bluuebunny/crossref_metadata_2025 huggingface dataset:
Wildlife Tourism Experience Based on Web Text Analysis
Authors: Wang Yiran
Published: July 2020

With the improvement of living standard, people are becoming more and more interested in traveling, especially to visit wild animals. How to analyze the tourism experience of tourists visiting wild animals has become a research hot spot. The text comments left by tourists on the Internet can provide relevant information, so it is essential to carry out the research on the tourism experience of wild animals based on the text analysis on the Internet. The purpose of this paper is to solve the problem on how to understand the tourism wild animals after the visit of the tourism experience problems, by studying the current common network text analysis method, the tourists leave comments on the Internet information extraction, using relevant software comprehensive analysis of relevant information, using content analysis and qualitative analysis of a combination of both sexual themes, on how to analyze tourism personnel to visit wildlife tourism experience has carried on the detailed analysis and research. The tourism experience of wildlife tourists is analyzed in detail and accurately. The results show that the core themes of wildlife tourism experience are tourists, destinations and wildlife. When tourists visit wild animals, they are more likely to take photos and get close contact with them. They are closer to wild animals and interact with them more, which means that tourists are more satisfied with their tourism experience. This web-based text analysis method is 20% more efficient than traditional methods such as questionnaires.
Design and Development of Two-level Deployed and Multi-level Applied Electric Energy Substitution Effect Improvement and Business Expansion Support Software
Authors: Miao Bo , Li Chang , Liu Hao , Lin Jingyi
Published: July 2020

With the in-depth promotion of electric energy substitution and the rapid development of grid informationization, the building of systematic and integrated electric energy substitution effect improvement and business expansion support software becomes an important means to further optimize the electric energy consumption management level and realize the overall improvement of electric energy utilization efficiency. This paper introduces the design idea of this software, shows the layer structure of the platform, describes the relationships among all layers, analyzes the key technologies of the system, and researches and designs the general architecture and function modules. This platform provides the strong technical support for the state to promote the lean management of electric energy substitution and for the State Grid to develop the building of electric energy substitution service system.
The Range of Exponents of Special Two-Colored Digraph with One Non-Common Arc
Authors: Luo Meijin , Li Xiaodong , Li Xi
Published: July 2020

So far, many problems of the primitive exponent of traditional single nonnegative matrix have been resolved. Currently, pushing traditional single nonnegative matrix to matrix pairs which have relatively application in many areas such as information science, communication networks, computer science, is a new trend. According to correspondence relation, two-colored digraphs can be used to solve matrix problems. We consider the uncolored digraph of two-colored digraph has vertices and none non-common arc. The range of exponents and extremal two-colored digraphs are given.
Analysis of Nantong Public Culture Supply Mode Innovation Based on "Internet +" Platform
Authors: Shen Xiaohu , Deng Yangyang
Published: July 2020

Currently, public cultural services are mainly provided by the government, there is a contradiction between supply and demand. Use the "Internet +" innovation-driven thinking to establish a demand-centric innovation mechanism for public cultural supply, rely on big data, cloud computing, information technology, cloud sharing and mobile Internet to build a public cultural Internet service platform, forming "Internet + "Public cultural services" resource information sharing model, innovate the supply of public culture, enrich the content of public cultural services, encourage social forces to participate in cultural construction, at the same time focus on the integration of science and technology, effectively meet the public cultural needs, solve the contradiction between supply and demand in public cultural services.
Practice of Gesture Recognition Based on Resnet50
Authors: Li Zhiming
Published: July 2020

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This paper mainly describes and analyzes the common network models of deep learning. By comparing the existing network structure in the industry, this paper focuses on the static gesture recognition algorithm based on the residual network resnet50. In this paper, we choose the depth residual network resnet50 to realize the gesture control of web browser, and apply the gesture recognition method proposed in this paper.
Design and Implementation of Agricultural Internet of Things System Based on Aliyun IoT Platform and STM32
Authors: Zhou Tianli , Zhang Jian
Published: July 2020

