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The world has been alarmed with the global warming effects. Global warming has been a distress towards the environment, thus shorten the Earths lifespan. It is a challenging task to reduce the global...
Since the availability of high-resolution Airborne Laser Scanning (ALS) data, substantial progress in geomorphological research, especially in landslide analysis, has been carried out. First and secon...
Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atm...
This study demonstrates the application of CIELAB, Color intensity, and One Dimensional Scalar Constancy as features for image recognition and classifying benthic habitats in an image with the coastal...
The high-dimensional feature vectors of hyper spectral data often impose a high computational cost as well as the risk of "over fitting" when classification is performed. Therefore it is necessary to ...
The critical impact of air pollution on human health and environment in one hand and the complexity of pollutant concentration behavior in the other hand lead the scientists to look for advance techni...
The Support Vector Machine is a theoretically superior machine learning methodology with great results in classification of highdimensional datasets and has been found competitive with the best machin...
An image classification method based on Support Vector Machine (SVM) is proposed on hyperspectral and 3K DSM data. To obtain training data we applied an automatic method relating to four classes nam...
Detection of coastline is an important procedure for management of coastal zones. According to the International Geographic Data Committee (IGDC), coastlines are one of the most important environmenta...
Crop mapping and time series analysis of agronomic cycles are critical for monitoring land use and land management practices, and analysing the issues of agro-environmental impacts and climate change....

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