The Decision‐Making/Accountability Spatial Incongruence Problem for Research Linking Environmental Science and Policy

Increasingly, scholars engage policy makers around fundamental, complex questions on environmental change in interdisciplinary settings. Researchers attempting to develop robust contributions to knowledge that can support policymaker understandings in this context face significant inferential challenges in dealing with the spatial dimension of their phenomenon of interest. In this paper, we extend an understanding of well‐defined methodological challenges familiar to applied spatial scientists by explicitly articulating the Decision‐Making/Accountability, Spatial Incongruence Problem, or DASIP. Three case studies illustrate how spatial incongruences matter to researchers who work on complex, interdisciplinary problems, while seeking to understand decision‐making or policy‐related phenomenon: urban heat‐island mitigation research in Arizona, water transfer conflicts in Kansas, and hydraulic‐fracturing debates in Texas. With such examples, we aim to evoke a deeper understanding of this problem in applied research and also inspire thinking about how scholars might innovate methods for creating knowledge about environmental change that supports spatially accountable decision making.     

LegalGEO: Conservation tool to guide the siting of legal reserves under the Brazilian Forest Code

The Brazilian Forest Code, enacted in 1965, was the first national law to mandate that private landowners maintain a portion of their land in natural vegetation. Effective implementation of the law is not only a national priority, but also a global one as Brazil hosts some of the greatest biodiversity and the largest carbon stores in the world. Under the Forest Code, landowners have options to either protect, restore, or offset to meet the legal requirements. Collectively planning and guiding where to locate these options within and outside a rural property can have positive impacts for the environment at both local and landscape levels. To that end, we developed the LegalGEO toolkit to assist government and non-government organizations in offering landowners solutions for complying with the Forest Code requirements while promoting positive outcomes for the environment. Here, we introduce the tools and spatial data associated with LegalGEO and discuss how these data are used within a spatial multi-criteria analysis to produce landscape prioritization maps to guide landowner decisions at the property level. As a case study, we apply LegalGEO to a collection of rural properties within the state of Minas Gerais, Brazil and compare the differences in the resulting landscape patterns against a scenario where landowners lack this guidance. Results from this comparison suggest that the use of the LegalGEO tool improves conservation outcomes at both landscape and property levels scales.     

基于暴雨内涝灾害情景推演的北京市应急救援方案评估与决策优化

城市自然灾害的情景推演与应急方案的动态预评估是优化应急决策的重要支撑。然而,传统的应急救援方案评估往往基于有限信息进行时间片段式的情景推演并采用应急方案的灾后评估。本文在构建基于内涝水淹模型和多智能体城市路况模型的全链条、多维度灾害情景推演方案的基础上,实施不同应急救援目标导向下多时间刻度的应急救援方案预评估,重点从受损车辆规模和遭受安全威胁人数定量评估基于救援人数、救援时间和救援空间布局原则的应急方案优劣,为灾害情景推演方案和应急决策优化提供了一种新的思路与解决方案。基于救援人数规模的应急方案表明,救援力量将优先布局在风险指数高企的区域,包括北蜂窝路、南蜂窝路、广莲路以及莲花桥等路段。在现实情况中及时参加的救援力量往往有限,此类根据不同救援力量数量的空间指向将对最优的救援决策起到关键作用。同时,研究也应证了救援力量多寡在应急事件处置中的基础性地位。基于救援启动时间的应急方案中得出,最优的救援启动时间在45 min到75 min之间,适时的救援启动可以有效规避过早启动导致的救援空间配置不当和过晚启动导致的救援失效两类问题。不同救援空间布局原则有着迥异的救援力量空间配置特点和最优运用条件。     

A cyber-enabled spatial decision support system to inventory Mangroves in Mozambique: coupling scientific workflows and cloud computing

Mangroves are an important terrestrial carbon reservoir with numerous ecosystem services. Yet, it is difficult to inventory mangroves because of their low accessibility. A sampling approach that produces accurate assessment while maximizing logistical integrity of inventory operation is often required. Spatial decision support systems (SDSSs) provide support for integrating such a sampling design of fieldwork with operational considerations and evaluation of alternative scenarios. However, this fieldwork design driven by SDSS is often computationally intensive and repetitive. In this study, we develop a cyber-enabled SDSS framework to facilitate the computationally challenging fieldwork design that requires the efficacious selection of base camps and plots for the inventory of mangroves. Our study area is the Zambezi River Delta, Mozambique. Cyber-enabled capabilities, including scientific workflows and cloud computing, are integrated with the SDSS. Scientific workflows enable the automation of data and modeling tasks in the SDSS. Cloud computing offers on-demand computational support for interoperation among stakeholders for collaborative scenario evaluation for the fieldwork design of mangrove inventory. Further, this framework allows for harnessing high-performance computing capabilities for accelerating the fieldwork design. The cyber-enabled framework provides significant merits in terms of effective coordination among science and logistical teams, assurance of meeting inventory objectives, and an objective basis to collectively and efficaciously evaluate alternative scenarios.     

