Dr Shirish Ravan
Team Coordinator, Geomatics Group
C-DAC, Pune
[email protected]
Computer based Decision Support System (DSS) has been a popular concept since the emergence of Information Technology. Database technologies such as DBMS/RDBMS hosted on powerful computers have been adopted to prepare decision support systems in various application areas. The biodiversity conservation planning is no exception. Conservationists and decision makers have been involved in generating huge databases on the species, its status, habitats, socioeconomic impacts, threats to its existence etc. Such alpha-numeric information gives scientific basis for decision making. However, with the availability of spatial data from remote sensing and advances in Geo-informatics, we are witnessing the paradigm shift from ‘conventional’ Decision Support System to the Spatial Decision Support System.
Spatial Decision Support System (SDSS)
Till the availability of spatial information from remote sensing data, not much thought was given to the ‘spatial’ dimension to DSS. In fact, any decision involving conservation issues invariably considers geographical parameters such as location, distance, direction, proximity, adjacency, topography etc. and there was long pending demand for providing ‘Spatial Dimension” to the alpha-numeric decision support system dedicated to biodiversity conservation.
Thus, we describe framework ‘Spatial Decision Support System’ (SDSS) as below:
- It is computer based information systems which offers decision making capabilities based on integration of alpa-numeric information with geographical parameters
- It models spatial processes using geographical parameters
- It allows to perform series of spatial analysis to generate new information
- It allows to perform interactive, iterative and systematic
- process of decision making
- It captures the decision making rules and filters voluminous information based on decision making criteria
- The resultant information is depicted essentially in the form of maps. Representation of information in textual/table/graphical form is also an integral feature.
Components of Spatial Decision Support System
Spatial Database
This is the most crucial and specialized component. Satellite remote sensing is the major spatial data provider in real or near real time. Remote sensing data can be interpreted in many ways and provides lots of inputs for biodiversity conservation. Information that can be directly interpreted from images include forest cover mapping, forest type mapping, crown density mapping, ecosystems mapping (such as wetland) etc. Digital nature of satellite data allows providing information on quantitative aspects of forests such as estimation of biomass, productivity, leaf area index etc. However, DSS needs much more spatial information such as locations of the important species, hotspots, habitats, administrative boundaries, management zones etc. Huge amount of non-spatial information (such as taxonomic details) goes in as attribute parameters. The major issue is the seamless integration of information from a variety of sources. This aspect is taken care by most of the commercially off the shelf (COTS) GIS tools adhering to the standards of Open GIS Consortium (OGC).
The software engine
The most efficient way of preparing SDSS is to customize COTS GIS softwares. Advantages of using COTS GIS are:
- It offers ready tool for display of spatial information
- It offers ready algorithms for ‘often required’ spatial analysis and modeling
- It offers ready tools for query and information retrieval
- Standard COTS GIS are OGC compatible and ensures data flow from one platform to another.
- COTS GIS are open for customization using their own macro-language or standard development tools such as visual basic.
Decision support
Based on strength of COTS GIS, DSS component can focus on:
- Development of spatial algorithms specific to biodiversity conservation (e.g. landscape characterization using spatial indices such as fragmentation, interspersion, juxtaposition)
- Development of models based on domain knowledge (e.g. Production Efficiency Models or Empirical Relationships Models between ecological parameters)
- Development of routines to perform series of analysis in desired sequence
- To programme decision rules so as to present information in ‘summary’ form to the decision makers
- The most important and appealing part is development ‘Graphical User Interface’ (GUI) so as to ensure effective use of system by decision maker without going in depth to the background processes.
SDSS can be hosted on Web for the purpose of extending benefits to remote users. Thanks to the commercially available Web-GIS Servers which provides technology to offer benefits of SDSS to internet users.
Why Spatial Decision Support System
Spatial databases and Geomatics technology have been exploited by the conservationists/scientists in India to the great extent and potential of technology has been demonstrated in multiple aspects of conservation studies discussed below. Discussion aims at offering benefits of scientific methods and models in the process of decision-making.
Forest mapping and monitoring changes: Nationwide mapping of the forest was demonstrated first by the National Remote Sensing Agency and subsequently taken up as scheduled task by the Forest Survey of India. ‘State of Forests’ is valuable publication by Forest Survey of India, which provides authentic information on status of forest cover in India. Forest cover map is readily available information for defining PA boundaries, planning ecological corridors, performing environmental impact assessment for development projects. Decision support systems can be built around temporal database on forest cover so as to highlight areas under drastic changes.
