期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2020
卷号：IV-3-W2-2020
页码：25-28
DOI：10.5194/isprs-annals-IV-3-W2-2020-25-2020
语种：English
出版社：Copernicus Publications
摘要：Gypsum-rich material covers the hillslopes above sim;thinsp;1000thinsp;m of the Atacama and forms the particular landscape. In this contribution, we evaluate random forest-based analysis in order to predict the gypsum distribution in a specific area of sim;thinsp;3000thinsp;kmsup2/sup, located in the hyperarid core of the Atacama. Therefore, three different sets of input variables were chosen. These variables reflect the different factors forming soil properties, according to digital soil mapping. The variables are derived from indices based on imagery of the ASTER and Landsat-8 satellite, geomorphometric parameters based on the Tandem-X World DEMtrade;, as well as selected climate variables and geologic units. These three different models were used to evaluate the Ca-content derived from soil surface samples, reflecting gypsum content. All three different models derived high values of explained variation (rsup2/supthinsp;gt;thinsp;0.886), the RMSE is sim;thinsp;4500thinsp;mg∙kgsupminus;1/sup and the NRMSE is sim;thinsp;6%. Overall, this approach shows promising results in order to derive a gypsum content prediction for the whole Atacama. However, further investigation on the independent variables need to be conducted. In this case, the ferric oxides index (representing magnetite content), slope and a temperature gradient are the most important factors for predicting gypsum content.
