A cloud-free MODIS snow cover dataset for the contiguous United States from 2000 to 2017

Abstract

This article presents a cloud-free snow cover dataset with a daily temporal resolution and 0.05° spatial resolution from March 2000 to February 2017 over the contiguous United States (CONUS). The dataset was developed by completely removing clouds from the original NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow Cover Area product (MOD10C1) through a series of spatiotemporal filters followed by the Variational Interpolation (VI) algorithm; the filters and VI algorithm were evaluated using bootstrapping test. The dataset was validated over the period with the Landsat 7 ETM+ snow cover maps in the Seattle, Minneapolis, Rocky Mountains, and Sierra Nevada regions. The resulting cloud-free snow cover captured accurately dynamic changes of snow throughout the period in terms of Probability of Detection (POD) and False Alarm Ratio (FAR) with average values of 0.955 and 0.179 for POD and FAR, respectively. The dataset provides continuous inputs of snow cover area for hydrologic studies for almost two decades. The VI algorithm can be applied in other regions given that a proper validation can be performed.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jan 15, 2019
Source ID
10.1038/sdata.2018.300

Entities

People

  • Hoang Tran
  • Kuo-lin Hsu
  • Mohammed Ombadi
  • Phu Nguyen
  • Qing Xia
  • Soroosh Sorooshian

Tags

Fields of Study

  • Environmental science

Readers

  • Business Analytics
  • Computer Vision.