Logo GISdevelopment.net

GISdevelopment > Proceedings > ACRS > 1989


1989 | 1990 | 1991 | 1992 | 1994 | 1995 | 1996 | 1997 | 1998 | 1999 | 2000 | 2002
Sessions

Agriculture / Soil

Agriculture / Forestry

Water Resources

Education / Training

Forestry

Mapping from Space

Oceanography

Land Use

Digital Image Processing 1

Digital Image Processing 2

Geology

Environment

Integrated Remote Sensing and GIS for Natural Resources Management

National Papers

Poster Sessions
  • Poster Paper 1
  • Poster Paper 2



  • ACRS 1989


    Agriculture & Forestry
    Printer Friendly Format

    Page 1 of 3
    | Next |


    Establishment of landsat MSS spectral classes of fairly homogeneous tropical peat swamp forests by transect analysis on the Orser batch-oriented image analysis system

    A.B. Ismail
    Research Officer,
    Malaysian Agricultural Research and Development Institute (MARDI).
    GPO Box 12301. 50774 Kuala Lumpur

    B. J. Turner
    Reader. Department of Forestry,
    Australian National University, Canberra.


    Introduction
    The hydromorphic nature of peat areas in Malaysia render the conventional methods of survey based on extensive filed work ineffective methods of survey based on extensive field work ineffective due to difficult accessibility. Remote sensing with its wide synoptic format and variable spectral discrimination, offers an attractive alternative for this purpose. Past study using Landsat MSS data (MAHMOOD) et. al., 1983), however, indicated that spectral reflectance's within peat swamp forest in Peninsular Malaysia are fairly homogeneous.

    Peat swamps in Malaysia are formed in water saturated saucer-shaped basins. Therefore, peat thickness along the perimeter is thineer as compared to the centre of the basins. The differences in ecology is expected to influence the forest composition occurring in the areas. especially from the point of view of root anchorage and nutrient availability. Natural zoning of forest compositions around the centre of the basins if therefore anticipated. For peat swamps in Sarawak, there are indications of dome-shaped surface structure ( ANDERSON, 1964: LIONG and SIONG, 1979) and zoning of forest compositions around the domes ( ANON, 1957: BRUNIG, 1970).

    Variations in forest compositions are demonstrated by the differences in dominant species, which among others, have a different pigmentation and leaf structure. Variations in pigmentation are detectable in visible spectrum, and structural differences in the spongy mesophy11 layer of leaves are indirectly observable in the near infrared region ( RHODE. 1971; RHODE and OLSON. 1971). It is therefore expected that the variations in forest compositon can be Detected by spectral analysis of Landsat MSS data. Furthermore, these areas are fairly flat and hence the possibility of spectral variation due to topographic effect is minimal. As such, a study was undertaking to assess the effectiveness of Landsat MSS data in detecting spectral variations within fairly homogeneous peat swamp forests in Malaysia.

    Study areas
    Two peat swap basins, one in Pahang and the other in Sarawak, were selected for the study. They are expected to represent different peat environments occurring in Malaysia. Standard Computer Compatible Tapes (CCTs) for these areas were recorded by Landsat 3 (August 8, 1978) and Landsat 4 (June 27, 1985), respectively. Majority of the study areas were free of cloud cover.

    Data processing and analysis
    The MSS data were processed and analysed using the ORSER image analysis software system (TURNER et al., 1978) run on a VAX 11/780 computer at the Australian National University. The system, which urns on batch oriented mode, was developed at the Pennsylvania State University. USA. In the following discussion, the ORSER routines employed in the study are indicated in parenthesis. Visual display and hardcopy printouts were done using the UNIRAS software on Tektronix 4113 and 4695, respectively.

    Difficult accessibility of the study areas render the stud areas render the normal method of selecting training areas ineffective. Spectral analysis along several transects across the basins, however, is expected to give maximum possibility for detecting spectral variations. Hence, spectral classes can be manual established and then used as training areas for supervised classification routine.

    After subsetting (SUBSET) the study areas from the CCTs, bringhtness classification mapping (NMAP) was carried out to visually verify the respective peat swamp areas. This was followed by homogeneity classification (UMAP) in order of high contrast and their boundaries. Based on these information, and coupled with various collateral data such as the peat basins were identified. For maximum possible variations, those transects were aligned across the widest parts of the basins and extended from the inland hilly areas to the sea. Three transects for each study areas were chosen for further analysis.

    Page 1 of 3
    | Next |

    Applications | Technology | Policy | History | News | Tenders | Events | Interviews | Career | Companies | Country Pages | Books | Publications | Education | Glossary | Tutorials | Downloads | Site Map | Subscribe | GIS@development Magazine | Updates | Guest Book