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Root exclusion methods for partitioning of soil respiration:Review and methodological considerations

Pedosphere 2023年第5期33卷 683-699页

作者： Mei-Yee CHIN Sharon Yu Ling LAU Frazer MIDOT Mui Sie Jee Mei Lieng LO faustina e.sangok Lulie MeLLING Sarawak Tropical Peat Research Institute Lot 6035Kuching-Kota Samarahan ExpresswayKota SamarahanSarawak 94300Malaysia

Soil respiration is a vital process in all terrestrial ecosystems,through which the soil releases carbon dioxide(CO_(2))into the atmosphere at an estimated annual rate of 68–101 Pg carbon,making it the second highest terrestrial contributor to carbon *** soil respiration consists of autotrophic and heterotrophic constituents,methods for accurately determining the contribution of each constituent to the total soil respiration are critical for understanding their differential responses to environmental factors and aiding the reduction of CO_(2)*** to its low cost and simplicity,the root exclusion(Re)technique,combined with manual chamber measurements,is frequently used in field studies of soil respiration ***,Re treatments alter the soil environment,leading to potential bias in respiration *** review aims to elucidate the current understanding of Re,i.e.,trenching(Tr)and deep collar(DC)insertion techniques,by examining soil respiration partitioning studies performed in several ***,we discuss methodological considerations when using Re and the combinations of Re with stable isotopic and modeling ***,future research directions for improving the Tr and DC insertion methods in Re are suggested.

关键词： autotrophic respiration deep collar insertion heterotrophic respiration microbial respiration root trenching soil microbial community soil respirationcomponent

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estimation of Land Surface Temperature from Landsat-8 OLI Thermal Infrared Satellite Data. A Comparative Analysis of Two Cities in Ghana

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Advances in Remote Sensing 2021年第4期10卷 131-149页

作者： Yaw A. Twumasi edmund C. Merem John B. Namwamba Olipa S. Mwakimi Tomas Ayala-Silva Diana B. Frimpong Zhu H. Ning Abena B. Asare-Ansah Jacob B. Annan Judith Oppong Priscilla M. Loh faustina Owusu Valentine Jeruto Brilliant M. Petja Ronald Okwemba Joyce McClendon-Peralta Caroline O. Akinrinwoye Hermeshia J. Mosby Department of Urban Forestry and Natural Resources Southern University and A&M College Baton Rouge Louisiana USA Department of Urban and Regional Planning Jackson State University Jackson Mississippi USA Institute of Resource Assessment University of Dares Salam Dares Salam Tanzania USDA-ARS Tropical Agriculture Research Station Mayaguez Puerto Rico USA Water Research Commission (WRC) Private Bag X03 Gezina South Africa

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (easons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software were used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was calculated by using red and near-infrared bands i.e. Band 4 and Band 5. Land surface emissivity (LSE) was also calculated to determine the efficiency of transmitting thermal energy across the surface into the atmosphere. Results of the study show variation of temperatures between different locations in two urban areas. The study found Accra to have experienced higher and lower dry season and wet season temperatures, respectively. The temperature ranges corresponding to the dry and wet seasons were found to be 21.0985e="font-family:;" "="">e="font-family:Verdana;">e="color:#4F4F4F;font-family:Simsun;font-

关键词： Remote Sensing Land Surface Temperature (LST) Atmospheric Spectral Radiance Normalized Difference Vegetation Index (NDVI) Land Surface emissivity (LSe) Landsat 8 Satellite Ghana

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