美国土地利用/土地覆盖变化的空间特征

1IntroductionInrecentyears,studyonglobalchangehasbecomethefocus,onwhichstresshasbeenlaidbytodayhumansociety.Inordertodealwithseriesofenvironmentalproblemssuchasdegradationoflandresources,globalwarming,destructionofozonosphereandsoon,andassurethestabilizationandsustainabledevelopmentofworldeconomy,IGBPhasestablishedthestudyframeforglobalchange.Withavastrangeofstudy,researchonglobalchangehasbroughtforwardagreatdealofimportantscientificquestionsrelatedtofeasibilityforhumanelivingoftheEarth.Inth…     

Exploring the impacts of future tourism development on land use/cover changes

Land use/cover changes (LUCC) are central to tourism because land is used in multiple ways as a resource for tourism-focused activities. Tourism is essentially a geographical phenomenon, encompassing the movement and flow of people (seen as the demand side) and spatial distribution patterns relating to land use consumption (seen as the supply side). However, the impacts of tourism on LUCC are difficult to track and monitor. Contributing factors of this problem include a lack of empirical studies, shortage of micro-level LUCC datasets, and scarce methodological frameworks which can be used for assessments. This paper aims to provide a LUCC modelling approach in order to explore the impacts of tourism development on built-up areas. We developed a Cellular automata model (CA) which integrates Markovian transition probabilities and logistic regression transition suitability maps. LUCC rules for tourism development are framed within the national land use policy guidelines for the development of new tourism accommodation establishments (TAE). This primarily takes into consideration land cover compatibility and the proposed development's proximity to the coastline.Three scenarios were established to explore the impacts of tourism development in LUCC for the year 2020 in a Portuguese coastal region: business as usual (BAU); tourism trends (TOUR); and natural restrictions (NATR). TOUR results indicate that the tourism and urban land use/cover growth is higher and focuses heavily on the coastal region (within 5,000 m) when compared to the other scenarios. The overall results for BAU and NATR show a general convergence with the land use policy guidelines in terms of tourism nucleation and new TAE distance to the coastline.     

地理学视角下土地利用/覆被分类发展探讨

随着对地观测和互联网技术的发展,地理大数据时代正在到来,其多尺度、长时序、多模态等海量“超”覆盖数据为土地利用/覆被（Land Use/Land Cover, 简称LULC）分类及变化检测带来巨大的机遇,支撑着新时代人、地两大系统相互作用关系的认知和实践。然而,多数地理学者认为地理学基本原理与核心思想并未因为大数据的到来而发生本质性变化。所以,从地理学基本原理角度理解LULC分类的发展,尤其在地理大数据时代的发展方向,不失为一条可行的途径。为此,本文从区域、尺度、综合三方面的地理学基本原理视角将LULC分类技术的发展划分为地球观测数据匮乏阶段、人类行为数据融合阶段以及地理大数据“超”覆盖阶段分别探讨分析,以期主动把握LULC分类技术及应用的未来发展趋势。研究结果显示：在地球观测数据匮乏阶段,LULC分类多以类型还不丰富的遥感数据源,在空间分辨率较低的像元尺度上,进行以地表覆被状态为主的分类;发展到人类行为数据融合阶段,LULC分类在城市区域率先出现了对地观测数据和人类行为数据相融合,在街区尺度上进行以空间功能异质性划分、识别为主导的城市功能区分类;在地理大数据“超”覆盖阶段,LULC分类将实现多尺度协同、面向全空间的功能异质性划分,并在主体功能的基础上融合“社会-经济-自然”多维定量属性,本文称之为“空间场景”。希望本文的探讨能够为地理大数据时代LULC分类的新技术发展和新产品应用提供有益启示。     

Spatial features of land use/land cover change in the United States

With the classification data covering American land-use/land-cover (LUCC) with 30 m resolution from the project of National Land Cover Data (NLCD), we normalized them and made their resolution changed into 1 km ×1 km, created the data of American land-use grade and analyzed the spatial distribution and features of American LUCC as well as the influence of population and altitude on the land-use grade in light of methods of sampling analysis and correlation study. Based on the analysis, we concluded that forestry and grassland, accounting for 71.24% of the whole country, has taken the main part of American land cover, and besides, construction and arable land has occupied 19.22% of the total land, the rest of land cover types, including water area, wetland and underdeveloped land, is 9.54% of the country's total. The developing potential of American land resources is enormous with less destroyed and disturbed ecological environment. Although, in some sense, the population and altitude influence the spatial variation of American land-use grade respectively, the influence of spatial variation of altitude and population density on that of land-use grade is not significanct.     

