近年来，人类对自然资源的开发力度逐渐增强，出现了如生态质量降低、生物多样性下降和生态环境污染加重等一系列环境问题。快速发展的社会经济与脆弱的生态环境矛盾日益加深，对区域生态安全造成威胁，严重影响了生态文明建设与区域协调发展，景观格局演变分析、生态质量评估和生态安全网络构建等研究应时而生。在生态文明建设背景下，研究土地覆盖的景观生态效应及评价区域生态安全水平，分析区域土地开发利用对生态环境的影响，进而在区域生态系统宏观尺度下，识别选取核心保护区域、重要路径和战略节点，构建并优化区域生态安全网络对提升区域环境质量与生态保护具有重要意义。
本文以位于黄土丘陵沟壑区的陕西省甘泉县为研究区，选取2010、2015、2020年3期土地利用数据，利用土地动态度模型、土地利用综合指数、景观指数法等分析甘泉县土地利用和景观格局变化；通过景观生态安全评价模型，探究甘泉县景观生态安全水平时空演变规律，并采用空间自相关模型分析甘泉县生态安全的空间相关性；在此基础上，通过生态系统服务价值计算和最小累积阻力模型构建甘泉县2020年生态安全网络并提出优化策略。研究主要结论如下：
（1）2010-2020年，甘泉县林地与耕地面积占比最大，其他用地动态度差异性最为明显，达到27.59%；综合土地利用动态度仅为0.48%，甘泉县土地利用类型面积变化相对平稳；土地利用综合指数由2010年的212.51%增加到2015年的213.84%，又下降到2020年的212.90%；在土地转换类型方面，耕地是甘泉县主要转出类型，林地是其主要转入类型；研究期间甘泉县斑块离散程度为增强趋势，景观形状复杂程度加大，斑块数量增加而平均面积减小，景观连通程度处于下降特征，景观异质性增强特征明显，景观类型分布较为均衡，有微弱下降趋势。
（2）2010-2020年，甘泉县的生态安全水平西南部高于中部和北部，整体上呈现以县域为中心向四周扩散的特征；面积变化上，2010-2020年甘泉县高生态安全、较高生态安全区域面积分别增加51.47km2、107.66km2，占比从14.63%、20.04%增加到16.90%、24.78%，中等生态安全区域占比由24.29%增加到26.06%，较低和低生态安全区域占比分别由23.54%、17.49%降至18.90%、13.37%，甘泉县生态安全水平处于良性发展趋势；在空间自相关分析中，全局自相关指数分别为0.6062、0.6115、0.5535，表明甘泉县生态安全具有显著的空间正相关性，局部自相关分析结果显示甘泉县生态安全空间分布均以“高-高”和“低-低”两个集聚类型为主，其他集聚区占比较低。
（3）从生态安全水平、生态服务价值评估和生态保护区3个层面提取甘泉县生态源地，生态源地面积约为441.66km2，占总面积的19.43%；在生态属性和干扰方面共选取7项阻力因子，确定权重并构建甘泉县综合阻力面；在此基础上采用最小累积阻力模型提取甘泉县生态廊道21条，借助水文分析工具提取生态节点93个，综合得到甘泉县2020年生态安全网络并提出优化策略：生态源地覆盖的生态保护区、洛河投入较多人力物力，划定林区、水域生态源地保护红线，生态源地未覆盖的石门镇、劳山乡和下寺湾镇北部应因地制宜的开发建设；生态廊道构建与城镇规划相联系，下寺湾镇北部、道镇南部地区适宜增加林草地与水域，同时通过造林工程构建河流、森林等缓冲区，扩展并丰富生态廊道与生态节点。

