Pedology and digital soil map** (DSM)

Y Ma, B Minasny, BP Malone… - European Journal of …, 2019‏ - Wiley Online Library
Pedology focuses on understanding soil genesis in the field and includes soil classification
and map**. Digital soil map** (DSM) has evolved from traditional soil classification and …

Conventional and digital soil map** in Iran: Past, present, and future

M Zeraatpisheh, A Jafari, MB Bodaghabadi, S Ayoubi… - Catena, 2020‏ - Elsevier
Demand for accurate soil information is increasing for various applications. This paper
investigates the history of soil survey in Iran, particularly more recent developments in the …

Machine learning in precision agriculture: a survey on trends, applications and evaluations over two decades

S Condran, M Bewong, MZ Islam, L Maphosa… - IEEE …, 2022‏ - ieeexplore.ieee.org
Precision agriculture represents the new age of conventional agriculture. This is made
possible by the advancement of various modern technologies such as the internet of things …

Machine learning for predicting soil classes in three semi-arid landscapes

CW Brungard, JL Boettinger, MC Duniway, SA Wills… - Geoderma, 2015‏ - Elsevier
Map** the spatial distribution of soil taxonomic classes is important for informing soil use
and management decisions. Digital soil map** (DSM) can quantitatively predict the spatial …

Soil map**, classification, and pedologic modeling: History and future directions

EC Brevik, C Calzolari, BA Miller, P Pereira, C Kabala… - Geoderma, 2016‏ - Elsevier
Soil map**, classification, and pedologic modeling have been important drivers in the
advancement of our understanding of soil from the earliest days of the scientific study of …

Digital map** of soil organic carbon using ensemble learning model in Mollisols of Hyrcanian forests, northern Iran

S Tajik, S Ayoubi, M Zeraatpisheh - Geoderma Regional, 2020‏ - Elsevier
This study was conducted to evaluate the efficacy of the ensemble machine learning model
to predict the spatial variation of soil organic carbon (SOC) concentration in a deciduous …

Comparing the efficiency of digital and conventional soil map** to predict soil types in a semi-arid region in Iran

M Zeraatpisheh, S Ayoubi, A Jafari, P Finke - Geomorphology, 2017‏ - Elsevier
The efficiency of different digital and conventional soil map** approaches to produce
categorical maps of soil types is determined by cost, sample size, accuracy and the selected …

Novel ensembles of COPRAS multi-criteria decision-making with logistic regression, boosted regression tree, and random forest for spatial prediction of gully erosion …

A Arabameri, M Yamani, B Pradhan, A Melesse… - Science of the total …, 2019‏ - Elsevier
Gully erosion is considered as a severe environmental problem in many areas of the world
which causes huge damages to agricultural lands and infrastructures (ie roads, buildings …

The effectiveness of digital soil map** to predict soil properties over low-relief areas

Z Mosleh, MH Salehi, A Jafari, IE Borujeni… - Environmental …, 2016‏ - Springer
This study investigates the ability of different digital soil map** (DSM) approaches to
predict some of physical and chemical topsoil properties in the Shahrekord plain of …

Updating soil survey maps using random forest and conditioned Latin hypercube sampling in the loess derived soils of northern Iran

MRP Rad, N Toomanian, F Khormali, CW Brungard… - Geoderma, 2014‏ - Elsevier
Many Iranian soil surveys need to be updated. Conventional soil survey methods are
expensive and time-consuming. Digital soil map** (DSM) can be used for updating soil …