Skip to main content

Advertisement

SpringerLink
Log in

Does building development in Dhaka comply with land use zoning? An analysis using nighttime light and digital building heights

  • Technical Report
  • Published:
Sustainability Science Aims and scope Submit manuscript

Abstract

Zoning is an important tool to regulate the use of land and to characterize built form over land, and thus to facilitate urban sustainability. Availability of reliable data is crucial for monitoring land use zoning, which contributes directly to the success of the Sustainable Development Goals (SDGs) in general, and SDG Goal 11 for sustainable cities and communities in particular. However, obtaining this valuable information using traditional survey methods is both costly and time-consuming. Remote sensing technology overcomes these challenges and supports urban policymaking and planning processes. This study unveils a novel approach to developing a cost-effective method for identifying building types using Sentinel-2A, Visible Infrared Imaging Radiometer Suite (VIIRS)–based nighttime light (NTL) data, and TanDEM-X–based Digital Surface Model (DSM) data. A newly developed index for this study, the Normalized Difference Steel Structure Index (NDSSI), is useful for rapidly mapping industrial buildings with steel structures. The implementation status of Dhaka’s existing land use plan was evaluated by analyzing the spatial distribution of different types of building uses. This study classifies residential, commercial, and industrial buildings within Dhaka using building height, and nighttime light emission. The experimental results reveal that about 67% of commercial and 51% of industrial buildings within the Dhaka Metropolitan Area (DMA) do not comply with the land use zoning by the Detailed Area Plan (DAP). It also reveals that approximately 10% of commercial buildings, 9% of industrial buildings, and 6% of residential buildings have encroached upon conservation zones (such as open space, flood-prone zones, water bodies, and proposed areas for future road extension). A major constraint in the study was the low spatial resolution of the nighttime light dataset, which made it difficult to distinguish individual sources of light. Still, the methodological approaches proposed in this study are expected to promote reduced costs and efficacious decision-making in urban transformation and to help achieve SDG 11, especially in developing countries.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

References

  • Abdin MJ (2019) 4th Industrial Revolution and Reality of Industrialisation in Bangladesh

  • Adhary Arbain A, Imasu R, Misra P, Takeuchi W (2019) Estimating PM_ {2.5} Emission from Brick Kiln Industry over Northern India with Numerical Model and Remote Sensing Observation. EGUGA 11915

  • Ahmad S (2015) Housing demand and housing policy in urban Bangladesh. Urban Stud 52(4):738–755

    Article  Google Scholar 

  • Ahmad S, Avtar R, Sethi M, Surjan A (2016) Delhi’s land cover change in post transit era. Cities 50:111–118

    Article  Google Scholar 

  • Ahmed B, Hasan R, Maniruzzaman KM (2014) Urban morphological change analysis of Dhaka city, Bangladesh, using space syntax. ISPRS Int J Geo Inf 3(4):1412–1444

    Article  Google Scholar 

  • Alam MJ, Ahmad MM (2010) Analysing the lacunae in planning and implementation: spatial development of Dhaka city and its impacts upon the built environment. Int J Urban Sustain Dev 2(1–2):85–106

    Article  Google Scholar 

  • Al-Kodmany K, Ali MM (2013) The future of the city: tall buildings and urban design. WIT press, Southampton

    Google Scholar 

  • Artmann M, Inostroza L, Fan P (2019) Urban sprawl, compact urban development and green cities. How much do we know, how much do we agree? Ecol Indic 96:3–9. https://doi.org/10.1016/j.ecolind.2018.10.059

    Article  Google Scholar 

  • Avtar R, Yunus AP, Kraines S, Yamamuro M (2015) Evaluation of DEM generation based on Interferometric SAR using TanDEM-X data in Tokyo. Phys Chem Earth Parts A/B/C 83:166–177

    Article  Google Scholar 

  • Avtar R, Tripathi S, Aggarwal AK (2019) Assessment of energy–population–urbanization nexus with changing energy industry scenario in India. Land 8(8):124

    Article  Google Scholar 

  • Avtar R, Aggarwal R, Kharrazi A, Kumar P, Kurniawan TA (2020a) Utilizing geospatial information to implement SDGs and monitor their progress. Environ Monit Assess 192(1):35

    Article  Google Scholar 

  • Avtar R, Komolafe AA, Kouser A, Singh D, Yunus AP, Dou J, Kumar P, Gupta RD, Johnson BA, Minh HVT (2020b) Assessing sustainable development prospects through remote sensing: a review. Remote Sens Appl Soc Environ 20:100402

