The forest composition monitoring system using k-means algorithms on satellite imagery. Case study - Indepedenta Forest.

The increasing use of satellite faraway sensing for civilian use has proved to be the most cost effective means of mapping and monitoring environmental changes. From this point, these new tools are now essential in monitoring operations for vegetation and non-renewable resources, especially in developing countries. Data can be gotten as frequently as required to deliver information for determination of quantitative and qualitative changes in terrain. In reaching the aim of studying the forest composition and the vegetation dynamics during the time using satelitar imagery a k-means algorithm of chromatic analysis is proposed. In this way, by using comparisons between chronologically ordered records, could be described the vegetation changes and its developments in a given area. The exposed method in the present work suggests the joining two successive phases: the first step were used resolution suitable satellite images in order to succeed in building a model. The study was conducted between 1990 and 2017 by using LANDSAT data set. In the second phase, are applied chromatic investigation algorithm in order to succeed in reaching a map of vegetation composition. The case study is that of Independenta Forest from Galati County. For discussion are presented three cases of September 2011, 2016 and 2017 Preliminary results on the composition evaluations are promising and the research is ongoing.