Hyperspectral remote sensing in laboratory, field and airborne levels as auxiliary tools in soil management

Author(s)

Marston Héracles Domingues Franceschini

• Document type: Master's Dissertation
• Press: Piracicaba.
• Institution: Universidade de São Paulo (USP). Escola Superior de Agricultura Luiz de Queiroz (ESALA/BC)
• Defense date: 2013-04-11

Examining board members

Jose Alexandre Melo Dematte; Jose Paulo Molin; Luiz Eduardo Vicente

• Advisor: Jose Alexandre Melo Dematte

Abstract

Agricultural production has increased in the last years stimulated by the population growth and technological advances. This can cause significant environmental impacts including soil degradation if suitable agricultural planning and soil management are not applied in order to ensure a competitive and sustainable production. For this purpose, the soil variability assessment is needed and it is conventionally performed through soil sampling and analysis. However, conventional methods have high costs and require considerable time and labor. When the amount of information needed increases, costs to describe soil spatial variability may become an obstacle if only conventional methodologies are applied. Therefore, alternative methods can help to depict soil properties variability on a scale suitable to soil management. So, Vis-NIR-SWIR reflectance spectroscopy (from 400 nm to 2500 nm) is proposed as a mean to predict soil properties. This is possible because spectral information has a direct relationship with soil constituents and characteristics. Therefore, in this study hyperspectral airborne imagery is evaluated as an information source to be used in soil properties quantification, via the PLSR method, and mapping, using kriging. The performance of the models derived from airborne imagery data was compared with the results obtained by models calculated from laboratory sensor data. The use of spectral information collected in the field (on-thego) was evaluated too using a field experiment in witch different rates of lime were applied. The experiment was allocated in two fields with different soil textures (one with about 100 g kg-1 of clay and other with about 320 g kg-1 of clay). The soil properties prediction based on the on-the-go spectral measurements were compared to predictions made using spectra collect in the laboratory and the PLSR method was used to calculate models. Satisfactory results were obtained with airborne sensor data, especially for clay, sand and CTC quantification (R2 of 0.73, 0.73 and 0.80, respectively). Regarding the on-the-go proximal sensing, better predictions were obtained for the clayey area, with R2 of 0.33, 0.38 and 0.61 for predictions of CEC, base saturation of the soil CEC (V%) and lime requirement, respectively. (AU)

• FAPESP's process: 11/04232-8 - Hyperspectral remote sensing in laboratory, field and airborne levels as auxiliary tools in soil management
• Grantee: Marston Héracles Domingues Franceschini
• Support Opportunities: Scholarships in Brazil - Master