• Title/Summary/Keyword: Habitat Prediction

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A Prediction Model and Mapping for Forest-Dwelling Birds Habitat Using GIS (GIS를 이용한 산림성 조류의 서식지 예측 모형 및 지도구축)

  • Lee, Seul-Gi;Jung, Sung-Gwan;Park, Kyung-Hun;Kim, Kyung-Tae;Lee, Woo-Sung
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.1
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    • pp.62-73
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    • 2010
  • A bird is needed efficient conservation through habitat management, as the representative of an organism to evaluate the steady of complex ecosystem. So, this study will offer the useful basic data for preserving habitat from now on, as presenting a estimating model with the GIS program which selected factors effecting the habitat of a forest-dwelling bird in Changwon. As the resort of the survey, the number of forest-dwelling birds living in the 135 survey sites were 5 order, 15 family, 26 species and 922 individual. Also, as the result of making habitat analysis into a predict model, 'NDVI', 'Distance to valley', 'Distance to mixed forest' and 'Area of field' were significant and they had R-squares of 51.3%. Next, as the resort of researching the accuracy of Model, it was a reasonable prediction, as the correlation coefficient is 0.735 and MAPE is 20.7%, and a predict map of habitat was made with the model. This map could predict species diversity of no investigated areas and could be an useful basic data for preserving habitat, as an on-the-spot survey.

Effects of Habitat Environment and Land Use on the Abundance of Japanese Tree Frog (Hyla japonica) in Incheon, Korea (인천에서 서식지 환경과 토지 이용이 청개구리 (Hyla japonica) 수도에 미치는 영향)

  • Park, So Hyun;Cho, Hyunsuk;Jin, Seung-Nam;Cho, Kang-Hyun
    • Ecology and Resilient Infrastructure
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    • v.4 no.4
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    • pp.200-206
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    • 2017
  • The damage and fragmentation of habitat due to urbanization pose a great threat to amphibians worldwide. To understand the effect of urbanization on the distribution and abundance of Hyla japonica, we measured their population sizes by listening frog calling and investigated the habitat their population sizes and land use in the 18 rice paddy fields located in Incheon and its surroundings. Abundance of H. japonica was 0 - 17 male adults / habitat or 0 - 41 male adults / ha in Incheon. The number of the frog was increased as the distance between the habitat and the road became longer or the ratio of circumstance / area of the habitat increased. Unlike the general prediction, the density of H. japonica showed a negative correlation with the size of the habitat and a positive correlation with the surrounding land use intensity. Our results suggested that H. japonica could be concentrated in a narrow habitat due to the habitat size decrease and the periphery development according to the urbanizaion.

Mapping the Potential Distribution of Raccoon Dog Habitats: Spatial Statistics and Optimized Deep Learning Approaches

  • Liadira Kusuma Widya;Fatemah Rezaie;Saro Lee
    • Proceedings of the National Institute of Ecology of the Republic of Korea
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    • v.4 no.4
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    • pp.159-176
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    • 2023
  • The conservation of the raccoon dog (Nyctereutes procyonoides) in South Korea requires the protection and preservation of natural habitats while additionally ensuring coexistence with human activities. Applying habitat map modeling techniques provides information regarding the distributional patterns of raccoon dogs and assists in the development of future conservation strategies. The purpose of this study is to generate potential habitat distribution maps for the raccoon dog in South Korea using geospatial technology-based models. These models include the frequency ratio (FR) as a bivariate statistical approach, the group method of data handling (GMDH) as a machine learning algorithm, and convolutional neural network (CNN) and long short-term memory (LSTM) as deep learning algorithms. Moreover, the imperialist competitive algorithm (ICA) is used to fine-tune the hyperparameters of the machine learning and deep learning models. Moreover, there are 14 habitat characteristics used for developing the models: elevation, slope, valley depth, topographic wetness index, terrain roughness index, slope height, surface area, slope length and steepness factor (LS factor), normalized difference vegetation index, normalized difference water index, distance to drainage, distance to roads, drainage density, and morphometric features. The accuracy of prediction is evaluated using the area under the receiver operating characteristic curve. The results indicate comparable performances of all models. However, the CNN demonstrates superior capacity for prediction, achieving accuracies of 76.3% and 75.7% for the training and validation processes, respectively. The maps of potential habitat distribution are generated for five different levels of potentiality: very low, low, moderate, high, and very high.

