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Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences

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A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: closed (27 May 2023) | Viewed by 23377

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Prof. Dr. Tung-Ching Su

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National Quemoy University, Kinmen, Taiwan
Interests: remote sensing; environmental monitoring; infrastructure inspection; artificial intelligence; risk assessment of cultural heritage

Special Issue Information

Dear Colleagues,

Archaeology, geography, and the Earth sciences can be regarded as an integrated field devoted to research about natural, environmental, humanities, and the social sciences. Active and passive remote sensing systems have been widely applied to the data acquisitions of various spatial scales. Innovations in image and signal processing techniques, algorithms, the Internet of Things (IoTs), big data analyses, and deep learning models induce new potentials in reconstruction and exploration of ancient people’s material culture, environment/landscape changes, and natural and humanistic connections.

This Special Issue focuses on applying remote sensing techniques coupled with data mining methods to analyze and discuss contexts among humanities, geographies, and environments. A formal integration of archaeology, geography, and the Earth sciences has been developed for the past twenty or thirty years. In spite of that, continuous innovations, whether in imaging spectroscopy and multimodal imaging or in imaging computing using deep learning models, still motivate scholars to address the related issues.

The aim of this Special Issue is to compile the latest achievements in the topic and to open up a forum where scholars can contribute their unique findings. Potential topics include but are not limited to the ones covered in the keywords.

Prof. Dr. Tung-Ching Su
Guest Editor

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Keywords

Environmental/landscape archaeology
Human geography
Active/passive remote sensing techniques
Geographic information systems
2D and 3D data processing for story mapping
Spatial analysis
Deep learning and data mining
Historical scene reconstruction
Detection and monitoring of environment/landscape changes
Documentation, risk assessment, and conservation for cultural heritage

Published Papers (12 papers)

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Editorial

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3 pages, 173 KiB

Open AccessEditorial

Special Issue on Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences

by Tung-Ching Su

Appl. Sci. 2023, 13(13), 7631; https://0-doi-org.brum.beds.ac.uk/10.3390/app13137631 - 28 Jun 2023

Viewed by 536

Abstract

Remote sensing has played a pivotal role in advancing the fields of archaeology, geography, and earth sciences, offering new perspectives and unparalleled opportunities for research, analysis, and interpretation within these disciplines [...] Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

Research

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17 pages, 15882 KiB

Open AccessArticle

The Use of Machine Learning and Satellite Imagery to Detect Roman Fortified Sites: The Case Study of Blad Talh (Tunisia Section)

by Nabil Bachagha, Abdelrazek Elnashar, Moussa Tababi, Fatma Souei and Wenbin Xu

Appl. Sci. 2023, 13(4), 2613; https://0-doi-org.brum.beds.ac.uk/10.3390/app13042613 - 17 Feb 2023

Cited by 3 | Viewed by 2391

Abstract

This study focuses on an ad hoc machine-learning method for locating archaeological sites in arid environments. Pleiades (P1B) were uploaded to the cloud asset of the Google Earth Engine (GEE) environment because they are not yet available on the platform. The average of the SAR data was combined with the P1B image in the selected study area called Blad Talh at Gafsa, which is located in southern Tunisia. This pre-desert region has long been investigated as an important area of Roman civilization (106 BCE). The results show an accurate probability map with an overall accuracy and Kappa coefficient of 0.93 and 0.91, respectively, when validated with field survey data. The results of this research demonstrate, from the perspective of archaeologists, the capability of satellite data and machine learning to discover buried archaeological sites. This work shows that the area presents more archaeological sites, which has major implications for understanding the archaeological significance of the region. Remote sensing combined with machine learning algorithms provides an effective way to augment archaeological surveys and detect new cultural deposits. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

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14 pages, 3463 KiB

Open AccessArticle

Field Radiometric Calibration of a Micro-Spectrometer Based on Remote Sensing of Plateau Inland Water Colors

by Jiarui Shi, Qian Shen, Yue Yao, Fangfang Zhang, Junsheng Li and Libing Wang

Appl. Sci. 2023, 13(4), 2117; https://0-doi-org.brum.beds.ac.uk/10.3390/app13042117 - 07 Feb 2023

