首页 | 官方网站   微博 | 高级检索  
相似文献
 共查询到19条相似文献,搜索用时 46 毫秒
1.
分析北部湾沿海地区广西钦州市土地利用格局及未来变化趋势,为开展该地区土地利用规划和生态服务价值中的水源涵养服务能力估算提供决策依据.以2000年、2010年的TM遥感影像以及各种驱动因子数据为基础,耦合Binary Logistic及CA-Markov模型对研究区2020年的土地利用格局进行模拟,并对研究区的水源涵养服务能力进行估算.结果表明:(1) 2000~2010年各种土地利用类型的转化强度大且比较复杂,尤以耕地、林地和水域之间的流动最为显著,建设占用耕地和林地的面积高达2 003.31 hm2;(2)由Binary Logistic逻辑斯蒂回归方程所得出的各种土地利用类型ROC拟合值中最小为0.686,最大达到0.952,模拟效果良好;(3)预测年2020年建设用地增加的区域主要集中在钦州市钦南区的市区周边,向东方向扩展,变化比较剧烈的地方主要是钦州港区和研究区域的北部;(4)单位面积水源涵养能力的排序依次为:水域>林地>草地>耕地>建设用地>未利用地,3个年份的水源涵养服务能力在空间上均呈现出“东南部高西北部低,中心地带持续衰减”的趋势.  相似文献   

2.
基于快速城镇化背景下秦淮河流域土地利用历史状况,选择CLUE-S模型对其2020年土地利用情况进行模拟预测。分别使用线性回归、Markov模型、灰色GM(1,1)模型预测CLUE-S模型非空间模块的土地利用需求量,再嵌入CLUE-S中得到3种预测结果,对预测结果进行比较。另外设定“自然发展”情景与考虑规划政策影响的“优化格局”情景,模拟2020年不同情景下秦淮河流域土地利用格局情况,并进行景观格局分析。结果表明:线性回归模型、Markov模型、灰色GM(1,1)模型的Kappa指数分别为0.866、0.849、0.867,3种方法均满足模型精度要求;自然发展情景中2020年水域、水田、林地、城镇用地、旱地面积相对于2010年分别变化21.5%、-15.3%、-9.0%、51.5%、-28.9%,而优化格局情景下水域、水田、林地、城镇用地、旱地面积分别变化3.1%、-1.6%、10.8%、6.3%、-10.6%,相比于自然发展情景,优化情景土地利用状况更符合保护基本农田、增加生态用地连通性、提高雨水下渗能力以及缓解城市热岛效应的要求,为后期土地利用规划提供了依据。  相似文献   

3.
大理市土地利用变化及其驱动力分析   总被引:1,自引:0,他引:1  
利用大理市1995年和2000年两期TM影像解译土地利用数据,在GIS分析工具支持下,对土地利用变化和驱动因素进行分析,得出以下结论:(1)1995年到2000年这5年期间,土地利用变化总体呈现出林地和草地减少、耕地和建筑用地增加的趋势,水域面积变化不明显;(2)土地利用年变化率为0.5%,其中以建设用地面积的年变化率最大为5.84%,耕地和林地的年变化率分别为1.85%和-1.41%,而草地和水域年变化率较小,分别为-0.7%和0.01%;(3)土地利用类型转化主要呈现出林地和草地转化为耕地,耕地和草地转化为建筑用地,林地和草地相互转化的特点;(4)土地利用结构变化不明显,总体上表现出林地占优势,耕地、草地、水域相当的结构特征;(5)自然条件对土地利用结构具有重要的控制作用,而人口增长,政府行为决策和经济的发展直接影响土地利用的变化。  相似文献   

4.
以遥感数据为基础数据源,通过人机交互判读提取广西大化县1988-2006年土地利用类型数据,并分析该区土地利用变化过程及其驱动力。基于中国陆地生态系统单位面积生态服务价值,对各地类生态服务价值重新赋值,估算近18年来研究区生态服务价值变化过程。结果表明:研究区土地利用变化明显,园地、城乡建设用地、裸岩砾石地持续增加,水田、中覆盖荒草地持续减少,旱地、水域先增后减,有林地、灌木林地、低覆盖荒草地先减后增,土地利用变化有明显的区域差异。脆弱生态环境与生存型经济双重驱动、库区建设、移民安置、人口增长、经济发展及国家政策是导致区域人地关系变化的主要动因。研究区土地利用变化对生态服务功能产生了显著影响,生态系统服务价值经历了先增后减的变化过程。调控区域土地利用方式,加大对国家生态政策实施力度,合理控制城镇建设用地的发展,是喀斯特库区持续发展的有效途径。探讨喀斯特地貌单元中土地利用变化的敏感区县,寻找区域土地利用类型的组合,是促进红水河梯级电站喀斯特库区生态服务价值良性发展的关键。  相似文献   

