Identification of multi-scale corresponding object-set pairs between two polygon datasets with hierarchical co-clustering

In this paper, we propose a means of finding multi-scale corresponding object-set pairs between two polygon datasets by means of hierarchical co-clustering. This method converts the intersection-ratio-based similarities of two objects from two datasets, one from each dataset, into the objects’ proximity in a geometric space using a Laplacian-graph embedding technique. In this space, the method finds hierarchical object clusters by means of agglomerative hierarchical clustering and separates each cluster into object-set pairs according to the datasets to which the objects belong. These pairs are evaluated with a matching criterion to find geometrically corresponding object-set pairs. We applied the proposed method to the segmentation result of a composite image with 6 NDVI images and a forest inventory map. Regardless of the different origins of the datasets, the proposed method can find geometrically corresponding object-set pairs which represent hierarchical distinctive forest areas.     

Augmenting forest inventory attributes with geometric optical modelling in support of regional susceptibility assessments to bark beetle infestations

Assessment of the susceptibility of forests to mountain pine beetle (Dendroctonus ponderosae Hopkins) infestation is based upon an understanding of the characteristics that predispose the stands to attack. These assessments are typically derived from conventional forest inventory data; however, this information often represents only managed forest areas. It does not cover areas such as forest parks or conservation regions and is often not regularly updated resulting in an inability to assess forest susceptibility. To address these shortcomings, we demonstrate how a geometric optical model (GOM) can be applied to Landsat-5 Thematic Mapper (TM) imagery (30 m spatial resolution) to estimate stand-level susceptibility to mountain pine beetle attack. Spectral mixture analysis was used to determine the proportion of sunlit canopy and background, and shadow of each Landsat pixel enabling per pixel estimates of attributes required for model inversion. Stand structural attributes were then derived from inversion of the geometric optical model and used as basis for susceptibility mapping. Mean stand density estimated by the geometric optical model was 2753 (standard deviation ± 308) stems per hectare and mean horizontal crown radius was 2.09 (standard deviation ± 0.11) metres. When compared to equivalent forest inventory attributes, model predictions of stems per hectare and crown radius were shown to be reasonably estimated using a Kruskal–Wallis ANOVA (p < 0.001). These predictions were then used to create a large area map that provided an assessment of the forest area susceptible to mountain pine beetle damage.     

Predictive landslide susceptibility assessment using the weight-of-evidence method in north-central Garhwal Himalaya,India

Landslides are frequent natural disasters in mountainous regions, particularly in the Himalayas in India during the southwest monsoon season. Although scientific study of landslides has been in progress for years, no significant achievement has been made to preclude landsliding and allay disasters. This research was undertaken to understand the areal distribution of landslides based on geological formations and geomorphological processes, and to provide more precise information regarding slope instability and mechanisms of failure. After completing a landslide inventory, prepared through field investigation and satellite image analysis, 493 landslides, comprising 131 investigated in the field and 362 identified from satellite imagery, were identified and mapped. The areal distribution of these landslides shows that sites more prone to landsliding have moderate to steep slopes, the lithology of the Lesser Himalayan formations, and excavations for road corridors. Landslide susceptibility zones were delineated for the area using the weight-of-evidence method on the basis of the frequency and distribution of landslides. Weights of selected variables were computed on the basis of severity of triggering factors. The accuracy of landslide susceptibility zones, calculated statistically (R² = .93), suggests high accuracy of the model for predicting landsliding in the area.     

