Geoid (E-Journal)
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Comparative Analysis Of Landsat 8 And Landsat 9 Satellite Image Data In Surface Temperature Estimation, NDVI and NDBI Using Goggle Earth Engine
No full textPembuatan Peta Foto Udara Desa Campurejo Skala 1:5000 Menggunakan Metode UAV Photogrammetry
Get PDFDesa Campurejo adalah salah satu desa pesisir yang terletak di bagian utara Provinsi Jawa Timur. Secara sekilas, desa ini memiliki kawasan terbangun yang cukup luas meskipun kawasan tidak terbangun berupa lahan pertanian, lahan terbuka, dan vegetasi juga cukup dominan. Desa ini memiliki luas wilayah sekitar 370 hektar yang terpisah ke dalam dua wilayah. Dengan kondisi geografis dan batas administrasi yang tidak biasa tersebut keberadaan peta desa berskala besar menjadi penting bagi Desa Campurejo. Salah satu metode untuk membuat peta berskala besar dengan murah dan cepat adalah menggunakan wahana Unmanned Aerial Vehicle (UAV). Penelitian ini memaparkan pembuatan peta Desa Campurejo menggunakan UAV. Proses akuisisi data dilakukan dengan wahana quadcopter dengan tinggi terbang 150 meter di atas permukaan tanah dengan pertampalan ke depan dan ke samping sebesar 80%. Untuk menjangkau seluruh area desa diperlukan 9 misi penerbangan yang menghasilkan 2163 foto. Proses pengolahan foto udara hingga menjadi citra ortofoto dilakukan dengan metode Structure from Motion (SfM). Dari hasil pengolahan tersebut diperoleh citra foto udara dengan Ground Sample Distance (GSD) sebesar 4,17 cm. Namun untuk efisiensi penyimpanan data, citra ortofoto yang digunakan memiliki resolusi spasial 10 cm. Secara geometrik citra ortofoto yang dihasilkan memiliki RMSE sekitar 5 cm, yang menurut kriteria CE90 memiliki akurasi horizontal sebesar 8 cm. Dengan akurasi tersebut citra yang dihasilkan dapat digunakan untuk membuat peta berskala 1:1000. Namun dengan pertimbangan luas, batas, dan kedudukan wilayah desa peta yang dihasilkan memiliki skala 1:5000 yang dapat memperlihatkan seluruh wilayah desa beserta eksklavenya dalam satu lembar peta. Peta tersebut juga dilengkapi dengan informasi sebaran fasilitas umum yang didapatkan dari hasil survey lapangan, dan informasi batas desa yang diperoleh dari INA Geoportal
Land Cover Projection of Jember Irrigation Area Using MOLUSCE QGIS
No full textJember Regency has the third largest agricultural area in East Java Province. However, the agricultural area has decreased due to the expansion of built-up areas in line with population growth. This indicates the need for special attention to controlling the expansion of built-up land in Jember Regency. This study focuses on predicting agricultural land loss and the increase in built-up land in Jember Regency. It examines land cover changes in the regency from 2017 to 2021. Sentinel-2 imagery was used to obtain land cover data for Jember Regency in 2017 and 2021. The 2017 and 2021 land cover maps will serve as reference maps to determine the 2025 land cover using the MOLUSCE plugin in QGIS. The obtained 2025 land cover map will be used to validate the model's accuracy by comparing it with the actual 2025 land cover using Kappa Accuracy. This model's Kappa Accuracy is 91%. The validated model will then be used to predict land cover for 2045. The analysis indicates a predicted reduction in agricultural area of 5.675 hectares and a predicted increase in built-up area in irrigated areas of 6.348 hectares during the 2025–2045 period. Over the next 20 years, irrigation areas under the authority of the regency are predicted to experience the highest growth in built-up land, at 46.1%. This is followed by areas under provincial authority, which are predicted to grow by 34.6%, and areas under central authority, which are predicted to grow by 110% of the total agricultural area in Jember Regency. These findings are important for local governments and stakeholders in land management and urban planning. They also contribute to the monitoring of agricultural land use and the development of effective policy strategies
Mangrove Density Analysis in Teluk Semanting Ecotourism Area using NDVI
Get PDFThe mangrove ecosystem is of critical importance as a coastal vegetation system, playing a significant role in maintaining environmental stability, supporting social welfare, and fostering economic growth. In Teluk Semanting, Berau, East Kalimantan, mangrove forests play a vital role in preventing erosion, mitigating abrasion, providing habitats for various fauna, and supporting sustainable livelihoods through ecotourism. However, the area's mangrove forests are under threat due to the impact of human activities. To monitor mangrove forest development and prevent further degradation, it is essential to assess changes in the spatial distribution of mangrove land cover. This study utilises Sentinel-2A satellite imagery and the Normalized Difference Vegetation Index (NDVI) algorithm to analyse the spatial and temporal dynamics of mangrove cover in Teluk Semanting during the period 2019–2023. The results indicate a substantial decline in the high-density mangrove category, from 844.93 hectares in 2019 to 676.00 hectares in 2023, while the low- and medium- density categories exhibited a significant increase in area. This indicates a shift in mangrove quality from high-density to medium- and low- density categories. Regression analysis demonstrated a strong positive correlation (R² = 72.43%) between NDVI values and mangrove canopy density observed in the field, thereby underscoring the reliability of satellite imagery for monitoring mangrove conditions. The study emphasises the necessity of continuous monitoring and the implementation of conservation strategies to ensure the preservation of the ecological and economic benefits provided by mangrove ecosystems. This is particularly pertinent given the area's designation for ecotourism, where inadequate management could have adverse effects on the local community and global environmental stability