In recent years, human beings have gradually increased their efforts to develop natural resources, and a series of environmental problems have emerged, such as a decline in ecological quality, a decline in biodiversity, and aggravation of ecological environment pollution. The contradiction between the rapidly developing social economy and the fragile ecological environment is deepening, posing a threat to regional ecological security and seriously affecting the construction of ecological civilization and the coordinated development of the region. . Under the background of ecological civilization construction, study the landscape ecological effect of land cover and evaluate the regional ecological security level, analyze the impact of regional land development and utilization on the ecological environment, and then identify and select core protection areas, important paths and As a strategic node, building and optimizing a regional ecological safety network is of great significance to improving regional environmental quality and ecological protection. This paper takes Ganquan County, Shaanxi Province, which is located in the loess hilly and gully area, as the research area, selects the land use data of 2010, 2015, and 2020, and uses the land dynamic model, comprehensive land use index, and landscape index method to analyze the land use and land use in Ganquan County. Landscape pattern change characteristics; through the landscape ecological security evaluation model, explore the landscape ecological security change characteristics and temporal and spatial evolution laws in Ganquan County, and use the spatial autocorrelation model to analyze the spatial correlation of ecological security in Ganquan County; on this basis, through the ecosystem services The value calculation and the minimum cumulative resistance model construct the ecological safety network of Ganquan County in 2020 and propose optimization strategies. The main conclusions of the study are as follows: (1) From 2010 to 2020, the forest land and cultivated land accounted for the largest proportion in Ganquan County, and the difference in the dynamic degree of other land use was the most obvious, reaching 27.59%; the comprehensive land use dynamic degree was only 0.48%, and the changes in the area of land use types in Ganquan County were relatively stable; The comprehensive land use index increased from 212.51% in 2010 to 213.84% in 2015, and then dropped to 212.90% in 2020; in terms of land conversion types, cultivated land is the main type of transfer out of Ganquan County, and forest land is the main type of transfer in. During the study period, the patch dispersion degree in Ganquan County showed an increasing trend, the complexity of the landscape shape increased, the number of patches increased and the average area decreased, the degree of landscape connectivity was declining, the landscape heterogeneity was enhanced significantly, and the distribution of landscape types was relatively balanced, with a slight downward trend. (2) From 2010 to 2020, the ecological security level of Ganquan County in the southwest was higher than that in the central and northern parts, showing the characteristics of spreading around the county as a whole; in terms of area change, from 2010 to 2020, Ganquan County had high ecological security and relatively low ecological security. The area of high ecological areas increased by 51.47km² and 107.66km² respectively, and the proportion increased from 14.63% and 20.04% to 16.90% and 24.78%. The proportion of medium ecological security increased from 24.29% to 26.06%, and the proportion of low and low ecological security areas increased from 24.29% to 26.06%. From 23.54% and 17.49% to 18.90% and 13.37% respectively, the ecological security level of Ganquan County is in a benign development trend; in the spatial autocorrelation analysis, the global autocorrelation indices are 0.6062, 0.6115 and 0.5535, respectively, indicating that the ecological security of Ganquan County has a high level of development. There is a significant positive spatial correlation. The results of local autocorrelation analysis show that the spatial distribution of ecological security in Ganquan County is dominated by two agglomeration types of "high-high" and "low-low", and other agglomeration areas account for a lower proportion. (3) The ecological source land of Ganquan County is extracted from three levels of ecological security level, ecological service value assessment and ecological protection area. The ecological source land area is about 441.66 km², accounting for 19.43% of the total area; a total of ecological attributes and interference are selected 7 resistance factors; determine the weights and construct the comprehensive resistance surface of Ganquan County; on this basis, the MCR model is used to extract 21 ecological corridors in Ganquan County, and 93 ecological nodes are extracted with the help of hydrological analysis tools, and the ecological safety network of Ganquan County in 2020 is comprehensively obtained. And put forward optimization strategies: ecological protection areas covered by ecological sources and Luohe will invest more manpower and material resources, delineate the protection red lines of forest areas and water ecological sources, and Shimen Town, Laoshan Township and Xiasi Bay that are not covered by ecological sources. The northern part of the town should be developed and constructed according to local conditions; the construction of ecological corridors is linked to urban planning. It is suitable to increase forests, grasslands and water areas in the northern part of Xiasiwan Town and the southern part of Dao Town. Expand and enrich ecological corridors and ecological nodes.