Based on the research of Internet of things, agricultural intelligent management system was proposed based on Aliyun IoT platform and STM32.Through the ZigBee wireless sensor technology to complete the data transmission function of each sensor by ESP8266 and the MQTT protocol complete STM32 access connection function of Aliyun IoT platform, through the cloud database RDS complete data storage function, and implements the Web visual development and system supporting Android APP development. A set of agricultural automation intelligent management system, which is portable, small and suitable for farmers’ consumption demand, has been developed.
Evaluation of Regional Logistics Competitiveness of Wuhan’s “1+8” Urban Circle Based on SPSS
Authors: Zhou Rong , Chen Rui
Published: July 2020

In this paper, 8 cities in the "1+8" urban circle of Wuhan were taken as research objects to construct the evaluation system of regional logistics competitiveness. Based on relevant data in 2017, the competitiveness of regional logistics in 8 cities was compared by factor analysis. Based on cluster analysis, the development level of regional logistics in the 8 cities was revealed. Finally, we put forward several suggestions to improve regional logistics competitiveness for the 8 different cities.
Equipment Storage and Supply Mode Based on Information Integration
Authors: Sun Wanguo , Liu Zongqiang , Jia Qi
Published: July 2020

This paper first analyzes the army equipment storage-supply mode and the deficiency of the existing problems to be solved, and then at the army information integration based on the existing study, further study of the guarantee of equipment and supplies, for equipment guarantee model for scientific and reasonable planning, this paper proposes a new equipment storage-supply model, mainly divided into reserve mode and supply mode, for the equipment security reform provides a new way of thinking.
E-Learning and Online Instructions of Higher Education during the 2019 Novel Coronavirus Diseases (COVID-19) Epidemic
Authors: Chang Chiu-Lan , Fang Ming
Published: July 2020

E-learning and online instructions of higher education play a key role in no suspension of learning and no suspension of teaching during the 2019 Novel Coronavirus Diseases (COVID-19) Epidemic. This study summarizes the responses from online instructors and analyzes the difficulties and solutions of the online learning and instructions. The results indicate that although most instructors try to prepare the contents of instructions well, however, it is still not an easy way to monitor and change the students’ learning behaviors in such a short term. We outline implications for practice and ideas for future research. The results could be used to serve as a benchmark for comparing levels of online learning and identify the main difficulties of online instructors during the outbreak circumstances of the COVID-19.
Construction of 3D Virtual Reality Insect Model Based on Ips typographus L
Authors: Wang XuanYao , Xiao Wei , Wang Zhiming , Shi Liwen
Published: July 2020

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

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

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

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

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

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

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

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

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

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

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

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

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

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

One 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

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

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%.
Remotes sensing capabilities on land subsidence and coastal water hazard and disaster studies
Authors: Andreas Heri , Abidin Hasanuddin Z. , Sarsito Dina A. , Pradipta Dhota
Published: July 2020

Lowering on land surface which is commonly known as land subsidence is quite an issue in Indonesia today especially for coastal low elevation young sediment area, including cities or urban area lies on top of it. Jakarta is one of the city with most famous for land subsidence at the moment. If we go along northern coast of Java, many cities are experiencing the same situation as Jakarta and even more. As the impact from land subsidence, those coastal areas may experience water disaster such as sea water inundation and intrusion, wider expansion of flood and aquifer damage. Investigation of such areas in large and even regional scale with limited research budget is a problem. Nevertheless we found way for at least reducing the problem by using the capabilities of remote sensing product, geological and geostatistic data. We can identify land subsidence, coastal effected by subsidence like mentioned above by only time series of satellite image archive such as Google earth or Landsat free distributed, geological map and published geostatistic data like water consumption and population growth, with sample validated by land subsidence measurement and groundwater monitoring points. This paper will highlight our finding.
Deforestation detection using multitemporal satellite images
Authors: Candra Danang Surya
Published: July 2020

