• Journal of Environmental Impact Assessment
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• v.33 no.2
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• pp.53-63
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• 2024

Biodiversity holds significant importance within the framework of environmental impact assessment, being utilized in site selection for development, understanding the surrounding environment, and assessing the impact on species due to disturbances. The field of environmental impact assessment has seen substantial research exploring new technologies and models to evaluate and predict biodiversity more accurately. While current assessments rely on data from fieldwork and literature surveys to gauge species richness indices, limitations in spatial and temporal coverage underscore the need for high-resolution biodiversity assessments through species richness mapping. In this study, leveraging data from the 4th National Ecosystem Survey and environmental variables, we developed a species distribution model using Random Forest. This model yielded mapping results of 24 mammalian species' distribution, utilizing the species richness index to generate a 100-meter resolution map of species richness. The research findings exhibited a notably high predictive accuracy, with the species distribution model demonstrating an average AUC value of 0.82. In addition, the comparison with National Ecosystem Survey data reveals that the species richness distribution in the high-resolution species richness mapping results conforms to a normal distribution. Hence, it stands as highly reliable foundational data for environmental impact assessment. Such research and analytical outcomes could serve as pivotal new reference materials for future urban development projects, offering insights for biodiversity assessment and habitat preservation endeavors.

• Journal of Microbiology and Biotechnology
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• v.28 no.9
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• pp.1517-1526
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• 2018

Investigating bacterial diversity and its metabolic capabilities is crucial for interpreting the ecological patterns in a desert environment and assessing the presence of exploitable microbial resources. In this study, we evaluated the spatial heterogeneity of physicochemical parameters, soil bacterial diversity and metabolic adaptation at meter scale. Soil samples were collected from two quadrats of a desert (Thar Desert, India) with a hot, arid climate, very little rainfall and extreme temperatures. Analysis of physico-chemical parameters and subsequent variance analysis (p-values < 0.05) revealed that sulfate, potassium and magnesium ions were the most variable between the quadrats. Microbial diversity of the two quadrats was studied using Illumina bar-coded sequencing by targeting V3-V4 regions of 16S rDNA. As for the results, 702504 high-quality sequence reads, assigned to 173 operational taxonomic units (OTUs) at species level, were examined. The most abundant phyla in both quadrats were Actinobacteria (38.72%), Proteobacteria (32.94%), and Acidobacteria (9.24%). At genus level, Gaiella represented highest prevalence, followed by Streptomyces, Solirubrobacter, Aciditerrimonas, Geminicoccus, Geodermatophilus, Microvirga, and Rubrobacter. Between the quadrats, significant difference (p-values < 0.05) was found in the abundance of Aciditerrimonas, Geodermatophilus, Geminicoccus, Ilumatobacter, Marmoricola, Nakamurella, and Solirubrobacter. Metabolic functional mapping revealed diverse biological activities, and was significantly correlated with physicochemical parameters. The results revealed spatial variation of ions, microbial abundance and functional attributes in the studied quadrats, and patchy nature in local scale. Interestingly, abundance of the biotechnologically important phylum Actinobacteria, with large proposition of unclassified species in the desert, suggested that this arid environment is a promising site for bioprospection.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.381-387
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• 2009

This paper is presented simultaneous localization and mapping (SLAM) based on feature map and path-planning using modified genetic algorithm for efficient driving of autonomous vehicle. The biggest problem for autonomous vehicle from now is environment adaptation. There are two cases that its new location is recognized in the new environment and is identified under unknown or new location in the map related kid-napping problem. In this paper, SLAM based on feature map using ultrasonic sensor is proposed to solved the environment adaptation problem in autonomous driving. And a modified genetic algorithm employed to optimize path-planning. We designed and built an autonomous vehicle. The proposed algorithm is applied the autonomous vehicle to show the performance. Experimental result, we verified that fast optimized path-planning and efficient SLAM is possible.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.1
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• pp.47-58
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• 2013

According to the increasing use of information in the mobile web environment, web information techniques previously developed considering only a specific platform become unable to use. Such techniques need to be replaced by the web standard techniques guaranteeing interoperability and to develop a new graphic user interface required in the mobile web environment. Based on such backgrounds, this paper surveyed the standards for implementing web geographic information system(GIS) service considering mobile and desktop environments. Based on the survey results, a GIS system configured with open source is designed and web mapping clients based on ExtJs are implemented for mobile and desktop environments. For the purpose of coping with the new web standard environment, the methods and prototype system suggested and implemented in the paper can be used as a case study to implement a GIS in the use of mobile and desktop environments.

• Journal of Korean Society on Water Environment
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• v.31 no.3
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• pp.241-252
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• 2015

Runoff behaviors by five bias correction methods were analyzed, which were Change Factor methods using past observed and estimated data by the estimation scenario with average annual calibration factor (CF_Y) or with average monthly calibration factor (CF_M), Quantile Mapping methods using past observed and estimated data considering cumulative distribution function for entire estimated data period (QM_E) or for dry and rainy season (QM_P), and Integrated method of CF_M+QM_E(CQ). The peak flow by CF_M and QM_P were twice as large as the measured peak flow, it was concluded that QM_P method has large uncertainty in monthly runoff estimation since the maximum precipitation by QM_P provided much difference to the other methods. The CQ method provided the precipitation amount, distribution, and frequency of the smallest differences to the observed data, compared to the other four methods. And the CQ method provided the rainfall-runoff behavior corresponding to the carbon dioxide emission scenario of SRES A1B. Climate change scenario with bias correction still contained uncertainty in accurate climate data generation. Therefore it is required to consider the trend of observed precipitation and the characteristics of bias correction methods so that the generated precipitation can be used properly in water resource management plan establishment.

• Korean Journal of Remote Sensing
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• v.17 no.1
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• pp.99-109
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• 2001

In order to establish effective fishing ground environment equipment and artificial reef in coastal area, the methodology to select the most suitable area for artificial reef should be applied after analyzing the correlation between fishing ground environment and ocean environment. In this paper, thematic maps were prepared by using satellite remote sensing and GIS for the sea surface temperature, chlorophyll, transparency, the depth of sea water and the condition of submarine geologic which are considered as the most elements when selecting suitable area for artificial reef in Tong-Yong bay. Then, the most suitable area for artificial reef was selected by giving weight score depending on the suitable condition of this area and analyzing spatial data. The results showed it makes possible for this methodology, which selects the suitable area for artificial reef using satellite remote sensing and GIS, to manage the institution of artificial reef more entirely and efficiently through analyzing and visualizing.

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.08a
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• pp.75-87
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• 2005

Remote sensing(RS)- and geographic information system(GIS)-based information management to measure and assess agri-environment schemes, and to quantify and map environment indicators for nature and land use, climate change, air, water and energy balance, waste and material flow is in high demand because it is very helpful in assisting decision making activities of farmers, government, researchers, and consumers. The versatility and ability of RS and GIS containing huge soil database to assess agricultural environment spatially and temporally at various spatial scales were investigated. Spectral and microwave observations were carried out to characterize crop variables and soil properties. Multiple sources RS data from ground sensors, airborne sensors, and also satellite sensors were collected and analyzed to extract features and land cover/use for soils, crops, and vegetation for support precision agriculture, soil/land suitability, soil property estimation, crop growth estimation, runoff potential estimation, irrigated and the estimation of flooded areas in paddy rice fields. RS and GIS play essential roles in a management and monitoring information system. Biosphere-atmosphere interection should also be further studied to improve synergistic modeling for environment and sustainability in agri-environment schemes.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.353-359
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• 2004

Underground facility DB that is constructed by NGIS project need efficient management methodology, because falling-off in quality was worried by confused of existing management affair and management affair of computerization environment. Through analysis of existing management affair, underground facility DB and management system decide that modification/renewal factor of underground facility DB and subject affair Through modification/renewal factor of underground facility DB, developed underground facility DB management methodology using MMS. Result that apply developed management methodology to subject affair, existing affair environment improved to computerization environment and Could improve underground facilities DB authoritativeness.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.194-202
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• 2008

This paper describes a new method for indoor environment mapping and localization with stereo camera. For environmental modeling, we directly use the depth and color information in image pixels as visual features. Furthermore, only the depth and color information at horizontal centerline in image is used, where optical axis passes through. The usefulness of this method is that we can easily build a measure between modeling and sensing data only on the horizontal centerline. That is because vertical working volume between model and sensing data can be changed according to robot motion. Therefore, we can build a map about indoor environment as compact and efficient representation. Also, based on such nodes and sensing data, we suggest a method for estimating mobile robot positioning with random sampling stochastic algorithm. With basic real experiments, we show that the proposed method can be an effective visual navigation algorithm.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.96-103
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• 2014

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.