Abstract
Multiband spatial remote sensing the multispectral remote sensing of SST and Chl-a is an
indirect tool for surveying the earth's surface and powerful for monitoring and understanding
oceanic and lacustrine processes at different spatial and temporal scales, contributing to the
sustainable management of natural resources and a major advance in our ability to understand
and monitor aquatic ecosystems on a global scale. This has enabled us not only to establish a
processing methodology for the satellite images captured in our study area, but also to obtain
results of different resolution. Continue to develop and improve data processing techniques
and predictive models based on these data.
In this work we have implemented a satellite image processing application providing valuable
data for aquaculture resource management. using the following methods:
Multispectral data analysis: Exploring image processing and spectral classification
techniques to accurately extract SST and Chl-a from satellite data.
- Variation modeling : Development of statistical and spatio-temporal models to quantify
variations and predict long-term trends, assessment of the impact of SST and Chl-a variations
on aquaculture ecosystems, with a focus on marine species.
SST-Chl-a interactions : Study of the complex relationships between SST and Chl-a, taking
into account environmental factors and seasonal cycles Application of regression and spatiotemporal modeling techniques to quantify variations and predict long-term trends.
- Use of results to optimize farm management, taking into account changing environmental
conditions, and to monitor these marine ecosystems on a large scale and at regular intervals,