Professional Summary
Remote Sensing Expert and Geospatial Specialist with 8+ years of progressive experience in satellite and aerial imagery analysis, environmental monitoring, land use/land cover classification, change detection, and GIS-based data integration for water resources, hydrogeological, and infrastructure projects. Specialized in analyzing satellite imagery (Sentinel-2, Landsat, MODIS, Sentinel-5P/TROPOMI) to assess environmental conditions, urban expansion, vegetation indices, water bodies, and hydrological cycles using advanced spectral analysis and machine learning classification techniques. Proven expertise integrating remote sensing data with GIS to create comprehensive decision-support models. Extensive experience in groundwater monitoring, water balance studies, water quality assessment, and predictive environmental modelling. Proficient in Google Earth Engine, QGIS, ArcGIS, SNAP, Python, and R for large-scale satellite data processing. Developer of open-source QGIS plugins and AI/deep learning geospatial tools. M.Sc. in Geomatics Engineering (GPA 3.50/4.00) with thesis on remote sensing and deep learning for crop area estimation and water productivity. Native Arabic speaker fluent in English and Turkish.
Core Competencies
Satellite & Aerial Imagery Analysis
Environmental Impact Assessment
Land Use / Land Cover Classification
Hydrological & Hydrogeological Modelling
Vegetation Indices & Spectral Analysis (NDVI, EVI)
Water Bodies & Water Quality Monitoring
Change Detection & Multi-temporal Analysis
GIS Data Integration & Spatial Databases
AI / Deep Learning for Remote Sensing (CNN, GCN, ViT)
Groundwater Monitoring & Water Balance Studies
Google Earth Engine & Cloud Computing
ISO / FAO LCCS Compliant Technical Reporting
QGIS Plugin Development (Python/PyQGIS)
Field Surveying & Ground Truth Data Collection
Technical Skills
Remote Sensing:Sentinel-2, Landsat, MODIS, Sentinel-5P/TROPOMI, WaPOR (FAO); image pre-processing (mosaicking, atmospheric correction), OBIA segmentation, supervised/unsupervised classification, change detection, spectral indicesGIS Software:QGIS (advanced + plugin developer), ArcGIS Pro / ArcMap, ERDAS Imagine, ENVI, SNAP, MapInfo, IdrisiCloud Platforms:Google Earth Engine (GEE), FAO SEPAL, Google ColabProgramming:Python (GeoPandas, Rasterio, scikit-learn, PyTorch, TensorFlow, Pandas, NumPy), R (sf, terra, tidyverse, ggplot2), SQL, batch scriptingAI & Machine Learning:Deep Learning (CNN1D, Vision Transformer, Graph Convolutional Network), SVM, Random Forest, K-Means, OBIA; up to 99.9% classification accuracyHydrological Modelling:HEC-RAS, HEC-GeoHMS, SWAT, water balance analysis, catchment hydrology, ADCP discharge measurementEnvironmental Analysis:LULC mapping, EIA, climate change analysis, water quality indices (NDCI, FAI, chlorophyll-a, turbidity, TSS, CDOM)Web GIS & Databases:PostGIS, Leaflet.js, D3.js, Streamlit, FastAPI, spatial databases, interactive dashboardsField Instruments:Total Station (Leica), GPS RTK, GNSS, Echo Sounder, ADCP, Level, Theodolite, ODK CollectStandards & QA:ISO standards, FAO LCCS / LCML (ISO 19144-2), Olofsson accuracy assessment, Pontius validation methods
Professional Experience
Hydraulics Research Center (HRC) — Ministry of Irrigation & Water ResourcesWad-Madani, Sudan
Remote Sensing Expert & GIS Specialist / Research AssistantOctober 2018 – Present
Satellite & Aerial Imagery Analysis
- Analyzed Sentinel-2 and Landsat multi-temporal imagery to assess environmental conditions, land use changes, and water resource status across major irrigation schemes and river basins in Sudan
- Selected satellite imagery based on resolution, coverage, and spectral characteristics for project-specific analyses; performed mosaicking, stacking, atmospheric corrections, and OBIA segmentation
- Extracted land cover types, vegetation indices (NDVI, EVI), water bodies, and cropland boundaries using supervised classification, spectral analysis, and machine learning models
- Monitored urban expansion, river morphology, and environmental change over time using multi-temporal imagery and automated change detection algorithms
