Engineering Headway Vol. 27

Abstract: Flooding is the most common disaster in Katingan Regency. However, global warming worsens the flood risk, and making a flood risk map is the first step in generating a disaster management policy in Katingan Regency. This research uses spatial data to create flood risk modelling for the Katingan Regency. The Composite Mapping Analysis (CMA) method was applied to map the flood risk in Katingan Regency using four parameters: slope, soil type, precipitation and land-use type. The flood risk map shows that there are five classes of flood risk in Katingan Regency that are low risk (580.319,25 Ha or 29,12%), relatively low risk (760.974,50 Ha or 38,18%), medium risk (308.233,16 Ha or 15,47%), relatively high risk (293.040,65 Ha or 14,70%) and high risk (50.439,87 Ha or 2,53%). Medium to high risk of flooding in Katingan Regency is primarily distributed near the river with developed areas since this land use group is the most vulnerable to loss from flooding. Moreover, the Katingan Regency area, formed from an alluvial process characterized by a flat slope and clay-textured soil, has a higher chance of puddles.

Abstract: There remain unresolved segments of land borders between Indonesia and Malaysia in Sebatik Island in Borneo. However, there has been a de facto boundary line used by local people as a reference in land utilisation. After a long process, the two countries have established a new border segment that is different from the de facto boundary line. This difference causes shift of some land parcels from Indonesia to Malaysia, and vice versa. The Ministry of Agrarian Affairs and Spatial Planning/National Land Agency (ATR/ BPN) is obliged to provide Land Administration data on affected areas to anticipate potential problems. Given its importance, the quality of land administration data is essential. This study evaluates the quality of registered land parcel data based on the ISO 19157:2013 on Data Quality using the completeness and consistency. The evaluation using the completeness element shows that the data of registered land parcels and attributes are not completely recorded. Similarly, the evaluation using the logical consistency element shows that there remain gaps and overlaps in the registered land parcels. Expectedly, these results can be used to improve the quality of land data for a better land policy making around the international borders in Sebatik island.

Abstract: Population growth exerts pressure on the development of settlements and public facilities. The increasing demand for settlement and infrastructure due to the urban population led to a fierce land transformation into built-up areas. Madiun City is one of the municipalities in East Java with a raised population every ten years of population census. As the center of development, Madiun City plays a role in encouraging growth in the western area of East Java. This rapid development needs to be well monitored and mapped to prevent the emergence of various urban problems. The study aims to provide information about built-up land changes and population distribution in Madiun City. This study used Geographic Information Systems and remote sensing data to identify changes in the built-up land from 2000 to 2020. The total built-up land in 2000 was around 36%, increasing to 58% in 2020. The southern and northern areas of Madiun City experienced the most significant changes. The development of built-up land moving away from the center and into the outskirts of a city. Population census data and the processed satellite data into a built-up map were combined to see the population distribution with the grid. The grid cells with high populations are in settlement areas and close to shopping centers, education facilities, health facilities, offices, and service facilities. This study provides a practical and effective way to map built-up expansion and population distribution. The results showed that the analysis of changing urban land use is adequate for understanding the urban population distribution density. Considering these changes and distribution is significant for managing urban growth. In addition, this method is essential for the government to formulate population policies to optimize spatial distribution for access to medical care, schools, markets, and transportation.

Abstract: Geomagnetic storms, triggered by enhanced solar activity, significantly impact the Earth's ionosphere, affecting space-based technologies. These storms occur when the solar wind carries charged particles into the Earth's atmosphere, disturbing the geomagnetic field. This study analyzes ionospheric responses to strong geomagnetic storm events at Pontianak, focusing on Vertical Total Electron Content (VTEC) and scintillation parameters indicated by the S4 Index. Data were obtained from a Septentrio instrument at the Pontianak station for three events (April 24, 2023, May 11, and August 12, 2024). VTEC measurements and the S4 Index were used to identify ionospheric irregularities. VTEC increased during the storm's expansion phase in April 2023 and May 2024, but differed in August 2024, possibly due to fluctuations in solar wind speed and the interplanetary magnetic field. Strong scintillation occurred approximately one day after the Dst minimum in April 2023 and August 2024, but did not occur in May 2024. The May 2024 event showed a delayed increase in the S4 Index, potentially due to variations in the interplanetary electric field and fluctuating auroral and mid-latitude magnetic activity. This research enhances our understanding of ionospheric behavior during intense geomagnetic storms, highlighting the complex interplay between solar-terrestrial interactions and ionospheric irregularities.