基于电网GIS的多维度智能分析决策平台

为有效应对电网分析决策面临数据量大、决策复杂、技术手段匮乏的局面,文中设计并实现了一种基于平台化设计、具备可视化及多维度智能分析决策支持功能的基于电网 GIS 的多维度智能分析决策平台。该平台与地理信息系统(GIS)密切融合,具备多源数据资源协同管理、电网可视化图形建模、电网仿真模拟,多维度智能分析、辅助决策、项目管理等功能。本文介绍的基于电网 GIS 的多维度智能分析决策平台建成了覆盖整个电网生命周期的一体化平台,具有电网分析可视化、决策智能化的特征,可对电网相关工作提供辅助决策支持。平台的设计与开发立足于项目实践,软件成果在全国多地电网相关部门得到实际应用,验证了文中的设计思路和实现方法。     

基于Radarsat-2双极化数据的南极半岛冰盖冻融探测研究

南极冰盖的融化对全球海平面上升和气候环境变化具有重要影响,合成孔径雷达(SAR)用于划分南极冰盖冰川带及冻融探测具有不可替代的作用。本文以南极半岛地区为例,基于C波段星载SAR影像进行南极冰盖冻融探测方法研究。通过对于南极冰盖干雪带、渗浸带和湿雪带的后向散射特征的分析,采用基于后向散射因子阈值的决策树分类划分冰盖冰川带。统计分析表明,冰川带后向散射因子分布并不集中,尤其是融化强烈时的湿雪带受融化程度影响很大,与干雪带相近而不能仅从后向散射因子数值区分。为将冰盖的冰川带分类,引入干雪带分布和海拔高度作为辅助信息,分别发展了两种决策树分类方法并比较分析,同时利用微波辐射计冰盖冻融探测结果和自动气象站数据做验证。结果表明利用双极化SAR数据的后向散射因子基于两种决策树分类都能够有效地划分冰川带并区分冻融状态,实现高分辨率的冰盖冻融探测。     

Error propagation in a fuzzy logic multi-criteria evaluation for petroleum exploration

This article applies error propagation in a Monte Carlo simulation for a spatial-based fuzzy logic multi-criteria evaluation (MCE) in order to investigate the output uncertainty created by the input data sets and model structure. Six scenarios for quantifying uncertainty are reviewed. Three scenarios are progressively more complex in defining observational data (attribute uncertainty); while three other scenarios include uncertainty in observational data (position of boundaries between map units), weighting of evidence (fuzzy membership assignment), and evaluating changes in the MCE model (fuzzy logic operators). A case study of petroleum exploration in northern South America is used. Despite the resources and time required, the best estimate of input uncertainty is that based on expert-defined values. Uncertainties for fuzzy membership assignment and boundary transition zones do not affect the results as much as the attribute assignment uncertainty. The MCE fuzzy logic operator uncertainty affects the results the most. Confidence levels of 95% and 60% are evaluated with threshold values of 0.7 and 0.5 and show that accepting more uncertainty in the results increases the total area available for decision-making. Threshold values and confidence levels should be predetermined, although a series of combinations may yield the best decision-making support.     

Web-based geospatial multiple criteria decision analysis using open software and standards

The emerging ubiquity of geospatial information is providing an unprecedented opportunity to apply Geographical Information Systems (GIS)-based multiple criteria decision analysis (MCDA) to a broad spectrum of use cases. Volunteered geographic information, open GIS software, geoservice-based tools, cloud-based virtualized platforms, and worldwide collaboration of both domain experts and general users have greatly increased the quantity and accessibility of geospatially referenced data resources. Currently, there is a lack of GIS-based MCDA tools that integrate this decision-driven process within a widely accessible, robust geoframework environment, designed for user-friendly interaction. In this contribution, we present a conceptual workflow and proof-of-concept software application, Geocentric Environment for Analysis and Reasoning (GEAR), which provides a viable transition path to enhance geospatial MCDA in the age of open GIS. We propose a Web-based platform that leverages open-source geotechnologies to incorporate a wide variety of geospatial data formats in a common solution space to allow for spatially enhanced and time-relevant decision analysis. Through the proposed workflow, a user can ingest and modify heterogeneous data formats, exploit temporally tagged data sources, create multicriteria decision analysis models, and visualize the results in an iterative and collaborative workspace. A sample case study applied to disaster relief is used to demonstrate the prototype and workflow. This proof-of-concept Web-based application provides a notional pathway of how to connect open-source data to open-source analysis through a geospatially enabled MCDA workflow that could be virtually accessible to many levels of decision makers from individuals to entire organizations.     

Place‐Making Through Beer‐Drinking: A Case Study of Montana's Craft Breweries

Montana's craft brewing industry has grown astronomically in the last few decades and has spawned many breweries with local names and themes. Using Montana's craft breweries as a case study, this paper demonstrates that craft breweries play a significant role in contemporary place‐making. First, brewery and beer names are analyzed to extract several place‐based themes, and it is argued that these perpetuate a particular New West identity for the state. Then, through the lens of tourism and the quest for “authenticity,” surveys of brewery visitors are used to identify the various attractions that drinking craft beer and visiting breweries offer their patrons. Besides the taste of the beer, the local nature of breweries and their community focus prove to be an important draw for brewery visitors and provide the chance to experience the community in a more authentic way, and thus, offer an opportunity to make a meaningful connection with place. This research proves that craft breweries have become an important venue for place‐making, not only in Montana, but in other cities and states with a significant craft‐brewing industry     

遥感影像提取土地覆盖信息的决策树优化方法

针对高分辨率遥感影像分类的传统ID3算法采用的信息增益熵为局部非回溯的启发式的缺点,提出了决策树引入模拟退火算法,得到一个面向影像特征优先级的优化的决策树分类算法。采用优化的决策树算法进行高分辨率遥感影像的分类,能较好地解决样本依赖性问题,并且得到一个全局优化的分类结果。通过实验,对农村地区的SPOT影像进行分类,并且通过对较优尺度下优化的决策树算法与神经网络算法和最大似然法对实验区域的影像分类精度的比较,证明了与ID3决策树分类方法相比较,优化的决策树方法能有效地提高农村地区在各尺度下SPOT影像的分类精度。