  • Bahauddin KM, Rahman MM, Ahmed F (2014) Towards urban city with sustainable buildings: a model for Dhaka city Bangladesh. Environ Urban Asia 5(1):119–130

    Article  Google Scholar 

  • Bangladesh National Building Code (2015) Housing and Building Research Institute, Dhaka, Bangladesh. https://bsa.com.bd/cms_cpanel/upload/pdf_file_upload__1540152875.pdf. Accessed 24 Mar 2020

  • Banzhaf E, Hofer R (2008) Monitoring urban structure types as spatial indicators with CIR aerial photographs for a more effective urban environmental management. IEEE J Sel Topics Appl Earth Observ Remote Sens 1(2):129–138

    Article  Google Scholar 

  • Baumgart S, Hackenbroch K, Hossain S, Kreibich V (2011) Urban development and public health in Dhaka, Bangladesh. Health in megacities and urban areas. Springer, Berlin, pp 281–300

    Chapter  Google Scholar 

  • Belgiu M, Tomljenovic I, Lampoltshammer T, Blaschke T, Höfle B (2014) Ontology-based classification of building types detected from airborne laser scanning data. Remote Sens 6(2):1347–1366

    Article  Google Scholar 

  • Bennett MM, Smith LC (2017) Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics. Remote Sens Environ 192:176–197

    Article  Google Scholar 

  • Berke P, Backhurst M, Day M, Ericksen N, Dixon J (2006) What makes plan implementation successful ? An evaluation of local plans and implementation practices in New Zealand. Environ Plan 33(4):581–600. https://doi.org/10.1068/b31166

    Article  Google Scholar 

  • Clark RA (1969) Selected references on land use inventory methods. Exchange Bibliography No. 92, ED101421

  • DasGupta R, Hashimoto S, Okuro T, Basu M (2019) Scenario-based land change modelling in the Indian Sundarban delta: an exploratory analysis of plausible alternative regional futures. Sustain Sci 14(1):221–240. https://doi.org/10.1007/s11625-018-0642-6

    Article  Google Scholar 

  • Doll CNH, Muller J-P, Morley JG (2006) Mapping regional economic activity from night-time light satellite imagery. Ecol Econ 57(1):75–92

    Article  Google Scholar 

  • Dolley J, Marshall F, Butcher B, Reffin J, Robinson JA, Eray B, Quadrianto N (2020) Analysing trade-offs and synergies between SDGs for urban development, food security and poverty alleviation in rapidly changing peri-urban areas: a tool to support inclusive urban planning. Sustain Sci 15:1601–1619

    Article  Google Scholar 

  • Duany A, Talen E (2001) Making the good easy: the smart code alternative. Fordham Urb LJ. https://doi.org/10.1525/sp.2007.54.1.23

    Article  Google Scholar 

  • Elmqvist T, Siri J, Andersson E, Anderson P, Bai X, Das PK, Gatere T, Gonzalez A, Goodness J, Handel SN, Hermansson Török E, Kavonic J, Kronenberg J, Lindgren E, Maddox D, Maher R, Mbow C, McPhearson T, Mulligan J, Vogel C et al (2018) Urban tinkering. Sustain Sci 13(6):1549–1564. https://doi.org/10.1007/s11625-018-0611-0

    Article  Google Scholar 

  • Elvidge CD, Baugh K, Zhizhin M, Hsu FC, Ghosh T (2017) VIIRS night-time lights. Int J Remote Sens 38(21):5860–5879

    Article  Google Scholar 

  • Feldman S, Geisler C (2011) Land grabbing in Bangladesh: in-situ displacement of peasant holdings. Int Conf Global Land Grab 39(3-4):971–993

  • Fischel WA (2000) Zoning and land use regulation. Encycl Law Econ 2:403–423

    Google Scholar 

  • Foley DL (1963) Controlling London’s growth: planning the great wen, 1940–1960. Univ of California Press, California

    Book  Google Scholar 

  • Gadda T, Gasparatos A (2009) Land use and cover change in Japan and Tokyo’s appetite for meat. Sustain Sci 4(2):165–177. https://doi.org/10.1007/s11625-009-0085-1

    Article  Google Scholar 

  • Geiß C, Wurm M, Breunig M, Felbier A, Taubenböck H (2015) Normalization of TanDEM-X DSM data in urban environments with morphological filters. IEEE Trans Geosci Remote Sens 53(8):4348–4362

