Prediction on Habitat Distribution in Mt. Inwang and Mt. An Using Maxent

Seo, Saebyul; Lee, Minjee; Kim, Jaejoo; Chun, Seung-Hoon; Lee, Sang−Don

doi:10.14249/eia.2016.25.6.432

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…Owing to its reliability demonstrated in several previous studies, we used the Maxent 3.4.4 model (Maxent) to predict the species distribution using the species appearance data of the target species. (26)(27)(28)(29) This model is a nonlinear and statistical distribution model that predicts the distribution of living creatures from the appearance data and environmental factors. This machine learning model can be helpful when data such as species appearance and nonappearance are minimal or when ordinary statistical inference methods cannot be used to derive a probability distribution.…”

Section: Species Distribution Modelmentioning

confidence: 99%

Analyzing the Efficiency of Increasing Suitable Habitat Area for Paridae by Roof Greening Method Based on Building Type: Case Study of Suwon City, Republic of Korea

Baek¹,

Kim²

2022

Sensors and Materials

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Owing to the proliferation of people in cities worldwide, the size of urban green areas has decreased along with biodiversity. Suwon City, a highly populated area adjacent to Seoul, the capital of the Republic of Korea, and the subject of this study, has been making significant efforts to prevent such a decrease in biodiversity. In this study, we aim to develop a suitable scenario for roof greening in Suwon City, analyze how the efficiency of increasing the suitable habitat area of the Paridae bird changes with the scenario, and propose the most efficient roof greening plan. For the development and application of this plan, public, commercial, and residential buildings were selected as target spaces to which roof greening was applied. Then, the appropriate roof greening area was determined (400000 m 2 , which is 0.712% of the area of Suwon) with reference to the Roof Greening Promotion Plan of Seoul. Subsequently, roof greening types were classified into low, medium, and high management based on the cases of roof greening. We found that the increase in the habitat area of Paridae depended on the types of roof greening and construction building. The buildings with the highest efficiency of increasing the habitat area in Suwon City (an increase of 1197.5%) were all commercial buildings except for those with low management, while the buildings with the lowest efficiency (115%) were public buildings. The information on the increases in the habitat area of Paridae and the cost of roof greening per area (m 2 ) for the three types of building can be used to establish suitable green roofs that will promote urban biodiversity.

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Section: Species Distribution Modelmentioning

confidence: 99%

Analyzing the Efficiency of Increasing Suitable Habitat Area for Paridae by Roof Greening Method Based on Building Type: Case Study of Suwon City, Republic of Korea

Baek¹,

Kim²

2022

Sensors and Materials

View full text Add to dashboard Cite

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Analysis of Changes in Suitable Habitat Areas of Paridae through Rooftop Greening Simulation—Case Study of Suwon-si, Gyeonggi-do, Republic of Korea

2021

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As many people live in cities that lack green space, biodiversity in such areas is decreasing. Suwon, the study site, a city that strives to improve its biodiversity, is close to the capital city of the Republic of Korea (ROK), and has a large population. This study aims to identify habitat-suitable areas using the longitudinal distribution model in Suwon-si, examine habitat changes when rooftop greening scenarios are applied to various use areas, and distinguish efficient use areas to expand the number of forms. To establish a rooftop greening creation scenario, the area was calculated based on the rooftop greening promotion plan in the metropolitan area, and a representative use area where rooftop greening can be applied was selected. To generate a scenario for creating rooftop greening, the property of the green area was assigned to the corresponding use area, and it was produced as an environmental variable, while the species distribution model was driven. As a result of the study, the area of increase in habitat area according to the rooftop greening for each usage area was derived, and the efficiency of the increase in habitat area compared to the rooftop greening area for each usage area was derived. To improve biodiversity in Suwon-si, rooftop greening in residential areas was found to be the most efficient, and rooftop greening efficiency in commercial areas was the lowest. It is expected that information on the increase and efficiency of the habitat of the wild birds due to rooftop greening by area of use derived from this study will help establish a rooftop greening plan and support decision-making to promote biodiversity in the city.

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Prediction on Habitat Distribution in Mt. Inwang and Mt. An Using Maxent

Cited by 2 publications

References 10 publications

Analyzing the Efficiency of Increasing Suitable Habitat Area for Paridae by Roof Greening Method Based on Building Type: Case Study of Suwon City, Republic of Korea

Analyzing the Efficiency of Increasing Suitable Habitat Area for Paridae by Roof Greening Method Based on Building Type: Case Study of Suwon City, Republic of Korea

Analysis of Changes in Suitable Habitat Areas of Paridae through Rooftop Greening Simulation—Case Study of Suwon-si, Gyeonggi-do, Republic of Korea

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