{"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":"8543d768-6166-4431-9668-b6306a7cd3fb","name":"remote-sensing-indicators-blm-aim-gmt-2","title":"Remote Sensing Indicators for BLM AIM GMT-2","author":"Timm Nawrocki","author_email":"twnawrocki@alaska.edu","maintainer":"Alaska Conservation Science Catalog","maintainer_email":"twnawrocki@alaska.edu","license_title":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/","notes":"\u003Cp\u003E\u003Cimg alt=\u0022survey team conducts line-point intercept in the GMT-2 area\u0022 title=\u0022\u0022 src=\u0022\/sites\/default\/files\/styles\/panopoly_image_original\/public\/Banner_GMT2.jpg\u0022 \/\u003E\u003C\/p\u003E\n\u003Cp\u003EThe Alaska Center for Conservation Science (ACCS) at University of Alaska Anchorage conducted Assessment, Inventory, and Monitoring (AIM) in the Greater Moose\u2019s Tooth \u2013 2 (GMT-2) area for Bureau of Land Management (BLM) during 2019 and 2021. In addition to the field measure core and supplemental AIM indicators, we provide remote sensing indicators, described in the attached user guide. AIM remote sensing indicators extend site-level monitoring measurements across entire landscapes and expand the suite of measured variables beyond those practical to measure extensively in the field. The AIM remote sensing indicators for GMT-2 relate to the National Petroleum Reserve \u2013 Alaska (NPR-A) ecosystem conceptual model developed for the AIM NPR-A pilot project (Boucher et al. 2018). The remote sensing indicators include the following data:\u003C\/p\u003E\n\u003Col\u003E\n\u003Cli\u003ESurficial features\u003C\/li\u003E\n\u003Cli\u003ESurface water\u003C\/li\u003E\n\u003Cli\u003EVegetation pattern (foliar cover)\u003C\/li\u003E\n\u003Cli\u003EExisting vegetation type\u003C\/li\u003E\n\u003Cli\u003EProductivity\u003C\/li\u003E\n\u003Cli\u003EPhenology\u003C\/li\u003E\n\u003C\/ol\u003E\n\u003Cp\u003E\u003Cstrong\u003EAbout the data\u003C\/strong\u003E\u003Cbr \/\u003E\nData are primarily .tif rasters. Data visualizations are provided as .lyrx files intended for use in ArcGIS Pro 3.0+. Users should download the attached zip folder containing the data and extract into a directory intended to store the data. More information regarding specific datasets can be found in the user guide.\u003C\/p\u003E\n\u003Cp\u003E\u003Cstrong\u003EAcknowledgements\u003C\/strong\u003E\u003Cbr \/\u003E\nThis project was made possible through funding from the Bureau of Land Management (BLM). Ecologists at BLM, Jornada Experimental Range, and ACCS developed the AIM program in NPR-A, including selecting remote sensing indicators (see Boucher et al. 2018). Numerous ecologists and technicians collected the field data necessary to make the dataset possible. Lindsey Flagstad provided comments on the map classification related to USNVC alliances.\u003C\/p\u003E\n","url":"https:\/\/accscatalog.uaa.alaska.edu\/dataset\/remote-sensing-indicators-blm-aim-gmt-2","state":"Active","private":true,"revision_timestamp":"Wed, 11\/01\/2023 - 10:43","metadata_created":"Tue, 03\/07\/2023 - 10:32","metadata_modified":"Wed, 11\/01\/2023 - 10:43","creator_user_id":"d81d7a64-7e59-4e25-83b9-978a7a7aab2c","type":"Dataset","resources":[{"id":"05731cd3-349a-4f9d-bf7c-5fc7fd08a7ce","revision_id":"","url":"https:\/\/accscatalog.uaa.alaska.edu\/sites\/default\/files\/BLM_AIM_GMT2_RemoteSensingIndicators_20221215.pdf","description":"\u003Cp\u003EThe user guide is a PDF document that provides an overview of methods and results, including the accuracy assessment, for the remote sensing indicators.\u003C\/p\u003E\n","format":"pdf","state":"Active","revision_timestamp":"Tue, 03\/07\/2023 - 10:35","name":"User Guide for the Remote Sensing Indicators for BLM AIM GMT-2","mimetype":"application\/pdf","size":"4.57 MB","created":"Tue, 03\/07\/2023 - 10:35","resource_group_id":"","last_modified":"Date changed  Tue, 03\/07\/2023 - 10:35"},{"id":"da019acb-c9e6-4169-a54d-781ec82129b6","revision_id":"","url":"\u003Cdiv class=\u0022field field-name-field-link-remote-file field-type-file field-label-hidden\u0022\u003E\u003Cdiv class=\u0022field-items\u0022\u003E\u003Cdiv class=\u0022field-item even\u0022\u003Ehttps:\/\/accs.uaa.alaska.edu\/files\/GMT2_RemoteSensing_v1_0.zip\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E","description":"\u003Cp\u003EThe data package contains .tif raster files for surficial features, surface water, vegetation pattern, existing vegetation type, productivity, and phenology. Where applicable, trained model results are also provided in the data package.\u003C\/p\u003E\n","format":"zip","state":"Active","revision_timestamp":"Tue, 03\/07\/2023 - 10:37","name":"Data Package for the Remote Sensing Indicators for BLM AIM GMT-2","mimetype":"zip","size":"","created":"Tue, 03\/07\/2023 - 10:37","resource_group_id":"","last_modified":"Date changed  Tue, 03\/07\/2023 - 10:37"},{"id":"f5978039-fecc-410c-8750-5981fa4cc6cf","revision_id":"","url":"https:\/\/github.com\/accs-uaa\/remote-sensing-gmt2","description":"\u003Cp\u003EThe code repository contains a suite of scripts based in Python, R, and Javascript to map the remote sensing indicators by linking training data or calibrated remotely sensed data to a suite of spectral, topographic, hydrographic, and ancillary covariates. All non-manual processing steps are included as scripts in the code repository.\u003C\/p\u003E\n","format":"html","state":"Active","revision_timestamp":"Tue, 03\/07\/2023 - 10:41","name":"Git Repository for the Remote Sensing Indicators for BLM AIM GMT-2","mimetype":"html","size":"","created":"Tue, 03\/07\/2023 - 10:41","resource_group_id":"","last_modified":"Date changed  Tue, 03\/07\/2023 - 10:41"}],"tags":[{"id":"8b89ca85-6db9-4297-a889-72ec201c8489","vocabulary_id":"2","name":"vegetation map"},{"id":"c8c1de90-5903-44f3-9bd7-17b5f78e15d2","vocabulary_id":"2","name":"North Slope"},{"id":"136c8552-df5c-4549-9386-330378d9e52a","vocabulary_id":"2","name":"npra"},{"id":"2f3b1cc7-68e7-4289-98dc-272d0bc342ce","vocabulary_id":"2","name":"abundance"},{"id":"1f483bc6-fd65-4b80-a521-906783693ed7","vocabulary_id":"2","name":"foliar cover"},{"id":"7f134d3c-4908-4ca3-bd59-979b6f123536","vocabulary_id":"2","name":"productivity"},{"id":"4843d711-fe6a-4a15-af7d-95f2c71d6108","vocabulary_id":"2","name":"phenology"},{"id":"e0c799d9-d528-4032-8ef4-bf0cd544f038","vocabulary_id":"2","name":"AKVEG"}]}]}