Abstract: The basic facilities in a port consist of shipping channels, berthing area, and turning basins. Those facilities will also be built at Branta Harbor so large ships can enter and dock. Those basic facilities are not yet available due to the lack of appropriate data. The port planning activities require bathymetric data, seabed imageries, tides, and topographic conditions of the port area. It is essential in port planning, which can guarantee the safety of maritime shipping. The depth of Branta Harbor ranges from 0.7 m to 25.2 m. The condition of the seabed is mostly sand, and several submarine pipes, trawl nets, and fishing nets were found in the area, although there were no endangered shipping objects. The shipping channels is designed as a two-way lane with a length of 1,550 m and a width of 200 m. The berthing area is 23 hectares, the emergency area is 11.56 hectares, and the turning basin is 7.06 hectares. The main facilities are designed with a depth of 8 m and must be dredged in the turning basin area and shipping channel. By this planning, it is hoped that the draft of ships that can enter Branta Harbor up to 7 m.

Abstract: An exploratory study was conducted using Landsat-8 (L8) and Sentinel-2 (S2) satellite images for the extraction of chlorophyll-a and SST, followed by determining their relationship with fish catch at Baron Beach due to the increasing fish catch in certain months. L8 and S2 can observe chlorophyll-a but not as optimum as low-resolution imagery such as MODIS due to the complex optical characteristics of seawater and their limited band types. Aside from observing the chlorophyll-a, L8 can observe SST value but S2 cannot because it currently has no thermal infrared band. Therefore, both images need to be compared to know their capability of extracting chlorophyll-a and SST. Data processing for chlorophyll-a and SST extraction used Google Earth Engine (GEE) and QGIS. Data extraction preparation involved cloud masking with four scenarios. Chlorophyll-a extraction used Ocean Color (OC) algorithm, while SST extraction at L8 used thermal-infrared band and optical band approach at S2. Differences in extraction results were analyzed using a non-parametric significance test with α = 0.05. The relationship between chlorophyll-a, SST and fish catch was assessed using Catch per Unit Effort (CPUE) values in the Spearman correlation test. The extraction results showed changes in chlorophyll-a and SST values each month in 2022 where both images show an increasing chlorophyll-a within June until October and decreasing within those months. However, the extraction results from both images are significantly different. Aside from the significantly different extraction results, there is a positive correlation between chlorophyll-a and fish catch, but the SST correlation varied between L8 and S2 images. This difference is thought to be caused by image characteristics, cloud masking, and extraction models that are not yet suitable for the Baron coastal area, which is characterized by high sedimentation coastal areas. In this context, correlation analysis showed a relationship between chlorophyll-a concentration and SST with fish production, but direct comparison data at Baron Beach is needed for further analysis.

Abstract: The increasing application of remote sensing technologies, particularly the use of Unmanned Aerial Systems (UAS), has significantly advanced forest resource assessment. Advances in remote sensing data acquisition technology, particularly Unmanned Aerial System (UAS), have expanded the knowledge of remote sensing in forestry to produce high-resolution images and affordable 3D data. This study aims to extract and automatically calculate the accuracy of individual tree detection for industrial plantation forests (Eucalyptus pellita) using the local maxima algorithm for Canopy Height Model (CHM) data and to assess silvicultural quality based on tree height. The study was conducted in industrial plantation forest areas located in Tapung District, Kampar Regency, Riau. Seven field plots measuring 4 x 4 trees were manually counted in the field. A total of 99 trees were successfully detected out of 112 trees in the entire plot, resulting in an accuracy of 88% (F-Score 0.89). Overall, the algorithm used missed 17 trees, incorrectly detected 5 trees, and correctly detected 93 trees, resulting in recall and precision values of 0.95 and 0.84, respectively. The COV, Gini, CRR, and PV50 indices yielded values of 0.71, 0.096, 0.12, and 7.57, respectively. Overall, the tree height distribution was relatively uniform with low variation and a moderate concentration of values.

