Theme 1-2: Rangeland/Grassland Ecology--Poster Sessions
Description
The wide availability of free satellite imagery, the recent development of cloud platforms dedicated to big spatial data (Big Data) that integrates both image archives from different providers, processing algorithms, distributed processing capabilities as well as an application programming interface (API) that facilitate scripting and automation process opened new perspectives for the use of vegetation observation time series over long timestamps and over large spatial scales (almost planetary).
This work aims at harnessing these technologies and building up an automated solution to monitor rangeland rehabilitation dynamics in arid lands and to assess the effectiveness of stakeholder’s management strategies. Such solution is based on graphical user interface that facilitate the process and on the use of analysis functions relaying on analysing temporal trajectories (time series) of different spectral indices derived from satellite images (Landsat or Sentinel) at the required spatial analysis scale.
The solution is implemented using java script as scripting language using the functions offered by GEE API. The graphical user interface of the first prototype is exploitable by the means of a standard web browser and it is accessible even to people without any background in regard to programming languages or to remote sensing skills. The process was tested for two arid sites on Morocco: acacia ecosystems on the southern part of Morocco and the highlands on Moroccan eastern parts mainly on sites recently rehabilitated. It has been qualified is promising solution.
Citation
Lahssini, Said; Moukrim, Said; Mharzi-Alaoui, H.; Rifai, N.; El Mansouri, L.; and El Wahidi, F., "Cloud Computing Solution for Monitoring Arid Rangeland Dynamics: Case of Moroccan Highlands and Southern Acacia Ecosystems" (2022). IGC Proceedings (1993-2023). 7.
https://uknowledge.uky.edu/igc/24/1-2/7
Included in
Cloud Computing Solution for Monitoring Arid Rangeland Dynamics: Case of Moroccan Highlands and Southern Acacia Ecosystems
The wide availability of free satellite imagery, the recent development of cloud platforms dedicated to big spatial data (Big Data) that integrates both image archives from different providers, processing algorithms, distributed processing capabilities as well as an application programming interface (API) that facilitate scripting and automation process opened new perspectives for the use of vegetation observation time series over long timestamps and over large spatial scales (almost planetary).
This work aims at harnessing these technologies and building up an automated solution to monitor rangeland rehabilitation dynamics in arid lands and to assess the effectiveness of stakeholder’s management strategies. Such solution is based on graphical user interface that facilitate the process and on the use of analysis functions relaying on analysing temporal trajectories (time series) of different spectral indices derived from satellite images (Landsat or Sentinel) at the required spatial analysis scale.
The solution is implemented using java script as scripting language using the functions offered by GEE API. The graphical user interface of the first prototype is exploitable by the means of a standard web browser and it is accessible even to people without any background in regard to programming languages or to remote sensing skills. The process was tested for two arid sites on Morocco: acacia ecosystems on the southern part of Morocco and the highlands on Moroccan eastern parts mainly on sites recently rehabilitated. It has been qualified is promising solution.
