Muhammad Waqas | GIS & Remote Sensing Researcher

5+Years Experience

3.72MS CGPA / 4.0

1Publication

10+Major Projects

About Me

Earth Scientist
with a Data Mind

I am a Remote Sensing & GIS researcher passionate about using satellite data and computational methods to understand our changing planet. With an MS in Remote Sensing & GIS (CGPA 3.72/4.0) from Pir Mehr Ali Shah Arid Agriculture University and over five years of industry experience, I combine rigorous academic training with production-grade engineering.

My work spans groundwater depletion monitoring with GRACE gravity data, SAR-based flood mapping, large-scale crop health surveillance using Sentinel imagery, and terabyte-scale geospatial pipeline automation with ArcPy and Python. Currently working as GIS Editor at Neo Space Group in Riyadh on enterprise-scale geospatial workflows for defense and government applications.

I am actively pursuing funded PhD opportunities in Europe, particularly in Earth Observation, hydrology, and climate-driven geospatial analytics.

📍

Location

Riyadh, Saudi Arabia

🎓

Degree

MS Remote Sensing & GIS

💼

Current Role

GIS Editor, Neo Space Group

🔬

ORCID

0000-0001-9532-7046

📧

wiftikhar128@gmail.com

🌐

Languages

English · Urdu · Punjabi

Technical Arsenal

Skills & Expertise

A multidisciplinary toolkit spanning geospatial software, programming, machine learning, and Earth Observation platforms.

GIS Platforms

ArcGIS ProQGISGlobal MapperFMEGeoServerWeb GISArcPyCadastral Mapping

Remote Sensing & EO

Google Earth EngineSentinel-1 SARSentinel-2 OpticalGRACE / GRACE-FOERDAS IMAGINEENVINDVI / EVISAR Processing

Programming & Scripting

PythonRJavaScript (GEE)ArcPyPandas / NumPyGDAL / OGRRasterioLaTeX

AI / Machine Learning

Random ForestCNN / Deep LearningImage ClassificationCrop Yield ForecastingScikit-learnObject DetectionPCA

Databases & Data

PostgreSQL / PostGISFile GDBGeoPackageShapefileSPSSTerabyte-scale Pipelines

Field & Survey

GPS / GNSSGPS RTKTotal StationField Survey DesignUAV / Drone Mapping

Career Path

Professional Experience

From cadastral mapping to terabyte-scale satellite pipelines — a journey through the full spectrum of applied GIS.

GIS Editor

Neo Space Group

Jan 2025 – Present

📍 Riyadh, Saudi Arabia

Developed ArcPy automation scripts reducing manual GIS processing time by 40% across production pipelines.
Extracted and processed Sentinel satellite data for accurate land-use analysis on the Makan project.
Managed terabyte-scale geospatial datasets with 99% validation accuracy during QC checks.
Designed schemas for UVMap, VMap1, VVOD, ETOD, and DVOF — international defense geospatial standards.
Converted global OpenStreetMap PBF data to Topographic Data Store (TDS) format for enterprise GIS systems.

GIS & RS Specialist

SAWIE Ecosystems

Mar 2023 – Dec 2024

📍 Islamabad, Pakistan

Automated geospatial workflows in Python, R, and GEE — reducing manual processing by 45%, improving accuracy.
Implemented ML models with >90% classification accuracy on multi-source satellite data for agricultural monitoring.
Specialized in CropScan Mapping (NDVI) for crop health monitoring, increasing assessment precision by 40%.
Developed cloud removal techniques ensuring 95% usable imagery for agricultural decision pipelines.

GIS Associate / Assistant

GreenAge Services

Jul 2019 – Feb 2023

📍 Islamabad, Pakistan

Led cadastral mapping of Punjab Division state lands under a Survey of Pakistan / BOR contract.
Supervised a team delivering high-accuracy land parcel surveys and digital maps across multiple districts.

Teaching Assistant

Pir Mehr Ali Shah Agriculture University

Feb 2022 – Jun 2022

📍 Rawalpindi, Pakistan

Assisted in practicals for Applied Remote Sensing and GIS; led lecture preparation and student assessment.

Academic Background

Education

Built on a strong foundation in geoinformatics, spatial analysis, and research methodology.

MS Remote Sensing & GIS

Pir Mehr Ali Shah Arid Agriculture University

Oct 2020 – Jul 2023 · Rawalpindi, Pakistan

⭐ CGPA 3.72 / 4.00

Advanced Remote Sensing & Digital Image Processing · Geospatial Data Modeling · Advanced GIS & Spatial Analysis · Advanced Research Methods

Thesis

Weeds Identification Using Image Processing and Deep Learning Techniques

BS Geo-Informatics

Pir Mehr Ali Shah Arid Agriculture University

Sep 2016 – Sep 2020 · Rawalpindi, Pakistan

⭐ CGPA 3.33 / 4.00

Spatial Data Analysis · Web GIS · Advanced Remote Sensing · Spatial Decision Support Systems · Computer Programming for GIS · Programming for Image Analysis

Final Year Project

Quantification of Greenhouse Gases at Urban Level Using Sentinel-5P — Case Study of Lahore

Research Focus

Research Interests

Where Earth observation meets environmental urgency — research at the intersection of satellite data and global challenges.