Environmental Modelling & Water Resources
- Analyzed FAO WaPOR remote sensing data to monitor crop water consumption, yield forecasts, water use efficiency, and groundwater-dependent agricultural productivity across Gezira Irrigation Scheme
- Developed water quality monitoring solutions using Sentinel-2 imagery and spectral indices (NDCI, FAI) to assess chlorophyll-a, turbidity, TSS, and CDOM — applied to Merowe Dam and irrigation waterways
- Conducted hydrographic surveys collecting cross-sectional data on channel geometry, slope, and discharge; applied remote sensing change detection to identify river morphological changes for hydrological modelling
- Developed spatial and attribute databases integrating satellite imagery, field data, and socioeconomic information for comprehensive environmental decision-support systems
AI / Deep Learning & Tool Development
- Performed crop classification using SVM and deep learning architectures (CNN1D, Vision Transformer, Graph Convolutional Network) from Sentinel-2 imagery — achieving up to 99.9% classification accuracy
- Developed two QGIS plugins: wapor-water-productivity (WaPOR-based evapotranspiration analysis) and GeoAccuRate (Olofsson/Pontius accuracy assessment with Kappa indices) — both published on QGIS Plugin Repository
- Built land cover monitoring workflows aligned with FAO LCCS and LCML/ISO 19144-2 standards; developed GEE scripts for large-scale satellite-based monitoring
Capacity Development & Reporting
- Authored monthly environmental monitoring reports on crop water consumption, yield forecasts, and water productivity performance for FAO, IFAD, and HRC institutional review
- Delivered recurring training programme as Certified Trainer on GIS, remote sensing, and surveying technologies — trained 200+ engineers and researchers; recognized by HRC Director General
Ministry of Infrastructure and TransportKhartoum, Sudan
Surveyor & Geospatial EngineerAugust 2017 – August 2018
- Conducted geospatial surveys and feasibility studies for road and dam infrastructure projects using GIS and remote sensing data; prepared technical reports and tender documents
- Supervised construction and rehabilitation projects ensuring adherence to engineering specifications; liaised with government agencies and UN stakeholders on multi-party projects
Key Internationally-Funded Projects
GIS & Remote Sensing — Gezira Irrigation Scheme Water Management (HRC)May 2023 – Present
Developing comprehensive spatial database integrating satellite imagery, field, and environmental data for sustainable water management, climate adaptation, and EIA across the Gezira Irrigation Scheme
FAO-Funded: Remote Sensing Analyst — Gezira Irrigation Scheme, SudanJan 2020 – May 2021
Integrated WaPOR remote sensing data and field observations for water management decisions; produced monthly monitoring reports; achieved FAO-commended 9% productivity improvement and 15% monitoring accuracy gain
IFAD-Funded: Water Resources Engineer — Gash Irrigation Scheme, KassalaMar 2019 – Apr 2020
Applied remote sensing and GIS to optimize water management and agricultural productivity; integrated satellite-derived soil moisture for water balance analysis and irrigation network mapping
ZOA-Funded: Hydrology & Remote Sensing Engineer — South Darfur, SudanDec 2019 – Apr 2020
Conducted catchment hydrological studies and flood risk remote sensing analysis; collected field data on rainfall, streamflow, water quality, and land use for infrastructure planning
Cropped Area Determination — Gezira & Al-Rahad Irrigation Schemes (HRC)Jan 2018 – May 2021
Leveraged Sentinel-2 satellite classification and ML models to map 2.2 million feddan of irrigated cropland — replacing manual surveying with automated remote sensing workflows; improved accuracy by 30%
Nile Gauging Station Site Selection — Northern Sudan / Egypt Border (HRC)Dec 2018 – Jun 2020
Used remote sensing change detection to analyze Nile morphological changes; conducted hydrographic surveys and rating curve development; coordinated site selection with Egyptian Ministry of Water Resources
