bluuebunny/crossref_metadata_2025_split huggingface dataset:
Construction of 3D Virtual Reality Insect Model Based on Ips typographus L
Authors: Wang XuanYao , Xiao Wei , Wang Zhiming , Shi Liwen 
Published: July 2020

Abstract
The development and application of the digital model database of insects has an academic and also practical value. To find a proper way of building 3D Virtual Reality Insect Model, we briefly studied the application in different fields of digital modeling technology and points out that artificial modeling technology is suitable for the 3D virtual insect data model. We also discuss the pipeline of making digital model database of insects and take an example of constructing digital model on bark beetle, Ips typographus L.
Optimization Model of Shortest Distribution Path Selection in Intelligent Logistics
Authors: He Lin 
Published: July 2020

Abstract
In order to quantitatively analyze the relationship between intelligent distribution path selection and logistics economic development and promote the development of logistics economy, an optimization model of intelligent logistics shortest distribution path selection is proposed. This paper analyzes the statistical characteristics of intelligent distribution path selection to the development of logistics economy, adopts the shortest path optimization method to select the intelligent distribution path, constructs the big data statistical analysis model of intelligent distribution path selection and logistics economic development by using quantitative regression analysis method, analyzes the development factors of logistics economy by intelligent distribution path selection combined with multiple linear fusion method, and combines the fuzzy constraint control method. Realize the optimization of logistics intelligent distribution path. According to optimization The distribution effect is modeled by statistical analysis of logistics economic development, and the quantitative relationship between intelligent distribution path selection technology and logistics economic development is analyzed. The results of empirical analysis show that the intelligent distribution path selection has a significant level to the development of logistics economy. This method has good optimization for logistics distribution path selection, improves logistics throughput and promotes the development of logistics economy.
Experiment of Stereo Matching Algorithm Based on Binocular Vision
Authors: Lv Dongdong , Jiao Guie 
Published: July 2020

Abstract
Binocular stereo matching is a hot topic in 3D reconstruction, target detection and target tracking. Through experiments, this paper analyzes and compares several classic binocular stereo matching algorithms, and finally selects SGBM with good comprehensive performance. Moreover, based on this, it gets accurate window size parameters through experiments, which provides a basis for the following 3D modeling.
Environmental Characteristics of World Heritage Sites Based on High Resolution Remote Sensing Data: A Case Study of Hailongdun, Guizhou Province
Authors: An Youzhi , Ma Fujun 
Published: July 2020

Abstract
In this study, by using descriptive statistical analysis and the method of setting up multiple study areas for comparison, with the help of high spatial resolution remote sensing interpretation data, the spatial distribution characteristics of land use in the study areas of World Heritage occurrence environment are studied. The results show that: (1) the mean value of each occurrence environment of Hailongdun World Heritage site is small, the degree of patch fragmentation is large, and the corresponding standard deviation is large, which is caused by the large difference of patch size. (2) The area of residential land, industrial and mining storage land, special land, cultivated land and forest land in Hailongdun World Heritage site is increasing from the core area, buffer area, Hailongdun village to the village boundary, which is in direct proportion to the area change of each environment.
Hotspots and Frontiers of Chinese Consumers’ Online Shopping Willingness -- Visualization Analysis of Bibliometrics Based on CSSCI (2005-2019)
Authors: Zu Xu , Gou Qingxin , Duan Renji , Guo Yunfeng , Zhang Zhengjie 
Published: July 2020

Abstract
In order to objectively reflect the development status and hotspots of research on consumers’ online shopping willingness, this article uses the relevant literature included in CSSCI as a data source, and uses Citespace software to visually analyze research results related to consumers’ online shopping willingness. The main authors and institutions, research hotspots and the frontiers of the context are discussed. It is found that the research on consumers’ online shopping willingness is currently in the development stage, which mainly focuses on the hot topics such as perceived risk, perceived value, trust, and on the cutting-edge content such as online shopping willingness of fresh produce and e-commerce marketing models.
Study of base map and marine thematic map usage to make coastal waters location permits map in coastal waters and small islands (study area: maratua island, east kalimantan)
Authors: Azzahrah S , Astor Y , Sidqi M 
Published: July 2020

