Session 9 : Spatial-temporal Models for Forest Inventory Data

Presenter Information/ Coauthors Information

Paul May, South Dakota School of Mines and TechnologyFollow

Presentation Type

Invited

Student

No

Track

Methodology

Abstract

The Forest Inventory and Analysis (FIA) program is tasked with monitoring forest resources in the United States. The program maintains a network of over 300,000 permanent field plots randomly distributed across the country. The plots are cyclically revisited and important forest attributes are measured. To estimate area-averages of attributes, FIA uses design-based inference, relying on the random selection of the plot locations. While random over space, the plots are not random over space-time. making time-specific estimates and change estimates difficult with design-based inference. I will discuss model-based solutions to this problem, addressing the complex nature of the data and the spatial-temporal relationships within.

Start Date

2-7-2025 2:30 PM

End Date

2-7-2025 3:30 PM

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Feb 7th, 2:30 PM Feb 7th, 3:30 PM

Session 9 : Spatial-temporal Models for Forest Inventory Data

Pasque (Room 255)

The Forest Inventory and Analysis (FIA) program is tasked with monitoring forest resources in the United States. The program maintains a network of over 300,000 permanent field plots randomly distributed across the country. The plots are cyclically revisited and important forest attributes are measured. To estimate area-averages of attributes, FIA uses design-based inference, relying on the random selection of the plot locations. While random over space, the plots are not random over space-time. making time-specific estimates and change estimates difficult with design-based inference. I will discuss model-based solutions to this problem, addressing the complex nature of the data and the spatial-temporal relationships within.