5.
以Landsat TM和HJ-1影像为数据源,运用CART(classification and regression tree)决策树分类方法提取了丹江口库区1990,1995,2000,2005,2010年的土地利用信息,在此基础上采用土地利用转移矩阵、土地利用动态度和单一土地利用类型相对变化率等评价指标全面分析了丹江口库区1990-2010年土地利用时空变化情况,并对土地利用变化的主要原因进行了探讨.研究表明:1990-2010年丹江口库区土地利用变化主要表现为灌木大量转化为林地,耕地大量转为草地、灌木、建设用地、林地和园地;库区地质地貌、降雨条件、生态建设工程、经济利益、库区工程建设、移民安置和城镇迁建以及城市化的发展是丹江口库区土地利用变化的主要驱动因素.丹江口库区土地利用变化研究为库区生态环境建设和土地可持续利用提供有效的决策支持.  相似文献   

6.
基于黑龙江省1960~2010年的土地利用变化,采用自然正交分解(EOF)、气候倾向率及Observation Minus Reanalysis (OMR)等方法,分析了土地利用变化对黑龙江省气温的影响。研究发现: 1960~2010年黑龙江省耕地、建设用地、水域面积依次增加,沼泽、草地和林地依次减少。土地利用变化区域性较明显,沼泽转变为耕地集中在东部,草地转为耕地集中分布在黑龙江省西部,沼泽转为林地和林地转为耕地集中在北部,建设用地增加主要集中在南部; 黑龙江省1960~2010年土地利用变化对年平均气温及各个季节平均气温均产生升高效应,但并不显著,对年气温的影响趋势为0.053℃/10a,贡献率为12.1%; 1960~2010年土地利用变化产生气温空间变化异质性,但没有改变气温纬向性空间分布特征; 1960~2010年,林地和沼泽的气温影响效应为升温,草地和耕地为降温,但各个季节有所差异,夏季和秋季表现出降温效应,建设用地全年及各个季节均表现出升温效应,冬季最强;林地转耕地、草地转耕地均以升温效应为主,沼泽转耕地为降温效应。  相似文献   

7.
土地利用变化研究是生态环境变化研究的重要基础,也是规范人类行为的科学决策依据。随着人口的持续增长和社会经济的快速发展,伊金霍洛旗土地利用发生了较大的变化。本文以伊金霍洛旗2009年~2012年土地利用统计资料为依据,利用土地利用土地利用转移矩阵、土地利用地类转入、转出动态度与活跃度模型等对该旗2009年~2012年的土地利用动态变化状况进行了分析。分析结果表明:伊金霍洛旗耕地、林地、草地、水域用地面积在减少,其他农用地、建设用地、其他土地在增加;其他农用地和建设用地年变化率达49.43%、3.993%;其他农用地转入和转出活跃度最大,为最活跃的土地利用类型;其次为建设用地;林地、草地和水域转入转出活跃度均为负值,反映出林地、草地和水域是一种比较稳定的土地利用类型。  相似文献   

8.
黄土台塬区土地利用转移流及空间集聚特征分析   总被引:17,自引:1,他引:16  
提出了土地利用转移流和土地利用活跃度的概念,基于Landsat 遥感影像数据,采用土地利用变化测度模型,以5 年和25 年两种时间尺度对黄土台塬区土地利用时空动态特征进行分析,并将密度制图法应用到土地利用变化的空间集聚特征识别中.研究表明:① 黄土台塬区耕地占绝对优势,后备耕地资源严重不足,林地、草地、水域比例较低,存在较大生态风险;② 耕地与建设用地、草地、林地之间的转移关系是黄土台塬区土地利用转移的关键关系,决定着台塬区土地利用变化特征;③ 1985-2010 年耕地转建设用地流高达26668.80 hm2,占土地转移流40.75%,草地转耕地流18923.90 hm2,占28.91%,建设占用耕地情况严重,耕地占补平衡主要通过挤占草地实现;④ 25 年以来,土地利用变化对水域扰动最大,其次为森林,草地第三;⑤ 土地利用变化存在阶段性,1990-2000 年土地利用变化速率高于其他时段;⑥不同时间尺度下土地利用变化的空间集聚特征不同,25 年尺度下城镇附近土地变化幅度较高,5 年尺度下土地利用变化热点区由台塬中部向东西边缘区推移.  相似文献   