[1] 吴浩, 吴霞, 王伟, 等. 2000年以来长江经济带土地利用时空演化分析与模拟研究[J].华中师范大学学报(自然科学版). 2019, 53(5): 692-702.

[2] 王秉义. 巢湖流域土地利用演变的生态响应与优化模拟研究[D]. 徐州: 中国矿业大学, 2018.

[3] 张杰. 东江流域景观生态风险评估及预测研究[D]. 大连: 辽宁师范大学, 2019.

[4] 许文雯, 孙翔, 朱晓东, 等. 基于生态安全网络分析的南京主城区重要生态斑块识别[J]. 生态学报, 2012, 32(4): 260-268.

[5] 李静, 朱永明, 张慧, 等. 北戴河新区景观生态安全网络源地动态识别[J]. 水土保持研究, 2016, 23(6): 340-344+351.

[6] 储金龙, 王佩, 顾康康, 等. 山水型城市生态安全格局构建与建设用地开发策略[J].生态学报, 2016, 36(23): 7804-7813.

[7] 宋佳佳. 基于遥感生态指数的拜泉县土地利用生态环境评价研究[D]. 长春: 东北农业大学, 2019.

[8] 彭建, 李慧蕾, 刘焱序, 等. 雄安新区生态安全网络识别与优化策略[J]. 地理学报, 2018, 73(4): 701-710.

[9] 李建春, 袁文华. 基于GIS格网模型的银川市土地生态安全评价研究[J]. 自然资源学报, 2017, 32(6): 988-1001.

[10] Rindfuss R R, Entwisle B, Walsh S J, et al. Land use change: complexity and comparisons[J]. Journal of land use science, 2008, 3(1): 1-10.

[11] 李虹睿. 娄烦县土地利用景观格局演变及其生态风险评价[D]. 太原: 山西大学, 2019.

[12] Qian F, Wang W, Zhang J, et al. Analysis on land use research progress by CiteSpace[J]. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(2): 344-351.

[13] Koko A F, Wu Y, Abubakar G A, et al. Monitoring and Predicting Spatio-Temporal LandUse/Land Cover Changes in Zaria City, Nigeria, through an Integrated Cellular Automataand Markov Chain Model (CA-Markov)[J]. Sustainability, 2020, 12(24): 104-112.

[14] Meyer M A, Früh-Müller A. Patterns and drivers of recent agricultural land-use change inSouthern Germany[J]. Land Use Policy, 2020, 99(10): 49-59.

[15] Suroso, Krishna K P, Santoso P B. Impact of Land Use Land Cover Changes on River Discharge at Brantas Catchment Area using SHETRAN Model[J]. IOP Conference Series:Materials Science and Engineering, 2020, 982(1): 20-37.

[16] 王少华. 郑州沿黄旅游区土地利用空间格局演变[J]. 地域研究与开发, 2017, 36(6): 115-118+130

[17] 邬亚娟, 刘廷玺, 童新, 等. 基于长时间序列landsat数据的科尔沁沙地土地利用演变分析[J]. 生态学报, 2020, 40(23): 8672-8682.

[18] Gergel S E, Turner M G, Miller J R, et al. Landscape indicators of human impacts to riverine systems. Aquatic Sciences. 2002, 64(2): 118 -128.

[19] Hermann A, Kuttner M, Hainz-Renetzeder C, et al. Assessment framework for landscape services in European cultural landscapes: An Austrian Hungarian case study[J]. Ecological Indicators, 2014, 37: 229-240.

[20] He Y, Chen G, Cobb R C, et al. Forest landscape patterns shaped by interactions between wildfire and sudden oak death disease[J]. Forest Ecology and Management, 2021, 486: 118987.

[21] Pei L, Shoujun J, Ruimei H, et al. Landscape Pattern and Ecological Security Assessment and Prediction Using Remote Sensing Approach [J]. Journal of Sensors, 2018, 2018:1-14.