Abstract: Mapping pipeline networks and their support is essential to asset information systems and asset integrity in supporting energy security. Important information from pipeline asset integrity, including pipeline network, support position, and condition, must be monitored well to allow damage to be detected as early as possible. The challenge of mapping the pipeline network and its support is the volume of the pipeline network, which can reach tens or even hundreds of kilometers. The technology often used for mapping pipeline assets is terrestrial surveys with total stations and GNSS-RTK. Alternative rapid mapping that can be an option is UAV LiDAR or UAV photos. Finding alternative pipeline mapping technology for accurate and economical mapping needs to be considered. This research analyzed the capabilities of UAV photos for mapping pipelines and their support in a 3 km-long pipeline area. With its rapid data acquisition, the point cloud extracted from UAV photos is used for pipeline and support location detection and its height. Furthermore, the appropriateness of UAV photo technology for pipeline mapping was tested compared to UAV LiDAR technology and GNSS terrestrial mapping on two practical parameters, namely (1) technical ability to provide results according to standards and expected output with a weight of 70% and (2) cost-effectiveness with a weight of 30%. Each parameter is then detailed and scored. The results of the analysis of the appropriateness of UAV photos compared to UAV LiDAR and the GNSS terrestrial survey found that the highest score was obtained by UAV LiDAR at 21.2, followed by the GNSS terrestrial survey at 15.9. The UAV photo method for pipeline network mapping only scored 12.5, the lowest among the three technologies. The UAV photo method falls on the assessment of technical capabilities, especially the ability to obtain the height of the pipeline and its support to the ground and the height of the surrounding environment. Given that height information is an inseparable part of the results of topographic maps and pipeline alignment that must be produced from pipeline network mapping surveys.

Abstract: Monitoring forest ecosystem is crucial steps for sustainable management. Development of various remote sensing sensors and algorithms for detecting forest change has increase the capability of multitemporal forest condition analysis. The Leuweung Sancang Nature Reserve (LSNR) is home for various endemic flora and fauna in Western Java. Forest condition information for this reserve is still limited, and various anthropogenic related development and activities has been increasing in recent years. This study aims to assess forest condition changes in LSNR by applying a multitemporal analysis using the Disturbance Index (DI), derived from the Tasseled Cap Transformation of Landsat sensors. We analyzed forest conditions within the LSNR borders from 1991 to 2023. Based on the DI for each year, the forest disturbance in LSNR have fluctuated, although generally decrease throughout the year. The change analysis mapped three forest condition, disturbance, regrowth, and stable from 1991 - 2023. We compared the ∆DI of 2000 – 2023 in order to match the analysis with the Hansen Global Forest Change dataset. Disagreement metrices resulted in 19.8% quantity disagreement and 81.15% allocation disagreement. The low quantity disagreement indicate that DI manage to produce similar result in term of class proportion quantity, although resulted in higher miss-classification.

Abstract: This research examines the spatial data quality of land parcels resulting from integrated physical data collection in 2023 in Samarinda City. The research samples consisted of parcels of land covered by vegetation and non-vegetation. Analysis of the results in land parcel accuracy tests referring to SNI-ISO 19113:2011 and spatial analysis of land parcel anomalies. The results of the side (distance) land parcel accuracy test in non-vegetation cover were that 183 sides met the tolerance, and 60 sides did not meet them, while in vegetation covers, 64 sides met tolerances, and 110 sides did not meet them. The accuracy test results on the area of land parcels in non-vegetation covers were that 58 areas met the tolerance. In contrast, in vegetation covers, as many as 27 areas met the tolerance, and 15 areas did not. The quality test classification results were excellent for 91 lands parcels. The 349 land parcel anomalies need to be improved regarding spatial data quality. Good-quality land parcels can become cadastral machines for implementing electronic services.