Journal Article2025Cited by 2

BOLM high resolution land use and land cover dataset and benchmark results for the rapidly developing City of Dhaka Bangladesh

Ovi Paul, Abu Bakar Siddik Nayem, Anis Sarker, Rakibul Hasan Rajib, Tahmid Hossain Jit, Armun Alam, M Ashraful Amin, Amin Ahsan Ali, AKM Mahbubur Rahman

Scientific Reports

Nature Publishing Group UK London, Vol. 15, Issue 1, pp. 37689, ISBN: 2045-2322

DOI: 10.1038/s41598-025-21458-9URL

Abstract

Land use land cover (LULC) mapping using deep learning greatly enhances our understanding of geographic, socioeconomic, and urban development patterns. However, annotated satellite data are scarce in developing countries in South and East Asia due to funding and urban heterogeneity. We present the Bangladesh Open LULC Map (BOLM), a high-resolution dataset with pixel-level annotations across eleven classes for the Dhaka metropolitan area and surrounding regions (4,392 [Formula: see text], 891 million pixels). Annotations were generated using high-resolution Bing imagery following a rigorous, multi-stage validation process supported by GIS experts. Although Bing data provides fine spatial detail for visual interpretation, multispectral data remain essential for spectral analysis and temporal monitoring. We benchmarked DeepLabV3+, HRNetv2, U-net, UnimatchV2 and Segmenter ViT-16 on five merged LULC classes, achieving an overall IoU of 0.50 and F1 score of 0.66 with the UnimatchV2. Further experiments using Sentinel-2A data highlight the trade-off between spatial and spectral resolution. Our results show that while DeepLabV3+ and HRNet are effective for LULC mapping, other models such as U-Net, Segmenter, and UniMatchV2 perform even better, highlighting the model-agnostic nature of our study. The BOLM dataset can support future deep learning models and domain adaptation for LULC tasks in data-scarce regions, addressing the critical gap of high-quality LULC data in South and East Asia.

Keywords

  • land use and land cover mapping
  • data-scarce regions
  • DeepLabV3+
  • U-Net
  • Sentinel-2A
  • Dhaka Metropolitan Area
  • pixel-level annotation
  • urban development

CCDS Authors

Ovi Paul
Ovi Paul

Ovi Paul

  • Research Assistant, CCDS

PhD Student

University of Houston

Published at

ICPR, ICIP, Scientific Reports

Research Interests

Machine Learning, Geosensing System Engineering

Abu Bakar Siddik Nayem
Abu Bakar Siddik Nayem

Abu Bakar Siddik Nayem

  • Research Assistant, CCDS

Lead ML Engineer

Acme AI

Published at

ICPR, ICIP, Scientific Reports

Research Interests

Machine Learning

Anis Sarker
Anis Sarker

Anis Sarker

  • Research Assistant, CCDS

AI Engineer

AinoviQ

Published at

ICPR, ICIP, Scientific Reports

Research Interests

Machine Learning

Rakibul Hasan Rajib
Rakibul Hasan Rajib

Rakibul Hasan Rajib

  • Research Assistant, CCDS

Published at

IJCNN, ICIP, Scientific Reports

Research Interests

Computer Vision, Multimodal Learning, Federated Learning

Armun Alam
Armun Alam

Armun Alam

  • Research Assistant, CCDS

Published at

ECCV, Scientific Reports

Research Interests

Machine Learning

Prof. M Ashraful Amin, PhD
M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

  • Founder Director, CCDS
  • Director, AI/ML, HCI & DS Wings

Professor

+1 more affiliation

Department of Information Sciences and Technology

George Mason University, USA

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

Research Interests

Machine Learning, Cognitive & Vision Science, Cybernetics, Surveillance & Security, ICT in Education, Health, & Agriculture, Human-Computer Interaction, Internet of Things, Robotics

Amin Ahsan Ali, PhD
Amin Ahsan Ali, PhD

Amin Ahsan Ali, PhD

  • Director, AI/ML Wing

Professor

Department of Computer Science and Engineering

Independent University, Bangladesh

Published at

ACL, CHI, UbiComp, ECCV, IJCAI, ECAI, WACV, IPSN, PAKDD, LREC, IJCNN, ICPR, ICIP, BEA, BLP, ICMLA, Scientific Reports, Scientific Data, Pattern Recognition, Information Sciences, Ad Hoc Networks, Drug and Alcohol Dependence, PLOS ONE

Research Interests

Artificial Intelligence, Machine Learning

AKM Mahbubur Rahman, PhD
AKM Mahbubur Rhman, PhD

AKM Mahbubur Rahman, PhD

  • Director, DS & IPT Wings

Associate Professor

Department of Computer Science and Engineering

Independent University, Bangladesh

Published at

CHI, ECCV, WACV, PAKDD, LREC, IJCNN, ICPR, ICIP, HCII, BEA, Scientific Reports, Information Sciences

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