区域尺度土壤固碳量估算方法评述

增加陆地生态系统碳汇已成为一项重要的减排手段,被纳入有关国际气候变化协定。区域尺度土壤固碳量估算成为当前研究的热点与难点。本文综述了目前国内外常用的区域土壤固碳量估算方法,并依据估算精度与方法差异将这些方法总结为四类:简易模型、清查法、经验模型和基于GIS的机理模型。同时对这四类方法的特点和适用性进行了评述,建议根据研究地区及目的不同选择合适的方法。此后,通过分析土壤固碳机理、数据收集、尺度推移、情景分析和土壤有机质机理模型发展等与区域土壤固碳量估算密切相关的各方面中存在的不足,提出今后区域尺度土壤固碳量估算方法将向耦合土壤有机质机理模型、土壤可溶性碳模型、土地利用模型和区域水文模型的基于GIS平台的区域综合模型方向发展。     

基于第二次冰川编目的中国冰川现状

以2004年之后的Landsat TM/ETM+和ASTER遥感影像为基础,参考第一次中国冰川目录及其他文献资料,经过影像校正、自动解译、野外考察、人工修订、交互检查和成果审定等技术环节,完成占全国冰川总面积85.5%的现状冰川编目,确定中国目前共有冰川48571条,总面积约5.18×10⁴βkm²,约占全国国土面积的0.54%,冰川储量约4.3~4.7×10³βkm³。中国冰川数量和面积分别以面积<0.5βkm²的冰川和面积介于1.0~50.0βkm²的冰川为主,面积最大的冰川是音苏盖提冰川（359.05βkm²）。中国西部14座山系（高原）均有冰川分布,其中昆仑山冰川数量最多,其次是天山、念青唐古拉山、喜马拉雅山和喀喇昆仑山,这5座山系冰川数量占全国冰川总数量的72.3%;冰川面积和冰储量位列前3位的山系分别为昆仑山、念青唐古拉山和天山,尽管喀喇昆仑山冰川数量和面积均小于喜马拉雅山,但前者冰储量高于后者。从冰川海拔分布来看,海拔4500~6500βm之间是冰川集中发育区域,约占全国冰川总面积的4/5以上。冰川资源在各流域分布差异显著,东亚内流区（5Y）是中国冰川分布数量最多、面积最大的一级流域,约占全国冰川总量的2/5以上;黄河流域（5J）是冰川数量最少、规模最小的一级流域,仅有冰川164条,面积126.72βkm²。新疆和西藏的冰川面积和冰储量约占全国冰川总面积的9/10。     

中国大陆Cs-137背景值研究

土壤侵蚀是关系人类生存与可持续发展的重大环境问题。20世纪60年代以来,Cs-137作为一种人工放射性示踪核素,被广泛应用于土壤侵蚀及堆积研究。而准确估算区域Cs-137背景值（Cs-137 Reference Inventory, CRI）是应用Cs-137开展土壤侵蚀研究的前提条件,其结果直接影响土壤侵蚀速率结果的准确性和可靠性。基于现有文献资料中获取的中国大陆102个CRI实测数据,以及全球降水气候中心提供的降水量再分析资料（空间分辨率2.5°×2.5°、0.5°×0.5°,1981-2010年）,在借鉴Walling & He模型（Walling & He Model, WHM）和Michio Aoyama模型（Michio Aoyama Model, MAM）的基础上,本文建立了中国大陆CRI修正模型（Modified CRI Model for the Mainland of China, MCM）,并利用Kriging/Cokriging插值方法计算了中国大陆CRI的空间分布。模型评估与对比分析表明,MCM模拟值与实测值大致吻合,且总体高于WHM和MAM模拟值,MCM能对中国大陆CRI进行较高分辨率、较高精度的模拟。模拟结果显示,中国大陆CRI的范围为141~12123 Bq/m²,在东北及新疆局部地区达到最大值,最小值主要集中于25°N以南地带。除新疆局部地区外,中国大陆CRI分布整体呈现自西向东,同纬度地区随降水量增加而增加的特点,而纬向上主要呈现随纬度增加而增加的特点。此外,大尺度大气流场、再悬浮过程、局部核试验等因素增加了中国大陆CRI分布的不均匀性。     

