Search Results (14)

Agrivoltaic (Agri-PV) systems face the critical challenge of balancing photovoltaic energy generation with crop productivity, yet systematic approaches to quantifying the trade-offs between these objectives remain scarce. In this study, we identify nine essential design indicators: panel tilt angle, elevation, photovoltaic coverage ratio, shading factor, land equivalent ratio, photosynthetically active radiation (PAR) utilization, crop yield stability index, water use efficiency, and return on investment. We introduce a novel dual matrix Analytic Hierarchy Process (AHP) to evaluate their relative significance. An international panel of eighteen Agri-PV experts, encompassing academia, industry, and policy, provided pairwise comparisons of these indicators under two objectives: maximizing annual energy yield and sustaining crop output. The high consistency observed in expert responses allowed for the derivation of normalized weight vectors, which form the basis of two Weighted Influence Matrices. Analysis of Total Weighted Influence scores from these matrices reveal distinct priority sets: panel tilt, coverage ratio, and elevation are most influential for energy optimization, while PAR utilization, yield stability, and elevation are prioritized for crop productivity. This methodology translates qualitative expert knowledge into quantitative, actionable guidance, clearly delineating both synergies, such as the mutual benefit of increased elevation for energy and crop outcomes, and trade-offs, exemplified by the negative impact of high photovoltaic coverage on crop yield despite gains in energy output. By offering a transparent, expert-driven decision-support tool, this framework enables practitioners to customize Agri-PV system configurations according to local climatic, agronomic, and economic contexts. Ultimately, this approach advances the optimization of the food energy nexus and supports integrated sustainability outcomes in Agri-PV deployment. Full article

Objectives: The increasing reliance on online platforms for dental education necessitates an assessment of the quality and reliability of available resources. This study aimed to evaluate YouTube videos as educational tools for Class IV resin composite restorations. Methods: The first 100 YouTube videos were screened, and 73 met the inclusion criteria. The videos were evaluated using the Video Information and Quality Index (VIQI) and specific content criteria derived from the dental literature. Videos with a score below the mean were identified as low-content videos. Results: No significant differences were noted between high- and low-content videos when examining the number of views, number of likes, duration, days since upload, viewing rate, interaction index, and number of subscribers (p > 0.05). The high-content videos demonstrated higher mean values compared with the low-content videos in flow (4.11 vs. 3.21; p < 0.0001), accuracy (4.07 vs. 3.07; p < 0.0001), quality (4 vs. 2.66; p < 0.0001), and precision (4.16 vs. 2.86; p < 0.0001). The overall VIQI score was significantly higher (p < 0.0001) for high-content videos (Mean 16.34; SD 2.46) compared with low-content videos (Mean 11.79; SD 2.96). For content score, high-content videos (Mean 9.36; SD 1.33) had a higher score (p < 0.0001) than low-content videos (Mean 4.90; SD 2.04). The key areas lacking sufficient coverage included occlusion, shade selection, and light curing techniques. Conclusions: While a significant portion of YouTube videos provided high-quality educational content, notable deficiencies were identified. This analysis serves as a call to action for both content creators and educational institutions to prioritize the accuracy and completeness of online dental education. Full article

In the context of cultural tourism integration, tourists’ spatial perception intention is an important carrier of spatial evaluation. In historic cultural districts represented by Jinan Mingfu City, tourists’ perceptual depth remains underexplored, leading to a misalignment between cultural tourism development and spatial quality needs. Taking Jinan Mingfu City as a representative case of a historic cultural district, while the living heritage model has revitalized local economies, the absence of a tourist perspective has resulted in misalignment between cultural tourism development and spatial quality requirements. This study establishes a technical framework encompassing “data crawling-factor aggregation-human-machine collaborative optimization”. It integrates Python web crawlers, SnowNLP sentiment analysis, and TF-IDF text mining technologies to extract physical elements; constructs a three-dimensional evaluation framework of “visual perception-spatial comfort-cultural experience” through SPSS principal component analysis; and quantifies physical element indicators such as green vision rate and signboard clutter index through street view semantic segmentation (OneFormer framework). A synergistic mechanism of machine scoring and manual double-blind scoring is adopted for correlation analysis to determine the impact degree of indicators and optimization strategies. This study identified that indicators such as green vision rate, shading facility coverage, and street enclosure ratio significantly influence tourist evaluations, with a severe deficiency in cultural spaces. Accordingly, it proposes targeted strategies, including visual landscape optimization, facility layout adjustment, and cultural scenario implementation. By breaking away from traditional qualitative evaluation paradigms, this study provides data-based support for the spatial quality enhancement of historic districts, thereby enabling the transformation of these areas from experience-oriented protection to data-driven intelligent renewal and promoting the sustainable development of cultural tourism. Full article

