Retrieval Study On Spatial And Temporal Distribution Of Soil Organic Carbon In Coal Mining Subsidence Area Of Cinnamon Soil Zone

Remote sensing retrieval has been widely used for dynamic monitoring of the physical and chemical properties of regional soil,but there are few studies on the areas with low organic carbon content and uneven underlying surface which have unremarkable soil spectral characteristics.The cinnamon soil belt in Loess Plateau has multiplicity topography,widely distributed hills and low organic matter content.Large areas soil degradation caused by mining activities has resulted in soil spectroscopy characteristics are strongly disturbed,which has some inhibiting effect on the remote sensing retrieval accuracy of soil organic carbon content at the regional scale.Based on cinnamon soil belt with typical coal mining subsidence area in Shanxi Province as an example,this research used the surface reflectance and outdoor sample data from the field of coal mining subsidence area to retrieve soil organic carbon content.Conducting comparative experiments on the atmospheric correction methods of the Landsat8 OLI image in the study area by the FLAASH model and the 6SV model combined with high spatial and temporal resolution aided meteorological data to analyze the effect on soil spectral curve and organic carbon content in the mining subsidence area of the cinnamon soil belt and recognize sensitive bands.Multiple linear regression?MLR?,BP neural network?BP?and partial least-squares regression?PLSR?model were established to retrieve soil organic carbon content by using the original spectral reflectance R and mathematical transformation forms such as R^1/2,log?1/R?and R'.The results can be used to reveal the spatial-temporal distribution of soilorganic carbon in the mining subsidence area of the cinnamon belt in the Loess Plateau,providing theoretical and technical support for improving regional soil spectral analysis,land reclamation evaluation,establishment of carbon flux observation network in mining subsidence area of the cinnamon belt and estimation of soil carbon pool,which provides the basis for the ecological sustainable development of the cinnamon belt in the regional and global scales.The main results and conclusions are as follows:?1?In the influence analysis of the accuracy of organic carbon inversion,the atmospheric correction effect of 6SV model was better than that of FLAASH model;the partial least squares regression model had the highest inversion accuracy,and the determination coefficient R² was 0.778.It was found that the 6SV atmospheric correction model combined with high spatial and temporal resolution meteorological data could significantly improve the accuracy of soil organic carbon retrival.?2?In generally,there were obvious differences in spectral reflectance characteristics of soil in the same year in different seasons,although the general trend was relatively consistent,the corresponding relationship between different spectral window spectra and soil information was different.Selecting remote sensing images with abundant bare soil information in spring and autumn and less water information caused by irrigation and rainfall could effectively improve the retrieval accuracy.?3?Based on OLI remote sensing images,the spatial differentiation characteristics of soil organic carbon in the reclamation period of 2013-2015 in the study area were inverted,and the spatial and temporal variation pattern of soil organic carbon in the Chang River Basin from 1986 to 2015 was explored by using TM and ETM +.The results showed that from 2013 to 2015,the soil organic carbon content in the study area from 1986 to 2015 was high in the middle and low in both sides.From a time perspective,the content of soil organic carbon was restored by reclamation in 2013-2015.The soil organic carbon content continued to decline from 1986 to 2001,and the soil organic carbon stopped decreasing and rebounded from 2001 to2015.The distribution of landform types such as plains,hills and mountains,as well as the increase and limitation of coal mining activities in different periods had became the main factors that form the characteristics of spatial differentiation at this time.?4?This study can obtain retrieval results and be clear for spatial and temporal distribution patterns that are close to the measured values.It provides a practical method and idea for accurately extracting soil organic carbon content,calculating soil organic carbon storage,and understanding and improving the spatial and temporal distribution of soil organic carbon.