土地利用视角下城市交通事故驱动机理的研究进展

城镇化与机动交通的快速发展,引发了城市土地利用与交通系统的重塑,导致城市交通安全问题日益严峻。为了优化土地利用布局并改善交通安全,需要从土地利用视角开展交通事故的驱动机理研究。国内外该方面研究形成了以交通流量和交通速度为主要中介因素联系土地利用与交通事故的经典理论框架,却忽略了源于土地利用并深刻影响交通安全的交通需求因素,导致缺乏“土地利用—交通需求—交通事故”完整路径链的研究。论文通过综述该领域文献,在归纳总结城市交通事故影响因素的基础上,揭示土地利用视角下交通事故的驱动机理并探讨未来研究方向。研究指出,土地利用的多维属性特征对交通事故具有重要影响,土地利用与交通系统的动态匹配关系及其对出行行为的影响是揭示交通事故驱动机理的关键突破口,对于构建交通安全导向的城市土地利用模式具有重要的理论与实践意义。     

京津冀地区耕地利用转型时空分异及驱动机制

耕地利用转型代表耕地利用形态的趋势性变化。论文以京津冀地区157个县域空间为基本研究单元,从显性形态与隐性形态双重属性出发构建耕地利用形态指标体系,运用冷热点、空间变差函数等方法分析1990—2015年耕地利用形态变化的时空特征,在此基础上,利用空间误差模型(spatial error model, SEM)对耕地利用转型的驱动机制进行了定量分析。结果表明：① 京津冀地区耕地利用形态指数空间分布呈东南高、西北低的格局,与该地区地形分布格局基本一致,且因坝上高原特色农业发展形成独立高值区。② 京津冀地区耕地利用形态指数空间分异呈现逐渐缩小的趋势,显著热点区与显著冷点区分布相对稳定且面积不断缩小,耕地利用转型较为平稳。显性形态值普遍呈现先升高后降低趋势,隐性形态值则呈升高趋势,表明京津冀耕地出现空间收缩、功能优化式转型。③ 高程是影响京津冀地区耕地利用形态空间特征的主要自然环境因素,二三产业占比、地均固定资产投资与城镇化率等经济发展和城镇建设因素则是驱动1990—2015年京津冀地区耕地转型的主导因素,但不同时段、不同县域单元耕地转型动力机制存在差异,各驱动因子作用强度也不完全一致。     

Ecosystem carbon storage under different scenarios of land use change in Qihe catchment,China

Regional land use change is the main cause of the ecosystem carbon storage changes by affecting emission and sink process.However,there has been little research on the influence of land use changes for ecosystem carbon storage at both temporal and spatial scales.For this study,the Qihe catchment in the southern part of the Taihang Mountains was taken as an example;its land use change from 2005 to 2015 was analyzed,the Markov-CLUE-S composite model was used to predict land use patterns in 2025 under natural growth,cultivated land protection and ecological conservation scenario,and the land use data were used to evaluate ecosystem carbon storage under different scenarios for the recent 10-year interval and the future based on the carbon storage module of the In VEST model.The results show the following:(1) the ecosystem carbon storage and average carbon density of Qihe catchment were 3.16×107 t and 141.9 t/ha,respectively,and decreased by 0.07×107 t and 2.89 t/ha in the decade evaluated.(2) During 2005–2015,carbon density mainly decreased in low altitude areas.For high altitude area,regions with increased carbon density comprised a similar percentage to regions with decreased carbon density.The significant increase of the construction areas in the middle and lower reaches of Qihe and the degradation of upper reach woodland were core reasons for carbon density decrease.(3) For 2015–2025,under natural growth scenario,carbon storage and carbon density also significantly decrease,mainly due to the decrease of carbon sequestration capacity in low altitude areas;under cultivated land protection scenario,the decrease of carbon storage and carbon density will slow down,mainly due to the increase of carbon sequestration capacity in low altitude areas;under ecological conservation scenario,carbon storage and carbon density significantly increase and reach 3.19×107 t and 143.26 t/ha,respectively,mainly in regions above 1100 m in altitude.Ecological conservation scenario can enhance carbon sequestration capacity but cannot effectively control the reduction of cultivated land areas.Thus,land use planning of research areas should consider both ecological conservation and cultivated land protection scenarios to increase carbon sink and ensure the cultivated land quality and food safety.     

