基于多源数据的河南省区域生态旅游适宜度评价

doi:10.3969/j.issn.1673-503X.2024.01.008

摘要/Abstract

摘要：

以2001—2020年MODIS遥感数据产品和河南省近30 a (1991—2020年)气候数据为数据源, 基于主成分分析方法建立由植被覆盖度、生态释氧量、气溶胶光学厚度和度假气候指数构成的生态旅游适宜度指数(ESI), 进而对河南省过去20 a的生态旅游适宜度进行评价研究。结果表明: 近20 a, 河南省植被覆盖度、生态释氧量整体呈现增长趋势, 变化量分别为12.5%和191 g·m^-2, 相对变化率达到30.2%和32.3%。气溶胶光学厚度和度假气候指数整体呈降低趋势, 变化量分别为-0.07和-1.65, 相对变化率分别达到-13.6%和-2.25%, 河南省生态环境整体呈现向好趋势。利用主成分分析构建的生态旅游适宜度指数(ESI)避免了因人为方法对权重设定不同所导致的结果偏差, 使其更加具有客观性和可靠性, 评价结果和目前河南省生态旅游景区分布情况整体一致, 能客观反映区域内生态旅游适宜度的空间差异。生态旅游适宜度指数空间分布的高值区域集中在西部伏牛山区域和南部大别山区域, 而低值区域集中在华北平原地区, 2020年相比2001年的相对变化率为3%, 生态旅游适宜度指数呈变好趋势。

关键词: 多源数据, 生态旅游适宜度, 主成分分析

Abstract:

Using MODIS remote sensing data products from 2001 to 2020 and climate data from He'nan province over the last 30 years (from 1991 to 2020), an ecological tourism suitability Index (ESI) considering vegetation coverage, ecological oxygen release, aerosol optical thickness, and holiday climate index was established based on the principal component analysis method. The ESI was then used to evaluate the ecological tourism suitability in He'nan province over the past 20 years. The results show that over the past 20 years, the vegetation coverage and ecological oxygen release in He'nan province have generally shown an increasing trend with change rates of 12.5% and 191 g·m^-2 as well as relative change rates of 30.2% and 32.3%, respectively. The aerosol optical thickness and holiday climate index show an overall decreasing trend with change rates of -0.07 and -1.65, and relative change rates of -13.6% and -2.25%, respectively, indicating an overall improvement in the ecological environment of He'nan province. The ESI constructed using principal component analysis avoids the bias in results caused by different weight settings due to subjective methods, and is more objective and reliable. The evaluation results are generally consistent with the current distribution of ecological tourism areas in He'nan province and can objectively reflect the spatial differences in ecological tourism suitability within the region. The high-value areas of the ESI are concentrated in the Funiu Mountain area of the west and the Dabie Mountain area of the south, while the low-value areas are concentrated in the North China Plain area. The change rate of the ESI in 2020 relative to that in 2001 was 3%, indicating an improving trend in the ESI.

Key words: Multi-source data, Ecotourism suitability, Principal component analysis

中图分类号:

冯杉,王新伟,朱晓晨. 基于多源数据的河南省区域生态旅游适宜度评价[J]. 气象与环境学报, 2024, 40(1): 63-70.

Shan FENG,Xinwei WANG,Xiaochen ZHU. Evaluation of regional ecotourism suitability in He'nan province based on multi-source data[J]. Journal of Meteorology and Environment, 2024, 40(1): 63-70.

