Soil Color and Mineralogy Mapping Using Proximal and Remote Sensing in Midwest Brazil

• Published in: Remote sensing (Basel, Switzerland) Vol. 12; no. 7; p. 1197
• Main Authors: Poppiel, Raúl Roberto, Lacerda, Marilusa Pinto Coelho, Rizzo, Rodnei, Safanelli, José Lucas, Bonfatti, Benito Roberto, Silvero, Nélida Elizabet Quiñonez, Demattê, José Alexandre Melo
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2020
• Subjects: Accuracy; aluminum oxide; Brazil; Cartography; Clay minerals; Climatic data; Color; data mining; derivative spectra; Diagnostic systems; expert opinion; Google Earth Engine; Hematite; Iron; Laboratories; Landsat; Landsat satellites; Machine learning; Mapping; meteorological data; Mineralogy; Minerals; Munsell color system; prediction; Reflectance; reflectance spectroscopy; Remote sensing; soil color; Soil mapping; Soil sciences; Soil types; Soils; spatial data; Spectra; Spectral bands; Spectrum analysis; subsoil; Subsoils; Topsoil; vegetation; Brazil; Cerrado Biome

Soil color and mineralogy are used as diagnostic criteria to distinguish different soil types. In the literature, 350–2500 nm spectra were successfully used to predict soil color and mineralogy, but these attributes currently are not mapped for most Brazilian soils. In this paper, we provided the fi...