基于GIS的城市土地利用分析与建模框架研究

本文针对城市土地利用数据的时空特性,依托地理信息系统(GIS)丰富的空间分析工具以及对海量空间数据的高性能计算优势,围绕城市土地利用研究有关数据的处理、分析、建模等方面问题设计了一个基于GIS的城市土地利用分析与建模框架;框架主体结构中有关城市土地利用变化的驱动力机制建模方法选取逻辑回归模型,对地理数据的空间自相关性处理则根据Getis自相关系数构建滤波模型;具体应用则结合深圳市国土资源局的"城市土地利用虚拟政策实验室"项目,取得良好效果     

Modeling land use decisions with Bayesian networks: Spatially explicit analysis of driving forces on land use change

Land use decisions result from complex deliberative processes and fundamentally influence the livelihoods of many. These decisions are made based on quantitatively measurable information like topography and on qualitative criteria such as personal preferences. Bayesian networks (BN) are able to integrate both quantitative and qualitative data and are thus suitable to approach such processes. We model land use decisions in a pre-Alpine area in Switzerland, integrating biophysical data and local actors' knowledge into a spatially explicit BN. A structured experts' process to elaborate three different BN including agriculture, forestry, and settlement provides the base for the modeling. A spatially explicit updating of the BN via questionnaires enables us to take local actors' characteristics into account. Results show which drivers are most important for land use decision-making in our case study region, and how an alteration of these drivers could change future land use. Furthermore, focusing on the probability of occurrence of various land uses in a spatially explicit manner gives insights into path-dependency of land use change. This knowledge can serve as information for planners and policy makers to design more effective policy instruments.     

Comparison of simulation models in terms of quantity and allocation of land change

Our article illustrates how to compare the outputs from models that simulate transitions among categories through time. We illustrate the concepts by comparing two land change models: Land Change Modeler and Cellular Automata Markov. We show how the modeling options influence the quantity and allocation of simulated transitions, and how to compare output maps from pairs of model runs with respect to a reference map of transitions during the validation interval. We recommend that the first step is to assess the quantity of each transition and to determine the cause of the variation in quantity among model runs. The second step is to assess the allocation of transitions and to determine the cause of the variation in allocation among model runs. The separation of quantity and allocation of the transitions is a helpful approach to communicate how models work and to describe pattern validation.     

基于空间信息多级网格的CA模型研究

具备时空计算特征的元胞自动机(CA)模型与GIS集成极大促进了GIS对地理过程的模拟能力。论文简要介绍了空间信息多级网格(SIMG)——一种既能适合网格计算环境又充分考虑到地球空间的自然特征和社会属性的差异性及经济发展不平衡的特点的空间信息表示新方法。充分研究了SIMG与CA之间的联系,分别讨论了在SIMG上CA元胞及状态的确定、元胞空间的确定、规则的定义、时间粒度确定等,提出了空间信息多级网格元胞自动机模型(SIMGCA),并提出了SIMGCA模型在土地利用/覆被变化中的应用框架。     

Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes

Global warming has obtained more and more attention because the global mean surface temperature has increased since the late 19th century. As more than 50% of the human population lives in cities, urbanization has become an important contributor for global warming. Pearl River Delta (PRD) in Guangdong Province, southern China, is one of the regions experiencing rapid urbanization that has resulted in remarkable Urban Heat Island (UHI) effect, which will be sure to influence the regional climate, environment, and socio-economic development. In this study, Landsat TM and ETM+ images from 1990 to 2000 in the PRD were selected to retrieve the brightness temperatures and land use/cover types. A new index, Normalized Difference Bareness Index (NDBaI), was proposed to extract bare land from the satellite images. Additionally, Shenzhen, which has experienced the fastest urbanization in Guangdong Province, was taken as an example to analyze the temperature distribution and changes within a large city as its size expanded in the past decade. Results show that the UHI effect has become more prominent in areas of rapid urbanization in the PRD region. The spatial distribution of heat islands has been changed from a mixed pattern, where bare land, semi-bare land and land under development were warmer than other surface types, to extensive UHI. Our analysis showed that higher temperature in the UHI was located with a scattered pattern, which was related to certain land-cover types. In order to analyze the relationship between UHI and land-cover changes, this study attempted to employ a quantitative approach in exploring the relationship between temperature and several indices, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Bareness Index (NDBaI) and Normalized Difference Build-up Index (NDBI). It was found that correlations between NDVI, NDWI, NDBaI and temperature are negative when NDVI is limited in range, but positive correlation is shown between NDBI and temperature.     

