Many Indonesian forests have been cleared and replaced by fast-growing cash crops (e.g., oil palm and rubber plantations), altering the vegetation structure of entire regions. Complex vegetation structure provides habitat niches to a large number of native species. Airborne laser scanning (ALS) can provide detailed three-dimensional information on vegetation structure. Here, we investigate the potential of ALS metrics to highlight differences across a gradient of land-use management intensities in Sumatra, Indonesia. We focused on tropical rainforests, jungle rubber, rubber plantations, oil palm plantations and transitional lands. Twenty-two ALS metrics were extracted from 183 plots. Analysis included a principal component analysis (PCA), analysis of variance (ANOVAs) and random forest (RF) characterization of the land use/land cover (LULC). Results from the PCA indicated that a greater number of canopy gaps are associated with oil palm plantations, while a taller stand height and higher vegetation structural metrics were linked with rainforest and jungle rubber. A clear separation in metrics performance between forest (including rainforest and jungle rubber) and oil palm was evident from the metrics pairwise comparison, with rubber plantations and transitional land behaving similar to forests (rainforest and jungle rubber) and oil palm plantations, according to different metrics. Lastly, two RF models were carried out: one using all five land uses (5LU), and one using four, merging jungle rubber with rainforest (4LU). The 5LU model resulted in a lower overall accuracy (51.1%) due to mismatches between jungle rubber and forest, while the 4LU model resulted in a higher accuracy (72.2%). Our results show the potential of ALS metrics to characterize different LULCs, which can be used to track changes in land use and their effect on ecosystem functioning, biodiversity and climate.

<p>The research aimed to analyze selected properties of peat degradation on different land uses and the sustainable management. The research area is located in the lowland dome peats in the catchment basin of Sibumbung River and Sibotak River in Sub District of East Pedamaran, OKI South Sumatra. The research method used an experimental design of Randomized Completely Block Design with two Blocks and five treatments (Site A: intercropping between oil palm and pineapples; Site B: oil palm plantations, Site C: peat forest; Site D: swamp bush; Site E: swamp grass). The research resulted that drainage and land uses decrease some properties of peats, namely C/N ratio, total pore space, fiber and ash content as well as organic C on cultivated peats and are significantly different at level of 5% compared with uncultivated peats. Bulk density increased due to peat compaction and groundwater table on cultivated peats, which is getting deeper, and significantly different compared with uncultivated peats. All soil series do not show any change because of drainage and different land uses. Sustainable peat management can be implemented through three approaches, namely managements of water, soil and crops.</p>

This paper tried to prove the capability of a geophysical method, called VLF (very low frequency) for peat thickness variability exploration. The method involved using the VLF receiver to measure the VLF properties emitted by the ground from the study area. The study was carried out in Jambi Province of Indonesia in three different depths of peat area, i.e.; very deep (8-15 m), deep (3-8 m) and shallow (0-3 m) peat. The depth was confirmed by direct measurement. The VLF measurement was done along transects on each areas. The data was processed using NAMEMD (Noise Assisted Multivariate Empirical Mode Decomposition) method and converted into value and depth of resistivity using Inv2DVLF software. The study indicated that the resistivity, shows significant difference (F(2,6317) = 4.525, p = 0.011) between the area of very deep peat and the shallow peat. The resistivity varies according to peat thickness. In the very deep area, it tends to be statistically similar until 7.32 meter depth and starts to differ significantly at the depth of 11.46 meters. In turn, in the area of deep peat, it is statistically similar until 4.72 meter and starts to show differences at 7.32 m depth. However, in shallow area, it does not exhibit the differences as in the area of deep peat. This proved that the VLF method works properly in deep and very deep peat and is capable of indicating the peat thickness.

Floods are the most common disasters in almost all places, including Indonesia and Jambi City in particular. Areas that are directly exposed to the threat of flooding are in the Watershed. Land conversion is one of the causes of flooding in the Kenali Kecil watershed. This study uses the standard SNI 8197:2015 regarding the Flood Hazard Mapping Method 1:50,000 and 1:25,000 scale. The approach used is landscape analysis, which emphasizes the process of forming natural systems on the earth's surface. This study aims to analyze and produce a map of the level of flood vulnerability in the Kenali Kecil watershed area. The data needed in this study are ten days of rainfall data, slope data and land cover data. Slope data was obtained from DEMNas data processing and land cover data was obtained from manual digitizing of Google Earth's High-Resolution Satellite Imagery data. Data processing uses ArcMap software with scoring and overlay techniques. The results showed that the Kenali Kecil watershed had a dendritic pattern with an area of 15.68 km2 and located in 5 villages, namely: Bagan Pete, Kenali Besar, Penyengat Rendah, Mendalo Darat and Pematang Gajah. The basic rainfall of the Kenali Kecil watershed is 204.21 mm, the slope is mostly >4% and the land cover is mostly residential. Based on the SNI 8197:2015 procedure and the results of the scoring and overlay process with ArcMap, the flood susceptibility level of the Kenali Kecil watershed is at a medium hazard level of 8.25 km2 (52.6%) and a height of 7.43 km2 (47.4%).

Geostatistics has been knowns as a reliable tool to explore variability in space of any measured parameter. This research aims to study how peat depth change and vary in space using geostatistics aproach. The research took place in a peat land inMuaro Jambi district, Jambi province of Indonesia. The three different areas of peat depth [very deep (area A), deep (area B) and shallow (area C)] were purposely selected to investigate through borehole. From the total 120 boreholes, peat depth data were analyses using ArcGIS geostatistical analyses.The result showed that peat variability in shallow area is higher than that of deep and very deep area.It is also found that the reliable sampling distance in peat exploration should not be less than 230 meter in very deep area, 275 meter in deep area and 41 meter in shallow area.