Remote Sensing Image Analysis. To support ecological planning land use and land management decisions aes geospatial has developed a specific expertise in remote sensing for vegetation analysis and other natural resource issues. Rsim group performs research in the fields of processing and analysis of remote sensing images acquired by satellite systems for earth observation with interdisciplinary approaches associated to remote sensing machine learning signal image processing and big data management.
Spanning the full spectrum from physical characterization and model inversion to thematic classification and machine learning application. Envi is the most widely used remote sensing and image analysis program within industry and research. Aes interprets remotely sensed data often from multiple sensors and platforms for applications in ecological restoration forestry agriculture and industrial sectors of electricity oil and gas.
The image analysis and classification section of frontiers in remote sensing seeks to publish original research covering all aspects of remote sensing image analysis.
The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Spanning the full spectrum from physical characterization and model inversion to thematic classification and machine learning application. Remote sensing is the science and technology of acquiring images of the earth s surface from spacecraft aircraft and drones to aid in the monitoring and management of the natural and built environments. Geographic object based image analysis geobia is a primary remote sensing tool utilized in land cover mapping and change detection.