A Comparative Study on HSI and MaxEnt Habitat Prediction Models: About Prionailurus bengalensis (HSI와 MaxEnt를 통한 삵의 서식지 예측 모델 비교 연구)

  • Yoo, Da-Young;Lim, Tai-Yang;Kim, Whee-Moon;Song, Won-Kyong
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.24 no.5
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    • pp.1-14
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    • 2021
  • Excessive development and urbanization have destroyed animal, plant, habitats and reduced biodiversity. In order to preserve species diversity, habitat prediction studies are have been conducted at home and overseas using various modeling techniques. This study was conducted to suggest optimal habitat modeling research by comparing HSI and MaxEnt, which are widely used among habitat modeling techniques. The study was targeted on the endangered species of Prionailurus bengalensis in nearby areas (5460.35km2) including Cheonan City, and the same data were used for analysis to compare those models. According to the HSI analysis, Prionailurus bengalensis's habitat probability was 74.65% for less than 0.5 and 25.34% for more than 0.5 and the top 30% were forest (99.07%). MaxEnt's analysis showed that 56.22% of those below 0.5 and 43.79% of those above 0.5 were found to have a high explanatory power of 78.3% of AUC. The Paired Wilcoxn test, which evaluated the significance of thoes models, confirmed that the mean difference between the two models was statistically significant (p<0.05). Analysis of the differences in the results of those models using the matrix table shows that score 24.43% HSI and MaxEnt was accordance,12.44% of the 0.0 to 0.2 section, 7.22% of the 0.2 to 0.4 section, 2.73% of the 0.4 to 0.6 section, 1.96% of the 0.6 to 0.8, and 0.08% of the 0.9 to 1.0. To verify where the score difference appears, the result values of those models were reset to values from 1 to 5 and overlaid. Overlapping analysis resulted in 30.26% of the Strongly agree values, 56.77% of the agree values, and 11.92% of the Disagree values. The places where the difference in scores occurs were analyzed in the order of forest (45.23%), agricultural land (34.57%), and urbanization area (7.65%). This confirmed that the analysis of the same target species within the same target site also has differences in forecasts depending on the modelling method. Therefore, a novel analysis method combining the advantages of each modeling in habitat prediction studies should be developed, and future study may be used to select Prionailurus bengalensis and species-protected areas and species protection areas in the future. Further research is judged to require higher accuracy studies through the use of various modeling techniques and on-site verification.

Habitat Analysis Study of Honeybees(Apis mellifera) in Urban Area Using Species Distribution Modeling - Focused on Cheonan - (종분포모형을 이용한 도시 내 양봉꿀벌 서식환경 분석 연구 - 천안시를 중심으로 -)

  • Kim, Whee-Moon;Song, Won-Kyong;Kim, Seoung-Yeal;Hyung, Eun-Jeong;Lee, Seung-Hyun
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.20 no.3
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    • pp.55-64
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    • 2017
  • The problem of the population number of honeybees that is decreasing not only domestically but also globally, has a great influence on human beings and the entire ecosystem. The habitat of honeybees is recognized to be superior in urban environment rather than rural environment, and predicting for habitat assessment and conservation is necessary. Based on this, we targeted Cheonan City and neighboring administrative areas where the distribution of agricultural areas, urban areas, and forest areas is displayed equally. In order to predict the habitat preferred by honeybees, we apply the Maxent model what based on the presence information of the species. We also selected 10 environmental variables expected to influence honeybees habitat environment through literature survey. As a result of constructing the species distribution model using the Maxent model, 71.7% of the training data were shown on the AUC(Area Under Cover) basis, and it was be confirmed with an area of 20.73% in the whole target area, based on the 50% probability of presence of honeybees. It was confirmed that the contribution of the variable has influence on land covering, distance from the forest, altitude, aspect. Based on this, the possibility of honeybee's habitat characteristics were confirmed to be higher in wetland environment, in agricultural land, close to forest and lower elevation, southeast and west. The prediction of these habitat environments has significance as a lead research that presents the habitat of honeybees with high conservation value of ecosystems in terms of urban space, and it will be useful for future urban park planning and conservation area selection.