清代中期江苏省土地利用格局网格化重建

针对当前历史土地利用空间重建研究多基于单一地类且空间分辨率较低的特征,提出较高分辨率全地类土地利用空间重建方法。以1820年为时间断面,以现代江苏省域为研究区,以历史文献记载、历史地理学研究成果、现代统计数据、自然环境数据等为支撑,将土地利用类型划分为耕地、聚落用地（含城镇用地、农村居民点用地）、水域和其他用地（含林草地及未利用地）,考虑区域自然资源和社会经济特征,提出理论假设,对府级耕地、城镇用地、农村居民点用地数量进行修正;沿用以现代土地利用格局为基础反演历史土地利用格局的基本思路,从人地关系角度出发,采用治所邻近度分析、综合评价等方法重建了1820年100 m×100 m空间格网下的江苏省土地利用格局,同时,通过不同地理分区统计及降尺度对比间接验证等分析了重建结果。结果表明：① 1820年江苏省耕地、城镇用地、农村居民点用地、水域用地及其他用地面积分别占区域总面积的48.49%、4.46%、0.16%、15.03%和31.86%;② 1820年研究区内土地垦殖率较高,但建设用地比率较低,受人口分布、地形及河网密度等影响,不同地理分区土地利用差异较为显著;③ 农村居民点用地及耕地的降尺度分析结果均呈显著线性正相关,在一定程度上表明研究结果具有合理性。     

额尔齐斯河-斋桑湖流域近20年来土地利用/土地覆被时空演变

土地利用/土地覆被变化(LUCC)是影响生态环境和气候变化的主要驱动力之一,同时又是受其影响的结果。LUCC研究对于开展生态环境变化及气候变化的研究均具有重要的意义。针对目前境外LUCC研究中土地利用/覆被分类效率低的问题,探索一种适用于大数据量而又精度较高的分类方法。以额尔齐斯河国外部分-斋桑湖流域为研究区域,以1990年及2007年的Landsat TM/ETM+夏秋季影像以及DEM作为数据源,综合利用影像光谱、纹理信息参与到决策树构造中,进而利用决策树分类方法分别提取这两个时期的土地利用/覆被空间分布信息,最后分析两个时期的土地利用时空变化状况。实验结果表明:(1)光谱与空间纹理信息参与的决策树分类方法具有较高的分类精度;(2)两个时期的土地利用变化分析发现,近20年来该区域土地利用发生了较大的变化,耕地和灌木林地大面积减少,而低覆盖度草地和未利用地却显著增加。     

陕西大理河流域土地利用/覆被变化的水文效应

近年来,土地利用/覆被变化的水文效应研究已成为国际的前沿和重点。在大理河流域,LUCC(包括水土保持措施)对水循环和水量平衡产生了深远影响,该流域LUCC水文效应的研究势在必行。根据研究区1990年代三期土地利用数据分析了LUCC的时空变化特征,采用特征变量时间序列法及降水-径流模型对LUCC水文效应进行了研究。结果表明:流域土地利用类型以耕地和草地为主,近10年来,耕地和草地面积有所减少,而林地和建设用地面积持续增加;流域年径流和月径流演化过程均表现出明显的下降趋势;LUCC及水土保持具有减少流域年径流、汛期流量以及增加枯季流量的作用,相对于降水因素,人类活动对流域水文的作用占主导地位;在1990~2000年期间,主要由LUCC引起的年均径流减少量达2616.6×10⁴ m³,占该期间实测减水总量的62.19%。     

