Evaluation of environmental functions of tropical forest in Kinabalu Park, Sabah, Malaysia using GIS and remote sensing techniques: Implications to forest conservation planning

Environmental functions of tropical forest can serve as criteria for forest conservation planning in the tropics. The objective of this study is to evaluate the environmental functions of tropical forest in Kinabalu Park, Sabah, Malaysia, using GIS and remote sensing techniques. Field data, statistical data, including weather data with geographic localities, maps and satellite image are collected. Linear regression models are developed for forests of different geological substrates, based on the relationships between altitude and biodiversity (Fisher’s alpha index). Biodiversity conservation function map is derived with the statistical models and a digital elevation model. Coupling with extensive literature review, an evaluation matrix for evaluating soil and water conservation functions including landslide prevention, flood prevention and drought prevention functions, is constructed. To evaluate the soil and water conservation functions, a weighted linear combination method is used with GIS layers of topography, geology, soil depth, rainfall and slope. Forest areas in Kinabalu Park are derived with land cover mapping using Landsat-TM image. Areas having high values of biodiversity conservation, flood and drought prevention functions are covered with mainly lowland rain forest. On the other hand, areas with high values of the landslide prevention function are covered with mainly subalpine forests. Using the environmental functions, a conservation index is computed to represent forests that are important to conservation. Based on theCI, the lowland rain forest receives highest priority in protection. In fact, it is located in the boundary areas of the park and thus exposed to illegal activities

Relationships between crown size and aboveground biomass of oil palms: an evaluation of allometric models

Oil palms (OP) in Sabah, Malaysia were studied to explore the relationship between canopy size and aboveground biomass (AGB). Four available allometric equations were used to calculate the dry AGB. Pearson’s correlation analysis was performed between crown diameter (CD) and crown area (CA) towards the variables of AGB, height and dbh. In this analysis, the transformation to natural log of variable resulted in better coefficient compared to the original one. The mean of various variables such as height (stem, total and height difference), biomass (crown, trunk and total), dbh (inner and outer) and number of petiole leaf were calculated based on 32 independent sample plots (N = 222 palms) across various age stages from 2 to 24 years. These variables were regressed against CD and age. AGB versus CD was a nonlinear with R2 ranging from 0.950 to 0.975. Random modelling and cross validation between AGB and CD was applied at the ratio of 70:30. Upon checking, the best estimation was achieved by using the allometric equation based on total height due to the lowest relative root mean square error (RMSE) (18.5%) and the least fluctuation between predicted and actual AGB. The other three models had relative RMSE that ranged between 23.9 and 68.8%. This study shows that AGB can be estimated using CD of OP consistently at all ages

Deforestation detection in Kinabalu Area, Sabah, Malaysia by using multi-sensor remote sensing approach

This paper examines use of multi-sensor remote sensing approach for deforestation detection in the tropics. Multi-sensor satellite data of Landsat-MSS of 1973 and Landsat-TM of 1991 and 1996 were employed. Accuracy of image-to-image registration was below 1 pixel. Relative radiometric normalization of Landat-MSS 1973 and Landsat-TM 1991 to Landsat-TM 1996 as the reference image was carried out to remove the unwanted variabilities between all the satellite images. Image differencing algorithm with Normalized Difference Vegetation Index (NDVI) was examined for deforestation detection. The performance of the NDVI image differencing algorithm for deforestation detection between 1973 and 1996 was investigated at three test sites covered with reliable ground truths. The accuracy of detection was satisfactory that the algorithm was used in deforestation detection of the whole study area in two change periods i.e. I: 1973-1991 and II: 1991-1996. Although false deforestation pixels in period I were also detected, it can easily be rectified using a land use map of 1984. In total, 2,445ha of forest, which is almost 1% of the study area, were cleared from 1973-1996 and most of them were deforested in period I (2,090ha). This study concludes that the multi-sensor approach is a useful solution for deforestation detection because of better temporal coverage. It can also provide more satellite data for the application and thus lessen data acquisition problem due to cloud cover which is a consistent problem for the tropics

Modeling the Natural Occurrence of Selected Dipterocarp Genera in Sarawak, Borneo

Dipterocarps or Dipterocarpaceae is a commercially important timber producing and dominant keystone tree family in the rain forests of Borneo. Borneo's landscape is changing at an unprecedented rate in recent years which affects this important biodiversity. This paper attempts to model the natural occurrence (distribution including those areas with natural forests before being converted to other land uses as opposed to current distribution) of dipterocarp species in Sarawak which is important for forest biodiversity conservation and management. Local modeling method of Inverse Distance Weighting was compared with commonly used statistical method (Binary Logistic Regression) to build the best natural distribution models for three genera (12 species) of dipterocarps. Database of species occurrence data and pseudoabsence data were constructed and divided into two halves for model building and validation. For logistic regression modeling, climatic, topographical and edaphic parameters were used. Proxy variables were used to represent the parameters which were highly (p>0.75) correlated to avoid over-fitting. The results show that Inverse Distance Weighting produced the best and consistent prediction with an average accuracy of over 80%. This study demonstrates that local interpolation method can be used for the modeling of natural distribution of dipterocarp species. The Inverse Distance Weighted was proven a better method and the possible reasons are discussed

Extracting oil palm crown from worldview-2 satellite image

Oil palm (OP) is the most commercial crop in Malaysia. Estimating the crowns is important for biomass estimation from high resolution satellite (HRS) image. This study examined extraction of individual OP crown from a WorldView-2 image using twofold algorithms, i.e., masking of Non-OP pixels and detection of individual OP crown based on the watershed segmentation of greyscale images. The study site was located in Beluran district, central Sabah, where matured OPs with the age ranging from 15 to 25 years old have been planted. We examined two compound vegetation indices of (NDVI+1)*DVI and NDII for masking non-OP crown areas. Using kappa statistics, an optimal threshold value was set with the highest accuracy at 90.6% for differentiating OP crown areas from Non-OP areas. After the watershed segmentation of OP crown areas with additional post-procedures, about 77% of individual OP crowns were successfully detected in comparison to the manual based delineation. Shape and location of each crown segment was then assessed based on a modified version of the goodness measures of Möller et al which was 0.3, indicating an acceptable CSGM (combined segmentation goodness measures) agreements between the automated and manually delineated crowns (perfect case is '1')

Estimation of stand volume of conifer forest: A Bayesian approach based on satellite-based estimate and forest register data

This paper highlights some problems underlying the gathering of stand volume information by forest register and the estimation of stand volume using satellite data. It was found that volume information from the forest register (Vreg) underestimates the actual stand volume. Satellite data is a promising source for estimating stand volume on a large‐area basis, but stand volume estimation remote sensing still suffers from the problem of large variations due to unwanted noise. We present a Bayesian approach that combines stand volume estimates from remotely sensed data (Landsat‐TM) and forest register. Pure Sugi (Cryptomeria japonica D.Don) forest stands were delineated using orthophotographs and forest information such as compartments, sub‐compartments and roads from a Geographic Information System (GIS) database. Pattern decomposition method (PDM) was used to derive remote sensing indices (vegetation, soil, and water indices), which were used for estimating stand age. Stand volume was indirectly estimated from remotely‐sensed data (VRS) through the use of stand age. A Bayesian estimate of stand volume by age class (VB) was performed by assuming the Vreg and VRS as a priori probability distribution and random sample distribution, respectively. The Bayesian approach was found to improve the volume estimate from the forest register. In this way, the widely available forest register can be effectively used together with remote sensing data for estimating stand volume, an approach that is potentially useful for monitoring stand volume on a regional or national scale

Carbon stock estimation of agroforestry system in Tawau, Sabah

Studies on total aboveground carbon (TAC) and belowground carbon (TBC) stock has been conducted in Balung Plantation, Tawau, Sabah. The main objective of the study was to determine the above and below ground carbon stock in agroforestry system. The combination of agroforestry systems with different ages were investigated, which is oil palm (25 years) and agarwood (7 years), oil palm (20 years) and agarwood (7 years), and oil palm (17 years) and agarwood (5 years). Monoculture of oil palm (16 years) and Tawau Hill Park forest reserve was set as control. A random systematic sampling method was used in conducting field inventory and soil sampling. The size of the sampled area in agroforestry and monoculture is 3 × 50m × 50m, while for forest reserve, the sampled area is 3 x 30m x 30m. Allometric equations were used to calculate the stand biomass. Sampling for organic and shrub layers were collected in a square frame (1m × 1m). Soil samples and bulk density was collected from three different layers which are 0 – 5 cm, 5 – 10 cm and 10 – 30 cm in randomly located sites within the plots. Soil samples, organic and shrub layer were analyzed using CHN628 series for carbon content. Result shows that the amount of total carbon stock in agroforestry was 79.12 tan C ha-1, 85.39 tan C ha-1 and 78.27 tan C ha-1, respectively. Monoculture of oil palm (16 years) has 76.44 tan C ha-1 while Tawau Hill Park forest reserve has total carbon stock at 287.38 tan C ha-1. Forest reserve stand has the highest total carbon stock compared to agroforestry and monoculture systems. But, in terms of soil carbon, forest reserve has the lowest TBC compared to agroforestry and monoculture systems. ANOVA was conducted to explore the impact of planting systems on total carbon stock. There was a statistically significant difference at the p < .05 level for soil carbon, living tree and organic layer between agroforestry, monoculture and forest reserve. Good crop and fertilizer management in agroforestry and monoculture systems helps in increasing soil organic carbon (SOC)

Aboveground carbon stock potential of teak (tectona grandis) under different land use system in Balung plantation, Tawau Sabah

Assessment of aboveground carbon stock in different teak plantation systems was conducted in Balung River Plantation, Tawau, Sabah. The objective of this study is to determine the potential of teak as the main tree components to increase the above ground carbon stock in different land use system. The above ground carbon stock of agroforestry and mixed plantation system of teak (Tectona grandis) were compared with natural forest and monoculture plantation of the species. The agroforestry combinations investigated are agroforestry system 1, teak (18 years) with snake fruit (8 years) and agarwood (8 years); agroforestry system 2, teak (17 years) with coffee (14 years); and also mixed timber plantation system, teak (18 years) with agarwood (8 years); while 20 years teak monoculture plantation and natural forest reserve was set up as a control. A random systematic sampling method was used in conducting field inventory. The methodologies used include the measurement of height and diameter breast height (DBH) of trees within a 50 m x 50 m plot dimension (for plantation) and 30 m x 30 m (forest). Allometric equations were used to derive the field measured attributes into stand biomass while carbon stock was estimated as 50 percent from the total biomass. The result shows the accumulation of carbon stock goes in the following order: forest reserve (213.84 t C/ha) > mixed timber plantation (69.94 t C ha-1 ) > agroforestry system 2 (37.75 t C/ha) > agroforestry system 1 (37.34 t C/ha) > teak monoculture (34.53 t C/ha) witnessing the teak trees to increase the total aboveground carbon stock in agroforestry and mixed timber plantation system by more than 60 percent. This study suggested that teak has great potential in transforming a low biomass land use into a carbon-rich tree based systems

Conservation gap analysis of dipterocarp hotspots in Sarawak using GIS, remote sensing and herbarium data

Dipterocarpaceae is the dominant tree family in the tropical rain forests of Southeast Asia. Borneo is the centre of diversity for the dipterocarps. Identification of hotspots is important for forest and biodiversity conservation efforts. Species Occurrence Models (SOMs) were generated for all 247 species of dipterocarps recorded in Sarawak using herbarium occurrence data and based on the best model selected. The species occurrence density map for each genus and category (endemic and non endemic) was generated by overlaying the SOMs of all species in each genus or category. The species occurrence density maps were analyzed with land cover map from Landsat 7-EMT+ images and protected forest areas for identifying hotspots for conservation in Sarawak. Overlaying the SOM maps revealed that areas in central Sarawak and the southwest region (northwest Borneo around Kuching) are the main hotspots of dipterocarp diversity in Sarawak while the coastal lowland areas in the lower Rejang and Baram River which are mainly peat swamp forest are poorer in species occurrence density. In terms of endemism, as with dipterocarp diversity, the mixed diptercarp forest of central Sarawak is also the most important hotspot. Gap analysis revealed that most protected forest areas are in southwest Sarawak (Bako, Kubah, Tanjung Datu and Gunung Gading National Parks) and in the northern part of Sarawak (Niah, Lambir Hills and Mt Mulu National Parks). This leaves the hotspot in the central part of Sarawak least protected. Protected areas only cover between 2 and 4% of the total areas for the different hotspots (75% species density) while majority of the hotspots that are still forested are outside the protected areas

Relationships between canopy Size and aboveground biomass of oil palms: an evaluation of allometric models

Oil palms (OP) in Sabah, Malaysia were studied to explore the relationship between canopy size and aboveground biomass (AGB). Four available allometric equations were used to calculate the dry AGB. Pearson’s correlation analysis was performed between crown diameter (CD) and crown area (CA) towards the variables of AGB, height and dbh. In this analysis, the transformation to natural log of variable resulted in better coefficient compared to the original one. The mean of various variables such as height (stem, total and height difference), biomass (crown, trunk and total), dbh (inner and outer) and number of petiole leaf were calculated based on 32 independent sample plots (N = 222 palms) across various age stages from 2 to 24 years. These variables were regressed against CD and age. AGB versus CD was a nonlinear with R2 ranging from 0.950 to 0.975. Random modelling and cross validation between AGB and CD was applied at the ratio of 70:30. Upon checking, the best estimation was achieved by using the allometric equation based on total height due to the lowest relative root mean square error (RMSE) (18.5%) and the least fluctuation between predicted and actual AGB. The other three models had relative RMSE that ranged between 23.9 and 68.8%. This study shows that AGB can be estimated using CD of OP consistently at all age