Detection of Plastic Greenhouses Using High Resolution Rgb Remote Sensing Data and Convolutional Neural Network

Detection of Plastic Greenhouses Using High Resolution Rgb Remote Sensing Data and Convolutional Neural Network

Agricultural production in greenhouses shows a rapid growth in many parts of the world. This form of intensive farming requires a large amount of water and fertilizers, and can have a severe impact on the environment. The number of greenhouses and their location is important for applications like sp...

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Bibliographic Details
Main Authors: Jakab Balázs, van Leeuwen Boudewijn, Tobak Zalán
Format: Article
Language:English
Published: Sciendo 2021-04-01
Series:Journal of Environmental Geography
Subjects:
plastic greenhouse
deep learning
convolutional neural network
satellite image
google earth
Online Access:https://doi.org/10.2478/jengeo-2021-0004
Description
Summary:Agricultural production in greenhouses shows a rapid growth in many parts of the world. This form of intensive farming requires a large amount of water and fertilizers, and can have a severe impact on the environment. The number of greenhouses and their location is important for applications like spatial planning, environmental protection, agricultural statistics and taxation. Therefore, with this study we aim to develop a methodology to detect plastic greenhouses in remote sensing data using machine learning algorithms.
ISSN:2060-467X

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