A GIS open-source application to enhance the identification of archaeological crop marks using remote sensing data

Lia Duarte; Jesús García Sánchez; João Fonte; Ana Cláudia Teodoro

doi:10.1117/12.2599743

12 September 2021 A GIS open-source application to enhance the identification of archaeological crop marks using remote sensing data

Lia Duarte, Jesús García Sánchez, João Fonte, Ana Cláudia Teodoro

Author Affiliations +

Proceedings Volume 11863, Earth Resources and Environmental Remote Sensing/GIS Applications XII; 118630C (2021) https://doi.org/10.1117/12.2599743
Event: SPIE Remote Sensing, 2021, Online Only

Abstract

The use of vegetation indices to highlight archaeological features from remote sensing (RS) sensors is increasingly in demand, especially due to the possibility of obtaining high-resolution multispectral images with drones. The objective of this work is divided in two steps: i) to test techniques for the semi-automatic identification of crop marks in a study zone, in Salvada, Portugal, and; ii) to develop a Geographical Information Systems (GIS) open-source application, named ArchMarks, under QGIS software, to enhance the identification of archaeological crop marks using RS data/techniques, integrating the automatic creation of indices and the identification techniques tested before. ArchMarks aims to compute several vegetation and soil indices from multispectral imagery considering four bands (Red, Green and Blue and Near InfraRed (NIR)) for enhancing the identification of archaeological crop marks. In order to define the best approach to implement in the plugin, some tests were performed with two algorithms available in QGIS: ContrastEnhancement and WatershedSegmentation. High-resolution aerial imagery (25-50 cm spatial resolution) was obtained from Web Map Service (WMS) services in addition to Sentinel-2 satellite image, whose spatial resolution is of 10 meters in the Red Green Blue-Near InfraRed bands. The application is free and can be adapted to other region of interest. In the future, the plugin will be improved with a methodology to download remote sensing data (aerial images and satellite data) from WMS sources, band stacking, and machine learning algorithms, such as Support Vector Machine (SVM) algorithm, to automatically classify archaeological traces on the vegetation or bare soil.

Conference Presentation

Citation Download Citation

Lia Duarte, Jesús García Sánchez, João Fonte, and Ana Cláudia Teodoro "A GIS open-source application to enhance the identification of archaeological crop marks using remote sensing data", Proc. SPIE 11863, Earth Resources and Environmental Remote Sensing/GIS Applications XII, 118630C (12 September 2021); https://doi.org/10.1117/12.2599743

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available