{"help":"Return the metadata of a dataset (package) and its resources. :param id: the id or name of the dataset :type id: string","success":true,"result":[{"id":"87f7c634-35ed-4b20-a307-e2c349022d9b","name":"data-unmanned-aerial-systems-measure-structural-habitat-features-wildlife-across-multiple","title":"Data from: Unmanned aerial systems measure structural habitat features for wildlife across multiple scales","author":"Peter J. Olsoy, Lisa A. Shipley, Janet L. Rachlow, Jennifer S. Forbey, Nancy F. Glenn, Matthew A. Brugess and Daniel H. Thornton","author_email":"peterolsoy@boisestate.edu","maintainer":"RCDS Data Repository","maintainer_email":"rcds-web@uidaho.edu","license_title":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/","notes":"\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\n\u003Cp\u003EAssessing habitat quality is a primary goal of ecologists. However, evaluating habitat features that relate strongly to habitat quality at fine-scale resolutions across broad-scale extents is challenging. Unmanned aerial systems (UAS) provide an avenue for bridging the gap between relatively high spatial resolution, low spatial extent field-based habitat quality measurements and lower spatial resolution, higher spatial extent satellite-based remote sensing. Our goal in this study was to evaluate the potential for UAS structure from motion (SfM) to estimate several dimensions of habitat quality that provide potential security from predators and forage for pygmy rabbits (Brachylagus idahoensis) in a sagebrush-steppe environment. 2.At the plant and patch scales, we compared UAS-derived estimates of vegetation height, volume (estimate of food availability), and canopy cover to estimates from ground-based terrestrial laser scanning (TLS), and field-based measurements. Then, we mapped habitat features across two sagebrush landscapes in Idaho, USA, using point clouds derived from UAS SfM. 3.At the individual plant scale, the UAS-derived estimates matched those from TLS for height (r2 = 0.85), volume (r2 = 0.94), and canopy cover (r2 = 0.68). However, there was less agreement with field-based measurements of height (r2 = 0.67), volume (r2 = 0.31), and canopy cover (r2 = 0.29). At the patch scale, UAS-derived estimates provided a better fit to field-based measurements (r2 = 0.51-0.78) than at the plant scale. Landscape-scale maps created from UAS were able to distinguish structural heterogeneity between key patch types. 4.Our work demonstrates that UAS was able to accurately estimate habitat heterogeneity for a key terrestrial vertebrate at multiple spatial scales. Given that many of the vegetation metrics we focus on are important for a wide variety of species, our work illustrates a general remote sensing approach for mapping and monitoring fine-resolution habitat quality across broad landscapes for use in studies of animal ecology, conservation, and land management.\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EUsage Notes\u003C\/strong\u003E\u003Cbr \/\u003E\n\u003Cem\u003ELandscape-scale maps of structural quality derived from UAS SfM at the Camas study site, Idaho, USA\u003C\/em\u003E\u003Cbr \/\u003E\nUnmanned aerial system (UAS) structural quality maps derived from structure from motion (SfM) photogrammetry at the Camas study site in Idaho, USA. The dense point cloud was produced in Agisoft PhotoScan, and then height filtered with the BCAL LiDAR Tools to create a canopy height model (5-cm pixel resolution). Separate maps of maximum vegetation height, volume, and canopy cover were then produced in ArcGIS at 1-m pixel resolution.