A web-based GIS Decision Support System for managing and planning USDA's Conservation Reserve Program (CRP)

Rao, Mahesh; Fan, Guoliang; Thomas, Johnson; Cherian, G.; Chudiwale, Varun; Awawdeh, Muheeb

doi:10.1016/j.envsoft.2006.08.003

Cited by 97 publications

(44 citation statements)

References 23 publications

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“…It has induced interests from domains like education & training (Cant, 2014;Granlund, 2000;Beam, 2006), design and production (Li, 2013;Wang, 2012), and military modelling and simulations (Page, 2000). There are also some works trying to incorporating GIS with WBS in ecology (Adeva, 2012) and agriculture planning (Rao, 2007). WBS is especially attractive in its capability for resource integration.…”

Section: Web Based Simulationmentioning

confidence: 99%

A Simulation-as-a-Service Framework Facilitating Webgis Based Installation Planning

Zheng

Chang

Fei

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Installation Planning is constrained by both natural and social conditions, especially for spatially sparse but functionally connected facilities. Simulation is important for proper deploy in space and configuration in function of facilities to make them a cohesive and supportive system to meet users' operation needs. Based on requirement analysis, we propose a framework to combine GIS and Agent simulation to overcome the shortness in temporal analysis and task simulation of traditional GIS. In this framework, Agent based simulation runs as a service on the server, exposes basic simulation functions, such as scenario configuration, simulation control, and simulation data retrieval to installation planners. At the same time, the simulation service is able to utilize various kinds of geoprocessing services in Agents' process logic to make sophisticated spatial inferences and analysis. This simulation-as-a-service framework has many potential benefits, such as easy-to-use, on-demand, shared understanding, and boosted performances. At the end, we present a preliminary implement of this concept using ArcGIS javascript api 4.0 and ArcGIS for server, showing how trip planning and driving can be carried out by agents.

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Section: Web Based Simulationmentioning

confidence: 99%

A Simulation-as-a-Service Framework Facilitating Webgis Based Installation Planning

Zheng

Chang

Fei

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Paterson and Bryan (2012) tackle an issue that has been of growing concern over the past decades, namely the impact on landscape and NRM caused by policies designed to produce environmental benefits in conjunction with maintenance of http://www.ecologyandsociety.org/vol18/iss1/art32/ productive farming and forestry. Such policies have been widespread from the mid-1980s in the European Union, following the creation of Environmentally Sensitive Areas (Hanley et al 1998, Wilson et al 2007, and in the United States, where the Conservation Reserve Program (Rao et al 2007, Sullivan et al 2004) and farmland preservation schemes have a long history (Dorfman et al 2009, Hellerstein andNickerson 2002). In recent years such measures have increasingly been linked directly to policy on climate change, and especially reductions in production of greenhouse gas emissions (Palm et al 2010).…”

Section: Developing Modelsmentioning

confidence: 99%

Applying Landscape Science to Natural Resource Management

Robinson¹,

Carson²

2013

E&S

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This is the introduction to the Ecology and Society special feature on "Applying Landscape Science to Natural Resource Management". Primarily drawing upon examples from Australia, the nine papers in the feature illustrate how landscape science seeks to integrate information from diverse sources to generate management solutions for implementation by individual land managers, communities, and governments at different levels. This introduction refers to the genesis of the feature, briefly outlines the nature and content of landscape science, and then summarizes key features of the nine papers. These are organized into two sections: one deals with inputs from human agents in the landscape, and one with the development of models enabling different management scenarios and environmental changes to be envisaged, understood, and applied to policy development

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“…Forecasting simultaneous change in multiple ecosystem services will be especially challenging, even for small ecosystems, because traditional forecasting was conducted by scientists within individual disciplines where a consistent means has rarely been used to develop the models, algorithms, and even the data structure among different scientific disciplines (Denzer, 2005). In addition, ecosystem disciplinary models often involve exchanging and analyzing geospatial data, which makes interoperability more difficult (Rao et al, 2007;Lee and Percivall, 2008). These differences must be resolved before it is possible to make disciplinary models interoperable for examining interdisciplinary ecological relationships and the dynamic evolution of ecosystems (Rizzoli and Young, 1997;Oxley et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

“…Besides the difficulties of setting up the computing environment for diverse models, it is usually very challenging to integrate these models because (1) semantic structure and format of model input/output data are heterogeneous, and (2) model coupling procedures do not exist or are not consistent. Keeping models in a centralized location also increases the difficulty for model users since it adds the additional burdens of tracking model versions and keeping them updated (Rao et al, 2007). Some disciplinary models are also location-specific, which may render them unusable elsewhere; thus, model metadata is required for model users to understand and use a particular model (Kouzes et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…Some disciplinary models have been integrated into complex decision support systems (DSS) for consideration of environmental and ecological aspects for the sustainable management of land and water ecosystems (Matthies et al, 2007;Rizzoli and Young, 1997;Oxley et al, 2004;Denzer, 2005;Rao et al, 2007). However, the model components within the systems were generally designed to run on standalone computers or in closed networks, rather than sharing and integrating resources in support of interdisciplinary model simulations (Goodchild, 2005).…”

Section: Introductionmentioning

confidence: 99%

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Prototyping an online wetland ecosystem services model using open model sharing standards

Feng

Liu

Euliss

et al. 2011

Environmental Modelling & Software

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a b s t r a c tGreat interest currently exists for developing ecosystem models to forecast how ecosystem services may change under alternative land use and climate futures. Ecosystem services are diverse and include supporting services or functions (e.g., primary production, nutrient cycling), provisioning services (e.g., wildlife, groundwater), regulating services (e.g., water purification, floodwater retention), and even cultural services (e.g., ecotourism, cultural heritage). Hence, the knowledge base necessary to quantify ecosystem services is broad and derived from many diverse scientific disciplines. Building the required interdisciplinary models is especially challenging as modelers from different locations and times may develop the disciplinary models needed for ecosystem simulations, and these models must be identified and made accessible to the interdisciplinary simulation. Additional difficulties include inconsistent data structures, formats, and metadata required by geospatial models as well as limitations on computing, storage, and connectivity. Traditional standalone and closed network systems cannot fully support sharing and integrating interdisciplinary geospatial models from variant sources. To address this need, we developed an approach to openly share and access geospatial computational models using distributed Geographic Information System (GIS) techniques and open geospatial standards. We included a means to share computational models compliant with Open Geospatial Consortium (OGC) Web Processing Services (WPS) standard to ensure modelers have an efficient and simplified means to publish new models. To demonstrate our approach, we developed five disciplinary models that can be integrated and shared to simulate a few of the ecosystem services (e.g., water storage, waterfowl breeding) that are provided by wetlands in the Prairie Pothole Region (PPR) of North America.Ó 2010 Elsevier Ltd. All rights reserved. Software availability

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A web-based GIS Decision Support System for managing and planning USDA's Conservation Reserve Program (CRP)

Cited by 97 publications

References 23 publications

A Simulation-as-a-Service Framework Facilitating Webgis Based Installation Planning

A Simulation-as-a-Service Framework Facilitating Webgis Based Installation Planning

Applying Landscape Science to Natural Resource Management

Prototyping an online wetland ecosystem services model using open model sharing standards

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