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Evaluation of Landsat 8 image pansharpening in estimating soil organic matter using multiple linear regression and artificial neural networks

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Geo-Spatial Information Science 2022年第3期25卷 353-364页

作者： Abdelkrim Bouasria Khalid Ibno Namr Abdelmejid Rahimi El Mostafa Ettachfini Badr Rerhou Faculty of Sciences Chouaib Doukkali UniversityEl JadidaMorocco Agricultural Development Department Doukkala Regional Agricultural Development OfficeEl JadidaMorocco soil Science Department Hassan II Agronomic and Veterinary InstituteRabatMorocco

In agricultural systems,the regular monitoring of soil organic matter(SOM)dynamics is essential.This task is costly and time-consuming when using the conventional method,especially in a very fragmented area and with intensive agricultural activity,such as the area of Sidi Bennour.The study area is located in the Doukkala irrigated perimeter in Morocco.Satellite data can provide an alternative and fill this gap at a low cost.Models to predict SOM from a satellite image,whether linear or nonlinear,have shown considerable interest.This study aims to compare SOM prediction using Multiple Linear Regression(MLR)and Artificial Neural Networks(ANN).A total of 368 points were collected at a depth of 0-30 cm and analyzed in the laboratory.An image at 15 m resolution(MSPAN)was produced from a 30 m resolution(MS)Landsat-8 image using image pansharpening processing and panchromatic band(15 m).The results obtained show that the MLR models predicted the SOM with(training/validation)R^(2)values of 0.62/0.63 and 0.64/0.65 and RMSE values of 0.23/0.22 and 0.22/0.21 for the MS and MSPAN images,respectively.In contrast,the ANN models predicted SOM with R2 values of 0.65/0.66 and 0.69/0.71 and RMSE values of 0.22/0.10 and 0.21/0.18 for the MS and MSPAN images,respectively.Image pansharpening improved the prediction accuracy by 2.60%and 4.30%and reduced the estimation error by 0.80%and 1.30%for the MLR and ANN models,respectively.

关键词： Digital soil mapping soil organic matter remote sensing multiple linear regression artificial neural networks irrigated area Doukkala Morocco

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Molecular signature of soil organic matter under different land uses in the Lake Chaohu Basin

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Eco-Environment & Health 2022年第4期1卷 212-218页

作者： Han Gao Huixin Li Chen Lin Pedro J.J.Alvarez Caroline A.Masiello Dongqiang Zhu Ao Kong Xiaolei Qu State Key Laboratory of Pollution Control and Resource Reuse School of the EnvironmentNanjing UniversityNanjing 210023China School of Finance Nanjing University of Finance and EconomicsNanjing 210023China Key Laboratory of Watershed Geographic Sciences Institute of Geography and LimnologyChinese Academy of SciencesNanjing 210008China State Environmental Protection Key Laboratory of soil Environmental Management and Pollution Control Nanjing Institute of Environmental SciencesMinistry of Ecology and Environment of ChinaNanjing 210042China Department of Civil and Environmental Engineering Rice UniversityHouston TX 77005USA Department of Earth Environmental and Planetary SciencesRice UniversityHouston TX 77005USA School of Urban and Environmental Sciences Peking UniversityBeijing 100871China

The concentration and molecular composition of soil organic matter(SOM)are important factors in mitigation against climate change as well as providing other ecosystem services.Our quantitative understanding of how land use influences SOM molecular composition and associated turnover dynamics is limited,which underscores the need for high-throughput analytical approaches and molecular marker signatures to clarify this etiology.Combining a high-throughput untargeted mass spectrometry screening and molecular markers,we show that forest,farmland and urban land uses result in distinct molecular signatures of SOM in the Lake Chaohu Basin.Molecular markers indicate that forest SOM has abundant carbon contents from vegetation and condensed organic carbon,leading to high soil organic carbon(SOC)concentration.Farmland SOM has moderate carbon contents from vegetation,and limited content of condensed organic carbon,with SOC significantly lower than that of forest soils.Urban SOM has high abundance of condensed organic carbon markers due to anthropogenic activities but relatively low in markers from vegetation.Consistently,urban soils have the highest black carbon/SOC ratio among these land uses.Overall,our results suggested that the molecular signature of SOM varies significantly with land use in the Lake Chaohu Basin,influencing carbon dynamics.Our strategy of molecular fingerprinting and marker discovery is expected to enlighten further research on SOM molecular signatures and cycling dynamics.

