bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatio-temporal Variation of Chlorophyll-a around the Flores Sea, Java Sea, and Makassar Strait and its Relationship with Temperature and Salinity
Authors: Putri Hanansyah Megivareza , Yuli Handoko Eko , Muryono Mukhammad 
Published: December 2024

Abstract
The Flores Sea, Java, and Makassar Strait are areas where water masses meet as well as one of the entry points for the Indonesian Through Flow. Freshwater mass from the Pacific Ocean enters Indonesian waters through the Makassar Strait. Not only that, Indonesia’s maritime region is influenced by the Asian-Australian Monsoon, which also causes seasonal changes in temperature and salinity. This phenomenon affects primary productivity in Indonesian waters as indicated by variations in chlorophyll-a concentrations in surface waters. Therefore, it is important to study the dynamics of chlorophyll-a in time series to better understand the ecosystem and the phenomena that occur. This study aimed to analyze the spatio-temporal variation of chlorophyll-a in the waters surrounding the Flores Sea, Java, and Makassar Strait, and its correlation with temperature and salinity over a period of seven years, from 2016 to 2023. This reasearch uses chlorophyll-a data collected from sensor, named Ocean and Land Color Instrument carried by the Sentinel-3 satellite. The chlorophyll-a data used is Ocean Color 4 for MERIS data. This study found that chlorophyll-a concentrations in the Flores Sea, Java, and Makassar Strait sample areas tend to be high during the Northwest Monsoon period, along with the arrival of the rainy season which increases river water runoff. On the other hand, chlorophyll-a concentrations in the southern waters of Java to Nusa Tenggara exhibit a notable increase during the Southeast Monsoon, which is subsequently accompanied by a decline in temperature of sea surface and a rise in salinity of sea surface. In 2018 and 2019, the occurrence of the El Niño phenomenon, along with the positive phase of the IOD, led to an increase in chlorophyll-a. From 2018 to 2019, the average chlorophyll-a reached 0.71 mg/m3 in the Flores Sea and Makassar Strait and 0.73 mg/m3 in the Java Sea. This study analyzes chl-a based on satellite observation data that may have errors due to cloud cover. Further research with in situ observation methods is needed for better results and a longer temporal range so that the variability of chl-a against the global phenomena of ENSO and IOD can be seen more clearly.
Mapping The Dynamics of Settlement Areas around the tourism areas by Using Geographic Information Systems (Case Study: Prambanan and Kalasan District)
Authors: Putra Wijaya Arwan , Syadayagra Arwanto Daffa , Novrizal Ramadhani Rizky , Wahyuddin Yasser 
Published: December 2024

Abstract
The construction of National tourism strategic area (KSPN) Prambanan - Kalasan is planned to begin in 2016 through the Master Plan and Detail Plan of KSPN Prambanan - Kalasan and its surroundings for the 2016 fiscal year. The development of tourist areas can have an impact on increasing the land value around tourist areas, and also cause the development of residential areas. Therefore, this research was conducted to analysis changes in land values around the KSPN development and also analysis changes in residential areas and the suitability of residential areas for land values in Prambanan and Kalasan Districts. The results of the suitability of residential areas were then superimposed on the analysis with the RDTR of Prambanan and Kalasan Regencies. The results show that in 2017-2024 there was an increase in residential land area by 67 hectares in Prambanan District and 73 hectares in Kalasan Regency and the highest significant increase in land value was in zone 50, namely Jl. Raya Solo-Yogyakarta for IDR. 6,597,200 and the lowest increase in land value was in zone 49 amounting to IDR. 158,500 to the north of Tamanmartani Village, Kalasan District. The relatively small increase in residential area in the highest land value zone and a large increase in residential area in the lowest land value zone. The suitability of the dominant residential area is very suitable in the highest land value zone and the suitability of the dominant residential area is less suitable in the lowest land value zone.
The Impact of Population Density, Land Cover, and Spatial Patterns on the Geoecological Evaluation of the Surabaya Coast
Authors: Safitri D.A. , Alina A.N. , Bespalova L.A. , Suprayitno W.E. , Dhani N.Q. 
Published: December 2024

