Preston Thomas Sorenson, J. Kiss, A. Bedard-Haughn
{"title":"Improved parent material map disaggregation methods in the Saskatchewan prairies using historical bare soil composite imagery","authors":"Preston Thomas Sorenson, J. Kiss, A. Bedard-Haughn","doi":"10.1139/cjss-2021-0154","DOIUrl":null,"url":null,"abstract":"Abstract The major drivers of soil variation in Saskatchewan at scales finer than the existing soil maps are parent material variance, slope position, and salinity. There is therefore a need to generate finer-scale parent material maps as part of updating soil maps in Saskatchewan. As spatially referenced soil point data are lacking in Saskatchewan, predictive soil mapping methods that disaggregate existing soil parent material maps are required. This study focused on investigating important environmental covariates to use in parent material disaggregation, particularly bare soil composite imagery (BSCI). Synthetic point observations were generated using an area-proportional approach based on existing soil survey polygons and a random forest model was trained with those synthetic observations to predict parent material classes. Including BSCI as environmental covariates increased model accuracy from 0.38 to 0.52 and the model Kappa score from 0.19 to 0.35 compared with models where it was not included. Models that included training points from all locations, regardless of whether BSCI was available, and included BSCI as environmental covariates had similar results to the BSCI model with an accuracy of 0.48 and a Kappa value of 0.30. Based on these results, BSCI is an important covariate for parent material disaggregation in the Saskatchewan Prairies. Future work to disaggregate soil classes based on slope position and salinity, and to combine those methods with parent material disaggregation is needed to generate detailed soil maps for the Canadian Prairies.","PeriodicalId":9384,"journal":{"name":"Canadian Journal of Soil Science","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2022-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Canadian Journal of Soil Science","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1139/cjss-2021-0154","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"SOIL SCIENCE","Score":null,"Total":0}
引用次数: 1
Abstract
Abstract The major drivers of soil variation in Saskatchewan at scales finer than the existing soil maps are parent material variance, slope position, and salinity. There is therefore a need to generate finer-scale parent material maps as part of updating soil maps in Saskatchewan. As spatially referenced soil point data are lacking in Saskatchewan, predictive soil mapping methods that disaggregate existing soil parent material maps are required. This study focused on investigating important environmental covariates to use in parent material disaggregation, particularly bare soil composite imagery (BSCI). Synthetic point observations were generated using an area-proportional approach based on existing soil survey polygons and a random forest model was trained with those synthetic observations to predict parent material classes. Including BSCI as environmental covariates increased model accuracy from 0.38 to 0.52 and the model Kappa score from 0.19 to 0.35 compared with models where it was not included. Models that included training points from all locations, regardless of whether BSCI was available, and included BSCI as environmental covariates had similar results to the BSCI model with an accuracy of 0.48 and a Kappa value of 0.30. Based on these results, BSCI is an important covariate for parent material disaggregation in the Saskatchewan Prairies. Future work to disaggregate soil classes based on slope position and salinity, and to combine those methods with parent material disaggregation is needed to generate detailed soil maps for the Canadian Prairies.
期刊介绍:
The Canadian Journal of Soil Science is an international peer-reviewed journal published in cooperation with the Canadian Society of Soil Science. The journal publishes original research on the use, management, structure and development of soils and draws from the disciplines of soil science, agrometeorology, ecology, agricultural engineering, environmental science, hydrology, forestry, geology, geography and climatology. Research is published in a number of topic sections including: agrometeorology; ecology, biological processes and plant interactions; composition and chemical processes; physical processes and interfaces; genesis, landscape processes and relationships; contamination and environmental stewardship; and management for agricultural, forestry and urban uses.