Topological approach to remote sensing

Summary. The topological problem underlying remote sensing is analysed by determining the geometric singularities that an unknown surface or structure generically impresses on a sensing wavefield. It is shown that the analytical singularities observed in scattering amplitudes and echograms are produced by the topological singularities of the scattering system. Imposing the principle of structural stability on the inverse scattering problem, the singularities that generically occur in recorded signals, travel-time curves, surface contour maps and Fresnel-zone topographies can, together with the associated high-intensity diffraction patterns, be classified into a few universal standard forms described by catastrophe polynomials. As the source-receiver positions vary, the patterns change their morphologies in terms of specific bifurcation sets. By applying singularity and bifurcation theory to allow the effects of caustics (both in ray and wave theory) to be incorporated into three-dimensional techniques for reconstructing surfaces and subsurface structures from their echoes, the interpretation process is considerably simplified and permits an on-site 3D survey. Universal power laws for singularity-dominated echo amplitude variations with the source frequency are deduced. The shape of a scattering surface is reconstructed using the high-frequency regime alone. Discontinuities in the surface, edges and faults, are discussed in terms of constraint catastrophes and the patterns they produce in echograms are classified.     

Knowledge diffusion from GIScience to other fields: the example of the usage of weighted surface networks in nanotechnology

This article demonstrates how the generalisation of topographic surfaces has been formalised by means of graph theory and how this formalised approach has been integrated into an ISO standard that is employed within nanotechnology. By applying concepts from higher-dimensional calculus and topology, it is shown that Morse functions are those mappings that are ideally suited for the formal characterisation of topographic surfaces. Based on this result, a data structure termed weighted surface network is defined that may be applied for both the characterisation and the generalisation of the topological structure of a topographic surface. Hereafter, the focus is laid on specific issues of the standard ISO 25178-2; within this standard change trees, a data structure similar to weighted surface networks, are applied to portray the topological information of topographic surfaces. Furthermore, an approach termed Wolf pruning is used to simplify the change tree, with this pruning method being equivalent to the graph-theoretic contractions by which weighted surface networks can be simplified. Finally, some practical applications of the standard ISO 25178-2 within nanotechnology are discussed.     

1960 年以来青藏高原气温变化研究进展

青藏高原是中国最大、世界海拔最高的高原,它对全球气候系统存在显著影响.本文对青藏高原自1960年以来的气温变化特征及其影响因素的研究进行了概述与总结.近50 年来,青藏高原气温明显上升,经历了一个冷期和一个暖期,气温在20 世纪80 年代发生突变,整体呈现前低后高波动上升的趋势;最低气温和最高气温呈不对称的线性增温趋势,最低气温的上升速率要比最高气温快得多;而极端事件频率、强度也有所变化,其中低温事件大大减少,高温事件则明显增加;各类界限温度的积温以及持续日数等生物温度指标也都显著增加.在空间分布上,青藏高原气温呈现出整体一致增暖,并且有西高东低、南北反相的变化形态.影响青藏高原气温变化的因素有很多,主要包括天文因素、高原内部气象要素以及外部环流影响等.     

深圳市不透水表面的遥感监测与时空格局

定量监测城市不透水表面扩展过程,是分析城市景观格局动态,深入剖析城市地区空间镶嵌体内部异质性景观相互转化的重要基础。以深圳市为例,通过定量划分城市不透水表面等级体系,计算不透水表面的转移矩阵与景观格局指数,分析不透水表面的时空动态,结果表明:1990～2005年间,高盖度及极高盖度的不透水表面持续增加,中盖度及低盖度不透水表面先增加后减少,而自然地表及极低盖度的不透水表面则为先减少后恢复,反映了城市化进程对城市地表覆被的结构性影响。景观格局变化显示景观多样性程度较高,且经历了低-高-低-高的变化;斑块在1990年以自然地表为主,1995年以后以中盖度等级为主,高盖度等级显著增加。自然地表和中等盖度的不透水表面变化分别主导着前期和中后期的变化过程。城市建设的迅速扩张,将林地、农田、水体及滩涂等自然地表快速地转变为不同功能的建设用地,主导着不透水表面等级分布的梯度性变化。     