Indonesia a megadiverse country which has the largest area of forest with the richest biodiversity in the world. Unfortunately, the forest-loss in this country is quite big, especially in Kalimantan and Sumatera. Therefore, a robust method for deforestation method has to be developed to monitor deforestation to minimize the forest-loss in this country. In this paper, we proposed a method for deforestation detection called Multitemporal Deforestation Detection (MDD). The basic idea of this method is to utilize the difference of reflectance values on the target image and original image. Band selection was used to select bands in developing the algorithm. To improve the accuracy of the results, NDVI and dNBR were combined to the algorithm. As a result, the MDD can detect deforestation from forest to heterogeneous land cover such as open land, land clearing for plantation, urban, road and small road, and burnt area accurately. The advantage of the MDD is that it does not interfere cloud and cloud shadow on the original image. As it is an automatic algorithm, it can support in detecting deforestation for a big dataset.
A preliminary study on machine learning and google earth engine for mangrove mapping
Authors: Kamal Muhammad , Farda Nur Mohammad , Jamaluddin Ilham , Parela Artha , Wikantika Ketut , Prasetyo Lilik Budi , Irawan Bambang
Published: July 2020

The alarming rate of global mangrove forest degradation corroborates the need for providing fast, up-to-date and accurate mangrove maps. Conventional scene by scene image classification approach is inefficient and time consuming. The development of Google Earth Engine (GEE) provides a cloud platform to access and seamlessly process large amount of freely available satellite imagery. The GEE also provides a set of the state-of-the-art classifiers for pixel-based classification that can be used for mangrove mapping. This study is an initial effort which is aimed to combine machine learning and GEE for mapping mangrove extent. We used two Landsat 8 scenes over Agats and Timika Papua area as pilot images for this study; path 102 row 64 (2014/10/19) and path 103 row 63 (2013/05/16). The first image was used to develop local training areas for the machine learning classification, while the second one was used as a test image for GEE on the cloud. A total of 838 points samples were collected representing mangroves (244), non-mangroves (161), water bodies (311), and cloud (122) class. These training areas were used by support vector machine classifier in GEE to classify the first image. The classification result show mangrove objects could be efficiently delineated by this algorithm as confirmed by visual checking. This algorithm was then applied to the second image in GEE to check the consistency of the result. A simultaneous view of both classified images shows a corresponding pattern of mangrove forest, which mean the mangrove object has been consistently delineated by the algorithm.
Post-liquefaction reconsolidation of coastal area in Talise Beach, Palu, Indonesia
Authors: Tampubolon Togi , Yanti Jeddah
Published: July 2020

Periodic generated, sequence of earthquakes with magnitude 7.5 at a depth of 10 km occurred in Palu Koro fault, Central Sulawesi, and was trigger tsunamis wave in Talise beach reach coastline in few minutes. It causes entire coastline become extremely attacked and moves gravitationally of the ground at a slope as well, known as flow of liquefaction. Reconsolidation of coastline structure in post-liquefaction event in Palu’s Talise beach had been heaving due to devastating aftermath of the earthquake and tsunami that hit Sulawesi. Lack and rough terrain are intensively associated with the difficult to assess post-area, so remote sensing can be efficiently and quickly to identify potential post-area occurrence. Satellite multispectral such as Sentinel, and SRTM DEM applied with a new approach to corporate post-event liquefaction in Talise beach, Central Sulawesi, Indonesia. In this result, we depict the 3D surface topography of pre and post event to analyse the liquefaction impact. We found the differentiation approach of pre and post event imply the liquefaction in variation of dimensional ratio. Therefore, our hypothesis may be useful to the preliminary research for mitigation and revitalization in post-area.
The effects of DEM specification on watershed model in Mataram City, West Nusa Tenggara Province
Authors: Susetyo Danang Budi , Purwono Nugroho , Rahadiati Ati
Published: July 2020

One of data resources for hydrologic modelling is Digital Elevation Model (DEM). In hydrologic modelling, watershed delineation is an important step to create boundary of inundation area, so that DEM plays a significant role in watershed model. Nowadays, there are many sources of DEM data available in Indonesia that was provided by Geospatial Information Agency (BIG), including LiDAR and DEMNAS (National DEM). Based on its resolution, DEMNAS is classified as data for medium scale mapping, while LiDAR is used for large scale mapping. For hydrological modelling, medium scale data has been widely applied, while the large-scale hydrological modelling is still limited. The availability of large-scale data is quite large, including the City of Mataram, is a good source to examine its effect for hydrological modelling, so this research is conducted to see the effects of DEM sources, namely LiDAR and DEMNAS, for watershed model generation. Analysis is conducted by comparison to existing official watershed in that area. From seven watersheds, LiDAR produce better geometry in four areas, while DEMNAS is better in the rest. This research is expected to support a policy relating hydrological modelling at large scale.
Correlation analysis of satellite-based mangrove index and mangrove forest health at Segara Anakan Cilacap, Central Java, Indonesia
Authors: Winarso Gathot , Kamal Muhammad , Rosid Syamsu , Asriningrum Wikanti , Supriyatna Jatna
Published: July 2020

