1. The Integrated Forest Resources Information System

2. FUNCTIONS OF IFRIS IFRIS is the storehouse of data on the natural forests of Indonesia, collected by FIMP and other projects and agencies. IFRIS is an information system on Indonesian forests, providing users in the forest sector with structured and easily accessible data relevant to forest planning and management. IFRIS contains information such as topographic, land-cover, biological and socio-economic data which is not restricted to forest applications, but may be of value to planners in other fields. IFRIS is a dynamic database, upgraded and added to periodically, and users will have access via the Internet and regular upgrades on CD ROM.

3. IFRIS CLIMATE SOCIO- ECONOMIC FAUNA TOPOGRAPHY TREES SOILS GEOLOGY PICTURES IMAGES VEGETATION MAPS FLORA

4. Satellite images, usually Landsat Thematic Mapper, but also sometimes SPOT,are purchased and geometrically corrected for all study areas These images are used to prepare vegetation maps, to check distribution of roads and settlements, and as a background to other maps in IFRIS

5. Vegetation maps at 1:50,000 scale are prepared for all study areas. These maps are interpreted from satellite imagery with extensive field-checking Up-to-date maps of the extent of primary, logged over and secondary forest, as well as agricultural land-cover, are essential to proper planning and management of forest resources

6. Digital contour, spot-height and drainage maps at a scale of 1:50,000 are purchased from BAKOSURTANAL. Digital elevation models with a cell-size of 50 metres are prepared from this topographic data. Topography is important in all aspects of land use planning. It plays a major role in determining land suitability and risk of erosion and controls access routes and settlement patterns. Elevation influences the local climate, and thus the vegetation, both natural and cultivated.

7. Slope maps are generated from digital elevation models using specialised computer software. Slope maps quantify topography. Legislation for forest classification and many other types of land use incorporates slope categories as an important factor. Slope maps give a visual indication of potential problem areas.

8. Land facets are an alternative way of classifying the landscape into discrete physiographic units. Land facet maps are prepared from digital elevation models using computer software developed by FIMP. Land facets are not used in current legal classifications of the landscape in Indonesia. Current research has indicated correlations between forest characteristics and land facets. In this map, ridges are coloured red, upper slopes in yellow, mid slopes in blue and lower slopes in green. Flat land in valleys is coloured purple.

9. River catchment boundaries can be generated automatically from the digital elevation model using special computer software. This map shows catchment boundaries in black superimposed on a vegetation map. Identification of catchments is important in soil erosion and forest conservation management, and allows prediction of the downstream effects of headwater degradation.

10. Maps of current forest land categories are obtained in digital form from provincial Forest Ministry offices Forest land category maps are based on the extent of forest cover, the boundaries of protected areas and logging concessions, and topography. The data in IFRIS can be used to update these maps.

11. Published 1:250,000 scale geological maps have been digitised for the four provinces of southern Sumatera Geology is an important factor determining soil types and topography

12. Climate data (rainfall and temperature) has been compiled and processed by FIMP for the period 1960-1990 for all of Indonesia. This data can be presented in the form of maps and graphs. Mean annual rainfall, the number of dry months per year, and the minimum mean monthly temperatures are important factors which determine the character of natural vegetation. This map shows mean annual rainfall in purple and blue, and low temperatures in the mountains as blue shading

13. FIMP has sampled six clusters of forest sample plots in Bengkulu province. In each cluster there are 45 sample plots, each 100 metres by 10 metres, spaced about 100 metres apart on three or four transects. Every tree >10 cm DBH is recorded, soil sampled in each plot, and fauna identified in and near plots. Plot clusters in Bengkulu province in black. The locations of sample plot clusters are selected by a stratification technique so as to cover the whole range of climatic, geological and topographic variation within a given elevation range

14. IFRIS allows the simultaneous viewing of plot maps and 3D trees.

15. One soil sample site is selected in each forest sample plot, and the individual soil horizons measured and sampled. Data on physical and chemical properties of soils can be accessed through views in IFRIS. These pie diagrams, one for each sample plot, show the relative proportions of sand, silt and clay in soil samples from the “B” soil horizon. Similar maps can be prepared for many different characteristics of each of the soil layers. Three-dimensional graphs allow examination of the variations in physical and chemical properties of soils both between sites and vertically through the soil profile.

16. Using a programme developed by FIMP, a species of mammal or bird can be selected from a list. The localities where the selected species has been recorded are highlighted in yellow. Data on fauna (mammals, birds, reptiles) have been collected from 18 clusters of forest sample plots in the 4 provinces of southern Sumatera.

17. Other themes in IFRIS provide quantitative information where this is available. This map shows the total number of bird species recorded at each the 18 sites.

18. This map shows the abundance of siamang (Symphalangus syndactylus), in terms of the number of individuals per square kilometre, at the forest sample plot sites.

19. Socio-economic data has been collected by FIMP from 51 villages in Bengkulu province. The villages are all close to the forest edge, and in the vicinity of FIMP forest sample plots. Data has been collected at the village level, using information from the Kepala Desa and the BKKN, supplemented by surveys of randomly selected households. This map shows the locations of villages sampled in Bengkulu

20. Socio-economic data collected by FIMP can be accessed in IFRIS through a series of graphical interfaces. Clicking on a village in the map view displays selected data from that village in a series of graphs.

21. Comparisons between villages are more clear in maps than in interactive graphs. Four types of socio-economic data from the FIMP study area in northern Bengkulu are displayed here.

22. As well as village level data, the socio-economic survey includes interviews of randomly selected households. Aggregated household data for each village is displayed graphically in this interactive view.

23. As with the village-level socio-economic data, some of the household data is better suited to map display. This view shows some examples.

24. Pictures taken in the field are incorporated in IFRIS, accessed through “Hot Links” from maps

25. 3D views of the landscape are prepared by combining satellite imagery and a Digital Elevation Model. These are accessed via “Hot Links” in IFRIS. This view shows coal mines (pale blue) at the foot of the Bukit Barisan inland from Bengkulu.

26. CONCLUDING REMARKS The Bengkulu IFRIS is a sub-set of the full national IFRIS, and contains a very wide range of data relating to the natural forests of Bengkulu and their environment. The user interface of IFRIS is designed to be easy to use, and the data in IFRIS is presented so as to maximise the information content without restricting the possibility for more specialised users to further process data themselves. Users of IFRIS do not require the most advanced “state-of-the-art” computers. The system is designed to run at acceptable speed on standard modern desk-top computers. Data in IFRIS is currently restricted to the province of Bengkulu and five FIMP study areas in the remaining three provinces of southern Sumatera. Geographic coverage will expand as FIMP progresses to other provinces and as provincial MOFEC offices start to generate new data.