We propose and demonstrate a fast, robust method for using satellite images to localize an Unmanned Aerial Vehicle (UAV). Previous work has large storage computation costs is unable run in real time. In this work, we collect Google Earth (GE) desired flight path offline autoencoder trained compress these low-dimensional vector representation while retaining the key features. This used UAV image...

The purpose of this study is to build the binary logit model of an airport pavement that could monitor the pavement condition in near real time using microwave remote sensing satellite, then the relationship between the international roughness index (IRI) of an airport and backscattering values from PALSAR images of the ALOS satellite was determined. Total 390 data were used in analysis. This m...

Nowadays a lot of satellite images are being received every day from several satellite sensors and with different resolutions. These images, especially Very High Resolution (VHR) satellite imagery (such as Ikonosand and Quickbird) provide valuable information to researchers for different applications. Because amount of remotely sensed data is enormous, for a human expert, manually extracting th...

in this research, the framework is presented for unsupervised change detection using multitemporal sar images based on integration clustering and level set methods. spatial correlation between pixels were considered by using contextual information. also as proposed method was used integration of gustafson-kessel clustering techniques (gkc) and level set methods for change detection. using clust...