9.
基于遥感和GIS的松嫩沙地土地利用/土地覆被时空格局研究   总被引:23,自引:9,他引:14  
利用1986年和2000年2期TM影像资料,建立相应的空间图形库系统,定量分析了松嫩沙地典型区近15a来土地利用数量变化,从土地利用斑块特征、斑块空间邻接关系变化和主导变化类型角度对土地利用/覆被格局进行了清晰的空间描述。结果表明,研究时段内该区土地利用量变和质变活跃。耕地面状成片、条带状延伸和斑块状空间扩展,从整体上呈现集中化特征。较大面积的草地和林地被分割、破碎化,小块盐碱化草地空间聚集与扩张。耕地与草地、草地与盐碱地空间相邻度变大,草地开垦强度增大、土地盐碱化日益严重。空间变化上表现为耕地、林地、草地和未利用地之间相互转化,以草地、林地-旱地,草地-未利用地,未利用地-旱地、水田及旱地-水田最为显著。  相似文献   

10.
珠江三角洲土地利用变化对生态系统服务价值的影响   总被引:4,自引:0,他引:4  
以珠江三角洲1990、2000和2006年的遥感解译数据为基础,参照谢高地等对中国陆地生态系统单位面积生态服务价值表,研究珠三角土地利用变化对生态系统服务价值的影响以及生态服务价值与土地利用结构的关系。结果表明:1990―2006年,珠三角耕地和林地大量减少,建设用地和水域快速增长,其它地类有所增加;研究区发生变化的土地占土地总面积的29.38%,耕地主要流向建设用地、水域和林地,建设用地的扩张主要来自耕地、林地和水域;由于水域生态价值系数相对较高,水域的增加抵消了由耕地、林地减少造成的生态服务总价值的下降,使得区域生态服务总价值略有减少;珠三角生态系统服务价值由1990年874.38亿元减至2006年的846.47亿元,变化率为3.19%;研究区内单位生态服务价值差异明显且逐渐扩大;单位生态服务价值与建设用地、林地、耕地所占比重明显相关,建设用地快速扩张,林地和耕地减少是导致生态服务价值减少的主要原因。  相似文献   

11.
Model simulation and scenario change analysis are the core contents of the future land-use change (LUC) study. In this paper, land use status data of the Three Gorges Reservoir Region (TGRR) in 1990 was used as base data. The relationship between driving factors and land-use change was analyzed by using binary logistic stepwise regression analysis, based on which land use in 2010 was simulated by CLUE-S model. After the inspection and determination of main parameters impacting on driving factors of land use in the TGRR, land use of this region in 2030 was simulated based on four scenarios, including natural growth, food security, migration-related construction and ecological conservation. The results were shown as follows: (1) The areas under ROC curves of land-use types (LUTs) were both greater than 0.8 under the analysis and inspection of binary logistic model. These LUTs include paddy field, dryland, woodland, grassland, construction land and water area. Therefore, it has a strong interpretation ability of driving factors on land use, which can be used in the estimation of land use probability distribution. (2) The Kappa coefficients, verified from the result of land-use simulation in 2010, were shown of paddy field 0.9, dryland 0.95, woodland 0.97, grassland 0.84, construction land 0.85 and water area 0.77. So the results of simulation could meet the needs of future simulation and prediction. (3) The results of multi-scenario simulation showed a spatial competitive relationship between different LUTs, and an influence on food security, migration-related construction and ecological conservation in the TGRR, including some land use actions such as the large-scale conversion from paddy field to dryland, the occupation on cultivated land, woodland and grassland for rapid expansion of construction land, the reclamation of woodland and grassland into cultivated land, returning steep sloping farmland back into woodland and grassland. Therefore, it is necessary to balance the needs of various aspects in land use optimization, to achieve the coordination between socio-economy and ecological environment.  相似文献   

