A geospatial raster processing library for machine learning

A scalable implimentation of HANTS for time sereis reconstruction in remote sensing on Google Earth Engine platform

Set of Machine Learning Algorithms developed with the aim of determining health states of different types of crops

This repository contains a pipeline blending Python and R features, first to: download, preprocess, and compute Sentinel-1 SAR vegetation indices (all in Python); following for image sampling in R.

Non-parametric weighted Whittaker smoothing

This repository holds the code for an R package called CropPhenology. The package extracts phenological information of crops from multi temporal remote sensing vegetation index images

Python coding that takes images acquired using a Near-Infrared (NIR) converted camera and generates a modified Normalized Differential Vegetation Index (NDVI). Contains standalone with colorbar legend and batch versions. ENDVI and SAVI Indexes also available and with greyscale options.

Get Sentinel-2 data from Google Earth Engine or from cloud-optimized geotiffs in AWS Open data registry maintained by Element84, and compute biophysical parameters using SNAP Biophysical processor algorithm.

Bu repoda ESA SNAP yazılımı ile temel Sentinel-2 görüntü işleme süreci özetlenecektir.

和高光谱数据处理相关程序

Notebooks for preprocessing and analysis of Planetscope 4 band data/imagery, using rasterio and fiona.

[doi: 10.1016/j.agrformet.2023.109337] Wenquan Zhu, Cenliang Zhao*, Zhiying Xie. An end-to-end satellite-based GPP estimation model devoid of meteorological and land cover data. Agricultural and Forest Meteorology, 2023

VICAL is a open-source implementation to calculate 23 VIs map (VIs commonly used in agricultural applications) and time series of any agricultural area

Repository of Jupyter notebooks aimed at learning how to use Python to retrieve data from Google Earth Engine

Ruby on Rails web-application that leverages libvips image processing library to apply VARI, NDVI and others Vegetation Indices (VIs) on map tiles.

QGIS module for calculating Vegetation Indexes on Sentinel-2 multispectral images. There are two branches: "Master" which supports photographs downloaded from scihub and "landviewer" which stands for photographs downloaded from eos-landviewer.

R scripts for converting PACE LandVI data from NetCDF to GeoTIF

Master Thesis// Thesis: Developing a web-based system to visualize vegetation trends by a nonlinear regression algorithm

ECOSTRESS Collection 2 STARS Data Fusion Product Generating Executable (PGE)

Segmentation of aerial images using two approaches: 1) texture features, 2) vegetation index

ECOSTRESS Collection 3 Level 2 Spatial Timeseries for Automated high-Resolution multi-Sensor (STARS) Data Fusion System

Feed an AOI --> get the vegetation report

ENVI/IDL extensions for NRS department

A study of the stress response of vegetation to drought situation through multispectral satellite imagery. Case of study of Como lake, summer 2022.

Using time series machine learning models to predict crop growth and processing image field data collected by IoT units as part of an AgAID internship

AppGro: Flutter realtime GGA and GA image calculator application made in flutter

📝 Simplify your note-taking with pyNotes, a user-friendly desktop app for adding, editing, and organizing notes using Python and PyQt6.

Spatiotemporal Analysis of Agricultural Drought Severity and Hotspots in Somaliland. It integrates MODIS-derived vegetation indices and CHIRPS precipitation data to identify and assess drought severity and hotspots over time.

A web-based app for visualizing vegetation and spectral indices from UAV imagery. Supports RGB and multispectral bands, real-time index switching, and interactive colormap preview.

Homeworks for the course Earth Observation Data Analysis, 2020, Sapienza University of Rome