User:Hiner/sdss

Spatial decision support systems (sDSS) developed in parallel with the concept of Decision Support Systems (DSS).

An sDSS is an interactive, computer-based system designed to support a user or group of users in achieving a higher effectiveness of decision making while solving a semi-structured spatial problem. It is designed to assist the spatial planner with guidance in making land use decisions. For example, when deciding where to build a new airport many contrasting criteria, such as noise pollution vs. employment prospects or the knock on effect on transportation links, which make the decision difficult. A system which models decisions could be used to help identify the most effective decision path.

An sDSS is sometime referred to as a Policy Support System

A spatial decision support system would typically consists of the following components.
 * 1) A database management system - This system holds and handles the geographical data.  A standalone system for this is called a Geographical Information System, (GIS).
 * 2) A library of potential models that can be used to forecast the possible outcomes of decisions.
 * 3) An interface to aid the users interaction with the computer system and to assist in analysis of outcomes.

This concept fits dialog, data and modelling concepts outlined by Sprague and Watson as the DDM paradigm.

How does an sDSS work?
The tools usually exist in the form of a computer model or collection of interlinked computer models. Although many other land use change models are available, two types are particularly suitable for sDSS. These are constrained Cellular Automata (CA) models and Multi-Agent based models (MAS).

The interlinked models are used to use data from a GIS or equivalent and produce a likely outcome. By using two (or, better, more) known points in history the models can be calibrated and then projections into the future can be made to theoretically test decisions made by spatial planners. Using these techniques many possible decisions or combinations of decisions can be tested, to provide information for planners to make informed decisions.

A spatial region is mapped using some form of GIS. This can include topics such as land use, transportation, water management, demographics, agriculture, climate, employment.

Then a variety of models are applied to this land use pattern and projections are made leading to predicted land use potentials. These potentials are then met by use regional or national demand projections given a potential outcome based on the criteria set for the model.

To allow the user to easily adapt the system to deal with possible intervention possibilities an interface allows for simple modification to be made.

MOLAND
The aim of MOLAND is to provide a spatial planning tool that can be used for assessing, monitoring and modeling the development of urban and regional environments. The project was initiated in 1998 (under the name of MURBANDY – Monitoring Urban Dynamics) with the objective to monitor the developments of urban areas and identify trends at the European scale. The work includes the computation of indicators and the assessment of the impact of anthropogenic stress factors (with a focus on expanding settlements, transport and tourism) in and around urban areas, and along development corridors.

MOLAND web site

MURBANDY
The overall objective of MURBANDY is to provide datasets to study past and current land uses, to develop an Earth Observation based procedure to monitor the dynamics of Europe?s cities; to develop a number of "urban" and "environmental" indicators that allow to understand these dynamics and the impact these cities have on the environment, and finally to elaborate scenarios of urban growth.

MURBANDY web site

LUMOCAP
LUMOCAP aims at delivering an operational tool for assessing land use changes and their impact on the rural landscape according to a Common Agricultural Policy (CAP) orientation. It focuses on the relations between the CAP and landscape changes and emphasizes the spatio-temporal dimension of the former. The core of the tool is a dynamic Cellular Automata based land use model.

LUMOCAP web site

TiGrESS
The TiGrESS project evaluated the usefulness of Time-Geographical methods for understanding the relationships between environmental change and social-economic driving factors. We undertook three focussed case studies looking at problems of demographics and water resource planning (along the M11 corridor in the UK), the dynamics of the European urban network  (the whole of Europe) and sustainable agriculture and land-use planning (around Madrid).

TiGrESS web site