説明
Locations of 577 plant occurrences (54 unique taxa) from the US Fish and Wildlife Service Ruby Lake National Wildlife Refuge Vegetation Mapping Survey for 2012-2013, carried out in collaboration with University of Nevada - Reno.
データ レコード
この オカレンス(観察データと標本) リソース内のデータは、1 つまたは複数のデータ テーブルとして生物多様性データを共有するための標準化された形式であるダーウィン コア アーカイブ (DwC-A) として公開されています。 コア データ テーブルには、577 レコードが含まれています。
この IPT はデータをアーカイブし、データ リポジトリとして機能します。データとリソースのメタデータは、 ダウンロード セクションからダウンロードできます。 バージョン テーブルから公開可能な他のバージョンを閲覧でき、リソースに加えられた変更を知ることができます。
バージョン
次の表は、公にアクセス可能な公開バージョンのリソースのみ表示しています。
引用方法
研究者はこの研究内容を以下のように引用する必要があります。:
Keller K (2022): USFWS - Ruby Lake National Wildlife Refuge - Vegetation Mapping Survey - 2012-2013. v1.2. United States Fish and Wildlife Service. Dataset/Occurrence. https://bison.usgs.gov/ipt/resource?r=usfws_ruby_lake_nwr_vegetation_mapping_survey&v=1.2
権利
研究者は権利に関する下記ステートメントを尊重する必要があります。:
パブリッシャーとライセンス保持者権利者は United States Fish and Wildlife Service。 To the extent possible under law, the publisher has waived all rights to these data and has dedicated them to the Public Domain (CC0 1.0). Users may copy, modify, distribute and use the work, including for commercial purposes, without restriction.
GBIF登録
このリソースをはGBIF と登録されており GBIF UUID: b1c0c801-1758-408d-aebd-777cbc1dfac7が割り当てられています。 GBIF-US によって承認されたデータ パブリッシャーとして GBIF に登録されているUnited States Fish and Wildlife Service が、このリソースをパブリッシュしました。
キーワード
Occurrence; vegetation survey; Metadata
外部データ
リソース データは他の形式で入手可能です。
U.S. Fish and Wildlife Service Catalog | https://ecos.fws.gov/ServCat/Reference/Profile/62884 utf-8 pdf |
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連絡先
- データ提供者
- データ公開者
- データ提供者
- データ公開者
地理的範囲
USFWS Ruby Lake National Wildlife Refuge: -115.53 to -115.39 longitude; 40.05 to 40.29 latitude.
座標(緯度経度) | 南 西 [40.05, -115.53], 北 東 [40.29, -115.39] |
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生物分類学的範囲
54 plant taxa; 53 species, 1 subspecies.
Species | Achillea millefolium, Achnatherum hymenoides, Agoseris glauca, Agropyron cristatum, Allium atrorubens, Alyssum desertorum, Argemone munita, Artemisia nova, Artemisia tridentata, Astragalus argophyllus, Astragalus calycosus, Astragalus purshii, Atriplex confertifolia, Atriplex gardneri, Atriplex micrantha, Atriplex truncata, Bassia hyssopifolia, Bromus tectorum, Carex praegracilis, Carex utriculata, Castilleja angustifolia, Caulanthus crassicaulis, Chrysothamnus viscidiflorus, Cirsium scariosum, Crepis runcinata, Descurainia sophia, Distichlis spicata, Eleocharis macrostachya, Elymus elymoides, Ericameria nauseosa, Erigeron lonchophyllus, Halogeton glomeratus, Hordeum jubatum, Juncus balticus, Juniperus osteosperma, Leymus cinereus, Leymus triticoides, Nitrophila occidentalis, Phlox hoodii, Poa secunda, Potentilla anserina, Pseudoroegneria spicata, Puccinellia lemmonii, Sarcobatus vermiculatus, Schoenoplectus acutus, Sonchus arvensis, Spartina gracilis, Suaeda occidentalis, Tetradymia canescens, Tetradymia spinosa, Thinopyrum intermedium, Tragopogon dubius, Triglochin maritima |
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Subspecies | Calamagrostis stricta ssp. Inexpansa |
時間的範囲
開始日 / 終了日 | 2012-07-10 / 2013-07-13 |
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プロジェクトデータ
The Ruby Lake National Wildlife Refuge (NWR) vegetation mapping project was conducted by the US Fish & Wildlife Service Pacific Southwest Region, National Wildlife Refuge System. The project was a collaboration between the Conservation Planning and Policy Branch and the Inventory and Monitoring program within the Division of Natural Resources, Ruby Lake NWR staff and the University of Nevada, Reno. The purpose of the project was to test field methods to classify the vegetation at Ruby Lake NWR and create a map to provide baseline vegetation information to the resource managers.
タイトル | U.S. Fish and Wildlife Service - Ruby Lake National Wildlife Refuge - Vegetation Mapping Survey - 2012-2013 |
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識別子 | https://ecos.fws.gov/ServCat/Reference/Profile/62884 |
ファンデイング | USFWS Refuge Planning and the Inventory and Monitoring Program |
Study Area Description | see: https://ecos.fws.gov/ServCat/DownloadFile/166789 |
研究の意図、目的、背景など(デザイン) | This vegetation dataset was produced through interpretation of multiple datasets, assisted by field data and site visits. The primary dataset utilized is NAIP orthoimagery from August of 2013. The NAIP imagery was combined with several addition derived products. These included a Normalized Difference Vegetation Index and a texture layer, derived from the NAIP imagery, as well as a digital elevation model and a canopy height model, both created from a LiDAR dataset acquired over the refuge in 2009. All of these inputs were stacked in one layer with a consistent pixel size and coordinate system and then analyzed using the RandomForest tool in R software. This tool uses a data mining approach with multiple decision trees to find patterns in the data. The tool is trained with known landcover types provided by the GIS analyst. In addition to using the RandomForest algorithm, the NAIP imagery was also divided into segments using eCognition Developer software. The pixel-based output from the RandomForest analysis was then converted to polygons by using a Majority zonal statistics in ArcMap. Note that the RandomForest analysis was run several times before an acceptable level of accuracy was reached. Following conversion to polygons, additional manual edits were made to problem areas and in specific areas, again in an effort to improve the overall accuracy of the product. An independent collection of over 400 ground control points was used in the validation and the overall accuracy was found to be 86%. |
プロジェクトに携わる要員:
- データ提供者
追加のメタデータ
Unique identifiers for each record was generated during data cleaning by combining dataset name, ordinal number of the record, and unique site ID values. County values were derived and included during data cleaning. StateProvince values were derived and included during data cleaning. Species names were updated according to the GBIF taxonomic backbone during data cleaning. Some field names were modified according to Darwin Core / IPT terms during data cleaning.
代替識別子 | b1c0c801-1758-408d-aebd-777cbc1dfac7 |
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https://doi.org/10.15468/p3sdpu | |
https://bison.usgs.gov/ipt/resource?r=usfws_ruby_lake_nwr_vegetation_mapping_survey |