An open framework for agent based modelling of agricultural land use change

There is growing interest in creating empirically grounded agent based models (ABMs) to simulate land use change at a variety of spatio-temporal scales. The development of land use change models is challenging, as there is a need to connect representations of human behavioural processes to simulations of the biophysical environment. This paper presents a new agent-based modelling framework (Aporia) that has the goal of reducing the complexity and difficulty of constructing high-fidelity land use models. Building on earlier conceptual developments for modelling land use change and the provision of ecosystem services, Aporia was designed to be modular, flexible and open, using a declarative, compositional approach to create complex models from subcomponents. The framework can be tightly or loosely coupled with multiple vegetation models, it can be set up to evaluate a range of ecosystem service indicators, and it can be calibrated for a range of different landscape-scale case studies and modelling styles. The framework is released under an Open Source licence, and can be freely re-used and modified to form the basis of new models. We illustrate this with two case studies implemented using Aporia, exploring different socio-economic scenarios and behavioural characteristics on the land use decisions of Swiss and Scottish farmers. We also discuss the benefits of frameworks in terms of their flexibility, expandability, verification and transparency.     

A spatially distributed risk screening tool to assess climate and land use change impacts on water-related ecosystem services

To support the implementation of the European Water Framework Directive (WFD), and as part of a tiered approach to prioritise detailed modelling, a high-level screening methodology has been developed to assess the vulnerability of water-related ecosystem services (ES) to future change. The approach incorporates a range of spatially distributed scenarios of land use and climate, which are used as inputs to a qualitative risk assessment model underpinned by expert opinion. The method makes use of widely available datasets and provides a structured way of capturing and “codifying” expert knowledge, as well as for assessing the degree of consensus between different expert groups. The range of model output reflects uncertainty in both the expert-derived assumptions and the climate & land use simulations considered. The approach has been developed in collaboration with the Scottish Environment Protection Agency (SEPA) and applied in Scotland to support the second cycle of River Basin Management Planning.     

Development of a land use regression model for daily NO2 and NOx concentrations in the Brisbane metropolitan area,Australia

Land use regression models are an established method for estimating spatial variability in gaseous pollutant levels across urban areas. Existing LUR models have been developed to predict annual average concentrations of airborne pollutants. None of those models have been developed to predict daily average concentrations, which are useful in health studies focused on the acute impacts of air pollution. In this study, we developed LUR models to predict daily NO₂ and NO_x concentrations during 2009–2012 in the Brisbane Metropolitan Area (BMA), Australia's third-largest city. The final models explained 64% and 70% of spatial variability in NO₂ and NO_x, respectively, with leave-one-out-cross-validation R² of 3–49% and 2–51%. Distance to major road and industrial area were the common predictor variables for both NO₂ and NO_x, suggesting an important role for road traffic and industrial emissions. The novel modeling approach adopted here can be applied in other urban locations in epidemiological studies.     

