基于知识的分层综合分类法在土地利用/土地覆盖遥感信息提取中的应用

土地利用/土地覆盖数据的获取是研究LUCC的重要基础工作。随着遥感技术的飞速发展,通过遥感提取土地利用/土地覆盖专题信息已成为LUCC研究必不可少的一步。目前遥感专题信息提取水平相对滞后于遥感数据获取,为了提高遥感数据在土地利用/土地覆盖的应用,寻找一种较好的、具有相对适用性的方法是目前遥感应用的一个迫切要求。本文比较了目前比较常用的几种土地利用/土地覆盖遥感信息提取方法,分别以西部干旱区(柴达木盆地)和东部地区(鄱阳湖地区)为例,提出在GIS支持下基于知识的分层综合分类方法,并通过和其他几种常用方法进行比较分析,得到如下结果:在自然环境相差较大的柴达木盆地和鄱阳湖地区,采用了GIS支持下基于知识的分层综合分类方法的提取精度均要比单独采用最大似然法、纹理分析法、神经网络分类法等方法的总体精度高出25%,Kappa系数高出0.2。由此可以说明了该方法对于土地利用/土地覆盖专题信息的提取是可行的,同时它也具有一定的适用性。     

Enhancing areal interpolation frameworks through dasymetric refinement to create consistent population estimates across censuses

To assess micro-scale population dynamics effectively, demographic variables should be available over temporally consistent small area units. However, fine-resolution census boundaries often change between survey years. This research advances areal interpolation methods with dasymetric refinement to create accurate consistent population estimates in 1990 and 2000 (source zones) within tract boundaries of the 2010 census (target zones) for five demographically distinct counties in the US. Three levels of dasymetric refinement of source and target zones are evaluated. First, residential parcels are used as a binary ancillary variable prior to regular areal interpolation methods. Second, Expectation Maximization (EM) and its data-extended version leverage housing types of residential parcels as a related ancillary variable. Finally, a third refinement strategy to mitigate the overestimation effect of large residential parcels in rural areas uses road buffers and developed land cover classes. Results suggest the effectiveness of all three levels of dasymetric refinement in reducing estimation errors. They provide a first insight into the potential accuracy improvement achievable in varying geographic and demographic settings but also through the combination of different refinement strategies in parts of a study area. Such improved consistent population estimates are the basis for advanced spatio-temporal demographic research.     

Projected changes in population exposure to extreme heat in China under a RCP8.5 scenario

Overall population exposure is measured by multiplying the annual average number of extremely hot days by the number of people exposed to the resultant heat. Extreme heat is also subdivided into high temperature (HT) and extremely high temperature (EHT) in cases where daily maximum temperature exceeds 35°C and 40°C, respectively. Chinese population exposure to HT and EHT over four periods in the future (i.e., 2021–2040, 2041–2060, 2060–2081 and 2081–2100) were projected at the grid cell level in this study using daily maximum temperature based on an ensemble mean of 21 global climate models under the RCP8.5 scenario and with a population projection based on the A2r socio-economic scenario. The relative importance of population and climate as drivers of population exposure was evaluated at different spatial scales including national and meteorological geographical divisions. Results show that, compared with population exposure seen during 1981–2010, the base period, exposure to HT in China is likely to increase by 1.3, 2.0, 3.6, and 5.9 times, respectively, over the four periods, while concomitant exposure to EHT is likely to increase by 2.0, 8.3, 24.2, and 82.7 times, respectively. Data show that population exposure to HT is likely to increase significantly in Jianghuai region, Southwest China and Jianghan region, in particular in North China, Huanghuai region, South China and Jiangnan region. Population exposure to EHT is also likely to increase significantly in Southwest China and Jianghan region, especially in North China, Huanghuai, Jiangnan, and Jianghuai regions. Results reveal that climate is the most important factor driving the level of population exposure in Huanghuai, Jianghuai, Jianghan, and Jiangnan regions, as well as in South and Southwest China, followed by the interactive effect between population and climate. Data show that the climatic factor is also most significant at the national level, followed by the interactive effect between population and climate. The rate of contribution of climate to national-level projected changes in exposure is likely to decrease gradually from ca. 70% to ca. 60%, while the rate of contribution of concurrent changes in both population and climate is likely to increase gradually from ca. 20% to ca. 40% over the four future periods in this analysis.     

地理系统模型研究进展

地理系统是多圈层交互的复杂巨系统。地理系统模型是理解和预测不同尺度地理系统格局和过程变化最重要的研究方法。地理系统模型作为可持续发展科学决策必需的工具,是自然地理学重要的研究方向。过去几十年来,在全球变化等全球性重大环境问题和人类科学决策需求的推动下,地理系统模型虽然发展迅速,但还不足以准确地模拟和预测复杂人地耦合系统。本文分别从模型原理、框架和尺度等方面回顾与梳理了地理系统模型从单要素到多要素、从统计到过程、从静态到动态、从单点到区域和全球尺度模拟等发展历程,并总结了地理系统模型对发展人类—自然耦合系统以及模型—数据融合系统的趋势。发展中国的地理系统模型将有助于中国和全球可持续发展的科学决策。     

Gen*: a generic toolkit to generate spatially explicit synthetic populations

Agent-based models tend to integrate more and more data that can deeply impact their outcomes. Among these data, the ones that deal with agent attributes and localization are particularly important, but are very difficult to collect. In order to tackle this issue, we propose a complete generic toolkit called Gen* dedicated to generating spatially explicit synthetic populations from global (census and GIS) data. This article focuses on the localization methods provided by Gen* that are based on regression, geometrical constraints and spatial distributions. The toolkit is applied for a case study concerning the generation of the population of Rouen (France) and shows the capabilities of Gen* regarding population spatialization.     

