土地整治区域生态资产的变化研究——以上海市松江区泖港镇为例

doi:10.3969/j.issn.1004-9479.2024.12.20230286

世界地理研究 ›› 2024, Vol. 33 ›› Issue (12): 119-130.DOI: 10.3969/j.issn.1004-9479.2024.12.20230286

土地整治区域生态资产的变化研究——以上海市松江区泖港镇为例

潘路康¹^,²^,³(), 陆衍⁴^,⁵, 过仲阳¹^,²^,³(), 杜欣怡¹^,²^,³, 李永阔¹^,²^,³

^1.地理信息科学教育部重点实验室，上海 200241
^2.华东师范大学地理科学学院，上海 200241
^3.自然资源部超大城市自然资源时空大数据分析应用重点实验室，上海 200241
^4.自然资源部大都市区国土空间生态修复工程技术创新中心，上海 200003
^5.上海市建设用地和土地整理事务中心，上海 200003

收稿日期:2023-05-13 修回日期:2023-11-09 出版日期:2024-12-15 发布日期:2024-12-23
通讯作者: 过仲阳
作者简介:潘路康（1999—），男，硕士研究生，研究方向为数据挖掘，E-mail：844097908@qq.com。
基金资助:
自然资源部大都市区国土空间生态修复工程技术创新中心开放课题(CXZX202206)

Research on changes of ecological assets in land consolidation areas: A case study of Maogang Town

Lukang PAN¹^,²^,³(), Yan LU⁴^,⁵, Zhongyang GUO¹^,²^,³(), Xinyi DU¹^,²^,³, Yongkuo LI¹^,²^,³

^1.Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
^2.School of Geographical Science, East China Normal Unversity, Shanghai 200241, China
^3.Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
^4.Technology Innovation Center for Land Spatial Eco-restoration in Metropolitan Area, MNR, Shanghai 200003, China
^5.Shanghai Center for Construction Land and Land Preparation, Shanghai 200003, China

Received:2023-05-13 Revised:2023-11-09 Online:2024-12-15 Published:2024-12-23
Contact: Zhongyang GUO

摘要/Abstract

摘要：

利用多时相高分二号影像及气象、土壤和社会经济等数据，对上海市泖港镇生态资产面积、质量及生态服务价值（ESV）进行核算，分析2017、2019和2022年泖港镇生态资产变化状况及主导因素。核算结果显示：（1）2017—2022年，泖港镇城镇不断扩张，森林生态系统面积在土地整治前开始减少，同时质量下降。2019—2022年土地整治后森林生态系统面积恢复，且优、良级面积占比增加。从生态资产综合指数分析，泖港镇生态资产综合指数在2017—2022年间先下降后上升，2017年泖港镇生态资产综合指数为49.54，2019年泖港镇生态资产综合指数为46.26，2022年泖港镇生态资产综合指数为50.38。（2）土地综合整治开展前，泖港镇生态服务价值（ESV）减少，从2017年的49 062.41万元减少至2019年的45 599.69万元。土地整治开展后，2022年ESV增长至49 337.27万元，其中土地整治重点区域行政村ESV增长10.80%，非土地整治重点区域行政村ESV增长7.23%，可见土地整治措施带来一定生态经济成效。（3）CP、POP、GDP、Slope、DEM与ESV存在负相关，PRE与ESV呈现正相关，其中社会经济因素CP、POP、GDP对ESV的影响相比自然因素更为显著，说明人类活动强度相较于自然因素对生态资产变化具有更明显的影响。

关键词: 生态资产, 土地整治, 生态系统服务价值, 泖港镇

Abstract:

Using multi-temporal GF-2 imagery and meteorological, soil, and socio-economic data, we analyzed the changes in ecological assets and the dominant factors in Maogang town in 2017, 2019, and 2022 by accounting for the area, quality, and ecological service value. Results show that: (1) From 2017 to 2022, towns of the research area continued expanding, while forest ecosystem area and quality decreased before land reclamation. After land consolidation from 2019 to 2022, forest ecosystem area and quality were restored. Analyzed by the Eco-Asset Composite Index,Maogang's Ecological Asset Composite Index was 49.54 in 2017, 46.26 in 2019, and 50.38 in 2022, Maogang's Eco-Asset Composite Index decreased and then increased. (2) The ecological service value (ESV) of Maogang decreased from $4.9062 billion in 2017 to $4.5597 billion in 2019 before the land consolidation was carried out. After land consolidation is carried out, ESV increases to $4.9337 billion in 2022, of which the ESV of villages in key areas of land consolidation increases by 10.80%, and the ESV of villages in non-key areas of land consolidation increases by 7.23%. This reveals that the land consolidation measures have brought about a certain degree of ecological and economic effectiveness.(3) CP, POP, GDP, Slope, and DEM have a negative correlation with ESV, and PRE shows a positive correlation with ESV. Socio-economic factors CP, POP, and GDP have a more significant influence on ESV compared to natural factors, indicating that the intensity of human activities has a more obvious influence on the change of ecological assets compared to natural factors.

