]. 生态学报, 36(12): 3525-3536. doi: 10.5846/stxb201410192053
	[Zhang J L, Liu F Z, Cui G F.2016. Spatio-temporal variation of vegetation and analysis of its driving factors in Changbai Mountain National Nature Reserve[J]. Acta Ecologica Sinica, 36(12): 3525-3536.] doi: 10.5846/stxb201410192053
[21]	赵晓飞, 牛丽君, 陈庆红, 等. 2004. 长白山自然保护区风灾干扰区生态系统的恢复与重建[J]. 东北林业大学学报, 32(4): 38-40. doi: 10.3969/j.issn.1000-5382.2004.04.014
	[Zhao X F, Niu L J, Chen Q H, et al.2004. Restoration and rebuilding of the wind disturbed ecosystems at the wind disaster region in the National Nature Reserve of Changbai Mountain[J]. Journal of Northeast Forestry University, 32(4): 38-40.] doi: 10.3969/j.issn.1000-5382.2004.04.014
[22]	郑勇. 2014. 基于TM数据的生态环境指数提取及变化分析[D]. 南京: 南京林业大学.
	[Zheng Y.2014. Eco-environment index extraction and change analysis based on the TM data[D]. Nanjing, China: Nanjing Forestry University.]
[23]	周文英, 何彬彬. 2014. 四川省若尔盖县生态环境质量评价[J]. 地球信息科学学报, 16(2): 314-319. doi: 10.3724/SP.J.1047.2014.00314
	[Zhou W Y, He B B.2014. Eco-environmental quality assessment of Ruoergai County in Sichuan Province based on multi-sources remote sensing data[J]. Journal of Geo-Information Science, 16(2): 314-319.] doi: 10.3724/SP.J.1047.2014.00314
[24]	Baig M H A, Zhang L F, Shuai T, et al.2014. Derivation of a tasselled cap transformation based on Landsat8 at-satellite reflectance[J]. Remote Sensing Letters, 5(5): 423-431. doi: 10.1080/2150704X.2014.915434
[25]	Crist E P.1985. A TM tasseled cap equivalent transformation for reflectance factor data[J]. Remote Sensing of Environment, 17(3): 301-306. doi: 10.1016/0034-4257(85)90102-6
[26]	Foody G M.2007. Editorial: Ecological applications of remote sensing and GIS[J]. Ecological Informatics, 2(2): 71-72. doi: 10.1016/j.ecoinf.2007.06.001
[27]	Goward S N, Xue Y K, Czajkowski K P.2002. Evaluating land surface moisture conditions from the remotely sensed temperature/vegetation index measurements: An exploration with the simplified simple biosphere model[J]. Remote Sensing of Environment, 79(2-3): 225-242. doi: 10.1016/S0034-4257(01)00275-9
[28]	Ju W M, Gao P, Wang J, et al.2010. Combining an ecological model with remote sensing and GIS techniques to monitor soil water content of croplands with a monsoon climate[J]. Agricultural Water Management, 97(8): 1221-1231. doi: 10.1016/j.agwat.2009.12.007
[29]	Malekmohammadi B, Blouchi L R.2014. Ecological risk assessment of wetland ecosystems using multi criteria decision making and geographic information system[J]. Ecological Indicators, 41: 133-144. doi: 10.1016/j.ecolind.2014.01.038
[30]	NASA. 2016. Landsat8(L8) data users handbook[EB/OL]. 2016-03-29[2016-04-20]. .
[31]	Rikimaru A, Roy P S, Miyatake S.2002. Tropical forest cover density mapping[J]. Tropical Ecology, 43(1): 39-47.
[32]	Sobrino J A, Jiménez-Muñoz J C, Paolini L.2004. Land surface temperature retrieval from Landsat TM5[J]. Remote Sensing of Environment, 90(4): 434-440. doi: 10.1016/j.rse.2004.02.003
[33]	van de Griend A A, Owe M.1993. On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces[J]. International Journal of Remote Sensing, 14(6): 1119-1131. doi: 10.1080/01431169308904400
[34]	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. doi: 10.1080/01431160802039957
[35]	Xu H Q.2010. Analysis of impervious surface and its impact on urban heat environment using the Normalized Difference Impervious Surface Index (NDISI)[J]. Photogrammetric Engineering and Remote Sensing, 76(5): 557-565. doi: 10.14358/PERS.76.5.557
[36]	Yu X L, Guo X L, Wu Z C.2014. Land surface temperature retrieval from Landsat8 TIRS: Comparison between radiative transfer equation-based method, split window algorithm and single channel method[J]. Remote Sensing, 6(10): 9829-9852. doi: 10.3390/rs6109829

年份	指标	第一主成分	第二主成分	第三主成分	第四主成分
1995年	绿度	0.21394	0.48829	0.77272	-0.34453
	湿度	0.88674	-0.24886	0.08159	0.38092
	热度	-0.19831	0.55139	0.06656	0.8076
	干度	-0.35860	-0.62898	0.62595	0.28979
	特征值	0.00200	0.00020	0.00015	0.00010
	贡献率/%	81.495	8.037	6.247	4.221
2007年	绿度	0.28814	0.27695	0.86125	0.31389
	湿度	0.82363	-0.13306	-0.37876	0.40059
	热度	-0.27079	0.75659	-0.33260	0.49358
	干度	-0.40656	-0.57720	0.06459	0.70525
	特征值	0.00130	0.00016	0.00007	0.00005
	贡献率/%	82.795	9.922	4.203	3.080
2015年	绿度	0.30949	0.32266	-0.77488	0.44684
	湿度	0.79965	-0.15642	0.45870	0.35454
	热度	-0.17019	0.86353	0.41960	0.22198
	干度	-0.48561	-0.35459	0.11442	0.79080
	特征值	0.01343	0.00153	0.00064	0.00026
	贡献率/%	84.684	9.674	4.018	1.624

年份	指标				RSEI
年份	绿度		湿度	热度	干度
1995年	0.564	0.672	0.641	0.439	0.571
2007年	0.570	0.740	0.488	0.316	0.610
2015年	0.600	0.770	0.485	0.409	0.648

等级	1995年			2007年			2015年
等级	面积/km²		百分比/%		面积/km²	百分比/%	面积/km²	百分比/%
差	121.218	6.226		23.355	1.200		16.099	0.827
较差	172.697	8.870		152.280	7.821		129.089	6.630
中等	688.908	35.384		476.441	24.471		318.410	16.354
良	917.577	47.129		1289.472	66.230		1455.216	74.744
优	46.549	2.391		5.402	0.278		28.137	1.445

类别	级差	级面积/km²	类面积/km²	类比例/%
变差	-4	0.949	76.819	3.945
	-3	7.665
	-2	8.724
	-1	59.480
不变	0	1082.462	1082.462	55.598
变好	1	717.931	787.670	40.457
	2	68.811
	3	0.921
	4	0.007

Assessment of ecological environment quality in the Changbai Mountain Nature Reserve based on remote sensing technology

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