Short Course Description
Soil and Plant spectroscopy from laboratory to satellite towards agriculture optimization
Executer: Prof. Jose Alexandre Dematte (Full Prof. Remote sensing and soils), University of São Paulo, Brazil
Open: to MSc students (and higher) with Introduction to Remote Sensing or equivalent background course.
Duties: Full attendees, Exam and Exercise
Scope: A theoretical course combined with practical exercises and laboratory work. Softwares: Qgis, R, Alrad.
Contents
· Fundamentals on soil characterization, mapping and its importance for community. The link with the soil sensing dicipline.
· Fundamentals of Soil spectroscopy (VIS-NIS-SWIR-MWIR-LWIR), its importance for soil analysis, state of art and perspectives.
· Soil spectral Library (SSL) : notation, definition, global coverage and limitation.
· A Soil Spectroscopy program on to insert/train wet soil laboratories into the new soil sensing era. Results and experience of the Brazilian Program of Soil Analysis via spectroscopy: importance for the community (food safety issues).
· Fundamentals of sensors in the electromagnetic spectrum and its state of art for soils and agriculture (gamma, x-ray fluorescence, ultraviolet, vis-nir, swir, mir, thermal, magnetic susceptibility, electric conductivity). A comparison between fundamentals of the wet laboratory and spectroscopy, including LIBS technology.
· Exploiting the SSL for field and remote sensing arena: problems solutions and practical utilization.
· Detailed descriptive analysis of soil spectra.
· Fundamentals of plant spectroscopy, its importance, state of art and perspectives and limitation
· A general review of available spectral data bases of plants
· Detection of bare soil by satellite images. Soil and plant image patterns based on color compositions and enhancement
· Remote (UVA, aerial-AISA, satellite-Landsat, Sentinel) and Proximal (laboratory, field, tractor) sensing applied to agriculture, present, future and limitations. Image and spectral signatures interpretation of soil and plant related to their composition. Data mining methods.
· A case study of the relationship between soil and plant spectra via images (VIS-NIR and thermal) plus field electrical conductivity on productivity.
· Image interpretation of objects, plants, soils types and agriculture management. From multi to hyperspectral sensing. Exploitation image data from air and space for soil mapping.
· Vegetation indices and spectral related productivity.
· Strategies on how to use spectral tools for soil management (e.g. degradation and fertilization).
· The soil sensing cycle and its powerful information for community.
Full Syllabus