Pooya Shirazi's Projects
This repository contains machine learning models for estimating cropland types (irrigated, non-irrigated, no crop) to assess climate change impact on agricultural land suitability across various carbon emission scenarios.
A GUI Panel providing Worker subscriptions and Fragment settings and configs, providing configs for cross-platform clients using (singbox-core and xray-core)
Code for Extract Data from RBSN Stations Data.
My Website!
Data to Decisions Dashboard
Minimal examples of multi-page apps using Dash Pages
KHRW Dashboard...
My Dashboard ...
Running V2ray inside edge/serverless runtime
Code and data to train the MLMs included in the article submitted to Journal of Hydroinformatics
Paper for IEEE Escience on Machine Learning and Evapotranspiration
Single Page App with Flask and Vue.js
Flet sample applications
Demo for using Machine Learning techniques in R to create flood susceptibility maps. Classification And Regression Tree (CART), Support Vector Machine (SVM), and Gradient Boosting Machine (GBM) are experimented with. This demo uses the Red River Valley in Manitoba as a case study, where there was a major flood that occurred back in 2011.
Gantt chart for HTML/JavaScript. Utilizes D3.js, Require.js, Backbone, and Underscore.
Code for the "Mapping hourly urban evapotranspiration using Sentinel-2, open geodata and machine learning" manuscript
Machine Learning models to predict daily Actual Evapotranspiration of citrus orchards
Machine learning to predict floods
Pooya's Dashboard ...
nodejsๅฎ็ฐvless
Introduction to Geospatial Concepts