Urban Heat Island (UHI) is a phenomenon specific to urban areas where higher air temperatures manifest in the city area in relation to its surrounding rural landscape. Currently, UHI is one of the most dangerous environmental conditions for cities as well as their residents. It is expected that the intensity of UHI will increase with climate change. This work presents an analysis of the UHI phenomenon for the City of Zagreb, Croatia in the summertime period 2013–2022. In order to explore UHI, Land Surface Temperature (LST) was calculated using Landsat 8 (OLI TIRS sensor) satellite imagery. After the delineation of UHI, calculated temperatures were put in relation to NDVI (Normalised Difference Vegetation Index) and NDBI (Normalised Difference Built-Up Index) indices for the study area. Results show the similarity of mean temperatures over the observed period. However, the influence of external variables on UHI’s spatial expression was observed. Forest-covered areas and other green parts of the city’s infrastructure express the lowest temperatures, while built-up sites are the hottest points in cities. Results confirm the importance of urban green infrastructure for resilient cities and present the results of a long-term UHI observation in a Southeast European city.

Background and Purpose: In Zagreb, the forests have assumed the characteristics of forest parks, of which the most famous and the most visited is Maksimir Park. The health condition of many trees has deteriorated due to environmental changes and the forest's age. The tree health status can be monitored by direct observation in the field using the terrestrial method, or by remote sensing methods. Recent advances in technology have made it possible to use high-resolution satellite imagery to monitor the damage. Materials and Methods: In order to estimate the health status of trees, the research area - Maksimir Forest Park - was visually interpreted by means of the WorldView 2 (WV2) satellite image, color composite (8, 5, 3). Such color composite was also used to delineate the strata. After delineation, a systematic sample of 25x25 m was laid over the stratum to help interpret the tree health status. Differences in tree damage were observed by comparing the WV2 images and other satellite images (Google Earth images from 2014 and 2016) recorded at different points in time. Field research was then conducted in order to inventory the current situation. Results: The main results of the research in Maksimir Forest Park include the calculation of damage indicators by tree species, as well as thematic maps with the spatial distribution of the mean damage (SO) and damage index (IO) for those tree species which are most represented in a particular stratum. Mean and significant damage of the most represented tree species and overall is also presented spatially in the form of thematic maps. A comparison of the results of WV2 satellite imagery and satellite images taken from Google Earth denoted a change in the tree health status, which confirms that satellite imagery can serve to inventory and track the condition in an area over a number of years. Field investigations and the assessment of tree health status confirmed the results obtained by satellite imagery interpretation. Conclusions: Since quality forest monitoring is based on systematic collection of forest data in any area or at any point in time, the obtained results not only represent the current health status, but also provide a basis for monitoring and predicting the future conditions.

Data on forests (e.g., height, diameter at breast height and volume) are increasingly being collected using remote sensing methods, leading to improved forest inventories. At present, a popular method for data collection is the use of unmanned aerial vehicles (UAVs) equipped with LiDAR sensors, which allow for a more detailed assessment of structural parameters in both space and time, facilitating the practical application of more complex forest management systems. Therefore, the main objective of this study was to measure the structural elements of stands (e.g., volume, basal area, tree count, height, diameter at breast height, crown width, and area) from LiDAR images and determine the accuracy of the obtained results. The research was conducted in a 5500 ha area containing some of the most valuable forests in Croatia, namely, lowland oak forests. The results of this study show that there are no statistically significant differences between the diameters and heights measured in the field and those from LiDAR images and, consequently, no difference in the calculated volume. This study also concluded that the use of unmanned aerial vehicles with various sensors can significantly reduce fieldwork while achieving the same accuracy in the results, thus leading to substantial savings in both time and money.

Data on forests (height, diameter at breast height, volume, etc.) are increasingly being collected using remote sensing methods, which improve forest inventories. The latest popular method of data collection is through unmanned aerial vehicles (UAVs) equipped with LiDAR sensors, which allow for a more detailed assessment of structural parameters in space and time, facilitating the practical application of more complex forest management systems. Therefore, the main objective of this study was to measure the structural elements of the stand (volume, basal area, tree count, height, diameter at breast height, crown width and area, etc.) from LiDAR images and determine the accuracy of the results obtained. The research was conducted in the area of the most valuable forests in Croatia – the lowland oak forests, covering an area of 5500 ha. The results of the study showed that there is no statistically significant difference between the diameters and heights measured in the field and those from LiDAR images, and consequently, no difference in the calculated volume. The study also concluded that the use of unmanned aerial vehicles with various sensors can significantly reduce fieldwork while achieving the same accuracy in the results, thus leading to substantial savings in both time and money.

Negativne posljedice propadanja šuma nastoje se umanjiti provođenjem gospodarskih mjera i praćenjem zdravstvenog stanja stabala, odnosno procjenom oštećenosti krošanja. Utvrđivanje zdravstvenog stanja šuma provodi se, osim terestričkim načinom, i met...