Digital Elevation Model (DEM) is a digital representation of ground surface topography or terrain. There are many freely available DEM data with a spatial resolution of 30 m to 90 m. Nevertheless, their vertical accuracy may vary, depending on the vegetation cover and terrain characteristics. This study examined the vertical accuracy of open-access global DEMs (ALOS PALSAR, ASTER GDEM3, SRTM, TanDEM-X) and fused DEM (EarthEnv-DEM90, MERIT DEM). Their performances were assessed using a Digital Terrain Model (DTM) generated using airborne LiDAR data that had an outstanding absolute vertical accuracy (mean error (ME) = 0.24 m; root mean square error (RMSEz) = 1.20 m). Height differences between the global DEMs and the LiDAR DTM were calculated and examined their performances by forested vs. non-forested, slope, and elevation classes. The results showed the MERIT DEM was superior to other DEMs in most of the testing methods. It outperformed other DEMs with an RMSEz value of 3.02 m in the forested areas, followed by ALOS PALSAR (9.29 m), EarthEnv-DEM90 (9.40 m), SRTM (9.80 m), TanDEM-X (10.41 m), and ASTER GDEM3 (12.57 m). The MERIT DEM also had the best accuracy in the higher elevation areas. Overall, the ASTER GDEM3 had the worst accuracies, with relatively large over-estimations compared to other DEMs. Despite its low spatial resolution, the MERIT DEM was the best for representing terrain elevation for applications over a large area.

Wood density (WD) is a critical determinant of estimating forest above-ground biomass (AGB) and carbon stock. Thus, heterogeneity in WD on individuals within species trees needs to be scrutinized, and acquisition of fixed WD value is essential to estimate carbon stock with confidence. This study investigated intraspecific variation in WD of Syzgium sp., also known as “Jambu” or “Kelat”. It is the most occurring species in study areas, and is regarded as an economically important species. Firstly, one half-diameter drilling from bark-to-pith measurement was taken per tree using Rinntech Resistograph R650-ED at breast height. Meanwhile, 5.15 mm-diameter core was sampled at 1.30 m above-ground, with DeWalt DCF899HP2 20V impact wrench 950 Nm and Haglöf increment borer. WD was estimated for each core sample using a dimensional method. Drilling resistance (DR) profiles were processed using DECOM 2.38m1 Scientific (c), and several independent variables were extracted from the resistogram. All resistogram-derived variables were positively correlated with field WD (R: 0.2 – 0.70). In addition, variability on WD in Syzgium sp. population is predominantly explained by the Resistograph amplitude, expressed as mean raw scale of adjusted DR (DR adj.RawSC) in a regression model. Given that intraspecific variation in WD is a crucial conjecture in forest AGB estimation, it is recommended to analyze with larger samples, and in-depth exploration on Resistograph-based variables is deemed to improve the accuracy of WD prediction models.

Earthquake is one of the most destructive natural disasters, which cause immediate and long-term changes to the river systems. This research aimed to examine the immediate and five-year impacts of the 2015 Ranau Earthquake (6.0 Mw) on river systems in Malaysian state of Sabah, a region of low earthquake hazard. We used object-based classification on Landsat 8 (2014 and 2015) and Sentinel-2A (2020) satellite imageries to derive land cover time series for investigating the impacts on the riparian areas. The earthquake removed vegetation in the riparian zones of four rivers, the highest being the Penataran River (69.21 ha). During the immediate impact period (2014-2015), river bar formation occurred in all rivers, with the largest increase occurring in the Kadamaian River (56.97 ha), followed by the Panataran River (54.36 ha), which had no river bar before the earthquake. The river bar of the Kadamaian River continued to increase, whereas the river bar of the Panataran River decreased five years after the earthquake. Land cover transition analysis revealed that 78.39 ha of vegetation, barren land, and river water areas changed to river bars in the Kadamaian riparian area during the immediate impact period. Except for 26.87 percent of river bars in the Kadamaian riparian area in 2015, most river bars transitioned to other land cover types five years later. During the period of immediate impact, 22.05 ha of vegetation and 10.71 ha of river water were transformed into river bars along the Penataran River. Five years later, except for 16.2 ha, all river bar areas had transitioned to other cover types. Additionally, 17.7 ha of new river bars were formed. This study provides crucial data on post-earthquake land cover changes, particularly river bar formation and changes, for assessing the earthquake impacts on the river systems and supporting impact mitigation.