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Making climate risk visible before it becomes a disaster!
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Making climate risk visible before it becomes a disaster!
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Achievement: StarstruckAchievement: Public Sponsor

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Achievement: StarstruckAchievement: Public Sponsor

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waleedgeo/README.md

Earth observation to environmental intelligence — geospatial grid and orbital globe Earth observation to environmental intelligence — geospatial grid and orbital globe

Mirza Waleed

GeoAI researcher · Physical geographer · Google Developer Expert, Earth Engine

I turn satellite observations into tools for understanding floods and environmental change. My work combines remote sensing, machine learning, and cloud/HPC computing to map flood susceptibility, assess exposure, and build reproducible geospatial workflows.

Ph.D. in Geography (Remote Sensing & GeoAI), Hong Kong Baptist University, 2026. Former Visiting Research Scholar at KAUST, 2024–2025.

Website · Google Scholar · Google Developer Profile · LinkedIn · Email

Selected work

GFSM v1 · Global flood susceptibility

Open 30 m dataset built with approximately 30.45 million training samples across 192 deployment units. Published in Scientific Data.

Explore the map · Paper · Dataset

BAM · Self-supervised burned-area mapping

Physics-informed mapping from multi-source Earth observation, using automatically generated training labels.

Launch the app · Paper

PI-SwinIR · Physics-informed terrain refinement

Swin transformers and multimodal Earth observation for terrain elevation refinement. Includes training, inference, evaluation, and checkpoints.

NFSEA · Flood intelligence

Research framework integrating near-real-time flood mapping, susceptibility estimation, and exposure analysis in Earth Engine.

More projects · Publications

Toolkit

Code & data — Python, JavaScript, R, SQL · Rasterio, GeoPandas, Xarray, PostGIS
Machine learning — PyTorch, scikit-learn, XGBoost, LightGBM · self-supervised learning, explainable AI
Earth observation — Google Earth Engine · Sentinel-1/2, Landsat, MODIS, ERA5 · QGIS, ArcGIS Pro
Compute — Google Cloud, Shaheen III, SLURM, Docker · reproducible cloud and HPC workflows

Open science & learning

I share code, datasets, and teaching materials to make geospatial research easier to reproduce and build on.

Interested in GeoAI, flood risk, or cloud-based Earth observation? Let's connect for research collaborations, consulting, and workshops.

Popular repositories Loading

  1. lulc_py lulc_py Public

    A framework for land-use classification using open sourced python based geospatial modules.

    Jupyter Notebook 35 12

  2. 30daymap-2023 30daymap-2023 Public

    Repository for hosting materials for my 30 Day Map Challenge (2023) Journey!

    Jupyter Notebook 33 4

  3. EarthEngineProjects EarthEngineProjects Public

    A repository containing open-sourced projects (mostly my contributed) on the use of Google Earth Engine for various environmental applications.

    JavaScript 28 13

  4. lulc_pk lulc_pk Public

    A repository containing data for the paper" Urbanization-led land cover change impacts terrestrial carbon storage capacity: A high-resolution remote sensing-based nation-wide assessment in Pakistan…

    JavaScript 21 13

  5. gee_py_ml gee_py_ml Public

    This repository contains materials for the workshop on Google Earth Engine Python API for ML-based Classification

    Jupyter Notebook 19 8

  6. FSM-PK FSM-PK Public

    The repository contains data for the paper titled"High-resolution flood susceptibility mapping and exposure assessment in Pakistan: An integrated artificial intelligence, machine learning and geosp…

    Jupyter Notebook 15 5