Foreword

Since the publication of the Google Earth software, many people have discovered what remote sensing is. Of course, Google Earth has also open the possibility of building new services and applications.

Even if I think that Google Earth may be very useful (like a map, a world map, enriched, on top of which everybody can publish information), there is one thing missing: up to date images and multi-temporal data.

Many applications of remote sensing imagery are oriented towards monitoring: landscape evolutions, change detection, etc. For this kind of applications, several images of the study site are needed. Furthermore, these images must yield the kind of information the user is looking for. This will determine the type of sensor to use: spectral bands, resolution, and so on.

Once the images are available, they have to be precisely calibrated: artifacts due to point of view, atmosphere or even changes at the sensor level have to be accounted for. Since each image may contain several millions of pixels, this calibration can not be performed manually. Therefore, computer programs have to be written in order to process the images automatically.

Also, the image processing needed for each application may be different and thus the algorithms may need to be tuned, that is, some parameters may have to be accurately chosen.

If the choice of algorithms and parameters is rather well known for some applications, there is still a need of research and development for many other uses. In most of the cases there is no need for a theoretical research, but rather an engineering work of getting the pieces together in order to build operational image processing chains.

My goal in writing this blog is to discuss about examples of applications and services which can be built upon remote sensing imagery and automated thanks to image processing techniques.