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.

Western Washington land cover change analysis.

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.

The Rangeland Analysis Platform ( rangelands.app) is a free online application that provides simple and fast access to geospatial vegetation data for U.S. rangelands. The tool was developed to provide landowners, resource managers, conservationists, and scientists access to data that can inform land management planning, decision making, and the evaluation of outcomes. The Rangeland Analysis Platform (RAP) uses innovative cloud computing technology to provide maps and analysis opportunities straight to your desktop, delivered securely and instantaneously. The maps and data provided by RAP are intended to be used alongside local knowledge and site-specific data to inform management actions that improve rangelands and wildlife habitat. Biomass The Rangeland Analysis Platform’s vegetation biomass product provides annual and 16-day aboveground biomass from 1986 to present of: annual forbs and grasses, perennial forbs and grasses, and herbaceous (combination of annual and perennial forbs and grasses). Estimates represent accumulated new biomass throughout the year or 16-day period and do not include biomass accumulation in previous years. Aboveground biomass was calculated by separating net primary production (paritioned by functional group) to aboveground and converting carbon to biomass (Jones et al. 2021, Robinson et al. 2019). Estimates are provided in United States customary units (lbs/acre) to facilitate use. Although these data were produced across a broad region, they are primarily intended for rangeland ecosystems. Biomass estimates may not be suitable in other ecosystems, e.g., forests., and are not to be used in agricultural lands, i.e., croplands. Cover The Rangeland Analysis Platform’s vegetation cover product provides annual percent cover estimates from 1986 to present of: annual forbs and grasses, perennial forbs and grasses, shrubs, trees, and bare ground. The estimates were produced by combining 75,000 field plots collected by BLM, NPS, and NRCS with the historical Landsat satellite record. Utilizing the power of cloud computing, cover estimates are predicted across the United States at 30m resolution, an area slightly larger than a baseball diamond. Partitioned NPP The Rangeland Analysis Platform provides net primary productivity (NPP) estimates from 1986 to present. Estimates are partitioned into the following functional groups: annual forb and grass, perennial forb and grass, shrub, and tree. NPP is the net increase (i.e., photosynthesis minus respiration) in total plant carbon, including above and below ground. NPP data download Partitioned NPP is available as GeoTIFFs from http://rangeland.ntsg.umt.edu/data/rap/rap-vegetation-npp/ and in Google Earth Engine (ImageCollection ‘projects/rap-data-365417/assets/npp-partitioned-v3’).

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.