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Akaike, H. (1974) A New Look at the Statistical Model Identification. IEEE Transactions on Automatic Control, 19, 716-723.
https://doi.org/10.1109/TAC.1974.1100705

has been cited by the following article:

  • TITLE: Grassland Height Assessment by Satellite Images

    AUTHORS: Alessandro Cimbelli, Valerio Vitale

    KEYWORDS: Biomass, Sentinel, Landsat, Grassland

    JOURNAL NAME: Advances in Remote Sensing, Vol.6 No.1, January 18, 2017

    ABSTRACT: Images collected by optical and radar satellite sensors represent a most viable solution for the extraction of biophysical parameters of the earth surface. The mid-resolution dataset acquired by Landsat and Sentinel satellites have recently become available free of charge for all users. At the same time, some software for image processing and GIS, like QGIS, R, and ImageJ, have reached a high level of maturity and a large community of users, thanks to their open source license. In this project, free satellite images and open source software have been used for the assessment of the grassland biomass. The overall goal is the enhancement of the statistics of grassland production and dried fodder for the animal breeding. Currently, the National Institute of Statistics collects this kind of dataset at the province level. The project consists in some “in situ” surveys in a specific site in central Italy and in the building of a regression model between the grassland heights and the corresponding radiometric values of the most relevant image bands.