Urban trees play a vital role in mitigating climate changes, maintaining the sustainability of ecosystems. This study focuses on the assessment of the resilience of cherry plums to climate changes, a fruit-bearing species that offers diverse ecosystem services within multifunctional urban and suburban landscapes. This study examines flowering and fruiting in the context of climate characteristics, expressed through the Day of the Year (DOY), Growing Degree Days (GDDs), and a yield over 17 consecutive years. The results indicate significant shifts in the DOY but not in the GDD, apart from the end of flowering. The onset of flowering was earlier and the end postponed, extending the phenophase by an average of 4 days. The cherry plum’s yield was unaffected by climate changes, including extreme events like a late-spring frost. The stability of the cherry plum was confirmed by the phenological patterns of the bullace (cherry plum and blackthorn hybrid) exhibiting repeated flowering in the warmest year of 2023. The cherry plum is an adaptive species, with a high adaptability to a changing climate and a high resistance to late-spring frosts; thus, it is a favorable choice in urban design and planning, demonstrating resilience to climate shifts and thriving in polluted urban environments. It is especially appreciated for multiple ecosystem services: biodiversity conservation in natural and semi-natural areas, yielding good provisions in challenging environments, and the preservation of ornamental values through an extended flowering phenophase.

The study focuses on describing key events in the flowering phenophases of woody taxa that promote practical landscape sustainability and design planning. Apart from the beginning of flowering, the full development and the duration of phenophases are important for landscape architecture, consumers, and pollination. The phenological patterns of 13 woody taxa were monitored for 16 years through 90,860 phenological observations from the BBCH scale for the period 2007–2022. Growing degree days were determined by combining phenological and climatic data and a linear trend was used to assess phenophase tendencies. Mann–Kendall and Sen’s slope tests and Spearman’s correlation coefficient were used to assess statistical significance. Shifts in flowering indicated warming trends, reflecting various changes in phenology. Early flowering taxa were affected the most, but plants shifted phenophases in both directions (earlier and later in the year). Repeated flowering (and occasionally fruiting) and even third flowering, as seen in 2022, can significantly affect biodiversity and lead to plant–pollinator asynchrony and changes in ecosystem functioning, ecological interaction, and landscape design. A list of native and introduced taxa and their adaptation mechanisms to climate change are provided and can be used for sustainable landscape design and nature-based solutions in landscape architecture.

The study evaluated a new model of a Plair SA airflow cytometer, Rapid-E+, and assessed its suitability for airborne pollen monitoring within operational networks. Key features of the new model are compared with the previous one, Rapid-E. A machine learning algorithm is constructed and evaluated for (i) classification of reference pollen types in laboratory conditions and (ii) monitoring in real-life field campaigns. The second goal of the study was to evaluate the device usability in forthcoming monitoring networks, which would require similarity and reproducibility of the measurement signal across devices. We employed three devices and analysed (dis-)similarities of their measurements in laboratory conditions. The lab evaluation showed similar recognition performance to that of Rapid-E, but field measurements in conditions when several pollen types were present in the air simultaneously showed notably lower agreement of Rapid-E+ with manual Hirst-type observations than those of the older model. An exception was the total-pollen measurements. Comparison across the Rapid-E+ devices revealed noticeable differences in fluorescence measurements between the three devices tested. As a result, application of the recognition algorithm trained on the data from one device to another led to large errors. The study confirmed the potential of the fluorescence measurements for discrimination between different pollen classes, but each instrument needed to be trained individually to achieve acceptable skills. The large uncertainty of fluorescence measurements and their variability between different devices need to be addressed to improve the device usability.

The positive impacts of urban forests on residents’ health are widely acknowledged. However, the methods used to quantify and demonstrate this relation are still a focus of research. The aim of the paper is to examine the relationship between the size and quality of different urban green areas to residents’ health based on the face-to-face survey and remote sensing data at 12 locations in Belgrade. The socio-economic and self-perceived health characteristics were analyzed. Based on green areas’ size and pollution, municipalities were divided into “less green” and “green”. Vegetation quality was assessed by Sentinel-2 vegetation indexes (VI). Results show that residents in less green and green municipalities differ in physical, social, and emotional health. The quality of green areas was inversely proportional to the amount of money spent on medications and the number of doctor’s visits indicating potential mechanisms of the health benefits of green areas. The lack of facilities led to different appreciation among residents. Results suggest that the quality of green infrastructure is more important than the amount in promoting residents’ health. Relating the characteristics of green areas to visitors proved to improve the correlation between residents’ health and the quality of green areas.

Remote sensing of phenology is adopted as the practice in greenery monitoring. Now research is turned towards the fusion of data from various sensors to fill in the gap in time series and allow monitoring of pests and disturbances. Poplar species were monitored for the determination of the best approach for detecting phenology and disturbances. With the adjustments that include a choice of indices, wavelengths, and a setup, a multispectral camera may be used to calibrate satellite images. The image processing pipeline included different denoising and interpolation methods. The correlation of the changes in a signal of top and lateral imaging proved that the contribution of the whole canopy is reflected in satellite images. Normalized difference vegetation index (NDVI) and normalized difference red edge index (NDRE) successfully distinguished among phenophases and detected leaf miner presence, unlike enhanced vegetation index (EVI). Changes in the indices were registered before, during, and after the development of the disease. NDRE is the most sensitive as it distinguished among the different intensities of damage caused by pests but it was not able to forecast its occurrence. An efficient and accurate system for detection and monitoring of phenology enables the improvement of the phenological models’ quality and creates the basis for a forecast that allows planning in various disciplines.