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Week 9 ArcGIS Earth and Online Geospatial Data
Introduction
Lab introduced ArcGIS Earth as a powerful GIS visualization and analysis tool that brings together remotely sensed data from multiple platforms and makes it easy to explore those datasets in a single environment. Through this lab, I learned how ArcGIS Earth can be used to view, analyze, and combine aerial and satellite imagery with UAS-collected data, which is especially valuable for mission planning and environmental interpretation. Remote sensing is the process of collecting information about Earth’s surface using satellites, aircraft, or drones, and it can include visible light, infrared, radar, and other parts of the electromagnetic spectrum. Because of this, remote sensing allows us to detect patterns that go beyond what the human eye can see, such as vegetation health, surface temperature, wildfire activity, and terrain elevation.
By working with ArcGIS Earth, I gained hands-on experience using layer options and analysis tools to investigate elevation change, vegetation condition, and active fire-related datasets using sources such as NAIP, MODIS, and thermal UAS imagery. These tools directly support UAS operations by helping pilots and mission planners anticipate terrain constraints, maintain safe line-of-sight, identify hazards, and design more efficient flight paths using pre-visualization. In addition, integrating GIS and remote sensing data improves post-mission analysis by allowing UAS outputs to be compared with existing environmental and geographic datasets. Compared to tools like Google Earth, ArcGIS Earth offers stronger GIS capabilities, including more advanced options for analyzing, managing, and interpreting spatial data.
In this document, I will walk through the steps I used to explore ArcGIS Earth, analyze remotely sensed datasets, and demonstrate how these capabilities can support UAS data collection, processing, and decision-making. The main objectives of this lab are to (1) discover and identify the capabilities of ArcGIS Earth as a GIS data viewing platform, (2) recognize and compare different forms of remotely sensed data within ArcGIS Earth, and (3) demonstrate proficiency in using ArcGIS Earth tools effectively for UAS mission planning and spatial analysis.
Using the Interactive Analysis tool, I created an elevation profile across the Wabash River Valley. This show me to see how ArcGIS Earth automatically calculates elevation and slope. Tools like this are useful for planning flight routes and keeping safe UAS altitudes above ground level (AGL).
CIR imagery shows vegetation in shades of red, where darker red usually means healthier plants. When I compared it with the NDVI layer, both showed similar vegetation patterns. However, CIR was easier to interpret visually because it made dense vegetation stand out more clearly than sparse areas.
The MODIS Thermal Hotspots layer shows wildfire activity across California. This information can support UAS operations for fire management by helping identify thermal anomalies and active fire perimeters.
When I zoomed out, the map revealed global fire patterns, showing that wildfires are not limited to North America—they occur worldwide wherever conditions allow.
The thermal orthomosaic shows temperature differences between the tree rows at the Martell site. The brighter lines match bare ground and vehicle tracks, which hold and release heat differently than the surrounding vegetation.
The RGB imagery provides a natural-color reference that makes it easy to identify vegetation, trees, and the Martell Trail running north–south through the field, while the thermal imagery highlights temperature differences that are invisible to the eye; together, they complement each other by combining clear visual context with heat-based insight.
Conclusion
Overall, this lab helped me move beyond basic map-reading and begin using ArcGIS in a way that connects directly to UAS operations. ArcGIS Earth made it simple to visualize elevation, vegetation health, and thermal data in one place, but this lab was only an introduction and covered just a few basic tools and imagery types. As I continue to use ArcGIS for UAS work, my proficiency will improve, and I will be able to apply layers like NDVI, CIR, and MODIS to add important context for mission planning and support better, data-driven decisions before flight.
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