    Article  Google Scholar 

  • Gielen DM, Tasan-Kok T (2010) Flexibility in planning and the consequences for public-value capturing in UK, Spain and the Netherlands. Euro Plan Stud 18(7):1097–1131. https://doi.org/10.1080/09654311003744191

    Article  Google Scholar 

  • Google Maps (2015) Talha Spinning Mils. Ltd., 24.2369764,90.4034633. Accessed 17 Apr 2020

  • Ha W, Gowda PH, Howell TA (2013) A review of downscaling methods for remote sensing-based irrigation management: Part I. Irrig Sci 31(4):831–850. https://doi.org/10.1007/s00271-012-0331-7

    Article  Google Scholar 

  • Haala N, Peter M, Kremer J, Hunter G (2008) Mobile LiDAR mapping for 3D point cloud collection in urban areas—a performance test. Int. Arch Photogramm Remote Sens Spat Inf Sci 37:1119–1127

    Google Scholar 

  • Heiple S, Sailor DJ (2008) Using building energy simulation and geospatial modeling techniques to determine high resolution building sector energy consumption profiles. Energy Build 40(8):1426–1436

    Article  Google Scholar 

  • Hiroi U, Murayama A, Chiba Y, Komatsu H, Mori M, Yamada K, Yamazaki M, Fukuwa N (2015) A proposal of multi-scale urban disaster mitigation planning that takes regional issues into consideration. J Disaster Res 10(5):887–899

    Article  Google Scholar 

  • Ikeda S (2018) How land-use regulation undermines affordable housing. SSRN Electron J. https://doi.org/10.2139/ssrn.3211656

    Article  Google Scholar 

  • Inostroza, L., & Barrera, F. de la. (2019). Ecosystem Services and urbanisation. a spatially explicit assessment in Upper Silesia, Central Europe. IOP Conference Series: Materials Science and Engineering, https://doi.org/https://doi.org/10.1088/1757-899X/471/9/092028

  • Islam I, Adnan MSG (2011) Commercial land use in Dhaka: an analysis of trends and patterns. In: Ahmed SU, Hafiz R, Rabbani AKMG (eds). vol 400, pp 277–296

  • Islam MS, Shahabuddin AKM, Kamal MM, Ahmed R (2012) Wetlands of Dhaka city: its past and present scenario. J Life Earth Sci 7:83–90

    Article  Google Scholar 

  • Jepson EJ, Haines AL (2014) Zoning for sustainability: a review and analysis of the zoning ordinances of 32 cities in the united states. J Am Plan Assoc 80(3):239–252. https://doi.org/10.1080/01944363.2014.981200

    Article  Google Scholar 

  • Jin X, Davis CH (2005) Automated building extraction from high-resolution satellite imagery in urban areas using structural, contextual, and spectral information. EURASIP J Adv Signal Process 2005(14):745309

    Article  Google Scholar 

  • Kadhim N, Mourshed M, Bray M (2016) Advances in remote sensing applications for urban sustainability. Euro Mediterr J Environ Integr 1(1):7

    Article  Google Scholar 

  • Kalam AKMA (2009) Planning Dhaka as a global city: a critical discourse. J Bangladesh Inst Plan 2:1–12

    Google Scholar 

  • Kamruzzaman M, Ogura N (2007) Apartment housing in Dhaka City: past, present and characteristic outlook. Building Stock Activation, Tokyo

    Google Scholar 

  • Kuzmichev AA, Loboyko VF (2016) Impact of the polluted air on the appearance of buildings and architectural monuments in the area of town planning. Proc Eng 150:2095–2101

    Article  Google Scholar 

  • Lehavi A (2017) One hundred years of zoning and the future of cities. In: One hundred years of zoning and the Future of Cities Springer International Publishing. https://doi.org/10.1007/978-3-319-66869-7

  • Liang X, Kankare V, Hyyppä J, Wang Y, Kukko A, Haggrén H, Yu X, Kaartinen H, Jaakkola A, Guan F (2016) Terrestrial laser scanning in forest inventories. ISPRS J Photogr Remote Sens 115:63–77

    Article  Google Scholar 

  • Ma T, Zhou C, Pei T, Haynie S, Fan J (2012) Quantitative estimation of urbanization dynamics using time series of DMSP/OLS nighttime light data: a comparative case study from China’s cities. Remote Sens Environ 124:99–107

