The field component of remote sensing is essential to a full competency in remote sensing and its use in GIS and environmental analysis. In this course you will gain experience making connections between what we see on imagery and what is present on the ground. For landcover/land- use mapping, you will learn image supervised classification using NAIP, Landsat, and Sentinel-2. To support biophysical estimations from remote sensing you will learn how forest biomass/carbon is measured in the field and statistically estimated in the lab; you will also become familiar with drone and lidar data for 3D visualization. For field ground-truth collection in support of remote sensing, you will use High Accuracy GNSS devices and ArcGIS Online's Field Maps, and a variety of analog and digital field measurement tools, and learn sampling methods. For the culmination of this course, you will be able to use GIS, remote sensing and field data to investigate a research question related to forest or ecosystem health at SEAS' properties. Course objectives will be addressed through presentations, guided computer image processing labs, field data collection exercises, and student individual and team approaches. This is a field exercise and lab- based course. Your field- and lab-based knowledge and skills will be transferable to other types of landscapes and environmental applications of remote sensing broadly. Class occurs once each week for 4 hours, with the expectation of some homework.