Abstract
Indonesia has 6.315.222 km2 of marine areas, 16.065 islands, and 99.093 kilometers of coastlines. The government arranges Coastal Waters Location Permit regulation to manage its abundance of marine resources. But there are no technical aspects that control the marine base and thematics map usage to make the Coastal Waters Location Permit Map. This research examines the usage of Base Map (LLN Map, RBI Map, and Nautical Chart) and marine thematics map (RZKSNT Map) in Coastal Waters Location Permit Map establishment by plotting the site plan in each base and marine thematics map. This study covers technical aspects such as scale, projection system, horizontal datum, vertical datum, and site plan’s area comparison. This study finds that the base map which fits the most in Coastal Waters Location Permit Map establishment is a base map that has sea depth information with a scale no smaller than 1: 50,000 at the latest year so that it has high horizontal accuracy and denser contour intervals. The area calculation comparison result by digitizing and mathematical methods (manual calculation) does not obtain any significant differences in the value of the Location Permit object area, the largest difference in the area for each method is 0,0003%.
Driving-factors identification of land-cover change in west java using binary logistic regression based on geospatial data
Authors: Pasaribu Udjianna Sekteria , Virtriana Riantini , Deliar Albertus , Sumarto Irawan 
Published: July 2020

Abstract
The Land is a fundamental factor in production activity. Accordingly, it is closely related to economic growth—which supports the living needs of human beings. In many cases, human activities related to land use are often uncontrollable, impacting many negative effects on the environment, both locally and globally. More broadly, these activities will lead to some changes in land cover and some other physical features such as climate. In order to understand the phenomenon of land cover changes, we approach them through modelling. To detect any changes in land cover in a region, it is necessary to identify the driving factors causing land-cover change. The relation between driving factors and response variables can be evaluated by using regression analysis techniques. In this case, land cover change is a dichotomous phenomenon, i.e., binary. Binary Logistic Regression (BLR) model is one of the regression analyses which can be used to describe the nature of dichotomy. From the results of this study, the driving factors causing land-cover change in West Java were found, those are: the distances to the central business districts in some certain areas such as Bandung City, Bekasi Regency, Bekasi City, Bogor Regency, Karawang Regency, and Sukabumi Regency; the distance to the the capital of the province; the distance to the main roads; the population numbers; and some physical features of the land such as slope, curvature, and height. This predictive model had an accuracy level of 49,79%, which equals to 1.827.217,44 ha area.
The effect of using different vegetation indices for mangrove leaf area index modelling
Authors: Prananda Aldo Restu Agi , Kamal Muhammad , Wijaya Kusuma Denny 
Published: July 2020

Abstract
Spectral vegetation index (SVI) is a mathematical combination of image spectral bands, especially ranges from visible to near infrared portion of the light spectrum. The purpose of SVI is to emphasize the vegetation content information from an image and doesn’t directly correlate with any physical or bio-physical characteristics of vegetation. One of the important biophysical parameters of vegetation that can be derived from SVI is Leaf Area Index (LAI). LAI can be defined as one half the total green leaf area per unit horizontal ground surface area and considered as an indicator to determine the level of mangrove health. Various SVIs have been developed and different SVI affects the accuracy of the LAI model. This study aimed to (1) compare and contrast the performance of several SVIs applied to WorldView-2 (WV-2) image to estimate the LAI, and (2) find the most accurate model for estimating LAI of mangrove forest in Perancak Estuary, Bali. The SVI used are Simple Ratio (SR), Normalized Differenced Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Green Atmospherically Resistant Vegetation Index (GARI), dan Wide Dynamic Range Vegetation Index (WDRVI). The LAI models developed were based on the semi-empirical relationships between SVIs and field LAI measured from hemispherical photograph. The corresponding values of both parameters were correlated to find the regression function for the modelling. The results show that the best accuracy was obtained from NDVI which has an R2
value of 0.83 and an estimation accuracy of 89.10 %.
Land cover identification using Pleiades satellite imagery by comparison of NDVI and BI method in Jatinangor, West Java
Authors: Arini Dwi , Guvil Quinoza , Wahidah Nur 
Published: July 2020

