customSoftware | description | Google Earth Engine (GEE) is a web-based scripting program that can be used for various remote sensing analyses. |
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source | https://earthengine.google.com/ |
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webToolMaintenanceAndSupport | Not applicable – the program is managed by Google. |
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languages | Java |
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restrictions | There are no restrictions on access to or use of Google Earth Engine. However, the user must register for an account prior to use. |
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environment | Microsoft Edge on Windows |
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name | Coding in Google Earth Engine (GEE) |
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description | R software is a public and free scripting program and language. R is used for a wide variety of statistical analyses, database management, as well as graphing applications. |
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source | https://www.r-project.org/about.html |
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webToolMaintenanceAndSupport | Not applicable – the program is managed by Google. |
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languages | R |
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restrictions | There are no restrictions on access to or use of R. |
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environment | Windows |
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name | Coding in R Software |
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dataProduct | metadata | A metadata product will not be produced for the report as this report will remain internal. |
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exclusiveUse | To protect the cultural resources and highly detailed spatial properties discussed in the report, this document will not be released publicly. This data is sensitive and, in respect to Tribal cultural traditions, will be available only to the Tribal members. |
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description | We are providing a report of the findings necessary to assist the San Carlos Apache Tribe in detailing restoration priorities and goals. This report is structured to provide an overview of the data products produced in this project and help inform the Tribe in the development of their restoration plan. |
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repository | This product will not be stored in a public repository. |
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dataLifespan | 50+ years |
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qualityChecks | The report will be thoroughly reviewed before being released. |
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citation | There will be no formal citation for this product. |
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format | The report is being provided to the San Carlos Apache Tribe as both a virtual Microsoft Word document as well as a hardcopy. |
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restrictions | This report will likely include sensitive data and will not be released publicly. |
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backupAndStorage | The products will be stored on a U.S. Geological Survey data server. |
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dataManagementResources | The production of the report detailing research results for restoration priorities represents roughly 20% of proposal resources allocated. |
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volumeEstimate | The estimated volume of these products should be less than 1 GB. |
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dataProcessing | We will review the overall results from the study and write a report that provides an overview of the specific results that can be used by the Tribe to inform their restoration priorities and goals. |
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name | Report of Findings for Restoration Priorities |
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doi | There will be no formal Digital Object Identifier for this product. |
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metadata | A metadata product will not be produced for the manuscript. However, metadata products and formal data releases associated with this project will be cited in the manuscript. |
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exclusiveUse | This manuscript will be made available at the end of the project. |
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description | We are publishing a professional manuscript detailing the research methodology and results for this study within the San Carlos Apache Reservation and the larger Upper Gila River watershed. Information identified as sensitive by the San Carlos Apache Tribe will not be included. The manuscript will be peer-reviewed using the U.S. Geological Survey internal system and submitted to a professional journal. |
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repository | The final manuscript will be stored by the publishing journal. |
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dataLifespan | 50+ years |
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qualityChecks | The final manuscript will be reviewed multiple times, including by the co-authors, a formal peer review conducted by the U.S. Geological Survey, as well as a formal review through an independent process established by the publishing journal. Finally, a U.S. Geological Survey approving official must sign off on the final manuscript before it can be released for publication. |
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citation | A formal citation will be determined at the time of the publication of the manuscript |
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format | The submitted manuscript will be a Microsoft Word document and will be published as a PDF. |
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restrictions | There are no restrictions in the usage of this manuscript. |
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backupAndStorage | The final submitted manuscript and related files and documents will be stored on a U.S. Geological Survey data server. |
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dataManagementResources | The development of the professional manuscript will represent roughly 20% of proposal resources allocated. |
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volumeEstimate | The estimated volume of these products should be less than 1 GB. |