Cited by 1 | Viewed by 1148

Abstract

Remote sensing reflectance (Rrs), which is currently measured mainly using the above-water approach, is the most crucial parameter in the remote sensing inversion of plateau inland water colors. It is very difficult to measure the Rrs of plateau inland unmanned areas; thus, we provide a measurement solution using a micro-spectrometer. Currently, commercial micro-spectrometers are not factory calibrated for radiation, and thus, a radiometric calibration of the micro-spectrometer is an essential step. This article uses an Ocean Optics micro-spectrometer (STS-VIS) and a traditional water spectrometer (Trios) to simultaneously measure the irradiance and radiance of diffuse reflectance plates with different reflectance values for field calibration. The results show the following: (1) different fiber types have different calibration coefficients, and the integration time is determined according to the diameter of the fiber and the type of fiber, and (2) by comparing the simultaneous measurement results of STS-VIS with Trios, the mean absolute percentage difference (MAPD) of both reached 18.64% and 5.11% for Qinghai Lake and Golmud River, respectively, which are accurate Rrs measurements of water bodies. The Rrs of the Hoh Xil and Qarhan Salt Lake water bodies in unmanned areas of China was measured, and this was the first collection of in situ spectral information with a micro-spectrometer. This article shows that the micro-spectrometer can perform the in situ measurement of water Rrs in unmanned inland areas. With this breakthrough in the radiometric performance of the micro-spectrometer, we are able to obtain more accurate remote sensing reflectance results of unmanned water bodies. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

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17 pages, 10513 KiB

Open AccessArticle

An Improved Shoulder Line Extraction Method Fusing Edge Detection and Regional Growing Algorithm

by Haoyang Jiao, Fayuan Li, Hong Wei and Wei Liu

Appl. Sci. 2022, 12(24), 12662; https://0-doi-org.brum.beds.ac.uk/10.3390/app122412662 - 10 Dec 2022

Cited by 2 | Viewed by 985

Abstract

Shoulder lines can best depict the morphological characteristics of the Loess Plateau. Moreover, a shoulder line depicts the external appearance of spatial differentiation of loess landforms and the internal mechanism of loess landform evolution. The efficient and accurate extraction of shoulder lines can help to deepen the re-understanding of the morphological structure and differentiation of loess landforms. However, the problem of shoulder line continuity in the extraction process has not been effectively solved. Therefore, based on high-resolution satellite images and digital elevation model (DEM) data, this study introduced the regional growing algorithm to further correct edge detection results, thereby achieving complementary advantages and improving the accuracy and continuity of shoulder line extraction. First, based on satellite images, the edge detection method was used to extract the original shoulder lines. Subsequently, by introducing the regional growing algorithm, the peaks and the outlet point extracted with the DEM were used as the growth points of the positive and negative (P-N) terrains to grow in four-neighborhood fields until they reached a P-N terrain boundary or a slope threshold. Finally, the P-N terrains extracted by the regional growing method were used to correct the edge detection results, and the “burr” was removed using a morphological image-processing method to obtain the shoulder lines. The experimental results showed that the method proposed in this paper can accurately and effectively complete the extraction of shoulder lines. Furthermore, the applicability of this method is better and opens new ideas for quantitative research on loess landforms. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

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19 pages, 20273 KiB

Open AccessArticle

GPR and Digital Survey for the Diagnosis and the 3D Representation of the Battle of Issus Mosaic from the House of the Faun, Pompeii (Naples, Italy)

by Marilena Cozzolino, Antonio De Simone, Vincenzo Gentile, Paolo Mauriello and Amanda Piezzo

Appl. Sci. 2022, 12(14), 6965; https://0-doi-org.brum.beds.ac.uk/10.3390/app12146965 - 09 Jul 2022