滇西北山区土地持续利用动态评价与分析--以云南省永胜县为例

以云南省永胜县为例,应用景观生态学原理,构建土地持续利用的时空耦合的综合评价指标体系,定量评价全县1996年、1999年和2001年间的土地利用可持续性动态,并构建指标贡献度与指标障碍度,定量表征各指标的相对作用强度。研究结果表明,研究时段内全县各乡镇土地利用可持续性整体均较低,相对差异大而稳定;区域土地利用系统在1999年前后发生了较大变化,偏离了土地持续利用目标;对全县各乡镇土地利用可持续性起重要贡献作用的因素主要是人口密度与土地利用程度指数,景观多样性与复种指数次之;主要障碍因素则是地均工农业总产值、粮食作物单产、景观破碎度,油料作物单产、单位面积耕地化肥使用量次之。     

Structural patterns of land types and optimal allocation of land use in Qinling Mountains

The case study based on Qinling Mountains in Shaanxi Province of China, in virtue of the information from TM image, classifies the land types and analyzes their spatial and temporal differential law, and puts forward three structural patterns of land types in mountainous areas, namely, spatial, quantitative and qualitative structures of mountainous land types. Furthermore, it has been noticed that the analysis of structural patterns can disclose the heterogeneity and orderliness of combination of land types, which can lay the theoretic foundation for comprehensively recognizing ecological characteristics and succession law of structure and function of land types. After the all-around comparative analysis, an optimal allocation of land use in Qinling Mountains has been put forward according to the principle of sustainable development and landscape ecology, which can lay the scientific foundation in practice for the structural adjustment and distribution optimization from the macro level to micro level.     

Structural patterns of land types and optimal allocation of land use in Qinling Mountains

1 IntroductionMountains，as one of the huge ecosystems in the world, play a significant role during human evolution and development[1]. As the treasury of ecological resources[2], mountains have faced the challenge of the degradation of their eco-environment and the difficulty in their regional poverty relief because of human unsuitable exploitation. The 53rd Conference of United Nations has claimed the year 2002 as the International Mountains Year and called on each country to pay attention…     

Incorporating spatial interaction patterns in classifying and understanding urban land use

Land use classification has benefited from the emerging big data, such as mobile phone records and taxi trajectories. Temporal activity variations derived from these data have been used to interpret and understand the land use of parcels from the perspective of social functions, complementing the outcome of traditional remote sensing methods. However, spatial interaction patterns between parcels, which could depict land uses from a perspective of connections, have rarely been examined and analysed. To leverage spatial interaction information contained in the above-mentioned massive data sets, we propose a novel unsupervised land use classification method with a new type of place signature. Based on the observation that spatial interaction patterns between places of two specific land uses are similar, the new place signature improves land use classification by trading off between aggregated temporal activity variations and detailed spatial interactions among places. The method is validated with a case study using taxi trip data from Shanghai.     

Land tenure and deforestation patterns in the Ecuadorian Amazon: Conflicts in land conservation in frontier settings

The Cuyabeno Wildlife Production Reserve (Cuyabeno Reserve), located in the northeastern Ecuadorian Amazon, is a special protected area. Using a satellite image time-series, landscape ecology and evolving boundary definitions, shifts in landscape composition are described that focus on the spatial and temporal dynamics of land use and cover change (LUCC) within the vicinity of the Cuyabeno Reserve. Changes in local land tenancy and the implementation of protection buffers have accelerated the process of fragmentation and exacerbated the conflict between development and protection. Further, variations in management strategies and ownership histories confound LUCC patterns, rates, and trajectories.     

基于Multi-Agent System的多尺度土地利用变化模型的构建与模拟

通过土地利用情景变化模型反映多尺度的土地利用现象,是学者们研究的焦点问题。本文基于MAS理论,构建从地块到村庄的多尺度土地利用变化模型,揭示微观层面不同尺度上土地利用变化的机制。应用该模型,以陕西省米脂县孟岔村为例进行研究,定量分析该村农户个体、农户群体和农户整体等不同尺度上的土地利用决策,并通过与2008年实际土地利用变化数据对比和分析,对构建的多尺度土地利用变化模型进行检验。通过分析,认为:(1)基于MAS的多尺度农户土地利用变化模型可较好地反映微观土地利用决策和空间的多尺度变化;(2)构建用 连续数值表示的农户土地利用决策与实际状况比较符合;(3) 本文为不同农户群体间的转化方法、农户间相互作用,以及市场与政策因素的作用等方面的研究打下坚实的基础。     