Abstract
Coastal areas are vulnerable to the influence of geomorphological processes from activities in the waters, so that the condition of coastal ecosystems will always change according to the dynamics that occur on the coast, both changes could be occurred in coastlines and land cover. Geoecology is the spatial interaction between natural phenomena and their relationship to phenomena in a particular ecosystem. Surabaya is a coastal city that frequently experiences changes in land cover. The construction of new settlements and changes in land use have a significant impact on the coastal environment of Surabaya. This research aims to determine the influence of population density, land cover and spatial plan on the geoecological evaluation of Surabaya’s coast using remote sensing data. The data used in the research is Landsat satellite image data from 1994, 2003 and 2018 (maximum likelihood classification method). The dynamics of changes in coastlines on the coast of Surabaya are caused by three phenomena, namely erosion, accretion and anthropogenic. Each phenomenon has a different value for land cover class, population density and spatial patterns. The research results show that geoecological evaluation is closely related to phenomena that occur on the Surabaya coast (value range 1-3). The geoecological evaluation value due to the erosion phenomenon is low (30%) and medium (70%). The geoecological evaluation value due to the accretion phenomenon is low (100%). Meanwhile, the geoecological evaluation value due to anthropogenic phenomena is low (25%) and medium (75%). Geoecological evaluation of Surabaya’s coast shows that it is in a “safe” condition, but there is requirement for coastline management. Where the coastal area planning process is carried out by identifying the dynamics of coastal areas and potential risks and consequences related to decisions that produce different future scenarios.
Waste Volume Estimation by Surface Changes of Sarimukti Landfill 2010 – 2023
Authors: Dzun Nurwinas Saepudin Muhammad , Lestari Nurmaulia Sella , Gumilar Irwan , Dirgaputera Trizky , Ibrahim Hakiem Haekal 
Published: December 2024

Abstract
Sarimukti landfill was established in 2006 and is located in Sarimukti Village, which is 45 km away from Bandung City. This landfill handles trash dumping from nearby areas such as Bandung City, Cimahi City, and West Bandung Regency. In 2010, this landfill underwent a rehabilitation project to optimize its trash handling capability. Several months ago, the Sarimukti landfill experienced a fire crisis which was successfully handled by the local government. After the crisis, speculations emerged regarding the rehabilitation of the landfill once again. In response to that idea, this research will explore several pieces of information that are required for the landfill to undergo another rehabilitation. Two of them are the latest topographic conditions and the latest waste volume. The latest topographic surface is determined by aerial photogrammetry, utilizing a multi-rotor UAV. The output will be used to estimate the waste volume by differentiating the latest topographic surface data with the 2010 topographic surface data, which was acquired from the previous rehabilitation project. Unfortunately, the 2010 data comes with an unknown coordinate system, so these two surfaces cannot be perfectly overlayed. Thus, the 2D coordinate transformation has to be performed. The transformation parameters, derived from multiple common points, exhibit an accuracy of 30 cm. Following this transformation, volumetric calculations reveal that several areas have a total volume increase of 2.3 million m3. Contrary to that, the remaining areas have a total volume decrease of 23,742 m3.
Discovering Hidden Pattern in COVID-19 Prevention through Exit-Entry Permit Letter (SIKM) System using Geospatial Analysis
Authors: Ismanto B , Hawaari T R , Anugraha A S , Silitonga M S , Juliendra G , Alifiyanti H , Erdiza H P , Sari P R , Apriyadi D 
Published: December 2024

