Article
Environmental Sciences
Jannis Heil, Christoph Joerges, Britta Stumpe
Summary: This study developed a method for predicting topsoil soil organic matter (SOM) at a high resolution on the field scale using soil color information gained from low-altitude UAV imagery and machine learning. The method showed good performance in predicting SOM with a random forest model, and the validation using external data indicated that the prediction models are transferable to neighboring fields, enabling carbon monitoring over time.
Article
Environmental Sciences
Xianglin Zhang, Jie Xue, Songchao Chen, Nan Wang, Tieli Xie, Yi Xiao, Xueyao Chen, Zhou Shi, Yuanfang Huang, Zhiqing Zhuo
Summary: This study used Quantile Regression Forest to map the spatial distribution of soil organic carbon in cropland in the Northeast China Plain. The results showed that SOC increased overall from the southern area to the northern area, and decreased with depth. Climate, position, and organism were identified as the dominant controlling factors. Additionally, higher uncertainty was observed in certain areas.
Article
Soil Science
Alice Alonso, Manuel Froidevaux, Mathieu Javaux, Eric Laloy, Samuel Mattern, Christian Roisin, Marnik Vanclooster, Charles Bielders
Summary: The study introduces a hybrid method that combines high-resolution soil penetration resistance measurements with soil core sampling to accurately assess changes in soil physical quality. This method can be used to compare different soil management techniques or monitor the temporal evolution of soil physical quality, making it a valuable tool for guiding agricultural soil management.
SOIL & TILLAGE RESEARCH
(2022)
Article
Environmental Sciences
Yang Yan, Jiajie Yang, Baoguo Li, Chengzhi Qin, Wenjun Ji, Yan Xu, Yuanfang Huang
Summary: This study aims to test the feasibility of using UAV hyperspectral data to map soil organic matter at a 1 m resolution. The results show that the random forest model based on UAV hyperspectral data can successfully predict soil organic matter with high accuracy, compared to other prediction methods.
Article
Meteorology & Atmospheric Sciences
Karam Alsafadi, Safwan Mohammed, Ali Mokhtar, Mohammed Sharaf, Hongming He
Summary: A study on annual precipitation in Syria from 1975 to 2010 used multivariate regression models to calculate precipitation at 1 km^2 spatial resolution, with the PSRMR-IDW-3 model found to be superior based on accuracy evaluations from 43 stations. The PSMRM-OK-EXP model had the least mean absolute error and mean absolute percentage error compared to other models.
ATMOSPHERIC RESEARCH
(2021)
Article
Environmental Sciences
Da He, Qian Shi, Jingqian Xue, Peter M. Atkinson, Xiaoping Liu, Marie Weiss
Summary: In this research, a learnable correlation-based sub-pixel mapping (LECOS) method is developed to tackle the mixed pixel effect in urban land use/land cover classification. The method effectively models teleconnections and diverse global correlation patterns, resulting in accurate sub-pixel reconstruction of complex urban scenes. The derived results demonstrate rich urban spatial heterogeneity and suggest the potential for greater understanding of urban issues.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Environmental Sciences
Yang Junting, Li Xiaosong, Wu Bo, Wu Junjun, Sun Bin, Yan Changzhen, Gao Zhihai
Summary: This study successfully established a soil organic matter (SOM) content model for topsoil in desertified land in northern China using a high spatial resolution dataset and machine learning methods. It highlighted the importance of quarterly information on green vegetation and non-photosynthetic vegetation, and demonstrated the effectiveness of combining Dead Fuel Index and Normalized Difference Vegetation Index of the four quarters to improve SOM estimation accuracy.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2021)
Article
Agriculture, Multidisciplinary
Joachim G. C. Deru, Nyncke Hoekstra, Maaike van Agtmaal, Jaap Bloem, Ron de Goede, Lijbert Brussaard, Nick van Eekeren
Summary: This study manipulated the soil Ca:Mg ratio by adding minerals in three dairy grasslands on peat. The study found that CaCO3 application increased soil Ca:Mg ratio and pH, decreased N-total and C-total, and increased P availability. MgCO3 had little influence on soil parameters and grass N yield. CaSO4 and MgSO4 reduced grass N yield in most cases. Results suggest that Ca binding can stabilize organic matter, and grass N yield is influenced by soil pH.