\u003Cbr \/\u003E\nCamas_landscape_maps.zip\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003ELandscape-scale maps of structural quality derived from UAS SfM at the Cedar Gulch study site, Idaho, USA\u003C\/em\u003E\u003Cbr \/\u003E\nUnmanned aerial system (UAS) structural quality maps derived from structure from motion (SfM) photogrammetry at the Cedar Gulch study site in Idaho, USA. The dense point cloud was produced in Pix4D, and then height filtered with the BCAL LiDAR Tools to create a canopy height model (5-cm pixel resolution). Separate maps of maximum vegetation height, volume, and canopy cover were then produced in ArcGIS at 1-m pixel resolution.\u003Cbr \/\u003E\nCedar_landscape_maps.zip\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003EUAS-TLS plant-scale structural metrics\u003C\/em\u003E\u003Cbr \/\u003E\nPlant-scale comparison of unmanned aerial system (UAS) structure from motion (SfM) and terrestrial laser scanning (TLS) structural metrics (shrub height, shrub volume, and canopy cover) at two study sites in Idaho, USA.\u003Cbr \/\u003E\nuas_tls_plant.csv\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003EUAS-Field plant-scale structural metrics\u003C\/em\u003E\u003Cbr \/\u003E\nPlant-scale comparison of unmanned aerial system (UAS) structure from motion (SfM) structural metrics and field-based measurements (shrub height, shrub volume, and canopy cover) at two study sites in Idaho, USA.\u003Cbr \/\u003E\nuas_field_plant.csv\u003C\/p\u003E\n\u003Cp\u003E\u003Cem\u003EUAS-Field patch-scale structural metrics\u003C\/em\u003E\u003Cbr \/\u003E\nPatch-scale comparison of unmanned aerial system (UAS) structure from motion (SfM) structural metrics and field-based measurements (shrub height, shrub volume, and canopy cover) at two study sites in Idaho, USA.\u003Cbr \/\u003E\nuas_field_patch.csv\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EData Use\u003C\/strong\u003E\u003Cbr \/\u003E\n\u003Cem\u003ELicense\u003C\/em\u003E\u003Cbr \/\u003E\n\u003Ca href=\u0022https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\u0022\u003ECC0-1.0\u003C\/a\u003E\u003Cbr \/\u003E\n\u003Cem\u003ERecommended Citation\u003C\/em\u003E\u003Cbr \/\u003E\nOlsoy PJ, Shipley LA, Rachlow JL, Forbey JS, Glenn NF, Burgess MA,Thornton DH. 2018. Data from: Unmanned aerial systems measure structural habitat features for wildlife across multiple scales [Dataset]. Dryad. \u003Ca href=\u0022https:\/\/doi.org\/10.5061\/dryad.631q1\u0022\u003Ehttps:\/\/doi.org\/10.5061\/dryad.631q1\u003C\/a\u003E\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EFunding\u003C\/strong\u003E\u003Cbr \/\u003E\nUS National Science Foundation: \u003Ca href=\u0022https:\/\/www.nsf.gov\/awardsearch\/showAward?AWD_ID=1146368\u0022\u003EDEB-1146368\u003C\/a\u003E\u003C\/p\u003E\n","url":"https:\/\/data.nkn.uidaho.edu\/dataset\/data-unmanned-aerial-systems-measure-structural-habitat-features-wildlife-across-multiple","state":"Active","log_message":"Edited by awchild.","private":true,"revision_timestamp":"Thu, 08\/17\/2023 - 10:59","metadata_created":"Thu, 03\/10\/2022 - 13:28","metadata_modified":"Thu, 08\/17\/2023 - 10:59","creator_user_id":"6cc16f2c-77c2-4d12-ac06-56bbb86b535b","type":"Dataset","resources":[{"id":"3f7371d9-1ffb-4c08-8783-319911a57365","revision_id":"","url":"https:\/\/doi.org\/10.5061\/dryad.631q1","description":"","format":"html","state":"Active","revision_timestamp":"Thu, 08\/17\/2023 - 10:55","name":"Data Access via Dryad | Data from: Unmanned aerial systems measure structural habitat features for wildlife across multiple scales","mimetype":"html","size":"","created":"Thu, 03\/10\/2022 - 13:29","resource_group_id":"bff301ea-b742-427b-954e-e6a326c2ea45","last_modified":"Date changed  Thu, 08\/17\/2023 - 10:55"}],"tags":[{"id":"0fd5f6e9-babb-45d4-a5fe-d355a4994b37","vocabulary_id":"2","name":"sagebrush (Artemisia spp.)"