Abstract
Land cover monitoring is important to maintaining human needs and ecological function balance that will be able to observe, analyse, and present land use form. Some methods that can be implemented to this case are Normalized Difference Vegetation Index (NDVI) and Bare soil Index (BI). Land cover identification is using Pleiades images in 2018 for Jatinangor area, with land cover classes were built in five class, divided by producer’s and user’s accuracy and validated with field survey results. Accuracy of NDVI method is 69.56% with kappa 0.57 also producer’s accuracy is 73.94% water bodies, 84.88% built land, 67.37% open field, 98.79% crops field, and 98.79% vegetation. User’s accuracy in a row for each class are 26.86% 82.78%, 20.01%, 76.15%, and 75.37%. The Accuracy of BI method is 69.17% with kappa 0.52. Producer’s accuracy for each class is 73.28% water bodies, 70.71% land build, 52.83% open filed, 63,04% crop field, and vegetation with 81.29%. User’s accuracy in a row for each class is 17.05%, 81.29%, 21.44%, 65.13%, and 88.54%. Validation of NDVI more fit in the field than BI that can be concluded NDVI has a good result than BI.
Analysis of dominant land cover class based on land change cluster pattern in West Java Province
Authors: Simanjuntak Christopher Imanuel , Deliar Albertus , Virtriana Riantini 
Published: July 2020

Abstract
Study of land cover change is important in order to understand the global environmental change. One of the causes of land cover change is human activity in an effort to fulfil their needs, such as agriculture and settlement. In an administrative area, land cover change occurs in several locations and sometimes grouped in adjacent locations. Each location may have different type of land cover change. The understanding of land cover dynamics can be enhanced by identifying the dominant land cover change, which will lead to a better land cover management. By analysing each grouping area, it indicates the pattern and concentration of the type of land cover change, so it can appropriately support the regional management and development strategies. Hence, it is necessary to identify the characters of each grouping area so that the characteristics of the class of land cover change can be obtained. The dominant land cover change is identified by analysing the mode of land cover change in each area. The results show that the dominant land cover change in West Java in 2005-2010 are heterogeneous, with the top three broadest classes changes are rice field to field/moor (144,662.76 hectares), forest to fields/moor (36,339.84 hectares), and fields/moor to settlement (36,069.39 hectares). This study managed to identify 99.94% of the grouping areas are the dominant land cover change and 0.06% of the grouping areas are remained the same class. These results are expected to continue the development of land cover change model in West Java.
Current development of community satellite processing package (CSPP) to support direct broadcast remote sensing satellite data processing
Authors: Gustiandi Budhi , Monica Donna 
Published: July 2020

Abstract
The Community Satellite Processing Package (CSPP) is developed by the Cooperative Institute for Meteorological Satellite Studies (CIMSS) at the Space Science and Engineering Center (SSEC) at the University of Wisconsin to support Direct Broadcast (DB) communities in processing various remote sensing satellite data. Currently, there are eleven satellites and 25 instruments supported by fifteen CSPP packages. Some packages have dependency with another package when an output of a package become an input to another package. However, there is no document that describes relationships among input and output data of the packages. Each package is only accompanied by its installation instruction and user manual. Thus, a main document describing interdependency of the packages is required. This paper can act as the main document because it describes the current development of the CSPP packages and their interdependency among one another. Information was gathered through installation, user manual and literature (proceedings and journal articles) reviews. The results are illustrated in term of intuitive diagrams that are not available in the current instructions or manuals. Thus, the main document that is described in this paper can be utilized to identify gaps that should be taken into considerations when developing the existing system in the future.
Habitat suitability modelling of Pasak Bumi (Eurycoma longifolia Jack.) in Riam Kanan conservation forest zone using Sentinel-2 biophysical parameters
Authors: Fithria Abdi 
Published: July 2020

