DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

DOWNLOAD RASTER IMAGERYThese layers show current Resource Inventory Units (RIUs) symbolized using attributes populated from remote-sensing predictionsRS-FRIS is a remote-sensing based forest inventory for WA DNR State Trust lands. RS-FRIS predicts forest conditions using statistical models that relate field measurements to three-dimensional remotely-sensed data (DAP and LiDAR point clouds). Forest metrics are predicted at a scale of 1/10th acre and stored as rasters. The attributes of each RIU are calculated as the mean of the raster cell values that fall within each polygon. Note: origin year and age are exceptions, and are based on the median value. RS-FRIS 4.0 was constructed using remote-sensing data collected in 2019 and 2020. Origin year and age are periodically updated to reflect harvest activities; all other attributes continue to report conditions as shown in the remote sensing data.Layers include: AGE, BA, BA_4, BA_4_CONIFER, BA_4_HWD, BA_6, BA_T100, BAP_HWD, BFVOL_GROSS, BFVOL_NET, BIOMASS_ALL, BIOMASS_LIVE, CANOPY_LAYERS, CARBON_ALL, CARBON_LIVE, CFVOL_DDWM, CFVOL_TOTAL, CLOSURE, COVER, HT_LOREY, HT_T40, HT_T100, HTMAX, QMD, QMD_6, QMD_T100, RD, RD_6, RD_SUM, SDI_SUM, SDI_SUM_4, SNAG_ACRE_15, SNAG_ACRE_20, SNAG_ACRE_21, SNAG_ACRE_30, TREE_ACRE, TREE_ACRE_4, TREE_ACRE_4_CONIFER, TREE_ACRE_6, TREE_ACRE_8, TREE_ACRE_11, TREE_ACRE_20, TREE_ACRE_21, TREE_ACRE_30 and TREE_ACRE_31.

Tree Equity Score UK is a map-based application that was created to help address disparities in urban tree distribution by identifying the areas in greatest need of people-focused investment in trees. The score sets a national standard in the USA to help make the case for investment in areas with the greatest need.

Tree Equity Score UK is a map-based application that was created to help address disparities in urban tree distribution by identifying the areas in greatest need of people-focused investment in trees. The score sets a national standard in each UK country to help make the case for investment in areas with the greatest need.

Tree Equity Score UK is a map-based application that was created to help address disparities in urban tree distribution by identifying the areas in greatest need of people-focused investment in trees. The score sets a national standard in each UK country to help make the case for investment in areas with the greatest need.

Tree Equity Score UK is a map-based application that was created to help address disparities in urban tree distribution by identifying the areas in greatest need of people-focused investment in trees. The score sets a national standard in each UK country to help make the case for investment in areas with the greatest need.

Tree Equity Score UK is a map-based application that was created to help address disparities in urban tree distribution by identifying the areas in greatest need of people-focused investment in trees. The score sets a national standard in each UK country to help make the case for investment in areas with the greatest need.

Tree Equity Score UK is a map-based application that was created to help address disparities in urban tree distribution by identifying the areas in greatest need of people-focused investment in trees. The score sets a national standard in each UK country to help make the case for investment in areas with the greatest need.