This study aims to introduce satellite-based Mangrove Index to substitute mangrove health indicator based on Normalized Difference Vegetation Index (NDVI) when it was failed to represent mangrove health at Segara Anakan mangrove area, Cilacap, Central Java, Indonesia. The Mangrove Index has potential to be implemented as indicator of mangrove health because it is deduced from two main characteristics of mangrove forest, which are vegetation condition and hydro-period parameters. Previous mangrove health identification was mainly conducted using visual analysis during the field check and used previous reports that could not be statistically analyzed. The correlation between Mangrove Index and mangrove health condition was analyzed to measure the degree and form of relationship between them as a basis for mangrove health modelling. We conducted paper review to synthesize the mangrove health condition and enriched our analysis by incorporating as many field data as possible related to canopy cover, stand density, seedling density, stake density, biodiversity index, soil moisture, pH, soil temperature, air temperature and air humidity. Our finding shows that the degree of correlation for each parameter were low. The maximum coefficient of determination (R2
) of 0.5 was found for combination between stand and sapling density divided by soil moisture. The combination these parameters was selected because Mangrove Index was produced from image bands that has high spectral reflectance response to vegetation (NIR) and soil moisture (SWIR). This result is not a final because limited parameters were incorporated in the analysis. Further deeper analysis to simulate all field parameters need to be done in the future.
Identifying geothermal steam spots based on binary logistic method to a high resolution imagery and field measurement
Authors: Gandes F. Z. , Saepuloh A. , Wikantika K.
Published: July 2020

The increasing population of a country has an impact on the number of energy needs that must be provided. Therefore, alternative sources of energy need to be developed to meet those needs. Indonesia is known as The Ring of Fire has very high geothermal resource potential. A study of geothermal mapping technology needs to be done to optimize the utilization of this energy. This study aims to recognize the relation between temperature and surface roughness on an up-flow zone of geothermal system and identify the steam spots at surface. We used a high resolution ALOS-2 PALSAR-2 images to obtain surface roughness and ASTER images to obtain a corrected Land Surface Temperature (LST). The study was conducted in an open area Papandayan Crater, Garut, West Java (Indonesia). Data pre-processing including atmospheric and geometric corrections were applied following an image processing to obtain the surface roughness and the corrected LST by estimating non-unique surface emissivity, pixel fitting between measured surface temperature and roughness at field, and identifying the steam spots of the geothermal system using binary logistic regression method. Equally good models of co-polarization and cross-polarization obtained because of the high correlation between co-polarization and cross-polarization surface roughness. There was a positive relationship between land surface temperature and surface roughness in the manifestation area of geothermal resources and surface roughness known more dominant in determining the manifestations of geothermal resources than surface temperature.
Spatial modelling of anthropogenic based peat land fire case study of the Kepulauan Meranti District
Authors: Turmudi  , Sutrisno Dewayany , Nahib Irmadi , Suryanta Jaka , Kardono Priyadi , Suwarno Yatin , Rahadiati Ati , Dewi Ratna Sari
Published: July 2020

Forest fires in Indonesia are 99% due to human intentional factors. The practice of burning forests is done because it is easy, fast, and inexpensive, and the assumption that the ashes produced will fertilize the soil. The practice of burning forests is done primarily for the purpose of clearing agricultural land and plantations. Land and forest fires will be even worse if they occur on peat lands. Fires on peat lands consist of crown fire, surface fire, and ground fire which have a more severe impact on environmental, social and economic impacts. In terms of management, it is also more difficult and longer than fires on mineral land. On the other hand, pea tlands in Indonesia, 30%, are peat lands that have the potential for agricultural and plantation cultivation. The main objective of this paper is to use spatial modeling to provide an early warning system for forest fires on peat lands based on anthropogenic aspects in the Meranti Islands Regency, Riau Province. Data compiled based on anthropogenic aspects include: accessibility, population distribution, land clearing patterns, land use, and land status. Spatial analysis was carried out on anthropogenic aspects and the distribution of hotspots that had a level of confident (c> 80%). The results of the paper indicate that anthropogenic aspects that are dominant in the occurrence of forest fires are accessibility of road than river.
The effect of building density on land surface temperature, (Case Study: Turikale District, Maros Regency)
Authors: Asyraf Muhammad Syahrul , Damayanti Astrid , Dimyati Muhammad
Published: July 2020

