Tropical Texture Determination by Proximal Sensing Using a Regional Spectral Library and Its Relationship with Soil Classification

Marilusa Lacerda,Caio Fongaro,Arnaldo Souza,Marcus Sato,José Demattê,Bruna Gallo

doi:10.3390/rs8090701

Marilusa Lacerda, Caio Fongaro + Show 4 more

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https://doi.org/10.3390/rs8090701

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Abstract

The search for sustainable land use has increased in Brazil due to the important role that agriculture plays in the country. Soil detailed classification is related with texture attribute. How can one discriminate the same soil class with different textures using proximal soil sensing, as to reach surveys, land use planning and increase crop productivity? This study aims to evaluate soil texture using a regional spectral library and its usefulness on classification. We collected 3750 soil samples covering 3 million ha within strong soil class variations in São Paulo State. The spectral analyses of soil samples from topsoil and subsoil were measured in laboratory (400–2500 nm). The potential of a regional soil spectral library was evaluated on the discrimination of soil texture. We considered two types of soil texture systems, one related with soil classification and another with soil managements. The soil line technique was used to assess differentiation between soil textural groups. Soil spectra were summarized by principal component analysis (PCA) to select relevant information on the spectra. Partial least squares regression (PLSR) was used to predict texture. Spectral curves indicated different shapes according to soil texture and discriminated particle size classes from clayey to sandy soils. In the visible region, differences were small because of the organic matter, while the short wave infrared (SWIR) region showed more differences; thus, soil texture variation could be differentiated by quartz. Angulation differences are on a spectral curve from NIR to SWIR. The statistical models predicted clay and sand levels with R2 = 0.93 and 0.96, respectively. Indeed, we achieved a difference of 1.2% between laboratory and spectroscopy measurement for clay. The spectral information was useful to classify Ferralsols with different texture classification. In addition, the spectra differentiated Lixisols from Ferralsols and Arenosols. This work can help the development of computer programs that allow soil texture classification and subsequent digital soil mapping at detailed scales. In addition, it complies with requirements for sustainable land use and soil management.

Highlights

Brazil is one of the world’s largest producers of agricultural goods
The soil samples were ordered by the simplified textural group according to SiBCS [4] and the system used in the management of land use (Figure 2a,b)
The texture classes from each group were represented by the average of spectral responses from 350 to 2500 nm

Summary

Introduction

Brazil is one of the world’s largest producers of agricultural goods. Sustainable land use is the basis to ensure soil quality. The increasing demand for food and renewable energy sources has required intensive land use, which in turn promotes disorderly land occupation, often driven by economic factors. This occupation may affect soil quality and compromise its potential for agricultural use. Detailed knowledge of pedological classes through mapping associated with climate information plays an important role in land use planning. This information provides the basis for the development of agricultural projects by identifying suitable areas for agricultural crops and contributing to soil conservation. It gives technical classification of soils (agricultural capacity, and land use capacity) [1]

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