Integration of remote sensing,county-level census,and machine learning for century-long regional cropland distribution data reconstruction

The Lower Mississippi Alluvial Valley (LMAV) was home to about ten million hectare bottomland hardwood (BLH) forests in the Southern U.S. It experienced over 80 % area loss of the BLH forests in the past centuries and large-scale afforestation in recent decades. Due to the lack of a high-resolution cropland dataset, impacts of land use change (LUC) on the LMAV ecosystem services have not been fully understood. In this study, we developed a novel framework by integrating the machine learning algorithm, county-level agricultural census, and satellite-based cropland products to reconstruct the LMAV cropland distribution during 1850–2018 at a 30-m resolution. Results showed that the LMAV cropland area increased from 0.78 × 10⁴ km² in 1850 to 6.64 × 10⁴ km² in 1980 and then decreased to 6.16 × 10⁴ km² in 2018. Cropland expansion rate was the largest in the 1960s (749 km² yr⁻¹) but decreased rapidly thereafter, whereas cropland abandonment rate increased substantially in recent decades with the largest rate of 514 km² yr⁻¹ in the 2010s. Our dataset has three notable features: (1) the depiction of fine spatial details, (2) the integration of the county-level census, and (3) the inclusion of a machine-learning algorithm trained by satellite-based land cover product. Most importantly, our dataset well captured the continuous increasing trend in cropland area from 1930–1960, which was misrepresented by other cropland datasets reconstructed from the state-level census. Our dataset would be important to accurately evaluate the impacts of historical deforestation and recent afforestation efforts on regional ecosystem services, attribute the observed hydrological changes to anthropogenic and natural driving factors, and investigate how the socioeconomic factors control regional LUC pattern. Our framework and dataset are crucial to developing managerial and policy strategies for conserving natural resources and enhancing ecosystem services in the LMAV.     

毛乌素沙地植被水分利用效率的时空格局

水分利用效率（WUE）是衡量生态系统碳水循环耦合程度的重要指标,明晰其动态变化规律有助于判断区域植被生态建设是否与当地的自然条件相适应。利用基于CASA（Carnegie-Ames-Stanford Approach）模型得到的植被净初级生产力（NPP）数据和MODIS系列产品中的蒸散发（ET）数据,估算了2001—2016年毛乌素沙地植被的WUE,并探讨了其时空演变特征及与气象因子的关系。结果显示：（1）WUE的多年平均值为0.62 gC·mm^-1·m^-2,空间上自东向西递减,在不同植被类型间表现为栽培植物>灌丛>草甸>草原>荒漠;（2）WUE以0.009 gC·mm^-1·m^-2·a^-1的速率上升,东部地区变化尤为显著,NPP的快速增长是WUE呈增加趋势的主要原因;（3）WUE与各气象因子的相关程度由大至小依次为太阳辐射、降水量、风速和气温,分布在西部地区的荒漠植被WUE受气象因子影响最小。经过一系列生态建设工程的治理,毛乌素沙地大部分地区自2001年以来NPP和WUE均呈增加趋势,即生态系统在变“绿”的同时还实现了水分的高效利用,有利于当地生态环境的健康发展;但在水热条件较差的中西部地区,新建设的植被生长缓慢且导致蒸散发产生强烈变化,使WUE呈减少趋势,暴露出植被建设规模与水资源承载能力不匹配的问题,需引起格外重视。     

城市增长边界研究进展——理论模型、划定方法与实效评价

新型城镇化背景下,传统粗放的城镇土地利用模式难以为继,控制城市规模、优化空间格局已成为当前国土资源管理的重点工作之一。城市增长边界(UGB)作为一种西方国家控制城市蔓延的技术手段和政策工具已逐渐被引入国内。采用文献资料法和归纳演绎法,梳理并分析了国内外城市增长边界的理论模型、划定方法与实效评价,挖掘未来城市增长驱动力和增长边界制定方法可能的研究方向,为后续研究和未来其在中国的实践提供参考。结果表明：① 城市增长边界实证研究的理论基础主要源于古典单中心城市模型,由于国情不同,国内主要关注经济水平、产业结构和可达性对城市增长的影响,而国外在此基础上还关注公共政策和服务、外部性以及主体间的博弈对城市蔓延的促进或抑制作用;② 城市增长刚性边界划定主要以土地适宜性和承载力评价为基础,弹性边界可采用元胞自动机进行空间辅助模拟;③ 国外城市增长边界的实施效果具有地区差异性,国内目前还缺乏城市增长边界实施效果评价相关方面的研究。因此,城市增长驱动力后续研究应吸纳多源理论,识别不同尺度下其机理特征,探索宏观环境的情景变量对微观环境下“驱动力—城市增长”这一关系的影响。城市增长弹性边界制定需要考虑城乡土地利用转换背后不同情景下主体间的复杂博弈对用地转换在空间上分布的决定作用。为了保证政策的持续性和统筹区域发展,未来需要明确城市增长边界的管理机构,制定对应的法律条款和管理体系。     

Local and landscape effects on spatial patterns of mangrove forest during wetter and drier periods: Moreton Bay,Southeast Queensland,Australia

Land use/cover and mangrove spatial changes were assessed for ten sites and their sub-catchments in Southeast Queensland, Australia. Two time periods were involved: 1972–1990, a period of relatively high rainfall, and 1990–2004, which was significantly drier. Aerial photographs and Landsat satellite imagery were used to map the inter-tidal wetlands and classify the land use/cover in the sub-catchments. A Maximum Likelihood Classification was used to map three types of land cover: agriculture, built-up and plantation forest. Mangroves (mainly Avicennia marina) were the focus as they have been recorded over recent decades encroaching into salt marsh. The Mangrove-Salt marsh Interface (MSI) Index was developed to quantify the relative opportunity for mangroves to expand into salt marshes, based on the shared boundary between them. The index showed a consistent relationship with mangrove expansion and change. To address problems of high dimensionality and multi-collinearity of predictor variables, a Partial Least Squares Regression (PLSR) model was used. A key finding of this research was that the contribution of environmental variables to spatial changes in the mangroves was altered following a reduction in rainfall. For example, agriculture had more influence on mangrove expansion and change during the wet period than during the dry period.     