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dataProcessing | The manuscript will detail the overall results determined in this study as well as provide an overview of the methodology that was used. We will write the manuscript at the end of the study. |
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name | Published Manuscript |
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doi | A formal Digital Object Identifier (DOI) will be determined at the time of the publication of the manuscript. |
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existingInput | fees | No additional fees are associated with obtaining the data. |
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description | The U.S. Geological Survey supports a national network of stream gages. Various data products, including temperature, gage height, discharge, and water quality characteristics, are typically collected at 15- to 60-minute intervals at each gage, depending on the gage. The data products can be downloaded on a daily time scale for selected gages in a tabular format. For gages located along the Gila River and its main tributaries – within our study area, daily data is available beginning in the 1920’s to present, |
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source | The U.S. Geological Survey. |
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qualityChecks | Quality checks of the stream gage data were completed by the source. |
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citation | USGS. (2021). USGS Current Water Data for the Nation. https://waterdata.usgs.gov/nwis/rt |
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format | The data is downloaded in a tabular format (i.e. text, CSV, or DBF). |
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restrictions | The stream age data is available to the public. There are no restrictions on access or reuse of this data. |
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backupAndStorage | The stream gage datasets are stored on a portable hard drive. The datasets are also backed up on the U.S. Geological Survey servers. |
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volumeEstimate | The combined size of the tabular data is small, likely less than 1 GB. |
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dataProcessing | The stream gage data has already been collected by the WGSC. We will extract data products from public stream gage datasets collected at locations along the San Carlos and Gila Rivers. The primary gages, identified by gage site number, we will consider are as follows: i) the Gila River: 9430500, 9432000, 9442000, 9448500, and 9455600, and ii) the San Carlos River: 9458600. All gages provide daily discharge in cubic feet per second (cfs). We intend to use R software to extract discharge data by date ranges and analyze the data. |
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name | U.S. Geological Survey Stream Gage Data |
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fees | No additional fees are associated with obtaining the data. |
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description | Google Earth Engine (GEE) is a web-based cloud computing application that is publicly available for remote sensing analyses. Many satellite imagery collections are stored in the GEE Data Catalog, including the Landsat series which has a temporal resolution of 16-days from 1984 to present and a spatial resolution of 30-m. Users can develop scripts, based on the language of Java, to extract various information from the satellite imagery, including vegetation indices derived using band combinations as well as more complex image properties. The data is spatially explicit and is actively available. |
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source | The Google Earth Engine (GEE) Data Catalog. |
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qualityChecks | Quality checks of the imagery were completed by the source. |
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citation | Landsat – NASA. (2021). Landsat Science. https://landsat.gsfc.nasa.gov/
GEE Data Catalog – Google Earth Engine. (2021). Datasets Tagged Highres in Earth Engine. https://developers.google.com/earth-engine/datasets/tags/highres |
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format | Not applicable – all the imagery is held by Google. |
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restrictions | The imagery is available to the public. There are no restrictions on access or reuse of this imagery. |
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backupAndStorage | Not applicable – all the imagery is held by Google. |
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volumeEstimate | Not applicable – all the imagery is held by Google. |
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dataProcessing | We will be using the publicly available satellite imagery in GEE, including the Landsat series, to derive vegetation characteristics. We will write scripts in GEE to develop indices including the Normalized Difference Vegetation Index (NDVI) and the multi-band Tasseled Cap Transformation. Each of these derived image products uses bands that are available in the Landsat series. |
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name | Public Satellite Imagery Available in the Google Earth Engine Data Catalog |
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fees | No additional fees are associated with obtaining the data. |
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description | Google Earth Engine (GEE) is a web-based cloud computing application that is publicly available for remote sensing analyses. Climate data collections are stored in the GEE Data Catalog, including the GRIDMET Drought collection, with a 5-day temporal resolution from 1984 to present and a spatial resolution of 4-km. The GRIDMET Drought product has continuous and spatially explicit drought index data. Users of GEE can develop scripts, based on the language of Java, to extract various information from the GRIDMET Drought data. The data is spatially explicit and is actively available. |
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source | The Google Earth Engine (GEE) Data Catalog. |
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qualityChecks | Quality checks of the imagery were completed by the source. |
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citation | GRIDMET Drought – GRIDMET DROUGHT: CONUS Drought Indices. (2022). Earth Engine Data Catalog. Available at: https://developers.google.com/earth-engine/datasets/catalog/GRIDMET_DROUGHT#description.
