Landsat 8 satellite data-based estimation of soil moisture in McMurdo Dry Valleys, Antarctica

• Main Author: Raga González, Raül
• Other Authors: Valdes, Maite Lezama, Meyer, Hanna, Silva, Joel Dinis Baptista Ferreira da
• Format: Master Thesis
• Language: English
• Published: 2021
• Subjects: Soil moisture; McMurdo Dry Valleys; Antarctica; Landsat 8; Climate stations; Estimation; Prediction; Regression model; Antarctic; Finn; Antarc*
• Online Access: http://hdl.handle.net/10362/113892

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies Soil moisture is the total amount of water present in the upper 10 cm of soil and it represents the water in land surface which resides in the pores of the soil which is not in river, lakes or groundwater and which depends of the weather conditions, soil type and associated vegetation, among others. Soil moisture assessments are important to understand the hydrological cycles and biophysical processes caused by global climate changes (Finn et al., 2011). Usually, soil moisture has been mapped with airborne microwave radiometers (Klemas et al., 2014) to measure the water retained in the spaces between soil particles. Its importance is due to the microorganism metabolic activity, regulation of the soil temperature and carriage of nutrients, among others. Soil moisture typically takes the form of small ice crystals, vapour, or small parts of liquid water in cold desert soils (Campbell & Claridge, 1982). Antarctic soils are composed by basically no organic and very low moisture content (Campbell and Claridge, 1987). Antarctica is a sensitive area to balance the global climate and its changes and its soil ecosystems are strongly regulated by variables of the abiotic environment and due to this, a research measures the incidence and spatial occurrence of the layer freezing to know how regional climate change could affect the energy exchange of this layer and its invertebrate communities (Wlostowski et al., 2017). Also, knowing how the dynamic of the surface varies in polar regions is transcendent to predict the impact of climate change in global sea-level rise in the future (Quincey & Luckman, 2009).