3S技术在海南省海岸保护利用规划中的应用

利用3s技术强大的空间信息处理和管理能力及制图能力,实现了在海南省海岸保护利用规划中多源地理数据采集处理、专题信息分析提取、规划图集编制和规划信息管理系统的建立等．结果表明：采用3S技术能够较好地处理海南省海岸保护利用规划中涉及的陆图、海图、遥感图、海洋功能区图、相关规划图和项目用海图等基础地理数据,以及现场调查、勘测数据的空间位置关系;提取了海南岛海岸类型、海岸开发利用现状等专题信息;结合海南社会经济发展对海岸资源开发利用的需求和生态环境保护要求,划分基本功能岸段,总体为北部海岸以港口、旅游岸段为主,东部海岸以旅游、渔业岸段为主,南部海岸以旅游、港口岸段为主,西部海岸以港口、渔业岸段为主．     

快速城镇化背景下的浙江省海岸带生态系统服务价值变化

从快速城镇化背景下土地利用变化的角度来分析浙江省海岸带生态系统服务价值(ESV)损益情况,将ESV的估算引入海岸带开发决策,对浙江省海岸带资源的可持续利用具有重要意义.以1990、2000、2010年遥感解译数据为基础,研究了快速城镇化背景下浙江省海岸带土地利用类型变化,并通过构建ESV估算模型,估算了1990~2010年间浙江省海岸带ESV变化.结果表明:1990~2010年间,由于城镇化速度不断加快,浙江省海岸带土地利用类型变化显著,主要表现为城镇建设用地大量增加,林地和耕地面积减少.期间浙江省海岸带ESV总量不断减少,从352.78亿元降至299.64亿元,降幅达15.06%.浙江省海岸带ESV空间分布不断由高价值区域向低价值区域转变.各土地利用类型价值系数(CS)均小于1,价值总量对价值系数弹性不大,所设置的ESV系数原始值较为合适.浙江省海岸带土地利用强度不断上升,其空间分布与ESV变化率空间分布具有一致性,无序增加的城镇建设用地占用林地和耕地而引起的土地利用结构转变是海岸带ESV不断减损的主要原因.     

顾及地类转换差异的城市空间扩展元胞自动机模型及应用研究

元胞自动机模型已经成为城市空间扩展模拟研究的重要方法之一,并得到广泛应用。然而,现有的城市扩展元胞自动机模型仍存在不足。由于元胞状态设置较为简单,从而使模型转换规则中对不同用地类型向城市用地转换的差异与强度考虑不够。基于此本文在元胞自动机模型的框架下,设计了多元结构的元胞状态及转换规则,提出了顾及地类转换差异与强度的城市扩展元胞自动机模型。在计算非城市用地向城市用地转换的转换概率时,该模型考虑了3个方面的概率：① 地形地貌、经济发展等城市发展的驱动因素对城市用地扩展的影响概率,该概率采用logistics方法进行计算;② 邻域元胞的用地类型对中心元胞转换概率的影响,该概率采用扩展摩尔型方法进行计算;③ 不同类型的非城市用地（本研究中包括耕地、林地和裸地3种类型）向城市用地转换的强度,该概率由模拟基期土地利用数据与目标年份土地利用数据的叠加,得出不同类型的非城市用地在此时间段内向城市用地转换的规模,进而确定不同类型的非城市用地向城市用地转换的强度。最后,将以上3种概率的乘积作为元胞转换的概率。通过转换概率与转换阈值的对比判断中心元胞是否在下一个阶段转换为城市用地。经过迭代计算,不断增加城市用地元胞的数量。当模拟城市用地的结果与目标年份的城市用地规模差值在一定的范围内时停止模拟,得出最终结果。模型构建完成后,本文以长株潭城市群核心区为例进行了模拟实验。以2001年该地区的土地利用数据为基期数据,模拟2010年该地区的城市用地规模和空间分布。研究结果表明,根据本文提出的模型模拟的城市扩展结果与真实数据相比具有较高的一致性。模拟结果正确率达到68.66%,比基于传统logistics回归的元胞自动机模型的模拟精度提高了4.25%,Kappa系数为0.675。该模型较好地模拟了长株潭城市群核心区城市扩展,在城市空间扩展模拟中具有较好的适应性与有效性。