 |
English
|
正體中文
|
简体中文
|
Post-Print筆數 : 27 |
Items with full text/Total items : 118940/150005 (79%)
Visitors : 83322466
Online Users : 5266
|
|
|
Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/158017
|
| Title: | 監測1985年至2020年間臺灣都市化動態—以深度學習方法對土地利用效率動態及其對城市生態系統的影響的特別調查
Monitoring of Urbanisation Dynamics in Taiwan between 1985 and 2020 -- An Investigation with Special Emphasis on the Dynamics of Land-Use Efficiency and the Impact on Urban Ecosystems using a Deep Learning Approach |
| Authors: | 范噶色 |
| Contributors: | 地政系 |
| Keywords: | 衛星遙測資料;土地覆蓋變化;土地使用效率(LUE);聯合國永續發展指標第15項(SDG 11);聯合國永續發展指標第15項(SDG 15);都市化及都市擴張;都市生態系統;都市生態服務;時空數據模型
Satellite Remote Sensing Data;Land Cover Change;Land Use Efficiency (LUE);Land Consumption Rate (LCR) SDG 11;SDG 15;Urbanization and Urban Expansion;Urban Ecosystem Services;Spatio-Temporal Data Models;Satellite Image Time Series (SITS) |
| Date: | 2021-12 |
| Issue Date: | 2025-07-14 11:10:54 (UTC+8) |
| Abstract: | 了解都市化動態並調整規劃策略對於建立永續都市環境而言非常重要。聯合國頒布之永續發展目標第11項（SDG 11）希望建立更適宜居住的永續城市。過去近50年來，遙測載具上的監測器提供了大量資料，幫助我們了解當前環境，作為未來決策過程之基礎。本研究針對1985年至2020年間動態，目的是調查臺灣都市地區土地覆蓋（LC）變化的動態及其對都市生態系統的影響。多時序資料包括區域土地覆蓋變化統計資料以及SDG 11.3.1中的土地利用效率（LUE）指標，及多期段事件間的動態關係，以評估當地政策的影響，並更好地了解都市發展趨勢。這種方法補充了以往較少全域及長期統計。所建立之監測框架可應用於監測國內永續發展指標發展，並作為決策過程基礎，協助區域規劃和政策制定，實現永續都市發展目標。下一階段，將利用土地覆蓋變化來評估都市擴張對生態系統的影響，特別是對調節都市生態系統服務提供和綠色基礎設施網絡的影響，以實現在SDG 15.1（陸地生活）中制定的目標。這項評估可為都市和景觀規劃者提供評估生態系統服務供應的損失，及可能的保護及復育策略。本計畫利用多時序及多光譜的遙感觀測資料，基於新穎的捲積神經網絡（CNN）進行分類，最終成果和地圖將透過互動WebGIS平台進行傳播，供公眾使用參考。
Understanding the dynamics of urbanisation and adjusting planning strategies are paramount in order to create sustainable urban environments. The aim of the Sustainable Development Goal (SDG) 11 (Sustainable Cities and Communities) is to achieve this goal by making cities 'inclusive, safe, resilient and sustainable'.The ability to adjust requires a thorough understanding of the dynamics of urban expansion, and this can only be achieved my closely monitoring urban as well as population developments. Sensors on remote-sensing platforms have been providing a plethora of data over the last almost 50 years which allows us to observe and investigate changes from a vantage point that gives us the means to understand and, ultimately, adjust processes towards a sustainable future.This research project is an investigation into the dynamics of Land Cover (LC) change of urban areas and its impact on urban ecosystems, under consideration also of associated population dynamics between 1985 and 2020. This research targets at a selection of urban centres in Taiwan, in order to create a reliable and meaningful workflow for application in change monitoring using satellite remote-sensing data. Derived multi-temporal event data include areal land-cover change statistics as well metrics on Land-Use Efficiency (LUE) as formulated in SDG 11.3.1, its associated statistics, and their respective dynamics between different time periods and events, in order to assess the impact of local policy implementations and to better understand trends in local urban development. This approach complements global and less granular long-term statistics currently provided by the Global Human Settlement Layer (GHSL) through the Joint Research Centre (JRC) of the European Commission (EC). This study is a high-resolution approach, both in scale and time, to monitor the domestic development of sustainability indicators which have the potential to support domestic decision-making processes and also allow comparison with developments in non-domestic urban centres. This project aims at providing a quantitative basis and monitoring framework to assist regional planning and policy development for a sustainable urban development process. In a next step, this project makes use of the Land Cover change assessment to statistically describe and evaluate the impact of urban expansion on ecosystems and, in particular, on regulating urban ecosystem service provision as well as green infrastructure networks, in response to the targets formulated in SDG 15.1 (Life on Land). This mutlitemporal assessment is aimed to provide a basis for urban and landscape planners to valuate the loss of ecosystem service provisions and to potentially develop targeted conservation and restoration strategies.This project makes use of co-registered multitemporal, multispectral amd multi-resolution remote-sensing observations partitioned into 5-year slices covering the years 1985 to 2020. Segmentation and classification are based on a novel Convoluted Neural Network (CNN) approach. Resulting datasets and cartographic products from this project are to be disseminated through an interactive webGIS platform accessible for public use. |
| Relation: | 科技部, MOST109-2410-H004-193, 109.10-110.09 |
| Data Type: | report |
| Appears in Collections: | [地政學系] 國科會研究計畫
|
Files in This Item:
| File |
Description |
Size | Format | |
|---|
| index.html | | 0Kb | HTML | 65 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
著作權政策宣告 Copyright Announcement1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.
2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(
nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(
nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
