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Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
CMHRP,
Cape Ann,
Coastal Armoring,
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
CMHRP,
Cape Lookout,
Cape Lookout,
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
CMGP,
Coastal Armoring,
Coastal Habitat,
Riparian and wetland systems were determined from NHD waterbodies, SWReGAP riparian landcover types, and LANDFIRE riparian existing vegetation types. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ and DEV_N_FZ) represent human development intensity values modeled...
The Visual Resource Inventory Classes data were provided by BLM. This dataset presents current and future change agent models and combined future potential for climate change (PFC) within Visual Resource Inventory Classes. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ...
The Visual Resource Management Classes data were provided by BLM.This dataset presents current and future change agent models and combined future potential for climate change (PFC) within Visual Resource Management Classes. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ...
The Visual Resource Management Classes data were provided by BLM.This dataset presents current and future change agent models and combined future potential for climate change (PFC) within Visual Resource Management Classes. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ...
Riparian and wetland systems were determined from NHD waterbodies, SWReGAP riparian landcover types, and LANDFIRE riparian existing vegetation types. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ and DEV_N_FZ) represent human development intensity values modeled...
The Visual Resource Inventory Classes data were provided by BLM. This dataset presents current and future change agent models and combined future potential for climate change (PFC) within Visual Resource Inventory Classes. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ...
This dataset presents current and future change agent models and combined future potential for change (PFC). Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ and DEV_N_FZ) represent human development intensity values modeled from the landscape condition model. Current...
This dataset presents current and future change agent models and combined future potential for change (PFC). Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ and DEV_N_FZ) represent human development intensity values modeled from the landscape condition model. Current...
The Visual Resource Management Classes data were provided by BLM.This dataset presents current and future change agent models and combined future potential for climate change (PFC) within Visual Resource Management Classes. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ...
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
CMGP,
Coastal Armoring,
Coastal Habitat,
Riparian and wetland systems were determined from NHD waterbodies, SWReGAP riparian landcover types, and LANDFIRE riparian existing vegetation types. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ and DEV_N_FZ) represent human development intensity values modeled...
The Visual Resource Inventory Classes data were provided by BLM. This dataset presents current and future change agent models and combined future potential for climate change (PFC) within Visual Resource Inventory Classes. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ...
Riparian and wetland systems were determined from NHD waterbodies, SWReGAP riparian landcover types, and LANDFIRE riparian existing vegetation types. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ and DEV_N_FZ) represent human development intensity values modeled...
The Visual Resource Inventory Classes data were provided by BLM. This dataset presents current and future change agent models and combined future potential for climate change (PFC) within Visual Resource Inventory Classes. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ...
The Visual Resource Management Classes data were provided by BLM.This dataset presents current and future change agent models and combined future potential for climate change (PFC) within Visual Resource Management Classes. Potential for change (PFC) was determined by calculating the maximum potential for change among all change agents within each 1 km reporting unit. Current and future landscape intactness (LCM_C_FZ and LCM_N_FZ) are based on measures of landscape development and invasive species. Current vegetation departure (VDEP) is based on LANDFIRE vegetation departure and characterizes the departure of current vegetation from historic reference vegetation conditions. Current and future human development (DEV_C_FZ...
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
CMGP,
Coastal Armoring,
Coastal Habitat,
Understanding how sea-level rise will affect coastal landforms and the species and habitats they support is critical for crafting approaches that balance the needs of humans and native species. Given this increasing need to forecast sea-level rise effects on barrier islands in the near and long terms, we are developing Bayesian networks to evaluate and to forecast the cascading effects of sea-level rise on shoreline change, barrier island state, and piping plover habitat availability. We use publicly available data products, such as lidar, orthophotography, and geomorphic feature sets derived from those, to extract metrics of barrier island characteristics at consistent sampling distances. The metrics are then incorporated...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Atlantic Ocean,
Barrier Island,
CMGP,
Coastal Armoring,
Coastal Habitat,
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