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参考文献 28

1	Perch-Nielsen S L , Amelung B , Knutti R . Future climate resources for tourism in Europe based on the daily tourism climatic index[J]. Climatic Change, 2010, 103 (3): 363- 381.
2	Amelung B , Nicholls S , Viner D . Implications of global climate change for tourism flows and seasonality[J]. Journal of Travel Research, 2007, 45 (2): 285- 296.
3	杨桂华, 钟林生, 明庆忠. 生态旅游(2版)[M]. 北京: 高等教育出版社, 2010.
4	Weaver D B , Lawton L J . Twenty years on: the state of contemporary ecotourism research[J]. Tourism Management, 2007, 28 (5): 1168- 1179. doi: 10.1016/j.tourman.2007.03.004
5	Salum L A . Ecotourism and biodiversity conservation in Jozani-Chwaka bay national Park, Zanzibar[J]. African Journal of Ecology, 2009, 47 (S1): 166- 170. doi: 10.1111/j.1365-2028.2008.01065.x
6	Blersch D M , Kangas P C . A modeling analysis of the sustainability of ecotourism in Belize[J]. Environment, Development and Sustainability, 2013, 15 (1): 67- 80. doi: 10.1007/s10668-012-9374-4
7	Broadbent E N , Zambrano A M A , Dirzo R , et al. The effect of land use change and ecotourism on biodiversity: a case study of Manuel Antonio, Costa Rica, from 1985 to 2008[J]. Landscape Ecology, 2012, 27 (5): 731- 744. doi: 10.1007/s10980-012-9722-7
8	Li R J , Lu Z , Li J F . Quantitative calculation of eco-tourist's landscape perception: strength, and spatial variation within ecotourism destination[J]. Ecological Informatics, 2012, 10, 73- 80. doi: 10.1016/j.ecoinf.2012.03.009
9	袁书琪. 试论生态旅游资源的特征、类型和评价体系[J]. 生态学杂志, 2004, 23 (2): 109- 113.
10	张昊楠, 秦卫华, 周大庆, 等. 中国自然保护区生态旅游活动现状[J]. 生态与农村环境学报, 2016, 32 (1): 24- 29.
11	Hytönen L , Leskinen P , Store R . A spatial approach to participatory planning in forestry decision making[J]. Scandinavian Journal of Forest Research, 2002, 17 (1): 62- 71. doi: 10.1080/028275802317221091
12	Phua M H , Minowa M . A GIS-based multi-criteria decision making approach to forest conservation planning at a landscape scale: a case study in the Kinabalu Area, Sabah, Malaysia[J]. Landscape and Urban Planning, 2005, 71 (2/4): 207- 222.
13	钟林生, 肖笃宁, 赵士洞. 乌苏里江国家森林公园生态旅游适宜度评价[J]. 自然资源学报, 2002, 17 (1): 71- 77.
14	贾铁飞, 张振国. 生态敏感区旅游资源开发的生态与环境适宜度研究——以内蒙古鄂尔多斯市东胜区为例[J]. 资源科学, 2006, 28 (5): 134- 139.
15	郑晓兴, 孙铭, 陈鹰, 等. 基于GIS和人工神经网络模型的区域生态旅游适宜度评价——以浙江省为例[J]. 生态学杂志, 2006, 25 (11): 1435- 1441.
16	李会琴, 侯林春, 肖拥军, 等. 基于RS、GIS的黄土高原环境脆弱区生态旅游适宜度评价——以山西省中阳县为例[J]. 测绘科学, 2009, 34 (6): 300- 302.
17	李俊英, 胡远满, 闫红伟, 等. 基于景观视觉敏感度的棋盘山生态旅游适宜性评价[J]. 西北林学院学报, 2010, 25 (5): 194- 198.
18	张爱平, 钟林生, 徐勇, 等. 基于适宜性分析的黄河首曲地区生态旅游功能区划研究[J]. 生态学报, 2015, 35 (20): 6838- 6847.
19	刘晓娜, 刘春兰, 张丛林, 等. 色林错—普若岗日国家公园潜在建设区生态环境脆弱性格局评估[J]. 生态学杂志, 2020, 39 (3): 944- 955.
20	赵迦琪. 呼包鄂地区气候舒适度时空变化及其关键气象因子分析[J]. 气象与环境学报, 2022, 38 (2): 78- 88.
21	徐静, 卢宪梅, 刘志刚, 等. 1966—2018年秦皇岛气候舒适度时空变化特征[J]. 气象与环境学报, 2020, 36 (3): 80- 86.
22	吴昊旻, 姜燕敏, 司波, 等. 丽水山地夏季避暑旅游气候适宜度评价[J]. 气象与环境学报, 2021, 37 (6): 106- 112.
23	周晓宇, 龚强, 赵春雨, 等. 辽宁省冰雪气候资源适宜性评价[J]. 气象与环境学报, 2020, 36 (5): 76- 85.
24	龙亚萍, 李立华. 四川省山地旅游气候资源评价[J]. 山地学报, 2018, 36 (1): 116- 124.
25	张立杰, 张丽, 李磊, 等. 2011年深圳人体舒适度空间分布特征及影响因子分析[J]. 气象与环境学报, 2013, 29 (6): 134- 139.
26	罗艳玲. 河南省生态旅游资源开发潜力评价及可持续发展策略[J]. 中国农业资源与区划, 2016, 37 (9): 40- 47.
27	卫淑芸, 史贝贝, 吴明作, 等. 河南省旅游气候舒适期及其时空变化研究[J]. 河南科学, 2017, 35 (1): 159- 165.
28	TANG M T. Comparing the 'tourism climate index' and 'holiday climate index' in major European urban destinations[D]. Waterloo: University of Waterloo, 2013.

HCI值	90~100	80~89	70~79	60~69	50~59	40~49	30~39	20~29	10~19
状态	理想状态	特别适宜	很适宜	适宜	可以接受	一般	不适宜	很不适宜	特别不适宜

[1]	王凯,周丽雅,鞠晓雨,程向阳. 2011—2019年中国长江三角洲区域闪电时空分布特征[J]. 气象与环境学报, 2021, 37(4): 100-106.
[2]	李永生, 王永光, 王莹. 黑龙江省夏季降水主模态异常型前兆信号分析[J]. 气象与环境学报, 2017, 33(3): 29-35.
[3]	李雪源, 景元书, 吴凡, 周连, 陈晓东. 南京市呼吸系统疾病死亡率和气象要素的关系及预测[J]. 气象与环境学报, 2012, 28(5): 46-.