Compilation of actual evapotranspiration and vegetation indices along critical riparian zones on the Navajo Nation from 2013-2023

These data were compiled for monitoring riparian zone trends and changes in the Navajo Nation as part of a study to document riparian ecosystem health and its water use in support of potential restoration efforts. The objective of our study was to monitor the short and medium-term effects on the riparian vegetation in relation to evapotranspiration changes, drought, and other hydrological processes, along some critical riparian zones in the Navajo Nation. These data represent time series of vegetation greenness and water use for the years 2013 to 2023. These data were collected from the spaceborne mission Landsat 8 which carries the OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) sensors for an area within the Navajo Nation in northeastern Arizona. The specific regions of interest were focused on some Culturally Important Riparian Areas (CIRAS), including Buell Park/Black Creek Headwaters, Ganado/Pueblo Colorado Wash, Grand Falls, Oraibi Headwaters, Pasture Canyon, and Tappan Springs. Landsat data are collected and distributed by the U.S. Geological Survey. The acquired imagery was filtered for quality and reprocessed by the Vegetation Index and Phenology Lab at the University of Arizona, to generate vegetation indices and evapotranspiration trends for these riparian corridors. These data summarize the time series over the 11-year study. Three vegetation indices (VIs) are computed and reported: the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and the Two-Band Enhanced Vegetation Index (EVI2). NDVI and EVI datasets were taken directly from Landsat products, EVI2 was calculated in the VIP Lab. Time series for daily Actual Evapotranspiration (ETa), in millimeters per day, were estimated from both EVI and EVI2 data using an ET empirical model (Nagler and others, 2013). These data can be used to study the trends in vegetation greenness, productivity, and water use, using VIs and ET respectively. These estimations can be linked to other variables or causes, and used to assess the effect climate change is having in this arid region in the period from 2013 to 2023.

                                            [
  "010:12"
]
                                        

                                            {
  "fn": "Pamela L Nagler",
  "@type": "vcard:Contact",
  "hasEmail": "mailto:pnagler@usgs.gov"
}
                                        

                                            [
  {
    "@type": "dcat:Distribution",
    "title": "Digital Data",
    "format": "XML",
    "accessURL": "https://doi.org/10.5066/P13VMGER",
    "mediaType": "application/http",
    "description": "Landing page for access to the data"
  },
  {
    "@type": "dcat:Distribution",
    "title": "Original Metadata",
    "format": "XML",
    "mediaType": "text/xml",
    "description": "The metadata original format",
    "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.67902085d34e28977994d30c.xml"
  }
]
                                        

                                            [
  "Arizona",
  "Black Creek",
  "Black Creek Headwaters",
  "Buell Park",
  "Ganado Wash",
  "Grand Falls",
  "Landsat images",
  "Navajo Nation",
  "Oraibi Headwaters",
  "Oraibi Wash",
  "Pasture Canyon",
  "Pueblo Colorado Wash",
  "Tappan Spring",
  "USGS:67902085d34e28977994d30c",
  "biogeography",
  "biota",
  "climatologyMeteorologyAtmosphere",
  "data release",
  "ecosystem monitoring",
  "environment",
  "evapotranspiration",
  "geoscientificInformation",
  "geospatial datasets",
  "image collections",
  "imageryBaseMapsEarthCover",
  "inlandWaters",
  "land use and land cover",
  "land use change",
  "phenology",
  "plant greenness",
  "precipitation (atmospheric)",
  "remediation",
  "remote sensing",
  "river ecosystems",
  "seasonal trends",
  "time series datasets",
  "vegetation",
  "water use",
  "wetland ecosystems"
]
                                        

                                            {
  "name": "U.S. Geological Survey",
  "@type": "org:Organization"
}
                                        

                                            [
  "Geospatial"
]