Mapping the Brazilian Amazon fluvial sensitivity index to oil spills with Shuttle Radar Topography Mission (SRTM) data

It is important to understand the Solimões River seasonal hydrological cycle and its dynamics to support systematic environmental monitoring efforts in the Amazon region. These are essential to the contingency response to possible accidents in the existing oil transportation network. This study seeks to map the environmental sensitivity to oil spills in the surroundings of Coari city, Amazonas State (AM). A computational method was employed representing the seasonal inundation phenomenon fluctuations, together with data from the Digital Elevation Model generated by the Shuttle Radar Topography Mission. These were matched with Coari fluviometric time series information and a Japanese Earth Resources Satellite-1 (JERS-1 SAR) geo-referenced mosaic of the Global Rain Forest Mapping Project. In this context, a mathematical morphology technique (watershed) integrated with all aforementioned data applying MatLab and ArcGIS computing resources generated results that enabled a better spatio-temporal understanding of the Amazon seasonal dynamics. Thus, the principal product of the research was the Coari fluvial oil spill sensitivity index map based on segmented inundation levels obtained with the proposed methodology.     

Assessment of Shuttle Radar Topography Mission Elevation Data Based on Topographic Maps in Turkey

Depending on scale, topographic maps depicting the shape of the land surfaces of the Earth are produced from different data sources. National topographic maps at a scale of 1:25 000 (25K maps) produced by General Command of Mapping are used as the base map set in Turkey. This map set, which consists of approximately 5500 sheets, covers the whole country and is produced using photogrammetric methods. Digital Elevation Models (DEMs) created from these maps are also available. Recently, another data source, Synthetic Aperture Radar (SAR) interferometric data, has become more important than those produced by conventional methods. The Shuttle Radar Topography Mission (SRTM) contains elevation data with 3 arc-second resolution and 16 m absolute height error (90 percent confidence level). These data are freely available via the Internet for approximately 80 percent of the Earth's land mass. In this study, SRTM DEM was compared with DEM derived from 25K topographic maps for different parts of Turkey. The study areas, each covering four neighboring 25K maps, and having an area of approximately 600 km², were chosen to represent various terrain characteristics. For the comparison, DEMs created from the 25K maps were obtained and organized as files for each map sheet in vector format, containing the digitized contour lines. From these data, DEMs in the resolution of 3 arc-second were created (25K-DEM), in the same structure as the SRTM DEM, allowing the 25K-DEMs and the SRTM DEM to be compared directly. The results show that the agreement of SRTM DEM to the 25K-DEM is within about 13 m, which is less than the SRTM's targeted error of 16 m. The spatial distribution of the height differences between SRTM-DEM and the 25K-DEM and correlation analysis show that the differences were mainly related to the topography of the test areas. In some areas, local height shifts were determined.     

Quantifying deforestation in the Brazilian Amazon using Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) and Shuttle Imaging Radar (SIR)-C data

The study examined the capability of dual-polarization SAR data for forest cover mapping and change assessment in the Brazilian Amazon Forest regions. Shuttle Imaging Radar (SIR)-C and Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data were analysed to map and quantify deforestation. The images were classified using hybrid classifier, where each land cover was grouped in various spectral sub-classes interpreted on the imagery and later merged together to generate the desired land cover classes. The classification accuracy for forest was reasonably high (>90%). The technique applied in this study can be extended for operational mapping and monitoring of deforestation in the tropics, particularly for those regions which are often covered by cloud.     

Cartographic Aspects of Land Cover Change Detection (Over- and Underestimation in the I&CORINE Land Cover 2000 Project)

Abstract

This paper presents the results of analysis of the data obtained by the method of computer-aided visual interpretation of satellite images used for identification of changes in land cover within the framework of the Image and CORINE Land Cover 2000 (I&CLC2000) Project (jointly managed by the European Environment Agency in Copenhagen, Denmark and the Joint Research Centre of the European Commission in Ispra, Italy). These data are also relevant in cartography. Land cover changes identified by the method mentioned may contain mistakes caused by over- or underestimation. The paper describes these mistakes. Overestimation (technical change) of the extent of land cover change is caused by adding the residual polygons (smaller than 25 ha) to neighbouring polygons. Underestimation is caused by the fact that discernible changes concerning areas larger than 5 ha which showed up in objects with areas smaller than 25 ha were not identified and, consequently, not included in either CLC90 or CLC2000 data layers; e.g. Dutch CLC_change database users' accuracy indicates an overestimation of 8.8% whereas the comparison of net change indicates a small, insignificant underestimation. In spite of the problems referred to, caused by overestimation or underestimation, the datasets on land cover changes in Europe for the 1990s and the year 2000 (± one year) can also be used for the compilation of land cover change maps at the regional, national and European levels.     