Ganges and Indus river basin land use/land cover (LULC) and irrigated area mapping using continuous streams of MODIS data

The overarching goal of this study was to map irrigated areas in the Ganges and Indus river basins using near-continuous time-series (8-day), 500-m resolution, 7-band MODIS land data for 2001-2002. A multitemporal analysis was conducted, based on a mega file of 294 wavebands, made from 42 MODIS images each of 7 bands. Complementary field data were gathered from 196 locations. The study began with the development of two cloud removal algorithms (CRAs) for MODIS 7-band reflectivity data, named: (a) blue-band minimum reflectivity threshold and (b) visible-band minimum reflectivity threshold.A series of innovative methods and approaches were introduced to analyze time-series MODIS data and consisted of: (a) brightness-greenness-wetness (BGW) RED-NIR 2-dimensional feature space (2-d FS) plots for each of the 42 dates, (b) end-member (spectral angle) analysis using RED-NIR single date (RN-SD) plots, (c) combining several RN-SDs in a single plot to develop RED-NIR multidate (RN-MDs) plots in order to help track changes in magnitude and direction of spectral classes in 2-d FS, (d) introduction of a unique concept of space-time spiral curves (ST-SCs) to continuously track class dynamics over time and space and to determine class separability at various time periods within and across seasons, and (e) to establish unique class signatures based on NDVI (CS-NDVI) and/or multiband reflectivity (CS-MBR), for each class, and demonstrate their intra- and inter-seasonal and intra- and inter-year characteristics. The results from these techniques and methods enabled us to gather precise information on onset-peak-senescence-duration of each irrigated and rainfed classes.The resulting 29 land use/land cover (LULC) map consisted of 6 unique irrigated area classes in the total study area of 133,021,156 ha within the Ganges and Indus basins. Of this, the net irrigated area was estimated as 33.08 million hectares—26.6% by canals and 73.4z5 by groundwater. Of the 33.08 Mha, 98.4% of the area was irrigated during khariff (Southwest monsoonal rainy season during June-October), 92.5% irrigated during Rabi (Northeast monsoonal rainy season during November-February), and only 3.5% continuously through the year.Quantitative Fuzzy Classification Accuracy Assessment (QFCAA) showed that the accuracies of the 29 classes varied from 56% to 100%—with 17 classes above 80% accurate and 23 classes above 70% accurate.The MODIS band 5 centered at 1240 nm provided the best separability in mapping irrigated area classes, followed by bands 2 (centered at 859 nm), 7 (2130 nm) and 6 (1640 nm).     

A physically based and machine learning hybrid approach for accurate rainfall-runoff modeling during extreme typhoon events

Accurate rainfall-runoff modeling during typhoon events is an essential task for natural disaster reduction. In this study, a novel hybrid model which integrates the outputs of physically based hydrologic modeling system into support vector machine is developed to predict hourly runoff discharges in Chishan Creek basin in southern Taiwan. Seven storms (with a total of 1200 data sets) are used for model calibration (training) and validation. Six statistical indices (mean absolute error, root mean square error, correlation coefficient, error of time to peak discharge, error of peak discharge, and coefficient of efficiency) are employed to assess prediction performance. Overall, superiority of the present approach especially for a longer (6-h) lead time prediction is revealed through a systematic comparison among three individual methods (i.e., the physically based hydrologic model, artificial neural network, and support vector machine) as well as their two hybrid combinations. Besides, our analysis and in-depth discussions further clarify the roles of physically based and data-driven components in the proposed framework.     

基于多智能体与GIS城市土地利用变化仿真研究*

摘要：为动态模拟城市土地利用变化,以复杂适应系统理论为基础,通过集成多智能体、GIS和元胞自动机建立城市发展模型,并以Repast和 ArcGIS为基础设计实现了城市土地利用动态模拟系统,并以广州市番禺区为例进行了仿真实验。仿真结果表明,该方法是一种模拟土地利用变化的有效方法,可以为城市建设、管理和规划工作提供辅助决策支持。     

An integrated modelling approach for the assessment of land use change effects on wastewater infrastructures

The simulation of sewage systems and wastewater treatment plants is strategic for assessing the effect of new dwellings on the existing water facilities. This paper introduces an integrated framework made by a land use change model, a sewage system simulator, and a wastewater treatment plant simulator. This is a complex system since each element is characterized by different dynamics. The land use change model simulates the annual expansion of an urban area according to planners’ guidelines; the sewage system simulator investigates the response of the drainage system to the expansion. The wastewater treatment plant is simulated in order to assess the impact of the new outflows on the existing plant. The three models are integrated into a Simulink model. Two components of the developed framework are based on models well established in literature. The proposed framework is tested on a simple case study of a small town located in south west of Scotland.     

