Picture courtesy of debannja on pixabay.com
Overview: Students had the day off to commemorate Memorial Day
Overview:
The day focused on introducing remote sensing technologies like LiDAR, SAR, and hyperspectral imaging, along with key resolution types and data sources such as NASA’s Earthdata and Planet.com. After lunch, the team explored their project on crop water stress, discussing goals, sensor types (UAS, soil moisture, weather), and data transmission methods like LoRaWAN. A crop tour followed, with hands-on learning about georeferencing, RTK accuracy, and how SFM creates 3D models from images.
Objective:
Students gained a foundational understanding of remote sensing tools, data integration, and field techniques essential for their crop monitoring project.
Overview:
The day began with an in-depth session on mission planning for UAV flights, covering key elements like payload, navigation, flight height, image overlap, speed, and weather. Emphasis was placed on safety, efficiency, and data quality. The team also reviewed FAA regulations, best practices for image overlap (70–85%), and flight speed considerations.
In the afternoon, the group practiced UAV data collection protocols using the MicaSense Altum PT sensor. They focused on consistency, timing (solar noon), and flight parameters to ensure high-quality, standardized data for crop monitoring.
Objective:
Students learned how to plan and execute UAV missions effectively, ensuring accurate and reliable data collection.
Overview:
The day focused on introducing students to the foundational concepts and applications of Structure from Motion (SfM) and photogrammetry. Participants engaged in detailed demonstrations and tutorials using the Unmanned Aircraft Systems (UAS Manual) by Texas A&M AgriLife Research. Hands-on activities included working with Agisoft Metashape for 3D modeling and using QGIS for geospatial data analysis. The day also included exploration of drone imagery and remote sensing techniques relevant to agricultural and environmental research.
Objective:
By the end of the day, students gained a practical understanding of how 2D images can be processed into 3D models using SfM techniques. They also developed skills in using software tools such as Agisoft Metashape and QGIS, including key workflows like plot boundary creation, NDVI calculation, and exporting geospatial data. These sessions equipped students with the technical know-how to apply photogrammetry and remote sensing tools in real-world research and fieldwork scenarios.
Overview:
The day focused on GIS fundamentals, including discrete vs. continuous data, spatial data formats, and key Esri platforms like ArcGIS Online and Pro. Students explored the USDA Census of Agriculture and learned about web maps and web apps for geospatial data sharing and collaboration. Afterward, the team visited the TAMUCC Autonomous Research Institution, where they observed advanced remote sensing technologies and discussed their applications.
Objective:
Students gained a practical understanding of GIS tools, spatial data formats, and web mapping, applying these skills in real-world agricultural and research settings.