Development

Land-use changes are typically modeled using geographic information systems because of the spatial nature of the data. But the complexity of coupled human and natural systems and the fourth dimension involved with change over time and time-series data expose some limitations of GIS tools when used on their own. In this paper we present the application of REPAST, a free and open source geospatial Multi-agent Model (a.k.a. Agent-based Model or ABM) to the dynamic simulation of greenhouse gas (GHG) changes in a sub-watershed in Ontario, Canada with predominantly agricultural land use. The combination of Geospatial analysis and use of an Agent Based Model is a new way to solve complex problems involving multiple decision makers on the landscape. The combination of these modeling approaches helps to address the time dimension in geospatial modeling problems. ABM can model dynamic systems, their evolutionary changes and importantly, can predict options for sustainable system configurations. As a part of this research project, open source tools were developed to integrate ABM and GIS environments, specifically with respect to data transport and coupling of GIS and REPAST tools. In this paper we present scenarios to estimate the GHG emissions in an agricultural watershed, and the FOSS tools we both adopted and have been developing to undertake this project.

Numerical models, such as hydrodynamic and climate models, produce output with a large number of variables and a large number of grid cells and time steps. Further use of the resulting data products has been challenging, especially for further use outside the institute of origin. Due to the vastness of the data, simply downloading copies of data is impossible. Web services are therefore used to access subsets of the data. The most mature candidates for working with gridded data are OPeNDAP and WCS. Here we compare these two protocols to serve gridded data through the web.

In the framework of the new Dutch National Model and Data Centre (NMDC) a distributed data storage has been realized by coupling OPeNDAP servers (data cloud). A WCS service layer is provided for the same data. This allows us to compare OPeNDAP and WCS. Using several use cases, we compare the data model, terminology, features and usability, both for developers and end-users.

The data models show the different origin of the two standards. The OPeNDAP data model, called the common data model (CDM), is based on the merge of the data models from the NetCDF software, the HDF5 software and the OPeNDAP protocol. It is based around the use of multidimensional arrays. The Coverage data model uses a more abstract terminology, based on geospatial data types.

The terminology that the CDM uses is more closely related to the terminology used in numerical modelling. A grid of air pressure depending on latitude longitudes is called a DiscreteGridPointCoverage in the WCS terminology, while it is represented by the variables latitude, longitude and air_pressure with the attribute coordinates=”lon lat” and grid_mapping in the CDM model with the CF convention.

The Embrapa Agricultural Informatics, decentralized unit of the Brazilian Agricultural Research Corporation (Embrapa), is developing a system for environmental regulation and licensing, called SISLA - Interactive System Support for Environmental Licensing. At first, the system is being used by the state of Mato Grosso do Sul, and the peculiarities of the system to specifically meet this state are being developed in partnership with the Environment Institute of Mato Grosso do Sul (Imasul).

The SISLA was conceived with the use of free or open source tools, such as PostgreSQL and its spatial extension PostGIS, MapServer and i3Geo. Among its main features, stand out the analysis of georeferenced surrounding farms applicants for environmental licensing for projects; queries georeferenced of licensing procedures; and technical analysis of the licensing process. The first allows enterprising to check, quickly and simply by the Internet, the proximity or intersection of​ your property in relation to protected areas by the state government. The second allows managers to monitor the evolution of state licensing processes in the various municipalities that comprise the state. Finally, the third allows a visual analysis of the areas of licensing applicants for technical expertise as well as its comparison with other themes, including satellite imagery, in order to find irregularities that might impede the continuity of the process.