Interaction between scale and scheduling choices in simulations of spatial agents

Spatial simulations are a valuable tool in understanding dynamic spatial processes. In developing these simulations, it is often required to make decisions about how to represent features in the environment and how events unfold in time. These spatial and temporal choices have been shown to significantly alter model outcomes, yet their interaction is less well understood. In this paper, we make use of a simple group foraging model and systematically vary how features are represented (cell size of the landscape) as well as how events unfold in time (order in which foragers take action) to better understand their interaction. Our results show similar nonlinear responses to changes in spatial representation found in the literature, and an effect of the order in which agents were processed. There was also a clear interaction between how features are represented and how events unfold in time, where, under certain environmental representations results were found to be more sensitive to the order in which individuals were processed. Furthermore, the effects of feature representation, scheduling of agents, and their interaction were all found to be influenced by the heterogeneity of the spatial surface (food), suggesting that the statistical properties of the underlying spatial variable will additionally play a role. We suggest that navigating these interactions can be facilitated through a better understanding of how these choices affect the decision landscape(s) on which agents operate. Specifically, how changes to representation affect aggregation and resolution of the decision surface, and thereby the degree to which agents interact directly or indirectly. We suggest that the challenges of dealing with spatial representation, scheduling, and their interaction, while building models could also present an opportunity. As explicitly including alternate representations and scheduling choices during model selection can aid in identifying optimal agent–environment representations. Potentially leading to improved insights into the relationships between spatial processes and the environments in which they occur.     

气候变化背景下陕西冷暖冬事件的多尺度特征研究

基于陕西省1960—2019年94个气象站点冬季逐日气温资料,分陕北、关中和陕南3个气候区,从时间和空间2种尺度分析了陕西冷、暖冬事件的变化特征.结果 表明:近60 a陕西冬季增温明显并在1987年前后发生突变,冬季平均0℃等温线北抬1～2个纬度,增温幅度以陕北最强陕南最弱.从时间尺度上,气候变化导致暖冬指数以9.5％...     

气候变率影响下博茨瓦纳河流流量的时空变化

The fourth assessment report of the IPCC highlights that the global average surface temperature is projected to increase by 1.8 to 4.0℃ by the year 2100 compared to current climate. Given that climate is the most important driver of the hydrological cycle, the rise in temperature could cause changes in occurrence patterns of extreme hydrologic events like streamflow droughts. An increase in frequency and severity of these events could pose seri-ous challenges for sustainable management of water resources particular in arid regions. However, the understanding of water resources dynamics and the possible impacts of climate change on these dynamics is hindered by uncertainties in climate change models and com-plex hydrological responses of streams and catchments to climatic changes. Therefore ob-servational evidence of streamflow dynamics at the local scale could play a crucial role in addressing these uncertainties and achieving a fuller reconciliation between model-based scenarios and ground truth. This paper determines spatial and temporal changes in stream-flow volumes and their association with climatic factors based on the non-parametric Mann-Kendall test and ANOVA to determine possible changes in streamflow over the years and their relation to climatic factors. Streamflow is generally stochastic highlighting the im-portance of factoring in temporal flow variability in water resources planning. There is no clear evidence that changes in climatic variables are related to streamflow behaviour.     

