人类活动干扰下土地利用异质性特征分析—以中山市为例

以中山市为例,在土地利用类型遥感解译数据的基础上,以系统网格采样法计算研究区内土地利用强度,并探索了土地利用强度的空间分布特征,以及受人类活动的驱动作用。研究结果表明：1 200 m能够很好地反映土地利用强度异质性在空间上的特征。研究区内的土地利用强度空间分布表现出较强的正相关性,2000—2010年,中山市土地利用强度分布模式由多点式向极化转变,而且还表现出核心区域的扩散效应。在整体的范围上看,土地利用强度的空间变异受尺度影响,随着尺度的增加各向同性的减弱,转变成明显的各向异性。研究区内自然条件以及区域发展政策的差异,导致研究区内行政单元间的土地利用强度空间分异明显。在人类活动影响的驱动下,研究区内土地利用强度异质性呈现增强的趋势。     

Decline of traditional rice farming constrains the recovery of the endangered Asian crested ibis (Nipponia nippon)

Traditional agriculture benefits a rich diversity of plants and animals. The winter-flooded rice fields in the Qinling Mountains, China, are the last refuge for the endangered Asian crested ibis (Nipponia nippon), and intensive efforts have been made to protect this anthropogenic habitat. Analyses of multi-temporal satellite data indicate that winter-flooded rice fields have been continuously reduced across the current range of crested ibis during the past two decades. The rate of loss of these fields in the core-protected areas has unexpectedly increased to a higher level than that in non-protected areas in the past decade. The best fit (R² = 0.87) numerical response model of the crested ibis population shows that a reduction of winter-flooded rice fields decreases population growth and predicts that the population growth will be constrained by the decline of traditional winter-flooded rice fields in the coming decades. Our findings suggest that the decline of traditional rice farming is likely to continue to pose a threat to the long-term survival and recovery of the crested ibis population in China.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0649-5) contains supplementary material, which is available to authorized users.     

土地资源的多级网格数据结构建立与应用研究

传统的基于行政区的土地统计数据不能完全表现区域内部土地利用的空间分异特征,以武汉市为实验区,对基于网格的统计信息算法STING(Statistical Information Grid-based method)进行扩展,以景观多样性指数为定量化指标对实验区进行四叉树划分生成不均匀多级网格,建立一种拟合了行政区划界线的不均匀的多级网格结构来存储、管理和分析土地数据。并以此多级网格数据结构为平台计算和生成实验区人口密度空间分异渲染图,初步抽取了人口分布与土地利用之间的关系。实验表明,基于多级网格的统计方法能更好地表达土地利用及其相关数据的空间分异性,利于对土地资源数据的进一步挖掘以抽取所需知识。     

产业园区外存量工业用地环境准入管控研究—以上海市为例

为探索在新产业布局及发展形势下的产业园区外存量工业用地环境准入分类管控模式,采用空间叠图分析和承载力评估方法,基于“三线一单”分区管控要求对上海市产业园区外存量工业用地的空间布局约束、资源环境承载和环境风险防控进行评估。综合评估结果、新法规要求和规划方向的指引,梳理典型区环境准入管理的试点经验,提出以下建议：生态环境及产业、规划相关部门对产业园区外存量工业用地的现状及规划实施动态排摸;结合各地块资源环境特征、规划发展意向等因素,对不同规划导向的地块实施差异化分类管控;针对近中期保留的产业园区外存量工业用地,通过开展区域环评强化环境准入。

     

华北油田二连分公司蒙古林作业区生态环境质量状况研究

本文选取二连油田蒙古林作业区生态环境质量为研究对象,对该区域内的土地利用／覆盖状况、植被状况、景观类型及其破碎度进行定性、定量研究。结果表明：（1）2008年,该区域土地利用类型主要为有林地、中覆盖度草地、低覆盖度草地、工矿交通建设用地和盐碱地等;工交建设占地明显。（2）该区2008年主要植物群落类型有：克氏针茅＋羊草＋杂类草、克氏针茅＋锦鸡儿＋杂类草、羊草＋针茅＋杂类草等;受到气候变暖等原因影响,小针茅已经在本区广泛分布。（3）该区2008年主要景观类型为针茅＋锦鸡儿草原景观、针茅草原景观、羊草草原景观、林地景观、人工建设区景观和道路景观;景观破碎度较高,人为干扰较为严重。建议相关单位足够重视并采取切实可行的措施,防止本区生态环境恶化。     

Temporal and Spatial Relationships Between Watershed Land Use and Salt Marsh Disturbance in a Pacific Estuary

Historical and recent remote sensing data can be used to address temporal and spatial relationships between upland land cover and downstream vegetation response at the watershed scale. This is demonstrated for sub-watersheds draining into Elkhorn Slough, California, where salt marsh habitat has diminished because of the formation of sediment fans that support woody riparian vegetation. Multiple regression models were used to examine which land cover variables and physical properties of the watershed most influenced sediment fan size within 23 sub-watersheds (1.4 ha to 200 ha). Model explanatory power increased (adjusted R(2) = 0.94 vs. 0.75) among large sub-watersheds (>10 ha) and historical watershed variables, such as average farmland slope, flowpath slope, and flowpath distance between farmland and marsh, were significant. It was also possible to explain the increase in riparian vegetation by historical watershed variables for the larger sub-watersheds. Sub-watershed area is the overriding physical characteristic influencing the extent of sedimentation in a salt marsh, while percent cover of agricultural land use is the most influential land cover variable. The results also reveal that salt marsh recovery depends on relative cover of different land use classes in the watershed, with greater chances of recovery associated with less intensive agriculture. This research reveals a potential delay between watershed impacts and wetland response that can be best revealed when conducting multi-temporal analyses on larger watersheds.     

MINIMIZING THE IMPACT OF URBANIZATION ON LONG TERM RUNOFF1

Increasing concern about the problems caused by urban sprawl has encouraged development and implementation of smart growth approaches to land use management. One of the goals of smart growth is water resources protection, in particular minimizing the runoff impact of urbanization. To investigate the magnitude of the potential benefits of land use planning for water resources protection, possible runoff impacts of historical and projected urbanization were estimated for two watersheds in Indiana and Michigan using a long term hydrological impact analysis model. An optimization component allowed selection of land use change placements that minimize runoff increase. Optimizing land use change placement would have reduced runoff increase by as much as 4.9 percent from 1973 to 1997 in the Indiana study watershed. For nonsprawl and sprawl scenarios in the Michigan watershed for 1978 to 2040, optimizing land use change placement would have reduced runoff increase by 12.3 percent and 20.5 percent, respectively. The work presented here illustrates both an approach to assessing the magnitude of the impact of smart growth and the significant potential scale of smart growth in moderating runoff changes that result from urbanization. The results of this study have significant implications for urban planning.     

我国耕地保护前景分析

耕地作为最重要的生产资料在国民经济建设中具有非常重要的地位，是社会稳定的重要物质基础。在分析我国人多地少、人增地减、人地矛盾日益突出的国情和今后一段时期国家对耕地大量需求的基础上，认为我国必须加强耕地保护，确保社会经济的可持续发展。     

A factor analytic study of attitudinal structure and its impact on rural landowners' access policies

Previous research has shown that rural landowners' hunter access policies are determined in large part by their attitudes towards hunters, legal liability, conservation, and economic incentives. The results of this study support this research and indicate that East Texas, USA, landowners' decisions to allow or restrict access are based, in part, on attitudes toward hunter behavior, hunting as a social activity, leasing as a management practice, and a perceived obligation toward wildlife stewardship. Attitude-based profiles of landowners who adopted one of four access policies are compared.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.