Classification of Alaska spring thaw characteristics using satellite L-band radar remote sensing

Jinyang Du, John S. Kimball, Marzieh Azarderakhsh, R. Scott Dunbar, Mahta Moghaddam, Kyle C. McDonald

Research output: Contribution to journalArticlepeer-review

Abstract

Spatial and temporal variability in landscape freeze-thaw (FT) status at higher latitudes and elevations significantly impacts land surface water mobility and surface energy partitioning, with major consequences for regional climate, hydrological, ecological, and biogeochemical processes. With the development of new-generation spaceborne remote sensing instruments, future L-band missions, including the NASA Soil Moisture Active and Passive mission, will provide new operational retrievals of landscape FT state dynamics at moderate (∼3 km) spatial resolution. We applied theoretical simulations of L-band radar backscatter using first-order radiative transfer models with twoand three-layer modeling schemes to develop a modified seasonal threshold algorithm (STA) and FT classification study over Alaska using 100-m-resolution satellite Phased Array L-band Synthetic Aperture Radar (PALSAR) observations. The backscatter threshold distinguishes between frozen and nonfrozen states, and it is used to classify the predominant frozen or thawed status of a grid cell. An Alaska FT map for April 2007 was generated from PALSAR (ScanSAR) observations and showed a regionally consistent but finer FT spatial pattern than an alternative surface air temperature-based classification derived from global reanalysis data. Validation of the STA-based FT classification against regional soil climate stations indicated approximately 80% and 75% spatial classification accuracy values in relation to respective station air temperature and soil temperature measurement-based FT estimates. An investigation of relative spatial scale effects on FT classification accuracy indicates that the relationship between grid cell size and classified frozen or thawed area follows a general logarithmic function.

Original languageEnglish
Article number2325409
Pages (from-to)542-556
Number of pages15
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume53
Issue number1
DOIs
StatePublished - Jan 2015

Keywords

  • Alaska
  • Freeze-thaw (FT)
  • Microwave scattering model
  • Modern Era Retrospective Analysis for Research and Applications (MERRA)
  • Phased Array L-band Synthetic Aperture Radar (PALSAR)
  • Soil Moisture Active and Passive (SMAP)

Fingerprint

Dive into the research topics of 'Classification of Alaska spring thaw characteristics using satellite L-band radar remote sensing'. Together they form a unique fingerprint.

Cite this