基于无人机摄影测量的地形变化检测方法与小流域输沙模型研究

流域输沙过程是地貌学和地表动力学的重要研究内容,但传统的输沙过程监测方法仅能得到某个区域的总输沙率,无法推算其空间分布。论文以黄土高原绥德县窑家湾小流域为例,利用无人机摄影测量技术得到其2006年和2019年2期数字高程模型(DEM)并计算地形变化量;然后,根据质量守恒原理和多流向算法建立泥沙在空间上的输送模型,进而计算小流域输沙率的空间分布。实验结果表明,该模型能有效模拟泥沙在空间上的输送情况,输沙率出现质量不守恒的区域面积占比小于4%,且不守恒区域多为人类活动影响区。同时,论文讨论了DEM的选择和不同地形变化检测水平对模型结果的影响。当使用第一期DEM进行泥沙搬运路径推算时,质量不守恒区域的面积显著降低。使用误差空间分布图进行地形变化检测得到的输沙率结果鲁棒性更强。使用中误差进行地形检测得到的结果在不同置信度下变化较大。基于无人机地形变化检测的空间输沙模型能方便、快捷地提供详尽的输沙率空间分布,为地表过程研究带来了新的机遇。     

近58 a新疆巴州极端气温事件变化特征

选取 WMO 推荐的 15 个极端气温指数,对 1959—2016 年新疆巴州地区 7 个气象站点观测的日最高、最低气温数据,采用一元线性回归法等多种统计方法对研究区极端气温事件进行分析。结果表明：近 58 a来新疆巴州地区冷暖指数变化呈非对称性,暖指数呈不同程度的显著上升,冷指数总体呈显著下降趋势,其中 TN90P 年际变化率最大,为 4.67 d·（10 a）^-1。夜指数（TN10P、TN90P）和昼指数（TX10P、TX90P）变化率前者大于后者。冷指数在 20 世纪 80 和 90 年代中后期发生突变,暖指数和GSL、WSDI突变时间一致为 90 年代中后期,冷指数对气候变化较敏感。发生频率：极端高温增加,极端低温降低;强度：增强;持续时间：作物生长期呈显著增加趋势,其中巴音布鲁克增加显著,幅度最大〔4.4 d·（10 a）^-1〕。TNx、TXx和GSL主周期均为 28 a。高载荷指数：TEM-A（0.335）,TN10P（-0.313）和TN90P（0.312）,是影响该地区整体气温发生变化的主要因素。     

An inconsistency measure of spatial data sets with respect to topological constraints

An inconsistency measure can be used to compare the quality of different data sets and to quantify the cost of data cleaning. In traditional relational databases, inconsistency is defined in terms of constraints that use comparison operators between attributes. Inconsistency measures for traditional databases cannot be applied to spatial data sets because spatial objects are complex and the constraints are typically defined using spatial relations. This paper proposes an inconsistency measure to evaluate how dirty a spatial data set is with respect to a set of integrity constraints that define the topological relations that should hold between objects in the data set. The paper starts by reviewing different approaches to quantify the degree of inconsistency and showing that they are not suitable for the problem. Then, the inconsistency measure of a data set is defined in terms of the degree in which each spatial object in the data set violates topological constraints, and the possible representations of spatial objects are points, curves, and surfaces. Finally, an experimental evaluation demonstrates the applicability of the proposed inconsistency measure and compares it with previously existing approaches.     

Efficiently implementable algebra for distributed in-network spatial analysis

Existing sensor network query processors (SNQPs) have demonstrated that in-network processing is an effective and efficient means of interacting with wireless sensor networks (WSNs) for data collection tasks. Inspired by these findings, this article investigates the question as to whether spatial analysis over WSNs can be built upon established distributed query processing techniques, but, here, emphasis is on the spatial aspects of sensed data, which are not adequately addressed in the existing SNQPs. By spatial analysis, we mean the ability to detect topological relationships between spatially referenced entities (e.g. whether mist intersects a vineyard or is disjoint from it) and to derive representations grounded on such relationships (e.g. the geometrical extent of that part of a vineyard that is covered by mist). To support the efficient representation, querying and manipulation of spatial data, we use an algebraic approach. We revisit a previously proposed centralized spatial algebra comprising a set of spatial data types and a comprehensive collection of operations. We have redefined and re-conceptualized the algebra for distributed evaluation and shown that it can be efficiently implemented for in-network execution. This article provides rigorous, formal definitions of the spatial data types, points, lines and regions, together with spatial-valued and topological operations over them. The article shows how the algebra can be used to characterize complex and expressive topological relationships between spatial entities and spatial phenomena that, due to their dynamic, evolving nature, cannot be represented a priori.     

