Impairing Land Registry: Social, Demographic, and Economic Determinants of Forest Classification Errors

Impairing Land Registry: Social, Demographic, and Economic Determinants of Forest Classification Errors

This paper investigates the social, demographic, and economic factors determining differences between forest identification based on remote sensing techniques and land registry. The Database of Topographic Objects and Sentinel-2 satellite imagery data from 2018 were used to train a forest detection...

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Bibliographic Details
Main Authors: Maciej Adamiak, Mirosław Biczkowski, Katarzyna Leśniewska-Napierała, Marta Nalej, Tomasz Napierała
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Remote Sensing
Subjects:
land cover
forest
convolutional neural networks
machine learning
land registry errors
Online Access:https://www.mdpi.com/2072-4292/12/16/2628

Internet

https://www.mdpi.com/2072-4292/12/16/2628

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