Homeworks for the course Earth Observation Data Analysis, 2020, Sapienza University of Rome
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Updated
Feb 25, 2023
Homeworks for the course Earth Observation Data Analysis, 2020, Sapienza University of Rome
Segmentation of aerial images using two approaches: 1) texture features, 2) vegetation index
A study of the stress response of vegetation to drought situation through multispectral satellite imagery. Case of study of Como lake, summer 2022.
Docker with python3 opencv and exiv2
Calculating NDVI(vegetation index in russian)/ Вычисление NDVI (вегетационного индекса)
清华大学校园绿化遥感监测与分析
Apresentação feita em R do meu estudo chamado "Are coexisting biomes in a heterogeneous tropical landscape alternative stable states?".
Script for automatic processing of Sentinel 2 images from Open Hub.
Asparagus Leaf Density Mapping Tools: Scripts for automatically quantifying and visualizing leaf density map from given images
Homeworks for the course Earth Observation Data Analysis, 2020, Sapienza University of Rome
Feed an AOI --> get the vegetation report
ENVI/IDL extensions for NRS department
AppGro: Flutter realtime GGA and GA image calculator application made in flutter
Master Thesis// Thesis: Developing a web-based system to visualize vegetation trends by a nonlinear regression algorithm
Repository of Jupyter notebooks aimed at learning how to use Python to retrieve data from Google Earth Engine
QGIS module for calculating Vegetation Indexes on Sentinel-2 multispectral images. There is two branches: "Master" supports photographs downloaded from scihub and "landviewer" stands for photographs downloaded from eos-landviewer.
Ruby on Rails web-application that leverages libvips image processing library to apply VARI, NDVI and others Vegetation Indices (VIs) on map tiles.
VICAL is a open-source implementation to calculate 23 VIs map (VIs commonly used in agricultural applications) and time series of any agricultural area
[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
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