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Proceedings Paper

Soil water content assessment: seasonal effects on the triangle method
Author(s): A. Maltese; F. Capodici; G. Ciraolo; G. La Loggia; C. Cammalleri
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Paper Abstract

Among indirect estimations of the soil water content in the upper layer, the "triangle method" is based on the relationship between the optical and thermal features sensed via Earth Observation. These features are controlled by water content at surface and within root zone, but also by meteorological forcing including air temperature and humidity, and solar radiation. Night and day-time MODIS composite land-surface temperature (LST) allowed applying the thermal admittance version of the method; by taking into account the temporal admittance of the soil, this version was previously found achieving high accuracy in estimate the soil water content at high spatial resolution within a short time period (a single irrigation season). In this study, the method has been applied on a long time series to analyse the seasonal influence of the meteorological forcing on the triangle method index (or temperature vegetation index, TVX). The Imera Meridionale hydrological basin (≈ 2000 km2, Sicily) has been chosen to test the method over a decade time series, since its climate varies during the year from arid to temperate. The climate is arid for ≈3-7 months (from April-May to August- October) depending on altitude. The temporal analysis reveals that NDVI and LST pairs moves circularly within the optical and thermal diachronic feature space. Concordantly, the boundaries of the triangle move during the seasons. Results suggest that the contribution of soil water content fluctuations need to be isolated from other environmental stress factors, or at least, the conceptual meaning of TVX have to be better interpreted.

Paper Details

Date Published: 25 October 2016
PDF: 11 pages
Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99980F (25 October 2016); doi: 10.1117/12.2246801
Show Author Affiliations
A. Maltese, Univ. of Palermo (Italy)
F. Capodici, Univ. of Palermo (Italy)
G. Ciraolo, Univ. of Palermo (Italy)
G. La Loggia, Univ. of Palermo (Italy)
C. Cammalleri, European Commission Joint Research Ctr. (Italy)

Published in SPIE Proceedings Vol. 9998:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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