Chenyang Xu | Search USGS

USGS2020

Surface soil temperature seasonal variation estimation in a forested area using combined satellite observations and in-situ measurements

Surface soil temperature is the soil temperature from the surface to 10 cm in depth. Surface soil temperature plays a significant role in agricultural drought monitoring, ecosystem energy transfer modeling, and global carbon cycle evaluation. Studies have been proposed to estimate surface soil temperature, but surface soil temperature monitoring within forested areas still poses a significant challenge. In this study, we proposed a surface soil temperature retrieval method using combined satellite observations and in-situ measurements for the Great Dismal Swamp (GDS). The GDS is a U.S. protected area managed and protected by the U.S. Fish and Wildlife Service. It is located along the boundary of Virginia and North Carolina, with maple gum, Atlantic white cedar, and pine pocosin as the main forest cover types. Ground-based surface soil temperature measurements were collected for these forest types from May 2015 to April 2017. Both the Land Remote Sensing Satellite (Landsat) Thermal Infrared Sensor (TIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) carry two thermal infrared (TIR) channels. The TIR channels with similar corresponding wavelengths were first fused using an improved fusing model to generate high resolution TIR measurements. Then the enterprise algorithm was applied to calculate land surface temperature (LST) from the fused TIR bands. An improved soil temperature retrieval method was applied to generate surface soil temperature based on LST and vegetation index (VI) within the study area for the three forest types. In-situ measurements were used to build the surface soil temperature retrieval method, and results were then validated. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were integrated separately as VIs in the model to monitor surface soil temperature. The R 2 for retrieved surface soil temperature through satellite observations was 0.76, and the RMSE was 1.96 ℃ ">℃ ℃ when NDVI was integrated in the model; the R 2 was 0.78, and the RMSE was 1.85 ℃ ">℃ ℃ when EVI was used.

North Carolina, Virginia↗

USGS2019

Carbon dioxide emissions and methane flux from forested wetland soils of the Great Dismal Swamp, USA

The Great Dismal Swamp, a freshwater forested peatland, has accumulated massive amounts of soil carbon since the postglacial period. Logging and draining have severely altered the hydrology and forest composition, leading to drier soils, accelerated oxidation, and vulnerability to disturbance. The once dominant Atlantic white cedar, cypress, and pocosin forest types are now fragmented, resulting in maple-gum forest communities replacing over half the remaining area. In order to determine the effect of environmental variabes on carbon emissions, this study observes 2 years of CO2 and CH4 soil flux, which will also help inform future management decisions. Soil emissions were measured using opaque, non-permanent chambers set into the soil. As soil moisture increased by 1 unit of soil moisture content, CH4 flux increased by 457 μg CH4–C/m2/h. As soil temperature increased by 1 °C, CO2 emissions increased by 5109 μg CO2–C/m2/h. The area of Atlantic white cedar in the study boundary has an average yearly flux of 8.6 metric tons (t) of carbon from CH4 and 3270 t of carbon from CO2; maple-gum has an average yearly flux of 923 t of carbon from CH4 and 59,843 t of carbon from CO2; pocosin has an average yearly flux of 431 t of carbon from CH4 and 15,899 t of carbon from CO2. Total Cha−1year−1 ranged from 1845 kg of Cha−1year−1 in maple-gum to 2024 kg Cha−1year−1 for Atlantic white cedar. These results show that soil carbon gas flux depends on soil moisture, temperature and forest type, which are affected by anthropogenic activities.

North Carolina, Virginia↗