Spatio-Temporal Analysis of Heavy Metals in Arid Soils at the Catchment Scale Using Digital Soil Assessment and a Random Forest Model

• Published in: Remote sensing (Basel, Switzerland) Vol. 13; no. 9; p. 1698
• Main Authors: Taghizadeh-Mehrjardi, Ruhollah, Fathizad, Hassan, Ali Hakimzadeh Ardakani, Mohammad, Sodaiezadeh, Hamid, Kerry, Ruth, Heung, Brandon, Scholten, Thomas
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 27.04.2021
• Subjects: algorithms; Arid regions; Arid zones; Catchment scale; Chemical contaminants; Contaminants; Contamination; Digital Elevation Models; digital soil mapping; Geology; georeferencing; Groundwater; Heavy metals; Hypercubes; Industrial development; Iran; Land use; Latin hypercube sampling; Lead; machine learning; Manganese; Metals; Nickel; Pollutants; Pollution control; Pollution sources; random forest; Remote sensing; Salinity; Sampling methods; Sediments; soil absorbable heavy metals; Soil contamination; Soil pollution; Soils; Spatial distribution; Temporal distribution; Trends; watersheds; Iran

Predicting the spatio-temporal distribution of absorbable heavy metals in soil is needed to identify the potential contaminant sources and develop appropriate management plans to control these hazardous pollutants. Therefore, our aim was to develop a model to predict soil adsorbable heavy metals in...