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In a second step, a stepwise forward regression using sample surface properties was performed to find explanatory variables for surface heat production. The spatial information of the hot spots was described using geostatistical semivariance. The characterization of hot moments was performed using a Gaussian curve fit. In a first step, surface temperature dynamics were characterized using mathematical and geostatistical methods concerning microbial hot spots and hot moments.
![preparation of undisturbed soil sample for test preparation of undisturbed soil sample for test](https://image2.slideserve.com/3863425/triaxial-shear-test-l.jpg)
Soil sample surface characterization was done by using active IRT for soil moisture approximation and surface structure, digital photography to estimate soil organic carbon (SOC) contents from soil color parameters, and zymography to get an indicator of initial microbial activity. The soil samples were incubated for five days during passive IRT measurements under controlled ambient conditions with a relative air humidity >95% and constant ambient air temperature of 20 ☌. The soil sample surface temperature was measured at 10-minute intervals and a spatial resolution of 0.17 mm per pixel. In this study, undisturbed top- and subsoils samples from two forest sites were used in a substrate-induced approach to capture surface heat production using passive IRT with homogeneously applied glucose and water. The technique has only been used on homogenized disturbed samples to characterize the in-situ heterogeneity of heat development.
![preparation of undisturbed soil sample for test preparation of undisturbed soil sample for test](https://uta.pressbooks.pub/app/uploads/sites/111/2020/11/ch-11-img-8.png)
Passive infrared thermography (IRT) has already been applied in several approaches for high-resolution and non-contact imaging of microbial hot spots and hot moments on soil sample surfaces.