The amount of land built has increased over the years as the population increases. This results in a higher building density, such as in Turikale District, Maros Regency. Each object on the earth’s surface has its distinctive temperature, such as the buildings. The heat of the earth’s surface on certain location points will be captured by the image as an area that has a different surface temperature. The purpose of this study is to determine the temporal-spatial pattern of building density and surface temperature in Turikale Subdistrict, Maros Regency in 2013 and 2018 and is expected to be useful for Turikale District spatial planning and urban environment. Building density data and surface temperature are obtained from Landsat 8 Path 114 row 063 in 2018 and 2013. The data is processed using the Normalized Difference Built-up Index (NDBI) algorithm and Land Surface Temperature (LST) using ArcGIS. Furthermore, an analysis of differences in building density patterns with land surface temperature is analyzed spatially and temporally. The results of the study show that the spatial pattern of building density grows to be higher in density each year, especially in densely populated residential areas and near Jalan Daya-Maros, Turikale District. Temporal patterns of land surface temperatures show significant increases between 2013 and 2018.
Determining location of tsunami disaster temporary evacuation shelter (TES) utilizes network analysis in City of Makassar, South Sulawesi Province
Authors: Ismiati Feni , Damayanti Astrid , Dimyati Muhammad
Published: July 2020

The city of Makassar is a vulnerable area of the tsunami because it is located on the southwest coast of Sulawesi Island. The population is the highest number on Sulawesi Island. People will cause a lot of losses in the event of a tsunami in Makassar City. Therefore, preventive measures are needed as disaster mitigation. One of them is to determine the location of the Temporary Evacuation Place (TES) in the tsunami-affected area. The purpose of this study is to determine the location of TES on the coast of Makassar City. The variables used are DEM, land use, and travel time. TES locations are determined using GIS, the network analysis method with the tool service area. The analysis used was to sort outbuildings in tsunami-affected regions based on the size and height of buildings according to the standards of the Federation Emergency Management Agency (FEMA). Based on the results of the research, there are 14 TES that are distributed in Makassar City. TES is in densely populated residential areas affected by the tsunami with an average height of 0-5 m above sea level. The TES in Makassar City is in the form of mosques, auditoriums, schools, and factories.
Bathymetry extraction of empirical models using SPOT 7 satellite imagery
Authors: Setiawan Kuncoro Teguh , Ginting Devica Natalia BR. , Manessa Masita D.M. , Surahman  , Winarso Gathot , Anggraini Nanin , Basith Abdul , Asriningrum Wikanti , Rosid Syamsu , Supardjo A. Harsono
Published: July 2020

Bathymetry is information on the depth of the sea that can describe the hydrographic conditions of the seabed. Satellite derived bathymetry has several methods that can be applied to the batimetric extraction process using optical satellite images. One of the satellite images that can be used is SPOT 7. The image is the latest generation of SPOT which has 4 multispectral channels with a spatial resolution of 6 meters so that it can be extracted to obtain information on shallow water bathymetry. The bathymetry extraction method uses the Van Hengel and Spitzer methods, 1991. The VS method is the principal component analysis method of three bands with respect to the rotation transformation factor. The purpose of this study is to extract SPOT 7 satellite image data to produce relative bathymetry information in shallow seas using the VS algorithm. The location of the study was carried out on Karimunjawa Island, Jepara Regency, Central Java. The data used is SPOT 7 imagery that was acquired May 18, 2017. The extraction algorithm is used the VS 1991 method. The results show that from SPOT 7 images produce depth index values ranging from 0.0985 to 0.6378.