Refining the Indonesian Geoid Model: A Comparative Study of Global Geopotential Models in East Kalimantan
No full textGravity field along with its derivative, geoid, is one of the important pillars of Geodesy. The geoid is utilized in many countries as the vertical reference system, Indonesia as well. However, Indonesia is unique in topography, made the computation of geoid model throughout the archipelago a challenge. The development of geoid model in Indonesia has 4 phases, with the latest in 2020 and 2023. INAGEOID2020 is the Indonesian geoid model used as vertical reference frame for vertical control in Indonesia, updated to version 2.0 in 2023. However, it has not achieved the target accuracy of 5 cm throughout the country. INAGEOID2020 v2.0 is based on the EGM2008 global geopotential model (GGM) with order and degree 360, which is now nearly 20 years old. The implementation of EGM2008 into the regional model also lacked a fitting process, relying solely on functional calculations. This study proposes using modern GGMs, namely EGM2008, XGM2019e, and SGG-UGM-2, along with a fitting process to improve geoid modeling, to optimize the future iteration of Indonesian Geoid Model. The research compares the gravimetric undulations of these models to geometric undulations at 264 validation points, both with and without fitting in East Kalimantan. The fitting improved the accuracy of EGM2008 and XGM2019e, but SGG-UGM-2 performed worse due to elevation discrepancies both before and after the fitting, mainly due to difference on the starting point close to the coast. XGM2019e at degree 2190, truncated to 720 and 360 showed the best results after the fitting, achieving standard deviation and root mean square error (RMSE) values of 0.061 m and 0.064 m, respectively. The performance of EGM2008 is not far behind XGM2019e. This finding indicates that the XGM2019e is the best out the trio, making it a promising alternative to be utilized for future geoid modeling in Indonesia
Development of Three JS-based 3D Scene with Seamless Visualization of Gaussian Splatting and Transformation to Global Coordinates
No full textExisting scholarly literature on the Gaussian Splatting algorithm has predominantly concentrated on improving the rendering and reconstruction of three-dimensional objects, as well as exploring its applications in various academic disciplines, such as medicine, robotics, and mapping, while being limited to local coordinate systems. This study describes the development of a 3D scene modeled using the Gaussian Splatting algorithm, featuring accurate distance and position geometry based on Three JS. The developed 3D scene was then evaluated with precise position and distance coordinates in the field and compared to the established SfM-MVS (Structure from Motion-Multi View Stereo) algorithm. The findings demonstrate that the proposed development successfully generated Three JS-based 3D scenes with global coordinate compatibility utilizing the Gaussian Splatting algorithm, achieving the same level of position and distance accuracy as the SfM-MVS algorithm, with a 95% confidence interval using T-Test. This research concludes that the developed approach is successful and can be further expanded for various scientific fields that require accurate position and distance information using Gaussian Splatting Algorithm
Simulation of Tidal Inundation along the Northern Coast of Central Java (Pantura) Using GIS-Based Analysis
No full textThe northern coast of Java Island (locally known as Pantura), is a strategically important area, particularly in the distribution sector. However, its topographical characteristics and proximity to the Java Sea make it vulnerable to the threat of tidal inundation. Moreover, environmental factors such as sea level rise, land subsidence, and coastal abrasion—which causes shoreline retreat—further exacerbate the region’s susceptibility to flooding. The rob phenomenon significantly impacts the socio-economic conditions of coastal communities, disrupting daily activities and damaging critical infrastructure such as residential housing and road networks. This study aims to simulate the impact of tidal flooding in terms of inundation depth and spatial extent, using the assumption of the Highest High Water Level (HHWL). The simulation results are intended to serve as an initial reference for the development of coastal flood mitigation strategies. The methodology