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1.
This study attempts to establish multi‐temporal accuracy of the predicted maps produced by a land use change simulation model over time. Validation of the forecasted results is an essential part of predictive modeling and it becomes even more important when the models are used for decision making purposes. The present study uses a popular land use change model called SLEUTH to investigate the temporal trend of accuracy of the predicted maps. The study first investigates the trend of accuracy of the predicted maps from the immediate future to the distant future. Secondly, it investigates the impact of the prediction date range on the accuracy of the predicted maps. The objectives are tested for the city of Gorizia (Italy) using three sets of map comparison techniques, Kappa coefficients, Kappa Simulation and quantity disagreement and allocation disagreement. Results show that, in addition to the model's performance, the decrease in the accuracy of the predicted maps is dependent on factors such as urban history, uncertainty of input data and accuracy of reference maps.  相似文献   

2.
遥感数据产品真实性检验不确定性分析研究进展   总被引：1，自引：1，他引：1  
不确定性分析是遥感产品真实性检验最重要的部分,本文以叶面积指数LAI为例,从测量、模型以及蕴含在测量和模型中的尺度效应3个方面分析产品真实性检验过程的不确定性来源,并针对问题提出减小其不确定性的办法。对于相对均一的地表,地面测量的空间代表性比较好,可不考虑地表空间代表性引起的尺度效应和蕴含在模型中的尺度效应引起的不确定性。针对异质性地表,分为两种情况:若模型是线性的,蕴含在模型中的尺度效应可以忽略,只需要考虑测量的不确定性、模型本身的不确定性、以及地面测量的空间代表性引起的尺度效应;若模型是非线性的,则测量、模型和蕴含在测量和模型中的尺度效应引起的不确定性都需要考虑。  相似文献   

3.
This paper presents novel techniques to estimate the uncertainty in extrapolations of spatially-explicit land-change simulation models. We illustrate the concept by mapping a historic landscape based on: 1) tabular data concerning the quantity in each land cover category at a distant point in time at the stratum level, 2) empirical maps from more recent points in time at the grid cell level, and 3) a simulation model that extrapolates land-cover change at the grid cell level. This paper focuses on the method to show uncertainty explicitly in the map of the simulated landscape at the distant point in time. The method requires that validation of the land-cover change model be quantified at the grid-cell level by Kappa for location (Klocation). The validation statistic is used to estimate the certainty in the extrapolation to a point in time where an empirical map does not exist. As an example, we reconstruct the 1951 landscape of the Ipswich River Watershed in Massachusetts, USA. The technique creates a map of 1951 simulated forest with an overall estimated accuracy of 0.91, with an estimated users accuracy ranging from 0.95 to 0.84. We anticipate that this method will become popular, because tabular information concerning land cover at coarse stratum-level scales is abundant, while digital maps of the specific location of land cover are needed at a finer spatial resolution. The method is a key to link non-spatial models with spatially-explicit models.  相似文献   

4.
Agent‐based modeling provides a means for addressing the way human and natural systems interact to change landscapes over time. Until recently, evaluation of simulation models has focused on map comparison techniques that evaluate the degree to which predictions match real‐world observations. However, methods that change the focus of evaluation from patterns to processes have begun to surface; that is, rather than asking if a model simulates a correct pattern, models are evaluated on their ability to simulate a process of interest. We build on an existing agent‐based modeling validation method in order to present a temporal variant‐invariant analysis (TVIA). The enhanced method, which focuses on analyzing the uncertainty in simulation results, examines the degree to which outcomes from multiple model runs match some reference to how land use parcels make the transition from one land use class to another over time. We apply TVIA to results from an agent‐based model that simulates the relationships between landowner decisions and wildfire risk in the wildland‐urban interface of the southern Willamette Valley, Oregon, USA. The TVIA approach demonstrates a novel ability to examine uncertainty across time to provide an understanding of how the model emulates the system of interest.  相似文献   