Abstract
COVID-19 was declared as a global pandemic in 2020, and described as a highly contagious virus that spreads through direct contact. Almost all countries affected by COVID-19 implement various steps to prevent its spread, one of which is lockdown, described as a prohibition of human movement outside the home. Jakarta, the capital city of Indonesia with a population of 10,609,681, implements restrictions on human movement entering and leaving of the city using the Exit-Entry Permit Letter (SIKM) system to prevent the spread of COVID-19. Lockdown does not chosen as option to prevent the spread of COVID-19 in Jakarta due to the consideration of its large population, which could have significant economic impacts on the community. Meanwhile, the SIKM system is designed to restrict the mobility of people entering and leaving Jakarta in order to control the spread of COVID-19, with the hope of minimizing significant impacts on the community’s economy. The aim of this research is to discover hidden patterns in human movement entering Jakarta through the SIKM system, utilizing geospatial analysis with Geographic Information System (GIS). The results of this research indicate that the central business district, known as the ‘Golden Triangle’ of Jakarta, emerges as the area with an economic activity zone with the densest hotspot as the primary destination for people during the implementation of the SIKM system. Furthermore, the hidden pattern of Jakarta’s spatial plan indicates that in general the economic activity tend to located in Central Jakarta, meanwhile the residence is tend to located around the borders of Jakarta. Therefore, with the geospatial analysis, hidden patterns of human movement during COVID-19 through the SIKM system can be identified for decision support system for Jakarta government.
Examining The Impact of The Transportation, Manufacturing, and Energy Sectors on Air Quality In Jakarta Using Spatial Regression
Authors: Iqbal M. , Susilo Bowo , Hizbaron D.R 
Published: December 2024

Abstract
This study employs Geographically Weighted Regression (GWR) to analyze the spatial distribution of air pollutants NO2, SO2, and CO in Jakarta and its surrounding areas, focusing on variations between dry and wet months in 2023. The analysis utilizes pollution data from Sentinel-5P images, processed using Google Earth Engine and ArcGIS/QGIS software. The study area, encompassing Jakarta and a 100 km radius, includes industrial and energy sector data to understand pollution source contributions. The GWR models explored three scenarios with different predictor variables: network density, number of intersections, and industrial proportion. The results reveal significant spatial heterogeneity in pollutant concentrations, with higher emissions during dry months. Scenario 1, which includes all predictor variables, shows the highest LocalR2 values in highly industrialized zones. Scenario 2, excluding the energy sector variable, demonstrates broader model applicability, while Scenario 3, with only transportation-related variables, offers the widest coverage but reduced specificity. These findings provide critical insights for policymakers to formulate targeted strategies for air quality management, aiming to mitigate the adverse effects of air pollution on the population.
Building Footprint Extraction from Fixed-Wing UAV Imagery using Mask R-CNN and Object-based Image Analysis Methods (Case Study: Banturejo Village, Malang Regency)
Authors: Hidayat Husnul , Dhihan Irawan Reyhan , Maulana Azhali Firmansyah 
Published: December 2024

Abstract
As a developing area in Malang Regency, Banturejo Village has many potencies since its location near the tourism area of Selorejo Dam. To maximally the harness of potencies while maintaining efficient land use in Banturejo village, mapping the built area in large scale should be carried out. The photogrammetric techniques using fixed-wing UAV could be a good alternative for large-scale mapping in this village area because of its capability to quickly acquire high resolution image with highly customizable mission specifications. But the problem arises in interpreting these imagery into meaningful cartographic representation which often requires cautious manual digitization in much slower rate that its acquisition. In this research the automatic image analysis method for building footprint extraction using Mask R-CNN algorithm and Object-Based Image Analysis was performed. The fixed wing UAV imagery was captured in 2023 and the structure from motion algorithm was employed for photogrammetric processing which produced 10-cm resolution orthophoto. Manually digitized building polygons from the same imagery serve as the gold standard for accuracy analysis, and small proportion of the data was used as training samples for the algorithm. The results shows that 1447 buildings with total area of 180,595 m2 was generated with Mask R-CNN algorithm, while OBIA-Mask R-CNN produced 572 buildings and total area of 201,932 m2. The confusion matrices reveal precision value of 77.94%, recall 51.54%, F1 Score 62.02% by Mask R-CNN method, and precision value of 35.95%, recall 9.21%, F1 Score 14.66% by OBIA-Mask RCNN method. Mask R-CNN method generated slightly lower accuracy of total building area, but in terms of precision the OBIA-Mask RCNN method produces lower number of building polygons.
From Space to Health: The Impact of Earth Observation Research on the Smart4COV19 Telemedicine project
Authors: Filchev Lachezar , Dimitrova Maria , Trenchev Plamen , Chanev Milen , Jelev Georgi 
Published: December 2024