Cited by 1 | Viewed by 1766

Abstract

The application of non-invasive geophysical techniques and digital surveys to explore cultural heritage is becoming a very important research field. The capability to detect inner and superficial changes in the inspected surfaces allows for imaging spatial inhomogeneity and material features and planning targeted conservation and restoration interventions. In this work, the results of a research project carried out on the famous Battle of Issus Mosaic, also known as the “Alexander Mosaic”, are presented. It is a masterpiece of ancient art that was found in 1831 in the House of Faun, the most luxurious and spacious house in Pompeii. It is notable for its size (3.41 × 5.82 m), the quality of workmanship and the subject that represents the culminating phase of the battle between Alexander Magno’s army and the Persian one of Darius. In 1916, it was moved inside the National Archaeological Museum of Naples, where the original horizontal location was changed with a vertical arrangement supported by an inner wooden structure, whose exact manufacture is unclear. Today, the mosaic is affected by important instability phenomena highlighted by the appearance of the significant detachment of tiles, superficial lesions and swelling of the surface. Given the important need to preserve it, a high-detail diagnostic study was realized through a digital survey and non-invasive geophysical surveys using ground-penetrating radar (GPR). The investigation was repeated after two years, in 2018 and 2020, with the aim of verifying the evolution of degradation. The work provided a high-resolution estimate of the state of the health of the mosaic and allowed for obtaining a three-dimensional reconstruction of the internal mosaic structure, including the formulation of hypotheses on the engineering supporting works of the twentieth century; this provides an essential tool for the imminent conservation project, which also implies restoring the original horizontal position. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

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12 pages, 2510 KiB

Open AccessArticle

A Simulation Method of Two-Dimensional Sea-Surface Current Field for Trajectory Crossing Spaceborne SAR

by Yan Li, Jinsong Chong and Zongze Li

Appl. Sci. 2022, 12(12), 5900; https://0-doi-org.brum.beds.ac.uk/10.3390/app12125900 - 09 Jun 2022

Cited by 2 | Viewed by 1310

Abstract

The trajectory-crossing method is an important and effective method for spaceborne SAR (synthetic aperture radar) to detect a two-dimensional current field. However, in practical applications, there are few spaceborne SAR data that meet the requirements of close acquisition time and overlapping trajectories, which makes it difficult to comprehensively analyze the impact of different systems and environmental parameters on current measurement results from real data processing. With the proposal of a SAR constellation plan in the future, the data resources will be constantly enriched, and the trajectory-crossing method will be widely used. It is, thus, necessary to lay some theoretical foundation at present. A two-dimensional sea-surface-current-field simulation method for trajectory crossing spaceborne SAR is proposed in this paper. Based on the principles of the trajectory-crossing method, the proposed method can realize the simulation of two-dimensional sea-surface-current field under given spaceborne SAR system and environmental parameters. In this paper, the simulation process of this method is given, and the simulation experiment is performed. Compared with the current measurement results of SAR data, the simulation experiment shows that the current velocity error is less than 0.03 m/s and the direction error is less than 10 degrees, which proves the reliability of the proposed simulation method. The proposed method lays a foundation for analyzing the influence of various parameters in the application of the trajectory-crossing method. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

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24 pages, 7984 KiB

Open AccessArticle

Utilization of 3D Digital Technologies in the Documentation of Cultural Heritage: A Case Study of the Kunerad Mansion (Slovakia)

by Michal Palčák, Pavol Kudela, Miriam Fandáková and Juraj Kordek

Appl. Sci. 2022, 12(9), 4376; https://0-doi-org.brum.beds.ac.uk/10.3390/app12094376 - 26 Apr 2022

Cited by 11 | Viewed by 2373

Abstract

Preservation of cultural heritage plays an important role in society, significantly contributing to its sustainability, which is important for human development and quality of life. The issue of cultural heritage digitization has recently been the subject of increasing research and is part of the initiatives of the European Commission for the Promotion of Cultural Heritage. Therefore, it is necessary to define the stages of the digitization process, which is crucial for cultural heritage preservation. The aim of this article was to examine currently used technologies and their role in the digitization workflow, and to present a detailed historical building information model (HBIM) developed during the digitization project at the historic Kunerad Mansion. To meet these goals, we will describe the best practices for each discussed technology. Special attention is paid to data processing at the very end of the object modeling process. Additionally, particular findings alert the reader to the need to create object element databases in terms of effective point cloud modeling and present the advantages of the technologies examined over traditional ways of preserving cultural heritage. In addition to predicting procedures, cooperation at a multidisciplinary level is needed in a narrower context. On the whole, the article provides some useful suggestions for both practitioners and stakeholders. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

