| id |
caadria2024_365 |
| authors |
Lahtinen, Aaro, Gardner, Nicole, Ramos Jaime, Cristina and Yu, Kuai |
| year |
2024 |
| title |
Visualising Sydney's Urban Green: A Web Interface for Monitoring Vegetation Coverage between 1992 and 2022 using Google Earth Engine |
| doi |
https://doi.org/10.52842/conf.caadria.2024.2.515
|
| source |
Nicole Gardner, Christiane M. Herr, Likai Wang, Hirano Toshiki, Sumbul Ahmad Khan (eds.), ACCELERATED DESIGN - Proceedings of the 29th CAADRIA Conference, Singapore, 20-26 April 2024, Volume 2, pp. 515–524 |
| summary |
With continued population growth and urban expansion, the severity of environmental concerns within cities is likely to increase without proper urban ecosystem monitoring and management. Despite this, limited efforts have been made to effectively communicate the ecological value of urban vegetation to Architecture, Engineering and Construction (AEC) professionals concerned with mitigating these effects and improving urban liveability. In response, this research project proposes a novel framework for identifying and conveying historical changes to vegetation coverage within the Greater Sydney area between 1992 and 2022. The cloud-based geo-spatial analysis platform, Google Earth Engine (GEE), was used to construct an accurate land cover classification of Landsat imagery, allowing the magnitude, spatial configuration, and period of vegetation loss to be promptly identified. The outcomes of this analysis are represented through an intuitive web platform that facilitates a thorough understanding of the complex relationships between anthropogenic activities and vegetation coverage. A key finding indicated that recent developments in the Blacktown area had directly contributed to heightened land surface temperature, suggesting a reformed approach to urban planning is required to address climatic concerns appropriately. The developed web interface provides a unique method for AEC professionals to assess the effectiveness of past planning strategies, encouraging a multi-disciplinary approach to urban ecosystem management. |
| keywords |
Urban Vegetation, Web Interface, Landsat Imagery, Land Cover Classification, Google Earth Engine |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (1,444,057 bytes) |
| references |
Content-type: text/plain
|
Basheer, S., Wang, X., Farooque, A. A., Nawaz, R. A., Liu, K., Adekanmbi, T., & Liu, S. (2022)
 Comparison of Land Use Land Cover Classifiers Using Different Satellite Imagery and Machine Learning Techniques
, Remote Sensing, 14(19), Article 19. https://doi.org/10.3390/rs14194978
|
|
|
|
|
Chaturvedi, V., & de Vries, W. T. (2021)
Machine Learning Algorithms for Urban Land Use Planning: A Review
, Urban Science, 5(3), Article 3. https://doi.org/10.3390/urbansci5030068
|
|
|
|
|
Chen, B., Nie, Z., Chen, Z., & Xu, B. (2017)
Quantitative estimation of 21st-century urban greenspace changes in Chinese populous cities
, Science of The Total Environment, 609, 956-965. https://doi.org/10.1016/j.scitotenv.2017.07.238
|
|
|
|
|
Coppin, P., Jonckheere, I., Nackaerts, K., Muys, B., & Lambin, E. (2004)
Digital Change Detection Methods in Ecosystem Monitoring: A Review
, International Journal of Remote Sensing - INT J REMOTE SENS, 25, 1565-1596. https://doi.org/10.1080/0143116031000101675
|
|
|
|
|
Davies, P., Corkery, L., Nipperess, D. A., van den Berg, F., Joei, C., Bishop, M., Staas, L., Hose, G., Pelleri, N., Osmond, P., Keane, A., Hochuli, D., Barnett, G., Lin, B., Threlfall, C., & Wilkinson, S. (2017)
Urban ecology: Theory, policy and practice in New South Wales, Australia
, National Green Infrastructure Network. https://www.mq.edu.au/research/research-centres-groups-and-facilities/secure-planet/centres/centre-for-green-cities/publications
|
|
|
|
|
Duncan, J. M. A., & Boruff, B. (2023)
Monitoring spatial patterns of urban vegetation: A comparison of contemporary high-resolution datasets
, Landscape and Urban Planning, 233, 104671. https://doi.org/10.1016/j.landurbplan.2022.104671
|
|
|
|
|
Gibril, M., Idrees, M., Yao, K., & Shafri, H. (2018)
Integrative image segmentation optimization and machine learning approach for high quality land-use and land-cover mapping using multisource remote sensing data
, Journal of Applied Remote Sensing, 12, 1. https://doi.org/10.1117/1.JRS.12.016036
|
|
|
|
|
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017)
Google Earth Engine: Planetary-scale geospatial analysis for everyone
, Remote Sensing of Environment, 202, 18-27. https://doi.org/10.1016/j.rse.2017.06.031
|
|
|
|
|
Hoang, N.-D., & Tran, X.-L. (2021)
Remote Sensing-Based Urban Green Space Detection Using Marine Predators Algorithm Optimized Machine Learning Approach
, Mathematical Problems in Engineering, 2021, 1-22. https://doi.org/10.1155/2021/5586913
|
|
|
|
|
Li, R., Zheng, S., Duan, C., Wang, L., & Zhang, C. (2022)
Land cover classification from remote sensing images based on multi-scale fully convolutional network
, Geo-Spatial Information Science, 25(2), 278-294. https://doi.org/10.1080/10095020.2021.2017237
|
|
|
|
|
Lu, D., Mausel, P., Brondízio, E., & Moran, E. (2004)
Change Detection Techniques
, International Journal of Remote Sensing, 25
|
|
|
|
|
Mehmood, M. S., Rehman, A., Sajjad, M., Song, J., Zafar, Z., Shiyan, Z., & Yaochen, Q. (2023)
Evaluating land use/cover change associations with urban surface temperature via machine learning and spatial modeling: Past trends and future simulations in Dera Ghazi Khan, Pakistan
, Frontiers in Ecology and Evolution, 11. https://www.frontiersin.org/articles/10.3389/fevo.2023.1115074
|
|
|
|
|
Shrestha, M., Mitra, C., Rahman, M., & Marzen, L. (2023)
Sydney, Australia Metro Area Population 1950-2023
, Remote Sensing, 15(1), Article 1. https://doi.org/10.3390/rs15010106
|
|
|
|
|
Wu, C., & Murray, A. T. (2003)
What is remote sensing and what is it used for? | U.S. Geological Survey
, Remote Sensing of Environment, 84(4), 493-505. https://doi.org/10.1016/S0034-4257(02)00136-0
|
|
|
|
|
Yang, Y., Song, F., Ma, J., Wei, Z., Song, L., & Cao, W. (2022)
Spatial and temporal variation of heat islands in the main urban area of Zhengzhou under the two-way influence of urbanization and urban forestry
, PLoS ONE, 17(8), e0272626. https://doi.org/10.1371/journal.pone.0272626
|
|
|
|
|
Zhang, L., Yang, L., Zohner, C. M., Crowther, T. W., Li, M., Shen, F., Guo, M., Qin, J., Yao, L., & Zhou, C. (2022)
Direct and indirect impacts of urbanization on vegetation growth across the worlds cities
, Science Advances, 8(27), eabo0095. https://doi.org/10.1126/sciadv.abo0095
|
|
|
|
| last changed |
2024/11/17 22:05 |
|
