Soil organic carbon and texture retrieving and mapping using proximal, airborne and Sentinel-2 spectral imaging

被引:333
作者
Gholizadeh, Asa [1 ]
Zizala, Daniel [1 ,2 ]
Saberioon, Mohammadmehdi [3 ]
Boruvka, Lubos [1 ]
机构
[1] Czech Univ Life Sci Prague, Fac Agrobiol Food & Nat Resources, Dept Soil Sci & Soil Protect, Prague 16500, Czech Republic
[2] Res Inst Soil & Water Conservat, Prague 15627, Czech Republic
[3] Univ South Bohemia Ceske Budejovice, Inst Complex Syst, Fac Fisheries & Protect Waters, South Bohemian Res Ctr Aquaculture & Biodivers Hy, Nove Hrady 37333, Czech Republic
关键词
Agricultural soil; Spectroscopy; Hyperspectral data; Superspectral sensor; Digital soil mapping; INFRARED REFLECTANCE SPECTROSCOPY; AGRICULTURAL SOILS; VEGETATION INDEXES; NIR SPECTROSCOPY; PREDICTION; FIELD; MATTER; PERFORMANCE; RESOLUTION; MISSIONS;
D O I
10.1016/j.rse.2018.09.015
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Soil Organic Carbon (SOC) is a useful representative of soil fertility and an essential parameter in controlling the dynamics of various agrochemicals in soil. Soil texture is also used to calculate soil's ability to retain water for plant growth. SOC and soil texture are thus important parameters of agricultural soils and need to be regularly monitored. Optical satellite remote sensing offers the potential for frequent surveys over large areas. In addition, the recently-operated Sentinel-2 missions provide free imagery. This study compared the capabilities of Sentinel 2 for monitoring and mapping of SOC and soil texture (clay, silt and sand content) with those obtained from airborne hyperspectral (CASI/SASI sensors) and lab ASD FieldSpec spectroradiometer measurements at four agricultural sites in the Czech Republic. Combination of 10 extracted bands of the Sentinel-2 and 18 spectral indices, as independent variables, were used to train prediction models and then produce spatial distribution maps of the selected attributes. Results showed that the prediction accuracy based on lab spectroscopy, airborne and Sentinel-2 in the majority of the sites was adequate for SOC and fair for clay; however, Sentinel-2 imagery could not be used to detect and map variations in silt and sand. The SOC and clay maps derived from the airborne and spaceborne datasets showed similar trend, with both performing better where SOC levels were relatively high, though at the highest levels Sentinel-2 was able to create the SOC map more precisely than the airborne sensors. Taken across all SOC levels measured in the reference data, Sentinel-2 results were marginally lower than lab spectroscopy and airborne imagery, but this reduction in precision may be offset by the extensive geographical coverage and more frequent revisit characteristic of satellite observation. The increased temporal revisit and area are expected to be positive enhancements to the acquisition of high-quality information on variations in SOC and clay content of bare soils.
引用
收藏
页码:89 / 103
页数:15
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