关键词： High-throughput untargeted mass spectrometry screening Mass spectrum processing algorithm soil organic matter Molecular signature Land use

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The application of proximal visible and near-infrared spectroscopy to estimate soil organic matter on the Triffa Plain of Morocco

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International soil and Water Conservation Research 2020年第2期8卷 195-204页

作者： Ayoub Lazaar Abdul Mounem Mouazen Kamal EL Hammouti Michael Fullen Biswajeet Pradhan Muhammad Sohail Memon Karim Andich Abdelilah Monir Laboratory of Applied Geosciences Department of GeologyFaculty of ScienceMohammed First UniversityOujdaMorocco Division of Mechatronics Biostatistics and Sensors(MeBioS)Faculty of Bioscience EngineeringKasteelpark Arenberg 30B-3001 HeverleeBelgium Faculty of Science and Engineering University of WolverhamptonWolverhamptonWV11LYUnited Kingdom Center for Advanced Modelling and Geospatial Information Systems(CAMGIS) Faculty of Engineering and Information TechnologyUniversity of Technology SydneySydney2007NSWAustralia Faculty of Agricultural Engineering Sindh Agriculture UniversityTandojam70060Pakistan Laboratory of Applied Geomatics and soil Science National Institute of Agronomic Research(INRA)OujdaMorocco Department of Mathematics EDP and Scientific Computing TeamMoulay Ismail UniversityMéknesMorocco

soil organic matter (SOM) is a fundamental soil constituent. The estimation of this parameter in the laboratory using the classical method is complex time-consuming and requires the use of chemical re-agents. The objectives of this study were to assess the accuracy of two laboratory measurement setups of the VIS-NIR spectroscopy in estimating SOM content and determine the important spectral bands in the SOM estimation model. A total of 115 soil samples were collected from the non-root zone (0-20 cm) of soil in the study area of the Triffa Plain and then analysed for SOM in the laboratory by the Walkley-Black method. The reflectance spectra of soil samples were measured by two protocols, Contact Probe (CP) and Pistol Grip (PG)) of the ASD spectroradiometer (350-2500 nm) in the laboratory. Partial least squares regression (PLSR) was used to develop the prediction models. The results of coefficient of determination (R2) and the root mean square error (RMSE) showed that the pistol grip offers reasonable accuracy with an R2=0.93 and RMSE=0.13 compared to the contact probe protocol with an R2=0.85 and RMSE = 0.19. The near-Infrared range were more accurate than those in the visible range for pre-dicting SOM using the both setups (CP and PG). The significant wavelengths contributing to the pre-diction of SOM for (PG) setup were at:424, 597, 1432, 1484, 1830,1920, 2200, 2357 and 2430 nm, while were at 433, 587, 1380, 1431, 1929, 2200 and 2345 nm for (CP) setup.

关键词： soil organic matter VIS-NIR spectroscopy Reflectance spectra SOM estimation SOM analysis

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Influence of Climate and Socio-Economic Factors on the Spatio-Temporal Variability of soil organic matter: A Case Study of Central Heilongjiang Province, China

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Journal of Integrative Agriculture 2014年第7期13卷 1486-1500页

作者： SHI Shu-qin CAO Qi-wen YAO Yan-min TANG Hua-jun YANG Peng WU Wen-bin XU Heng-zhou LIU Jia LI Zheng-guo School of Management Tianjin Polytechnic University Key Laboratory of Agri-Informatics Ministry of Agriculture/Institute of Agricultural Resources & Regional Planning Chinese Academy of Agricultural Sciences College of Management Tianjin University

