Land Cover Maps for the Scotts Creek Watershed, Lake County, California for 2018, 2020, and 2022
공공데이터포털
The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial products of the Scotts Creek Watershed in Lake County, California, using National Agriculture Imagery Program (NAIP) imagery from 2018, 2020 and 2022. The imagery was downloaded from United States Department of Agriculture (USDA) - Natural Resources Conservation Service (NRCS) Geospatial Data Gateway (https://datagateway.nrcs.usda.gov). The NAIP imagery from 2018, 2020 and 2022 was classified using Random Forest Modeling to produce land cover maps with three main classifications – bare, vegetation, and shadows. A total of 600 independent reference points were used in the accuracy assessment. The overall accuracy for all classes for each dataset is 98%. See attached ScottsCreek_20XX_AccuracyAssessment.csv files (contained within each LandCoverMap_associated_files_20XX.zip for each year respectively) for details. A preview image of the land cover map for 2018 is attached to this data release as an example (see LandCoverMap_RF_ScottsCreekWatershed_USGS2022_CC0.png). The percentage of bare, vegetation and shadow pixels were calculated for the complete watershed and each individual NHDPlus2.1 catchment basins (slightly modified to support hydrological modeling). These metrics can be used to quantify bare and vegetated areas and detect and quantify vegetation changes over time. Users should be aware of the inherent errors in remote sensing products.
Land Cover Maps for the Scotts Creek Watershed, Lake County, California for 2018, 2020, and 2022
공공데이터포털
The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial products of the Scotts Creek Watershed in Lake County, California, using National Agriculture Imagery Program (NAIP) imagery from 2018, 2020 and 2022. The imagery was downloaded from United States Department of Agriculture (USDA) - Natural Resources Conservation Service (NRCS) Geospatial Data Gateway (https://datagateway.nrcs.usda.gov). The NAIP imagery from 2018, 2020 and 2022 was classified using Random Forest Modeling to produce land cover maps with three main classifications – bare, vegetation, and shadows. A total of 600 independent reference points were used in the accuracy assessment. The overall accuracy for all classes for each dataset is 98%. See attached ScottsCreek_20XX_AccuracyAssessment.csv files (contained within each LandCoverMap_associated_files_20XX.zip for each year respectively) for details. A preview image of the land cover map for 2018 is attached to this data release as an example (see LandCoverMap_RF_ScottsCreekWatershed_USGS2022_CC0.png). The percentage of bare, vegetation and shadow pixels were calculated for the complete watershed and each individual NHDPlus2.1 catchment basins (slightly modified to support hydrological modeling). These metrics can be used to quantify bare and vegetated areas and detect and quantify vegetation changes over time. Users should be aware of the inherent errors in remote sensing products.
Riparian vegetation metrics for the Colorado River between Glen Canyon Dam and Lake Mead, AZ
공공데이터포털
These data were compiled to assess the status and trends of riparian plant communities along the Colorado River between Glen Canyon Dam and Lake Mead, AZ. Three metrics have been proposed to evaluate the "Riparian Vegetation" goal identified in the Glen Canyon Dam Adaptive Management Program's Long Term Experimental and Management Plan (U.S. Department of Interior, 2016). The three metrics are total living plant cover, the proportion of living cover composed of native species, and native species richness. Current policies for Glen Canyon Dam operations result in three longitudinal bands within the riparian area that are flooded at different frequencies. The band, or hydrologic zone, that is most frequently inundated is referred to here as the “active channel” or “AC.” This includes all areas inundated by releases up to 25,000 cubic feet per second (707 m3/s). The “active floodplain” or “AF” is inundated by high flow experiments and includes areas that are inundated by releases between 25,000 cubic feet per second and 45,000 cubic feet per second (1,274 m3/s). The “inactive floodplain” or “IF” is the area along the river that is inundated by releases over 45,000 cubic feet per second, which is not planned under current policies. The metrics are assessed for each of these hydrologic zones. Data from the Grand Canyon Monitoring and Research Center's riparian vegetation monitoring protocol (Palmquist and others, 2018) can be used to evaluate these metrics, which is what is provided here. In short, 80-100 sample sites are randomly selected each year. These sites include debris fans, eddy sandbars, and channel margins. At each randomly selected sample site, ocular cover estimates of each plant species occurring in 1-m2 quadrats spanning the hydrological zones are recorded, along with an estimate of total living plant cover and associated environmental variables. The first metric, total living plant cover, consists of two pieces of data; plant occurrence (a plant is present in the sample frame) and plant cover (proportion of the sample frame covered with living plants). Cover is represented by both an ordinal cover class (1, 2, 3, 4, 5, 6, etc.) and the midpoint of the cover class value (0.01%, 0.5%, 1%, 5%, 10%, 15%, etc). The proportion of native cover is the sum total of native plant cover divided by the sum total of plant cover (native plus nonnative cover) for a sample frame. Native plant richness is the total number of native species rooted inside a sample frame. The total living plant cover data are available for 2016 through 2023. The native cover and richness data are available for 2014 and 2016 through 2023.
Select watershed attributes for California stream segments (NHDPlus V.1)
공공데이터포털
This data set includes 28 physical watershed attributes for each of 135,118 stream segments (National Hydrodraphy Dataset, Version 1) in California. These data were used to support a report entitled: "Classification of California streams using combined deductive and inductive approaches: setting the foundation for analysis of hydrologic alteration" authored by Pyne, Carlisle, Konrad, and Stein, and published in the journal Ecohydrology. Specifically, these data were used in a classification (ie, cluster) analysis to identify unique groupings of watersheds with similar hydrological characteristics.
Select watershed attributes for California stream segments (NHDPlus V.1)
공공데이터포털
This data set includes 28 physical watershed attributes for each of 135,118 stream segments (National Hydrodraphy Dataset, Version 1) in California. These data were used to support a report entitled: "Classification of California streams using combined deductive and inductive approaches: setting the foundation for analysis of hydrologic alteration" authored by Pyne, Carlisle, Konrad, and Stein, and published in the journal Ecohydrology. Specifically, these data were used in a classification (ie, cluster) analysis to identify unique groupings of watersheds with similar hydrological characteristics.