Impact of Topography on Accuracy of Land Cover Spectral Change Vector Analysis Using AWiFS in Western Himalaya

The present paper discusses the impact of topography on accuracy for land cover classification and “from-to class change using improved spectral change vector analysis suggested by Chen et al. (2003). Two AWiFS sensor images of different dates are used. Double Window Flexible Pace Search (DFPS) is used to estimate threshold of change magnitude for change/no change classes. The topographic corrections show accuracy of 90% (Kappa coefficient 0.7811) for change/no change area as compared to 82% (Kappa coefficient 0.6512) in uncorrected satellite data. Direction cosines of change vector for determining change direction in n-dimensional spectral space is used for image classification with a minimum distance categorizing technique. The results of change detection are compared (i) Improved CVA with conventional two bands CVA and (ii) Improved CVA before and after topographic corrections. The improved CVA with topographic correction consideration using slope match show maximum accuracy of 90% (Kappa coefficient 0.83) as compared to conventional CVA which show maximum accuracy of 82% (Kappa coefficient 0.6624). The overall accuracy of ”from- to class using improved CVA increases from 86% (Kappa coefficient 0.7817) to 90% (Kappa coefficient 0.83) after topographic corrections. The improved CVA with proper topographic corrections is found to be effective for change detection analysis in the rugged Western Himalayan terrain.     

Using Pattern‐oriented Modeling (POM) to Cope with Uncertainty in Multi‐scale Agent‐based Models of Land Change

Local land‐use and ‐cover changes (LUCCs) are the result of both the decisions and actions of individual land‐users, and the larger global and regional economic, political, cultural, and environmental contexts in which land‐use systems are embedded. However, the dearth of detailed empirical data and knowledge of the influences of global/regional forces on local land‐use decisions is a substantial challenge to formulating multi‐scale agent‐based models (ABMs) of land change. Pattern‐oriented modeling (POM) is a means to cope with such process and parameter uncertainty, and to design process‐based land change models despite a lack of detailed process knowledge or empirical data. POM was applied to a simplified agent‐based model of LUCC to design and test model relationships linking global market influence to agents’ land‐use decisions within an example test site. Results demonstrated that evaluating alternative model parameterizations based on their ability to simultaneously reproduce target patterns led to more realistic land‐use outcomes. This framework is promising as an agent‐based virtual laboratory to test hypotheses of how and under what conditions driving forces of land change differ from a generalized model representation depending on the particular land‐use system and location.     

都江堰震后土地利用/覆被变化信息提取方法研究

快速和精确评估"5·12"汶川地震后的土地利用/覆被变化对科学减灾、灾后重建及生态环境恢复具有重要意义。常规方法从遥感图像上提取土地利用/覆被变化信息时,多以研究区整体为处理对象,直接对全图像进行分类提取,容易忽略地形地貌和地质构造等背景因素对分类结果的影响。本文以都江堰为试验区,根据地质构造展布特征及地形地貌发育形态将其分成平原区(Ⅰ区)、低山区(Ⅱ区)、中高山区(Ⅲ区)和高山区(Ⅳ区)。对Ⅰ区采用ISODATA方法进行非监督分类;对Ⅱ区和Ⅲ区分别采用最大似然(ML)分类法进行监督分类;对Ⅳ区采用人机交互解译方法进行分类。试验结果表明,基于地理地质环境的分块分类方法是高效、精确的。     

三江源地区基于MODIS数据地表温度与土地覆盖定量关系研究

以三江源自然保护区为研究区,基于MODIS L1 B数据,采用劈窗算法反演地表温度,分析了地表温度空间分布的特征,与计算得到的归一化植被指数进行回归分析。结果表明地表温度与归一化植被指数存在很好的负相关性。分析讨论了地表温度的空间分布与土地覆盖及其他影响因子之间存在的定量关系,探讨了植被生产力与气候变化之间的相互作用以及发展趋势。研究结果有利于三江源湿地的生态保护,可为土地覆盖的动态监测提供有力的科学参考。     

The Influence of Digital Surface Model Choice on Visibility‐based Mobile Geospatial Applications