GEE Data Catalog – Google Earth Engine. (2021). Datasets Tagged Highres in Earth Engine. https://developers.google.com/earth-engine/datasets/tags/highres
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format | Not applicable – all the imagery is held by Google. |
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restrictions | The imagery is available to the public. There are no restrictions on access or reuse of this imagery. |
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backupAndStorage | Not applicable – all the imagery is held by Google. |
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volumeEstimate | Not applicable – all the imagery is held by Google. |
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dataProcessing | We will be using the publicly available climate data in GEE. We will write scripts in GEE to extract precipitation and temperature data for specific areas across defined time intervals. We will extract images and tabular datasets from GEE. |
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name | Public Climate Data Available in the Google Earth Engine Data Catalog |
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fees | No additional fees are associated with obtaining the data. |
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description | The National Agriculture Imaging Program (NAIP) of the U.S. Department of Agriculture has collected high-resolution aerial imagery across the United States for public use since 2003. Recent NAIP imagery has a spatial resolution of 0.6 meters. The imagery has four bands, including the three visible bands, i) Red, ii) Green, iii) Blue (i.e., combined RGB), and iv) a Near Infrared band. For the state of Arizona, NAIP imagery for a single date in 2019 and 2021 has been obtained by the Western Geographic Science Center (WGSC). For the state of New Mexico, NAIP imagery was collected in 2020 and has been obtained by the WGSC. Multiple scenes are required because NAIP imagery is provided at either a county-wide or scene-wide level. |
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source | The U.S. Department of Agriculture. |
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qualityChecks | Quality checks of the imagery were completed by the source. |
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citation | USDA. (2021). NAIP Imagery. https://www.fsa.usda.gov/programs-and-services/aerial-photography/imagery-programs/naip-imagery/ |
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format | The images are GeoTIFFs. |
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restrictions | The imagery is available to the public. There are no restrictions on access or reuse of this imagery. |
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backupAndStorage | The images are stored on a portable hard drive. The images are also backed up on the U.S. Geological Survey servers. |
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volumeEstimate | The NAIP images for Arizona and New Mexico are roughly 50 GB. |
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dataProcessing | The data will not be manipulated from the original form. |
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name | 2019/2020/2021 National Agriculture Imaging Program (NAIP) Aerial Imagery |
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fees | No additional fees are associated with obtaining the data. |
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description | Aerial imagery for 1935 was acquired by Fairchild Inc. for the Soil Conservation Service in locations across Arizona and New Mexico. The U.S. Geological Survey Western Geographic Science Center has since obtained the scans of the images for the Upper Gila River Hydrologic Unit Code (HUC) Level 4 watershed, divided into 44 image quads. The scans have been georeferenced and mosaicked into separate images for Arizona and New Mexico. The images are single band images and are black and white. For the imagery from both states, the spatial resolution is sub-3-m, at roughly 2.7-m. |
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source | The U.S. Geological Survey Western Geographic Science Center. |
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qualityChecks | Formal quality check will be completed to ensure high data quality. |
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citation | These images are not publicly available. Therefore, no citation currently exists. |
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format | The images are TIFFs. |
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restrictions | There are no restrictions to accessing the imagery because of the partnership with the U.S. Geological Survey Western Geographic Science Center. |
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backupAndStorage | The images are stored on a USGS portable hard drive. The images are also backed up on the U.S. Geological Survey servers. |
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volumeEstimate | The volume of information that will be generated is estimated be less than 10 GB. Each image quad is approximately 50 MB. |
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dataProcessing | The imagery that was collected by the Western Geographic Science Center required initial processing for use in this study. The following steps were applied to process the images that will be used for analysis – for both the Arizona and New Mexico images. First, the original images were georeferenced to define a spatial projection using a 1st Order Polynomial approach with high resolution imagery. Second, we clipped the georeferenced images to a 10-km buffer surrounding the Gila River and selected main tributaries in order to remove areas that will not be considered in this study. Third, we completed a secondary georeferencing process, using a 2nd Order Polynomial approach, for the clipped images to better ensure the quality of the product. Finally, a different team member reviewed the overall georeferencing process and appended points, when necessary, to produce a final image that will be used in the analysis. |
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name | 1935 Aerial Imagery |
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history | 2023-02-03 13:03:57 MST: phase Approved DMP
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newInput | metadata | Formal FGDC compliant metadata will be produced for the data products and released. |
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exclusiveUse | These products will be made available to the Tribe at the end of the project to evaluate their release. |
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description | This data collection will consist of maps depicting the changes that occurred within the riparian vegetation and river channel between 1935 and 2021. The maps will visualize specific spatially explicit changes that occurred, including changes in the location of the floodplain, river channel, and vegetated areas, among others. |
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repository | The U.S. Geological Survey digital repository, ScienceBase, will serve as the repository for public release of this data. |
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dataLifespan | 50+ years |
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qualityChecks | Formal quality check will be completed to ensure high data quality. |
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protocols | We plan follow the protocols developed in Petrakis et al. (2017) – see the Data Processing & Scientific Workflows section for citation. |
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citation | A formal citation will be determined at the time of the data release. |
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format | Highly detailed maps of the Upper Gila Watershed will be released, where available, in various formats including raster images (i.e. IMG, GeoTIFF), vector products (i.e. KML, shapefile), and formal map documents (i.e. PDF). |
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restrictions | There are no restrictions in the usage of this data by the USGS. |
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backupAndStorage | The products will be stored on a U.S. Geological Survey data server. |
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dataManagementResources | The production of the maps showing changes in the riparian vegetation and river channel properties between 1935 and 2021 represents roughly 5% of proposal resources allocated. |
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volumeEstimate | The estimated volume of these products should be less than 5 GB. |
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dataProcessing | The map products will be developed by differencing the two classifications using a similar protocol used to document changes in the vegetation and river channel properties along the Middle Rio Grande in New Mexico in Petrakis et al. (2017).
