结合地形因子与分层策略的喀斯特地区无人机影像分类

西南喀斯特山区地形起伏较大,地物分布较为破碎,致使传统的光谱特征一次分类方法的精度较低。本文基于高分辨率无人机正射影像和地形指标,充分利用无人机遥感影像空间特征、光谱特征、纹理特征及地形特征,采取面向对象CART决策树算法与分层策略提取了研究区土地覆盖类型。研究表明,结合空间地形因子和分层策略的方法减少了破碎区地物间的相干扰,故具有较高的分类精度,总体分类精度达91.2%,Kappa系数为0.87,较传统一次分类精度提高了9.8%,Kappa系数提高了0.13。该方法对西南喀斯特地区土地覆盖解译精度较好,可为土地利用监测提供参考。     

TGP二维与三维地质预报成果对比

以TGP超前地质预报理论和实际工程资料为基础,运用信息化逻辑方法对TGP二维与三维地质预报成果进行分析对比,主要从预报地质构造的位置、规模、围岩级别和产状四个成果比较二者的相同和不同之处。结果表明,对于隧道前方岩性无明显差异的围岩,二维与三维的地质预报结果基本相同;对于与隧道斜交的地质构造,二维与三维地质预报在构造产状预报结果上相近,但二维地质预报在围岩级别预测方面有利,三维地质预报在规模和位置的预报方面有利;对于与隧道激发炮孔连线一侧边墙不相交的地质构造,二维与三维地质预报结果基本不同,且三维比二维的地质预报结果有利。     

学科树视角下地理学和建筑学人居环境研究比较

本文从学科树视角比较分析地理学和建筑学的人居环境研究进展。首先,梳理研究脉络,指出两个学科具有相同的“树根”（即五大系统和五大层次）、“树干”（即九大主题和八大尺度）和“树枝”（即33个研究领域）,以及相异的“树叶”（即各领域数量迥异的研究成果）。其次,比较研究成果特点,发现两个学科成果差异明显,表现为在适宜性等6个二级主题上,地理学成果较多,建筑学成果较少;在规划等6个二级主题和建筑尺度上,建筑学成果较多,地理学成果较少;在空间格局等12个二级主题和城市等6个尺度上,两个学科成果均较多,但侧重点不同;在行为二级主题和全球尺度上,两个学科成果均较少,但侧重点不同。最后,剖析学科成果差异的生成逻辑,并展望未来进路。学科成果差异的逻辑起点是学科门类差异,逻辑链条是“学科门类—学科特性—研究主体—研究偏好—研究范式—研究成果”的差异传导机制,其中研究范式差异是链条中的重要环节。未来人居环境研究应促进框架延伸化、主题展拓化、尺度统筹化、数据多源化、方法混合化等范式提升,同时回应全球化、美好人居、突发事件、跨学科等现实需求。     

人类关键区的科学逻辑与研究趋势

人类关键区是人类社会进入人类世时代,人类所创造的地表景观在地理圈层中的特征区域。人类近万年历史对人地关系的认知可分为人类文明与地球环境、人类活动与地理环境、空间行为与土地利用3个层级。人类关键区具有全球尺度、国家尺度、区域尺度、地方尺度以及社区尺度。全球尺度的人类关键区可划分为建成区、农业区、生态区、裸露区。人类关键区未来的研究主要包括人类关键区的识别,人类关键区物质循环与能量流动,人类关键区耦合机理与动力机制,人类关键区地理模拟（器）与调控决策。人类关键区的提出为全球可持续发展提供中国地理科学的创新理论与实践路径。     

基于LiDAR点云数据的树冠空隙度指数分析

分形维数法是分析空间结构分布的一种典型方法,但它对于区分不同的分布形式还存在缺陷。针对这一问题,该文介绍了空隙度指数的定义和树冠空隙度的计算方法;以模拟的树冠点云数据为对象,提出了一种基于三维凸包和三维滑动盒算法的激光雷达(Li DAR)点云数据空隙度分析方法,详尽分析了不同冠型产生的空隙度指数差异;并利用4棵实测的树冠点云数据做检验;最后阐述了空隙度指数在树冠空间异质性分析研究中的作用,并对其应用范围和前景作了展望。结果表明:划分尺度相同时,在一定的尺度范围内,锥型树冠、半球型和半椭球型树冠的差别可以通过空隙度指数曲线有效地区分,实测树冠的结果也体现了空隙度指数对于判断树冠空间结构的有效性。     

分类器和时相结合的流域下垫面分类方法

文章探讨提高卫星遥感大范围流域下垫面分类方法:通过集合贝叶斯分类器和决策树分类器的优势,充分利用TM影像覆被信息,结合影像时相动态信息以获得分类准确的土地覆盖/利用类型;再结合DEM生成的坡度信息得到下垫面类型,最终确定水文地理单元.以河南省的东湾流域为例进行验证,结果表明:贝叶斯法和决策树法分类各有优势,两者结合可以获取更准确的土地覆盖/利用分类结果,辅以时相类信息可以进一步修正类别间的混淆.     

