five

NASA SPoRT Dust Event Labels

收藏
NIAID Data Ecosystem2026-03-12 收录
下载链接:
https://zenodo.org/record/4627951
下载链接
链接失效反馈
官方服务:
资源简介:
GENERAL INFORMATION 1. Title of Dataset: SPoRT Dust Event Labels 2. Author Information:   A. Nicholas Elmer       NASA Postdoctoral Program       NASA Marshall Space Flight Center       Huntsville, Alabama, USA       nicholas.j.elmer@nasa.gov    B. Emily Berndt        Earth Science Office        NASA Marshall Space Flight Center        Huntsville, Alabama, USA        emily.b.berndt@nasa.gov 3. Date of data collection: 2018-01-14 to 2020-06-09 4. Geographic location of data collection: Southwest United States    West longitude: 126.0 W    East longitude:  90.0 W    South latitude:  24.0 N    North latitude:  45.0 N 5. Funding source:     Data collection was supported by the NASA Short-term Prediction Research and Transition (SPoRT)    project at NASA Marshall Space Flight Center.    DATA & FILE OVERVIEW 1. File List:    testing_dataset.txt    training_dataset.txt    validation_dataset.txt    Georeferenced polygon shapefiles, comprising .shp, .shx, .dbf, and .prj files with timestamp {YYYY}{MM}{DD}T{HH}{MM}{SS}. 2. Relationship between files:    This dataset contains:    1) Georeferenced (WGS 1984) polygon shapefiles containing image classification for airborne dust.    2) Text files listing the timestamp of shapefiles used in the training, testing, and validation datasets       used by the Berndt et al. (2021) random forest dust detection model. METHODOLOGICAL INFORMATION. 1. Description of methods for collection:    The dust labels were manually assigned by atmospheric scientists based largely on the GOES-16 ABI Dust RGB imagery but    supplemented by GOES-16 true color imagery, Area Forecast Discussions issued by NOAA National Weather Service    Weather Forecast Offices, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)    measurements. 2. Methods for processing the data:    GOES-16 ABI Dust RGB imagery was downloaded from Amazon Web Services and regridded to a 2-km rectangular grid. Feature labels were manually drawn on the imagery and classified by experts with the aid of a Python Graphical User Interface (GUI) based on the Tkinter python package. DATA-SPECIFIC INFORMATION FOR SHAPEFILES: 1. Shapefile coordinate system: WGS 1984 2. Number of Shapefiles: 83 3. Number of Polygons per Shapefile: Varies 4. Number of Attributes per polygon: 1 5. Attribute list:    A. Class: 0 --> No Dust              1 --> Dust              2 --> Reserved for future use              3 --> No Data Value
创建时间:
2021-04-01
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作