[22] 陈昆仑, 齐漫, 王旭, 等. 1995-2015年武汉城市湖泊景观生态安全网络演化[J]. 生态学报, 2019, 39(5): 1725-1734.

[23] 卢晓宁, 黄玥, 洪佳, 等. 基于Landsat的黄河三角洲湿地景观时空格局演变[J]. 中国环境科学, 2018, 38(11): 4314-4324.

[24] 田雨, 周宝同, 付伟, 等. 2000-2015年山地城市土地利用景观格局动态演变研究-以重庆市渝北区为例[J]. 长江流域资源与环境, 2019, 28(6): 1344-1353.

[25] 王权, 李阳兵. 岩溶槽谷区地形起伏特征及其对景观格局的影响[J]. 山地学报, 2019, 37(5): 702-716.

[26] 易阿岚, 王钧. 上海市湿地景观格局时空演变与驱动机制的量化研究[J]. 生态学报, 2021, 41(7): 2622-2631.

[27] Xu Q, Wang W, Mo L. Evaluation of landscape stability in Beijing-Tianjin-Hebei region [J]. Acta Ecologica Sinica, 2018, 38(12): 4226-4233.

[28] 张起鹏, 王建, 张志刚, 等. 高寒草甸草原景观格局动态演变及其驱动机制[J]. 生态学报, 2019, 39(17): 6510-6521.

[29] 欧定华. 城市近郊区景观生态安全网络构建研究-以成都市龙泉驿区为例[D]. 雅安:四川农业大学, 2016.

[30] 庞雅颂, 王琳. 区域生态安全评价方法综述[J]. 中国人口•资源与环境, 2014, 24(S1): 340-344.

[31] Jogo W, Hassan R. Balancing the use of wetlands for economic well-being and ecological security: The case of the Limpopo wetland in southern Africa[J]. Ecological Economics, 2010, 69(7): 1569-1579.

[32] Sajjad H, Nasreen I, Shahzad, et al. Assessing Spatiotemporal Variation in Agricultural Sustainability Using Sustainable Livelihood Security Index: Empirical Illustration from Vaishali District of Bihar, India[J]. Journal of Sustainable Agriculture, 2014, 38(1):46-68.

[33] Theisen G, Silva J J C, Silva J S, et al. The birth of a new cropping system: towards sustainability in the sub-tropical lowland agriculture[J]. Field Crops Research, 2017, 212: 82-94.

[34] Velde M V D, Ye L. Assessing the impact of soil degradation on food production [J]. Current Opinion in Environmental Sustainability, 2012, 4(5): 478-488.

[35] Fischer G, Shah M, Tubiello F, et al. Socio-economic and climate change impacts on agriculture: An integrated assessment, 1990-2080 [J]. Philosophical Transactions of The Royal Society B: Biological Sciences, 2005, 360: 2067-2083.

[36] 雷金睿, 陈宗铸, 陈毅青, 等. 1990-2018年海南岛湿地景观生态安全网络演变[J]. 生态环境学报, 2020, 29(2): 293-302.

[37] 杨青生, 乔纪纲, 艾彬. 快速城市化地区景观生态安全时空演化过程分析-以东莞市为例[J]. 生态学报, 2013, 33(4): 1230-1239.

[38] 虞继进, 陈雪玲, 陈绍杰. 基于遥感和PSR模型的城市景观生态安全评价-以福建省龙岩市为例[J]. 国土资源遥感, 2013, 25(1): 143-149.

[39] 宋晓媚, 周忠学, 王明. 城市化过程中都市农业景观变化及其生态安全评价-以西安市为例[J]. 冰川冻土, 2015, 37(3): 835-844.

[40] 韩逸, 郭熙, 江叶枫, 等. 南方丘陵区耕地景观生态安全影响因素及其空间差异[J].生态学报, 2019, 39(17): 6522-6533.

[41] 罗斌, 杨雄, 何毅. 基于耦合赋权法与灰色关联法在小流域生态安全评价中的应用[J]. 三峡大学学报(自然科学版), 2020, 42(1): 7-12.