In this work we investigate the effectiveness of different types of visibility models for use within location‐based services. This article outlines the methodology and results for our experiments, which were designed to understand the accuracy and effects of model choices for mobile visibility querying. Harnessing a novel mobile media consumption and authoring application called Zapp, the levels of accuracy of various digital surface representations used by a line of sight visibility algorithm are extensively examined by statistically assessing randomly sampled viewing sites across the 1 km² study area, in relation to points of interest (POI) across the University of Nottingham campus. Testing was carried out on three different surface models derived from 0.5 m LiDAR data by visiting physical sites on each surface model with 14 random point of interest masks being viewed from between 10 and 16 different locations, totalling 190 data points. Each site was ground‐truthed by determining whether a given POI could be seen by the user and could also be identified by the mobile device. Our experiments in a semi‐urban area show that choice of surface model has important implications for mobile applications that utilize visibility in geospatial query operations.     

Integrating Remote Sensing Techniques,Geographical Information Systems (GIS), and Stochastic Models for Monitoring Land Use and Land Cover (LULC) Changes in the Northern Coastal Region of Nayarit,Mexico

Land use and land cover (LULC) changes in northern Nayarit, Mexico were estimated using post-classification change detection methods and a Markov chain model. Three thematic maps were generated by classifying Landsat images from 1973, 1900, and 2000, which were then overlaid to generate three change-detection matrices to assess the intensity and direction of changes. Between 25% and 30% of the region displayed LULC changes, attributable to a stochastic behavior that can be modeled with a first-order Markov chain. The steady-state distribution estimates indicate that the LULC patterns in the region have not yet reached equilibrium and predict the expansion of the agricultural boundaries.     

关于图解(航测)法在浙江省土地确权中精度影响因素的探讨

开展土地确权登记是贯彻党的"十八大"精神,开展不动产登记的重要内容,是中央的重大决策部署。农业部经过多年试点颁发了土地确权标准,是基于全国统盘考虑的。浙江省人多地少,且地块面积小,大多数分布在丘陵山区地带,通过图解法能否满足土地土地确权标准要求,笔者通过对某地区的试验,得出结论与体会,以飨读者。     

The network K‐function in context: examining the effects of network structure on the network K‐function

The flaws of using traditional planar point‐pattern analysis techniques with network constrained points have been thoroughly explored in the literature. Because of this, new network‐based measures have been introduced for their planar analogues, including the network based K‐function. These new measures involve the calculation of network distances between point events rather than traditional Euclidean distances. Some have suggested that the underlying structure of a network, such as whether it includes directional constraints or speed limits, may be considered when applying these methods. How different network structures might affect the results of the network spatial statistics is not well understood. This article examines the results of network K‐functions when taking into consideration network distances for three different types of networks: the original road network, topologically correct networks, and directionally constrained networks. For this aim, four scenarios using road networks from Tampa, Florida and New York City, New York were used to test how network constraints affected the network K‐function. Depending on which network is under consideration, the underlying network structure could impact the interpretation. In particular, directional constraints showed reduced clustering across the different scenarios. Caution should be used when selecting the road network, and constraints, for a network K‐function analysis.     

The Contribution of the Cartographic Visualisation in Understanding the Historical Geography of an Old Land Property Regime in Mouth Athos (Karyes)

Abstract

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The peninsula of Mount Athos is the largest monastic gathering of Modern Orthodoxy in the world, operating continually under the same regime since 883 AD. Focusing on Mount Athos, this paper attempts to examine the spatial regime continuation and identify the relation to what is considered to be a small residential unit around a central church (Protatos) within the limits of the Athos peninsula. The paper investigates the delimitation of the area, mapping and recording the relevant changes cartographically. At the same time, the paper creates a cadastral plan of the present regime, recording real estate owners in a cadastral table. Finally, the paper focuses on the significance of the findings to the historical geography of Athos, as well as the emergence of a new ‘area’, added to the twenty monasteries of the peninsula after 1450.     