Modelling the impacts of land system dynamics on human well-being: Using an agent-based approach to cope with data limitations in Koper,Slovenia

To cope with data limitations and to provide insight into the dynamics of LUCC for local stakeholders in the Municipality of Koper, Slovenia, we constructed an ABM (loosely defined) that integrates utility theory, logistic regression, and cellular automaton-like rules to represent the decision-making strategies of different agents. The model is used to evaluate the impact of LUCC on human well-being, as represented by the provision of highly productive agricultural soil, the extent of noise pollution, and quality-of-life measurements. Results for the Municipality of Koper show that, under a range of model assumptions, (1) high quality agricultural soils are disproportionately affected by urban growth, (2) aggregate resident quality of life increases non-linearly with a change in development density, (3) some drivers of residential settlement produce non-linear preference responses, and (4) clustering industrial development had a beneficial impact on human well-being. Additional novel contributions include the incorporation of noise pollution feedbacks and an approach to empirically inform agent preferences using a conjoint analysis of social survey data.     

Development of a computationally efficient semi-distributed hydrologic modeling application for soil moisture,lateral flow and runoff simulation

A new automated workflow based computationally efficient hydrologic modeling application is developed for soil moisture and runoff simulation. The spatially distributed conceptual framework underpinning the Soil Moisture And Runoff simulation Toolkit (SMART) resolves water balance in large upland catchments where topography and land cover are significant drivers of rainfall-runoff transformations. SMART's computational efficiency is achieved by delineation of contiguous and topologically connected hydrologic response units and solving the water balance equation on spatially representative Equivalent Cross-Sections (ECSs). ECSs are formulated by aggregating topographic and physiographic properties of the complete or part of the first order Strahler sub-basins, thereby reducing the number of computational elements. Water balance simulations across the ECSs in two sub-basins illustrated little loss of accuracy compared to the distributed cross section delineations and soil moisture observations. A 2-dimensional Richards' equation based hydrologic model in SMART can be augmented with additional functionalities or replaced with other model structures.     

Construction of an analytical framework for polygon-based land use transition analyses

Polygon representation is important for characterizing land uses and the relationships among them. This study aims to establish an analytical framework for polygon-based land use transitions to understand the processes of change regarding types of land uses and their shapes. The polygon event and polygon state help to reveal continuity both spatially and temporally. A polygon event represents a combination of changes in both the type of land use and its shape through a transition process. A polygon state reflects homogeneity during the transition process. Two indices, the stability index and the compactness, were used to enhance the understanding of the transition process. The stability index evaluates the succession of an attribute, while compactness recognizes the geometrical characteristics of a polygon. A case study on Tsukuba City, Japan, was evaluated to demonstrate the feasibility of the approach that is presented here. The proposed analytical framework supports the clarification of land use transition patterns and is effective in explaining the spatiotemporal land use transition process.     

A national-scale GIS-based system for modelling impacts of land use on water quality

Management of freshwater quality requires modelling tools for rapid evaluation of land use and management scenarios. This paper presents the CLUES (Catchment Land Use and Environmental Sustainability) model to address this need. CLUES provides steady state, spatially distributed, integrated catchment models tightly coupled to GIS software to predict mean annual loads of total nitrogen, total phosphorus, sediments and E. coli, and concentration of nutrients throughout New Zealand (268,000 km²) with a subcatchment resolution of 0.5 km². CLUES also estimates potential nutrient concentrations for estuaries and provides key farm socio-economic indicators. The model includes a user interface for study area selection, scenario creation, data geo-visualisation, and export of results. It is pre-populated with spatial data and parameter values for New Zealand. Evaluation of the model and a summary of applications demonstrate the tractability and utility of national-scale rapid scenario assessment tools within a GIS framework.     