For the scientific management of farmland, it is significant to understand the spatio-temporal variability of soil organic matter and to study the influences of related factors. Using geostatistical theory, GIS spatial analysis, trend analysis and a Geographically Weighted Regression （GWR） model, this study analyzed the response of soil organic matter to climate and socio-economic factors in central Heilongjiang Province during the past 25 years. Second soil survey data of China for 1979-1985, 2005 field sampling data, climate observations and socio-economic data for 1980-2005 were analyzed. First, soil organic matter in 2005 was spatially interpolated using the Co-Kriging method along with auxiliary data sets of soil type and pH. The spatio-temporal variability was then studied by comparison with the 1980s second soil census data. Next, the temporal trends in climate and socio-economic factors over the past 25 years were investigated. Finally, we examined the variation of the response of soil organic matter to climate and socio-economic factors using the GWR model spatially and temporally. The model showed that 53.82% area of the organic matter content remained constant and 29.39% has decreased during the past 25 years. The impact of precipitation on organic matter content is mainly negative, with increasing absolute values of the regression coefficient. The absolute value of regression coefficient of annual average temperature has decreased, and more areas are now under its negative effects. In addition, the areas of positive regression coefficient of annual sunshine hours have northward shifted, with the increasing absolute value of positive coefficient and decreasing absolute value of negative coefficient. The areas of positive regression coefficient of mechanized farming as a socio-economic factor have westward shifted, with the increasing absolute value of negative coefficient and decreasing absolute value of positive coefficient. The area of regions with the positive regression coefficient of irrigation ha

关键词： soil organic matter climate socio-economic factors GWR Heilongjiang Province

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Applications of physical methods in estimation of soil biota and soil organic matter

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soil Ecology Letters 2020年第3期2卷 165-175页

作者： Chagovetc Sergei Shenglei Fu Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions Ministry of EducationCollege of Environment and PlanningHenan UniversityKaifeng 475004China Henan Key Laboratory of Integrated Air Pollution Control and Ecological Security Henan UniversityKaifeng 475004China

soil biota is the living component of soil organic matter(SOM),and plays a key role in the decomposition of SOM.Both soil biota and SOM are indicators of soil fertility and soil quality.However,they both are sensitive to soil disturbance.Although researchers developed various technologies to detect soil biota and SOM,they are mostly destructive and cause disturbance to soil,which may not reflect the actual situation of soil biota and SOM.Therefore,here we mostly focused on the non-destructive physical methods for estimating soil biota and SOM and discussed their advantages and disadvantages.These methods include but not limited to acoustic detection,radio frequency identification,radioactive tagging,hyperspectral sensing and electron energy loss spectroscopy.In addition,we pointed out the current research problems and the potential research directions for applications of physical methods in estimation of soil biota and SOM.

关键词： soil organic matter soil biota Advanced method Acoustic method Spectroscopy Tagging

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Mapping soil organic matter in cultivated land based on multi-year composite images on monthly time scales

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Journal of Integrative Agriculture 2024年第4期23卷 1393-1408页

作者： Jie Song Dongsheng Yu Siwei Wang Yanhe Zhao Xin Wang Lixia Ma Jiangang Li State Key Laboratory of soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008China Agricultural and Rural Bureau of Luanping County Luanping 068250China Chinese Academy of Sciences University Beijing 100049China

Rapid and accurate acquisition of soil organic matter(SOM)information in cultivated land is important for sustainable agricultural development and carbon balance management.This study proposed a novel approach to predict SOM with high accuracy using multiyear synthetic remote sensing variables on a monthly scale.We obtained 12 monthly synthetic Sentinel-2 images covering the study area from 2016 to 2021 through the Google Earth Engine(GEE)platform,and reflectance bands and vegetation indices were extracted from these composite images.Then the random forest(RF),support vector machine(SVM)and gradient boosting regression tree(GBRT)models were tested to investigate the difference in SOM prediction accuracy under different combinations of monthly synthetic variables.Results showed that firstly,all monthly synthetic spectral bands of Sentinel-2 showed a significant correlation with SOM(P<0.05)for the months of January,March,April,October,and November.Secondly,in terms of single-monthly composite variables,the prediction accuracy was relatively poor,with the highest R^(2)value of 0.36 being observed in January.When monthly synthetic environmental variables were grouped in accordance with the four quarters of the year,the first quarter and the fourth quarter showed good performance,and any combination of three quarters was similar in estimation accuracy.The overall best performance was observed when all monthly synthetic variables were incorporated into the models.Thirdly,among the three models compared,the RF model was consistently more accurate than the SVM and GBRT models,achieving an R^(2)value of 0.56.Except for band 12 in December,the importance of the remaining bands did not exhibit significant differences.This research offers a new attempt to map SOM with high accuracy and fine spatial resolution based on monthly synthetic Sentinel-2 images.

