منابع مشابه
Sequential Land Cover Classification
Land cover classification using remotely sensed data is a critical first step in large-scale environmental monitoring, resource management and regional planning. The classification task is made difficult by severe atmospheric scattering and absorption, seasonal variation, spatial dependence, complex surface dynamics and geometries, and large intra-class variability. Most of the recent research ...
متن کاملLand use and Land Cover Classification using RGB&L Based Supervised Classification Algorithm
After the Geometric correction and resampling the image should be classified. This paper introduced a new method for classifying the areas in a remotely sensed image under the category of supervised classification techniques. This classification technique describes how to classify the geographical areas in given image under supervised classification techniques conventions. So to tell the abstra...
متن کاملRemote Sensing and Land Use Classification: Supervised vs. Unsupervised Classification
In this time of large-scale planning and land management on public lands, managers are increasingly looking for faster and less expensive methods of data collection. In efforts to make better decisions, planners need to be able to look at changes over time to assess trends. Policy makers are also looking to assess the effects of policies such as prescribed fire or fire suppression. All of these...
متن کاملUrban Land Cover Classification Using Hyperspectral Data
Urban land cover classification using remote sensing data is quite challenging due to spectrally and spatially complex urban features. The present study describes the potential use of hyperspectral data for urban land cover classification and its comparison with multispectral data. EO-1 Hyperion data of October 05, 2012 covering parts of Bengaluru city was analyzed for land cover classification...
متن کاملStatistical Modeling for Improved Land Cover Classification
Novel statistical modeling and training techniques are proposed for improving classification accuracy of land cover data acquired by LandSat Thermatic Mapper (TM). The proposed modeling techniques consist of joint modeling of spectral feature distributions among neighboring pixels and partial modeling of spectral correlations across TM sensor bands with a set of semi-tied covariance matrices in...
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ژورنال
عنوان ژورنال: The Forestry Chronicle
سال: 1940
ISSN: 0015-7546,1499-9315
DOI: 10.5558/tfc16119-2