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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 R 2 = 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.

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the earth's surface dynamics provide essential information for guiding environmental and agricultural policies. Uncovered and unprotected surfaces experience several undesirable effects, which can affect soil ecosystem functions. We developed a technique to identify global bare surface areas and their dynamics based on multitemporal remote sensing images to aid the spatiotemporal evaluation of anthropic and natural phenomena. The bare Earth's surface and its changes were recognized by Landsat image processing over a time range of 30 years using the Google Earth Engine platform. Two additional products were obtained with a similar technique: a) Earth's bare surface frequency, which represents where and how many times a single pixel was detected as bare surface, based on Landsat series, and b) Earth's bare soil tendency, which represents the tendency of bare surface to increase or decrease. This technique enabled the retrieval of bare surfaces on 32% of Earth's total land area and on 95% of land when considering only agricultural areas. From a multitemporal perspective, the technique found a 2.8% increase in bare surfaces during the period on a global scale. However, the rate of soil exposure decreased by ~4.8% in the same period. The increase in bare surfaces shows that agricultural areas are increasing worldwide. The decreasing rate of soil exposure indicates that, unlike popular opinion, more soils have been covered due to the adoption of conservation agriculture practices, which may reduce soil degradation. Soils are directly related to global issues, such as food supply, water security and climate regulation 1-4. Considering that soil health is easily disturbed by modifications of physical, chemical and biological conditions, soil management must be carefully delineated and constantly monitored 5. The high occurrence of bare surfaces in agricultural areas may increase soil degradation, influencing soil health and affecting important ecosystem functions 6. Surface exposure triggers a sequence of events, which may result in soil erosion 7 , contamination 8 , desertification 9 , salinization 10 , acidification 11 , compaction 12 , biodiversity loss 13 , nutrient depletion 14 , and loss of soil organic carbon (SOC) 15. Despite the need to preserve soil ecosystems for future generations, we will still need to feed 9.7 billion people by the middle of this century 16. To date, the total area of worldwide crop and pasture lands is estimated at 49 million km 2 , which represents approximately 30% of the total global land area 17. The world's future demand for water, energy and food is closely related to the intensification of agriculture and the preservation of ecosystems. Sustainable land use requires data-driven policymaking and management strategies, which are currently hampered by the high cost and time-consuming characteristics of soil data acquisition 2. The remote sensing (RS) technique is an indispensable tool for multitemporal and spatial data acquisition, as it enables the collection of soil information at gl...