Item talk:Q227425

From geokb

{

 "@context": "http://schema.org/",
 "@type": "WebPage",
 "additionalType": "Project",
 "url": "https://www.usgs.gov/centers/fort-collins-science-center/science/using-remotely-sensed-data-evaluate-aspects-land-health",
 "headline": "Using remotely sensed data to evaluate aspects of land health at watershed scales for the Bureau of Land Management in Colorado",
 "datePublished": "January 10, 2022",
 "author": [
   {
     "@type": "Person",
     "name": "Sarah Carter, PhD",
     "url": "https://www.usgs.gov/staff-profiles/sarah-carter",
     "identifier": {
       "@type": "PropertyValue",
       "propertyID": "orcid",
       "value": "0000-0003-3778-8615"
     }
   },
   {
     "@type": "Person",
     "name": "Nathan Kleist, PhD",
     "url": "https://www.usgs.gov/staff-profiles/nathan-kleist",
     "identifier": {
       "@type": "PropertyValue",
       "propertyID": "orcid",
       "value": "0000-0002-2468-4318"
     }
   }
 ],
 "description": [
   {
     "@type": "TextObject",
     "text": "The Bureau of Land Management (BLM) manages for conditions that sustain land health on over 1 million acres of public rangelands. They have traditionally assessed conditions using small-scale field data, but agency guidance suggests assessment at larger spatial scales, such as an entire watershed. The BLM can align current methods with original land health guidance by using remotely sensed data to evaluate aspects of land health over time and across large spatial extents. Remotely sensed data provide information on trends over time and space that provide spatial and temporal context for field-based results. This can help BLM staff to interpret field-based monitoring data and provides an updated context to view prior land health assessments. Remotely sensed data be particularly helpful for regions without mapped reference conditions, and can provide valuable cross-cutting information to support other BLM decisions and field operations."
   },
   {
     "@type": "TextObject",
     "text": "For this pilot study, we are exploring methods to quantify and interpret remotely sensed data that are relevant to Colorado land health standards, specifically standards related to upland soils, riparian systems, and native and other desirable species. We first reviewed standards and indicators for aspects that could be assessed using remotely sensed data, and limited consideration of potential datasets to those that included an accuracy assessment and were spatially explicit, published, and publicly available."
   },
   {
     "@type": "TextObject",
     "text": "This project is being coproduced with BLM staff from the Colorado State Office, the Little Snake Field Office, and the National Operations Center to ensure that significant staff input at all levels is considered as the process is developed."
   },
   {
     "@type": "TextObject",
     "text": "The Bureau of Land Management (BLM) manages for conditions that sustain land health on over 1 million acres of public rangelands. The BLM has traditionally assessed rangelands using small-scale data, but agency guidance suggests assessment of land health standards at watershed scales. We are exploring methods to integrate remotely sensed data into BLM land health processes."
   },
   {
     "@type": "TextObject",
     "text": "We found that multiple aspects of Colorado land health standards could be quantified using remotely sensed data; using these, we identified several spatial datasets that met our criteria and addressed information needs of staff in the Little Snake Field Office. We used the Rangeland, Condition, Monitoring, Assessment, and Projection dataset to quantify bare ground from 1985-2018; eMODIS Phenological Metrics from 2003-2018 as measure of vegetation productivity, and LANDFIRE Existing Vegetation Types to represent priority vegetation types in the region."
   }
 ],
 "funder": {
   "@type": "Organization",
   "name": "Fort Collins Science Center",
   "url": "https://www.usgs.gov/centers/fort-collins-science-center"
 },
 "about": [
   {
     "@type": "Thing",
     "name": "Landscape Change"
   },
   {
     "@type": "Thing",
     "name": "Land Management Practices"
   },
   {
     "@type": "Thing",
     "name": "Information Systems"
   },
   {
     "@type": "Thing",
     "name": "Landscape Science"
   },
   {
     "@type": "Thing",
     "name": "Fish and Wildlife"
   },
   {
     "@type": "Thing",
     "name": "Methods and Analysis"
   },
   {
     "@type": "Thing",
     "name": "Geology"
   },
   {
     "@type": "Thing",
     "name": "Energy"
   },
   {
     "@type": "Thing",
     "name": "Environmental Health"
   },
   {
     "@type": "Thing",
     "name": "Water"
   },
   {
     "@type": "Thing",
     "name": "Ecosystems"
   },
   {
     "@type": "Thing",
     "name": "Tools for Landscape Assessment"
   },
   {
     "@type": "Thing",
     "name": "Land Management"
   },
   {
     "@type": "Thing",
     "name": "Science Technology"
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 ]

}