12.
Model simulation and scenario change analysis are the core contents of the future land-use change(LUC) study. In this paper, land use status data of the Three Gorges Reservoir Region(TGRR) in 1990 was used as base data. The relationship between driving factors and land-use change was analyzed by using binary logistic stepwise regression analysis, based on which land use in 2010 was simulated by CLUE-S model. After the inspection and determination of main parameters impacting on driving factors of land use in the TGRR, land use of this region in 2030 was simulated based on four scenarios, including natural growth, food security, migration-related construction and ecological conservation. The results were shown as follows:(1) The areas under ROC curves of land-use types(LUTs) were both greater than 0.8 under the analysis and inspection of binary logistic model. These LUTs include paddy field, dryland, woodland, grassland, construction land and water area. Therefore, it has a strong interpretation ability of driving factors on land use, which can be used in the estimation of land use probability distribution.(2) The Kappa coefficients, verified from the result of land-use simulation in 2010, were shown of paddy field 0.9, dryland 0.95, woodland 0.97, grassland 0.84, construction land 0.85 and water area 0.77. So the results of simulation could meet the needs of future simulation and prediction.(3) The results of multi-scenario simulation showed a spatial competitive relationship between different LUTs, and an influence on food security, migration-related construction and ecological conservation in the TGRR, including some land use actions such as the large-scale conversion from paddy field to dryland, the occupation on cultivated land, woodland and grassland for rapid expansion of construction land, the reclamation of woodland and grassland into cultivated land, returning steep sloping farmland back into woodland and grassland. Therefore, it is necessary to balance the needs of various aspects in land use optimization, to achieve the coordination between socio-economy and ecological environment.  相似文献   

13.
Land use/cover change has been recognized as a key component in global change and has attracted increasing attention in recent decades. Scenario simulation of land use change is an important issue in the study of land use/cover change, and plays a key role in land use prediction and policy decision. Based on the remote sensing data of Landsat TM images in 1989, 2000 and 2010, scenario simulation and landscape pattern analysis of land use change driven by socio-economic development and ecological protection policies were reported in Zhangjiakou city, a representative area of the Poverty Belt around Beijing and Tianjin. Using a CLUE-S model, along with socio-economic and geographic data, the land use simulation of four scenarios–namely, land use planning scenario, natural development scenario, ecological-oriented scenario and farmland protection scenario–were explored according to the actual conditions of Zhangjiakou city, and the landscape pattern characteristics under different land use scenarios were analyzed. The results revealed the following: (1) Farmland, grassland, water body and unused land decreased significantly during 1989–2010, with a decrease of 11.09%, 2.82%, 18.20% and 31.27%, respectively, while garden land, forestland and construction land increased over the same period, with an increase of 5.71%, 20.91% and 38.54%, respectively. The change rate and intensity of land use improved in general from 1989 to 2010. The integrated dynamic degree of land use increased from 2.21% during 1989–2000 to 3.96% during 2000–2010. (2) Land use changed significantly throughout 1989–2010. The total area that underwent land use change was 4759.14 km2, accounting for 12.53% of the study area. Land use transformation was characterized by grassland to forestland, and by farmland to forestland and grassland. (3) Under the land use planning scenario, farmland, grassland, water body and unused land shrank significantly, while garden land, forestland and construction land increased. Under the natural development scenario, construction land and forestland increased in 2020 compared with 2010, while farmland and unused land decreased. Under the ecological-oriented scenario, forestland increased dramatically, which mainly derived from farmland, grassland and unused land. Under the farmland protection scenario, farmland was well protected and stable, while construction land expansion was restricted. (4) The landscape patterns of the four scenarios in 2020, compared with those in 2010, were more reasonable. Under the land use planning scenario, the landscape pattern tended to be more optimized. The landscape became less fragmented and heterogeneous with the natural development scenarios. However, under the ecological- oriented scenario and farmland protection scenario, landscape was characterized by fragmentation, and spatial heterogeneity of landscape was significant. Spatial differences in landscape patterns in Zhangjiakou city also existed. (5) The spatial distribution of land use could be explained, to a large extent, by the driving factors, and the simulation results tallied with the local situations, which provided useful information for decision-makers and planners to take appropriate land management measures in the area. The application of the combined Markov model, CLUE-S model and landscape metrics in Zhangjiakou city suggests that this methodology has the capacity to reflect the complex changes in land use at a scale of 300 m×300 m and can serve as a useful tool for analyzing complex land use driving factors.  相似文献   

14.
洮河流域土地利用/土地覆被变化及其驱动机制研究   总被引:1,自引:1,他引:0  
系统收集和整理1970s后期至2000s洮河流域土地利用/土地覆被、水文气象和经济社会发展数据,采用综合利用指数、转移矩阵、动态度、相关性和主成分分析方法及多元线性回归方法,得到结果表明,过去30 a,洮河流域总体表现为林、草面积减少、耕地面积增加、土地开发利用程度进一步提升。驱动因子相关性及主成分分析表明,洮河流域LULCC受“区域经济+农耕因素+城镇化和气候”3个主成分大类的交互影响和驱动;基于此构建的LULCC多元回归驱动模式,在率定期和验证期精度良好,能够反映洮河流域经济社会发展及区域气候对LULCC的驱动和影响。  相似文献   

