IGARSS 2018  2018 IEEE International Geoscience and Remote Sensing Symposium
 Anthology ID:
 G1815
 Month:
 Year:
 2018
 Address:
 Venue:
 GWF
 SIG:
 Publisher:
 IEEE
 URL:
 https://gwfuwaterloo.github.io/gwfpublications/G1815
 DOI:
Contributions of Geophysical and CBand SAR Data for Estimation of Field Scale Soil Moisture
Aaron Berg

Mitchell Krafczek

Daniel Clewley

J. Whitcomb

Ruzbeh Akbar

Mahta Moghaddam

Heather McNarin
In this study we evaluate a Random Forest (RF) model for characterizing the spatial variability of soil moisture based on model derived from in situ soil moisture samples, geophysical data and RADAR observations. The RF model is run with and without Cband SAR backscatter to understand the importance of the inclusion of SAR data for mapping of soil moisture at field scale. The inclusion of SAR data in the RF resulted in a modest improvement however the geophysical parameters (e.g. soil types and terrain properties) were of greater importance.
Application of Photon Recollision Probability Theory for Compatibility Check Between Foliage Clumping and Leaf Area Index Products Obtained from Earth Observation Data
Jan Písek

Henning Buddenbaum

Fernando Camacho

Joachim Hill

Jennifer Jensen

Holger Lange

Zhili Liu

Arndt Piayda

Yonghua Qu

Olivier Roupsard

Shawn Serbin

Svein Solberg

Oliver Sonnentag

Anne Thimonier

Francesco Vuolo
Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given value of leaf area index (LAI). Both the CI and LAI can be obtained from global Earth Observing (EO) systems such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the compatibility between CI and LAI products derived from EO data is examined independently using the theory of spectral invariants, also referred to as photon recollision probability theory (i.e. ‘ $p$ theory’), along with raw LAI2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types (PFTs). The $p$ theory describes the probability (pvalue) that a photon, having intercepted an element in the canopy, will recollide with another canopy element rather than escape the canopy. Our results indicate that the integration of empiricallybased CI maps with the MODIS LAI product is feasible, providing a potential means to improve the accuracy of LAI EO data products. Given the strong results for the large range of PFTs explored here, we demonstrate the capacity to obtain pvalues for any location solely from EO data. This is relevant for future applications of the photon recollision probability concept for global and local monitoring of vegetation using EO data.