Soil moisture assessments for brown locust Locustana pardalina breeding potential using synthetic aperture radar

WT Crooks, RA Cheke

Research output: Contribution to journalArticle

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Abstract

Synthetic aperture radar (SAR) imagery was collected over a brown locust Locustana pardalina outbreak area to estimate soil moisture relevant to egg development. ERS-2/RadarSat overpasses and field studies enabled parameterization of surface roughness, volumetric soil moisture, soil texture, and vegetation cover. Data were analyzed both when the target area was assessed as nonvegetated and when treated as vegetated. For the former, using the integral equation model (IEM) and soil surface data combined with the sensitivity of the IEM to changes in surface roughness introduced an error of ~ ± 0.06 cm3 cm-3 in volumetric soil moisture. Comparison of the IEM modeling results with backscatter responses from the ERS-2/RadarSat imagery revealed errors as high as ±0.14 cm3 cm-3, mostly due to IEM calibration problems and the impact of vegetation. Two modified versions of the water cloud model (WCM) were parameterized, one based on measurements of vegetation moisture and the other on vegetation biomass. A sensitivity analysis of the resulting model revealed a positive relationship between increases in both vegetation biomass and vegetation moisture and the backscatter responses from the ERS-2 and RadarSat sensors. The WCM was able to explain up to 80% of the variability found when the IEM was used alone. © The Authors.
Original languageEnglish
Article number084898
JournalJournal of Applied Remote Sensing
Volume8
Issue number1
DOIs
Publication statusPrint publication - Mar 2014
Externally publishedYes

Keywords

  • Brown locust
  • Egg development
  • Integral equation model
  • Locustana pardalina
  • Soil moisture
  • Surface roughness
  • Synthetic aperture radar
  • Vegetation
  • Water cloud model

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