University of Tehran | Iran
Zahra Rasaei is a soil scientist specializing in Digital Soil Mapping, legacy soil inventories, soil classification, and clay mineralogy. She holds a PhD in Digital Soil Mapping and has conducted extensive research on integrating legacy soil data with modern geospatial and Bayesian statistical techniques to improve the accuracy of soil property and soil class predictions in Iran. Her work focuses on spatial filtering, Bayesian data fusion, land evaluation, and soil genesis, contributing to the modernization of Iran’s soil information systems. She has authored 6 scientific publications, with an h-index of 4 and 68 citations, reflecting her growing influence in pedometrics and geospatial soil science. Her research experience spans digital soil modeling, remote-sensing data integration, and the rescue of old soil survey inventories for national soil mapping. She has also served as a peer reviewer for the Journal of South American Earth Sciences. Her research interests include soil salinity prediction, zero-inflated data modeling, DEM-based covariate analysis, and improved soil classification frameworks. Although early in her career, she has made significant contributions to digital soil mapping methodologies, and her work supports soil-resource management and sustainable land-use planning. Overall, she is a promising researcher advancing modern soil-mapping science.
Featured Publications
Rasaei, Z., Sarmadian, F., Jafari, A., & Flynn, T. (2025). Digital mapping of soil salinity: Overcoming the challenges of zero-inflated and skewed sample distributions. Pedosphere.
Rasaei, Z., Rossiter, D. G., & Farshad, A. (2020). Rescue and renewal of legacy soil resource inventories in Iran as an input to digital soil mapping. Geoderma Regional, 21, e00262.
Rasaei, Z., & Bogaert, P. (2019). Spatial filtering and Bayesian data fusion for mapping soil properties: A case study combining legacy and remotely sensed data in Iran. Geoderma, 344, 50–62.
Rasaei, Z., & Bogaert, P. (2019). Bayesian data fusion for combining maps of predicted soil classes: A case study using legacy soil profiles and DEM covariates in Iran. Catena, 182, 104138.
Rasaei, Z., Sarmadian, F., & Jafari, A. (2019). Comparison of fertility capability and taxonomic classification systems to classify soil map units in parts of Chaharmahal-va-Bakhtiari Province. Desert.