    Article  Google Scholar 

  • Malpica JA, Alonso M (2010) Urban changes with satellite imagery and LIDAR data. Int Arch Photogr Remote Sens Spatial Inf Sci—ISPRS Arch, 38, part8, Kyoto, Japan

  • Meter SQMSQ, Mapper TMT (2015) Nighttime light remote sensing: monitoring human societies from outer space. Remote Sens Water Resour Disasters Urban Stud 289

  • Mill T, Alt A, Liias R (2013) Combined 3D building surveying techniques–terrestrial laser scanning (TLS) and total station surveying for BIM data management purposes. J Civil Eng Manage 19(sup1):S23–S32

    Article  Google Scholar 

  • Milojevic-Dupont N, Hans N, Kaack LH, Zumwald M, Andrieux F, de Barros Soares D, Lohrey S, Pichler P-P, Creutzig F (2020) Learning from urban form to predict building heights. PLoS ONE 15(12):e0242010

    Article  CAS  Google Scholar 

  • Mishra RK (2017) Solar photovoltaic panel and roofing material detection using WorldView-3 imagery. https://www2.unb.ca/gge/Pubs/TR310.pdf. Accessed 14 Jan 2020

  • Misra P, Avtar R, Takeuchi W (2018) Comparison of digital building height models extracted from AW3D, TanDEM-X, ASTER, and SRTM digital surface models over Yangon City. Remote Sens 10(12):2008

    Article  Google Scholar 

  • Moga ST (2017) The zoning map and American city form. J Plan Educ Res 37(3):271–285

    Article  Google Scholar 

  • Mohsin KM (1989) Commercial and industrial aspects of Dhaka in the eighteen century. In: Ahmed SU (ed) Dhaka Past Present Future. The Asiatic Society of Bangladesh

  • Moreira A, Krieger G, Hajnsek I, Hounam D, Werner M, Riegger S, Settelmeyer E (2004) TanDEM-X: a TerraSAR-X add-on satellite for single-pass SAR interferometry. IGARSS 2004. 2004 IEEE Int Geosci Remote Sens Symp 2:1000–1003

    Article  Google Scholar 

  • Mustafizur RM, Mizanur RM, Ms M (2019) Environmental quality evaluation in Dhaka City Corporation (DCC)-using satellite imagery. Proc Inst Civil Eng Urban Des Plan 172(1):13–25. https://doi.org/10.1680/jurdp.17.00032

    Article  Google Scholar 

  • Nicholls E, Ely A, Birkin L, Basu P, Goulson D (2020) The contribution of small-scale food production in urban areas to the sustainable development goals: a review and case study. Sustain Sci. https://doi.org/10.1007/s11625-020-00792-z

    Article  Google Scholar 

  • Okada S, Takai N (2000) Classifications of structural types and damage patterns of buildings for earthquake field investigation.In: Proceedings of the 12th World Conference on Earthquake Engineering (Paper 0705), Auckland

  • Pal M (2002) Factors influencing the accuracy of remote sensing classifications: a comparative study. University of Nottingham

  • Pissourios IA (2019) Survey methodologies of urban land uses: an oddment of the past, or a gap in contemporary planning theory? Land Use Policy 83:403–411

    Article  Google Scholar 

  • Plan DS (2015) Dhaka Structure Plan, 2016–2035. Rajdhani Unnayan Kartripakkha (RAJUK)

  • Rahman MM, Avtar R, Yunus AP, Dou J, Misra P, Takeuchi W, Sahu N, Kumar P, Johnson BA, Dasgupta R, Kharrazi A, Chakraborty S, Agustiono Kurniawan T (2020) Monitoring effect of spatial growth on land surface temperature in Dhaka. Remote Sens 12(7):1191. https://doi.org/10.3390/rs12071191

    Article  Google Scholar 

  • Ramaiah M, Avtar R (2019) Urban green spaces and their need in cities of rapidly urbanizing India: a review. Urban Sci. https://doi.org/10.3390/urbansci3030094

    Article  Google Scholar 

  • Sadeghi Y, St-Onge B, Leblon B, Simard M (2016) Canopy height model (CHM) derived from a TanDEM-X InSAR DSM and an airborne lidar DTM in boreal forest. IEEE J Select Topics Appl Earth Observ Remote Sens 9(1):381–397

    Article  Google Scholar 

  • Samsudin SH, Shafri HZM, Hamedianfar A, Mansor S (2015) Spectral feature selection and classification of roofing materials using field spectroscopy data. J Appl Remote Sens 9(1):95079