Application of Statistical and Machine Learning Techniques for Habitat Potential Mapping of Siberian Roe Deer in South Korea

  • Lee, Saro;Rezaie, Fatemeh
    • Proceedings of the National Institute of Ecology of the Republic of Korea
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    • v.2 no.1
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    • pp.1-14
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    • 2021
  • The study has been carried out with an objective to prepare Siberian roe deer habitat potential maps in South Korea based on three geographic information system-based models including frequency ratio (FR) as a bivariate statistical approach as well as convolutional neural network (CNN) and long short-term memory (LSTM) as machine learning algorithms. According to field observations, 741 locations were reported as roe deer's habitat preferences. The dataset were divided with a proportion of 70:30 for constructing models and validation purposes. Through FR model, a total of 10 influential factors were opted for the modelling process, namely altitude, valley depth, slope height, topographic position index (TPI), topographic wetness index (TWI), normalized difference water index, drainage density, road density, radar intensity, and morphological feature. The results of variable importance analysis determined that TPI, TWI, altitude and valley depth have higher impact on predicting. Furthermore, the area under the receiver operating characteristic (ROC) curve was applied to assess the prediction accuracies of three models. The results showed that all the models almost have similar performances, but LSTM model had relatively higher prediction ability in comparison to FR and CNN models with the accuracy of 76% and 73% during the training and validation process. The obtained map of LSTM model was categorized into five classes of potentiality including very low, low, moderate, high and very high with proportions of 19.70%, 19.81%, 19.31%, 19.86%, and 21.31%, respectively. The resultant potential maps may be valuable to monitor and preserve the Siberian roe deer habitats.

Distribution of Subgenus Lycoctonum in Korea: Analysis and Verification by GIS (한국산 진범 종집단의 서식상황: GIS를 이용한 분석과 검증)

  • Lee, Soo-Rang;Jeong, Jong-Chul;Park, Chong-Wook
    • Spatial Information Research
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    • v.15 no.2
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    • pp.135-146
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    • 2007
  • The purpose of this study was to ascertain and analyze environmental factors of subgenus Lycoctonum in Korea for conservation and management of rare high land plant species by GIS. We derived the habitat model of Lycoctonum from GPS coordination, habitat factors and digital topology maps. Suitable altitude fur the subgenus Lycoctonum is from 470m to 1320m, and northern slopes(between 15.5 and 36 degrees) are ideal for the Lycoctonum populations. In addition to altitude, slope and aspect, deciduous forest and approximation to water source were found as important factor. Using GIS and the Lycoctonum habitat model, we overlaid elevation, aspect, slope and land cover layers and analyzed buffer from the water source on two topology maps, Yang-Soo and Mock-Dong. After making prediction map for Lycoctonum habitat, we verified the existence of Lycoctonum populations on the predicted sites through field survey. Through this research, we're convinced that GIS software is powerful tool for plants conservation, such as finding unknown habitat or selecting alternative habitat.

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Development of a habitat suitability index for the habitat restoration of Pedicularis hallaisanensis Hurusawa