Biomass and productivity estimation: Biomass and productivity models have been developed and tested by the researcher Indian Institute of Remote Sensing and National Remote Sensing Agency. Well-tested models can become part of Decision Support System, thus offering rapid and customized methods for biomass and productivity estimation for providing inputs to decision-makers to deal with global issues such as global warming and understanding carbon flux.
Landscape level assessment: Landscape level assessment provides in-direct method to assess ecological status of forest. The analysis is purely based on the forest cover/type map prepared from remote sensing data. The models developed based on the ‘Principles of Landscape Ecology’ provides rapid assessment, with limited ground observation. Thus, one can study fragmentation, energy within patches, and ecological status of given forest patch vis-à-vis neighbouring landuses etc. The work done at Indian Institute of Remote Sensing has resulted in development of standard methodology to assess forest at landscape level.
Biodiversity characterisation: Concept based on Geomatics differs from traditional methods of inventorying the flora and fauna in certain locations. The biodiversity characterization using Geomatics takes into account much wider aspects by analyzing threats to the biodiversity in long-term, thus decides places where biodiversity will sustain for longer period. The model works on the ‘Principles of Landscape Ecology’, integrated with field based inventory of flora/fauna. Thus resultant maps show spatial distribution of biodiversity richness.
Wetland conservation planning: Although wetland mapping has been carried out at 1:250,000 scale, many more small wetlands have not been mapped and nation-wide prioritization of wetlands has concluded that as many as 700 wetlands do not have any data of use for prioritization. Development of GIS database on network of wetlands make lots of sense to prioritize inland wetlands for a network of protected areas. The initiative taken up by Salim Ali Centre for Ornithology and Natural History towards providing basic information on wetland is helpful to build GIS based Decision Support System for wetland conservation.
Habitat suitability analysis: Habitat is governed by set of parameters such as vegetation type, forest cover density, arrangement of forest and other landuses measured as patch configuration, isolation, interspersion, juxtaposition etc. Researchers have exploited multicriteria analysis and spatial modeling techniques to analyse habitat suitability and wildlife corridor analysis. Corridor assessment using Geomatics has already been demonstrated in and around landscape of Kanha Tiger Reserve by Wildlife Institute of India.
Forest fire modeling and mitigation planning: Use of Geomatics based Decision Support System has two aspects towards management of forest fires. First one focuses on modeling the spatial data to identify fire prone places, whereas as the latter focuses on providing near-real time information on forest fire spread. First one provides inputs for preparedness, while latter provides information for controlling fire. Both aspects are important and provide valuable inputs for decision making in order to save forest damage due to fires. Space Application Centre has provided near-real time forest fire monitoring to the forest department in Gir Forests of Gujrat.
Protected area networking: Protected areas maintain biodiversity by maintaining the habitat and ecosystem processes that species require for their existence. However, the habitat requirements of most species are not known. For this reason an individual-species approach to habitat conservation is unworkable. Protected areas that are isolated from each other, and function as habitat islands, are prone to the loss of species. To ensure ecological integrity, connectivity among protected areas must be maintained in order to maintain biodiversity within the system of reserves. Connectivity reduces the risk of species loss. Managing protected area network of large country like India calls for GIS based Information System to study distribution of protected area in a given landscape.
Eco-development planning: India Ecodevelopment Project was conceived as a pilot project in June, 1994, on the basis of an Indicative Plan prepared by the Indian Institute of Public Administration on behalf of the Government of India after the study of eight sites selected by the Ministry of Environment and Forests. Keeping in view the primary objectives of satisfying the basic need of local people and improving the productivity of buffer zone of protected areas, various socio-economic welfare activities are envisaged in eco-development programme. Many of these call for inputs from Geomatics Technology, mainly to identify site suitability for raising of fuel-wood and fodder plantations, soil water conservation structures, irrigation dams and drinking water targeting,
While appreciating potential of technology, it may be noted that technology has not been received in totality by the decision makers and implementers, who are responsible for executing biodiversity conservation plans in the field. Spatial Decision Support System offers the system, which captures knowledge of scientists / conservationists and requirements of decision makers. In order to translate efforts of scientists / conservationists / technologists in reality, the role of Spatial Decision Support System is enormous.
