Monitoring of water consumption in irrigation systems is paramount to integrated water management. This is already possible with Low spatial resolution (LSR) satellite remote sensing. However,... More > smaller pixel size is still required for more local management, while keeping return period within few days.High spatial resolution (HSR) satellite imagery is indeed available for calculation of evapotranspiration, and has been used in many studies already. However, its practical return period is a major drawback to its implementation for monitoring irrigation systems. This thesis is perusing into the use of genetic algorithms to assimilate parameters of an agro-hydrological model called SWAP for each of the pixels of HSR images contained into one single pixel of a LSR multi-temporal image. The methodology developed and experimented here is trying to take advantage of the spatial content of HSR images and the temporal content of LSR images by fusing them by the process of data assimilation.< Less
This textbook aims at expanding basics of GIS programming for Vector, Database and Raster.
It should be taken as an overview more than an thorough material, and by no mean dealing with all of the... More > subject.
After going through this book, the reader will be able to have a basic knowledge of the technology available
for GIS data programming, and a good practical hand on most common ways to investigate them.< Less
``How can I load input satellite imagery, compute an input raster into a given result and write that result as a new image to the hard disk''.
This book gives a range of programming options to... More > answer this question, using high-level and low-level programming languages, some serial (C, Python, R) but also some in parallel (OpenMP, MPI-C, CUDA, OpenCL).
Additionally, it also demonstrates how to perform various levels of integrations into few programming languages and environments having GUI functionality (WxPython and GRASS GIS).< Less