Open-Source Research Software — github.com/Osman-Geomatics93
- wapor-water-productivity — QGIS plugin for FAO WaPOR-based water productivity analysis, ETa, AGBP, GBWP, NBWP mapping (QGIS Plugin Repository)
- GeoAccuRate — QGIS plugin implementing Olofsson (2014) accuracy assessment with Pontius area-adjusted estimates, Kappa, and bias-corrected area (QGIS Plugin Repository)
- GCN-Crop-Classification — Graph Convolutional Network pipeline for Sentinel-2 multi-temporal LULC classification — 99.9% overall accuracy (PyTorch)
- crop-classification-deep-learning — Multi-architecture Sentinel-2 crop classification comparing CNN1D, Hybrid CNN+MLP, and Vision Transformer (ViT)
- Merowe-Dam-Water-Quality — Multi-parameter water quality monitoring via Sentinel-2 and GEE using NDCI, FAI spectral indices (chlorophyll-a, turbidity, TSS, CDOM)
- Sudan-Flood-Disaster-Management — PostGIS and Leaflet.js environmental disaster response and flood risk mapping system for Sudan
- pansharpening-toolkit — Classical (IHS, Brovey, PCA) and deep learning satellite image pansharpening with quality metrics (ERGAS, SAM, Q-index)
- gezira-lens — Interactive geospatial dashboard for Gezira Irrigation Scheme monitoring (Leaflet, D3.js, Streamlit, time animation)
- TerraDiff — LiDAR point cloud 3D change detection and volumetric analysis for terrain and glacier surface dynamics
Education
Master of Science in Geomatics Engineering (Remote Sensing & GIS)August 2024
Karadeniz Technical University (KTU), Trabzon, Turkey
GPA: 3.50 / 4.00 | Supervised by Assoc. Prof. Dr. Volkan Yilmaz
Thesis: “Application of Remote Sensing and Deep Learning for Estimating Crop Areas, Yield, and Water Productivity of Wheat in the Gezira Irrigation Scheme”
Focus Areas: Satellite Image Processing, Spectral Analysis, Deep Learning, Environmental Modelling, GIS, WaPOR
B.Sc. (Hons.) in Surveying Engineering — First Class HonoursJuly 2017
Omdurman Islamic University, Faculty of Engineering, Khartoum, Sudan
Thesis: “Evaluating Roads within Omdurman Islamic University Utilizing Geographic Information Systems Technology”
Certifications & Professional Development
Remote Sensing, GIS & Water Resources:
- Remote Sensing Image Acquisition, Analysis and Applications — UNSW Sydney & IEEE GRSS, Coursera (2023)
- Spatial Analysis and Satellite Imagery in a GIS — University of Toronto, Coursera (2023)
- Geospatial Analysis with ArcGIS — University of California, Davis, Coursera (2023)
- Python for WaPOR Geospatial Analyses — FAO / IHE Delft Institute for Water Education (2024)
- GIS & Remote Sensing in WaPOR System — Hydraulics Research Center, Sudan (2020)
- Geographic Information System (GIS) using QGIS — IOM–UN Migration, UNAMID & WES Sudan (2020)
- Basics of Remote Sensing & Water Harvesting Applications — UNESCO RCWH, Sudan (2019)
- Python for GIS Development — PARIS Training Center (2019)
- Hydraulic Engineering in River Basins — Regional Training Center, Hydraulics Research Institute, Egypt (2021)
AI, Deep Learning & Data Science:
- Advanced Computer Vision with TensorFlow — DeepLearning.AI, Coursera (2024)
- Sequence Models (Deep Learning Specialization) — DeepLearning.AI, Coursera (2024)
- AI Agents and Agentic AI with Python — DeepLearning.AI, Coursera (2024)
- Data Analysis with Python — IBM, Coursera (2024)
- Data Analysis with R Programming — Google, Coursera (2023)
- Advanced Data Visualization with R — Coursera (2024)
Professional Recognition:
- Certified Trainer — GIS, Remote Sensing & Surveying Engineering — Hydraulics Research Center, Sudan (2020)
- Introduction to Front-End Development — Meta / Coursera (2024)
Languages
English
Professional — B2/C1
Listening B2 · Speaking B2 · Reading C1 · Writing B2
Turkish
Advanced — C1
Listening C1 · Speaking C1 · Reading C1 · Writing B2
References
Assoc. Prof. Volkan Yilmaz
Dept. of Geomatics Engineering, Karadeniz Technical University
Phone: +90-462-377-2778
Assoc. Prof. Younis A. Gismalla (PhD)
General Director, Hydraulics Research Center, Sudan
Phone: +249-912-833-773