Article
Geosciences, Multidisciplinary
Gabor Szatmari, Laszlo Pasztor, Annamaria Laborczi, Gabor Illes, Zsofia Bakacsi, Dora Zachary, Tibor Filep, Zoltan Szalai, Gergely Jakab
Summary: The objective of the study is to develop a cubist-based pedotransfer function (PTF) for predicting and mapping the saturated SOC content of the topsoils (0-30 cm) in Hungary. The study found that both the physicochemical properties of soils and environmental conditions, such as topography and climate, are important factors in predicting the level of SOC saturation. The results show that there is a significant SOC deficit in a large part of the country, with high spatial variability.
Article
Multidisciplinary Sciences
Samer Alomar, Seyed Ahmad Mireei, Abbas Hemmat, Amin Allah Masoumi, Hossein Khademi
Summary: This study utilized Vis-NIR spectroscopy with CCD and InGaAs spectrometers, using PLS and ANN techniques to accurately predict physicochemical characteristics of calcareous topsoil. The results showed that InGaAs spectrometer data was crucial for achieving the best predictions, while CCD device also provided acceptable predictions for certain soil properties. Variability mapping based on the best predictive models showed promising results for site-specific soil management.
SCIENTIFIC REPORTS
(2022)
Article
Remote Sensing
Emmanuelle Vaudour, Cecile Gomez, Philippe Lagacherie, Thomas Loiseau, Nicolas Baghdadi, Diego Urbina-Salazar, Benjamin Loubet, Dominique Arrouays
Summary: The spatial assessment of soil organic carbon (SOC) using Sentinel-2 satellite images is challenging due to limited applicability of spectral models on bare soils. This study compared different temporal mosaic approaches to predict SOC content, highlighting the importance of combining multiple indicators such as moisture, bare soil, and roughness for maintaining accuracy and extending coverage over larger areas.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Geosciences, Multidisciplinary
Qian Liu, Li He, Long Guo, Mengdi Wang, Dongping Deng, Pin Lv, Ran Wang, Zhongfu Jia, Zhongwen Hu, Guofeng Wu, Tiezhu Shi
Summary: The study focuses on the digital soil mapping of Soil Organic Carbon Density (SOCD) in agricultural land using different spectral data, including laboratory, airborne, and Sentinel 2 spectra. The results show that laboratory spectra perform the best in SOCD prediction, followed by airborne and Sentinel 2 spectra. The study also compared the performance of bare soil spectral indices (BSSIs) and vegetation indices (VIs) in SOCD prediction and found that BSSIs have higher accuracy. Among the three prediction models used, the deep neural network (DNN) model shows the best performance in digital soil mapping of SOCD.
Article
Multidisciplinary Sciences
Qi Song, Xiaohong Gao, Yuting Song, Qiaoli Li, Zhen Chen, Runxiang Li, Hao Zhang, Sangjie Cai
Summary: Soil texture is an important property of soil, and this study focuses on monitoring it using UAV hyperspectral data. The results show that combining UAV hyperspectral imagery with machine learning can achieve accurate estimation and mapping of soil texture. This study provides technical support and decision-making assistance for future agricultural land planning on the Tibetan Plateau.
SCIENTIFIC REPORTS
(2023)
Article
Soil Science
D. J. Burger, S. L. Bauke, W. Amelung, M. Sommer
Summary: Erosion of fertile topsoil leads to land degradation and yield loss, but a long-term field experiment in NE Germany shows that reformation of fertile topsoil and increase in crop yield is possible through good agricultural management within a few decades.
Article
Environmental Sciences
Guoru Wei, Chunlai Zhang, Qing Li, Hongtao Wang, Rende Wang, Yajing Zhang, Yixiao Yuan
Summary: Through analyzing soil samples from 12 deserts in China, it was found that Chinese deserts have a significant amount of organic carbon storage, with the Taklimakan Desert having the highest storage. Soil grain-size and element geochemistry are the main factors influencing organic carbon density in Chinese deserts, while precipitation is the main climatic factor affecting its distribution. Based on climate and vegetation cover trends in the past 20 years, Chinese deserts have a high potential for future organic carbon sequestration.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Geosciences, Multidisciplinary
Sushil Lamichhane, Lalit Kumar, Kabindra Adhikari
Summary: This study predicted and mapped the soil organic carbon content in the topsoil of the Sarlahi district in Nepal, comparing the performance of different techniques and identifying silt deposition from river systems as a key predictor for SOC content. Random Forest technique outperformed Stepwise-Multiple-Linear-Regression-Kriging in predicting SOC, indicating the importance of silt deposition in low-relief alluvial regions.