Petrakis, R. E., van Leeuwen, W., Villarreal, M. L., Tashjian, P., Dello Russo, R., & Scott, C. (2017). Historical Analysis of Riparian Vegetation Change in Response to Shifting Management Objectives on the Middle Rio Grande. Land, 6(2), 29. https://doi.org/10.3390/land6020029. |
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name | Maps of Changes in Riparian Floodplain and River Channel Structural Properties |
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doi | A formal Digital Object Identifier (DOI) will be determined at the time of the data release. |
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metadata | Formal FGDC compliant metadata will be produced for the data products and released. |
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exclusiveUse | These products will be made available at the end of the project. |
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description | To draw conclusions between climate and the vegetation properties, we first used the climate data to produce a series of climate periods. Using those periods as constraints, we developed a geospatial database that consists of data products showing the trends in the vegetation properties. The trends in the vegetation properties will be primarily defined by satellite measured greenness, wetness, and brightness from 1985 through 2021 using the Normalized Difference Vegetation Index and the Tasseled Cap Transformation metrics. Multi-temporal trends were developed for identified vegetation types or locations for the study area. The climate data is available from 1980 to present-day and is measured at a watershed scale. |
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repository | The U.S. Geological Survey digital repository, ScienceBase, will serve as the repository for public release of this data. |
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dataLifespan | 50+ years |
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qualityChecks | Formal quality check will be completed to ensure high data quality. |
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citation | A formal citation will be determined at the time of the data release. |
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format | The database will primarily consist of various formats including raster images (i.e., TIFF), tables (i.e., CSV), text metadata documents (i.e., TXT), where available. |
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restrictions | There are no restrictions in the usage of this data. |
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backupAndStorage | The products will be stored on a U.S. Geological Survey data server. |
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dataManagementResources | The development of the geospatial database consisting of the trends in vegetation properties and climate adaptation variables will represent roughly 40% of proposal resources allocated. |
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volumeEstimate | The estimated volume of these products should be less than 5 GB. |
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dataProcessing | The trend products will be developed using Google Earth Engine (GEE) and R software programs. In GEE, time-series and trends of vegetation properties can be quantified using satellite imagery and limited to various spatial scales or areas – which were determined based on the development of prior products. Similarly, GEE was used to determine time-series and trends of the climate variables, which are held in the GEE data catalog. R was used to determine time-series and trends of the climate variables. |
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name | Database of Trends in Vegetation Properties and Climate Adaptation Variables |
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doi | A formal Digital Object Identifier (DOI) will be determined at the time of the data release. |
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metadata | Formal FGDC compliant metadata will be produced for the data products and released. |
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exclusiveUse | These products will be made available to the Tribe at the end of the project to evaluate their release. |
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description | This data collection consists of maps of the San Carlos Apache Reservation and larger Upper Gila River watershed. We include separate products (i.e., spatial layers, maps) detailing the riparian vegetation and river channel structural profile for both 1935 and 2021. The products will show the full extent of the floodplain across our study site. The temporal scope of each product is one year. The geographic scope is the primary riparian areas along the San Carlos and Gila Rivers within the Upper Gila River Watershed. |
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repository | The U.S. Geological Survey digital repository, ScienceBase, will serve as the repository for public release of this data. |
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dataLifespan | 50+ years |
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qualityChecks | Formal quality check will be completed to ensure high data quality. |
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citation | A formal citation will be determined at the time of the data release. |
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format | Highly detailed products of the Upper Gila Watershed will be released, where available, in various formats including raster images (i.e. IMG, TIFF), vector products (i.e. KML, shapefile), and formal map documents (i.e. PDF). |
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restrictions | There are no restrictions in the usage of this data by the USGS. |
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backupAndStorage | The products will be stored on a U.S. Geological Survey data server. |
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dataManagementResources | The production of the 1935 and 2021 riparian vegetation and river channel classifications will represent roughly 15% of proposal resources allocated. |
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volumeEstimate | The estimated volume of these products should be less than 5 GB. |
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dataProcessing | The 1935 and 2021 riparian vegetation and river channel maps will be developed using the 1935 aerial photography and 2019-2021 NAIP imagery, respectively. To develop the structural profiles, we plan to perform image analysis using Adobe Photoshop and ESRI ArcGIS to delineate vegetation and other structural traits. |
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name | 1935 and 2021 Riparian Floodplain and River Channel Structural Profile |
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doi | A formal Digital Object Identifier (DOI) will be determined at the time of the data release. |
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phase | Approved DMP |
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templateName | CASC DMP v4 |
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