The physical face of slums: a structural comparison of slums in Mumbai, India, based on remotely sensed data

被引:102
作者
Taubenboeck, H. [1 ]
Kraff, N. J. [1 ]
机构
[1] DLR, German Aerosp Ctr, German Remote Sensing Data Ctr DFD, Wessling, Germany
关键词
Slum; (In)formal settlement; Remote sensing; Structural urban analysis; Mumbai; INFORMAL SETTLEMENTS; SPATIAL METRICS; SATELLITE DATA; LAND-USE; BUILDINGS; IMAGERY; ACCRA; AIR;
D O I
10.1007/s10901-013-9333-x
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The term "slum" is difficult to define, but if we see one, we know it. Definitions for slums are qualitative such as "areas of people lacking, for example, durable housing or easy access to safe water". This study aims at identifying characteristic physical features of the built environment that allows defining slum areas based on quantitative and measurable parameters. In general, spatial data on slums are generalized, outdated, or even nonexistent. The bird's eye view of remotely sensed data is capable to provide an independent, area-wide spatial overview, to capture the complex morphological pattern and at the same time capture the large-scale individual objects typical for slums. Using high-resolution optical satellite data, parameters such as building density, building heights, and sizes are used to differentiate between slums and formal settlements. From it, the physical features are used to analyze structural homogeneity and heterogeneities within and across slums and to suggest characteristic physical features for spatial slum delineation at three study sites in Mumbai, India.
引用
收藏
页码:15 / 38
页数:24
相关论文
共 50 条
  • [31] Shoreline change detection from Karwar to gokarna - south west coast of India using remotely sensed data
    Choudhary, Richa
    Gowthaman, R.
    Sanil Kumar, V.
    International Journal of Earth Sciences and Engineering, 2013, 6 (03): : 489 - 494
  • [32] Comparison of global inventories of CO emissions from biomass burning derived from remotely sensed data
    Stroppiana, D.
    Brivio, P. A.
    Gregoire, J. -M.
    Liousse, C.
    Guillaume, B.
    Granier, C.
    Mieville, A.
    Chin, M.
    Petron, G.
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2010, 10 (24) : 12173 - 12189
  • [33] Comparison of remotely sensed and meteorological data-derived drought indices in mid-eastern China
    Zhou, Lei
    Zhang, Jie
    Wu, Jianjun
    Zhao, Lin
    Liu, Ming
    Lu, Aifeng
    Wu, Zhitao
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2012, 33 (06) : 1755 - 1779
  • [34] USING GIS-BASED SPATIAL GEOCOMPUTATION FROM REMOTELY SENSED DATA FOR DROUGHT RISK-SENSITIVE ASSESSMENT
    Lin, Meng-Lung
    Chen, Cheng-Wu
    INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL, 2011, 7 (02): : 657 - 668
  • [35] A comparison of remotely sensed and pollen-based approaches to mapping Europe's land cover
    Woodbridge, Jessie
    Fyfe, Ralph M.
    Roberts, Neil
    JOURNAL OF BIOGEOGRAPHY, 2014, 41 (11) : 2080 - 2092
  • [36] Comparative Analysis of Machine Learning Algorithms for Soil Erosion Modelling Based on Remotely Sensed Data
    Fernandez, Daniel
    Adermann, Eromanga
    Pizzolato, Marco
    Pechenkin, Roman
    Rodriguez, Christina G. G.
    Taravat, Alireza
    REMOTE SENSING, 2023, 15 (02)
  • [37] Integrating Gravity Data With Remotely Sensed Data for Structural Investigation of the Aynak-Logar Valley, Eastern Afghanistan, and the Surrounding Area
    Azizi, Masood
    Saibi, Hakim
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2015, 8 (02) : 816 - 824
  • [38] Niche differentiation and fine-scale projections for Argentine ants based on remotely sensed data
    Roura-Pascual, Nuria
    Suarez, Andrew V.
    McNyset, Kristina
    Gomez, Crisanto
    Pons, Pere
    Touyama, Yoshifumi
    Wild, Alexander L.
    Gascon, Ferran
    Peterson, A. Townsend
    ECOLOGICAL APPLICATIONS, 2006, 16 (05) : 1832 - 1841
  • [39] Prediction of hookworm prevalence in southern India using environmental parameters derived from Landsat 8 remotely sensed data
    Kulinkina, Alexandra V.
    Sarkar, Rajiv
    Mohan, Venkata R.
    Walz, Yvonne
    Kaliappan, Saravanakumar P.
    Ajjampur, Sitara S. R.
    Ward, Honorine
    Naumova, Elena N.
    Kang, Gagandeep
    INTERNATIONAL JOURNAL FOR PARASITOLOGY, 2020, 50 (01) : 47 - 54
  • [40] Identifying baseflow source areas using remotely sensed and ground-based hydrologic data
    Ahamed, Aakash
    Knight, Rosemary
    Alam, Sarfaraz
    HYDROLOGICAL PROCESSES, 2024, 38 (02)