Detection surveys are the primary method of collecting Geospatial data on the health of treed areas affected by insects and disease and stored in a National Insect and Disease Survey (IDS) database. This process involves conducting annual aerial and ground surveys using the following systems:

With the growing need to conduct complex spatial analysis and manage large datasets, the GIS and Spatial Analysis program has begun to develop applications to aid in data management and analysis. Examples of applications developed by FHAAST include:

FHAAST provides support for both tactical and strategic forest health risk assessments. In addition, this program coordinates, in collaboration with the USDA Forest Service Forest Health Monitoring program (FHM), the development of a National Insect and Disease Risk Map (NIDRM) and database.

The Individual Tree Species Parameter Maps (ITSP) map basal area and stand density index for each individual tree species. The parameter products are based on 30-meter Landsat satellite data, climate, terrain, and soil predictor layers and ground samples from the USFS Forest Inventory and Analysis plot data.

The maps are an integration of various sources, reviewed by regional authorities. They are intended to display the biological extent of major damage agents, or the range over which they have been a managerial concern.

The Soil Drainage and Productivity Indexes provide information on the Drainage Index (DI) and Productivity Index (PI) of all soils that are classified within the US system of Soil Taxonomy. These data aid in the identification of areas at risk to various forest insects and diseases because of their ability to identify regions of potential tree stress.

The SPB Prevention and Restoration Program, along with local and regional resource managers, use the maps in planning activities and also to prioritize where prevention and restoration treatments should occur on the landscape to get the most cost-effective treatments.

With the growing need to conduct complex spatial analysis and manage large datasets, the GIS and Spatial Analysis program has begun to develop applications to aid in data management and analysis. Examples of applications developed by FHAAST include: