Sentence examples for used maximum likelihood classification from inspiring English sources

In this paper, we will study how the accuracy of a commonly used maximum likelihood classification (MLC) algorithm is affected by spatial elements typical of a Caribbean atoll system present in high spectral and spatial resolution imagery.

The algorithm uses maximum likelihood classification combined with a certainty based fusion criterion.

This study uses Maximum Likelihood Classification analysis in GIS to create a mosaic landscape of 22 paleoclimate zones to reconstruct what Europe may have looked like during the Last Interglacial Eemian.

Past changes in area and patch fragmentation of land cover classes and individual forest patches in the Gamo Highlands, Ethiopia, were assessed using maximum-likelihood classification of LANDSAT images.

We used maximum likelihood estimation, which is the most commonly used supervised classification method in the field, as implemented in the ENVI software.

Estimates used maximum likelihood.

These images were spatially subset, and then classified using maximum likelihood supervised classification.

For this, satellite images from LISS III were converted to LULC rasters using maximum likelihood method under image classification extension of ArcGIS (Fig. 3a, b).

We show that the proposed method outperforms the results obtained using maximum likelihood and usual stochastic distance classification methods.

Supervised classification methodology has been employed using maximum likelihood technique in ERDAS 9.3 Software.

The training sites were determined and a supervised classification was performed on both images using Maximum Likelihood algorithm.