Analytical modeling of H‐shape distributed topology with bandpass negative group delay behavior

This article describes an analytical modeling of a distributed negative group delay (NGD) circuit presenting a H‐shape topology. It acts as an innovative typical transmission line (TL) based topology with a feedback connected with an open‐stub termination. The equivalent circuit diagram is established based on TL representation of H‐topology constituting elements. The S‐matrix analytical model is developed. To validate the analytical model, a proof‐of‐concept prototype implemented in microstrip topology is designed, simulated, fabricated, and measured. The compared calculated, simulated, and measured S‐parameters are in very good agreement. In addition, the microstrip prototype confirm the bandpass NGD behavior of the H‐topology circuit with NGD value of approximately ?2 ns around the center frequency 1.67 GHz.     

A C++ program for retrieving land surface temperature from the data of Landsat TM/ETM+ band6

A C++ language-based software tool for retrieving land surface temperature (LST) from the data of Landsat TM/ETM+ band6 is developed. It has two main functional modules: (1) Three methods to compute the ground emissivity based on land use/cover classification image, NDVI image and the ratio values of vegetation and bare ground and (2) Converting digital numbers (DNs) from TM/ETM+ band6 to LST. In the software tool, Qin et al.'s mono-window algorithm and Jiménez-Muňoz and Sobrino's single channel algorithm are programmed to retrieve LST. It will be a useful software tool to study the thermal environment of ground surface or the energy balance between the ground and the bottom atmosphere by using the thermal band of Landsat TM/ETM+.     

扩展UML活动图在工作流建模中的应用*

针对UML对数据和信息流描述缺乏充分表达业务工作流程的问题,借助新创建的活动图,提出了基于扩展UML活动图的工作流过程建模方法。应用实例表明,扩展的UML活动图对工作流程的语义表达更丰富,更准确地描述工作流建模所需表达的内容,以满足工作流过程建模的要求。     

Bangla language modeling algorithm for automatic recognition of hand-sign-spelled Bangla sign language

Because of using traditional hand-sign segmentation and classification algorithm,many diversities of Bangla language including joint-letters,dependent vowels etc.and representing 51 Bangla written characters by using only 36 hand-signs,continuous hand-sign-spelled Bangla sign language(BdSL)recognition is challenging.This paper presents a Bangla language modeling algorithm for automatic recognition of hand-sign-spelled Bangla sign language which consists of two phases.First phase is designed for hand-sign classification and the second phase is designed for Bangla language modeling algorithm(BLMA)for automatic recognition of hand-sign-spelled Bangla sign language.In first phase,we have proposed two step classifiers for hand-sign classification using normalized outer boundary vector(NOBV)and window-grid vector(WGV)by calculating maximum inter correlation coefficient(ICC)between test feature vector and pre-trained feature vectors.At first,the system classifies hand-signs using NOBV.If classification score does not satisfy specific threshold then another classifier based on WGV is used.The system is trained using 5,200 images and tested using another(5,200×6)images of 52 hand-signs from 10 signers in 6 different challenging environments achieving mean accuracy of 95.83%for classification with the computational cost of 39.972 milliseconds per frame.In the Second Phase,we have proposed Bangla language modeling algorithm(BLMA)which discovers allhidden charactersbased onrecognized charactersfrom 52 hand-signs of BdSL to make any Bangla words,composite numerals and sentences in BdSL with no training,only based on the result of first phase.To the best of our knowledge,the proposed system is the first system in BdSL designed on automatic recognition of hand-sign-spelled BdSL for large lexicon.The system is tested for BLMA using hand-sign-spelled 500 words,100 composite numerals and 80 sentences in BdSL achieving mean accuracy of 93.50%,95.50%and 90.50%respectively.