[42] 王毅, 魏江超, 孙启元, 等. 基于ARIMA-ANN模型的生态安全评价及预测-以河西走廊城市群为例[J]. 生态学杂志, 2020, 39(1): 326-336.

[43] 李杨帆, 林静玉, 孙翔. 城市区域生态风险预警方法及其在景观生态安全网络调控中的应用[J]. 地理研究, 2017, 36(3): 485-494.

[44] 梁发超, 刘浩然, 刘诗苑, 等. 闽南沿海景观生态安全网络空间重构策略-以厦门市集美区为例[J]. 经济地理, 2018, 38(9): 231-239.

[45] World Environment and Development Commissions. Our Common Future[M]. Jilin: Jilin People Press, 1997: 23.

[46] Blaikie P. Epilogue: Towards a future for political ecology that works[J]. Geoforum, 2008, 39(2): 765-772.

[47] Yu K. Security patterns and surface model in landscape ecological planning[J]. Landscape & Urban Planning, 1996, 36(1): 1-17.

[48] Motesharrei S, Rivas J, Kalnay E, et al. Modeling sustainability: population, inequality, consumption, and bidirectional coupling of the Earth and Human Systems[J]. National Science Review, 2016, 3(4): 470-494.

[49] Pickard B R, Daniel J, Mehaffey M, et al. EnviroAtlas: A new geospatial tool to foster ecosystem services science and resource management[J]. Ecosystem Services, 2015, 14: 45-55.

[50] 彭建, 贾靖雷, 胡熠娜, 等. 基于地表湿润指数的农牧交错带地区生态安全网络构建-以内蒙古自治区杭锦旗为例[J]. 应用生态学报, 2018, 29(6): 1990-1998.

[51] 杜悦悦, 胡熠娜, 杨旸, 等. 基于生态重要性和敏感性的西南山地生态安全网络构建-以云南省大理白族自治州为例[J]. 生态学报, 2017, 37(24): 8241-8253.

[52] 王天宇, 惠怡安, 师莹, 等. 延河流域景观格局的演变、预测及优化-以陕西省延长县为例[J]. 水土保持通报, 2020, 40(6): 130-136+329.

[53] 杨姗姗, 邹长新, 沈渭寿, 等. 基于生态红线划分的生态安全网络构建-以江西省为例[J]. 生态学杂志, 2016, 35(1): 250-258.

[54] 杨天荣, 匡文慧, 刘卫东, 等. 基于生态安全网络的关中城市群生态空间结构优化布局[J]. 地理研究, 2017, 36(3): 441-452.

[55] 赵宏波, 马延吉. 东北粮食主产区耕地生态安全的时空格局及障碍因子-以吉林省为例[J]. 应用生态学报, 2014, 25(2): 515-524.

[56] 侯鹏, 杨旻, 翟俊, 等. 论自然保护地与国家生态安全网络构建[J]. 地理研究, 2017, 36(3): 420-428.

[57] 蒙吉军, 朱利凯, 杨倩, 等. 鄂尔多斯市土地利用生态安全网络构建[J]. 生态学报, 2012, 32(21): 6755-6766.

[58] 倪庆琳, 侯湖平, 丁忠义, 等. 基于生态安全网络识别的国土空间生态修复分区-以徐州市贾汪区为例[J]. 自然资源学报, 2020, 35(1): 204-216.

[59] 张天海, 田野, 徐舒, 等. 滨海城市土地利用格局演变及对生态系统服务价值的影响[J]. 生态学报, 2018, 38(21): 7572-7581.

[60] 彭建, 赵会娟, 刘焱序, 等. 区域水安全格局构建:研究进展及概念框架[J]. 生态学报, 2016, 36(11): 3137-3145.

[61] 胡海德, 李小玉, 杜宇飞. 大连城市生态格局的构建[J]. 东北师大学报(自然科学版), 2013, 45(1): 138-143.