5.
Uncertainty research represents a research stream of high interest within the community of geographical information science. Its elements, terminology and typology are still under strong discussion and adopted methods for analysis are currently under intensive development. This paper presents a conceptual framework for systematic investigation of uncertainty which occurs in applications of land cover change modelling in Geographical Information Systems (GIS) based on historical map data. Historical, in this context, means the map is old enough to allow identification of changes in landscape elements of interest, such as vegetation. To date such analyses are rarely conducted or not satisfactorily carried out, despite the fact that historical map data represent a potentially rich information source. The general validity and practicability of the framework for related applications is demonstrated with reference to one example in which forest cover change in Switzerland is investigated. The conceptual model consists of three domains in which main potential sources of uncertainty are systematically exposed. Existing links between data quality research and uncertainty are investigated to access the complex nature of uncertainty and to characterise the most suitable concepts for analysis. In accordance with these concepts appropriate methods and procedures are suggested to assess uncertainty in each domain. One domain is the production‐oriented amount of uncertainty which is inherent in the historical map. Vagueness and ambiguity represent suitable concepts for analysis. Transformation‐oriented uncertainty as the second domain occurs owing to editing and processing of digital data. Thereby, the suitable concept of uncertainty is error. The third domain is the application‐oriented uncertainty which occurs in comparing semantically different data. This domain relates to multi‐temporal discord which assumes the assessment of ‘equi‐temporal’ ambiguity and is thus connected to the production‐oriented domain. The framework provides an estimation of the overall amount of uncertainty. This can be linked to subsequent assessment of ‘fitness for use’. Thus the model provides a practicable and systematic approach to access the complex nature of uncertainty in the scope of land cover change modelling.  相似文献   

6.
This paper presents a methodology for the evaluation of land condition and for the allocation of areas requiring restoration. It is based on spatial simulation analysis and fuzzy logic. The method is demonstrated in a restoration allocation problem within a military training area in Texas. Fuzzy logic is integrated with spatial analysis through Geographic Information Systems (GIS) to make land condition assessment geographically specific. Two sources of uncertainty in Land Condition Analysis are considered in this paper. First is the uncertainty due to incomplete information on land condition. Second is the uncertainty emanating from identifying the condition of a particular parcel of land. The first is addressed by using sequential Gaussian simulation, a geostatistical tool. Erosion status is selected as the land condition factor, and uncertainty associated with it is considered in this study. Land allocation is based on fuzzy logic to reflect the continuous transition between different land conditions and the minimization of loss that is expected to occur in the case of misallocation. Various forms of loss functions are used for allocating areas in need of restoration. An important result of the study is a map showing the areas allocated for restoration. The proposed method is compared to two alternative methods with varying degrees of determinism and uncertainty. The incorporation of uncertainty led to better allocation strategies and results that are more realistic.  相似文献   

7.
Sprawl measures have largely been neglected in land‐use forecasting models. The current approach for land‐use allocation using optimization mostly utilizes objective functions and constraints that are non‐spatial in nature. Application of spatial constraints could take care of the contiguity and compactness of land uses and can be utilized to address urban sprawl. Because a land‐use model is used as an input to transportation modeling, a better spatial allocation strategy for more compact land‐use projections will promote better transportation planning and sustainable development. This study formulates a scenario‐based approach to normative modeling of urban sprawl. In doing so, it seeks to improve the land‐use projections by employing a spatial optimization model with contiguity and compactness consideration. This study incorporates urban sprawl measures based on smart growth principles together with a mixed‐use factor, and adjacency consideration of nearby land uses. The objective function used in the study maximizes net suitability based on imposed constraints. These constraints are based on smart growth principles that enhance walkability in neighborhoods, promote better health for residents, and encourage mixed‐use development. The formulated model has been applied to Collin County, TX, a fast‐developing suburban county located to the north of the Dallas–Fort Worth metroplex. The suitability of land cells indicates the probability of conversion, which is calculated using spatial discrete choice analysis with Moran eigenvector spatial filtering for vacant cells at a resolution of 150 × 150 m employing factors of the built environment, and socioeconomic and demographic characteristics. This study demonstrates how spatial proximity between land uses, which has been ignored to date, can be used to control sprawl, resulting in better mixing of different land uses based on constraints imposed in a spatial optimization problem.  相似文献   