Abstract
This study investigates the potential of Earth observation research in improving air quality management and supporting telemedicine initiatives in response to the COVID-19 pandemic. Utilizing ground stations in Sofia and Burgas, we collected hourly measurements of NO2, CO, PM10, and PM2.5. Satellite data from TROPOMI-S5p and ground-based air quality observations were integrated to assess the spatial distribution of surface particulate matter concentrations. Our results demonstrate the feasibility of leveraging satellite-derived atmospheric chemistry data to enhance air pollution modeling and urban-scale air quality management. Furthermore, the technology developed for Burgas has the potential for expansion to other Bulgarian cities and replication in different urban centers. Overall, this research highlights the importance of Earth observation research in addressing critical environmental and public health challenges. Telemedicine via smartphones can help manage these risks by offering assistance to patients with mild symptoms, thereby minimizing their exposure to COVID-19 patients. The study also presents the findings of models used to convert TROPOMI – S5p aerosol data into PM concentrations in Burgas, Bulgaria.
Three-dimensional City Modeling for Microclimate Simulation of Urban Areas
Authors: Izzah Aryana K , Hepi Hapsari H , Gusti Ngurah A I , Zenda Mergita F 
Published: December 2024

Abstract
Increasing urbanization and building density can trigger an increase in environmental temperature, thereby influencing urban climate change. Urban management that responds to climate change is urgently needed, requiring a smarter urban design approach than before. As geospatial science and technology develop, conventional two-dimensional methods will transition to more complex three-dimensional spatial modeling. This approach has great potential in supporting climate change-responsive decision making in urban environments. Three-dimensional city modeling at the LOD 2.0 level was used for the microclimate simulation. The research was conducted in the Central Business District (CBD) of Mayjend Sungkono, Surabaya, which has special urban characteristics related to the urban climate, such as variations in the use of building functions, such as residential, village, commercial, apartment, or hotel, as well as unique types of roofs in the area. The parameters used for the simulation included air temperature (°C), relative humidity (%), wind speed (m/s), and wind direction. Three-dimensional city modeling was performed using a semi-automatic method based on LiDAR data and aerial photos. The simulation was carried out by integrating three-dimensional city modeling with the visualization of microweather parameters in Envi-Met, along with pattern indicators from building facades. In addition, a vegetation scenario was created to reduce the temperature. The second factor is a comparison between the existing conditions and the scenarios that have been created.
Utilization of SAR Data to Evaluate Industrial Locations on the North Coast of Central Java
Authors: Mispaki Syachril W , Ar Rosyid Muhammad H , Rahmawaty Mitha A 
Published: December 2024

Abstract
Central Java province, located on the northern coast of Java Island, holds a strategic position as a busy land transportation route, connecting cities in southern Central Java and East Java with the capital city. The growth of industrial centers and industrial zones along the northern coast of Central Java is a positive effect of this position. However, the subsidence of land along the northern coast of Central Java is its negative impact. This can be detrimental to industrial areas and settlements along the northern coast of Central Java. Therefore, spatial planning must consider this land subsidence. The utilization of SAR data to periodically monitor land subsidence is crucial in formulating spatial arrangements that can accommodate the impact of land subsidence. In this study, to obtain land subsidence, the InSAR method was used. The data processed in this study consisted of Sentinel 1 from 2015 – 2023. It was found that land subsidence in the coastal areas of northern Central Java ranges from 0 to 25 cm per year. This data on land subsidence serves as an important basis for policymakers, planners, and stakeholders to develop more effective adaptation and mitigation strategies in spatial planning in the coastal areas of northern Central Java.
Integrating Remote Sensing and GIS for Precision Agriculture: Leveraging Google Earth Engine for Enhanced Agricultural Management
Authors: Yuli Handoko Eko , Fahriza Achmad , Muryono Mukhamad 
Published: December 2024

