urban forest

Published: 28 July 2022| Version 1 | DOI: 10.17632/j739yc6cgc.1
Fatwa Ramdani,


This data contain of: 1. Data of satellite imagery of PlanetScope of University of Brawijaya with 3m spatial resolution. 2. Data training and testing in CSV format 3. R Script of four different algorithms (XGBoost, Random Forest, Support Vector Machine, and Neural Networks) The manuscript that using this dataset has been submitted to F1000 Research (https://f1000research.com/)


Steps to reproduce

The satellite imagery of PlanetScope was acquired from Planet.com under education and academic license. The scene then clipped for only within the study area using QGIS software. The RStudio software then used to do classification process using four different algorithms.


Universitas Brawijaya, Tsukuba Daigaku


Remote Sensing, Geographic Information Systems, Geospatial Data Repository