scholarly journals Towards National Archaeological Mapping. Assessing Source Data and Methodology—A Case Study from Scotland

Geosciences ◽  
2018 ◽  
Vol 8 (8) ◽  
pp. 272 ◽  
Author(s):  
Łukasz Banaszek ◽  
Dave Cowley ◽  
Mike Middleton

While the National Record of the Historic Environment (NRHE) in Scotland contains valuable information on more than 170,000 archaeological monuments, it is clear that this dataset is conditioned by the disposition of past survey and changing parameters of data collection strategies over many decades. This highlights the importance of creating systematic datasets, in which the standards to which they were created are explicit, and against which the reliability of our knowledge of the material remains of the past can be assessed. This paper describes issues of data structure and reliability, then discussing the methodologies under development for expediting the progress of national-scale mapping with specific reference to the Isle of Arran. Preliminary outcomes of a recent archaeological mapping project of the island, which has been used to develop protocols for rapid large area mapping, are outlined. The primary sources for the survey were airborne laser scanning derivatives and orthophotographs, supplemented by field observation, and the project has more than doubled the number of known monuments of Arran. The survey procedures are described, followed by a discussion of the utility of ‘general purpose’ remote sensed datasets, focusing on the assessment of strengths and weaknesses for rapid mapping of large areas.

2019 ◽  
Vol 31 (1) ◽  
pp. 105-133
Author(s):  
Zdzisław Kurczyński

Abstract The article is a retrospective analysis of the development of airborne laser scanning technology in the country in the past twenty years, i.e. from the beginnings of this technique use in Poland to the present day. The emphasis in the text is placed on development trends and scientific and application problems in the field of technology undertaken by national research centres. The review is based on numerous publications in this field, which have been released over two decades mainly in the “Archive of Photogrammetry, Cartography and Remote Sensing”. Therefore, the article is a presentation of the progress in the area of airborne laser scanning through an attempt to systematize and review national publications in this scope. It also presents the development of the national production potential and the level of the country’s coverage with data and products derived from airborne laser scanning.


2018 ◽  
Vol 8 (2) ◽  
pp. 20170033 ◽  
Author(s):  
Sanna Kaasalainen ◽  
Markku Åkerblom ◽  
Olli Nevalainen ◽  
Teemu Hakala ◽  
Mikko Kaasalainen

Multispectral terrestrial laser scanning (TLS) is an emerging technology. Several manufacturers already offer commercial dual or three wavelength airborne laser scanners, while multispectral TLS is still carried out mainly with research instruments. Many of these research efforts have focused on the study of vegetation. The aim of this paper is to study the uncertainty of the measurement of spectral indices of vegetation with multispectral lidar. Using two spectral indices as examples, we find that the uncertainty is due to systematic errors caused by the wavelength dependency of laser incidence angle effects. This finding is empirical, and the error cannot be removed by modelling or instrument modification. The discovery and study of these effects has been enabled by hyperspectral and multispectral TLS, and it has become a subject of active research within the past few years. We summarize the most recent studies on multi-wavelength incidence angle effects and present new results on the effect of specular reflection from the leaf surface, and the surface structure, which have been suggested to play a key role. We also discuss the consequences to the measurement of spectral indices with multispectral TLS, and a possible correction scheme using a synthetic laser footprint.


Silva Fennica ◽  
2021 ◽  
Vol 55 (4) ◽  
Author(s):  
Hans Ørka ◽  
Endre Hansen ◽  
Michele Dalponte ◽  
Terje Gobakken ◽  
Erik Næsset

Tree species composition is an essential attribute in stand-level forest management inventories and remotely sensed data might be useful for its estimation. Previous studies on this topic have had several operational drawbacks, e.g., performance studied at a small scale and at a single tree-level with large fieldwork costs. The current study presents the results from a large-area inventory providing species composition following an operational area-based approach. The study utilizes a combination of airborne laser scanning and hyperspectral data and 97 field sample plots of 250 m collected over 350 km of productive forest in Norway. The results show that, with the availability of hyperspectral data, species-specific volume proportions can be provided in operational forest management inventories with acceptable results in 90% of the cases at the plot level. Dominant species were classified with an overall accuracy of 91% and a kappa-value of 0.73. Species-specific volumes were estimated with relative root mean square differences of 34%, 87%, and 102% for Norway spruce ( (L.) Karst.), Scots pine ( L.), and deciduous species, respectively. A novel tree-based approach for selecting pixels improved the results compared to a traditional approach based on the normalized difference vegetation index.22Picea abiesPinus sylvestris


2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Ho-Kyeong Ra ◽  
Hee Jung Yoon ◽  
Sang Hyuk Son ◽  
John A. Stankovic ◽  
JeongGil Ko

With the exponential improvement of software technology during the past decade, many efforts have been made to design remote and personalized healthcare applications. Many of these applications are built on mobile devices connected to the cloud. Although appealing, however, prototyping and validating the feasibility of an application-level idea is yet challenging without a solid understanding of the cloud, mobile, and the interconnectivity infrastructure. In this paper, we provide a solution to this by proposing a framework called HealthNode, which is a general-purpose framework for developing healthcare applications on cloud platforms using Node.js. To fully exploit the potential of Node.js when developing cloud applications, we focus on the fact that the implementation process should be eased. HealthNode presents an explicit guideline while supporting necessary features to achieve quick and expandable cloud-based healthcare applications. A case study applying HealthNode to various real-world health applications suggests that HealthNode can express architectural structure effectively within an implementation and that the proposed platform can support system understanding and software evolution.


2014 ◽  
pp. 131-142
Author(s):  
Vito Porcelli ◽  
Fernando Cotino Villa ◽  
Josep Blasco i Senabre ◽  
Vicent Escrivá Torres ◽  
Julian Esteban Chapapría

2014 ◽  
Vol 72 (1) ◽  
pp. 47-56 ◽  
Author(s):  
Andreas Barth ◽  
Johan J. Möller ◽  
Lars Wilhelmsson ◽  
John Arlinger ◽  
Rikard Hedberg ◽  
...  

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