A computer-implemented method of monitoring a physical environmental property that has non-stationary heteroscedastic noise, the method comprising: a processor receiving physical environmental measurement data comprising measured values of: a dependent variable which represents the physical environmental property; and at least one independent variable with which the physical environmental property is correlated; wherein the processor receiving the physical environmental measurement data comprises, for the measured values of the at least one independent variable, the processor receiving measurement signals transmitted by one or more remote sensors disposed in the environment or by an associated remote data logger disposed in proximity to and in communication with the remote sensors; the method characterized by: the processor constructing a combined input and output noise levels matrix containing output noise terms associated with the physical environmental property and input noise terms associated with the at least one independent variable with which the physical environmental property is correlated; using the combined input and output noise levels matrix, the processor constructing a main Gaussian Processes model that models the physical environmental property and its non-stationary heteroscedastic noise; and the processor co-operating with an output device to generate and perceptibly output a predictive probabilistic representation of the environmental property, using the main GP model, wherein the predictive probabilistic representation comprises a respective range of possible values of the physical environmental property for each respective value of the at least one independent variable, the range of possible values reflecting both the input noise terms associated with the independent variable and the output noise terms associated with the physical environmental property. a processor receiving physical environmental measurement data comprising measured values of: a dependent variable which represents the physical environmental property; and at least one independent variable with which the physical environmental property is correlated; a dependent variable which represents the physical environmental property; and at least one independent variable with which the physical environmental property is correlated; wherein the processor receiving the physical environmental measurement data comprises, for the measured values of the at least one independent variable, the processor receiving measurement signals transmitted by one or more remote sensors disposed in the environment or by an associated remote data logger disposed in proximity to and in communication with the remote sensors; the method characterized by: the processor constructing a combined input and output noise levels matrix containing output noise terms associated with the physical environmental property and input noise terms associated with the at least one independent variable with which the physical environmental property is correlated; using the combined input and output noise levels matrix, the processor constructing a main Gaussian Processes model that models the physical environmental property and its non-stationary heteroscedastic noise; and the processor co-operating with an output device to generate and perceptibly output a predictive probabilistic representation of the environmental property, using the main GP model, wherein the predictive probabilistic representation comprises a respective range of possible values of the physical environmental property for each respective value of the at least one independent variable, the range of possible values reflecting both the input noise terms associated with the independent variable and the output noise terms associated with the physical environmental property. the processor constructing a combined input and output noise levels matrix containing output noise terms associated with the physical environmental property and input noise terms associated with the at least one independent variable with which the physical environmental property is correlated; using the combined input and output noise levels matrix, the processor constructing a main Gaussian Processes model that models the physical environmental property and its non-stationary heteroscedastic noise; and the processor co-operating with an output device to generate and perceptibly output a predictive probabilistic representation of the environmental property, using the main GP model, wherein the predictive probabilistic representation comprises a respective range of possible values of the physical environmental property for each respective value of the at least one independent variable, the range of possible values reflecting both the input noise terms associated with the independent variable and the output noise terms associated with the physical environmental property.