nitinmagima/endofseasonmonitoring_madagascar

Code for End of Season Monitoring - Madagascar # Trigger Monitoring Dashboard for Anticipatory Action (AA) Author - Nitin Magima Date - March 2024 Version - 1.0 This is a README file created for the Trigger Monitoring Dashboard for Anticipatory Action Programs for WFP in various countries. The dashboard has been built in python using "Shiny for Python". The struture is similar to the Python maproom created for AA Design. The code base has been designed in such a way that only the YAML file needs to be updated to create a new Trigger Monitoring Dashboard. The Trigger Monitoring Dashboard takes advantage of the map rooms already created for respective countries and pulls the data from there.The code has been divided into four files: 1. eos_madagascar_v1.ipynb - creates the front end of the dashboard. Creates filterable tables for admin 0 and admin 1 levels. 2. utils.py - contains functions to use the maproom API 3. config.yaml - contains the data for the functions to work in utils.py 4. get_admin1data.py - help manually update the config.yaml file of admin1_list. ### Purpose The Jupyter Notebook aims to do a post-assessment of drought in Madagascar during the relevant seasons such as October-November-December (OND) and December-January-February (DJF). ### Audience Tailored for Madagascar government officials in agriculture, water resources, and disaster management sectors. ### Objectives To provide an in-depth analysis of drought conditions during OND and DJF, historical drought patterns in these months, and predictive insights for future OND seasons. ### Summary The jupyter notebook uses VIIRS product #13, Gridded Vegetation Indices (VNP13 Level 3 suite). The level 3 gridded vegetation indices are standard products designed to extend the significant VI time series derived from AVHRR and MODIS (Huete et al. 2002). The level 3 spatial and temporal gridded vegetation index products are composites of daily surface reflectances. They are generated at 500m, 1km, and 0.05o (~5.6km) every 8 days (quasi), 16 d …