Temporal replication of the national land cover database using active machine learning

Regional and national level land cover datasets, such as the National Land Cover Database (NLCD) in the United States, have become an important resource in physical and social science research. Updates to the NLCD have been conducted every 5 years since 2001; however, the procedure for producing a new release is labor-intensive and time-consuming, taking 3 or 4 years to complete. Furthermore, in most countries very few, if any, such releases exist, and thus there is high demand for efficient production of land cover data at different points in time. In this paper, an active machine learning framework for temporal updating (or backcasting) of land cover data is proposed and tested for three study sites covered by the NLCD. The approach employs a maximum entropy classifier to extract information from one Landsat image using the NLCD, and then replicate the classification on a Landsat image for the same geographic extent from a different point in time to create land cover data of similar quality. Results show that this framework can effectively replicate the land cover database in the temporal domain with similar levels of overall and within class agreement when compared against high resolution reference land cover datasets. These results demonstrate that the land cover information encapsulated in the NLCD can effectively be extracted using solely Landsat imagery for replication purposes. The algorithm is fully automated and scalable for applications at landscape and regional scales for multiple points in time.     

均生函数与BP神经网络耦合模拟预测模型(MGF-BP-I)的建立与应用

水文气候因子模拟预测对气候变化研究、农业墒情预报、生态环境改善、水资源合理开发利用等具有一定参考意义。均生函数、BP神经网络及其结合改进方式在模拟预测中各有优点,被广泛应用,但仍有进一步改进空间。针对MGF、MGF-OSR、MGF-OSR-BP等方法粗选因子集、粗选集组合筛选、收敛适应性、精度控制等可改进空间,进一步发挥均生函数和BP神经网络优势,建立了MGF-BP-I模拟预测模型。利用MGF-OSR、MGF-OSR-BP、MGF-BP-I对科尔沁沙地区域平均年降水进行了模拟预测。结果表明,建模期MGF-OSR-BP、MGF-BP-I拟合效果均较好,MGF-BP-I建模阶段最优模式精度优于MGF-OSR-BP,MGF-BP-I整体同时最优模式结果也非常好。检验期,MGF-BP-I检验阶段最优及整体同时最优两种模式拟合效果最好,相比其他模式精度有所提高。MGF-BP-I考虑更加全面,充分发挥了均生函数和BP神经网络优势,精度远高于MGF-OSR和MGF-OSR-BP,MGF-BP-I整体同时最优模式更符合实际应用,效果理想,可用于水文气候因子模拟预测。     

基于层次分析法的德州地面沉降易发区的可拓学划分应用

基于物元模型的可拓学理论分析,提出华北平原德州地面沉降易发区的可拓学划分方法。利用地面沉降易发性分级、分类标准和影响因子分析,构造出经典域物元和节域物元,应用物元和可拓集合中的关联函数,建立了易发性等级综合评判的可拓评价模型,通过基于层次分析法的可拓学评价分析,采用正方形等间距(2km×2km)剖分了135个网格,再将剖分单元转化成面元,经过等值差分,得到了地面沉降易发区划结果。计算结果显示,可拓学方法能够实现定量化、多因子评价地面沉降易发性等级问题,从而科学合理地指导地面沉降综合分区防治。     

肥城市土地生态系统安全评价研究

在分析土地生态系统安全内涵的基础上,以肥城市为研究区域,选取24个指标构建土地生态系统安全评价指标体系,采用熵值法、综合指数法和GIS相结合的方法,对肥城市2000—2013年的土地生态系统安全状况进行分析。研究结果表明:14年来,肥城市土地生态系统安全状况处于波动状态,土地生态系统安全面临着诸多压力。最后提出了提高土地生态系统安全状况的对策建议。     

基于地学规律的科尔沁沙地土地整治与生态修复规划方法

内蒙古科尔沁沙地历史上曾是科尔沁大草原,现在是农牧交错区,该区的土地利用关系到生态安全、国家粮食安全和农民生计。该区域“坨甸相间”地貌特点造成不同地形部位土壤含水量存在差异,降水量年际变化大。通过卫星影像数据解译出土地利用/覆被类型图与土壤图进行叠加,获得了显性沙地和隐性沙地数量与分布信息。首先保留耕地以外的其他地类,再利用卫星影像数据反映不同降水年型耕地的归一化植被指数(NDVI),将偏欠水年NDVI低于平均值的耕地退耕还草,消除这些耕地的冬春沙化风险,以进行土地利用布局调整。这种直接利用遥感数据获取土地利用/覆被类型和耕地的NDVI进行土地利用空间布局调整的方法,十分简单实用。本文还根据地貌和沙地降水入渗快的特点,提出了与高标准农田建设模式不同但与区域地理环境相吻合的农田整治模式,即利用自然沙丘作为区域风沙防护工程,土地开发不做大平整,不修建灌溉系统,发展雨养农业。以上根据区域地理环境条件进行土地利用布局和确定农田开发建设模式,可将农业生产与荒漠化防治和谐结合在一起,实现土地可持续利用。     

