Method to classify vegetation cover using satellite images and artificial intelligence

Utilizing satellite images and artificial neural networks in estimation of vegetation fraction in arid regions

Detection of land use and vegetation changes in Poldokhtar Using Landsat Satellite Images

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A Sparse Representation Method to Detect Saffron Agricultural Lands Using Sentinel-II Satellite Images Time

Nowadays, agricultural management via remote sensing technology has gained a special position among managers and the people who are in charge of this industry. Saffron (Red Gold) is one of specific Iran’s agricultural products with a high economic valance which is used in different fields of food and medical industries. Considering the cultivation conditions of the saffron, there has not a pers...

Presentation of Suitable Model to Estimate Vegetation Fraction Using Satellite Images in Arid Region (Case Study: Sadough- Yazd, Iran)

One of the influential tools concerning the rangeland and vegetation sciences isthe technology of remote sensing and satellite data. Satellite data have played essentialroles in preparing the needed information for studying the vegetation. Vegetation has beenwidely recognized as one of the best indicators for determining the land conditions. Usingvegetation indices is one of the techniques of r...

Land Cover Classification of Satellite Images Using Contextual Information

This paper presents a method for the classification of satellite images into multiple predefined land cover classes. The proposed approach results in a fully automatic segmentation and classification of each pixel, using a small amount of training data. Therefore, semantic segmentation techniques are used, which are already successful applied to other computer vision tasks like facade recogniti...