Abstract
Pasak bumi usually grow under the tree canopies. So that the character of its habitat is assumed to be estimated using several biophysical parameters of the tree canopy around it. The purpose of this research was to model the suitability of the pasak bumi habitat in the Riam Kanan conservation forest zone, using a number of biophysical parameters extracted from Sentinel-2 MSI imagery. Those parameters are Leaf Area Index (LAI), Canopy Chlorophyll Content (CCC), Canopy Water Content (CWC), Fraction of Vegetation Cover (FVC), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). Ground surveys were carried out to find the coordinates of pasak bumi using accidental sampling method. Pasak bumi coordinate points are overlaid with biophysical parameters. Statistical analysis was then applied to predict the range of population values from each biophysical parameter, using Confidence Interval (CI) 95%. The results of the research show that CI LAI 2.532-2.772, CI CCC 137.101-158.028 gr/cm2, CI CWC 0.05-0.057 gr/m2, CI FVC 0.698-0.737, and CI FAPAR 0.732-0.765. The values of these biophysical parameters directly describe the biophysical characteristics of the pasak bumi habitat in the research location. These CI values are then implemented using binary modelling to predict the habitat of pasak bumi. Based on the results of modelling, it was found that the area suitable for pasak bumi plants was an area of 1,807.91 hectares. This area has a proportion of 1.55% of the total area of the conservation zone. To improve accuracy, other biophysical parameters can be considered to be involved in modelling.
Analisa filter spekle single dan multitemporal data Sentinel 1-A
Authors: Indriasari Novie , Arief Rahmat , Kustiyo  , Budiono Marendra Eko , Dyatmika Haris Suka , Rahayu Mulia Inda , Payani Agnes Sondita , Amriya Qonita , Maulana Rahmat , Ali Shadiq 
Published: July 2020

Abstract
Speckle is noise found in SAR data that will affect the image interpretation process. To reduce the presence of speckle in SAR data, a speckle filtering process is needed. This study will evaluate the multi temporal speckle filtering for Sentinel-1 image, VH polarisation. The data used in this study are 30 SENTINEL-1 images recorded in different seasons in 2018. The methods applied for multi temporal speckle filters are Boxcar, Frost, Lee, Gamma Map and Lee Sigma with window sizes of 5x5 and 7x7. The quality test for speckle filter results will be done qualitatively (by looking at the visual appearance of the filter results) and quantitatively (Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Normalized Mean (NM). The best qualitative and quantitative multitemporal speckle filter results are obtained from the Frost Filter 5x5 with a minimum of 3 scene data.
Prediction and location suitability of settlement growth at The BWK II of Semarang City
Authors: Pigawati B , Sugiri A , Putra I N A M , Suryani T A 
Published: July 2020

Abstract
Population growth in urban areas leads to the increasing demand for settlement areas and the expansion of settlement growth in inappropriate locations. Semarang is one of the important metropolitan cities in Indonesia which has problems with the supply of settlement areas. The main focus of this research is to understand the problem, including the aspects of settlement growth, forecasting, and proposing recommendations for expansion of the settlement areas. The study area is BWK II of Semarang City which consists of two Districts, Candisari and Gajahmungkur. The study area is a very potential area for settlement growth. The aim of the research was to predict the settlement growth and assess the location suitability of settlement growth based on the Master Plan document of Semarang City. The primary data for the study is obtained from QuickBird data image, and the spatial analysis was conducted by utilizing Remote Sensing, Geographic Information System, and LanduseSim as the software for prediction simulation. Accessibility and existing settlement location are considered as the driving factor while the river is considered as the constraint factor. The result of the study shows that the prediction of settlement growth is mostly consistent with the Master Plan of Semarang City. The study provides evidence that settlement growth was also observed in the conservation area and flood-prone area which are restricted for further development. The findings are beneficial for planners to reformulate the policies and strategies for future settlement growth.
Design of automate SAR processing system in LAPAN to support easier and fast data services
Authors: Budiono Marendra Eko , Dyatmika Haris Suka , Indriasari Novie , Amriya Qonita , Arief Rahmat , Maulana Rachmat , Ali Shadiq 
Published: July 2020

