Improvement of river network representation in Africa: application of an approach based on digital elevation data and environmental characteristics

In many continental databases representing rivers across Africa, information on rivers characteristics (length, width, intermittent or perennial) is often incomplete, and small streams are largely underrepresented. Fortunately, the use of topographic information from digital elevation models (DEMs) provides an opportunity to have more detailed information on rivers, particularly small streams in broad areas. A common approach to extract streams from DEM is to consider as a stream all DEM cells that drain at least a certain upstream surface, commonly known as the minimum contributing area (Amin). This parameter (Amin) is generally defined uniformly over large areas and this independently of the very variable climate and landscape conditions so that the generated streams have a rather uniform spatial distribution. To address this issue, using a 3′′ (approx. 90 m × 90 m) DEM of Burkina Faso, the relationship between Amin and the observed drainage density (Ddobs) was established with satisfactory performance (r2=0.86). In ongoing work, the functional relationship between the observed drainage densities (Ddobs) and environmental variables (lithology, climate, geology, vegetation cover) should allow for the establishment of the relationships between Amin and the environmental variables. This relationship allows for spatially variable Amin values depending on landscape characteristics. Before extracting river networks in Africa, the next step will be to validate or update these relationships in several countries.

New insights on the Ife-Ilesha schist belt using integrated satellite, aeromagnetic and radiometric data

The present study combined analysis of satellite, aeromagnetic and radiometric data for evaluation of structural features within the Ife-Ilesha schist belt. Shuttle Radar Topographic Mission digital elevation data have been enhanced using hill-shading technique for the delineation of morphological features. The superposition of total gradient amplitude lineaments on the 3-D Euler deconvolution map revealed the trends and depth of structural features within the study region. The major trends are NE–SW, NNE–SSW, E–W and minor trends in the N–S direction, including the Ifewara shear zone that trends in the NNE–SSW. The estimated depths to the top of the sources within the shear zone varies from 90 to 200 m. Complementary analysis of the airborne radiometric data revealed that the Ifewara shear zone and adjacent regions are characterized by radiometric anomalies, indicating regional mineralization alteration zone. Generally, there is a good correlation between the satellite, radiometric, aeromagnetic maps which provides new insights and re-evaluation of structural features.

Penggunaan Citra DEMNAS untuk Desain Pola Tanam Alley Cropping pada Lahan Garapan Anggota KPPH Talang Mulya Kabupaten Pesawaran Provinsi Lampung

Talang Mulya KPPH farmers has been applying agroforestry system for their land cultivation, but the cropping pattern applied has not been adapted to its sloping conditions and plant spacing which result on non-optimal yields produce. Alley Cropping pattern consider as the most suitable approach. Current analysis can be carried out using mapping techniques and remote sensing using digital elevation data imagery. The DEMNAS imagery was used in this study, results showed that the mean altitude reached 396.67 masl and land slope reached 20.92% in average. The design of the cropping pattern using 1 meter height intervals shows the results of the number of planting arrays of 31.96 strips with 3,564.96 meters in length which is higher than the land with a height interval of 2 meters which results in a total of 10.6 strips with and 942.97 meter lengths. However, the field of agricultural cultivation that can be formed on land with 1 meter height intervals only reaches 4.94 meters, while at 2 meters height intervals it can reach 16.03 meters.

Validation of an Index for Susceptibility to Earthquake-Induced Landslides Derived from Helicopter-Borne Electromagnetic Resistivity and Digital Elevation Data

Catastrophic earthquake-induced landslides can occur on slopes composed of loosened and fractured rock masses. Although it is impossible to prevent such landslides, estimation of the susceptibility of slopes to earthquake-induced landslides is useful for risk management. An index of susceptibility to earthquake-induced landslides (ISEL) was developed by using helicopter-borne electromagnetic resistivity data. However, the ISEL has not yet been validated through the analysis of pre-earthquake data. In this study, ISEL values were estimated from resistivity and digital elevation data obtained in 2013 around Mt. Aso, Kyushu, before the 2016 Kumamoto earthquake. Although most of the landslides around Mt. Aso during the 2016 Kumamoto earthquake were mass movements of volcanic tephra layers, some of them occurred on loosened rock masses. Landslide susceptible areas at loosened rock masses are the target for ISEL value estimation. Our results validated the effectiveness of the ISEL as a predictor of earthquake-induced rock mass landslides.