Article
Multidisciplinary Sciences
Bullo Yami, N. J. Singh, B. K. Handique, Sanjay Swami
Summary: The soil carbon sinking ability is mainly controlled by factors such as topography, soil-crop management, and traditional farming practices, which are also related to the food demand of the population. The degradation of natural resources leading to poor soil health is likely to put strain on hilly and mountain ecosystems. This study utilizes geospatial tools and techniques to map the distribution of soil organic carbon (SOC) in rice-fallow systems with varying slopes and investigate its changes over the past 20 years under traditional management practices. Regression models of SOC were developed using remote sensing (RS)-based indices, with the MLR-stepwise model performing the best in terms of SOC prediction.
Article
Engineering, Environmental
Liyang Yang, Yu Chen, Jiajun Lei, Zhuoyi Zhu
Summary: Sediment organic matter plays an important role in the biogeochemical cycling of carbon, nutrients, and pollutants in the coastal environment, which is increasingly affected by aquaculture activities. However, it is challenging to identify aquaculture signals in sediment organic matter in complex coastal environments. This study used multiple analytical methods to investigate sediment in a shellfish and algae culture area in Southeast China, and found that the quantity and composition of organic matter were correlated with grain size. Optical analysis provided valuable indices for assessing the quantity of organic matter. The study also revealed that aquaculture had limited influence on sediment organic matter in the study area, indicating the sustainability of these aquaculture practices. The results have implications for understanding biogeochemical processes and ecosystem sustainability in coastal environments with intense aquaculture activities.
Article
Computer Science, Information Systems
Yayu Yang, Kun Shang, Chenchao Xiao, Changkun Wang, Hongzhao Tang
Summary: Estimation of soil organic matter content (SOMC) is essential for soil quality evaluation. This study analyzed and evaluated the SOMC-related spectral indices suitable for the ZY1-02D satellite and successfully applied them to SOMC mapping and estimation.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Agriculture, Multidisciplinary
Jie Wang, Dongxue Zhao, Ehsan Zare, Michael Sefton, John Triantafilis
Summary: This study explores various models to predict soil organic carbon, and finds that the hybrid models RFRK and SVMRK perform the best in terms of prediction accuracy. The DSM using RFRK provides a method for farmers to determine nitrogen fertilizer rates based on soil conditions, resulting in a potential decrease in fertilizer application cost.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Review
Environmental Sciences
Emmanuelle Vaudour, Asa Gholizadeh, Fabio Castaldi, Mohammadmehdi Saberioon, Lubos Boruvka, Diego Urbina-Salazar, Youssef Fouad, Dominique Arrouays, Anne C. Richer-de-Forges, James Biney, Johanna Wetterlind, Bas Van Wesemael
Summary: This review paper focuses on the satellite-based spectral approaches for assessing soil organic carbon (SOC) in various geographical contexts. Most studies have been conducted in temperate croplands in Europe, China, and North America, with dry combustion and wet oxidation being the commonly used methods for SOC determination. The findings suggest that satellite-derived SOC spectral models, particularly under bare soil conditions, have the potential for further investigations. However, there is a need for future research on deep learning methods, performance evaluations, and uncertainty analysis of spatial model predictions.
Article
Geosciences, Multidisciplinary
Yongsheng Hong, Jonathan Sanderman, Tomislav Hengl, Songchao Chen, Nan Wang, Jie Xue, Zhiqing Zhuo, Jie Peng, Shuo Li, Yiyun Chen, Yaolin Liu, Abdul Mounem Mouazen, Zhou Shi
Summary: This study used a globally distributed topsoil MIR spectral library to predict SOC using different modeling methods. The results showed that fractional-order derivatives (FODs) improved the prediction accuracy of SOC. The 0.75-order derivative was found to be optimal for ratio index-based linear regression (RI-LR) models, while the convolutional neural network (CNN) model outperformed other models for full-spectrum modeling.
Article
Environmental Sciences
Caroline C. Womack, Katherine M. Manfred, Nicholas L. Wagner, Gabriela Adler, Alessandro Franchin, Kara D. Lamb, Ann M. Middlebrook, Joshua P. Schwarz, Charles A. Brock, Steven S. Brown, Rebecca A. Washenfelder
Summary: The study used an enhanced spectrometer to retrieve the optical properties of biomass burning aerosol, demonstrating high sensitivity of the technique to constrain the optical properties of brown carbon aerosol but presenting challenges for fresh smoke dominated by black carbon aerosol. The accuracy of Mie theory retrievals decreases as the fraction of black carbon mass increases.
