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Large scale vector databases are valued tools for forest management. It is therefore important to keep these databases up to date and various change detection methods have been designed in this aim. ...
This paper describes a contextual classification approach to classify complex forest change classes. Multi temporal forest change classifications are performed comparing the 1989 baseline for the Kyot...
As part of a Tanzanian-Norwegian cooperation project on Monitoring Reporting and Verification (MRV) for REDD+, 2007-2011 C- and L-band synthetic aperture radar (SAR) backscatter data from Envisat AS...
Assessing land cover changes in tropical rain forest areas is an issue of worldwide importance. Multi-spectral, higher spatial resolution satellite data are often the only data source for generating ...
MULTITEMPORAL FOREST CHANGE ANALYSIS     Sariyer  Landsat TM  GCP  RMS  ISODATA       2015/2/4
In this study, differentiability of vegetation at Sariyer, an area with rich forest due to its geographical situation and general characteristics, has been analysed through the satellite images used ...
An object-based approach for forest disaster change detection using High Resolution (HR) satellite images is proposed. An automatic feature selection process is used to optimize image segmentation via...
Airborne LiDAR data has become an important tool for both the scientific and industry based investigation of forest structure. The uses of discrete return observations have now reached a maturity leve...
Tree height is a fundamental parameter for describing the forest situation and changes. The latest development of automatic Digital Surface Model (DSM) generation techniques allows new approaches of...
The importance of accurate and timely information describing the nature and extent of land resources and changes over time is increasing, especially in mountainous areas. We have developed a methodolo...

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