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21 pages, 6728 KiB

Open AccessFeature PaperArticle

Style Recognition of Door God Paintings by Hypothesis Testing for Texture Features of Painting Patterns

by Tung-Ching Su, Tsung-Chiang Wu, Ming-Hung Wun and Cheng-Wei Wang

Appl. Sci. 2022, 12(5), 2637; https://0-doi-org.brum.beds.ac.uk/10.3390/app12052637 - 03 Mar 2022

Cited by 1 | Viewed by 1229

Abstract

Many studies in the literature have presented multiple remote sensing techniques for defect inspection of paintings. At present, however, papers on defect inspection and restoration of oriental architectural arts—such as door god paintings—are still rare. If an aged and damaged door god painting needs a restoration, then following the style and treatment skill of the original artist as much as possible is important for the restoration. Unfortunately, it is usually difficult to access the original artists for some of the aged door god paintings. This paper considers the texture features of auspicious patterns of armors on warrior door gods as useful information to recognize styles of door god paintings by unknown artists. First, a two-level two-dimensional discrete wavelet transform coupled with co-occurrence matrix calculation was adopted to analyze the texture features, based on the descriptors of angular second moment (ASM), entropy (ENT), contrast (CON), homogeneity (HOM), dissimilarity (DIS), correlation (COR), and cluster tendency (CLU), in the four orientations of 0° (horizontal), 45° (vertical), and 90° and 135° (double diagonal). Second, a two-tailed t-test based on the analyzed texture features was introduced into the hypothesis testing for demonstrating the master and apprentice relationships between the surveyed artists, and for recognizing the door god painting styles of unknown artists as well. The experimental results show that the proposed method effectively describes the texture features of the auspicious patterns of the surveyed door god paintings, and is able to determine the useful co-occurrence features for recognizing unknown artists’ painting styles. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

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18 pages, 6758 KiB

Open AccessArticle

Development of an Underground Tunnels Detection Algorithm for Electrical Resistivity Tomography Based on Deep Learning

by Yin-Chun Hung, Yu-Xiang Zhao and Wei-Chen Hung

Appl. Sci. 2022, 12(2), 639; https://0-doi-org.brum.beds.ac.uk/10.3390/app12020639 - 10 Jan 2022

Cited by 1 | Viewed by 2300

Abstract

Kinmen Island was in a state of combat readiness during the 1950s–1980s. It opened for tourism in 1992, when all troops withdrew from the island. Most military installations, such as bunkers, anti airborne piles, and underground tunnels, became deserted and disordered. The entries to numerous underground bunkers are closed or covered with weeds, creating dangerous spaces on the island. This study evaluates the feasibility of using Electrical Resistivity Tomography (ERT) to detect and discuss the location, size, and depth of underground tunnels. In order to discuss the reliability of the 2D-ERT result, this study built a numerical model to validate the correctness of in situ measured data. In addition, this study employed the artificial intelligence deep learning technique for reprocessing and predicting the ERT image and discussed using an artificial intelligence deep learning algorithm to enhance the image resolution and interpretation. A total of three 2D-ERT survey lines were implemented in this study. The results indicate that the three survey lines clearly show the tunnel location and shape. The numerical simulation results also indicate that using 2D-ERT to survey underground tunnels is highly feasible. Moreover, according to a series of studies in Multilayer Perceptron of deep learning, using deep learning can clearly show the tunnel location and path and effectively enhance the interpretation ability and resolution for 2D-ERT measurement results. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

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15 pages, 9331 KiB

Open AccessFeature PaperArticle

Photogrammetry (SfM) vs. Terrestrial Laser Scanning (TLS) for Archaeological Excavations: Mosaic of Cantillana (Spain) as a Case Study

by Carmen Marín-Buzón, Antonio Miguel Pérez-Romero, Manuel J. León-Bonillo, Rubén Martínez-Álvarez, Juan Carlos Mejías-García and Francisco Manzano-Agugliaro

Appl. Sci. 2021, 11(24), 11994; https://0-doi-org.brum.beds.ac.uk/10.3390/app112411994 - 16 Dec 2021

Cited by 18 | Viewed by 3096

Abstract

The discovery of a Roman mosaic from the 2nd century AD in Cantillana (Seville) generated interest and the need for exhaustive documentation, so that it could be recreated with real measurements in a 3D model, not only to obtain an exact replica, but with the intention of analyzing and studying the behavior of two main geomatics techniques. Thus, the objective of this study was the comparative analysis of both techniques: near object photogrammetry by SfM and terrestrial laser scanner or TLS. The aim of this comparison was to assess the use of both techniques in archaeological excavations. Special attention was paid to the accuracy and precision of measurements and models, especially in altimetry. Mosaics are frequently relocated from their original location to be exhibited in museums or for restoration work, after which they are returned to their original place. Therefore, the altimetric situation is of special relevance. To analyze the accuracy and errors of each technique, a total station was used to establish the real values of the ground control points (GCP) on which the comparisons of both methods were to be made. It can be concluded that the SfM technique was the most accurate and least limiting for use in semi-buried archaeological excavations. This manuscript opens new perspectives for the use of SfM-based photogrammetry in archaeological excavations. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

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16 pages, 5776 KiB

Open AccessArticle

Spatiotemporal Assessment of Air Quality and Heat Island Effect Due to Industrial Activities and Urbanization in Southern Riyadh, Saudi Arabia

by Abeer Salman, Manahil Al-Tayib, Sulafa Hag-Elsafi, Faisal K. Zaidi and Nada Al-Duwarij

Appl. Sci. 2021, 11(5), 2107; https://0-doi-org.brum.beds.ac.uk/10.3390/app11052107 - 27 Feb 2021

Cited by 6 | Viewed by 2318

Abstract

The aim of this paper is to evaluate the air and thermal pollution in the southern suburbs of Riyadh, where people are suffering from poor air quality due to the rapid development of the industrial facilities in the area. The study involved the distribution of questionnaires to 405 residents living in that area in order to obtain their opinions about air pollution. In addition, land surface temperature and 12 components of air were measured at 18 points. In addition, the air quality data from 2016 to 2020 for Al Khaldya and Southern Ring Road air stations were assessed. Al Misfat (Oil Refinery) and the Second Industry City are significant contributors to air pollution and also result in the urban heat island effect from high temperature due to factories and industrial activities. However, all the measured components of air quality are lower than the standard limits except the element particulate matter (PM)10, which exceeds the standard limits in several parts of the study area and during several months of the year. This can surely have a negative impact on the health of residents. At the same time, this study found that the preventive measures taken to stop the spread of COVID-19 infections have led to a positive impact in the area in terms of improvement in air quality. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

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Review

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28 pages, 6100 KiB

Open AccessReview

Geographic Scene Understanding of High-Spatial-Resolution Remote Sensing Images: Methodological Trends and Current Challenges

by Peng Ye, Guowei Liu and Yi Huang

Appl. Sci. 2022, 12(12), 6000; https://0-doi-org.brum.beds.ac.uk/10.3390/app12126000 - 13 Jun 2022

Cited by 3 | Viewed by 2265

Abstract

As one of the primary means of Earth observation, high-spatial-resolution remote sensing images can describe the geometry, texture and structure of objects in detail. It has become a research hotspot to recognize the semantic information of objects, analyze the semantic relationship between objects and then understand the more abstract geographic scenes in high-spatial-resolution remote sensing images. Based on the basic connotation of geographic scene understanding of high-spatial-resolution remote sensing images, this paper firstly summarizes the keystones in geographic scene understanding, such as various semantic hierarchies, complex spatial structures and limited labeled samples. Then, the achievements in the processing strategies and techniques of geographic scene understanding in recent years are reviewed from three layers: visual semantics, object semantics and concept semantics. On this basis, the new challenges in the research of geographic scene understanding of high-spatial-resolution remote sensing images are analyzed, and future research prospects have been proposed. Full article

(This article belongs to the Special Issue Remote Sensing Applications in Archaeology, Geography, and the Earth Sciences)

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