Filters: partyWithName: Jon E Keeley (X) > Types: Downloadable (X)

Filters Date Range Past year (0) Past month (0) Past week (0) Past day (0) Custom range... To   Search Extensions Shapefile (4) Raster (1) Types Map Service (5) OGC WFS Layer (4) OGC WMS Layer (4) Shapefile (4) GeoTIFF (1) Raster (1) Contacts Teresa J Brennan-Kane Western Ecological Research Center U.S. Geological Survey - ScienceBase Ecosystems U.S. Geological Survey, Western Ecological Research Center More... Categories Data (5) Tag Types Theme (5) USGS Scientific Topic Keyword (4) Place (5) Harvest Set (5) Tag Schemes ISO 19115 Topic Category (5) None (4) USGS Thesaurus (4) Common Geograhic Areas (1) Common geographic areas (1) View Results as: JSON ATOM CSV

Vegetation Type Conversion in Southern California Between 1943 and 2018 This dataset contains data pertaining to ground surface cover in 30 meter plots around a random selection of points within chaparral from Santa Barbara county south to San Diego County in southern California, USA. These data were obtained from historical aerial imagery from 1943 to 1959 and current imagery from 2016 to 2018 and they were compared to quantify changes in cover type over time. These data support the following publication: Syphard, A.D., Brennan, T.J., Rustigian‐Romsos, H. and Keeley, J.E., 2022. Fire‐driven vegetation type conversion in southern California. Ecological Applications, p.e2626. https://doi.org/10.1002/eap.2626. Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Botany, Forestry, Land Use Change, Remote Sensing, Southern California, All tags... USGS Science Data Catalog (SDC), biota, chaparral, environment, image analysis, imageryBaseMapsEarthCover, shrubland ecosystems, type conversion, Fewer tags Vegetation type conversion in chaparral in San Diego County, California, USA between 1953 and 2016 This dataset contains data pertaining to ground surface cover in a 30 meter radius around a random selection of points within San Diego County, California. These data were obtained from aerial imagery for the years 1953 and 2016 and were used to assess changes in cover type over time. These data support the following publication: Syphard, A.D., Brennan, T.J. and Keeley, J.E., 2019. Extent and drivers of vegetation type conversion in Southern California chaparral. Ecosphere, 10(7), p.e02796. Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Chaparral, San Diego County, San Diego County, Southern California, USGS Science Data Catalog (SDC), All tags... biota, environment, imageryBaseMapsEarthCover, plants (organisms), type conversion, Fewer tags Chaparral Type Conversion into Herbaceous Vegetation in Coastal Southern California from 1947 to 2014, Data Compiled from Aerial Imagery, Geographic NAD83 (2017) This dataset contains data pertaining to vegetation type, woody versus herbaceous versus non-vegetated, for a random selection of points within the Santa Monica Mountains National Recreation Area of Southern California. These data were obtained from aerial imagery for the years 1947, 1977, 1995, 2005, and 2014 and were used to determine changes in cover type over time. These data support the following publication: Syphard, A.D., Brennan, T.J. and Keeley, J.E., 2018. Drivers of chaparral type conversion to herbaceous vegetation in coastal Southern California. Diversity and Distributions. https://doi.org/10.1111/ddi.12827 Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Land Use Change, Remote Sensing, Southern California Coastal, USGS Science Data Catalog (SDC), biota, All tags... chaparral, vegetation type conversion, Fewer tags Data for Use in poscrptR Post-fire Conifer Regeneration Prediction Model These data support poscrptR (Wright et al. 2021). poscrptR is a shiny app that predicts the probability of post-fire conifer regeneration for fire data supplied by the user. The predictive model was fit using presence/absence data collected in 4.4m radius plots (60 square meters). Please refer to Stewart et al. (2020) for more details concerning field data collection, the model fitting process, and limitations. Learn more about shiny apps at https://shiny.rstudio.com. The app is designed to simplify the process of predicting post-fire conifer regeneration under different precipitation and seed production scenarios. The app requires the user to upload two input data sets: 1. a raster of Relativized differenced Normalized... Categories: Data; Types: Downloadable, GeoTIFF, Map Service, Raster; Tags: Botany, California, Forestry, Oregon, USGS Science Data Catalog (SDC), All tags... biota, elevation, environment, forest ecosystems, geoscientificInformation, geospatial datasets, gymnosperms, imageryBaseMapsEarthCover, topography, Fewer tags The Effect of Prolonged Drought on Chaparral Dieback within the Perimeters of the Thomas and Woolsey Fires in Southern California, USA This dataset contains data pertaining to chaparral vegetation dieback based on the difference or change in the Normalized Difference Vegetation Index (NDVI) prior to and 6 years into an extensive drought before the 2017 Thomas and 2018 Woolsey Fires in southern California. The difference in mean NDVI is provided for 9322 study plots as are values for a number of physical and climatological variables and burn severity following the two fires. These data support the following publication: Keeley, J.E., Brennan-Kane, T.J., and Syphard, A.D., 2022. The effects of prolonged drought on vegetation dieback and megafires in southern California chaparral. Ecosphere, 13(8), e4203. https://doi.org/10.1002/ecs2.4203. Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, Shapefile; Tags: Chaparral, Climatology, Ecology, Environmental Health, Remote Sensing, All tags... Southern California, Thomas Fire, USGS Science Data Catalog (SDC), Wildfire, Woolsey Fire, biota, droughts, environment, fires, imageryBaseMapsEarthCover, vegetation, Fewer tags