Data for: The Annual Cycle of Landfast Ice in the Eastern Bering Sea
Large quantities of data were used for this study. Due to the 10gb file limit of Mendely Data, we can only include instructions on how to acquire the SAR imagery, with R and python scripts to complete the remaining steps. The data is uploaded as a compressed file that unzips into a folder. Within th...
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Language: | unknown |
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2020
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Online Access: | http://nbn-resolving.org/urn:nbn:nl:ui:13-9h-lstr https://easy.dans.knaw.nl/ui/datasets/id/easy-dataset:297227 |
Summary: | Large quantities of data were used for this study. Due to the 10gb file limit of Mendely Data, we can only include instructions on how to acquire the SAR imagery, with R and python scripts to complete the remaining steps. The data is uploaded as a compressed file that unzips into a folder. Within the folder there are two subdirectories: “SAR_Imagery” and “Gradient_Analysis”. The SAR_Imagery subdirectory includes python scripts to initiate downloads of Radarsat-1 imagery covering geographic regions within our study area. The download is accomplished via the Alaska Satellite Facility Data Portal; the creation of an account will be required to download this imagery. The Gradient_Analysis subdirectory includes two folders: “Dates” and “Scripts”. The “Dates” folder includes CSV files listing the three dates used in each “triplet”. These CSV files are needed for the execution of the scripts contained in the “Scripts” folder. To run these scripts, you need R-Studio, a free and open-sourced IDE for the R programming language. Step1_Subfolders.R loops through the dates contained within the CSV files in the “Dates Folders”, and deposits the three SAR images in a new subdirectory. Step2_Gradient.R then loops through these subdirectories and performs the net-gradient-difference analysis needed to procure imagery for identifying landfast ice. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE |
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