The LAB-Net Soil Moisture Network: Application to Thermal Remote Sensing and Surface Energy Balance

A set of Essential Climate Variables (ECV) have been defined to be monitored by current and new remote sensing missions. The ECV retrieved at global scale need to be validated in order to provide reliable products to be used in remote sensing applications. For this, test sites are required to use in calibration and validation of the remote sensing approaches in order to improve the ECV retrievals at global scale. The southern hemisphere presents scarce test sites for calibration and validation field campaigns that focus on soil moisture and land surface temperature retrievals. In Chile, remote sensing applications related to soil moisture estimates have increased during the last decades because of the drought and water use conflicts that generate a strong interest on improved water demand estimates. This work describes the Laboratory for Analysis of the Biosphere (LAB)—NETwork, called herein after ‘LAB-net’, which was designed to be the first network in Chile for remote sensing applications. The test sites were placed in four sites with different cover types: vineyards and olive orchards located in the semi-arid region of Atacama, an irrigated raspberry crop in the Mediterranean climate zone of Chimbarongo, and a rainfed pasture in the south of Chile. Over each site, well implemented meteorological and radiative flux instrumentation was installed and continuously recorded the following parameters: soil moisture and temperature at two ground levels (10 and 20 cm), air temperature and relative humidity, net radiation, global radiation, radiometric temperature (8–14 µm), rainfall and soil heat flux. The LAB-net data base post-processing procedure is also described here. As an application, surface remote sensing products such as soil moisture data derived from the Soil Moisture Ocean Salinity (SMOS) and Land Surface Temperature (LST) extracted from the MODIS-MOD11A1 and GOES LST from Copernicus products were compared to in situ data in Oromo LAB-net site. Moreover, land surface energy flux estimation is also shown as an application of LAB-net data base. These applications revealed a good performance between in situ and remote sensing data. LAB-net data base also contributes to provide suitable information for land surface energy budget and therefore water resources management at cultivars scale. The data based generated by LAB-net is freely available for any research or scientific purpose related to current and future remote sensing applications.