AbstractOne of the Indonesia’s National Institute of Aeronautics and Space (LAPAN) task is to supply and distribute remote sensing data based on Indonesia national needs as mandated by space law no 21 year 2013. One of the satellite image acquired and distributed by LAPAN including TerraSAR-X/TanDEM-X, a twin satellite from Germany launched in 2007. Acquisition of the TerraSAR-X/TanDEM-X satellite began in 2017 with aim for coverage of whole Indonesian area. With respect to the data size and data availability, an automate data processing method is needed to process all of the available TerraSAR-X/TanDEM-X data. This paper will discuss a system design that automate the LAPAN’s TerraSAR-X/TanDEM-X data processing and method of presenting the data to the users as tiled data.
LiDAR application of intertidal coastal zoning for aquaculture in Wolo Village, Kolaka, Southeast Sulawesi
Authors: Ulfiasari S , Ratri S D 
Published: July 2020

Abstract
Coastal Zones or Regions have abundant natural resources, support polluted areas’ welfare and are a source of regional income. Wolo Village coastal resources supporter a regional economy covering 3.44 square kilometers, as it is presented in the RTRW master plan and included in the regional-based maritime and fisheries and economic development concept (Minapolitan). The characteristics of the Wolo village coast support various types of aquaculture which are beneficial to its population. However, for sustainable growth, there is a need for aquaculture zoning of the intertidal areas. This zoning will provide the means to maintain the balance of coastal resources, ensures sustainability and it will support government developing programs. Intertidal coastal area zoning can be carried out by a zoning system that obtains space utilization in accordance with a criterion that supports the sustainable development of existing coastal resources and follows the RTRW master plan. To determine the physical condition of region spatially, DTM and DSM data obtained from Light Detection and Ranging (LiDAR) data can be used. The sustainable zoning boundaries for each cultivation would be found by using Geographic Information System. The results obtained using this method are that most of the coast in Wolo village included in Zoning III, which has potential for the development of coral reefs cultivation and Zoning I, which has the potential for the development of seaweed cultivate. From the obtained results, it can be concluded that the potential on the coastal of Wolo Village, as a producer of seaweed that can be further developed in accordance with sustainable zoning program and support the national Minapolitan Area.
Investigation method for shaded coffee plantation detection using aerial photography
Authors: Tridawati A , Wikantika K , Harto A B , Ghazali M F , Suprihatini R , Suhari K T 
Published: July 2020

Abstract
Coffee plantation is one of the main agricultural sectors in the world, especially in Indonesia. For sustainable coffee management, it is important to obtain an assessment of the spatial distribution of coffee plantation. In fact, most of the coffee trees planted under the forest canopy as jungle coffee. However, remote sensing studies devoted to coffee in Indonesia have been limited due to spectral similarity with forest. Hence, the shaded coffee plantation has been difficult to be mapped. This condition takes aerial photography as an alternative solution to detect the distribution of shaded coffee plantation with high spatial resolution. This paper presents an assessment of the classification method of aerial photography for detecting shaded coffee plantation. The data used in this study is aerial photography captured in a shaded coffee field located in Gunung Puntang. Some classification methods namely Pixel-Based and Object-Based Image Analysis (OBIA) were used. Those method performances were evaluated by comparing the classification result as overall accuracy. The result shows that OBIA is the best method for detecting shaded coffee plantation. It produces an overall accuracy of 73.01%.