Data from: Mapping Potential Forest Canopy Top Height over Eastern United States for Aid in Restoration and Silviculture Planning

Potential Forest Canopy Top Height for the Eastern United States Overview This dataset provides 1-km resolution maps of potential forest canopy top height (pCTH) for various forest type groups (FTGs) across the Eastern United States. Potential canopy top height is defined as the maximum height a forest canopy can be expected to reach under current, stable environmental and climatic conditions, without major disturbances. This dataset was developed to provide a quantitative, spatially explicit baseline for future forest conditions, serving as a valuable tool for a wide range of applications in ecology, conservation, and forest management. The data is provided under three distinct masking schemes, each offering a different perspective on potential future forest composition: Current Forest Type Group (FTG) Distribution: Assumes that the current distribution of FTGs remains static. Ecoregional Dominant FTGs: Allows for the potential spread of dominant FTGs within their respective ecoregions. Projected Potential FTG (LANDFIRE ESP): Uses the LANDFIRE Environmental Site Potential (ESP) product to represent a "natural" or "climax" distribution of FTGs. Methodology The pCTH maps were generated using a process-based, mechanistic model grounded in the hydraulic limitation hypothesis. The model simulates the equilibrium between water availability (influenced by climate and topography) and canopy water use (transpiration), which is linked to tree height through allometric scaling relationships. Model parameters were calibrated for each forest type group using a Bayesian inference framework, which integrates multi-source data including field measurements, remote sensing products, and forest trait databases. The model was calibrated and validated using canopy height observations from NASA's Global Ecosystem Dynamics Investigation (GEDI) mission, with a focus on old-growth forests to approximate climax conditions. Prediction uncertainty was quantified by propagating uncertainties from both the model parameters and climate inputs. For a complete description of the methodology, please refer to the accompanying preprint: https://doi.org/10.22541/au.176281856.64381389/v1. Dataset Files and Content The dataset is provided as a set of GeoTIFF files, each corresponding to one of the masking schemes. The pixel values in each file represent the mean predicted potential canopy top height in meters. An additional set of files is provided to represent the uncertainty (standard deviation) of the predictions. pCTH_FTG800_maskS1_1km.tif: Potential canopy top height for Maple/Beech/Birch group (FTG=800, see USFS page) based on the 1st masking scheme (the FTG's current distribution). pCTH_STD_FTG500_maskS3_1km.tif: Standard deviation of the pCTH predictions for Oak/Hickory group based on the 3rd masking scheme (the FTG's potential distribution from LANDFIRE ESP). The 1st masking scheme also includes FTG-specific layers of relative deviation. RelDev_FTG160_wGEDI_maskS1_1km.tif: Relative deviation for Loblolly/Shortleaf Pine Group, comparing pCTH with the GEDI L3 product, masked by the 1st masking scheme. A QGIS project file (PCTH_Eastern_US.qgz) is provided for visualization. Potential Applications This dataset is intended to support a variety of applications, including: Forest Restoration and Reforestation Planning: Identifying suitable areas for restoration and setting realistic targets for future forest structure. Carbon Accounting and Climate Mitigation: Estimating the potential for aboveground biomass and carbon sequestration in forests of the Eastern US. Silviculture and Forest Management: Informing long-term management strategies and the selection of appropriate species for planting. Biodiversity and Habitat Modeling: Assessing the potential for future habitat availability for forest-dwelling species. Limitations and Disclaimer Users of this dataset should be aware of the following limitations: The predictions are based on current climate conditions and do not account for future climate change. The model assumes that forests reach a climax state without major disturbances such as fire, pests, or hurricanes. The predictions are primarily driven by an equilibrium state of water accessibility and demand, and do not explicitly model other factors that may limit tree height, such as nutrient availability or wind stress. The 3rd masking scheme may have ambiguity from the rough mapping relationship between FTG and ESP classes. The model performs well in mountainous regions (relative deviation~0) but have overestimation on nutient-limited wetlands. The spatial resolution is 1-km, and the data may not capture fine-scale variations in site conditions. This dataset should be used as a tool for understanding the potential of forest ecosystems, rather than a definitive prediction of future forest conditions. Citation If you use this dataset in your research, please cite the accompanying publication. As of November 2025, the manuscript is under review and the preprint is recommended to cite: Zhenpeng Zuo, Hangkai You, Katie Glodzik, Dongchen Zhang, Yupan Zhang, Ranga B Myneni. Mapping Potential Forest Canopy Top Height over Eastern United States for Aid in Restoration and Silviculture Planning. Authorea. November 10, 2025. https://doi.org/10.22541/au.176281856.64381389/v1