珠江三角洲地区登革热流行风险空间模拟与预测

近年来日益严重的登革热疫情已在中国南部地区形成疫情高发区,并对中国的公共卫生安全形成了一定的威胁。登革热主要受到区域内复杂的自然环境条件以及社会经济因素的影响,而利用地理空间分析方法和模型探究登革热疫情的影响因素,并对其未来流行风险的空间分布进行模拟,是有效开展登革热预防控制工作的重要基础。本文收集了珠江三角洲地区2010-2014年的登革热病例资料和土地利用、人口密度两种社会经济要素数据,构建土地利用回归（LUR）模型以分析登革热疫情与不同空间范围内的土地利用和人口密度之间的关系,并结合SLEUTH模型获取的2030年土地利用数据以及基于人口密度预测模型获取的2030年人口密度数据,预测珠江三角洲地区2030年登革热疫情风险的空间分布。结果表明,社会经济要素对登革热疫情空间分布的影响在不同范围内存在差异,半径分别为10、7、10、2和1 km的缓冲区内的人口密度、草地、城镇用地、林地和耕地进入LUR模型并对疫情有显著的影响（相关系数分别为0.779、-0.473、0.818、-0.642和-0.403）,所构建的LUR模型效果较好（调整R²为0.796,F=390.409,P<0.01）,留一交叉检验结果显示模型的相对均方根误差为0.7046,预测值与实测值的拟合精度达到0.7101。2030年城市空间扩展的区域主要分布在深圳、东莞以及广佛的交界地区,而登革热风险预测模型表明2030年登革热疫情风险较大的区域与珠江三角洲城镇用地占比、人口分布较高的地区有高度的一致性,尤其是广佛地区。因此,LUR模型可以较好地预测登革热疫情的空间分布,从而为当地卫生部门防控登革热提供方法支持。     

Measuring the effect of an ongoing urbanization process on biodiversity conservation suitability index: integrating scenario-based urban growth modelling with Conservation Assessment and Prioritization System (CAPS)

The present study adopts an integrative modelling methodology, which combines the strengths of the SLEUTH model and the Conservation Assessment and Prioritization System (CAPS) method. By developing a scenario-based geographic information system simulation environment for Hashtpar City, Iran, the manageability of the landscape under each urban growth scenario is analysed. In addition, the CAPS approach was used for biodiversity conservation suitability mapping. The SLEUTH model was implemented to generate predictive urban layers of the years 2020, 2030, 2040 and 2050 for each scenario (dynamic factors for conservation suitability mapping). Accordingly, conservation suitability surface of the area is updated for each time point and under each urban development storyline. Two-way analysis of variance and Duncan’s new multiple range tests were employed to compare the functionality of the three scenarios. Based on results, the managed urban growth scenario depicted better results for manageability of the landscape and less negative impact on conservation suitability values.     

基于SLEUTH模型的城市空间增长模拟研究--以焦作市为例

利用1988,1992,2001,2008年4个时相的遥感影像和GIS技术获取历史数据,采用SLEUTH模型,对焦作市未来城市空间演变进行研究。结果显示：SLEUTH模型重现了焦作市1988~2008年城市空间演变形态,模拟结果与实际情况比较吻合,充分证明SLEUTH模型具有普适性,通过校正能较好地描述城市增长的自然规律;预测模拟了2009~2020年城市空间增长,城市扩展趋势是新扩展中心出现边缘式扩展,向周围地区蔓延,在交通轴线连接下,形成组团式布局。研究结果为研究区城市发展及政府制定规划提供了科学决策依据。     

A general-purpose parallel raster processing programming library test application using a geographic cellular automata model

A general-purpose parallel raster processing programming library (pRPL) was developed and applied to speed up a commonly used cellular automaton model with known tractability limitations. The library is suitable for use by geographic information scientists with basic programming skills, but who lack knowledge and experience of parallel computing and programming. pRPL is a general-purpose programming library that provides generic support for raster processing, including local-scope, neighborhood-scope, regional-scope, and global-scope algorithms as long as they are parallelizable. The library also supports multilayer algorithms. Besides the standard data domain decomposition methods, pRPL provides a spatially adaptive quad-tree-based decomposition to produce more evenly distributed workloads among processors. Data parallelism and task parallelism are supported, with both static and dynamic load-balancing. By grouping processors, pRPL also supports data–task hybrid parallelism, i.e., data parallelism within a processor group and task parallelism among processor groups. pSLEUTH, a parallel version of a well-known cellular automata model for simulating urban land-use change (SLEUTH), was developed to demonstrate full utilization of the advanced features of pRPL. Experiments with real-world data sets were conducted and the performance of pSLEUTH measured. We conclude not only that pRPL greatly reduces the development complexity of implementing a parallel raster-processing algorithm, it also greatly reduces the computing time of computationally intensive raster-processing algorithms, as demonstrated with pSLEUTH.     

The inclusion of differentially assessed lands in urban growth model calibration: a comparison of two approaches using SLEUTH

This research sought to understand the role that differentially assessed lands (lands in the United States given tax breaks in return for their guarantee to remain in agriculture) play in influencing urban growth. Our method was to calibrate the SLEUTH urban growth model under two different conditions. The first used an excluded layer that ignored such lands, effectively rendering them available for development. The second treated those lands as totally excluded from development. Our hypothesis was that excluding those lands would yield better metrics of fit with past data. Our results validate our hypothesis since two different metrics that evaluate goodness of fit both yielded higher values when differentially assessed lands are treated as excluded. This suggests that, at least in our study area, differential assessment, which protects farm and ranch lands for tenuous periods of time, has indeed allowed farmland to resist urban development. Including differentially assessed lands also yielded very different calibrated coefficients of growth as the model tried to account for the same growth patterns over two very different excluded areas. Excluded layer design can greatly affect model behavior. Since differentially assessed lands are quite common through the United States and are often ignored in urban growth modeling, the findings of this research can assist other urban growth modelers in designing excluded layers that result in more accurate model calibration and thus forecasting.     

基于空间句法耦合SLEUTH模型的新老城区扩展模拟研究——以开封市为例

在快速城镇化背景下,历史文化名城常扩建新区并形成新老城区联动发展格局,新建城区以“飞地”形式扩张,不易被传统的元胞自动机方法准确模拟。空间句法是基于空间拓扑的整体性交通网络研究方法,其自上而下的建模策略与元胞自动机自下而上的邻域转换规则起到了互补,两种模型相结合提供了解决上述问题的途径。本文在验证交通土地空间关联的基础上,将句法变量融入SLEUTH模型的排除图层,对开封城市扩张进行了综合模拟。研究结果表明：① 交通增量与用地扩张具有显著的正相关,其关联度随研究单元粒度的扩大而提升。② 在城市从飞地新区扩建到后续填补开发的过程中,与用地扩张关联最高的交通类型由穿行性交通转向到达性交通,且遍历全局的计算结果方位指向性特征更加明显,遍历局部的计算结果片区集聚性特征更加明显。③ 将空间句法与SLEUTH模型松散耦合,可以有效捕捉飞地型城市新增团块,开封市中心城区空间扩张类型可被解读为老城区边缘型增长和新城区飞地型增长并存的模式。④ 空间句法模型不仅能够反演城市交通流,而且对城市产业布局、规划现状与演化轨迹具有间接指向性,这对城市增长模拟十分重要。     

SLEUTH城市扩展模型的应用与准确性评估

基于多时相TM遥感影像, 利用SLEUTH模型对沈阳市1988～2004年间的城市扩展过程进行了模拟.采用ROC曲线、多分辨率误差估算和景观指数3种方法对SLEUTH模型在总体预测能力、城市扩展数量、空间位置和空间格局上的模拟准确性给予全面定量评估.结果表明,SLEUTH模型具有可信精度, 对城市扩展总体趋势拟合较好, 但是对城市扩展空间位置的预测和城市空间格局的表达还有待于提高.     

基本农田信息对SLEUTH模型模拟准确性的影响——以常州市中心城区为例

以常州市中心城区为研究区,探索规划基本农田信息对SLEUTH模型校准过程产生的作用,在此基础上对常州市中心城区的城市扩张进行预测。采用一组对比试验:排除层E1不包含规划基本农田信息,排除层E2包含规划基本农田信息,限制城市发展。试验结果表明,排除层的设计影响模型的校准过程,在研究区内将规划基本农田信息纳入排除层可以有效提高模型校准精度,从而更好地预测常州市中心城区未来城市扩张情况。     

基于地理模拟方法的昆明市空间拓展情景分析

改革开放以来,西部高原湖滨城市经历的快速城镇化进程给湖泊流域带来了较为严重的生态环境问题,未来城市空间发展政策的调整需要关注城市空间拓展对区域生态环境的影响。以位于滇池湖滨地区的昆明市为例,设定6种不用的城市空间拓展政策情景,应用SLEUTH模型预测了6种情景下未来20年的城市空间格局,采用空间指数和空间分析方法对预测结果进行了分析评价。结果表明：昆明市城市建成区具有典型的摊大饼式空间拓展模式,城市道路网对城市形态具有重要的影响。6种情景模式下未来昆明市建成区空间格局既有相似性,也表现出显著的差异。城市建设用地空间格局总体上呈集约、紧凑型的发展趋势。生态保护与城市发展管制相结合的政策情景对滇池湖滨地区的景观影响最小。多中心城市发展格局和城市发展管制相结合的政策情景对城市总体空间规模的控制具有明显的效果,但不宜在湖滨地区实施。滇池湖滨地区需要划定景观或生态保护区,严格禁止城市建设用地对湖滨用地景观的占用与分割。滇池湖滨以外的区域,适宜执行生态保护与城市发展管制相结合的多中心发展模式。     

广州市海珠区高密度城区扩展SLEUTH模型模拟

高密度城区是城市的核心区,也是城区扩展的源,对该区域的精确识别以及扩展模拟研究,具有重要的意义与价值。以广州市海珠区1979、1990、2000、2008 年4 期Landsat 影像为数据源,运用非渗透表面端元选取模型(V-I-S) 与归一化混合光谱分析模型(NSMA) 相结合的方法,辅以单窗算法反演地表温度数据(LST),高精度提取非渗透表面丰度,进而设置合适阈值表征研究区高密度城区范围。在此基础上基于SLEUTH模型设置4 种场景模拟和预测海珠区高密度城区扩展,并用景观指数分析方法对研究区1979-2050 年长达70 年的空间扩展状况进行分析。主要结论为：① SLEUTH模型同样适用于小尺度区域的扩展模拟。② SLEUTH模型模拟中基于自然、人文以及城市扩展内在动力机制等条件参数的设置,促使模拟结果精度更高。③ SLEUTH模型模拟结果表明,自1979 至今,海珠区高密度城区以较快扩展速率扩张,尤以1990-2004 年间变动增长最快;未来的20 年其增长速率减缓,并于2030 年前后趋于稳定。这种扩张格局与变化状况与研究区产业结构、经济政策、土地规划决策等因素密不可分。