NDVI changes in China between 1989 and 1999 using change vector analysis based on time series data

1 Introduction The land surface has considerable control on the planet抯 energy balance, biogeochemical cycles and hydrologic cycle, which in turn significantly influences the climate system. Therefore, the global environmental change community has paid great attention to the land use/cover change (LUCC). Many researchers have focused on the land cover classification and change by using remotely sensed data. Changes in land-cover are driven by four categories of causes[1]: (1) long-term nat…     

NDVI changes in China between 1989 and 1999 using change vector analysis based on time series data

Change vector analysis (CVA) and principal component analysis in NDVI time-trajectories space are powerful tools to analyze land-cover change. The magnitude of the change vector indicates amplitude of the change, while its direction indicates the nature of the change. CVA is applied to two remotely sensed indicators of land surface conditions, NDVI and spatial structure, in order to improve the capability to detect and categorize land-cover change. The magnitude and type of changes are calculated in China from 1989 to 1999. Through the research, the main conclusions are drawn as follows: 1) The changes of NDVI are quite different between eastern China and western China, and the change range in the east is bigger than that in the west. The trend in NDVI time series is smoothly increasing, the increases happen mostly in Taiwan, Fujian, Sichuan and Henan provinces and the decreases occur in Yunnan and Xinjiang. 2) The spatial structure index can indicate changes in the seasonal ecosystem dynamics for spatially heterogeneous landscapes. Most of spatial structure changes, which occurred in southern China, correlated with vegetation growth processes and strike of mountains.     

Monitoring qualitative spatiotemporal change for geosensor networks

Recent technological advances in geosensor networks demand new models of distributed computation with dynamic spatial information. This paper presents a computational model of spatial change in dynamic regions (such as may be derived from discretizations of continuous fields) founded on embeddings of graphs in orientable surfaces. Continuous change, connectedness and regularity of dynamic regions are defined and local transition rules are used to constrain region evolution and enable more efficient inference of a region's state. The model provides a framework for the detection of global high‐level events based on local low‐level ‘snapshot’ spatiotemporal data. The approach has particular relevance to environmental monitoring with geosensor networks, where technological constraints make the detection of global behaviour from local conditions highly advantageous.     

不同城市化阶段景观演变的热环境效应动态——以深圳西部地区为例

热环境效应是城市化过程中景观格局演变对区域生态环境影响研究的重要内容之一。通过热环境效应动态研究有助于理解景观对区域生态环境效应的影响在不同阶段的规律特性。本文利用深圳市1987年、1995年和2005年3期Landsat TM影像,通过构建热环境效应变化指数描述不同城市化阶段热环境效应的发展特征,并通过景观分布指数表征景观演变对其的影响作用。结果表明热环境效应的空间特征在城市化进程中由聚集型逐渐转变为零散与破碎分布;在快速城市化阶段,景观演变对热环境效应动态的影响主要体现为热中心的扩展,同时自然景观对热环境效应的缓解作用有所减弱;城市化稳定阶段,景观变化的热环境效应由空间的扩张转为强度的提高。     

