bluuebunny/crossref_metadata_2025_split huggingface dataset:
Above-ground biomass estimation of mangrove forest using WorldView-2 imagery in Perancak Estuary, Bali
Authors: Utari Dian , Kamal Muhammad , Sidik Frida 
Published: July 2020

Abstract
Global warming is the important issues because is caused by the concentration increase of greenhouse gasses in the atmosphere. Mangrove ecosystem has a function to reduce climate change through carbon sequestration. Estimates of biomass can be done through an approach from the value of vegetation biomass. Allometric equations method is used for calculating biomass values. Remote sensing technology is used for mapping mangrove ecosystems to determine the spatial distribution of mangrove biomass that is WorldView-2 (WV-2) image. Transformation of the vegetation index are Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) are used to estimate of mangrove forest biomass. The aim of this study is to determine the most accurate vegetation index in estimating the mangrove above-ground biomass (AGB) value. The field biomass data was obtained from mangrove tree diameter at breast height (DBH) measurement. Using the allometric equation, the field AGB can be calculated. A regression analysis between field biomass and WV-2 image pixel value was performed to build regression function to estimate the mangrove AGB. The results of this study show that the SAVI provided higher accuracy for mangrove AGB estimation with R2
of 0.4125 and resulting the AGB value between 1124.81 to 4499.25 kg/m.
Application of remote sensing and analytical hierarchy process (AHP) for developing landslide vulnerability zone in Boja District, Kendal Regency, Central Java Province
Authors: Prayudi S D , Trisnawati D , Putranto T T , Najib  
Published: July 2020

Abstract
Landslide is one of geomorphology process that can be a natural hazard for humans. An area has internal parameters that can cause landslide occurrences such as slope, lithology, rainfall, and hydrology. Furthermore, human activities can increase susceptibility for the landslide. Thus, the landslide vulnerability mapping is required to obtain potential of landslide susceptibility of an area. The study area is located in the Boja District. The goals are to determine the weight of internal factors which can cause vulnerable for landslide and to develop vulnerable landslide zone. The methods were remote sensing analysis using Digital Elevation Model (DEM) data and Analytical Hierarchy Process (AHP) to define the weight of internal parameters which cause a landslide. The results show that there are three levels of the vulnerable zone i.e. low, moderate, and high vulnerable levels of the landslide.
The influence of water balance in mangrove forests growth to mangrove’s degradation and depletion, case study: Southeast Asia
Authors: Wilwatikta F N , Sakti A D , Syahid L N , Wikantika K 
Published: July 2020

Abstract
As natural drivers of mangrove forests’ degradation and depletion, mangrove forests’ water balance, as the ability of them to absorb and release water, which is related to mangrove’s coefficient growth, also makes an impact to those circumstances. The intention of this research is to identify the mangrove growth coefficient that used to analyze mangrove’s water balance and to identify the influence of mangrove’s water balance from mangrove’s depletion and degradation. The research is situated at Southeast Asia in 2000 and 2012. As a proxy for mangrove coefficient growth, MOD13A1 V6 satellite imagery that provides vegetation index values were used and will be multiplied by using the linear regression model that establishes the relationship between vegetation index and mangrove coefficient growth. The procedure for quantifying the mangrove’s water balance is carried out by multiplying the mangrove coefficient growth with evapotranspiration data derived from MOD16A2 V5 and then deducting it by precipitation data from CHIRPS V2. The results presented will confirm how these parameters influence the mangrove’s water balance and influential or not against the mangrove’s lost.
GEOBIA for mangrove mapping using UAV-modified NIR 1 camera sensor
Authors: Khakhim N , Marfai M A , Putri R F , Wicaksono A , Lazuardi W , Isnaen Z , Walinono T 
Published: July 2020