[62] 王秀兰, 包玉海. 土地利用动态变化研究方法探讨[J]. 地理科学进展, 1999, 18(1): 83-89.

[63] 庄大方, 刘纪. 中国土地利用程度的区域分异模型研究[J]. 自然资源学报, 1997(2): 10-16.

[64] 王玲, 米文宝, 王鑫, 等. 限制开发生态区土地利用变化驱动力分析-以宁夏西吉县为例[J]. 干旱区资源与环境, 2019, 33(1): 51-57.

[65] Kowe P, Mutanga O, Dube T. Advancements in the remote sensing of landscape pattern of urban green spaces and vegetation fragmentation[J]. International Journal of Remote Sensing, 2021, 42(10): 3797-3832.

[66] He Y F. Analysis of spatial behavior characteristics of land use in Poyang Lake area based on fractal theory [J]. Journal of Resources and Ecology, 2021, 12(2): 192-202.

[67] 张小强, 王云燕, 黄娟. 2010-2015年江苏省环太湖及沿海地区土地利用变化和生态风险分析[J]. 安徽农业科学, 2020, 48(17): 97-103+132.

[68] 潘竟虎, 刘晓. 疏勒河流域景观生态风险评价与生态安全网络优化构建[J]. 生态学杂志, 2016, 35(3): 791-799.

[69] 许凤娇. 基于土地利用变化的江苏沿海地区生态风险格局[D]. 曲阜: 曲阜师范大学, 2018.

[70] Singh K, Kumar V. Hazard assessment of landslide disaster using information value method and analytical hierarchy process in highly tectonic Chamba region in bosom of Himalaya[J]. Journal of Mountain science, 2018, 15(4): 808-824.

[71] 丁雪姣, 沈强, 聂超甲, 等. 省域尺度下不同时序景观指数集与粒度效应分析[J]. 中国农业资源与区划, 2019, 40(3): 111-120.

[72] Li Q, Guo F, Guan Y. A GIS-Based Evaluation of Environmental Sensitivity for an UrbanExpressway in Shen-zhen, China[J]. Engineering, 2018, 4(2): 230-234.

[73] 史娜娜, 韩煜, 王琦, 等. 青海省保护地生态安全网络构建与优化[J]. 生态学杂志, 2018, 37(6): 1910-1916.

[74] 付梦娣, 罗建武, 田瑜, 等. 基于最小累积阻力模型的自然保护区网络构建与优化-以秦岭地区为例[J]. 生态学杂志, 2018, 37(4): 1135-1143.

[75] 谢高地, 张彩霞, 张雷明, 等. 基于单位面积价值当量因子的生态系统服务价值化方法改进[J]. 自然资源学报, 2015, 30(8): 1243-1254.

[76] 李怡, 郭力宇, 温豪. 陕西渭北旱塬区土地利用与生态系统服务价值变化-以陇县为例[J]. 水土保持研究, 2019, 26(1): 368-373.

[77] Schirpke U, Kohler M, Leitinger G, et al. Future impacts of changing land-use and climate on ecosystem services ofmountain grassland and their resilience [J]. Ecosystem Services, 2017, 26: 79-94.

[78] 刘媛. 基于MCR模型的志丹县土地利用生态安全网络构建[D]. 西安: 长安大学, 2017.

[79] 汪宏伟. 瓦埠湖流域核心区景观格局变化与生态安全网络构建研究[D]. 合肥: 安徽建筑大学, 2021.

[80] Knaapen J P, Scheffer M, Harms B. Estimating habitat isolation in landscape planning[J]. Landscape & Urban Planning, 1992, 23(1):1-16.

[81] Cushman S A, Elliot N B, Macdonald D W, et al. A multi-scale assessment of population connectivity in African lions (Panthera leo) in response to landscape change[J]. Landscape Ecology, 2016, 31(6): 1337-1353.

[82] Zeller K A, Mcgarigal K, Cushman S A, et al. Using step and path selection functions for estimating resistance to movement: pumas as a case study[J]. Landscape Ecology, 2016, 31(6):1319-1335.