Application of orbital cross-sensor techniques for detection and characterization of spatial-temporal changes of relative phytomass in sugar cane parcels

Abstract

The sugarcane crop has great importance for the Brazilian economy and currently, São Paulo State is the largest producer in the country. Over the last years, the pace of technological change has increased and remote sensing images have been widely used for the study of the sugarcane areas. However, the use of these images is restricted to scientific researches and it's barely applied in sugarcane production system due the complexity of the methods, techniques and incompatible results scale. The objective of this project is to introduce the effective use of remote sensing products in the sugarcane production system with the establishment of a methodology to detect and characterize the spatial and temporal changes of the relative biomass in sugarcane parcels. A change detection and multisensor approach will be employed to monitor crop development in a suitable scale with a high temporal frequency. This research assumes that the systematic monitoring of phenological development of the sugarcane field, fulfilled with high temporal frequency, can provide important quantitative indicators for characterization and evaluation of plant health and tillage quality, contributing to the productivity and longevity of the crop. The results of this study will assist the identification of low productivity areas with speed and precision, providing quantitative and qualitative indicators for specific interventions in the field. Through the systematic knowledge of the development curve of sugarcane culture, it can work proactively to estimate agricultural productivity, providing greater reliability in the values combined with low operating costs. Thus, this research proposal is an alternative for identification of inadequate management or biotic/abiotic interference that decrease the productivity of sugarcane parcels. In addition, it is emphasized that the confirmation of the viability of the proposed methodology will enable these procedures to be expanded to monitoring other agricultural commodities. (AU)