Abstract
Mangrove ecosystem is a natural resource that can be beneficial for coastal community. One of its benefits is it can be utilized as an ecotourism spot such as Baros Mangrove Conservation Area in Kretek, Bantul. Hence, mangrove ecosystem must be conserved or expanded if possible. The first step to conserving mangrove ecosystem is to map its existing condition. UAV can be used to acquire a high-resolution imagery quickly. With modified near-infrared (NIR) sensor from a pocket camera can produce three band i.e. NIR, green, and blue that can be used to calculate several vegetation indices such as Simple Ration (SR), Normalized Difference Vegetation Index (NDVI), and Enhanced Difference Vegetation Index (ENDVI). Those bands and vegetation indices then used to map mangrove using Geographic Object-Based Image Analysis approach. The result indicated that high-resolution imagery from modified NIR camera sensor can be used to detect mangrove and distinguish it from other object using supervised classification. The digitally classified imagery then compared to manually digitized mangrove map to calculate the total error of the map.
Land surface temperature analysis based on land cover variations using satellite imagery
Authors: Himayah Shafira , Ridwana Riki , Ismail Arif 
Published: July 2020

Abstract
The remote sensing satellite sensor can not only record the visual appearance of the earth’s surface characteristics but also can capture phenomena that cannot be seen by a human, such as the earth’s surface temperature. Bandung is located at a basin-shaped area and has a variety of land cover, natural and man-made. The diversity of land cover is indicated to have an effect on the characteristics of the land surface temperature recorded by satellite sensing sensor. This assumption then examined by considering the land cover type and the value of land surface temperature as its parameters. This research aims to: 1) Estimating the land surface temperature with digital image processing, 2) Visual interpreting of land cover type based on land surface temperature similarity, and 3) Analyze the level of land surface temperature with a variation of land cover type in the south-western part of Bandung Basin. The visual interpretation method was used to obtain a land cover type with high-resolution image. Whereas the transformation of the Landsat 8 thermal band index is used to acquire the land surface temperature. An analysis was carried out to observe the results of land surface temperature estimation and land cover based on land surface temperature resemblance. Then it is expected to be a consideration in terms of determining policies regarding conversion of land cover from natural to artificial forms indicated as a contributing factor to rising land surface temperatures.
Stream order selection for model generalization of the topographic map of Indonesia
Authors: Hidayat Fahrul , Purwono Nugroho , Susetyo Danang Budi , Hariyono Mochamad Irwan , Rizka Tia , Rachma Nuzula , Windiastuti Rizka 
Published: July 2020

Abstract
The importance of stream networks is related to other features in the topographic map e.g. as weighted-parameter for contour derivation. The generalization of these features needs complex parameters specifically geometrical and conceptual aspects. Geometric parameters consist of stream length and vertices, while the conceptual part handles stream networks connectivity as logical consequences. Stream networks selection is a type of important step on map features analysis and in map databases. This paper proposes a new approach for stream networks generalization of Topographic Map of Indonesia (as known as RBI) for 1:5,000 to 1:25,000 of scale by using geometrical and conceptual parameters. Three stages used in this research were: data pre-processing (include resolving the topological errors), generating stream order (1:5,000 of scale as an input), comparing stream order algorithms (Strahler, Scheidegger, Shreve, and Drwal), and performing feature similarity-based analysis (comparison of stream ordering results and 1:25,000 of scale). The research resulted four different stream orders and eight different similarity-analysis values since each algorithm was tested in two scenarios (in 1st scenario, order > 1 were selected while in 2nd scenario, order > 2 were selected). Eventually, after comparing those results, the Scheidegger method obtained the highest similarity value in on both 1st and 2nd scenarios. Further, generalization by using stream order selection delivered the representation of river in constructing map elements of RBI.
Early study of magnetic permeability and magnetic susceptibility of peat in Ogan Komering Ilir, South Sumatera, Indonesia
Authors: Anisah  , Marpaung F , Purwandani A , Nugroho D , Sumargana L 
Published: July 2020

