Pribadi, Didit Okta and Xu, Chao (2017) Optimizing Ecosystem Services of Urban Green Spaces Based on Integer Programming Approach. In: Proceedings of 2017 International Conference on Smart Cities, Automation & Intelligent Computing Systems (ICON-SONICS 2017), 08 November 207, Yogyakarta.
Full text not available from this repository.Abstract
As most of people will live in the cities in the coming decades, the needs for a better living environment in the urban areas have become of concern. Initiatives and movements have been emerged to promote ecosystem services as part of public goods that should be provided by urban governance. This idea leads to the green infrastructure concept as a way to gain benefits from nature. Therefore, planning the urban green spaces as a key element of green infrastructures becomes crucial. However, unlike the other types of infrastructures (i.e. roads, shops, hospitals, schools, bus station, etc.) that have obvious capacity and coverage area of services, urban green spaces relate to land use allocation where their size, shapes, compactness, contiguity, and distribution determine their capacity to deliver services. Therefore, there is a need to define spatial planning of urban green spaces which is able to maximize the provision of ecosystem services throughout the urban landscapes. This study aims to develop an optimization model that can be used to define the spatial shape of urban green spaces to maximize their potential of delivering different types of ecosystem services. The results show different optimization models that can be used to design urban green spaces which are capable of maximizing their coverage area of services.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Keywords: | ecosystem services; green infrastructures; urban green spaces; optimization model; integer programming |
| Subjects: | 600 Technology (Applied Sciences) > 620 Engineering > 628 Environmental Protection Engineering |
| Divisions: | Universitas Multimedia Nusantara |
| Depositing User: | Administrator UMN Library |
| Date Deposited: | 01 Mar 2018 04:19 |
| Last Modified: | 11 Jan 2023 06:28 |
| URI: | https://kc.umn.ac.id/id/eprint/2784 |
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