Abstract
Abstract. The objective of this analysis is to provide a quantitative estimate of the fluctuations of land surface temperature (LST) with varying near surface soil moisture (SM) on different land-cover (LC) types. The study area is located in the Canterbury Plains in the South Island of New Zealand. Time series of LST from the MODerate resolution Imaging Spectro-radiometer (MODIS) have been analysed statistically to study the relationship between the surface skin temperature and near-surface SM. In-situ measurements of the skin temperature and surface SM with a quasi-experimental design over multiple LC types are used for validation. Correlations between MODIS LST and in-situ SM, as well as in-situ surface temperature and SM are calculated. The in-situ measurements and MODIS data are collected from various LC types. Pearson’s r correlation coefficient and linear regression are used to fit the MODIS LST and surface skin temperature with near-surface SM. There was no significant correlation between time-series of MODIS LST and near-surface SM from the initial analysis, however, careful analysis of the data showed significant correlation between the two parameters. Night-time series of the in-situ surface temperature and SM from a 12 hour period over Irrigated-Crop, Mixed-Grass, Forest, Barren and Open- Grass showed inverse correlations of -0.47, -0.68, -0.74, -0.88 and -0.93, respectively. These results indicated that the relationship between near-surface SM and LST in short-terms (12 to 24 hours) is strong, however, remotely sensed LST with higher temporal resolution is required to establish this relationship in such time-scales. This method can be used to study near-surface SM using more frequent LST observations from a geostationary satellite over the study area.
Highlights
Near surface soil moisture (SM), defined as the water content of the upper 10 cm of the soil (Wang and Qu, 2009), is measured by remote sensing satellites using the electromagnetic radiation in three distinct ranges: the visible and near-infrared region, thermal region and the microwave region
Apart from the visual comparison, statistical analysis of the correlations between the two parameters was necessary to ensure if any longterm relationship exists between land surface temperature (LST) and SM in the area, which is discussed
Lack of continuous observations for a day from the MODerate resolution Imaging Spectro-radiometer (MODIS) product restricted a diurnal analysis using this dataset, only in-situ data were used for a single day
Summary
Near surface soil moisture (SM), defined as the water content of the upper 10 cm of the soil (Wang and Qu, 2009), is measured by remote sensing satellites using the electromagnetic radiation in three distinct ranges: the visible and near-infrared region, thermal region and the microwave region. Other works have used a combination of optical, thermal and microwave remote sensing data (Wang et al, 2004, Hassan et al, 2007, Gruhier et al, 2010, Hain et al, 2011). More complex methods such as the Soil-Vegetation-Atmosphere-Transfer (SVAT) model (Carlson et al, 1994) exploit combination of the remotely sensed data to establish a relationship between surface SM, surface temperature and vegetation cover. Considering the objective of the current research, thermal remote sensing algorithms are of interest in this paper
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