TY - GEN
T1 - Open-Source Mapping Method Applied to Thermal Imagery
AU - Vong, André
AU - Matos-Carvalho, João P.
AU - Pedro, Dário
AU - Tomic, Slavisa
AU - Beko, Marko
AU - Azevedo, Fábio
AU - Correia, Sérgio D.
AU - Mora, André
N1 - Funding Information:
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04111%2F2020/PT#
info:eu-repo/grantAgreement/FCT/3599-PPCDT/PCIF%2FSSI%2F0102%2F2017/PT#
info:eu-repo/grantAgreement/FCT/Investigador FCT/IF%2F00325%2F2015%2FCP1275%2FCT0001/PT#
info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00066%2F2020/PT#
This project was partially funded by AI4RealAg project.
The goal of the AI4RealAg project is to develop an intelligent knowledge extraction system, based in Artificial Intelligence and Data Science, to increase sustainable agricultural production.
The project is financed by Portugal 2020, under the Lisbon’s Regional Operational Programme and the Competitiveness and Internationalization Operational Programme, worth 1.573.672.61 euros, from the European Regional
and also Instituto Lusófono de Investigação e Desenvolvimento (ILIND) under Project COFAC/ILIND/COPELABS/1/2020.
Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - The increase of the world population has had an impact in the agricultural field. As a consequence, this implies an increase in food production. To address this demand, farmers had to boost crop yields and land sizes. The latter one led to ineffectiveness of traditional methods for crop monitoring. For this reason, farmers began to adopt and adapt technological breakthroughs into agriculture by applying the concept of remote sensing. Remote sensing aims to collect information at a distance through the use of cameras and, in some cases, aerial platforms. Furthermore, multispectral cameras allowed farmers to better understand the management of crops and crop’s health. Also, through study of literature, it was found that thermal imaging could be an important tool to measure the crop’s condition. However, due to complexity of thermal images, an open-source tool that integrated this functionality was not found. Therefore, this paper proposes an open-source method that addresses the complexities of thermal images and is able to produce maps by exploiting them.
AB - The increase of the world population has had an impact in the agricultural field. As a consequence, this implies an increase in food production. To address this demand, farmers had to boost crop yields and land sizes. The latter one led to ineffectiveness of traditional methods for crop monitoring. For this reason, farmers began to adopt and adapt technological breakthroughs into agriculture by applying the concept of remote sensing. Remote sensing aims to collect information at a distance through the use of cameras and, in some cases, aerial platforms. Furthermore, multispectral cameras allowed farmers to better understand the management of crops and crop’s health. Also, through study of literature, it was found that thermal imaging could be an important tool to measure the crop’s condition. However, due to complexity of thermal images, an open-source tool that integrated this functionality was not found. Therefore, this paper proposes an open-source method that addresses the complexities of thermal images and is able to produce maps by exploiting them.
KW - Orthomap
KW - Photogrammetry
KW - Remote sensing
KW - Structure from Motion (SfM)
KW - Thermal images
UR - http://www.scopus.com/inward/record.url?scp=85135020837&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-10461-9_3
DO - 10.1007/978-3-031-10461-9_3
M3 - Conference contribution
AN - SCOPUS:85135020837
SN - 978-3-031-10460-2
T3 - Lecture Notes in Networks and Systems
SP - 43
EP - 57
BT - Intelligent Computing - Proceedings of the 2022 Computing Conference
A2 - Arai, Kohei
PB - Springer
CY - Cham
T2 - Computing Conference, 2022
Y2 - 14 July 2022 through 15 July 2022
ER -
