Evaluation of Changes in the City Fabric Using Multispectral Multi-temporal Geospatial Data: Case Study of Milan, Italy

被引:1
|
作者
Cuca, Branka [1 ]
机构
[1] Politecn Milan, I-20133 Milan, Italy
关键词
Earth Observation; Geospatial open data; Landsat; Copernicus programme; PCA; Urban planning; Milan;
D O I
10.1007/978-3-030-58811-3_58
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In recent decades the global effects of climate change have requested for a more sustainable approach in thinking and planning of our cities, making them more inclusive, safe and resilient. In terms of consumption of natural resources and pollution, cities are seen as entities with most significant impact to the natural environment. Strategic policies focused on tackling the challenges induced by climate change suggest in fact the necessity to start from the management and operating models of the cities themselves. This study illustrates an initial evaluation of parameters for purposes of urban generation studies using optical multi-spectral satellite imagery from Landsat-5, Landsat-8 and Sentinel-2 missions. The changes in land occupation and urban density are the first aspects chosen to be examined for the period 1985-2020. The focus was given on possible modifications occurred in occasion of Milano Expo 2015. The paper firstly explores the known best band combination for observation of urban fabric. Suggestions derived have then been calibrated with reference to ground truth data, while the image pairs over the 35 years span were then build with selected bands. Finally, all image pairs have been processed for Principal Component Analysis in order to identify possible "hot-spots" of significant changes. The results found on the image pair 2006-2015 have been explored in detail and checked upon official orthophotos. Monitoring of changes in urban fabric using multispectral optical imagery can provide valuable insights for further evaluation of single urban generation interventions. Such contributions could be considered in the processes of urban planning policies in a more systematic manner.
引用
收藏
页码:813 / 828
页数:16
相关论文
共 50 条
  • [41] Synergistic monitoring of transport infrastructures by multi-temporal InSAR and GPR technologies: a case study in Salerno, Italy
    Clementini, Chiara
    Latini, Daniele
    Gagliardi, Valerio
    Ciampoli, Luca Bianchini
    D'Amico, Fabrizio
    Del Frate, Fabio
    EARTH RESOURCES AND ENVIRONMENTAL REMOTE SENSING/GIS APPLICATIONS XII, 2021, 11863
  • [42] Monitoring of land use/land cover changes and its implications in the peri-urban areas using multi-temporal landsat satellite data: a case study of Guwahati city, Assam, India
    Bhattacharjee, Jeni
    Mishra, Sudisht
    Acharjee, Swapna
    PROCEEDINGS OF THE INDIAN NATIONAL SCIENCE ACADEMY, 2022, 88 (04): : 778 - 789
  • [43] Monitoring of land use/land cover changes and its implications in the peri-urban areas using multi-temporal landsat satellite data: a case study of Guwahati city, Assam, India
    Jeni Bhattacharjee
    Sudisht Mishra
    Swapna Acharjee
    Proceedings of the Indian National Science Academy, 2022, 88 : 778 - 789
  • [44] Monitoring of land use/land cover changes and its implications in the peri-urban areas using multi-temporal landsat satellite data: a case study of Guwahati city, Assam, India
    Bhattacharjee, Jeni
    Mishra, Sudisht
    Acharjee, Swapna
    Proceedings of the Indian National Science Academy, 2022, 88 (04): : 778 - 789
  • [45] Assessment of land-use/land- cover change in Muharraq Island using multi-temporal and multi-source geospatial data
    Modara, Marjan
    Belaid, Mohamed Ait
    AlJenaid, Sabah
    INTERNATIONAL JOURNAL OF IMAGE AND DATA FUSION, 2014, 5 (03) : 210 - 225
  • [46] Landslide assessment by using multi-temporal UAV datasets: a case study in northern Pakistan
    Ahmad N.
    Shafique M.
    Hussain M.L.
    Arabian Journal of Geosciences, 2021, 14 (18)
  • [47] Geospatial analysis of September, 2019 floods in the lower gangetic plains of Bihar using multi-temporal satellites and river gauge data
    Bhatt, C. M.
    Gupta, Amitesh
    Roy, Arijit
    Dalal, Prohelika
    Chauhan, Prakash
    GEOMATICS NATURAL HAZARDS & RISK, 2021, 12 (01) : 84 - 102
  • [48] Rice Yield Estimation Using Multi-Temporal Remote Sensing Data and Machine Learning: A Case Study of Jiangsu, China
    Liu, Zhangxin
    Ju, Haoran
    Ma, Qiyun
    Sun, Chengming
    Lv, Yuping
    Liu, Kaihua
    Wu, Tianao
    Cheng, Minghan
    AGRICULTURE-BASEL, 2024, 14 (04):
  • [49] UAV data for multi-temporal Landsat analysis of historic reforestation: a case study in Costa Rica
    Marx, Andrew
    McFarlane, Donald
    Alzahrani, Ahmed
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2017, 38 (8-10) : 2331 - 2348
  • [50] Uncertainty assessment of multi-temporal airborne laser scanning data: A case study on an Alpine glacier
    Joerg, Philip Claudio
    Morsdorf, Felix
    Zemp, Michael
    REMOTE SENSING OF ENVIRONMENT, 2012, 127 : 118 - 129