},{"id":"425f965a-f839-486d-be20-95827298c8c0","vocabulary_id":"2","name":"ecology"},{"id":"3674bcbf-dfe1-49a4-a7f1-02453987f97e","vocabulary_id":"2","name":"geospatial science"},{"id":"c57b6327-705e-4431-b293-6b751290e656","vocabulary_id":"2","name":"landscape"},{"id":"3e857422-f378-4e8a-9318-7e8c1f8b24e6","vocabulary_id":"2","name":"legacy data"},{"id":"385f043c-10c3-4661-ac92-92b7bab3ce17","vocabulary_id":"2","name":"remote sensing"},{"id":"15630280-92f9-415b-967a-1a7440d4fd2f","vocabulary_id":"2","name":"unoccupied aerial systems (UAS)"},{"id":"435edef7-8f56-48e1-851a-1231e1537ef4","vocabulary_id":"2","name":"wildlife"},{"id":"ac64353c-b86d-4f98-9e34-fdf049edacd6","vocabulary_id":"2","name":"canopy cover"},{"id":"15fe8d19-6c72-4abf-af1c-957722a47a02","vocabulary_id":"2","name":"shrub height"},{"id":"8b4e98f3-4815-4654-b512-502198d5d44a","vocabulary_id":"2","name":"shrub volume"},{"id":"6b29d68e-985a-4661-b6f3-2c373c3e920b","vocabulary_id":"2","name":"terrestrial laser scanning"}],"groups":[{"description":"\u003Cp\u003EBoise State University is a Carnegie-classified doctoral research university and our students have opportunities to work with talented and accomplished faculty on research, even as undergraduates.  Our students go into the workforce better prepared, with expertise outside of their major by taking advantage of opportunities such as certificates in business anthropology, entrepreneurship, or cybersecurity.  \u003C\/p\u003E\n\u003Cp\u003ELearn more at \u003Ca href=\u0022https:\/\/www.boisestate.edu\/\u0022\u003Ehttps:\/\/www.boisestate.edu\/\u003C\/a\u003E\u003C\/p\u003E\n","id":"bff301ea-b742-427b-954e-e6a326c2ea45","image_display_url":"https:\/\/data.nkn.uidaho.edu\/sites\/default\/files\/bsu_logo.jpg","title":"Boise State University","name":"group\/boise-state-university"},{"description":"\u003Cp\u003EThe primary objective of Idaho EPSCoR is to stimulate research in niche areas that can become fully competitive in the disciplinary and multidisciplinary research programs of the National Science Foundation and other relevant agencies. Idaho EPSCoR provides support for sustainable increases in Research and Development capacity and advances science and engineering capabilities within the state. \u003C\/p\u003E\n\u003Cp\u003EVisit them at \u003Ca href=\u0022https:\/\/www.idahoepscor.org\u0022\u003Ehttps:\/\/www.idahoepscor.org\u003C\/a\u003E\u003C\/p\u003E\n","id":"e696b239-9ecb-412e-b032-03a75b2b9fd6","image_display_url":"https:\/\/data.nkn.uidaho.edu\/sites\/default\/files\/Idaho_epscor_logo_no_white_background.png","title":"Idaho EPSCoR","name":"group\/idaho-epscor"},{"description":"\u003Cp\u003EGEM3 is an NSF EPSCoR research program seeking to understand how genetic diversity and phenotypic plasticity affect species response to environmental change, shaping both population response and adaptive capacity.\u003C\/p\u003E\n\u003Cp\u003EVisit them at: \u003Ca href=\u0022https:\/\/www.idahogem3.org\u0022\u003Ehttps:\/\/www.idahogem3.org\u003C\/a\u003E\u003C\/p\u003E\n","id":"1812a312-11a4-492d-960b-9a78b4abfe0c","image_display_url":"https:\/\/data.nkn.uidaho.edu\/sites\/default\/files\/GEM3_nov5_logo.png","title":"EPSCoR GEM3","name":"group\/epscor-gem3"}]}]}<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN"
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