哈尔滨市景观生态风险时空变化驱动力及分布预测

doi:10.13474/j.cnki.11-2246.2022.0048

测绘通报 ›› 2022, Vol. 0 ›› Issue (2): 83-89,94.doi: 10.13474/j.cnki.11-2246.2022.0048

哈尔滨市景观生态风险时空变化驱动力及分布预测

张玉娟, 曲建光, 侯建国

黑龙江工程学院测绘工程学院, 黑龙江哈尔滨 150050

收稿日期:2021-01-19 修回日期:2021-12-01 发布日期:2022-03-11
作者简介:张玉娟(1979-),女,博士,副教授,主要研究方向为遥感与地理信息应用。E-mail:zyjamy@126.com
基金资助:
黑龙江省博士后专项经费（LBH-Q20171）；黑龙江省省属本科高校基本科研业务费（2020CX01）；黑龙江工程学院省级领军人才梯队培育计划（2020LJ01）；国家自然科学基金（31800538）

Spatial-temporal change driving forces and distribution prediction of landscape ecological risk in Harbin

ZHANG Yujuan, QU Jianguang, HOU Jianguo

College of Surveying and Mapping Engineering, Heilongjiang Institute of Technology, Harbin 150050, China

Received:2021-01-19 Revised:2021-12-01 Published:2022-03-11

摘要/Abstract

摘要： 本文以哈尔滨市为研究对象，首先构建了景观生态风险及预测模型；然后对1998—2018年景观生态风险时空变化驱动力进行分析；最后对研究区域2023年景观生态风险空间分布进行预测。结果表明：①研究区域近20年景观生态风险先降低后升高，空间格局变化较为显著。②道路距离、第二产业、农业、高程为景观生态风险变化主要驱动力。1998—2008年，主城区周围道路距离系数逐年减小，南部地区逐年增高，其他时间内未见明显变化；农业和高程对区域景观生态风险的总体影响显著，存在空间差异；第二产业对区域景观生态风险影响程度呈现先增后降的变化。③预测所得的2023年景观生态风险空间差别不明显，降低区域比升高区域面积大。

关键词: 景观生态风险, 生态服务价值, 地理加权回归, 灰色预测, 哈尔滨市

Abstract: This paper takes Harbin as the research object,constructs a landscape ecological risk and prediction model, analyzes the driving force of temporal and spatial change of landscape ecological risk from 1998 to 2018, and predicts the spatial distribution of regional landscape ecological risk in 2023. The results show that：①The regional landscape ecological risk decreased firstly and then increased in recent 20 years, and the spatial pattern changed significantly. ②Road distance, secondary industry, agriculture and elevation are the main driving forces for the change of landscape ecological risk. From 1998 to 2008, the distance coefficient of roads decreased around the main urban area and increased in the south. No significant change was observed at other times.The overall impact of agriculture and elevation on regional landscape ecological risk was significant, and there were spatial differences. The degree of impact of secondary sector of the economy on regional landscape ecological risk increased first and then decreased. ③The predicted spatial difference of landscape ecological risk in 2023 is not obvious, and the reduced area is larger than the increased area.

Key words: landscape ecological risk, ecological service value, geographically weighted regression, grey prediction, Harbin city

中图分类号:

P208

张玉娟, 曲建光, 侯建国. 哈尔滨市景观生态风险时空变化驱动力及分布预测[J]. 测绘通报, 2022, 0(2): 83-89,94.

ZHANG Yujuan, QU Jianguang, HOU Jianguo. Spatial-temporal change driving forces and distribution prediction of landscape ecological risk in Harbin[J]. Bulletin of Surveying and Mapping, 2022, 0(2): 83-89,94.