💧

Climate Change Impact on Hydrological Processes and Agricultural Responses

🌍

Natural Resource Management, Sustainable Development & Resource-Based Urban Studies

🛰️

Remote Sensing and GIS in Environmental Monitoring and Land Use Change Detection

🌿

Ecosystem Services, Function Analysis, and Sustainability Assessment

🤖

Big Data, Machine Learning, and UAV Applications in Remote Sensing Workflows

🌊

Disaster Risk Management, Flood Mapping, and Renewable Energy Resource Assessment

🌾

AI-Driven Remote Sensing for Agriculture, Crop Monitoring, and Yield Forecasting

📡

GRACE/GRACE-FO Groundwater Storage Anomaly Detection and Basin-scale Hydrology

Research Output

Publications & Research

Contributing to peer-reviewed science at the intersection of geospatial modeling and environmental monitoring.

Integration of RUSLE Model with Remotely Sensed Data over Google Earth Engine to Evaluate Soil Erosion in Central Indus Basin

📖 Earth Surface Processes and Landforms

Applied the RUSLE model integrated with Google Earth Engine to assess spatial and temporal soil erosion patterns across the Central Indus Basin. Combines multi-source satellite data (Sentinel, SRTM DEM, MODIS) with biophysical parameters to produce actionable erosion risk maps for sustainable land management.

✓ Published View on ORCID

Featured Work

Projects

Production-grade geospatial systems, research-quality Earth Observation pipelines, and precision agriculture platforms.

🏙️

Makan Project — Enterprise GIS Pipeline

Large-scale satellite image processing and automated data extraction system for the Saudi National Geospatial Programme. Managed terabyte-scale datasets with 99% accuracy, designed VPF schemas for defense GIS, and automated workflows with ArcPy cutting processing time by 40%.

ArcPySentinelVPF/TDSPythonArcGIS Pro

🌊

GRACE Groundwater Storage Analysis — Indus Basin

Spatiotemporal analysis of groundwater depletion using GRACE/GRACE-FO total water storage anomaly data. Integrates GLDAS model layers to isolate groundwater signal, highlighting seasonal and long-term storage trends for Pakistan's water security.

GRACEGEEPythonGLDASHydrology

🌾

Advanced Crop Mapping with GEE + ML

Integrated Sentinel-1 SAR and Sentinel-2 optical data with Random Forest and CNN models for near-real-time crop monitoring and yield forecasting. Automated workflows in Python & GEE, reducing manual processing by 50%.

Sentinel-1Sentinel-2GEERandom ForestCNN

🧵

Organic Cotton Field Mapping — Sapphire

Precision agriculture project using Sentinel-2 imagery to map and monitor organic cotton fields for international certification compliance. Applied NDVI, vegetation indices, and field survey ground-truth integration.

Sentinel-2NDVIGEEPrecision Ag

💧

Flood Mapping — District Layyah (SAR)

Rapid flood extent mapping and damage assessment using Sentinel-1 SAR data processed in Google Earth Engine. Change detection between pre- and post-flood imagery to delineate inundated areas.

Sentinel-1 SARGEEChange DetectionDisaster RS

🗺️

Pakistan Village-Level Shapefiles (Open Data)

Open-source geodataset providing village-level administrative shapefiles for districts in Punjab, Pakistan. Useful for socio-demographic research, development planning, and policy analysis.

Open GIS DataShapefilePakistan AdminQGIS

🌫️

Greenhouse Gas Mapping — Lahore (Sentinel-5P)

Mapped urban greenhouse gas concentrations using Sentinel-5P TROPOMI data over Lahore. Quantified NO₂, CO, and aerosol optical depth distributions to assess air quality patterns in a major South Asian megacity.

Sentinel-5PTROPOMIAir QualityGEE

🏔️

Soil Erosion Modeling — Central Indus Basin (Published)

RUSLE-based soil erosion risk assessment in GEE combining DEM-derived slope, land cover from Sentinel, rainfall erosivity, and soil erodibility. Published in Earth Surface Processes and Landforms.

RUSLEGEESRTM DEMMODISPublished

Let's Connect

Get in Touch

Whether you're a PhD supervisor looking for a motivated Earth Observation researcher, a geospatial team seeking production-grade Python expertise, or a collaborator interested in GRACE hydrology or SAR-based environmental monitoring — I'd love to hear from you.

✉️

Primary Email

wiftikhar128@gmail.com