人工神经网络和决策树模型在滑坡易发性分析中的性能对比

机器学习模型广泛应用于区域性滑坡易发性分析。模型的选择关系到评价结果的可信度、准确率和稳定性。现有滑坡易发性分析模型对比研究侧重模型的预测精度。模型的稳定性和数据量敏感性对机器学习模型的性能评估同样非常重要。本文以福建省南平市蔡源流域为研究区,以四川省绵阳市北川县为验证区,从预测精度、稳定性和数据量敏感性3个方面深入对比BP（Back Propagation）人工神经网络模型和CART（Classification and Regression Tree）决策树模型在滑坡易发性分析中的效果,主要结论如下:① 在逐渐增加一定数量训练样本的过程中,BP人工神经网络模型预测精度的增长率更高。在蔡源流域内,当训练样本数量增加10 000时,BP人工神经网络模型的预测精度上升5.22%,CART决策树模型的预测精度上升2.11%。② BP人工神经网络的预测精度高于CART决策树模型,且较为稳定。在100组数据集上,BP人工神经网络模型验证集预测精度的均值和验证集滑坡样本预测精度的均值分别为81.60%和84.86%,高于CART决策树模型的72.97%和76.59%。与此同时,BP人工神经网络模型对应预测精度的标准差分别是0.32%和0.37%,小于CART决策树模型的0.35%和0.67%。③ BP人工神经网络模型分析的滑坡易发区相比CART决策树模型,更接近实际滑坡的空间分布。最后,北川县的验证实验也出现了相同的现象。     

Glacial forest refugium in Howard Valley,South Island,New Zealand

Fossils of forest habitat beetles and leaves of Nothofagus menziesii provide evidence of a forest refugium at times between ca. 34 000 and ca. 18 500 cal. a BP at an upland site in Howard Valley, located adjacent to glaciated valleys in South Island, New Zealand. The stratigraphy of the glacial‐aged terrace sequence of organic‐rich silts and fluvial sand/gravels indicates that soil development occurred episodically for around 15 000 a. Fifty‐four beetle taxa represent seven habitat types: forest, forest or scrub, riparian and aquatic, litter, grass/tussock, marshland and moss habitats. Leaf and beetle fossils indicate that forest dominated by N. menziesii persisted at the site for most of the time period represented, and tree line taxa such as Taenarthrus sp. 1 (Carabidae) and Podocarpus sp. (Podocarpaceae) indicate that the site may represent the upper tree limit for full‐glacial time. The finding of forest at this elevated site adds to the growing fossil evidence for multiple forest refugia in New Zealand during the last glaciation and is consistent with the pollen records, which have consistently indicated the presence of forest species during the last glaciations. Copyright © 2009 John Wiley & Sons, Ltd.     

Central England temperature since AD 1850: the potential of stable carbon isotopes in British oak trees to reconstruct past summer temperatures

In regions with seasonal temperate climatic regimes, tree growth is rarely controlled by any single environmental factor. As a consequence, the development of robust palaeoclimate reconstructions has proved challenging. Tree‐ring stable carbon isotope ratios (δ¹³C), however, are controlled primarily by photosynthetic rate, not by net growth. Therefore, at sites where climatic controls on tree‐ring growth are not strongly expressed, a robust (isotopic) palaeoclimate signal may still potentially be preserved. This hypothesis was tested using a 160‐year record of δ¹³C measured from the pooled latewood cellulose of six Quercus petraea L. (sessile oak) trees from Allt Lan‐las in West Wales, UK. Raw δ¹³C values were corrected for changes in the isotopic ratio of atmospheric carbon dioxide and for changes in the behaviour of trees due to the increasing availability of atmospheric CO₂ since AD 1850. Strong correlations with local summer temperature and sunshine are reported, and also with the Central England Temperature record over the full length of the isotopic chronology (AD 1850–2010) (r = 0.69, P < 0.001). We conclude that tree‐ring stable isotopes can be used to extract strong palaeoclimate signals even from oak trees growing in a temperate maritime climate. This demonstrates the potential for extracting robust palaeoclimatic information from the very long and well‐replicated oak chronologies which have been developed in western and central Europe primarily for dating rather than palaeoclimatic research purposes. Copyright © 2012 John Wiley & Sons, Ltd.     

Fuzzy logic model approaches to daily pan evaporation estimation in western Turkey / Estimation de l’évaporation journalière du bac dans l’Ouest de la Turquie par des modèles à base de logique floue

Abstract

Abstract Evaporation is one of the fundamental elements in the hydrological cycle, which affects the yield of river basins, the capacity of reservoirs, the consumptive use of water by crops and the yield of underground supplies. In general, there are two approaches in the evaporation estimation, namely, direct and indirect. The indirect methods such as the Penman and Priestley-Taylor methods are based on meteorological variables, whereas the direct methods include the class A pan evaporation measurement as well as others such as class GGI-3000 pan and class U pan. The major difficulty in using a class A pan for the direct measurements arises because of the subsequent application of coefficients based on the measurements from a small tank to large bodies of open water. Such difficulties can be accommodated by fuzzy logic reasoning and models as alternative approaches to classical evaporation estimation formulations were applied to Lake Egirdir in the western part of Turkey. This study has three objectives: to develop fuzzy models for daily pan evaporation estimation from measured meteorological data, to compare the fuzzy models with the widely-used Penman method, and finally to evaluate the potential of fuzzy models in such applications. Among the measured meteorological variables used to implement the models of daily pan evaporation prediction are the daily observations of air and water temperatures, sunshine hours, solar radiation, air pressure, relative humidity and wind speed. Comparison of the classical and fuzzy logic models shows a better agreement between the fuzzy model estimations and measurements of daily pan evaporation than the Penman method.