Publications

Lu, YL; Horton, R; Zhang, X; Ren, TS (2018). Accounting for soil porosity improves a thermal inertia model for estimating surface soil water content. REMOTE SENSING OF ENVIRONMENT, 212, 79-89.

Abstract
Soil thermal inertia (P), a property that controls the temporal variation of near-surface temperature, has been used to estimate surface water content (theta) in remote sensing studies. The accuracy of theta estimates, however, is affected by surface soil porosity (n). We hypothesize that n can be derived using a simple linear n-P relationship of a dry surface soil layer, and that accounting for n improves the accuracy of theta estimation using a P(theta) model. The P of a surface layer was measured by using the heat pulse method during a drying period, and the feasibility of estimating theta with a P(theta) model that included n was explored. The approach was also tested with published P values derived from meteorological data and MODIS data against in situ theta measurements at two field sites in Arizona, USA. The results on a partially vegetated shrubland indicated that by using the P-derived n, the P(theta) model provided more accurate theta estimates than by using the literature n values. Discrepancies between modeled theta and in situ theta measurements were observed at small theta values, which were caused in part by the fact that the modeled theta represented soil layers a few millimeters thick, while the in situ measurements represented theta at the 5 cm depth. The new n-P function has potential for estimating surface theta accurately using multi-scale P data on bare soils or on sparsely vegetated lands.

DOI:
10.1016/j.rse.2018.04.045

ISSN:
0034-4257