Changing the land cover/ land use has serious environmental impacts affecting the ecosystem in Malaysia. The impact of land cover changes on the environmental functions such as surface water, loss water, and soil moisture is considered in this paper on the Kelantan river basin. The study area at the east coast of the peninsular Malaysia has suffered significant land cover changes in the recent years. The current research tried to assess the impact of land cover changes in the study area focused on the surface water, loss water, and soil moisture from different land use classes and the potential impact of land cover changes on the ecosystem of Kelantan river basin. To simulate the impact of land cover changes on the environmental hydrology characteristics, a deterministic regional modeling were employed in this study based on five approaches, i.e. (1) Land cover classification based on Landsat images; (2) assessment of land cover changes during last three decades; (3) Calculation the rate of water Loss/ Infiltration; (4) Assessment of hydrological and mechanical effects of the land cover changes on the surface water; and (5) evaluation the impact of land cover changes on the ecosystem of the study area. Assessment of land cover impact on the environmental hydrology was computed with the improved transient rainfall infiltration and grid based regional model (Improved-TRIGRS) based on the transient infiltration, and subsequently changes in the surface water, due to precipitation events. The results showed the direct increased in surface water from development area, agricultural area, and grassland regions compared with surface water from other land covered areas in the study area. The urban areas or lower planting density areas tend to increase for surface water during the monsoon seasons, whereas the inter flow from forested and secondary jungle areas contributes to the normal surface water.
This paper describes the application of the geostastistical method to quantify noise from a compact airborne spectrograhic imager (CASI) data set. Estimation of noise contained within a remote sensing image is essential in order to quanitfy the effects of noise contamination. Noise was estimated from CASI imagery by calculation the noise as the square root of the nugget variance, a parameter of a fitte semivariogram model. The signal-to-noise ratio (SNR) can then be estimated by dividing the mean vaue by the square root of the nugget variance. Three wavebands 0.46-049μm (blue), 0-63-0.64μm (red) and 0.70-071μm (near-infrared) were used in the analysis. A total of five land covers were selected, each representing a common land cover type in the area which are i)bracken ii)conifer woodland iii)grassland iv)heathland and v)deciduous woodland. The results shows that the noise varies in different land cover types and wavelengths.