Abstract
Increasing peat fire in Indonesia have encouraged government or research institutes to develop an early warning system. This system needs various parameters in order to have an accurate result. Magnetic permeability and susceptibility are the physical properties of peat which expected to support this system. Field and laboratory measurements were conducted to determine the relationship between the peat temperature rise and the physical properties of the peat. A total of 30 samples was collected from Ogan Komering Ilir (OKI) Regency, South Sumatera, Indonesia. Each sample was tested with a temperature rise of 20°C until reach the convergent temperature. Statistical analysis were then performed. The results show that the magnetic permeability correlate with the peat temperature but the coefficient of the linear regression model is very small, with the constanta of 1.0022 from the linear regression model. In addition, magnetic susceptibility have a small correlation and a small determination coefficient with temperature. Therefore, it indicates that magnetic susceptibility can’t support this system.
Oil spill contingency plan (OSCP) by environmental sensitivity index (ESI) analysis at East Barito District, South Barito District and Kapuas District (Tamiang Layang, Buntok and surrounding area), Central Kalimantan Province
Authors: Hernawan Undang , Risdianto Rahayu Kusuma 
Published: July 2020

Abstract
The central Kalimantan has envolved into a new oil and gas industry area where potential impact on environmental need to be anticipated comprehensively for environmental protection from oil spill. The locations are East Barito District, South Barito District and Kapuas District (Tamiang Layang, Buntok and surrounding area), Central Kalimantan Province. The main problem of this study is determining areas of sensitive and vulnerability to oil spill. The aims of study were to identify the factors and components that affect the level of ESI to oil spill and analyse and establish environmental sensitivity rank for oil spill contingency plan. The methodology of study carried out by identifying and assessing each landuse unit and analyse performed by GIS method with ESI formula. Interpretation and classification of landuse used Landsat TM imagery that acquired in 2014 and updated in 2018 and field survey in October 2014. The result of analysis showed environmental sensitivity index divided into four categories, dominated by high sensitive (40,8%) due to the presence of protected and conservation forest, less sensitive (31,9%), moderately sensitive (14,6%), and insensitive (12,8%). General condition of study area is lowland and swamp area and potential to flood. The environmental protection from oil spill should be mitigated and prioritized for sustainable development.
Precise topographic mapping using direct georeferencing in UAV
Authors: Syetiawan A , Gularso H , Kusnadi G I , Pramudita G N 
Published: July 2020

Abstract
Mapping using UAV has become very popular today due to the rapid development of electronic technology. UAVs are needed to support rapid mapping activities, such as natural disaster management, SAR applications, agricultural applications and forest fire monitoring. In addition to spatial resolution, it is also needed the accuracy of position accuracy. In general, the georeferenced process of aerial photo processing uses Ground Control Points (GCP) from GPS measurements. The disadvantage of using GCP is that GPS measurement takes a long time and the costs incurred are relatively more expensive. For this reason, certain techniques are needed to produce topographic maps with more efficient times. Direct Georeferencing on UAV is an aerial triangulation technique without the use of ground control points (GCP). Direct Georeferencing techniques will cut field surveys and produce high accuracy topographic maps. The hope is that by using this technique, the measurement of tie points can be as minimal as possible and do not even need to use a control point. This study is to evaluate Direct Georeferencing techniques in UAVs to produce accurate topographic map. Aerial photo using multi rotor UAV DJI Phantom 4 RTK/PPK. This multi rotor is equipped with a high accuracy GPS antenna and that is capable to storing GPS observation data. Photo coordinate processing using the Post Processing Kinematic (PPK) method. Accuracy of ortho rectification results of aerial photo geometry compared to check point coordinates (CP). The test results of horizontal accuracy indicate the value of 0.040 m using Circular Error 90% (CE90). Based on BIG standard the accuracy of the base map, these results can be entered on a scale of 1: 1,000 class 1. Direct Georeferencing techniques in UAVs produce high accuracy maps for relatively not extensive mapping areas.
Preliminary study on validation of HIMAWARI-8 data with ground based rainfall data at South Sumatera, Indonesia
Authors: Meliani F , Sulistyowati R , Permata Z D O , Sumargana L , Amaliyah R , Purwandani A , Putrantijo N , Ramadhan A R 
Published: July 2020