ATMOSPHERIC CHEMISTRY AND PHYSICS
(2021)
Review
Geosciences, Multidisciplinary
Jesus Ruiz-Fernandez, Marc Oliva, Daniel Nyvlt, Nicoletta Cannone, Cristina Garcia-Hernandez, Mauro Guglielmin, Filip Hrbacek, Matej Roman, Susana Fernandez, Jeronimo Lopez-Martinez, Dermot Antoniades
EARTH-SCIENCE REVIEWS
(2019)
Article
Chemistry, Analytical
Javier F. Calleja, Alejandro Corbea-Perez, Susana Fernandez, Carmen Recondo, Juanjo Peon, Miguel Angel de Pablo
Article
Astronomy & Astrophysics
A. Castro-Gonzalez, E. Diez Alonso, J. Menendez Blanco, J. Livingston, J. P. de Leon, J. Lillo-Box, J. Korth, S. Fernandez Menendez, J. M. Recio, F. Izquierdo-Ruiz, A. Coya Lozano, F. Garcia de la Cuesta, N. Gomez Hernandez, J. R. Vidal Blanco, R. Hevia Diaz, R. Pardo Silva, S. Perez Acevedo, J. Polancos Ruiz, P. Padilla Tijerin, D. Vazquez Garcia, S. L. Suarez Gomez, F. Garcia Riesgo, C. Gonzalez Gutierrez, L. Bonavera, J. Gonzalez-Nuevo, C. Rodriguez Pereira, F. Sanchez Lasheras, M. L. Sanchez Rodriguez, R. Muniz, J. D. Santos Rodriguez, F. J. de Cos Juez
Summary: The K2-OjOS project, a collaboration between professional and amateur astronomers, identified four new planets and 14 planet candidates, improving the precision of transit ephemeris using a combination of archival and new data. Some systems exhibited features related to period commensurabilities, while new single transits and uncertain signal origins were also detected.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2022)
Article
Environmental Sciences
Alejandro Corbea-Perez, Javier F. Calleja, Carmen Recondo, Susana Fernandez
Summary: This study compared MODIS albedo products over Antarctica with in situ data, finding that MOD10A1 had the best correlation in clear-sky conditions. It also concluded that MODIS products can accurately describe the trend of in situ albedo data.
Article
Environmental Sciences
Carmen Recondo, Alejandro Corbea-Perez, Juanjo Peon, Enrique Pendas, Miguel Ramos, Javier F. Calleja, Miguel Angel de Pablo, Susana Fernandez, Jose Antonio Corrales
Summary: In this article, empirical models for estimating daily mean air temperature in the Hurd Peninsula of Livingston Island (Antarctica) were presented using MODIS LST data and spatiotemporal variables. The models were obtained and validated using in situ meteorological stations' data and MODIS data. The results showed that the models were accurate and useful for estimating long-term trends in air temperature.
Article
Water Resources
C. Allende-Prieto, J. Roces-Garcia, C. Recondo, L. A. Sanudo-Fontaneda, M. R. Gonzalez-Moradas
Summary: Monitoring Sustainable Drainage Systems (SuDS) often requires intrusive methods and onsite personnel. Remote sensing in SuDS, especially vegetation-based techniques, still requires further development. This study proposes an exploratory method combining Synthetic Aperture Radar (SAR) images and onsite measurements to develop performance models. Linear regression models were used to compute soil moisture, with variables such as backscatter coefficient (& sigma;& DEG;), temperature, normalized difference vegetation index (NDVI), and topographic wetness index (TWI). The models showed medium to high predictive capacity, ranging from 0.53 to 0.66, with temperature being the most influential variable. This research opens the path for future use of remote sensing tools in vegetation-based SuDS monitoring, highlighting the need for further research.
URBAN WATER JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Javier F. Calleja, Ruben Muniz, Susana Fernandez, Alejandro Corbea-Perez, Juanjo Peon, Jaime Otero, Francisco Navarro
Summary: The study characterized the snow albedo decay over Hurd Peninsula, Livingston Island, Antarctica from 2000 to 2016. It found that the albedo decay typically starts in late September and lasts for about 96 days.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Geography, Physical
M. A. De Pablo, J. J. Jimenez, M. Ramos, M. Prieto, A. Molina, G. Vieira, M. A. Hidalgo, S. Fernandez, C. Recondo, J. F. Calleja, J. J. Peon, A. Corbea-Perez, C. N. Maior, M. Morales, C. Mora
CUADERNOS DE INVESTIGACION GEOGRAFICA
(2020)