Key words: ecological assets, land consolidation, ecosystem services value, Maogang town

潘路康, 陆衍, 过仲阳, 杜欣怡, 李永阔. 土地整治区域生态资产的变化研究——以上海市松江区泖港镇为例[J]. 世界地理研究, 2024, 33(12): 119-130.

Lukang PAN, Yan LU, Zhongyang GUO, Xinyi DU, Yongkuo LI. Research on changes of ecological assets in land consolidation areas: A case study of Maogang Town[J]. World Regional Studies, 2024, 33(12): 119-130.

图/表 9

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土地利用类型	生态系统类型
林地	森林生态系统
绿草地	草地生态系统
河流、湖泊、水产养殖用地	湿地生态系统
耕地	农田生态系统
建设用地、未利用地	城镇生态系统

土地利用类型	生态系统类型
林地	森林生态系统
绿草地	草地生态系统
河流、湖泊、水产养殖用地	湿地生态系统
耕地	农田生态系统
建设用地、未利用地	城镇生态系统

生态系统类型	评价指标	分级标准
生态系统类型	评价指标	优	良	中	差	劣
林地	相对生物量密度	≥85%	70%~85%	50%~70%	25%~50%	＜25%
草地	植被覆盖度	≥85%	70%~85%	50%~70%	25%~50%	＜25%
耕地	耕地地力指数	≥85%	70%~85%	50%~70%	25%~50%	＜25%
湿地	水质等级	Ⅰ类	Ⅱ类	Ⅲ类	Ⅳ类	Ⅴ类和劣Ⅴ类

生态系统类型	评价指标	分级标准
生态系统类型	评价指标	优	良	中	差	劣
林地	相对生物量密度	≥85%	70%~85%	50%~70%	25%~50%	＜25%
草地	植被覆盖度	≥85%	70%~85%	50%~70%	25%~50%	＜25%
耕地	耕地地力指数	≥85%	70%~85%	50%~70%	25%~50%	＜25%
湿地	水质等级	Ⅰ类	Ⅱ类	Ⅲ类	Ⅳ类	Ⅴ类和劣Ⅴ类

时间	城镇生态系统	森林生态系统	草地生态系统	湿地生态系统	农田生态系统
2017	14.53	13.23	3.14	6.18	20.40
2019	14.83	12.90	2.87	6.18	20.68
2022	15.94	14.04	2.33	6.14	19.03

土地整治区域生态资产的变化研究——以上海市松江区泖港镇为例

Research on changes of ecological assets in land consolidation areas: A case study of Maogang Town

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Metrics

类型	优			良			中			差			劣
类型	2017	2022	变化量	2017	2022	变化量	2017	2022	变化量	2017	2022	变化量	2017	2022	变化量
林地	1.30	3.71	2.42	3.24	4.98	1.74	4.21	4.05	-0.17	3.52	1.24	-2.28	0.96	0.07	-0.90
草地	1.70	1.49	-0.21	0.88	0.63	-0.25	0.45	0.20	-0.26	0.10	0.01	-0.09	0.01	0.00	-0.01
湿地	0.00	0.00	0.00	0.00	0.00	0.00	6.18	6.14	-0.04	0.00	0.00	0.00	0.00	0.00	0.00
耕地	3.44	3.10	-0.34	5.38	4.35	-1.03	9.06	7.96	-1.10	1.78	2.23	0.45	0.74	1.39	0.65

时间	综合指数	林地指数	草地指数	湿地指数	耕地指数
2017年	49.54	13.94	4.73	6.45	24.42
2019年	46.26	11.61	3.82	6.45	24.38
2022年	50.38	18.49	3.68	6.41	21.80
变化量	0.84	4.55	-1.05	-0.04	-2.62
变化率/%	1.70	32.64	-22.20	-0.62	-10.73

ESV	2017年		2019年		2022年
ESV	价值/万元	比例/%	价值/万元	比例/%	价值/万元	比例/%
合计	49 062.41	100	45 599.69	100	49 337.27	100
固碳释氧	628.80	1.28	303.29	0.66	818.26	1.66
土壤保持	429.17	0.88	363.20	0.80	613.43	1.24
空气净化	222.26	0.45	216.58	0.47	234.90	0.48
水质净化	404.80	0.83	404.96	0.89	402.43	0.81
气候调节	27 472.01	55.99	27 458.83	60.22	27 336.78	55.41
水源涵养	19 905.37	40.57	16 852.82	36.96	19 931.48	40.40

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