8.
Advances in computer technologies have improved the quality of maps, making map comparison and analysis easier, but uncertainty and error still exist in GIS when overlaying geographic data with multiple or unknown confidence levels. The goals of this research are to review current geospatial uncertainty literature, present the Error‐Band Geometry Model (EBGM) for classifying the size and shape of spatial confidence intervals for vector GIS data, and to analyze the interpretability of the model by looking at how people use metadata to classify the uncertainty of geographic objects. The results from this research are positive and provide important insight into how people interpret maps and geographic data. They suggest that uncertainty is more easily interpreted for well defined point data and GPS data. When data is poorly defined, people are unable to determine an approach to model uncertainty and generate error‐bands. There is potential for using the EBGM to aid in the development of a GIS tool that can help individuals parameterize and model spatial confidence intervals, but more research is needed to refine the process by which people use the decision tree. A series of guiding questions or an “uncertainty wizard” tool that helps one select an uncertainty modeling approach might improve the way people apply this model to real‐world applications.  相似文献   

9.
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10.
Land-use/land-cover information constitutes an important component in the calibration of many urban growth models. Typically, the model building involves a process of historic calibration based on time series of land-use maps. Medium-resolution satellite imagery is an interesting source for obtaining data on land-use change, yet inferring information on the use of urbanised spaces from these images is a challenging task that is subject to different types of uncertainty. Quantifying and reducing the uncertainties in land-use mapping and land-use change model parameter assessment are therefore crucial to improve the reliability of urban growth models relying on these data. In this paper, a remote sensing-based land-use mapping approach is adopted, consisting of two stages: (i) estimating impervious surface cover at sub-pixel level through linear regression unmixing and (ii) inferring urban land use from urban form using metrics describing the spatial structure of the built-up area, together with address data. The focus lies on quantifying the uncertainty involved in this approach. Both stages of the land-use mapping process are subjected to Monte Carlo simulation to assess their relative contribution to and their combined impact on the uncertainty in the derived land-use maps. The robustness to uncertainty of the land-use mapping strategy is addressed by comparing the most likely land-use maps obtained from the simulation with the original land-use map, obtained without taking uncertainty into account. The approach was applied on the Brussels-Capital Region and the central part of the Flanders region (Belgium), covering the city of Antwerp, using a time series of SPOT data for 1996, 2005 and 2012. Although the most likely land-use map obtained from the simulation is very similar to the original land-use map – indicating absence of bias in the mapping process – it is shown that the errors related to the impervious surface sub-pixel fraction estimation have a strong impact on the land-use map's uncertainty. Hence, uncertainties observed in the derived land-use maps should be taken into account when using these maps as an input for modelling of urban growth.  相似文献   

11.
Landslide databases and input parameters used for modeling landslide hazard often contain imprecisions and uncertainties inherent in the decision‐making process. Dealing with imprecision and uncertainty requires techniques that go beyond classical logic. In this paper, methods of fuzzy k‐means classification were used to assign digital terrain attributes to continuous landform classes whereas the Dempster‐Shafer theory of evidence was used to represent and manage imprecise information and to deal with uncertainties. The paper introduces the integration of the fuzzy k‐means classification method and the Dempster‐Shafer theory of evidence to model landslide hazard in roaded and roadless areas illustrated through a case study in the Clearwater National Forest in central Idaho, USA. Sample probabilistic maps of landslide hazard potential and uncertainties are presented. The probabilistic maps are intended to help decision‐making in effective forest management and planning.  相似文献   

