The Conservation of Ground Water Levels in the Peat Swamp Forest at Ayer Hitam North Forest Reserve, Muar in Johor, Malaysia

The management of peat swamp forests in Malaysia contends with two major issues: forest fires and the effects of abandoned forest-logging drainage systems or canals. Forest fire occurs during low rainfall season related to the local people activities. The drainage networks change the hydrological function of the intact forest ecosystem. A key function of the hydrological system in the undisturbed forest is to absorb water during rainfall season, thus delaying downstream runoff and preventing flash floods. The objective of the project described here is to restore the hydrological function of peat swamp forest (PSF) at Ayer Hitam North Forest Reserve (AHNFR) in Muar, Johor, Malaysia. The oil palm plantations, especially in the southern part of the area affect the forest reserve. Water flows out of the forest reserve through the drainage system constructed for managing these plantations. In 2016 and 2017, two water block structures or check dams were constructed near the boundaries of the forest reserve to hold the water and raise the groundwater level in the forest reserve. The implementation of the check dams at the two locations has conserved the groundwater level and subsequently, about 1.2 million m3 of water was saved annually from leaving the forest reserve from each of the check dam. This project is also part of the Coca-Cola Company’s sustainability commitment for water strategy with the global that is to replenish 100% of the equivalent volume of water consumed in their products and production by 2020. Replenishment is the key sustainability commitment for the Company.

Mapping Deciduous Broad-leaved Forested Swamps Using ALOS/Palsar Data

Accurate, updated information on the distribution of wetlands is essential for estimating net fluxes of greenhouse gases and for effectively protecting and managing wetlands. Because of their complex community structure and rich surface vegetation, deciduous broad-leaved forested swamps are considered to be one of the most difficult types of wetland to classify. In this research, with the support of remote sensing and geographic information system, multi-temporal radar images L-Palsar were used initially to extract the forest hydrological layer and phenology phase change layer as two variables through image analysis. Second, based on the environmental characteristics of forested swamps, three decision tree classifiers derived from the two variables were constructed to explore effective methods to identify deciduous broad-leaved forested swamps. Third, this study focused on analyzing the classification process between flat-forests, which are the most severely disturbed elements, and forested swamps. Finally, the application of the decision tree model will be discussed. The results showed that: 1) L-HH band(a L band with wavelength of 0–235 m in HH polarization mode; HH means Synthetic Aperture Radars transmit pulses in horizontal polarization and receive in horizontal polarization) in the leaf-off season is shown to be capable of detecting hydrologic conditions beneath the forest; 2) the accuracy of the classification(forested swamp and forest plat) was 81.5% based on hydrologic features, and 83.5% was achieved by combining hydrologic features and phenology response features, which indicated that hydrological characteristics under the forest played a key role. The HHOJ(refers to the band created by the subtraction with HH band in October and HH band in July) achieved by multi-temporal radar images did improve the classification accuracy, but not significantly, and more leaf-off radar images may be more efficient than multi-seasonal radar images for inland forested swamp mapping; 3) the lower separability between forested swamps dominated by vegetated surfaces and forest plat covered with litter was the main cause of the uncertainty in classification, which led to misleading interpretations of the pixel-based classification. Finally, through the analysis with kappa coefficients, it was shown that the value of the intersection point was an ideal choice for the variable.