Data Acquisition through Remote Sensing for Management Planning of National Parks and Protected Areas
Study Area
Two sample areas were selected from the list of protected areas, both in the dry to semi-dry zones of Sri Lanka. the area (1) northern part of Wasgamuwa National Park, E longitudes and (2) Kahalla-Pallekelle sanctuary situated in the districts of Kurunegala and Anuradhapura between 285 and 307 N latitudes and 163 and 168 longitudes.
Methods:
The study methods included the visual interpretation of Landsat imagery, spot imagery the scale 1:50,000 of HRV 2 XS (1996) interpretation of aerial photo of 1:20,000 of the same areas, and computer-aided IRS data analysis. The digital computer-aided analysis involved machine -aided "training field selection" or "non supervised spectral response resorted to. A limited field surveys and other secondary data were used to verify the computer aided classification and visual interpretations.
Results and Discussion
Geomorphology and Landform
The visual interpretation of Landsat imagery and false colour composite maps provided useful information on landform for both study areas. However, only the very distinct geomorphic units such as high relief ridges and hills were easily identified. The more subdued landform such as river levees, rock knob plains and inland valleys were not conspicuous in the images use, therefore,
such features are not identified.
The aerial photo interpretation provided more detailed information on important landform features. In the study area (1) the river levees, rock knob plains and ridges which are very important feature in distinguishing wild life habitat types were conspicuous and were easily mapped.
Soils
Digital processing of IRS data or visual interpretation of spot imagery could not identify the soil variations on land slopes. Also the residual from alluvial soils could not be separated by this methods. for semi-detailed mapping of soil variations in small areas such as few thousand hectares of protected area, low altitude aerial photography proved to be the most useful.
Hydrology
Except for the linearity of the geologic features, the structural information on the geologic formations could not be inferred. There are not distinct lineaments present in the study areas. The high relief of ridges and low density of dissection suggest that the ridges are formed of rocks resistant weathering. The MSS band 7 image showed very low stream density. These geologic features in sample areas are very well covered with vegetation. Therefore, it is possible that the rainfall runoff is low and much of the rainfall is infiltrated through the ridge surface. These geologic features should, therefore act as a ground water reservoir, and that water should emerge at the base of the ridges. During the field surveys the existence of a series of springs along the foot of the ridges were observed and confirmed the inferences drawn from the visual interpretation of the remote sensing data.
Vegetative Cover types
The computer-aided analysis of the IRS data by the unsupervised method of training field selection in the first instant classified the spectral response into six ecological classes. This resulted in the division of the dense forest vegetation into two different spectral signature classes. The dense forest vegetation on the west face of the ridge, which had the shadows of the ridges at the time of the data acquisition had the same spectral class as the agriculture field in the adjacent areas. The other spectral class included all the forest types, i.e. dense forest, open forest and grasslands with sparse tree cover (Damana or dry savanna).
