Skills: ArcGIS, QGIS, ENVI, Google Earth, JavaScript, Python, Geoserver
Degrees: Master Of Science in Remote Sensing
2020-2023
GPA: 3.87/4
Bachler Of Science in Geomatic
2016-2020
GPA: 3.73/4
Technical Proficiencies: Programming:
Python (Expert), SQL (intermediate), JavaScript(Beginner), R(Beginner)
AI:
Machine Learning (Scikit-Learn), Deep Learning (Torch, TensorFlow)
Libraries:
Pandas, Numpy, Matplotlib
GDAL, Geopandas, Shapely,
OpenCV, Rasterion, GeeMap
Version Control:
Git, Gitlab
Software:
ENVI, SNAP, QGIS, ArcGIS, PIX4D, AGISOFT
Cloud Platform:
Google Earth engine, Google Collab, Microsoft Planetary Computer
Service Categories: 1. Data Acquisition and Processing
Satellite Imagery Acquisition: Capturing imagery from various satellite platforms (optical, radar, thermal).
Preprocessing: Data calibration, correction (geometric, radiometric), and enhancement.
Data Fusion: Combining data from multiple sources (e.g., multi-sensor integration).
2. Image Analysis and Interpretation
Classification: Land cover, vegetation, and object classification using techniques like supervised and unsupervised classification.
Change Detection: Monitoring changes over time in land use, vegetation, urban development, etc.
Feature Extraction: Identifying and extracting specific features (e.g., roads, buildings, water bodies).
Object Detection: Detecting and identifying specific objects (e.g., vehicles, ships) using AI and machine learning.
3. Geospatial Data Management
GIS Integration: Incorporating remote sensing data into Geographic Information Systems (GIS) for spatial analysis.
4. Environmental Monitoring
Land Use and Land Cover Mapping: Monitoring and mapping changes in land use and vegetation cover.
Climate and Weather Monitoring: Analyzing atmospheric data for weather prediction and climate studies.
Disaster Management: Monitoring and assessing natural disasters (e.g., floods, earthquakes, wildfires).
5. Agriculture and Forestry
Precision Agriculture: Monitoring crop health, soil moisture, and agricultural productivity.
Forest Monitoring: Assessing forest cover, deforestation, and forest health.
Yield Prediction: Estimating crop yields using remote sensing data.
6. Urban and Infrastructure Planning
Urban Mapping: Monitoring urban sprawl, land use, and infrastructure development.
Infrastructure Monitoring: Inspecting roads, bridges, and buildings using high-resolution imagery.
7. Hydrology and Water Resources
Water Quality Monitoring: Assessing water quality in rivers, lakes, and coastal areas.
Flood Mapping: Monitoring flood extents and predicting flood risks.
Watershed Analysis: Analyzing watershed boundaries, flow paths, and water resources.
8. Custom Solutions and Consulting
Custom Algorithm Development: Creating bespoke algorithms for specific remote sensing applications.
Training and Capacity Building: Providing training on remote sensing techniques and tools.
Consulting Services: Offering expert advice and solutions for complex remote sensing challenges.
Summary Statement: I am an engineer, researcher, and developer in remote sensing with nearly one year of practical experience in the field. I am passionate about leveraging advanced remote sensing techniques to address complex environmental challenges and optimize processes. My expertise spans climate monitoring, groundwater mapping, natural hazard assessment, and agricultural applications, underpinned by a strong background in machine learning, deep learning, and geospatial data analysis. In addition to my environmental monitoring expertise, I have significant experience working with high-resolution imagery for precision agriculture, which enables accurate analysis and informed decision-making for sustainable agricultural practices.
Currently, as a UAV specialist, I am responsible for capturing and processing aerial imagery using drones. In this role, I use these images to generate Digital Terrain Models (DTM), Digital Elevation Models (DEM), and orthomosaics. These models are crucial for volume estimation.