Abstract
An accurate rainfall data has an important role in the Indonesia Fire Danger Rating System (Ina-FDRS) which has been developed by PTPSW – BPPT since 2017. Continuing the previous study, during wet and dry season, an accurate rainfall data becomes one of the important inputs and has big impact on the Ina-FDRS. Unfortunately, surface rainfall data from AWS and ARG have limited availability especially on the spatial resolution data, therefore Ina-FDRS will use HIMAWARI-8 rain rate data as an input. On the other hand, satellite rainfall data also has limitation on the accuracy, HIMAWARI-8 detects top cloud temperature, then by using IMSRA method to calculate rainfall values. This preliminary study aims to validate rain rate from HIMAWARI-8 satellite image data with ground-based rainfall data from AWS/ARG during fire and non-fire period, from 1 – 31 August 2015 and 15 April – 15 May 2018. Afterward, we will use the validated rainfall data as an input for Ina-FDRS.
Assessing the effect of various training and testing set ratios to model the satellite derived bathymetry
Authors: Dewi R S , Lumban-Gaol Y , Safi’I A N , Rizaldy A , Syetiawan A , Rahadiati A 
Published: July 2020

Abstract
Depth determination in shallow water area is critical to model for instance, a detailed shoreline position, a change in beach topography, and the potency of beach erosion. Multispectral images can provide a complete map of areas that are difficult to map by conventional hydrographic surveys due to their logistics difficulties and limited spatial coverage. The aim of this study is to evaluate the effect of various training and testing set ratios to model bathymetric data from remotely sensed imagery. This research applied three methods to derive shallow water bathymetric data tested on two subsets located along Tanjung Kelayang coastal areas. The methods combined echo-sounding measurements and the reflectance of blue, green, red and near infrared of Sentinel 2A image with 10 m spatial resolution. In the experiment, the echo-sounding data set was split into training and testing set in three different ratios to see the effect of these various training and testing ratios to the accuracy of all algorithms. From the results, we can see that all models perform well in estimating bathymetric data for the shallow water depth, however, the accuracies were slightly changing by the variation of the training and testing data included in the model. In general, all methods provide a comparable performance for shallow water depth with RMSE less than 1 m and can be used effectively for deriving accurate and updated medium resolution bathymetric maps.
Spatial analysis of rice phenology using Sentinel-1 and Sentinel-2 in Karawang Regency
Authors: Supriatna  , Rokhmatuloh  , Wibowo A , Shidiq I P A 
Published: July 2020

Abstract
Karawang Regency is the top rice producer within West Java, Indonesia. Accurate information about the number of harvest area is essential in rice production in Indonesia. The Sentinel imageries (Sentinel-1 and Sentinel-2) which have a spatial resolution of 10 meters can provide spectral information on the earth surface in relatively narrow temporal resolution. The study aims to spatially analyze the rice field phenology using Sentinel-1 and Sentinel-2 imagery and estimate the rice productivity in Karawang Regency. The study used Synthetic Aperture Radar (SAR) Sentinel-1, with the C-Band, which are capable of monitoring rice phenology and Sentinel-2. The combination of polarization from SAR and vegetation index algorithm from the optical image are used to determine the age of rice plants, which then used to estimate rice productivity. The stage of rice was land preparation, vegetative, generative, and harvesting. The result from the estimation of harvest area is between 102,965.00 - 109,338.27 hectares, and the estimation of rice productivity is 5-6 tons/hectares in Karawang Regency.
A fusion of digital elevation model based on interferometry SAR technique from ascending and descending path in urban area
Authors: Arief Rahmat , Dyatmika Haris Suka , Suhermanto  , Ali Shadiq 
Published: July 2020

Abstract
The height of the earth’s surface can be measured using synthetic aperture radar (SAR) images using interferometry (InSAR). The InSAR method uses phase information to produce the height of the earth’s surface. The accuracy of the DEM produced by InSAR depends on the shadow, the layover area, and the coherence of two SAR data. This paper proposes a technique for combining DEM derived from the InSAR method from ascending and descending paths using high resolution TerraSAR-X/TanDEM-X. Generating DEM was done by the InSAR method which covers the same test area and came from one pair of ascending TanDEM-X images and one descending pair of TerraSAR-X. The combination of the two DEMs from the ascending and descending path has been done by assessing the weighting factors so that the accuracy of the DEM can be increased. The weighting factors are calculated from the height error map, layover and shadow map. The height error map is calculated from the interferometric coherence with geometrical considerations and the layover and shadow map is calculated using TerraSAR-X/TanDEM-X DEM. The images pairs with 33 angles and 37 degrees were used in this study for the InSAR method in urban areas (Jakarta city). The experimental results show a significant reduction in missing pixel counts due to layover, shadow and low coherences after combining.
Profile of dielectric constant of peat in Ogan Komering Ilir Regency, Indonesia using SAR Sentinel-1 and ground penetrating radar
Authors: Marpaung F , Sumirah  , Sumargana L , Nugroho D 
Published: July 2020