    Article  Google Scholar 

  • Sansilvestri R, Cuccarollo M, Frascaria-Lacoste N, Benito-Garzon M, Fernandez-Manjarres J (2020) Evaluating climate change adaptation pathways through capital assessment: five case studies of forest social-ecological systems in France. Sustain Sci 15(2):539–553

    Article  Google Scholar 

  • Schaubroeck T (2018) Towards a general sustainability assessment of human/industrial and nature-based solutions. Sustain Sci 13(4):1185–1191

    Article  Google Scholar 

  • Schmidt S, Buehler R (2007) The planning process in the US and Germany: a comparative analysis. Int Plan Stud 12(1):55–75

    Article  Google Scholar 

  • Scholten HJ, Stillwell J (2013) Geographical information systems for urban and regional planning, vol 17. Springer, Berlin

    Google Scholar 

  • Shih W-Y, Ahmad S, Chen Y-C, Lin T-P, Mabon L (2020) Spatial relationship between land development pattern and intra-urban thermal variations in Taipei. Sustain Cities Soc 62:102415

    Article  Google Scholar 

  • Shumon S (2013) Steel buildings to redraw industrial landscape. The Daily Star. https://www.thedailystar.net/news/steel-buildings-to-redraw-industrial-landscape. Accessed 18 Feb 2020

  • Sikder SK, Behnisch M, Herold H, Koetter T (2019) Geospatial Analysis of building structures in Megacity Dhaka: the use of spatial statistics for promoting data-driven decision-making. J Geovisual Spatial Anal 3(1):7

    Article  Google Scholar 

  • Spyra M, Inostroza L, Hamerla A, Bondaruk J (2019) Ecosystem services deficits in cross-boundary landscapes: spatial mismatches between green and grey systems. Urban Ecosyst 22(1):37–47. https://doi.org/10.1007/s11252-018-0740-3

    Article  Google Scholar 

  • Sritarapipat T, Takeuchi W (2017) Building classification in Yangon City, Myanmar using Stereo GeoEye images, Landsat image and night-time light data. Remote Sens Appl Soc Environ 6:46–51

    Google Scholar 

  • Sterling EJ, Pascua P, Sigouin A, Gazit N, Mandle L, Betley E, Aini J, Albert S, Caillon S, Caselle JE, Cheng SH, Claudet J, Dacks R, Darling ES, Filardi C, Jupiter SD, Mawyer A, Mejia M, Morishige K, McCarter J et al (2020) Creating a space for place and multidimensional well-being: lessons learned from localizing the SDGs. Sustain Sci. https://doi.org/10.1007/s11625-020-00822-w

    Article  Google Scholar 

  • Sun Y, Zhang X, Zhao X, Xin Q (2018) Extracting building boundaries from high resolution optical images and LiDAR data by integrating the convolutional neural network and the active contour model. Remote Sens 10(9):1459

    Article  CAS  Google Scholar 

  • Swapan M, Zaman A, Ahsan T, Ahmed F (2017) Transforming urban dichotomies and challenges of South Asian megacities: rethinking sustainable growth of Dhaka Bangladesh. Urban Sci 1(4):31. https://doi.org/10.3390/urbansci1040031

    Article  Google Scholar 

  • Taubenböck H, Klotz M, Wurm M, Schmieder J, Wagner B, Wooster M, Esch T, Dech S (2013) Delineation of central business districts in mega city regions using remotely sensed data. Remote Sens Environ 136:386–401

    Article  Google Scholar 

  • The Steel Construction Institute (SCI) Technische Universität Dortmund (2018) Best Practice in steel construction

  • Tian T, Li C, Xu J, Ma J (2018) Urban area detection in very high resolution remote sensing images using deep convolutional neural networks. Sensors 18(3):904

    Article  Google Scholar 

  • Topaloğlu RH, Sertel E, Musaoğlu N (2016) Assessment of classification accuracies of SENTINEL-2 and LANDSAT-8 data for land cover/use mapPING. Int Arch Photogr Remote Sens Spatial Inf Sci 41(B8):1055–1059

  • Wang B, Jia K, Liang S, Xie X, Wei X, Zhao X, Yao Y, Zhang X (2018) Assessment of Sentinel-2 MSI spectral band reflectances for estimating fractional vegetation cover. Remote Sens 10(12):1–20. https://doi.org/10.3390/rs10121927

    Article  Google Scholar 

  • Wheeler SM (2013) Planning for sustainability: creating livable, equitable and ecological communities. Routledge, Milton Park