Spatiotemporal wetland changes and their threats in North Central Ethiopian Highlands

Wetlands are important environmental resources for rural livelihoods in Ethiopia. The study investigated spatiotemporal change of wetlands, drivers and effects in North Central Ethiopian Highlands. Landsat satellite imageries of 1984, 1993, 2000, and 2013 were used to analyse wetland changes over the last three decades. Practical observations, interviews and discussions with local communities and officers were also conducted to address the main objective. Furthermore, secondary data on crop yields were collected to supplement the primary data. The study shows that wetlands have been converted into built‐up areas and farmlands. Wetlands in the study area experienced annual loss across the entire study period. Consequently, the area size of wetlands decreased from 7.4 per cent in 1984 to 2.6 per cent in 2013. About 66 per cent of the total wetlands was lost within 30 years mainly due to farmland encroachment and urban expansions. The highest rate of wetland change was recorded between 2000 and 2013. Such wetland changes increased conflicts among land users. However, the converted wetlands increased short‐term benefits due to wetland recession agriculture. To conclude, wetland resources are under enormous threats, and challenge the sustainability of livelihoods. Thus, integrated and adaptive wetland restoration policies could improve the degraded wetlands.     

中国14个连片特困地区的森林转型及其解释

利用MODIS土地覆盖数据,分析了2002-2013年中国14个连片特困地区森林转型的特点,探明了连片特困地区林地变化的趋势及其空间异质性。在此基础上,选择空间变量,建立线性回归模型探究林地面积变化的影响因素,得出连片特困地区森林转型所遵循的路径。结果表明,2002-2013年间,中国14个连片特困地区林地面积净增加106554.75 km²,增长率为11.93%,森林进入转型后期,即森林面积净增加阶段;秦巴山区、武陵山区、西藏地区东南部、四省藏区东部、燕山—太行山区东部是林地增长的热点区域,而林地增长冷点区域则主要分布在800 mm等降水量线以北的广大区域、大别山区和滇桂黔石漠化区东部;非农人口的增加以及林业工程的实施都对林地面积的增加有显著的促进作用,中国14个连片特困地区的森林转型主要遵循着经济发展路径和国家森林政策路径。在连片特困地区,应加快小城镇建设的步伐,同时依托其丰富的自然资源,因地制宜地发展乡村生态旅游业;国家森林政策方面,应将连片特困地区作为生态建设重点区域,切实保护中国的森林资源。     

基于相互作用关系的中国省际人口流动研究

基于2000年、2010年人口普查及2005年、2015年人口抽样调查数据,采用相互作用关系模型计算了中国“人口流动系统”和“单向相互作用关系值”。结果表明：① 人口流动具有明显的凝聚性,东部地区对流动人口的吸引力依然具有绝对优势;② 省际人口流动呈“非对称双向迁移模式”,人口回流的趋势已不容忽视;③ 长三角地区逐渐代替珠三角成为新的人口流动中心,人口流动开始北移;④ 中西部地区的人口流动分中心某种意义上已经出现,人口就近转移日渐凸显。将2010-2015年间省际人口流动新规律和特征与1995-2010年进行动态对比,对于制定未来人口和区域发展政策,继续缩小东西部地区之间的差距,最终实现区域协调发展具有重要意义。     

中国人口健康脆弱性地区差异与影响因素分析

通过构建人口健康脆弱性评价指标体系,利用集对分析法对中国31个省级行政区（不含港、澳、台）的健康脆弱性指数进行测算,同时引入障碍度模型考察脆弱性指数分布差异的影响因素,并对各省区主要障碍因子进行识别。研究发现：① 2014年中国人口健康脆弱性省际差异较大,总体上处于中、高水平,在空间上呈现明显的“西高、东低、中部居中”分异格局,与健康敏感性、应对性指数的地域分布不尽一致;② 各省区健康脆弱性指数分布的地域级差化特征明显,低脆弱省市均分布在东部地带,高脆弱省区均分布在西部地带,中度和较高脆弱水平的省区数量最多,在三大地带上均有分布;③ 健康脆弱性降低的主要障碍因子存在较大地区差异,促进经济发展、增加社保支出、加大卫生投入、改善医疗条件和优化生态环境对降低脆弱性尤为重要。     

Development of an establishment scheme for a DGVM

Environmental changes are expected to shift the distribution and abundance of vegetation by determining seedling establishment and success. However, most current ecosystem models only focus on the impacts of abiotic factors on biogeophysics (e.g., global distribution, etc.), ignoring their roles in the population dynamics (e.g., seedling establishment rate, mortality rate, etc.) of ecological communities. Such neglect may lead to biases in ecosystem population dynamics (such as changes in population density for woody species in forest ecosystems) and characteristics. In the present study, a new establishment scheme for introducing soil water as a function rather than a threshold was developed and validated, using version 1.0 of the IAP-DGVM as a test bed. The results showed that soil water in the establishment scheme had a remarkable influence on forest transition zones. Compared with the original scheme, the new scheme significantly improved simulations of tree population density, especially in the peripheral areas of forests and transition zones. Consequently, biases in forest fractional coverage were reduced in approximately 78.8% of the global grid cells. The global simulated areas of tree, shrub, grass and bare soil performed better, where the relative biases were reduced from 34.3% to 4.8%, from 27.6% to 13.1%, from 55.2% to 9.2%, and from 37.6% to 3.6%, respectively. Furthermore, the new scheme had more reasonable dependencies of plant functional types (PFTs) on mean annual precipitation, and described the correct dominant PFTs in the tropical rainforest peripheral areas of the Amazon and central Africa.