CLUE-S模型的改进与土地利用变化动态模拟——以张家界市永定区为例

区域土地利用变化模拟是LUCC研究的核心内容之一。以地处湘西北岩溶山区的张家界市永定区为研究对象,针对目前国际上广泛使用的CLUE-S土地利用变化模型,通过在传统Logistic回归模型中引入空间自相关变量,对CLUE-S模型的空间分析模块进行了改进。实验与分析结果表明,改进的空间分析模块拟合优度、拟合精度都有较大的提高。耕地、林地及居民点工矿用地的拟合优度(ROC值)分别从0.784、0.821和0.741提高到0.827、0.875和0.838。在此基础之上,采用改进的CLUE-S模型,模拟和预测了研究地区2005~2020年的土地利用时空变化。研究结果说明对CLUE-S模型空间分析模块的改进在一定意义上是合理的,同时也可以为永定区及其相似地区的土地利用规划决策提供更为科学的依据。     

土地利用变化时空模型的图谱方法--以黄河三角洲为例

Changesinlandcoverandland-usehaveimpactsandimplicationsatlocal,regionalandglobalscalesbecauseofthewaytheyalterbiophysical,biogeochemicalandhydrologicalstatesandprocesses(Alcamoetal.,1996;Li,1996).Since1990,scientistsathomeandabroadhavebeenpayingattentiontoresearchesonland-useandland-coverchange(LUCC)(Turneretal.,1990;MeyerandTurner,1994),butresearchisnotenoughon"spaceandprocess"ofLUCC(Turneretal.,1995).Spatialrelationshipbetweenvariablesyethasnotbeenestablished(Bockstael,1996).Soitispara…     

土地利用/土地覆被时空分布100年数字重建——以大庆市杜尔伯特蒙古族自治县为例

长时间序列的土地利用/ 土地覆被数据是开展全球变化、可持续发展及生态安全等各项研究的重要基础。然而,早期的土地利用/ 土地覆被数据,特别是卫星遥感数据出现之前 的土地利用/ 土地覆被信息通常很难获取。利用TM、MSS 遥感影像数据和地形图、气候、地质、地貌、土壤、植被、水文等自然环境背景图件以及数据,社会经济统计数据等多源数 据,选择大庆市杜尔伯特蒙古族自治县作为典型案例区,在GIS 技术支持下建立了土地利用/ 土地覆被数字重建模型,再现了典型研究区20 世纪30 年代和50 年代土地利用/ 土地覆被空间分布状况。通过野外调查和历史文献资料对土地利用数字重建结果进行精度评价并初步得到以下结论：① 采用逐个图斑跟踪记录的方法对研究区各个时期土地利用/ 覆被变化的敏感 性进行分析,有利于揭示区域土地利用/ 土地覆被变化的规律;② 在定量、定位分析环境背景对土地利用/ 土地覆被分布及其变化的影响基础上,综合判断各种土地利用/ 土地覆被分布概率,其结果可为土地利用数字重建提供依据;③ 对1:10 万地形图提取土地利用信息的可行性与可信度分析表明,地形图中土地利用信息完全能够达到一级土地利用分类精度,同时疏林地、灌木林、沼泽地、盐碱地、沙地等二级分类信息也能获取。     

Modeling spatially non-stationary land use/cover change in the lower Connecticut River Basin by combining geographically weighted logistic regression and the CA-Markov model

Simulating land use/cover change (LUCC) and determining its transition rules have been a focus of research for several decades. Previous studies used ordinary logistic regression (OLR) to determine transition rules in cellular automata (CA) modeling of LUCC, which often neglected the spatially non-stationary relationships between driving factors and land use/cover categories. We use an integrated geographically weighted logistic regression (GWLR) CA-Markov method to simulate LUCC from 2001–2011 over 29 towns in the Connecticut River Basin. Results are compared with those obtained from the OLR-CA-Markov method, and the sensitivity of LUCC simulated by the GWLR-CA-Markov method to the spatial non-stationarity-based suitability map is investigated. Analysis of residuals indicates better goodness of fit in model calibration for geographically weighted regression (GWR) than OLR. Coefficients of driving factors indicate that GWLR outperforms OLR in depicting the local suitability of land use/cover categories. Kappa statistics of the simulated maps indicate high agreement with observed land use/cover for both OLR-CA-Markov and GWLR-CA-Markov methods. Similarity in simulation accuracy between the methods suggests that the sensitivity of simulated LUCC to suitability inputs is low with respect to spatial non-stationarity. Therefore, this study provides critical insight on the role of spatial non-stationarity throughout the process of LUCC simulation.     