Abstract
Profile of dielectric constant of a substance or a surface indicates its electromagnetic parameters. The profile is associated with electric polarization, permeability with magnetic polarization, and conductivity with an electric current field. In the practice, the Synthetic Aperture Radar (SAR) and the Ground Penetrating Radar (GPR) are commonly utilized to determine how much velocity of a substance and its scattering profiles. However, information about the profile radar scattering mechanisms in tropical peatland is still limited. Therefore, we evaluated dielectric constant from the field using GPR and estimated its spatial variation from a dual-polarization Sentinel-1A type C-band SAR in Ogan Komering Ilir, South Sumatera Province, Indonesia. We measured dielectric constant at the two major types of land use, namely oil palm and acacia. Results indicated that the dielectric constant derived from SAR Sentinel-1A and GPR are affected by peat moisture. It increases as the peat moisture increases. Results show that during peat dry conditions, the profiles of dielectric constant derived from dual-pol Sentinel-1A images are relatively similar to the dielectric constant of peat in Siak Regency. It ranges between 31.78 and 59.3. The dielectric constant derived from GPR ranges between 69 and 70.
Utilization of google maps for depicting landslide pattern in Indonesia
Authors: Sukristiyanti S , Wikantika K , Sadisun I A , Yayusman L F , Pamela P 
Published: July 2020

Abstract
The historical landslide data in GIS (Geographic Information System) environment is valuable to estimate pattern in landslides distribution and frequency, which are useful for landslide hazard analysis and mitigation. By using the landslide reports released officially by The National Agency for Disaster Management (BNPB), those non-spatial data need to be converted into the spatial ones. The reports primarily contain location, date of event, impact and triggering factor. This study is exploring Google Maps which is a web mapping service to process the historical landslide data of Indonesia. By preparing historical landslide data in the form of spreadsheet, Google Maps directly can change the whole data into a custom map ‘landslide distribution map’. The attribute can be edited, the map can change interactively, and vice versa. The appearance of the custom map can be styled by a certain column so its statistical information comes up. A landslide distribution map produced in Google Maps can be shared to others and can be exported as a GIS layer for further analysis. This article shows the utilization of facilities provided by Google Maps to prepare and analyse the landslide inventory map.
Geometry accuracy analysis of the three-dimensional model using the close-range photogrammetry method for conservation object of culture (case study: Cow Statue, Faculty Of Livestock, Diponegoro University)
Authors: Prasetyo Yudo , Bashit Nurhadi , Silaen Billy 
Published: July 2020

Abstract
Conservation of cultural objects in the form of maintenance and protection to keep objects from damage and authenticity important. Documentation using a three-dimensional model (3D model) is a cheap, effective and relatively fast solution. The documentation results in the form of a three-dimensional model, which itself must have a good fit of visuals and geometry. The purpose of this study was to analyze the geometry accuracy level and the suitability of the three-dimensional model of physical objects using the close-range photogrammetric method (CRP). This study, using a non-metric camera, namely a DSLR camera to take photos of objects simultaneously and thoroughly according to the CRP concept. The results of the photos are processed based on near-range photogrammetric methods using the VisualSfM technique in point cloud creation followed by Meshlab in making three-dimensional models. The results showed that the shape and color of the model were quite good but still had some rough areas due to a lack of point cloud data. The level of color suitability of the digital model is quite good with several colors in coarse-textured areas that look less suitable for physical objects. The suitability of the geometry of the model through the difference in distance between the test points has an average of 3.524 mm and a standard deviation of 2.989 mm.