青藏高原东北缘马衔山夷平面特征指标的提取与分析

夷平面研究在地貌演化和新构造运动,特别是青藏高原隆升过程研究中占有极其重要的地位,准确界定夷平面分布范围是开展夷平面定量--半定量研究的重要基础.截至目前,前人已利用计算机图像处理技术和目视解译等方法开展了相关工作,并取得重要研究进展.然而,以往利用坡度高程指标提取夷平面时存在一定的随意性和主观性.青藏高原内部及其周边地区发育系列夷平面,其中高原东北缘马衔山地区较好的保存了两级夷平面.被夷平的地层为前寒武系马衔山群混合岩,山顶面上发育冰缘地貌,主夷平面波状起伏,上有岛山和晚新生代沉积,局部覆盖有40 m左右红粘土和30 m以上更新世黄土,并在局地残留3 m以上风化壳,是开展夷平面研究的理想地区.为探讨如何确定提取夷平面的最佳坡度高程指标,本文基于夷平面的特殊地貌几何形态,利用均值变点分析法和最小误差法确定了提取夷平面的最佳高程和坡度指标,并据此对马衔山地区的两级夷平面的分布范围进行提取和统计分析.最后结合剖面线,坡向分布图和区域地质资料探讨了夷平面的构造变形特征.研究发现马衔山地区两级夷平面最佳坡度指标均为12°,山顶面和主夷平面高程主要分布在3470~3640 m和2670~2870 m;统计分析表明山顶面面积约为6.4 km²,平均高程为3559 m,主夷平面面积约为15.5 km²,平均高程为2771 m;而夷平面的变形特征主要受控于区域断层.     

基于ETM+与MODIS数据融合的伊洛河流域地表蒸散估算

MODIS数据时间分辨率较高,在对地能量和水分变化监测应用中具有不可比拟的优势。但其空间分辨率较低,混合象元效应显著,尤其在地表土地利用类型复杂和空间异质性较大时,会带来较大的误差。而ETM+数据具备较高的空间分辨率,但其单一的热红外波段导致反演的地表温度精度不高,且时间分辨率低,因而限制了在地表蒸散监测中的应用。本文探讨了将TM/ETM+与MODIS数据相融合估算区域地表蒸散的一种多尺度遥感方法,利用TM/ETM+计算得到的植被指数,基于空间增强方法将MODIS反演的地表温度尺度提高到30 m,并结合SEBS模型对伊洛河流域的地表蒸散进行了估算。验证与分析的结果表明,估算精度得到提高,研究区当日蒸散量在0～5.32 mm/d之间,空间分布具有明显的地域性差异,区域分布不均衡。     

数字拓扑研究现状及其在GIS中的应用

数字拓扑主要研究栅格空间中离散几何对象的拓扑性质,这些性质在GIS空间分析和栅格数据处理中非常重要。该文从图论、混合拓扑和公理型3方面对数字拓扑的研究现状进行了分类和综述,并讨论数字拓扑在GIS领域的应用,指出三维数字拓扑和球面数字拓扑是数字拓扑在GIS中的两个发展趋势和研究热点。     

Third-order geomorphometric variables (derivatives): definition,computation and utilization of changes of curvatures

Third-order geomorphometric variables (based on third derivatives of the altitudinal field) have been neglected in geomorphometry, but their application to the delimitation of surface objects will lead to their increasing significance in future. New techniques of computation, presented and evaluated here, facilitate their use. This paper summarizes recent knowledge concerning definition, computation and geomorphologic interpretation of these variables. Formulae defining various third-order variables are unified based on the physical definition of slope gradient. Methods for their computation are compared from the point of view of method error and error generated by digital elevation model (DEM) inaccuracy. For exact mathematical test surfaces, the most natural and simple variant of the method of central differences (CD2) shows a method error 2–3 times smaller than the other methods used recently in geomorphometry. However, success in coping with DEM inaccuracy depends (for a given grid mesh) on the number and weighting of points from which the derivative is computed. This was tested for surfaces with varying degrees of random error. Here least squares-based methods are the most effective for mixed derivatives (especially for finer grids and less accurate DEMs), while a variant of the CD method, that repeats numerical evaluation of first derivatives (CD1), is the most successful for derivatives in cardinal directions. The CD2 method is generally the most successful for coarser grids where the method error is dominant.

Utilization of third-order variables is documented from examples of terrain feature (ridge, valley and edge) extraction and from a first statistical test of the hypothesis that real segments of the land surface have a tendency to a constant value of some morphometric variable. For detection of (sharp) ridges and valleys, it is shown that the rate of change of tangential curvature is inadequate: rate of change of normal curvature is also required. A basic confirmation of the constant-value tendency is provided.