A technical and scientific overview regarding satellite-derived bathymetry (SDB)—one of the most promising and relatively cheap methods of shallow water depth determination—is presented. The main goal of the article is to present information about the possibilities of the SDB method to meet the demanding standard of bathymetric measurements in coastal mapping areas up to 20 m deep, i.e., up to depth areas where the largest number of ports and access waterways are located, as obtained using the bibliometric analysis. The Web of Science (WoS) and Scopus scientific databases, as well as R studio applications Bibliometrix and Biblioshiny, were used for scientific analysis. The bibliometric analysis presents the quantitative aspects of producing and disseminating scientific and professional articles with SDB as their topic. Therefore, the purpose of this study was to give the academic community an insight into the current knowledge about the SDB method, its achievements and shortcomings. The results of the bibliometric analysis of articles dealing with SDB show that most authors use empirical statistical methods. However, in recent years, articles using automated artificial intelligence methods have prevailed, especially the machine learning method. It is concluded that SDB data can become a very important low-cost source of bathymetric data in shallow coastal areas. Satellite methods have been proven to be very effective in very shallow coastal areas (up to a depth of about 20 m), and their biggest advantage is that the depth data obtained in this way are relatively low cost, while major limitations are associated with the parameters that determine the properties of the atmosphere and water column (clear atmosphere and water column) and bottom material. Procedures for different bathymetric applications are being developed. Regardless of the significant progress of the SDB method, which was manifested in the development of sensors and processing methods, its results still do not meet the International Hydrographic Organization (IHO) Standards for Hydrographic Surveys S-44.

In the last several decades, the disposal and accumulation of debris in the marine and coastal environment has been one of the biggest and fastest-growing threats to the health of the world's oceans. Marine debris is present in all marine habitats and represents a great danger to global environmental and human health. Therefore, this paper aims to support efforts to achieve Good Environmental Status with respect to marine debris in all oceans and seas. The application of optical remote sensing methods for floating marine debris detection was briefly reviewed and the bibliometric analysis of the professional and scientific literature elaborated upon. In the overview part, previously used marine debris detection methods have been listed. The WoSCC (Web of Science Core Collection) and Scopus databases were considered, and the R Studio Bibliometrix and Biblioshiny software tools used for bibliometric analysis. 209 documents that can be classified into 43 research fields were identified in the two databases. Approximately 20% of the documents were published in two journals: the Marine Pollution Bulletin and Remote Sensing. Marine debris research was mainly published in the USA, Portugal, Italy, the United Kingdom, Germany, and China. A total of 54 countries participated in the publication of documents and it should be emphasized that all countries have shown great interest in international cooperation during the scientific research on marine debris. Scientific research on marine debris was found to have increased significantly since 2017, which is highly important for the protection of the environment and human health.

The paper gives a brief description of the remote sensing method used for the identification and extraction of water surfaces. Landsat 8 and Sentinel 2 satellite imagery was used to separate land from bodies of water in the complex karst area surrounding the Croatian Cetina River, flowing into the Adriatic Sea. Water indexing methods are presented in detail. The most frequently used water indices were selected: NDWI, MNDWI, AWEI_nsh, AWEI_sh, WRI and LSWI, and their results compared. The combination of satellite imagery and calculated water indices is concluded to be very useful for the identification and mapping of the area and banks of lakes, riverine zones, river mouths and the coastline in the coastal zone. Landsat 8 satellite imagery is slightly inferior to Sentinel 2 due to lower image resolution. The best results were obtained with the NDWI water index and the worst with LSWI.

Split Metropolitan area surface temperature assessment with remote sensing method Land surface temperature (LST) is a very important parameter for a wide variety of Earth processes. The satellite thermal data enable us to obtain information on land surface temperature. The Landsat Mission is the most important and longest satellite mission with the thermal band capability and a sufficient spatial resolution. Landsat thermal channels have been used in this research to determine the LST within the metropolitan area of Split. The results point to the phenomenon of urban heat islands (UHI), as the simultaneous effect of intensive urbanization in the city of Split metropolitan area, and the observed climate changes.

This study presents a comprehensive framework for evaluating urban heat resilience, incorporating urban climatology models, their characteristics, and simulation programs. Utilizing the local climate zone (LCZ) classification method, this research explores how urban geomorphology influences the thermal characteristics of the area. This study integrates spatial data at different “levels of detail” (LOD), from the meso- to building scales, emphasizing the significance of detailed LOD 3 models acquired through 3D laser scanning. The results demonstrate the ability of these models to identify urban heat islands (UHIs) and to simulate urban planning scenarios, such as increasing green spaces and optimizing building density, to mitigate the UHI effect. The ST3D 3D model of the city of Split, represented using an LOD 2 object model, is utilized for meso- and local-scale analyses, while LOD 3 models derived from laser scanning provided in-depth insights at the building scale. The case studies included the Faculty of Civil Engineering, Architecture, and Geodesy building on the University of Split campus and the old town hall in the densely built city center. This framework highlights the advantages of integrating GIS and BIM technology with urban climate analyses, offering tools for data-driven decision-making and fostering sustainable, climate-resilient urban planning.

The article presents the most critical factors that affect the soil temperature, such as the effects of the canyon, anthropogenic heat, greenhouse effect, effective reflectivity, evaporating reduction and turbulent transfer of heat. Most...