Clustering analysis applied to NDVI/NOAA multitemporal images to improve the monitoring process of sugarcane crops

Author

Romani, L.A.S. ; Gonçalves, R. R V ; Amaral, B.F. ; Chino, D.Y.T. ; Zullo, J., Jr. ; Traina, C., Jr. ; Sousa, E.P.M. ; Traina, A.J.M.

Author_Institution

Embrapa Agric. Inf., Campinas, Brazil

fYear

2011

fDate

12-14 July 2011

Firstpage

33

Lastpage

36

Abstract

This paper discusses how to take advantage of clustering techniques to analyze and extract useful information from multi-temporal images of low spatial resolution satellites to monitor the sugarcane expansion. Additionally, we introduce the SatImagExplorer system that was developed to automatically extract time series from a huge volume of remote sensing images as well as provide algorithms of clustering analysis and geospatial visualization. According to experiments accomplished with spectral images of sugarcane fields, this proposed approach can be satisfactorily used in crop monitoring.

Keywords

geophysical image processing; time series; vegetation mapping; NDVT-NOAA multitemporal images; SatlmagExplorer system; clustering analysis algorithms; clustering techniques; crop monitoring; geospatial visualization; low spatial resolution satellites; monitoring process; remote sensing images; spectral images; sugarcane crops; sugarcane expansion; sugarcane fields; time series; Agriculture; Monitoring; Productivity; Satellites; Time series analysis; US Government agencies; K-means; K-medoids; NOAA/AVHRR; Time series; productivity;

fLanguage

English

Publisher

ieee

Conference_Titel

Analysis of Multi-temporal Remote Sensing Images (Multi-Temp), 2011 6th International Workshop on the

Conference_Location

Trento

Print_ISBN

978-1-4577-1202-9

Type

conf

DOI

10.1109/Multi-Temp.2011.6005040

Filename

6005040