Our investigation showed that the pattern of soil freezing and thawing depended on soil moisture, land use, and temperature during the freezing period (deep of frost).
The objective of this study was to exploit the synergy between SMOS and SMAP based on vegetation optical depth (VOD) to improve brightness temperature (TB) simulations and land surface soil moisture (SM) retrievals in arid regions of the world.
Morse, JL; Bernhardt, ES, Using 15N dual tracers to estimate the relative contribution of nitrification and denitrification to N2O and N2 emissions in coastal plain wetlands under contrasting land uses and soil moisture conditions, Soil Biology and Biochemistry, vol. 57 (2012), pp. 635-643.
In addition, five more variables (altitude, land cover, soil type, soil moisture, and solar radiation) were added to the modelling study based on the published literature (Taylor and Kumar 2012, 2013) (details of the data sources and correlation table are provided in Supporting Information ).
This data will include information from wide variety of sensors (measuring things like soil moisture, land-surface temperature or biomass), weather and climate data, as well as information regarding agricultural best practices.
Our investigations showed that soil moisture and land use governed the initial rate of soil respiration, duration of freezing and thawing of soil, pattern of CO2 dynamics and extra CO2 fluxes.
Therefore, we applied a Random Forest model, which includes the MIRS spectra, temperature, soil moisture, and land use as predictor variables.
It has demonstrated its potential to sense the atmosphere and ionosphere, ocean, land surfaces (including soil moisture) and the cryosphere.
In this study, the influence of land use on soil moisture dynamics is investigated for monitoring purposes.