    Book  Google Scholar 

  • Wicht M, Kuffer M (2019) The continuous built-up area extracted from ISS night-time lights to compare the amount of urban green areas across European cities. Euro J Remote Sens 52(sup2):58–73

    Article  Google Scholar 

  • Wilkinson SJ, Kibblewhite T (2004) Building surveying: a UK phenomenon or a profession with genuine global appeal?. In: FIG 2004: Proceedings of the 2004 International Federation of Surveyors Conference

  • Wurm M, Taubenböck H, Schardt M, Esch T, Dech S (2011) Object-based image information fusion using multisensor earth observation data over urban areas. Int J Image Data Fusion 2(2):121–147

    Article  Google Scholar 

  • Xiao Y, Zhan Q (2009) A review of remote sensing applications in urban planning and management in China. Joint Urban Remote Sens Event 2009:1–5

    Google Scholar 

  • Xu R, Liu J, Xu J (2018) Extraction of high-precision urban impervious surfaces from Sentinel-2 multispectral imagery via modified linear spectral mixture analysis. Sensors 18(9):2873

    Article  Google Scholar 

  • Zhou G, Zhou X (2014) Seamless fusion of LiDAR and aerial imagery for building extraction. IEEE Trans Geosci Remote Sens 52(11):7393–7407

    Article  Google Scholar 

  • Zhuo L, Ichinose T, Zheng J, Chen J, Shi PJ, Li X (2009) Modelling the population density of China at the pixel level based on DMSP/OLS non-radiance-calibrated night-time light images. Int J Remote Sens 30(4):1003–1018

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank the Hokkaido University and Japan Student Services Organization (JASSO) for supporting us in completing this research. This research was partially funded by the Environment Research and Technology Development Fund (S-15 “Predicting and Assessing Natural Capital and Ecosystem Services” (PANCES) JPMEERF16S11510, Ministry of the Environment, Japan and the Scottish Funding Council (SFC) Global Challenge Research Fund for 2019-21 (Project Number 308286) and Kurata Hitachi grant. We are also thankful to the German Aerospace Center (DLR), NOAA, and Copernicus, providing valuable databases. The authors also acknowledge the support of the Capital City Development Authority (RAJUK), Dhaka, Bangladesh for providing necessary data and information.

Author information

Authors and Affiliations

  1. Graduate School of Environmental Science, Hokkaido University, Sapporo, Hokkaido, 060-0810, Japan

    Md. Mustafizur Rahman & Ram Avtar

  2. Capital City Development Authority (RAJUK), Dhaka, Bangladesh

    Md. Mustafizur Rahman

  3. Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Hokkaido, 060-0810, Japan

    Ram Avtar

  4. Urban Studies, School of Social and Political Sciences, University of Glasgow, Glasgow, UK

    Sohail Ahmad

  5. Institute of Geography, Ruhr University Bochum, Bochum, Germany

    Luis Inostroza

  6. Universidad Autonoma de Chile, Temuco, Chile

    Luis Inostroza

  7. Research Institute for Humanity and Nature (RIHN), Kamigamo, Kita-ku, Kyoto, 603-8047, Japan

    Prakhar Misra

  8. Natural Resources and Ecosystem Services, Institute for Global Environmental Strategies (IGES), Hayama, 240-0115, Japan

    Pankaj Kumar & Osamu Saito

  9. Institute of Industrial Science, The University of Tokyo, Tokyo, 153-8505, Japan

    Wataru Takeuchi

  10. Charles Darwin University, Darwin, Australia

    Akhilesh Surjan

Authors
  1. Md. Mustafizur Rahman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ram Avtar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sohail Ahmad
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Luis Inostroza
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Prakhar Misra
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Pankaj Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Wataru Takeuchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Akhilesh Surjan
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Osamu Saito
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ram Avtar.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Handled by Vinod Tewari, The Energy and resources Institute (TERI), India.

Appendix

Appendix

See Appendix Tables 6, 7.

Table 6 Building Development Permission and Land use Zoning According to DAP (2010–2015) for DMA
Full size table
Table 7 Percentage of identified buildings area in development permitted but not in compatible zone
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rahman, M.M., Avtar, R., Ahmad, S. et al. Does building development in Dhaka comply with land use zoning? An analysis using nighttime light and digital building heights. Sustain Sci 16, 1323–1340 (2021). https://doi.org/10.1007/s11625-021-00923-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11625-021-00923-0

Keywords

Search

Navigation