基于新陈代谢的PGM(1,1)模型在建筑物变形监测中的应用

针对目前灰色理论模型在变形监测中的应用,本文分析了PGM(1,1)模型中的参数及其求解的方法;对于建模时前期观测值对后期预测值的影响,引入新陈代谢理论,通过整体最小二乘求解得到模型的背景值。结合高层建筑物沉降监测的实例进行计算分析,结果表明,基于新陈代谢的PGM(1,1)模型相比于传统的GM(1,1)模型,在建筑物沉降预测方面具有较好的效果。     

地理信息系统(GIS)在新发H7N9禽流感防控中的应用

通过对H7N9禽流感防控研究的归纳,总结了目前GIS技术在新发H7N9禽流感疫情的时空分布、流行规律、影响因素和风险评估等方面的应用研究,揭示了GIS技术在疫情防控中发挥的重要作用,为其他传染病特别是新发传染病的防控研究提供了借鉴。     

一种改进灰色预测模型在变形预测中的应用

针对传统的单一模型和非线性GM(1,1)-AR组合模型无法实现对非平稳、含噪时间序列信号进行优化处理的问题,该文提出了一种新的基于小波的GM(1,1)-AR模型预测算法。采用小波变换原理对监测数据进行消噪处理和不同频带的分离,有效地获取了实际变形量;利用GM(1,1)模型和AR时序分析模型对具有确定性的趋势项和不确定性的随机项进行建模组合,较好地综合了灰色模型拟合功能强大和时间序列善于处理细节信息两者优势。通过工程实例对比分析结果表明:基于小波的GM(1,1)-AR模型不仅有效剔除了多余噪声,还利用各种模型有机嵌套组合实现优势互补,新算法预测结果比各单一模型、非线性GM(1,1)-AR模型结果更为精确。     

The landscape-unit approach applied to geology, on SPOT images, in temperate climate zones using a test-area in the Cévennes (Massif Central, France)

Classification image processing is based mainly upon spectral features but this information alone is inadequate for drawing comprehensive maps or reliably distinguishing lithological or structural targets, especially in vegetation-covered areas. It is therefore of interest to explore an approach in which subtle features of the image are matched with field data in a variety of parameters either measured or assessed qualitatively. This approach is necessarily multidisciplinary, the three basic aspects being geomorphological, botanical and geological.The Cévennes massif, in southern France, with its sedimentary margins was selected as a test area, having both varied geology, giving a variety of landscapes, and a range of climatic zones, from Mediterranean to sub-Alpine.The present work is distinguished by its use of the landscape unit, which is rarely considered in geology. Landscapes units are recognized and defined, and the spectral homogeneity of the units is then assessed. They are combined with satellite and other data in order to improve the digital processing for geological purposes.The parameters characterising each landscape unit define the various elements contributing to the landscape, the most important of which are morphology, vegetation and geology, and their interactions. Our results using these parameters show the interest of the management of both the satellite (SPOT in this case) and non-satellite (exogenous) data.     

基于移动定位(LBS)技术的GPS-PDA在地下电力管线抢修中的应用

地下电力管线是电力系统的重要组成部分,具有一定的隐蔽性。在其发生故障时,如何快速准确地找到故障电缆和故障点关系到人们的正常生活。本文对现行抢修机制进行分析,在此基础上提出了一种新的基于移动定位技术的抢修机制,并结合实际详细介绍该办法的应用。     

训练样本对TM尺度小麦种植面积测量精度影响研究（Ⅰ）——训练样本与分类方法间分类精度响应关系研究

准确的遥感农作物类型识别和种植面积统计,不仅仅取决于不同分类方法的选择,同时还要看输入分类器用以学习的训练样本数据,训练样本对分类精度的影响比分类技术本身对测量精度的影响还要大。训练样本对测量精度的影响包含样本的质量和数量两个方面。为了探讨训练样本对农作物种植面积测量精度的影响,本文以小麦为例,选择典型试验区,利用较常用的TM遥感影像,结合高分辨率SPOT数据和野外GPS数据,在构建标准训练样本和检验样本数据集的基础上,在不同训练样本量下,分别对光谱角制图、平行六面体、马氏距离、最小距离、最大似然和支持向量机6种方法进行了多次试验,并对测量结果进行了对比分析。研究结果表明:①不同样本量下6种方法10次测量的结果存在不同程度的波动,而且地块越破碎的地区波动越大,但这种波动随样本量的增加会减少,说明目前在小麦面积测量中,用单次分类的结果作为最终的提取结果的做法存在一定的随机误差,在实际的工作中,应尽可能多的获取训练样本,以提高小麦面积测量的稳定性,同时利用多次测量结果求均值的方式,来消减或者抵消测量的随机误差;②相同样本量下,各种方法测量出的全区和破碎区的小麦像元个数(总量)不一致,种植结构复杂且破碎的地区,各种方法测量出的小麦面积总量差异会更大,说明不同方法对同一地区小麦的识别能力是不同的,同种方法对于不同地区小麦的识别能力也是不一样的,但是通过分析小麦识别的产品精度和用户精度,可以判断出哪个结果最接近于真实总量。