12.
Land cover maps play an integral role in environmental management. However, countries and institutes encounter many challenges with producing timely, efficient, and temporally harmonized updates to their land cover maps. To address these issues we present a modular Regional Land Cover Monitoring System (RLCMS) architecture that is easily customized to create land cover products using primitive map layers. Primitive map layers are a suite of biophysical and end member maps, with land cover primitives representing the raw information needed to make decisions in a dichotomous key for land cover classification. We present best practices to create and assemble primitives from optical satellite using computing technologies, decision tree logic and Monte Carlo simulations to integrate their uncertainties. The concept is presented in the context of a regional land cover map based on a shared regional typology with 18 land cover classes agreed on by stakeholders from Cambodia, Laos PDR, Myanmar, Thailand, and Vietnam. We created annual map and uncertainty layers for the period 2000–2017. We found an overall accuracy of 94% when taking uncertainties into account. RLCMS produces consistent time series products using free long term historical Landsat and MODIS data. The customizable architecture can include a variety of sensors and machine learning algorithms to create primitives and the best suited smoothing can be applied on a primitive level. The system is transferable to all regions around the globe because of its use of publicly available global data (Landsat and MODIS) and easily adaptable architecture that allows for the incorporation of a customizable assembly logic to map different land cover typologies based on the user's landscape monitoring objectives  相似文献   

13.
Geo‐questionnaire involves an integration of sketchable maps with questions, aimed at eliciting public preferences and attitudes about land allocation and services. Respondents can link their answers with corresponding locations on a map by marking points or sketching polygon features. Geo‐questionnaires have been used to learn about perceptions and preferences of city residents for specific types of land use, place‐based services, and development projects. This article reports on results of an empirical study, in which an online geo‐questionnaire was designed and implemented to elicit preferences of residents in guiding an urban development plan. Preferences collected in the form of polygon sketches were processed using GIS operations and mapped for visual interpretation. The article focuses on aggregation and analysis of respondent preferences including the analysis of positional and attribute uncertainty. Results of the study show that geo‐questionnaire is a scalable method for eliciting public preferences with a potential for meaningfully informing land use planning.  相似文献   

14.
The ways in which geographic information are produced have expanded rapidly over recent decades. These advances have provided new opportunities for geographical information science and spatial analysis—allowing the tools and theories to be expanded to new domain areas and providing the impetus for theory and methodological development. In this light, old problems of inference and analysis are rediscovered and need to be reinterpreted, and new ones are made apparent. This article describes a new typology of geographical analysis problems that relates to uncertainties in the relationship between individual‐level data, represented as point features, and the geographic context(s) that they are associated with. We describe how uncertainty in context linkage (uncertain geographic context problem) is also related to, but distinct from, uncertainty in point‐event locations (uncertain point observation problem) and how these issues can impact spatial analysis. A case study analysis of a geosocial dataset demonstrates how alternative conclusions can result from failure to account for these sources of uncertainty. Sources of point observation uncertainties common in many forms of user‐generated and big spatial data are outlined and methods for dealing with them are reviewed and discussed.  相似文献   

15.
Spatial decision support systems (SDSS) are designed to make complex resource allocation problems more transparent and to support the design and evaluation of allocation plans. Recent developments in this field focus on the design of allocation plans using optimization techniques. In this paper we analyze how uncertainty in spatial (input) data propagates through, and affects the results of, an optimization model. The optimization model calculates the optimal location for a ski run based on a slope map, which is derived from a digital elevation model (DEM). The uncertainty propagation is a generic method following a Monte Carlo approach, whereby realizations of the spatially correlated DEM error are generated using 'sequential Gaussian simulation'. We successfully applied the methodology to a case study in the Austrian Alps, showing the influence of spatial uncertainty on the optimal location of a ski run and the associated development costs. We also discuss the feasibility of routine incorporation of uncertainty propagation methodologies in an SDSS.  相似文献   

16.
Many land allocation issues, such as land-use planning, require input from extensive spatial databases and involve complex decision-making. Spatial decision support systems (SDSS) are designed to make these issues more transparent and to support the design and evaluation of land allocation alternatives. In this paper we analyze techniques for visualizing uncertainty of an urban growth model called SLEUTH, which is designed to aid decision-makers in the field of urban planning and fits into the computational framework of an SDSS. Two simple visualization techniques for portraying uncertainty—static comparison and toggling—are applied to SLEUTH results and rendered with different background information and color schemes. In order to evaluate the effectiveness of the two visualization techniques, a web-based survey was developed showing the visualizations along with questions about the usefulness of the two techniques. The web survey proved to be quickly accessible and easy to understand by the participants. Participants in the survey were mainly recruited among planners and decision-makers. They acknowledged the usefulness of portraying uncertainty for decision-making purposes. They slightly favored the static comparison technique over toggling. Both visualization techniques were applied to an urban growth case study for the greater Santa Barbara area in California, USA.  相似文献   