Geomorphological Characterization of Rivers Using Virtual Globes and Digital Elevation Data: A Case Study from the Naryn River in Kyrgyzstan

In recent years, fluvial geomorphology included a range of new technologies for the characterization of riverine landscapes in the pool of methods. LIDAR, the analysis of drone imagery or satellite remote sensing improved the ability to analyze river systems in manifold ways. However, the high demand for (often expensive) data and processing skills limit the application commonly to smaller study reaches or to regions where data is already available. In contrast, a range of conceptual frameworks for the geomorphological characterization of river systems highlights the relevance of integrating the catchment scale context. Against this background, virtual globes such as Google Earth are cost-efficient alternatives as they make high resolution satellite imagery available almost worldwide. Merging the information mapped from virtual globes with digital elevation data allows the interpretation of riverscape attributes in the context of the longitudinal profile. In our study, we present the geomorphological mapping of the more than 600 km long Naryn River in Kyrgyzstan based on different virtual globes and the SRTM-1 digital elevation model. The experience from this mapping exercise suggests that the combination of virtual globe imagery and elevation data is a powerful and cost-efficient approach for river research and application in the context of data-scarce river corridors.

A Parallel Computing Approach to Spatial Neighboring Analysis of Large Amounts of Terrain Data Using Spark

Spatial neighboring analysis is an indispensable part of geo-raster spatial analysis. In the big data era, high-resolution raster data offer us abundant and valuable information, and also bring enormous computational challenges to the existing focal statistics algorithms. Simply employing the in-memory computing framework Spark to serve such applications might incur performance issues due to its lack of native support for spatial data. In this article, we present a Spark-based parallel computing approach for the focal algorithms of neighboring analysis. This approach implements efficient manipulation of large amounts of terrain data through three steps: (1) partitioning a raster digital elevation model (DEM) file into multiple square tile files by adopting a tile-based multifile storing strategy suitable for the Hadoop Distributed File System (HDFS), (2) performing the quintessential slope algorithm on these tile files using a dynamic calculation window (DCW) computing strategy, and (3) writing back and merging the calculation results into a whole raster file. Experiments with the digital elevation data of Australia show that the proposed computing approach can effectively improve the parallel performance of focal statistics algorithms. The results also show that the approach has almost the same calculation accuracy as that of ArcGIS. The proposed approach also exhibits good scalability when the number of Spark executors in clusters is increased.

Aboveground Biomass Changes in Tropical Montane Forest of Northern Borneo Estimated Using Spaceborne and Airborne Digital Elevation Data

Monitoring anthropogenic disturbances on aboveground biomass (AGB) of tropical montane forests is crucial, but challenging, due to a lack of historical AGB information. We examined the use of spaceborne (Shuttle Radar Topographic Mission Digital Elevation Model (SRTM) digital surface model (DSM)) and airborne (Light Detection and Ranging (LiDAR)) digital elevation data to estimate tropical montane forest AGB changes in northern Borneo between 2000 and 2012. LiDAR canopy height model (CHM) mean values were used to calibrate SRTM CHM in different pixel resolutions (1, 5, 10, and 30 m). Regression analyses between field AGB of 2012 and LiDAR CHM means at different resolutions identified the LiDAR CHM mean at 1 m resolution as the best model (modeling efficiency = 0.798; relative root mean square error = 25.81%). Using the multitemporal AGB maps, the overall mean AGB decrease was estimated at 390.50 Mg/ha, but AGB removal up to 673.30 Mg/ha was estimated in the managed forests due to timber extraction. Over the 12 years, the AGB accumulated at a rate of 10.44 Mg/ha/yr, which was attributed to natural regeneration. The annual rate in the village area was 8.31 Mg/ha/yr, which was almost 20% lower than in the managed forests (10.21 Mg/ha/yr). This study identified forestry land use, especially commercial logging, as the main driver for the AGB changes in the montane forest. As SRTM DSM data are freely available, this approach can be used to estimate baseline historical AGB information for monitoring forest AGB changes in other tropical regions.