基于GIS的冰川中流线自动提取方法设计与实现

冰川长度是冰川编目的重要组成部分, 在冰川变化研究中具有十分重要的作用. 基于冰川轮廓矢量数据和数字高程模型数据, 从冰川形态角度提出了针对单一盆地与单一出口、复式盆地与单一出口、冰帽三种类型冰川的中流线自动提取方案, 并在GIS软件支持下实现了冰川海拔最高点与最低点、冰川中流线的自动提取. 以乌鲁木齐河源1号冰川、喀纳斯冰川、古里雅冰帽和野牛沟冰帽为例, 分别提取了各条冰川的中流线, 结果表明SRTM和ASTER GDEM两类数字高程模型数据对冰川海拔最高点与最低点的位置判别影响较小; 对单一盆地与单一出口类型冰川中流线实现了自动化提取, 而对于复式盆地与单一出口冰川类型和冰帽类型, 在冰川中流线提取中仍需专家知识支撑. 与我国第一次冰川编目中的长度数据相比, 本方法提取的冰川长度数据更加合理, 对于补充与完善我国第二次冰川编目数据集具有一定的参考价值.     

彩红外航空像片应用于森林灾害调查的方法与结果分析

本文应用联邦德国的一个实例,介绍了大比例尺(1:5000)彩红外航空像片应用于森林灾害调查的程序和方法。总结了彩红外航空像片判读树种和林木受损害等级的标志;并分析了不同树种、年龄和海拔高度等因素对林木受损害程度的影响;最后提出了调查精度。结果表明:利用彩红外航空像片调查林木因大气污染、病虫害、自然灾害等因子影响而受损的程度的方法,可以为合理经营规划森林资源快速提供较精确的信息。     

Mathematical Geology in Perspective: Has Objective Hypothesis Testing Become Overlooked?

The meaning of the term Mathematical Geology was contentious at the founding meeting of IAMG in 1968 and has remained so ever since. In North American usage, it has primarily meant statistical applications in geology, and thus is an extension of inventory that has been traditional in geology. To the Leningrad school (originally led by A. B. Vistelius), it is the discipline of testing geological hypotheses mathematically. Although mathematical hypothesis testing has considerable potential for the earth sciences, unfortunately, by comparison with inventory-type studies, it has received very little attention. Reference is drawn to recent papers in which geological hypotheses have been tested mathematically.     

Ground-Based and Airborne Measurements of Nonmethane Hydrocarbons in BERLIOZ: Analysis and Selected Results

During the Berlin Ozone Experiment BERLIOZ in July–August 1998 quasi-continuous measurements ofC₂–C₁₂ nonmethane hydrocarbons (NMHCs) were carried out at 10 sites in and around the city of Berlin using on-line gas-chromatographic systems (GCs) with a temporal resolution of 20–120 minutes. Additional airborne NMHCmeasurements were made using canister sampling on three aircraft and an on-line GC system on a fourth aircraft. The ground based data are analyzed to characterize the different sites and to identify the influence of emissions from Berlin on its surroundings. Benzene mixing ratios at the 4 rural sites were rather low (<0.5 ppbv). Berlin (and the surrounding highway ring) was identified as the main source of anthropogenic NMHCs at Eichstädt and Blossin, whilst other sources were important at the furthermost site Menz. The median toluene/benzene concentration ratio in Berlin was 2.3 ppbv/ppbv, agreeing well with measurements in other German cities. As expected, the ratios at the background sites decreased with increasing distance to Berlin and were usually around one or below. On 20 and 21 July, the three northwesterly sites were situated downwind of Berlin and thus were influenced by its emissions. Considering the distance between the sites and the windspeed, the city plume was observed at reasonable time scales, showing decreasing toluene/benzene ratios of 2.3, 1.6 and 1.3 with increasing distance from Berlin. Isoprene was the only biogenic NMHC measured at BERLIOZ. It was themost abundant compound at the background sites on the hotter days, dominating the local NMHC reactivity with averaged contributions to the total OH loss rate of 51% and 70% at Pabstthum and Blossin, respectively. Emissionratios (relative to CO and to the sum of analysed NMHCs) were derived from airborne measurements. The comparison with an emission inventory suggests traffic-related emissions to be the predominating source of the considered hydrocarbon species. Problems were identified with the emission inventory for propane, ethene and pentanes.