Results 11 to 20 of about 131 (110)

Advancing Soil Organic Carbon Prediction: A Comprehensive Review of Technologies, AI, Process-Based and Hybrid Modelling Approaches. [PDF]

Adv Sci (Weinh)
This review highlights advances in soil organic carbon (SOC) quantification using remote sensing, proximal soil sensing, AI (ML and DL), and biogeochemical modelling. Integrating diverse data sources and models improves SOC prediction accuracy. Key priorities include enhancing data availability, refining models, incorporating microbial processes, and ...
Ding Z, Liu K, Grunwald S, Smith P, Ciais P, Wang B, Wadoux AMJ, Ferreira C, Karunaratne S, Shurpali N, Yin X, Roberts D, Madgett O, Duncan S, Zhou M, Liu Z, Harrison MT.   +16 more
europepmc   +2 more sources

Diffuse Reflectance Spectroscopy for Mapping Soil Carbon Stock in the Gilbués Desertification Region at Brazilian Cerrado

Land, 2023
The carbon stock (C Stock) is a key soil attribute, especially in areas under degradation. The objective of this study was to map the C Stock and other physical and chemical attributes on the soil surface of a micro-watershed located in the Gilbués ...
Julio César Galdino de Sousa, Yuri Jacques Agra Bezerra da Silva, Vanessa Martins, Sueli Rodrigues, Marcos Paulo Rodrigues Teixeira, Paulo Henrique Dalto, Laércio Vieira de Melo Wanderley Neves, Antonio Rafael Sánchez-Rodríguez, Ronny Sobreira Barbosa   +8 more
doaj   +1 more source

Australian soil microbiome: A first sightseeing regional prediction driven by cycles of soil temperature and pedogenic variations

Molecular Ecology, Volume 32, Issue 23, Page 6243-6259, December 2023., 2023
Abstract Declines in soil multifunctionality (e.gsoil capacity to provide food and energy) are closely related to changes in the soil microbiome (e.g., diversity) Determining ecological drivers promoting such microbiome changes is critical knowledge for protecting soil functions.
Vanessa Pino, Mario Fajardo, Alex McBratney, Budiman Minasny, Neil Wilson, Chris Baldock   +5 more
wiley   +1 more source

3–4D soil model as challenge for future soil research: Quantitative soil modeling based on the solid phase

Journal of Plant Nutrition and Soil Science, Volume 185, Issue 6, Page 720-744, December 2022., 2022
Abstract A 3–4D soil model represents a logical step forward from one‐dimensional soil columns (1D), two‐dimensional soil maps (2D), and three‐dimensional soil volumes (3D) toward dynamic soil models (4D), with time as the fourth dimension. The challenge is to develop modeling tools that account for the states of soil properties, including the spatial ...
Horst H. Gerke, Hans‐Jörg Vogel, Tobias K.D. Weber, W. Marijn van der Meij, Thomas Scholten   +4 more
wiley   +1 more source

Assessment of global, national and regional‐level digital soil mapping products at different spatial supports

European Journal of Soil Science, Volume 73, Issue 5, September–October 2022., 2022
Abstract Digital soil mapping provides estimates of soil properties and, in turn, an understanding of the spatial variation in soil across landscapes. In recent years, several digital soil mapping products have been released across the world. An end user in New South Wales (NSW), Australia, could choose between a global product (SoilGrids), a national ...
Si Yang Han, Patrick Filippi, Kanika Singh, Brett M. Whelan, Thomas F. A. Bishop   +4 more
wiley   +1 more source

Topsoil Texture Regionalization for Agricultural Soils in Germany—An Iterative Approach to Advance Model Interpretation

Frontiers in Soil Science, 2022
Site-specific spatially continuous soil texture data is required for many purposes such as the simulation of carbon dynamics, the estimation of drought impact on agriculture, or the modeling of water erosion rates.
Anika Gebauer, Ali Sakhaee, Axel Don, Matteo Poggio, Mareike Ließ   +4 more
doaj   +1 more source

Mapping depth to Pleistocene sand with Bayesian generalized linear geostatistical models

European Journal of Soil Science, Volume 73, Issue 1, January–February 2022., 2022
Abstract Spatial soil applications frequently involve binomial variables. If relevant environmental covariates are available, using a Bayesian generalized linear model (BGLM) might be a solution for mapping such discrete soil properties. The geostatistical extension, a Bayesian generalized linear geostatistical model (BGLGM), adds spatial dependence ...
Luc Steinbuch, Dick J. Brus, Gerard B. M. Heuvelink   +2 more
wiley   +1 more source

Mapping soil carbon, particle-size fractions, and water retention in tropical dry forest in Brazil [PDF]

Pesquisa Agropecuária Brasileira, 2016
The objective of this work was to compare ordinary kriging with regression kriging to map soil properties at different depths in a tropical dry forest area in Brazil.
Gustavo Mattos Vasques, Maurício Rizzato Coelho, Ricardo Oliveira Dart, Ronaldo Pereira Oliveira, Wenceslau Geraldes Teixeira   +4 more
doaj   +2 more sources

Pedometric Mapping of Soil Classes: A Case Study of San Mateo de Otao, Peru

Applied and Environmental Soil Science, Volume 2022, Issue 1, 2022., 2022
Conventional soil maps are designed based on expert criteria, a characteristic that reduces their reproducibility and generates subjective uncertainty. Pedometric mapping uses mathematical and statistical principles, which makes it the opposite of conventional mapping.
Carlos J. Mestanza, Julio C. Nazario, Balram Ambade   +2 more
wiley   +1 more source

Regenerative agriculture and integrative permaculture for sustainable and technology driven global food production and security

Agronomy Journal, Volume 113, Issue 6, Page 4541-4559, November/December 2021., 2021
Abstract A growing world population and increases in food and energy consumption have placed production agriculture in a difficult situation. The rapid growth in food production through specialized operations such as monoculture cropping systems has aligned to satisfy increases in demand for food and fiber.
Everald McLennon, Biswanath Dari, Gaurav Jha, Debjani Sihi, Vanaja Kankarla   +4 more
wiley   +1 more source