17.
MODIS土地覆盖分类的尺度不确定性研究   总被引：2，自引：0，他引：2  
以空间异质性较强的枯水期鄱阳湖为研究区,以搭载于同一卫星平台、具有同一观测时间和较高空间分辨率的ASTER数据为参照,分析研究了MODIS数据在土地覆盖分类中由空间尺度带来的不确定性。首先基于MODIS三角权重函数,建立了从ASTER到MODIS的尺度转换方法;然后对不同空间分辨率的数据进行土地覆盖分类,并基于误差矩阵和线性模型分析了MODIS土地覆盖分类结果的误差来源。结果表明,空间分辨率和光谱分辨率与成像方式这两类因素对MODIS与ASTER分类结果差异的贡献比例约为(6.6—11.2):2;MODIS像元尺度对研究区水体的分类不确定性影响较低,而对森林的不确定性影响可达63%。由此可见,在基于MODIS数据的土地覆盖分类研究中,空间尺度所产生的不确定性是比较显著的。这些研究结果对于土地覆盖分类及变化检测、尺度效应和景观生态学不确定性研究,有积极的参考意义。  相似文献   

18.
GIS中属性不确定性的处理方法及其发展   总被引：6，自引：0，他引：6  
史文中  王树良 《遥感学报》2002,6(5):393-400
属性数据的不确定直接影响决策的准确性和可靠性,特别是对侧重于属性分析的领域,在研究属性不确定性的基础上,分析了GIS中的主要处理方法及其研究进展,具体地就基于GIS的模型,概率论及数理统计学,模糊集合,云理论,粗集等方法及进展进行讨论.  相似文献   

19.
Coupling land use allocation models with raster GIS   总被引：5，自引：0，他引：5  
As geographic information systems (GIS) have moved from information storage and retrieval operations towards more decision support functions, there is a need for more integration of spatial analytical modules that can assist in locational decisions. This paper presents a methodology for coupling land use allocation models with a raster GIS. For raster systems, the integration of any decision module has been limited by the size of raster datasets that may contain hundreds of thousands of pixels. Therefore, decision heuristics have been used rather than exact methods such as mathematical programming models. For the problem of land use allocation, the special structure of the generalized assignment problem is used here to handle large scale datasets. The advantage of the mathematical programming approach is the additional information associated with the dual variables and opportunity costs that can be used in subsequent sensitivity analyses. Received: 7 April 1998/Accepted: 2 October 1998  相似文献   

20.
An important component of natural resource management is determining how to allocate resources within a landscape to different stakeholders in a manner that satisfies multiple objectives. Developing decision making tools for assisting natural resource allocation is a challenging endeavor as stakeholders' objectives typically exist at varying spatial scales, their actions are defined by the spatial constraints in which they operate, and the spatial distribution of resources can be altered due to system disturbances. The nature of such challenges suggests the need for a geographic approach that can investigate these spatial complexities in order to generate a suitable set of solutions. The objective of this study is to develop and evaluate an Intelligent Agent Model for multiobjective natural resource allocation. The model integrates agent-based modeling in a GIS environment with reinforcement learning – a heuristic method for generating, evaluating, and improving multiobjective decision making solutions. The model is implemented by simulating a forest management scenario in which agents that represent forest companies learn how to harvest trees in a manner that maximizes economic return while minimizing the adverse ecological impact to the surrounding landscape. In addition, the model simulates forest disturbances of varying frequencies and intensities to determine how disturbance events affect the decision-making ability of agents. The model is validated to demonstrate that it can provide practical solutions to natural resource decision making.  相似文献   

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