Job Description
- Process, analyze, and interpret remote sensing data from various sources, including satellite and aerial imagery, to support project objectives in environmental monitoring, land cover mapping, and resource management.
- Conduct Land Use and Land Cover (LULC) analysis, including image classification, change detection, and thematic mapping, to support projects in agriculture, forestry, urban planning, and natural resource management.
- Perform accuracy assessments to evaluate the reliability of classification and analysis outputs, using field data and statistical methods to ensure high-quality results.
- Develop and implement algorithms in Python and utilize Google Earth Engine to automate workflows, analyze large datasets, and extract meaningful information from remote sensing data.
- Use software tools such as ENVI and SNAP to conduct advanced image processing and analysis, including spectral analysis, vegetation indices, and multi-temporal analysis.
- Collaborate with project teams to understand data needs, deliver analytical insights, and provide remote sensing support tailored to specific project goals.
- Prepare detailed reports, maps, and visualizations to communicate findings, including graphical and statistical summaries that meet project requirements.
- Stay updated on remote sensing technologies, software updates, and industry trends to incorporate the latest methods into workflows, improving analysis accuracy and efficiency.
- Assist in field validation and data collection as needed, ensuring ground truth data aligns with satellite-based findings for robust analysis.
- Document methodologies and workflows to standardize processes and support knowledge sharing within the team.
Qualifications
- Bachelor's degree in a relevant field such as Geographic Information Science (GIS), Geospatial Information Technology, Geomatics Engineering, Geodesy, Environmental Science, or a related field.
- 1-2 years of experience in remote sensing data analysis and processing.
- Proficiency in remote sensing data processing, with proven skills in Land Use and Land Cover (LULC) analysis.
- Familiarity with Python programming.
- Experience working with Google Earth Engine.
- Strong working knowledge of remote sensing software, such as ENVI or SNAP
- Excellent problem-solving abilities and a high level of attention to detail in data analysis, ensuring accuracy and reliability in outputs.
- Good communication skills to present analytical findings clearly and collaborate with cross-functional teams.
- Strong time management skills with the ability to meet project deadlines and work effectively both independently and as part of a team.