The article describes the use of publicly available materials of radar mapping from spacecraft as a way to increase the reliability, as well as to reduce the cost and time of work to select the site of linear construction projects situated in remote underdeveloped areas. Based on the results of theoretical study and practical application of radar mapping of the Earth's surface from spacecrafts the conclusion is made about the availability of these materials, their reliability (relevance) and accuracy in order to select the site of linear construction projects at the concept design stage.

The integration of LiDAR and Artificial Intelligence (AI) has revolutionized feature detection in urban environments. LiDAR systems, which utilize pulsed laser emissions and reflection measurements, produce detailed 3D maps of urban landscapes. When combined with AI, this data enables accurate identification of urban features such as buildings, green spaces, and infrastructure. This synergy is crucial for enhancing urban development, environmental monitoring, and advancing smart city governance. LiDAR, known for its high-resolution 3D data capture capabilities, paired with AI, particularly deep learning algorithms, facilitates advanced analysis and interpretation of urban areas. This combination supports precise mapping, real-time monitoring, and predictive modeling of urban growth and infrastructure. For instance, AI can process LiDAR data to identify patterns and anomalies, aiding in traffic management, environmental oversight, and infrastructure maintenance. These advancements not only improve urban living conditions but also contribute to sustainable development by optimizing resource use and reducing environmental impacts. Furthermore, AI-enhanced LiDAR is pivotal in advancing autonomous navigation and sophisticated spatial analysis, marking a significant step forward in urban management and evaluation. The reviewed paper highlights the geometric properties of LiDAR data, derived from spatial point positioning, and underscores the effectiveness of machine learning algorithms in object extraction from point clouds. The study also covers concepts related to LiDAR imaging, feature selection methods, and the identification of outliers in LiDAR point clouds. Findings demonstrate that AI algorithms, especially deep learning models, excel in analyzing high-resolution 3D LiDAR data for accurate urban feature identification and classification. These models leverage extensive datasets to detect patterns and anomalies, improving the detection of buildings, roads, vegetation, and other elements. Automating feature extraction with AI minimizes the need for manual analysis, thereby enhancing urban planning and management efficiency. Additionally, AI methods continually improve with more data, leading to increasingly precise feature detection. The results indicate that the pulse emitted by continuous wave LiDAR sensors changes when encountering obstacles, causing discrepancies in measured physical parameters.

There have been various concerns about the environmental impact of construction works. This generates a need to take a more proactive approach in evaluating the environmental impacts of construction operations and further explore ways to reduce the environmental impacts. Enormous opportunities exist within the building industry to achieve a reduction in greenhouse gas emissions. The aim of the study is to develop a framework for the evaluation of improvement opportunities for environmental impact for onsite and offsite building construction works using life cycle assessment (LCA) and value-stream-mapping concepts. Various tools for LCA exist; however, there is a need for the development of an LCA framework and improvement opportunities that can be localized to various communities to evaluate improvement opportunities for building construction. This study conducts a review of methods to evaluate the LCA of buildings on local construction sites. A procedure for establishing improvement opportunities is also developed. Based on the author’s knowledge and experience, including site visits, using value stream mapping (VSM) techniques, a conceptual framework of the present state map and future state map of residential construction works was developed. The study presents a procedure for the evaluation of improvement opportunities for the environmental impacts of construction operations.

Today, the presentation of a three-dimensional model of real-world features is very important and widely used and has attracted the attention of researchers in various fields, including surveying and spatial information systems, and those interested in the three-dimensional reconstruction of buildings. The building is the key part of the information in a three-dimensional city model, so extracting and modeling buildings from remote sensing data is an important step in building a digital model of a city. LiDAR technology due to its ability to map in all three modes of one-dimensional, two-dimensional, and three-dimensional is a suitable solution to provide hyperspectral and comprehensive images of the building in an urban environment. In this review article, a comprehensive review of the methods used in identifying buildings from the past to the present and appropriate solutions for the future is discussed.

Mashhad is one of the important metropolitans in the northeast of Iran with over 25 million tourists per year. After evaluating the physical space of Mashhad in terms of semantics and identity with the aim of promoting tourism, 127 valuable places with cultural, historical, and religious values were identified, assessed, and analyzed using a Geographic Information Systems (GIS). Therefore, the appropriate distribution of tourist routes for travelers to visit the city of Mashhad was done and 10 corridors and zones were selected. The basis of this choice was the existence of a valuable place at origin and destination of the routes and the existence of appropriate tourism, commercial, welfare and cultural infrastructure and ability to access various uses. Percentage and number of valuable places in each proposed route necessarily meant percentage of the total, excluding repetition in other routes.

This paper discusses the analysis of correct digitization practices to follow for maximum performance of the technique. Although it is written for cases that fall within the broader context of culture and cultural heritage, it is ultimately about writing rules that are not limited to the above-mentioned cases, but can be used in more general situations, particularly printed materials. This paper will therefore discuss the technical characteristics of the choice of digital imaging devices and distinguish the types of quality calculation in the different cases of digitized text, digitized manuscript, digitized maps, and photographs.

This paper deals with the mapping of shorelines through existing maps. Its main purpose is not to give an accurate change of sea level and shoreline in general, but to give guidelines to a more general mapping of shorelines. Geographic Information System (GIS) and paleoenvironmental analysis are powerful tools for archaeology and environmental researches and contributes in such a direction. Furthermore, this essay will present an analysis of the shoreline changes and the resultant geomorphologies during the prehistoric eras, especially the Mesolithic, Neolithic, and the Helladic eras of the area. The study area which was selected concerns the west part of Messenia Prefecture in Greece. More specifically it concerns the wider area of Pylos and the Navarino bay. The Navarino bay is located near the ancient city of Pylos and the kingdom and palace of Nestor during the Mycenaean period