Comparing the MLC and JavaNNS Approaches in Classifying Multi-Temporal LANDSAT Satellite Imagery over an Ephemeral River Area

This paper analyzes two pixel-based classification approaches to support the analysis of land cover transformations based on multitemporal LANDSAT sensor data covering a time space of about 24 years. The research activity presented in this paper was carried out using Lama San Giorgio (Bari, Italy) c...

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Veröffentlicht in:	International journal of agricultural and environmental information systems 2015-10, Vol.6 (4), p.83-102
Hauptverfasser:	Tarantino, Eufemia, Novelli, Antonio, Aquilino, Mariella, Figorito, Benedetto, Fratino, Umberto
Format:	Artikel
Sprache:	eng
Schlagworte:	Analysis Artificial neural networks Catchment areas Classification Classifiers Computer simulation Earth resources technology satellites Floods Hydrology Land cover Land use Landsat Landsat satellites Learning theory Methods Neural networks Remote sensing Rivers Satellite imagery
Online-Zugang:	Volltext
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