关键词： soil organic matter Sentinel-2 monthly synthetic images machine learning model spatial prediction

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Deadwood affects the soil organic matter fractions and enzyme activity of soils in altitude gradient of temperate forests

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Forest Ecosystems 2023年第3期10卷 316-327页

作者： Ewa Błońska Wojciech Prazuch Jarosław Lasota Department of Ecology and Silviculture Faculty of ForestryUniversity of Agriculture in Krakow29 Listopada 46 Str.31-425KrakowPoland

The main objective of our study has been to determine the role of deadwood in the shaping of the amount of soil organic matter fractions in mountain forest soils.For this purpose,a climosequence approach comprising north(N)and south(S)exposure along the altitudinal gradient(600,800,1000 and 1200 m a.s.l.)was set up.By comparing the properties of decomposing deadwood and those of the soils located directly beneath the decaying wood we drew conclusions about the role of deadwood in the shaping of soil organic matter fractions and soil carbon storage in different climate conditions.The basic properties,enzymatic activity and fractions of soil organic matter(SOM)were determined in deadwood and affected directly by the components released from decaying wood.Heavily decomposed deadwood impacts soil organic matter stabilization more strongly than the less decayed deadwood and the light fraction of SOM is more sensitive to deadwood effects than the heavy fraction regardless of the location in the altitude gradient.Increase in SOM mineral-associated fraction C content is more pronounced in soils under the influence of deadwood located in lower locations of warmer exposure.Nutrients released from decaying wood stimulate the enzymatic activity of soils that are within the range of deadwood influence.

关键词： Enzyme activity Forest soils Heavy fraction Light fraction soil organic matter

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Effects of free iron oxyhydrates and soil organic matter on copper sorption-desorption behavior by size fractions of aggregates from two paddy soils

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Journal of Environmental Sciences 2009年第5期21卷 618-624页

作者： WANG Fang, PAN Genxing, LI Lianqing Institute of Resource, Ecosystem and Environment of Agriculture, Nanjing Agricultural University, Nanjing 210095, China. Institute of Resource Ecosystem and Environment of Agriculture Nanjing Agricultural University Nanjing 210095 China

Effects of free iron oxyhydrates （Fed） and soil organic matter （SOM） on copper （Cu^2＋） sorption-desorption behavior by size fractions of aggregates from two typical paddy soils （Ferric-Accumulic Stagnic Anthrosol （soil H） and Gleyic Stagnic Anthrosol （soil W）） were investigated with and without treatments of dithionite-citrate-bicarbonate and of H2O2. The size fractions of aggregates were obtained from the undisturbed bulk topsoil using a low energy ultrasonic dispersion procedure. Experiments of equilibrium sorption and subsequent desorption were conducted at soil water ratio of 1：20, 25℃. For soil H, Cu^2＋ sorption capacity of the DCB-treated size fractions was decreased by 5.9% for fine sand fraction, by 40.4% for coarse sand fraction, in comparison to 2.9% for the bnlk sample. However, Cu^2＋ sorption capacities of the H2O2-treated fractions were decreased by over 80% for the coarse sand fraction and by 15% for the clay-sized fraction in comparison to 88% for bulk soil. For soil W, Cu^2＋ sorption capacity of the DCB-treated size fraction was decreased by 30% for the coarse sand fraction and by over 75% for silt sand fraction in comparison to 44.5% for the bulk sample. Cu^2＋ sorption capacities of the H2O2-treated fractions were decreased by only 2.0% for the coarse sand fraction and by 15% for the fine sand fraction in comparison to by 3.4% for bulk soil. However, Cu^2＋ desorption rates were increased much in H2O2-treated samples by over 80% except the clay-sized fraction （only 9.5%） for soil H. While removal of SOM with H2O2 tendend to increase the desorption rate, DCB- and H2O2-treatments caused decrease in Cu^2＋ retention capacity of size fractions, Particularly, there hardly remained Cu^2＋ retention capacity by size fractions from soil H after H2O2 treatment except for clay-sized fraction. These findings supported again the dominance of the coarse sand fraction in sorption of metals and the preference of absorbed metals bound to SOM in differently stabilized status among the size fractions. Thus, enrichmen

关键词： paddy soils Cn^2＋ sorption-desorption soil organic matter free iron oxyhydrates size fraction of aggregates