15.
利用地理信息系统技术,在空间数据库平台的支持下,对成都市20世纪90年代中期到2000年间的土地利用动态变化进行了研究.分析表明,在1995-2000年间,耕地与建设居民用地、耕地与林地、林地与草地以及水体与耕地等之间的转换强度较高.耕地减少10972hm2,林地减少2220hm2,草地增加8042hm2,建设居民用地增加4830hm2,水体增加323hm2.减少耕地的主要去向是建设居民用地、草地和林地;减少林地的主要去向是草地.人口总数,第三产业从业人口,工业国内生产总值,第二、三产业的国内生产总值与建设居民用地同步增加;第一产业从业人员与耕地同步减少.  相似文献   

16.
20世纪90年代无定河流域土地利用的时空变化   总被引:8,自引:2,他引:8  
本文基于ArcGIS平台,以LandsatTM影像解译得到的三期土地利用数据为基础,结合统计分析工作,对无定河流域20世纪90年代土地利用数量、类型及其变化进行了分析。分析得出,前后2个5年间,无定河流域耕地、林地和未利用土地都是先减少而后稍有增加,草地则是先增加后稍有减少。在10年尺度上土地利用总的动态特征是,耕地与未利用土地面积减少,林地、草地面积增加。前5年无定河流域综合土地利用动态度为0.85%,未利用土地和草地的年变化率较大,耕地与水域年变化率较低。后5年无定河流域综合土地利用动态度为0.3%,林地与未利用土地年变化率较大,耕地与水域变化率较小。最后引入单一土地利用类型相对变化率反映出无定河流域土地利用变化存在明显的区域差异。  相似文献   

17.
遥感和GIS支持下的云南省退耕还林还草决策分析   总被引:52,自引:4,他引:52  
以云南省为例,探讨利用地理信息系统技术来确定需要退耕还林还草的耕地数量及其空间分布,其中包括4个步骤,首行,建立土地利用,土壤侵蚀,坡度,植被指数,水体,降雨和温度等数据库,其次,从土地利用数据库中提取旱地的数据,并与坡度数据,土壤侵蚀数据,植被指数数据进行叠架分析,对水体建立缓冲区,并与耕地数据进行叠加分析,再次,退耕还林还草的原则,并在GIS的支持下,确定需要退耕还林还草的空间分布及其面积,最后,利用降雨和温度数据进一步确定分别退耕还林和还草的空间分布及其面积,研究结果可以为云南省的生态环境建设提供科学的依据。  相似文献   

18.
北方农牧交错带退耕还林还草经济政策优化调控   总被引:4,自引:0,他引:4  
退耕还林还草作为北方农牧交错带生态重建的切入点,在实际操作中也不可避免地存在一定的问题。文章对当前退耕还林还草的社会经济特征、政策安排、协调机制及制约因素进行了分析。提出:区域粮食适度自给定位、部门协调机制创新、产权制度改革、区域产业专业化分工、适度生态移民及建立生态补偿机制为进行政策优化调控的主要途径。  相似文献   

19.
Altay region is located in the northern part of Xinjiang, and has complex and diverse internal geomorphic types, undulating terrain and a fragile ecosystem. Studying the impact of land use changes on habitat quality is of great significance to regional ecological protection and development, rational planning and utilization, and ensuring the sustainable development of the ecological environment. Based on the InVEST model, combined with land use panel data and topographic relief data of the Altay region, this paper studied the habitat quality from 1995 to 2018. The results show that cultivated land, water area and construction land increased gradually from 1995 to 2018, while grassland and unused land decreased. Forestland remained stable in the first five periods, but increased significantly in 2018. During 1995-2018, all land use types were transferred, mainly between cultivated land, forestland, grassland and unused land in the flat and slightly undulating areas. Poor habitat quality was dominant during 1995-2018. Habitat quality decreased significantly in 2015, which was related to the rapid expansion of cultivated and construction land as threat sources, as well as the decrease of forest and grassland as sensitive factors. However, habitat quality improved significantly in 2018, because a large amount of cultivated land and unused land were converted into forest land and grassland with high habitat suitability. Land use type has an important influence on habitat quality. The distribution characteristics of habitat quality for topographic relief types from good to bad were: large undulating area>medium undulating area>small undulating area>flat area>slightly undulating area. The findings of this study are of great significance for coordinating social, economic, and ecological development in this region and in similar areas.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司    京ICP备09084417号-23

京公网安备 11010802026262号