Abstract
This study aims to develop a plant health monitoring platform using Google Earth Engine and Sentinel-2 satellite imagery. This platform enables real-time and accurate monitoring of plant conditions in Ponorogo Regency, supporting better decision-making in agricultural management. The platform utilizes high-resolution multispectral data such as the NDVI, Chlorophyll Vegetation Index, and Normalized Difference Built-up Index to generate vegetation indices, providing comprehensive information about plant structure and condition. The Google Earth Engine platform offers a robust platform for monitoring and analysis functions within the platform, providing valuable insights for precision agriculture applications
Optimization of GGMplus Gravity Data to Identify Sumatran Faults Segments in Kaba Stratovolcano, Bengkulu, Revealed by FHD and SVD Techniques
Authors: Murdapa Fauzan , Sumanjaya Erlan , Ikhlas Fadli Darmawan , Ridki Permana Nanda , Sari Atika , Purqan Aulia 
Published: December 2024

Abstract
Kaba volcano is a perilous and currently active volcanic site located near the Sumatran fault, specifically within the Kepahiyang region of Bengkulu. Given the intricate nature of its location, it is crucial to monitor the local fault zone activity in the vicinity of the Kaba volcano. meanwhile, these fault zones are typically associated with high permeability areas and are characterized by high-density contrasts. Therefore, we applied First Horizontal Derivative (FHD) and Second Vertical Derivative (SVD) methods to identify the presence of the Musi Kepahiyang segment in Bengkulu, using GGMplus high resolution gravity data. Based on the results of the FHD analysis, clear gravity anomalies are observed along the northwest (NW) and southeast (SE) regions of Kepahiyang, with Bouguer anomaly values reaching 800 mGal. The discernible patterns unveiled through FHD analysis distinctly delineate the Musi fault (NW), Kepahiyang fault (SW), and Garba fault, unveiling a rich tapestry of tectonic activity surrounding the Kepahiyang area in Bengkulu. Complementing these findings, SVD analysis reveals a consistent anomaly distribution, albeit with marginally diminished Bouguer anomaly values, affirming the robustness of the detected features. Through the fusion of FHD and SVD methodologies, our study offers an understanding of the structural complexities pervading the segment in Kaba Stratovolcano, shedding light on its dynamic geological evolution, and fortifying our comprehension of fault dynamics in the Sumatra region.
Application of Density Lineament Mapping as an Indication of CBM Potential in Tanjung Agung, Muara Enim, South Sumatera
Authors: Singgih Purwanto Moh , Navisa Siti , Khadar Kinasih Ardelia , Ramadhani Yuniar , Winda Avrilla Vicka , Ayu Nuridhiani Fathan 
Published: December 2024

Abstract
Coal Bed Methane (CBM) gas is formed and trapped within coal seams, offering significant economic potential as it can be converted into electricity or transported through pipelines for various purposes. Indonesia is estimated to have approximately 574 trillion cubic feet (TCF) of CBM gas reserves, capable of meeting domestic energy needs. South Sumatera is classified as a province with the largest coal reserves in Indonesia, indicating abundant potential for CBM gas resources. This research aims to identify potential CBM indicators based on structural lineament interpretation using DEMNAS data. Field research was conducted to gather necessary data, and the findings from the study indicate that the surveyed area has a high potential for Coal Bed Methane (CBM) due to the high lineament density, ranging from 570/km2 to 710/km2 indicating high permeability that supports the well development of CBM gas. Optimal permeability can enhance the quantity of trapped Coal Bed Methane (CBM) gas, given the available space for the gas.