参考文献

[1] 曹祺文,张曦文,马洪坤,等.景观生态风险研究进展及基于生态系统服务的评价框架:ESRISK[J].地理学报, 2018, 73(5):843-855.
[2] 彭建,党威雄,刘焱序,等.景观生态风险评价研究进展与展望[J].地理学报, 2015, 70(4):664-677.
[3] XIE H, WANG P, HUANG H. Ecological risk assessment of land use change in the Poyang Lake Eco-economic Zone, China[J]. International Journal of Environmental Research and Public Health, 2013, 10(1):328-346.
[4] FAN Jiahui, WANG Ya, ZHOU Zhen, et al. Dynamic ecological risk assessment and management of land use in the middle reaches of the Heihe river based on landscape patterns and spatial statistics[J]. Sustainability, 2016, 8(6):536.
[5] 周汝佳,张永战,何华春.基于土地利用变化的盐城海岸带生态风险评价[J].地理研究, 2016, 35(6):1017-1028.
[6] PENG Jian, ZONG Minli, HU Yina, et al. Assessing landscape ecological risk in a mining city:a case study in Liaoyuan city, China[J]. Sustainability, 2015, 7(7):8312-8334.
[7] 吕乐婷,张杰,孙才志,等.基于土地利用变化的细河流域景观生态风险评估[J].生态学报, 2018, 38(16):5952-5960.
[8] LEUVEN R S E W, POUDEVIGNE I. Riverine landscape dynamics and ecological risk assessment[J]. Freshwater Biology, 2002, 47(4):845-865.
[9] 汪翡翠,汪东川,张利辉,等.京津冀城市群土地利用生态风险的时空变化分析[J].生态学报, 2018, 38(12):4307-4316.
[10] 税伟,付银,林咏园,等.基于生态系统服务的城市生态安全评估、制图与模拟[J].福州大学学报(自然科学版), 2019, 47(2):143-152.
[11] SHRESTHA M K, YORK A M, BOONE C G, et al. Land fragmentation due to rapid urbanization in the Phoenix Metropolitan Area:analyzing the spatiotemporal patterns and drivers[J]. Applied Geography, 2012, 32(2):522-531.
[12] 王海军,张彬,刘耀林,等.基于重心-GTWR模型的京津冀城市群城镇扩展格局与驱动力多维解析[J].地理学报, 2018, 73(6):1076-1092.
[13] CABRAL P,ZAMYATIN A. Markov processes in modeling land use and land cover changes in Sintra-Cascais,portugal[J].DYNA,2009,76(158):191-198.
[14] 宋丽丽,白中科.煤炭资源型城市生态风险评价及预测:以鄂尔多斯市为例[J].资源与产业, 2017, 19(5):15-22.
[15] 刘春艳,张科,刘吉平. 1976-2013年三江平原景观生态风险变化及驱动力[J].生态学报, 2018, 38(11):3729-3740.
[16] 陈彧,李江风,徐佳.基于生态功能分区的湖北省土地利用及其生态服务价值变化研究[J].国土资源科技管理, 2015, 32(3):25-33.
[17] 王惠,许月卿,刘超,等.基于地理加权回归的生境质量对土地利用变化的响应:以河北省张家口市为例[J].北京大学学报(自然科学版), 2019, 55(3):509-518.
[18] BROWN C W, HOOD R R, LONG W, et al. Ecological forecasting in Chesapeake Bay:using a mechanistic-empirical modeling approach[J]. Journal of Marine Systems, 2013, 125:113-125.
[19] RICCIARDI A, AVLIJAS S, MARTY J. Forecasting the ecological impacts of the Hemimysis anomala invasion in North America:lessons from other freshwater mysid introductions[J]. Journal of Great Lakes Research, 2012, 38:7-13.
[20] 程珍珍,张永福,范小晶,等.基于GIS干旱区绿洲县域土地利用生态风险分析及动态预测[J].安徽农业科学, 2018, 46(3):44-48.
[21] 张月,张飞,王娟,等.基于LUCC的艾比湖区域生态风险评价及预测研究[J].中国环境科学,2016,36(11):3465-3474.
[22] 马丽娜,张永福,阿地来·阿地力.基于GIS的干旱区绿洲县域土地利用生态风险分析及预测[J].安徽农业科学, 2019, 47(2):52-56.
[23] 康璇.渭干河-库车河三角洲绿洲生态风险评价及预警研究[D].乌鲁木齐:新疆师范大学, 2017.
[24] 刘引鸽.西北地区生态风险态势及预测[J].中国农学通报, 2014, 30(23):133-138.
[25] 谢高地,张彩霞,张昌顺,等.中国生态系统服务的价值[J].资源科学, 2015, 37(9):1740-1746.
[26] 张玉娟,曲建光,王雷.生态系统服务价值时空变化及分布均匀度变化分析[J].福州大学学报(自然科学版), 2020, 48(5):653-660.

哈尔滨市景观生态风险时空变化驱动力及分布预测

Spatial-temporal change driving forces and distribution prediction of landscape ecological risk in Harbin

RichHTML

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 11

编辑推荐

Metrics

本文评价

[1]	艾敏, 景慧, 田禹东, 郭兰勤, 裴渊杰. 近20年哈尔滨市呼兰区土地利用覆盖变化及驱动分析[J]. 测绘通报, 2022, 0(7): 124-128.
[2]	张瑞, 李朝奎, 姚思妤, 李维贵. 融合地理探测器和地理加权回归的太原市建设用地变化因素研究[J]. 测绘通报, 2022, 0(5): 106-109,119.
[3]	张兰兰, 吴启明, 申朝永, 刘芳, 陈砚国. 地理空间要素与贫困分布的关系研究——以赫章县为例[J]. 测绘通报, 2021, 0(12): 120-123,129.
[4]	高照忠, 黄雅君, 魏海霞, 张金兰. 近30年云贵高原水蚀荒漠化遥感监测及影响因子时空分异规律[J]. 测绘通报, 2021, 0(10): 117-122.
[5]	刘振涛, 杨毅, 王东超, 谢晓尧. 一种基于CUDA的大数据量地理加权回归并行加速算法[J]. 测绘通报, 2020, 0(12): 1-5.
[6]	于志英, 张福浩, 仇阿根, 赵阳阳. 基于IGGⅢ的地理加权回归模型研究[J]. 测绘通报, 2019, 0(7): 23-27.
[7]	邓悦, 刘洋, 刘纪平, 徐胜华, 罗安. GBGWR模型在降水量空间分布模拟中的应用[J]. 测绘通报, 2018, 0(3): 32-37,42.
[8]	肖屹, 何宗宜, 苗静, 潘峰, 杨好. 利用搜索引擎数据模拟疾病空间分布[J]. 测绘通报, 2018, 0(2): 94-98.
[9]	董珍珍, 王亮, 仇阿根. 协同遥感信息与统计信息的人口空间格局分析[J]. 测绘通报, 2017, 0(5): 88-94.
[10]	武文娟, 徐京华, 时进, 任红艳, 王渊博. 基于GWR的四川省医院床位数时空分布及其影响因素研究[J]. 测绘通报, 2016, 0(4): 49-53.
[11]	龚循强熊小容周秀芳. 高铁桥墩沉降预测方法研究[J]. 测绘通报, 2014, 0(4): 48-50.