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Impacts of soil organic matter, pH and exogenous copper on sorption behavior of norfloxacin in three soils

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Journal of Environmental Sciences 2009年第5期21卷 632-640页

作者： ZHANG Jie LI Zhaojun GE Gaofei SUN Wanchun LIANG Yongchao WU Laosheng College of Natural Resources and Environmental Sciences Nanjing Agricultural University Nanjing 210095 China Ministry of Agriculture Key Laboratory of Crop Nutrition and Fertilization Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing 100081 China Key Laboratory of Oasis Eco-Agriculture and College of Agriculture Shihezi University Shihezi 832003 China Department of Environmental Sciences University of California Riverside Riverside CA 92521 USA

Norfloxacin sorption and the factors （soil organic matter （SOM）, pH, and exogenous copper （Cu） influencing the sorption were investigated in a black soil （soil B）, a fluvo-aquic soil （soil F）, and a red soil （soil R）. With increasing norfloxacin concentrations, sorption amount of norfloxacin increased in both the bulk soils and their SOM-removed soils, but the sorption capacity of SOM-removed soils was higher than that of their corresponding bulk soils, indicating that the process of norfloxacin sorption in soil was influenced by the soil properties including SOM. The sorption data in all bulk soils and SOM-removed soils were fitted to Freundlich and Langmuir models. The correlation coefficients suggested that the experimental data fitted better to Freundlich equation than to Langmuir equation. Furthermore, the data from soil F and SOM-removed F could not be described by Langmuir equation. The norfloxacin sorption amount decreased in soil B and soil F, whereas it increased in soil R as solution pH increased. The maximum KD and Koc were achieved in soil R when the equilibrium solution pH was 6. The norfloxacin sorption was also influenced by the exogenous Cu^2＋, which depended on the soil types and Cu^2＋ concentrations. With increasing Cu^2＋ concentrations in solution, generally, sorption amount, KD and Koc for norfloxacin in soils increased and were up to a peak at 100 mg/L Cu^2＋, and then the sorption amount decreased regardless of norfloxacin levels.

关键词： copper norfloxacin pH soil organic matter sorption

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Spatial Distribution of soil organic matter and Nutrients in the Pear Orchard Under Clean and Sod Cultivation Models

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Journal of Integrative Agriculture 2013年第2期12卷 344-351页

作者： XU Ling-fei ZHOU Peng HAN Qing-fang LI Zhi-hui YANG Bao-ping NIE Jun-feng College of Horticulture Northwest A&F University Key Laboratory of Horticultural Plant Biology and Germplasm Innovation in Northwest China Ministry of Agriculture Key Laboratory of Crop Production and Ecology Minister of Agriculture

The soil organic matter and nutrients are fundamental for the sustainability of pear production, but little is known about the spatial distribution of soil organic matter and nutrients in a pear orchard. With the soil of the pear （cv. Dangshansu on P.betulifolia Bunge. rootstock） orchard under clean and sod cultivation models as test materials, the experiment was conducted to evaluate spatial variability of soil organic matter （SOM）, total nitrogen （STN）, total phosphorus （STP）, total potassium （STK）, available nitrogen （SAN）, and available potassium （SAK） in and between rows at different soil depths （0-60 cm）. The SOM, STN, STP, STK, SAN and SAK of the different soil layers under the two tillage models were different in the vertical direction. The SOM, STN, STP and SAN in the 0-20 cm soil layer were higher than those in the 20-40 and 40- 60 cm soil layers. The STK of 40-60 cm soil layer was higher than that in the 0-20 and 20-40 cm soil layers. The STK increased with the depth of soil in the vertical direction in the clean cultivated pear orchard. Variability of the SOM, STN, STP, STK, SAN and SAK of sample sites in between rows of the same soil layer was found in the pear orchard soil in the horizontal direction under clean and sod cultivation management systems, except that STK of all sites did not show the difference in identical soil layers in the pear orchard under clean cultivation. The sod cultivation model improved the SOM, STN, and STK in the 0-20 cm soil layer in the pear orchard, and the three components increased by 12.8, 12.7 and 7.3% compared to clean cultivation, respectively. The results can be applicable to plan collection of orchard soil samples, assess orchard soil quality, and improve orchard soil management practices.

关键词： spatial distribution soil organic matter soil nutrients clean cultivation sod cover pear orchard

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