Replication data for: Mapping oak wilt disease from space using land surface phenology
Data files
Jan 15, 2025 version files 96.34 GB
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HySpex_2018-coregistered.zip
5.60 GB
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HySpex_2021-coregistered.zip
1.16 GB
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NAIP_2019-coregistered_X0014_Y0024.zip
13.58 GB
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NAIP_2019-coregistered_X0015_Y0024.zip
13.26 GB
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NAIP_2019-coregistered_X0016_Y0024.zip
11.98 GB
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NAIP_2019-coregistered_X0016_Y0025.zip
10.01 GB
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NAIP_2019-coregistered_X0016_Y0027.zip
13.09 GB
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NAIP_2019-coregistered_X0017_Y0024.zip
11.99 GB
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NAIP_2019-coregistered_X0017_Y0026.zip
10.53 GB
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NAIP_2019-coregistered_X0017_Y0027.zip
5.13 GB
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Point_pixel-extraction.zip
142.46 KB
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Polygon_crown-delimitation.zip
190.04 KB
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README.md
6.50 KB
Abstract
These datasets are mostly for the replication of the manuscript 'Mapping oak wilt disease from space using land surface phenology'. It is composed of five datasets: pixels extracted from spatial points of healthy, symptomatic, and dead oak tree (i), pixels from polygons delineated on symptomatic oak trees (ii), and high-resolution RGB scenes coregistered to our Sentinel-2 ARD from HySpex sensor on 2018 (iii) and 2021 (iv), and NAIP according to the tiles evaluated (v). Please refer to the manuscript for details on the methods to derive these datasets.
README
This readme.txt file was generated on 2024-12-26 by J. Antonio Guzman Q.
Recommended citation for the data: Please follow the instructions at https://github.com/ASCEND-BII/Oak-wilt_disease
GENERAL INFORMATION
- Title of Dataset
Data for the manuscript 'Mapping oak wilt disease from space using land surface phenology' by Guzman J.A., Pinto-Ledezma J.N., Frantz D., Townsend P.A., Juzwik J. and Cavender-Bares J., 2023. Remote Sensing of Environment, 298, p.113794.'
- Date published or finalized for release:
August 23, 2023
- Date of data collection (single date, range, approximate date):
Observations extracted from pixels between 2018 to 2021.
- Geographic location of data collection (where was data collected?):
Central Minnesota
- Overview of the data (abstract):
Data used to assess the mapping of oak wilt disease from space using Land Surface Phenology. It represents pixels extracted from
points (single trees) and polygons (tree crown extend) to develop classification models and evaluate the effect of crown size on
classification probabilities. Coregistered scenes (i.e., HySpec and NAIP) to satellite observations (Sentinel-2) used to digitize
these points and polygons are also enclosed for reproducibility purposes.
SHARING/ACCESS INFORMATION
- Licenses/restrictions placed on the data: CC0
- Links to publications that cite or use the data: https://github.com/ASCEND-BII/Oak-wilt_disease
DATA & FILE OVERVIEW
- File List
A. Filename: HySpex_2018-coregistered.zip
Description: These are GeoTiff RGB scenes from the 2018 HySpex airborne surveys co-registered to our Sentinel-2 ARD at 5 sites. Each folder name denote a location at central Minnesota. Within each folder a base layer '2016-2022_182-243_HL_TSA_SEN2L_RED_FBY.tif' or 'NAIP_coregister.tif' was used for co-registration. Files within the 'coregistered' folder are GeoTiffs, each of them describing a fly lines. These GeoTiffs files contain pixel values of reflectance, scalled to 1000 for the red, green, and blue bands. These scenes can be opened using QGIS.
