Soil moisture deficit estimation using satellite multi-angle brightness temperature

Abstract

General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms Soil moisture deficit estimation using satellite multi-angle brightness temperature products. This study has also demonstrated the informative capability of the gamma test in the input data selection for model development. These results provide interesting perspectives for dataassimilation in flood-forecasting.

A Pilot Study to Explore the Possibility of Combining Field and Remotely Sensed Data for Agricultural Resources Management

“…Aerial images of the research plot was collected using the DJI Inspire 1 drone using the Drone Deploy phone application for June 5-June 21, 2017. The images were processed using Pix4D software (Pix4D 2017) and analyzed in ArcMap v. 10 Figure 2 Hourly change in soil moisture and temperature in the upslope region of the research plot (June 21, 2017) Figure 2 shows hourly trends of soil moisture and temperature for a 24-hour period (June 21, 2017). An overall increasing trend in soil moisture is observed for soil moisture for Station 1 from 12:00 am to 11:59 PM, which showed the highest soil moisture measurement.…”

“…Generally, soil moisture and temperature are monitored using field equipment, but monitoring crop health can be difficult, especially at large scale farming. However, recent studies have shown remotely sensed data such as satellite images or aerial images from drones could be used to predict crop growth and yield (Yang et al 2015;Zhuo et al 2016). The use of remote sensing data for precision agriculture started in early 1980s, and the data were used to study variations for crop and soil conditions.…”

Soil moisture retrieval over agricultural fields from L-band multi-incidence and multitemporal PolSAR observations using polarimetric decomposition techniques

“…Soil moisture (SM) is a key parameter in hydrological, meteorological, and climatological modelling (Hajnsek et al, 2003;Huang et al, 2016a;Iodice et al, 2013;Jagdhuber et al, 2013;Karthikeyan et al, 2017a;Wang et al, 2017) as it influences the exchange of water, carbon and heat flux between the atmosphere and the land surface (Karthikeyan et al, 2017b;Sánchez-Ruiz et al, 2014;Zhuo et al, 2016). It also provides essential information for drought forecasting, flood prediction and crop management (Di Martino et al, 2016;El Hajj et al, 2016).…”

Evaluation of Remotely Sensed Soil Moisture for Landslide Hazard Assessment

“…However, model-based methods tend to suffer from time drifts problem (e.g., error accumulation over times), require a large number of accurate data inputs and are normally computationally intensive particularly for large monitoring areas. Alternatively, remote sensing is an advanced technology in soil moisture monitoring on a global scale [28][29][30]. There have been enormous investments by various organisations such as ESA (European Space Agency), NASA (National Aeronautics and Space Administration) and EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites), in a wide range of soil moisture observational programs (e.g., ENVISAT (Environmental Satellite), ASCAT (Advanced Scatterometer), AMSR-E (Advanced Microwave Scanning Radiometer for EOS), SMOS (Soil Moisture and Ocean Salinity), and SMAP (Soil Moisture Active Passive)).…”