NEW ZEALAND JOURNAL OF AGRICULTURAL RESEARCH
(2023)
Article
Geosciences, Multidisciplinary
Brian T. Dinkelacker, Pablo Garcia Rivera, Ioannis Kioutsioukis, Peter J. Adams, Spyros N. Pandis
Summary: This study aims to accurately predict urban PM2.5 concentrations and composition by increasing the resolution of the prediction model. The improved model performance at higher resolutions can support emissions control policy development and address environmental justice issues.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2022)
Article
Soil Science
Thiago M. Inagaki, Angela R. Possinger, Steffen A. Schweizer, Carsten W. Mueller, Carmen Hoeschen, Michael J. Zachman, Lena F. Kourkoutis, Ingrid Kogel-Knabner, Johannes Lehmann
Summary: The spatial distribution of organic substrates and microscale soil heterogeneity significantly influence organic matter (OM) persistence as constraints on OM accessibility to microorganisms. However, it is unclear how changes in OM spatial heterogeneity driven by factors such as soil depth affect the relative importance of substrate spatial distribution on OM persistence.
SOIL BIOLOGY & BIOCHEMISTRY
(2023)
Article
Environmental Sciences
Yongyue Wang, Qiwei Li, Zhenyu Luo, Junchao Zhao, Zhaofeng Lv, Qiuju Deng, Jing Liu, Majid Ezzati, Jill Baumgartner, Huan Liu, Kebin He
Summary: By combining high-resolution PM2.5 concentration and population distribution, this study considers indoor/outdoor exposure differences and provides personal daily PM2.5 internal dose. The study utilizes assimilation methods and mobile signaling data to determine population-weighted ambient PM2.5 concentrations and exposure diversity.
COMMUNICATIONS EARTH & ENVIRONMENT
(2023)
Article
Environmental Sciences
Timothy J. Fahey, Joseph B. Yavitt, Marc Goebel, Gwendolyn Pipes
Summary: The decomposition of fine root litter and its conversion into stable soil organic matter (SOM) has been poorly studied. By labeling fine roots of sugar maple with C-13 and tracing the label for 7 years, we found that only 8.9% of the C-13 label was recovered, with most of it found in coarse particulate organic matter. The formation of microaggregates from fine root detritus was most pronounced in a higher pH soil with high iron oxide content.
Article
Environmental Sciences
M. B. Siewert, H. Lantuit, A. Richter, G. Hugelius
Summary: Spatial analysis in earth sciences often relies on spatial autocorrelation, but permafrost soils show significant variability at different scales, contradicting Tobler's first law of geography. Understanding these complexities is crucial for mapping and predicting permafrost carbon feedbacks.
GLOBAL BIOGEOCHEMICAL CYCLES
(2021)
Article
Engineering, Electrical & Electronic
Haoxuan Yang, Qunming Wang, Xiaofeng Ma, Wenqi Liu, Huanjun Liu
Summary: This study used a spatiotemporal fusion method to generate high temporal resolution simulated Landsat-8 data, aiming to improve the accuracy of digital soil mapping (DSM). The results showed that the fused data had increased class separability, leading to a 3.099% increase in overall accuracy and a 0.047 increase in kappa coefficient. This article explores the potential of the spatiotemporal fusion method for DSM, providing a new solution for remote-sensing-based DSM.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Agronomy
Dorota Pikula, Olga Ciotucha
Summary: Understanding the transformation processes of organic matter in soil is crucial for managing soil organic carbon dynamics. This study found that both crop rotation and manure fertilization had significant effects on soil organic matter fractions and humus humification index. Additionally, mineral nitrogen fertilization and pH conditions also played a role in the composition of humus compounds in the soil.
Article
Soil Science
Carsten W. Mueller, Markus Steffens, Henning Buddenbaum
Summary: This study introduces a new method using Vis-NIR spectroscopy and resin-embedded soil core sections to determine microscale soil structure arrangement through image classification, including quantification of soil organic matter fractions. This approach helps to scale up from microscale spectromicroscopic techniques to the centimeter and possibly pedon scale.
EUROPEAN JOURNAL OF SOIL SCIENCE
(2021)
Article
Environmental Sciences
Jane J. Meiforth, Henning Buddenbaum, Joachim Hill, James Shepherd
Article
Soil Science
Evelin Pihlap, Markus Steffens, Ingrid Koegel-Knabner
Summary: This study aims to elucidate the initial aggregate formation in calcareous loess, showing that organic matter induces the formation of large macroaggregates, while microaggregates do not accumulate soil organic carbon. The findings suggest that soil aggregate formation on young calcareous soils involves both fresh soil organic matter contributing to macroaggregate formation and intrinsic cementation of loess through carbonates affecting microaggregate stability.
Article
Automation & Control Systems
Babatunde K. Agbaogun, Jose M. Alonso, Henning Buddenbaum, Klaus Fischer
Summary: This study utilized ANFIS to predict the sorption coefficients of phenylurea herbicides in soils, with results indicating that ANFIS models outperformed MLR models in terms of accuracy and interpretability. Therefore, the use of ANFIS for predicting compound sorption coefficients in soils is recommended.