近两百年江苏省城乡建设用地数量估算与空间重建

以典型历史断面下的建设用地为研究对象,以数量估算控制下的空间格局重建为基本思路,在200 m×200 m网格下,估算并重建了近200年5个时间断面下的江苏省建设用地（城镇用地和农村聚落用地）的空间格局。在数量估算方面,历史时期（1820年）的城镇用地主要采用城垣、市镇四栅等作为代用指标;近现代时期（1911年、1936年、1952年）,主要通过人口、社会经济等数据,结合一定假设确定人均用地数量进行推导;各时期的农村聚落用地均以人口数量为基础,根据人均住房面积和社会经济数据修正确定。在空间重建方面,结合遥感数据解译获得的现代（1985年）土地利用数据,借助基础地理数据,在一定假设条件下,通过数量控制、边界控制、适宜性控制,兼顾用地连片性等予以确定。结果表明：① 各时间断面下的江苏省建设用地数量分别为963.46 km²（1820年）、1041.94 km²（1911年）、1672.40 km²（1936年）、1980.34 km²（1952年）和10687.18 km²（1985年）;② 建设用地在空间分布上具有亲水网、路网等特征,并随居民点极化与扩散效应而不断扩张;③ 通过变化过程与演化趋势检验、建设用地与生产协调性分析、居民点空间数量与格局分析等方法,间接证明了重建结果的合理性。     

Tupu methods of spatial-temporal pattern on land use change: a case study in the Yellow River Delta

Comprehensive study on land-use change of spatial pattern and temporal process is the key component in LUCC study nowadays. Based on the theories and methods of Geo-information Tupu (Carto-methodology in Geo-information, CMGI), integration of spatial pattern and temporal processes of land-use change in the Yellow River Delta (YRD) are studied in the paper, which is supported by ERDAS and ARC/INFO software. The main contents include: (1) concept models of Tupu by spatial-temporal integration on land-use change, whose Tupu unit is synthesized by "Spatial·Attribute·Process" features and composed of relatively homogeneous geographical unit and temporal unit; (2) data sources and handling process, where four stages of spatial features in 1956, 1984, 1991, and 1996 are acquired; (3) integration of series of temporal-spatial Tupu, reconstruction series of "Arising" Tupu, spatial-temporal Process Tupu and the spatial temporal Pattern Tupu on land-use change by remap tables; (4) Pattern Tupu analysis on land-use change in YRD during 1956-1996; and (5) spatial difference of the Pattern Tupu analysis by dynamic Tupu units. The various landform units and seven sub-deltas generated by the Yellow River since 1855 are different. The Tupu analysis on land-use in the paper is a promising try on the comprehensive research of "spatial pattern of dynamic process" and "temporal process of spatial pattern" in LUCC research. The Tupu methodology would be a powerful and efficient tool on integrated studies of spatial pattern and temporal process in Geo-science.     

Improving the simulation of fine-resolution landscape changes by coupling top-down and bottom-up land use and cover changes rules

Modelling land use and cover changes (LUCC) at local and landscape scales simultaneously, in terms of composition and configuration, remains today highly challenging. Agricultural landscapes offer an illustrative context for this purpose. This article presents a modelling platform (DYPAL) able to simulate LUCC at both local (agricultural parcel, farm) and landscape levels by combining LUCC processes with an optimization algorithm. The efficiency of this approach is assessed by comparing it with an approach applying the same LUCC processes without optimization. Simulations have been developed for two representative case studies of temperate intensive agricultural mosaics: (1) neutral landscapes with simple and theoretical rules and (2) observed landscapes with realistic crop successions rules. Results show that this modelling platform improves the simulation of LUCC achieved at fine resolution, although not systematically. Improvements are observed when compared to theoretical farming practices. But, when compared with an observed landscape, it is true for one type of (arable) farms only. Several hypotheses are discussed, such as the fact that farmers possibly do not follow optimized rules. Finally, this study illustrates that the use of several indices is crucial to assess whether a simulated landscape is realistic or not, because it does not rely to the assessment of the predictive power of the model.