冈瓦纳大陆边缘罗斯运动的岩浆活动时代:来自北维多利亚地松散沉积物锆石年龄的证据

横穿南极大陆中部的横贯南极山脉是早古生代时期古太平洋向东冈瓦纳活动大陆边缘俯冲形成的罗斯造山带,该阶段的地层沉积、变形变质以及花岗质岩浆侵入代表了罗斯运动的演化过程。由于岩浆活动与沉积地层和变形变质在时代上存在明显差异,罗斯运动的时代仍缺乏精确的限定。通过采集北维多利亚地难言岛地区冰碛物和海岸沉积物中的松散砂砾石样品,并进行碎屑锆石U-Pb测年得出:4件不同粒径的冰碛物和海岸沉积样品中的碎屑锆石年龄峰谱具有单一峰谱的特征,年龄区间为2443~323 Ma,主要集中于530~450 Ma之间,峰值年龄约为485 Ma;锆石Th/U比值均大于0.1,而且以＞0.4为主,其CL图像也具有明显的振荡环带,稀土元素特征主体具有岩浆锆石的特征,反映了样品物源区岩浆活动的时代特征。碎屑锆石年龄组成与周缘地区岩浆活动和陆内变形以及沉积地层时代基本一致,表明北维多利亚地及其周缘地区在罗斯运动晚期陆内变形阶段的岩浆活动应持续至450 Ma,这可能代表了罗斯运动结束的时代,该结果为冈瓦纳大陆边缘罗斯运动的构造演化过程提供了新的约束。      

由非季风区向季风区过渡过程中大气边界层结构的变化分析

利用中国西北中部具有代表性的非季风区、夏季风影响过渡区和季风区的7个高空站的2013年夏季晴天07时、13时、19时（北京时）的大气边界层资料,通过分析大气边界层位温、比湿、风速的垂直结构,发现大气边界层结构及厚度在不同区域的分布特征:稳定边界层厚度、残余层顶高度和对流边界层厚度从非季风区、夏季风影响过渡区至季风区出现阶梯性大幅降低,从非季风区至夏季风影响过渡区,以及从夏季风影响过渡区至季风区,对流边界层厚度降幅依次为25.6%和81.8%,稳定边界层厚度降幅依次为58.3%和41.8%;在稳定边界层条件下,可观察到低空急流的存在,非季风区低空急流出现高度明显高于夏季风影响过渡区和季风区,且非季风区的低空急流风速也明显大于夏季风影响过渡区和季风区。通过分析与大气边界层发展最为密切的陆面热力因素在不同气候区的分布,净辐射值、日地-气温差最大值以及感热通量值在非季风区大于夏季风影响过渡区和季风区,从陆面热力过程为非季风区大气边界层厚度大于夏季风影响过渡区和季风区提供了理论依据。     

The relative influence of climate and housing development on current and projected future fire patterns and structure loss across three California landscapes

Climate and land use patterns are expected to change dramatically in the coming century, raising concern about their effects on wildfire patterns and subsequent impacts to human communities. The relative influence of climate versus land use on fires and their impacts, however, remains unclear, particularly given the substantial geographical variability in fire-prone places like California. We developed a modeling framework to compare the importance of climatic and human variables for explaining fire patterns and structure loss for three diverse California landscapes, then projected future large fire and structure loss probability under two different climate (hot-dry or warm-wet) and two different land use (rural or urban residential growth) scenarios. The relative importance of climate and housing pattern varied across regions and according to fire size or whether the model was for large fires or structure loss. The differing strengths of these relationships, in addition to differences in the nature and magnitude of projected climate or land use change, dictated the extent to which large fires or structure loss were projected to change in the future. Despite this variability, housing and human infrastructure were consistently more responsible for explaining fire ignitions and structure loss probability, whereas climate, topography, and fuel variables were more important for explaining large fire patterns. For all study areas, most structure loss occurred in areas with low housing density (from 0.08 to 2.01 units/ha), and expansion of rural residential land use increased structure loss probability in the future. Regardless of future climate scenario, large fire probability was only projected to increase in the northern and interior parts of the state, whereas climate change had no projected impact on fire probability in southern California. Given the variation in fire-climate relationships and land use effects, policy and management decision-making should be customized for specific geographical regions.     

The role of global dietary transitions for safeguarding biodiversity

Diets lower in meat could reduce agricultural expansion and intensification thereby reducing biodiversity impacts. However, land use requirements, associated with alternate diets, in biodiverse regions across different taxa are not fully understood. We use a spatially explicit global food and land system model to address this gap. We quantify land-use change in locations important for biodiversity across taxa and find diets low in animal products reduce agricultural expansion and intensity in regions with high biodiversity. Reducing ruminant meat consumption alone however was not sufficient to reduce fertiliser and irrigation application in biodiverse locations. The results differed according to taxa, emphasising that land-use change effects on biodiversity will be taxon specific. The links shown between global meat consumption and agricultural expansion and intensification in the biodiverse regions of the world indicates the potential to help safeguard biodiverse natural ecosystems through dietary change.     

海南岛不同土地覆盖资料对WRF模拟的影响*

提取GLC2009土地覆盖数据,将其运用到WRF数值模式并与模式自带的MODIS、USGS土地覆盖进行对比,以海南岛做为研究区域,选择一次海风锋天气过程进行敏感性分析,结果表明：①GLC2009对海南岛农耕地、森林的划分最接近实际情况,在海南岛平原以及丘陵地带,MODIS和USGS划分的农耕地比例过高,而在山区森林比例偏低;②GLC2009、MODIS、USGS对海南岛北部的降水模拟出现了空报,但是GLC2009对东海岸的强降水模拟的较好,并避免了MODIS和USGS在海南西南部的降水空报的情况;③GLC2009模拟的10米风场清晰刻画了东海岸海风锋辐合,其相对合理的森林覆盖提高了地表粗糙度并增强了风场辐合、低反照率对地面气温的增加和海陆热力差异的增强有一定的促进作用。④GLC2009对这次海风锋过程中模拟的感热通量和潜热通量都要高于MODIS和USGS,这种陆气间的热通量交换利于强对流天气的触发,发展。