JOURNAL OF CHEMOMETRICS
(2021)
Article
Soil Science
Alix Vidal, Tobias Kloffel, Julien Guigue, Gerrit Angst, Markus Steffens, Carmen Hoeschen, Carsten W. Mueller
Summary: The interface between decaying plant residues and soil minerals is crucial for the formation of soil organic matter, with microbial activity playing a key role in promoting the formation of mineral-associated organic matter. The transfer of carbon and nitrogen from plant residues to the mineral soil is mediated by microorganisms, leading to the formation of mineral-associated organic matter.
SOIL BIOLOGY & BIOCHEMISTRY
(2021)
Article
Multidisciplinary Sciences
Markus Steffens, Lilli Zeh, Derek M. Rogge, Henning Buddenbaum
Summary: Organic matter is crucial for soil functions and ecosystem services, but its heterogeneous distribution in the soil profile makes assessment challenging. The current lack of a technique to accurately measure soil organic matter quality and quantity with high spatial resolution hinders research progress. Imagining visible light and near infrared spectroscopy shows promise for this purpose.
SCIENTIFIC REPORTS
(2021)
Article
Forestry
Michael S. Watt, Ellen Mae C. Leonardo, Honey Jane C. Estarija, Peter Massam, Dilshan de Silva, Renelle O'Neill, David Lane, Rebecca McDougal, Henning Buddenbaum, Pablo J. Zarco-Tejada
Summary: Research on describing long-term water stress in radiata pine using hyperspectral imagery revealed key indicators and significant treatment differences after 108 DAT. Water indices showed stronger correlations with water stress compared to physiological index PRI and other structural indices.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Soil Science
M. Krauss, M. Wiesmeier, A. Don, F. Cuperus, A. Gattinger, S. Gruber, W. K. Haagsma, J. Peigne, M. Chiodelli Palazzoli, F. Schulz, M. G. A. van der Heijden, L. Vincent-Caboud, R. A. Wittwer, S. Zikeli, M. Steffens
Summary: Reduced tillage in organic farming can increase SOC stocks in surface layers, decrease them in intermediate layers, and increase them in deeper soil layers. The cumulative SOC stocks increased by 1.7% or 1.5 Mg ha-1 (0-50 cm, n = 9) and 3.6% or 4.0 Mg ha-1 (0-100 cm, n = 7) compared with ploughing. The estimated mean C sequestration rates were 0.09 and 0.27 Mg ha-1 yr-1, respectively.
SOIL & TILLAGE RESEARCH
(2022)
Article
Soil Science
Johanna Wetterlind, Raphael A. Viscarra Rossel, Markus Steffens
Summary: This study utilized diffuse reflectance spectroscopy to characterize and model the functional chemistry of SOC. NMR-derived C functional groups could be modeled with vis-NIR and mid-IR diffuse reflectance spectra, allowing for the characterization of SOC chemical composition on whole mineral soil samples and improving the spatial and temporal characterization of SOC composition.
EUROPEAN JOURNAL OF SOIL SCIENCE
(2022)
Article
Environmental Sciences
Babatunde Kazeem Agbaogun, Bamidele Iromidayo Olu-Owolabi, Henning Buddenbaum, Klaus Fischer
Summary: This study investigated the sorption of Pb, Cd, and Cu in five natural soils of Nigerian origin and compared the predictive performance of the adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) models. The results showed that ANFIS outperformed MLR in predicting the adsorption capacities of the soil-metal ion systems.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Forestry
Philipp Kaiser, Henning Buddenbaum, Sascha Nink, Joachim Hill
Summary: This paper presents the use of multitemporal Sentinel-1 synthetic aperture radar (SAR) data to detect drought-affected and fire-endangered forest stands with high spatial and temporal resolution. The authors developed a novel Sentinel-1 Radar Drought Index (RDI) to reduce speckle noise and created a spatially explicit detection map of drought-affected forest stands in the Donnersberg study area in Germany. The results showed a significant correlation between RDI values and monthly mean temperatures, indicating the potential of Sentinel-1 data for timely detection of drought-affected and fire-prone forest areas.
Article
Agronomy
Michael S. Watt, Tomas Poblete, Dilshan de Silva, Honey Jane C. Estarija, Robin J. L. Hartley, Ellen Mae C. Leonardo, Peter Massam, Henning Buddenbaum, Pablo J. Zarco-Tejada
Summary: Dothistroma needle blight is a widespread and damaging disease of pine trees caused by fungi, resulting in chlorosis, necrosis, and premature needle loss. This study used hyperspectral data collected from a UAV to improve predictions of disease severity using plant functional traits determined from a 3D radiative transfer model. The final model accurately predicted disease severity with an R2 of 0.85.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Book Review
Soil Science
Else K. Bunemann, Markus Steffens
NUTRIENT CYCLING IN AGROECOSYSTEMS
(2023)