follows the Technical Guidelines for Disaster Risk Assessment issued by Indonesia’s National Disaster Management Agency (BNPB) and integrates various spatial datasets, including land cover data from Sentinel Land Cover by ESRI, topographic data from the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and maximum tidal height data processed using the Admiralty method. The analysis shows that, assuming a Highest High Water Level of 1.2 meters, Kendal Regency, Brebes Regency, and Semarang City are the most affected areas in terms of both flood depth and extent. The inundated areas are estimated at 3,744.91 hectares in Kendal Regency, 2,880.58 hectares in Brebes Regency, and 513.17 hectares in Semarang City. This situation could become more severe in the event of storm surge, extreme weather, or climate anomalies if timely and effective mitigation measures are not implemented. These findings are expected to provide a strong foundation for policymakers to formulate targeted, data-driven, and sustainable mitigation strategies to protect communities and infrastructure along Java’s northern coastal region
Analisis Kualitas Air Serta Status Mutu Dengan Menggunakan Metode Indeks Pencemaran Pada Hari Panas Dan Hujan Di Kawasan Mangrove Desa Poka, Kota Ambon
Get PDFMangrove merupakan salah satu ekosistem pesisir yang memiliki peranan penting dalam menjaga keseimbangan lingkungan. Namun ekosistem ini juga rentan mengalami kerusakan, baik secara alami maupun aktifitas manusia. Penelitian ini bertujuan untuk menganalisis kualitas air serta tingkat pencemaran air di aliran sungai hingga pesisir kawasan mangrove Desa Poka, Kota Ambon dengan menggunakan metode Indeks Pencemaran (IP). Pengambilan data air dilakukan pada hari panas dan hari hujan untuk mengukur beberapa parameter kualitas air. Hasil penelitian menunjukkan adanya perbedaan nilai parameter antara hari panas dan hari hujan. Sementara itu, berdasarkan hasil perhitungan IP, status mutu air berada pada katergori tercemar ringan hingga sedang
Land Value Modeling Using Log-Linear Multiple Regression
Get PDFLand value is an assessment of land based on its economic potential. It is influenced by various factors, including public facilities, road networks, and proximity to supporting infrastructure. Land value information plays a crucial role in infrastructure development, budget planning, and site selection for new infrastructure projects. According to the Surabaya City Regional Spatial Plan (Rencana Tata Ruang Wilayah – RTRW) 2014–2034, the development of Teluk Lamong Port, located in the Tambak Osowilangun Subdistrict, aims to enhance national logistics efficiency by alleviating traffic congestion at Tanjung Perak Port, which has exceeded its maximum capacity. This development is expected to affect land values in the subdistrict. Therefore, an objective land valuation is necessary, which can be achieved through modeling. This study employs a Multiple Linear Regression (MLR) approach with a log-lin model to determine land values. The modeling was conducted using 87 land sale and purchase transaction records, which were adjusted based on Circular Letter of the Directorate General of Taxes No. SE-55/PJ.6/1999. The independent variables used in the model include Land Area (LT), Land Use (PL), Distance to Road (JJ), Distance to Port (JPTL), Distance to the Central Business District (JCOP), and Distance to the Terminal (JTTO). The model was evaluated using statistical tests, including the coefficient of determination, partial test, simultaneous test, multicollinearity test, and Coefficient of Variation (CoV) for model evaluation. The resulting land value model is expressed as: Ln NTE = 9.305184 + (1.053730 × PL) + (-0.000450 × JCOP) + (0.000823 × JPTL). The CoV value obtained remains acceptable as it is below 20%, indicating the model's reliability
Pendugaan Potensi Air Tanah di daerah Rawan Air berbasis SIG dengan Analisis Multi Kriteria
Get PDFPenelitian ini bertujuan untuk menduga potensi air tanah di daerah rawan air dengan pendekatan Sistem Informasi Geografis (SIG) dan Analisis Multi Kriteria (MCA). Studi ini dilakukan di Kabupaten Tuban dengan mempertimbangkan berbagai parameter geospasial, seperti kemiringan lereng, jenis tanah, kondisi geologi, indeks vegetasi (NDVI), tutupan lahan, curah hujan, dan densitas drainase. Data yang digunakan meliputi DEMNAS, peta geologi, peta jenis tanah, serta data curah hujan dari BMKG. Hasil analisis menunjukkan bahwa potensi air tanah di Kabupaten Tuban berkisar antara kategori sedang hingga tinggi. Faktor utama yang mendukung potensi air tanah tinggi meliputi kemiringan lereng landai (0–5%), jenis tanah berpasir, struktur geologi berupa batu gamping dan endapan aluvium, tutupan lahan dominan berupa agrikultur dan hutan, serta curah hujan tinggi (>1.000 mm/tahun). Kecamatan dengan potensi air tanah tinggi antara lain Montong, Merakurak, Semanding, Rengel, dan Plumpang. Penelitian ini menegaskan bahwa metode SIG dan MCA efektif dalam mengidentifikasi potensi air tanah berdasarkan parameter geospasial. Hasil studi ini dapat digunakan sebagai referensi dalam perencanaan pengelolaan sumber daya air tanah serta mitigasi kekurangan air di daerah rawan