B. Filename: NAIP_2019-coregistered_X00_Y00.zip
Description: These are folders that contain GeoTiff RGB scenes from NAIP co-registered to our Sentinel-2 ARD. There are 8 of them (NAIP_2019-coregistered_X0014_Y0024.zip, NAIP_2019-coregistered_X0016_Y0024.zip, NAIP_2019-coregistered_X0015_Y0024.zip, NAIP_2019-coregistered_X0016_Y0025.zip, NAIP_2019-coregistered_X0017_Y0027.zip, NAIP_2019-coregistered_X0017_Y0026.zip, NAIP_2019-coregistered_X0016_Y0027.zip, NAIP_2019-coregistered_X0017_Y0024.zip), each of them describing a unique tile (e.g., X0000_Y0000) following descriptions in Guzman et al. 2023. Within each folder a base layer '2016-2022_182-243_HL_TSA_SEN2L_RED_FBY.tif' was used for co-registration. Files within the 'coregistered' folder are coregistered NAIP GeoTiffs, each of them describing an area of interest. These GeoTiffs files contain pixel values from 0 to 255 for the red, green, and blue bands. These GeoTiffs can be opened using QGIS.
C. Filename: HySpex_2021-coregistered.zip
Description: Description: These are GeoTiffs RGB scenes from the 2021 HySpex airborne survey co-registered to our Sentinel-2 ARD at Cedar Creek, Minnesota. Within the folder base layer '2016-2022_182-243_HL_TSA_SEN2L_RED_FBY.tif' or 'NAIP_coregister.tif' was used for co-registration. Files within the 'coregistered' folder are Geotiffs (e.g., Cedar_XX.tif), each of them describing a fly lines. These Geotiffs files contain pixel values of reflectance, scalled to 1000 for the red, green, and blue bands. These GeoTiffs can be opened using QGIS.
D. Filename: Point_pixel-extraction.zip
Description: Pixels extracted from the coregistered scenes using spatial points of the three oak conditions (Healthy, Symptomatic, and Dead). These tabular data contains 10 columns: 1) title: the tile location of the pixel extracted, 2) ID: a unique pixels ID, 3) Condition: refers to the condition assigned from the photo-interpretation, 4 and 5) Northing and Easting of location of the pixels (EPSG:102004), 6) dataset: refers to the year extraction of the data based on the available datasets, 7) VI: vegetation index (e.i., CCI = Chlorophyll-Carotenoit index). 8) VCV: the z-score of the value of coefficient of variation of the CCI though the growing season, 9) VES: the z-score of the CCI value at the end of the season, and 10) VSS: the z-score of the CCI value at the start of the season.
E. Filename: Polygon_crown-delimitation.zip
Description: A zip folder describing the pixels extracted from the coregistered scenes using spatial polygons from delineated crowns of symptomatic oak trees. In the folder three vector files (X0014_Y0024_polygon.gpkg, X0015_Y0024_polygon.gpkg, X0016_Y0024_polygon.gpkg) from three tiles contain polygons identified with the symptomatic condition. These vector files (e.i., gpkg can be opened using QGIS). In addition, a tabular file 'master_polygon_LSPz-score.csv' with the pixel values extracted using the polygons in enclosed in the folder. This tabular data present 11 columns: 1) title: the tile location of the pixel extracted, 2) ID: a unique polygon ID, 3) Condition: refers to the condition assigned from the photo-interpretation, 4 and 5) Northing and Easting of location of the pixels (EPSG:102004), 6) area: refers to area of the polygon, 7) fraction: refers to how much area of the pixel is covered by the polygon, 8) VI: vegetation index (e.i., CCI = Chlorophyll-Carotenoit index), 9) VCV: the z-score of the value of coefficient of variation of the CCI though the growing season, 10) VES: the z-score of the CCI value at the end of the season, and 11) VSS: the z-score of the CCI value at the start of the season.
Relationship between files: The digitization of the location of the files D and E derives from files A, B, and C.
METHODOLOGICAL INFORMATION
- Description of methods used for collection/generation of data:
Point or crown delineation using QGIS, see details in the manuscript.
- Instrument- or software-specific information needed to interpret the data:
Please use a GIS software (e.g., QGIS or ArcGIS)
- Standards and calibration information, if appropriate:
In all the instances our spatial that is projected to USA Contiguous Lambert projection (EPSG:102004).
Usage notes
Any GIS software (QGIS or ArcGIS)