Climate Engine App Adds New Masking, Base Maps, and Overlay Functionality

Article Table of Contents

Summary of New Updates

As of October 2, 2025, Climate Engine introduces new capabilities that give users greater flexibility and precision in analyzing spatial and temporal data, while also supporting visualization of additional map layers. These updates are reflected in several changes to the user interface. There are three core features of these updates, 1) categorical raster masks, 2) custom base maps, and 3) raster map overlays.


Categorical Raster Masks

The new categorical raster masking functionality applies to both maps and graphs made in Climate Engine and allows users to subset their computed map layers and timeseries analysis based on categorical datasets such as land ownership, landcover, or wetland types. For example, users can now subset their maps of summer Normalized Difference Vegetation Index (NDVI) trends to Valley Bottom Extraction Tool (VBET) extents, allowing riparian assessments to be masked to predefined valley bottom areas across broad regions—without the need to manually upload or draw polygons.

Fig 1. Trend map of June, July, August mean NDVI in Elevated and Lowlying Valley Bottom.


The new raster masking functionality allows users to select up to two masking layers with various categories within each masking layer. One of the layers that is available for masking is the Surface Management Agency dataset maintained by the Bureau of Land Management. When using the Surface Management Agency mask, users can select land management agencies such as the Bureau of Land Management, National Park Service, and U.S. Forest Service to focus their analysis on specific land ownership types. Users can select as many categories as are available in each layer. When multiple categories are selected within a single masking layer, the output is always the union of those categories (e.g., choosing both National Park Service and Bureau of Land Management results in an analysis of all lands managed by either agency). By contrast, when two distinct masking layers are applied together, users can choose whether the output is based on their intersection (i.e., only locations where selected categories in both datasets overlap) or on their union (see step-by-step examples below).  


Masking can be applied to both maps and graphs in Climate Engine, enabling users to focus their maps on specific areas of the landscape and to subset their time series analysis based on their needs. For example, users are now able to produce timeseries charts of summer NDVI for the low-lying or elevated valley bottoms in the VBET extent for regions of interest like grazing allotments, HUCs, etc.

Fig 2. Summary timeseries of June, July, August mean NDVI in Lowlying Valley Bottom.


Custom Base Map 

The new custom base map functionality allows users to add high-resolution imagery and high-resolution digital elevation models (DEMs) as an additional base map layer (above the standard base map and below the Climate Engine computed map). For example, if a user is interested in what an area looked like prior to a restoration action, they can select a National Agriculture Imagery Program (NAIP) layer, specify the year of interest, and select between true color, color infrared, or NDVI layers to visualize in the map. Additional layers include historical imagery provided by USDA-NRCS and high-resolution slope and hillshade layers from the US Geological Survey’s 3DEP program. Alongside Climate Engine’s core functionality, these new basemap layers provide essential context for interpreting timeseries trends and landscape patterns. For best performance, users must zoom into their area of interest before turning on the custom base map.