| File Name: | MODIS Land Cover Mapping and Analysis in Google Earth Engine |
| Content Source: | https://www.udemy.com/course/modis-land-cover-mapping-and-analysis-in-google-earth-engine |
| Genre / Category: | Other Tutorials |
| File Size : | 586.7 MB |
| Publisher: | Earth’s AI |
| Updated and Published: | July 23, 2025 |
This course, “MODIS Land Cover Mapping and Analysis in Google Earth Engine” offers a comprehensive exploration of satellite-based land cover monitoring and analysis using state-of-the-art Earth observation tools. Students will begin with foundational knowledge of remote sensing principles, understanding how electromagnetic signals captured by satellites translate into meaningful information about Earth’s surface. The course emphasizes the critical importance of land cover data in environmental management, urban planning, agriculture, and climate studies, highlighting real-world applications and decision-making processes supported by such data.
Next, learners will be introduced to Google Earth Engine (GEE), a powerful cloud-based geospatial analysis platform that enables efficient processing and visualization of large satellite datasets. The course details how to access, filter, and manipulate MODIS land cover products, focusing on the MCD12Q1 dataset, which classifies global land surface types annually with multiple classification schemes.
Students will gain hands-on experience interpreting MODIS land cover classes and learn how to apply these datasets for detecting changes over time, critical for tracking urban expansion, deforestation, and habitat alteration. The curriculum culminates in practical implementation exercises within GEE, guiding users to create multi-year land cover visualizations, generate time series analyses, and export high-quality geospatial data outputs like GeoTIFFs for further research or reporting.
By the end of the course, students will be proficient in leveraging MODIS land cover data and GEE tools to conduct robust land cover change detection workflows applicable to academic research, environmental monitoring, and industry projects.
Who this course is for:
- Students and researchers in agriculture, environmental science, geography, or remote sensing looking to apply satellite data in real-world scenarios.
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