NASA CMS: Tree Canopy Cover and Canopy Height at 1-Meter Resolution in New Jersey, USA

This dataset provides 1-meter resolution tree canopy cover and canopy height data for the state of New Jersey. The data were derived using a rules-based expert system that integrated leaf-on LiDAR and imagery data into a single classification workflow, utilizing spectral, height, and spatial information from the datasets. The canopy cover and canopy height data are organized by county. In the canopy cover file, a grid cell value of 1 indicates the presence of canopy cover. In the canopy height files, the values represent canopy height in meters, with a scaling factor of 100 applied to reduce file size.

This dataset has been used as input for a novel forest carbon monitoring and modeling system, which integrates a mechanistic model (i.e., Ecosystem Demography EDv3), multi-source remote sensing data, meteorological reanalysis, and soil properties. It enables the estimation of carbon dynamics from the past to the present  and projects future carbon sequestration (Hurtt et al.,2019 and 2024; Huang et al.,2019; Ma et al 2021; Tang et al., 2021).

Similar data for other states in the northeastern U.S. are archived in other repositories.

Reference

1. Hurtt, G., Zhao, M., Sahajpal, R., Armstrong, A., Birdsey, R., Campbell, E., ... & Tang, H. (2019). Beyond MRV: high-resolution forest carbon modeling for climate mitigation planning over Maryland, USA. Environmental Research Letters, 14(4), 045013.

2. Huang, W., Dolan, K., Swatantran, A., Johnson, K., Tang, H., O’Neil-Dunne, J., ... & Hurtt, G. (2019). High-resolution mapping of aboveground biomass for forest carbon monitoring system in the Tri-State region of Maryland, Pennsylvania and Delaware, USA. Environmental Research Letters, 14(9), 095002.

3. Ma, L., Hurtt, G., Tang, H., Lamb, R., Campbell, E., Dubayah, R., Guy, M., Huang, W., Lister, A., Lu, J., Dunne, J. O., Rudee, A., Shen, Q. & Silva, C. High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA. Environmental Research Letters (2021). doi:https://doi.org/10.1088/1748-9326/abe4f4 

4. Tang, H., Ma, L., Lister, A., O'Neil-Dunne, J., Lu, J., Lamb, R. L., Dubayah, R. & Hurtt, G. High-resolution forest carbon mapping for climate mitigation baselines over the RGGI region, USA. Environ Res Lett 16, 035011 (2021).

5. Hurtt, G. C., Ma, L., Lamb, R., Campbell, E., Dubayah, R. O., Hansen, M., ... & Tang, H. (2024). Beyond MRV: combining remote sensing and ecosystem modeling for geospatial monitoring and attribution of forest carbon fluxes over Maryland, USA. Environmental Research Letters, 19(12), 124058.