  • Rae-Ha, Jang;Sunryoung, Kim;Jin-Woo, Jung;Jae-Hwa, Tho;Seokwan, Cheong;Young-Jun, Yoon
    • Journal of Ecology and Environment
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    • v.46 no.4
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    • pp.316-323
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    • 2022
  • Background: We developed a habitat suitability index (HSI) model for Pedicularis hallaisanensis, a Grade II Endangered Species in South Korea. To determine the habitat variables, we conducted a literature review on P. hallaisanensis with a specific focus on the associated spatial factors, climate, topography, threats, and soil factors to derive five environmental factors that influence P. hallaisanensis habitats. The specific variables were defined based on the collected data and consultations with experts in the field, with the validity of each variable tested through field studies. Results: Mt. Seorak had a suitable habitat area of 2.48 km2 for sites with a score of 1 (0.62% of total area) and 0.01 km2 for sites with a score of 0.9. Mt. Bangtae had a suitable habitat area of 0.03 km2 for sites with a score of 1 (0.02% of total area) and 0 km2 for sites with a score of 0.9. Mt. Gaya showed 0.13 km2 of suitable habitat for sites with a score of 1 (0.17% of total area) and 0 km2 for sites with a score of 0.9. Lastly, Mt. Halla showed 3.12 km2 of suitable habitat related to sites with a score of 1 (2.04% of total area) and 4.08 km2 of sites with a score of 0.9 (2.66% of total area). Mt. Halla accounts for 73.1% of the total core habitat area. Considering the climatic, soil, and forest conditions together with standardized collection sites, our results indicate that Mt. Halla should be viewed as a core habitat of P. hallaisanensis. Conclusions: The findings in this study provide useful data for the identification of core habitat areas and potential alternative habitats to prevent the extinction of the endangered species, P. hallaisanensis. Furthermore, the developed HSI model allows for the prediction of suitable habitats based on the ecological niche of a given species to identify its unique distribution and causal factors.

Structural and Layout Design Optimization of Ecosystem Control Structures (2) -Characteristics of Subsidence and Burial of Artificial Habitat due to Sediment Transport in Flow Field- (생태계 제어 시설물의 설계 및 배치 최적화(2) -흐름장에서의 인공어초의 침하 및 매몰 특성-)

  • RYU Cheong-RO;KIM Hyeon-Ju;LEE Han-Su;SHIN Dong-Il
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.30 no.1
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    • pp.139-147
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    • 1997
  • Sediment transport around artificial habitat which is induced by the change ol flow due to installation of the structure plays a role not only as a defect function of subsidence and burial but also bottom-environment control function. This study examined the characteristics of local scouring and deposition with sediment sizes, current velocities and installation direction of artificial habitat in flow field. Resultant subsidence and burial processes are investigated and discussed with Reynolds number. Together with sediment number and dimensionless time elapse, prediction formulas are established by combining these relationships. Bottom control function as cultivating effects is discussed with installation direction, and applicability of countermeasures is compared and stone pavement method is recommended.

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Distribution and Potential Suitable Habitats of an Endemic Plant, Sophora koreensis in Korea (MaxEnt 분석을 통한 한반도 특산식물 개느삼 서식 가능지역 분석)

  • An, Jong-Bin;Sung, Chan Yong;Moon, Ae-Ra;Kim, Sodam;Jung, Ji-Young;Son, Sungwon;Shin, Hyun-Tak;Park, Wan-Geun
    • Korean Journal of Environment and Ecology
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    • v.35 no.2
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    • pp.154-163
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    • 2021
  • This study was carried out to present the habitat distribution status and the habitat distribution prediction of Sophora koreensis, which is the Korean Endemic Plant included in the EN (Endangered) class of the IUCN Red List. The habit distribution survey of Sophora koreensis confirmed 19 habitats in Gangwon Province, including 13 habitats in Yanggu-gun, 3 habitats in Inje-gun, 2 habitats in Chuncheon-si, and 1 habitat in Hongcheon-gun. The northernmost habitat of Sophora koreensis in Korea was in Imdang-ri, Yanggu-gun; the easternmost habitat in Hangye-ri, Inje-gun; the westernmost habitat in Jinae-ri, Chuncheon-si; and the southernmost habitat in Sungdong-ri, Hongcheon-gun. The altitude of the Sophora koreensis habitats ranged from 169 to 711 m, with an average altitude of 375m. The area of the habitats was 8,000-734,000 m2, with an average area of 202,789 m2. Most habitats were the managed forests, such as thinning and pruning forests. The MaxEnt program analysis for the potential habitat of Sophora koreensis showed the AUC value of 0.9762. The predictive habitat distribution was Yanggu-gun, Inje-gun, Hwacheon-gun, and Chuncheon-si in Gangwon Province. The variables that influence the prediction of the habitat distribution were the annual precipitation, soil carbon content, and maximum monthly temperature. This study confirmed that habitats of Sophora koreensis were mostly found in the ridge area with rich light intensity. They can be used as basic data for the designation of protected areas of Sophora koreensis habitat.