To address the escalating urban heat stress driven by global warming and rapid urbanization, this study integrates multi-source remote sensing data to assess the spatiotemporal dynamics of summer thermal comfort across the Yangtze River Delta Urban Agglomeration (YRDUA) from 2000 to 2020. By combining 2D landscape pattern metrics with 3D building morphological features, this study employs an XGBoost model enhanced with SHAP and PDP techniques to reveal the nonlinear and threshold effects of landscape configurations on the Universal Thermal Climate Index (UTCI). The results show the following: (1) during the study period, over 90% of the region experienced strong or extreme heat stress, and 76.8% of the area exhibited a rising UTCI trend, with an average increase of 0.09 °C per year; (2) forest coverage exceeding 50% reduced the UTCI by approximately 2.5 °C, and an increased water area lowered the UTCI by around 1.5 °C, while highly clustered cropland intensified the UTCI by about 1.5 °C; and (3) a moderate increase in building height and shape complexity improved ventilation and shading, reducing the UTCI by roughly 0.5 °C. These findings highlight that optimizing the blue–green infrastructure and 3D urban form are effective strategies to mitigate urban heat stress, offering scientific guidance for sustainable urban planning. Full article

The homogeneous turbid medium assumption inherent to the Beer-Lambert’s law can lead to a reduction in the shading effect between leaves when non-green vegetation canopies are present, resulting in an overestimation of the fraction of absorbed photosynthetically active radiation (FAPAR). This paper proposed a method to improve the FAPAR estimation (FAPAR_FVC) based on Beer-Lambert’s law by incorporating fractional vegetation coverage (FVC). Initially, the canopy-scale leaf area index (LAI) of the green canopy distribution area within the pixel (sample site) was determined based on the FVC. Subsequently, the canopy-scale FAPAR was calculated within the green canopy distribution area, adhering to the assumption of a homogeneous turbid medium in the Beer-Lambert’s law. Finally, the average FAPAR across the pixel (sample site) was calculated based on the FVC. This paper conducted a case study using measured data from the BigFoot Project and grass savanna in Senegal, West Africa, as well as Moderate Resolution Imaging Spectroradiometer (MODIS) LAI/FPAR products. The results indicated that the FAPAR_FVC approach demonstrated superior accuracy compared to the FAPAR determined by MODIS LAI, according to the Beer-Lambert’s law (FAPAR_LAI) and MODIS FPAR products (FAPAR_MOD). The mean absolute percentage error of FAPAR_FVC was 48.2%, which is 25.6% and 52.1% lower than that of FAPAR_LAI and FAPAR_MOD, respectively. The mean percentage error of FAPAR_FVC was 16.8%, which was 71.6% and 73.4% lower than that of FAPAR_LAI and FAPAR_MOD, respectively. The improvements in accuracy and the decrease in overestimation for FAPAR_FVC became more pronounced with increasing FVC compared to FAPAR_LAI. The findings suggested that the FAPAR_FVC method enhanced the accuracy of FAPAR estimation under the presence of non-green vegetation canopies. The method can be extended to regional scale FAPAR and gross primary production (GPP) estimations, thereby providing more accurate inputs for understanding its tempo-spatial patterns and drivers. Full article

With the acceleration of global climate change and urbanization, the urban heat island effect has significantly impacted the quality of life of urban residents. Although numerous studies have focused on macro-scale factors such as air temperature, surface albedo, and green space coverage, relatively little attention has been paid to micro-scale factors, such as shading provided by building facades and tree canopy coverage. However, these micro-scale factors play a significant role in enhancing pedestrian thermal comfort. This study focuses on a city community in China, aiming to assess the thermal comfort of urban streets during the summer. Utilizing high-resolution 3D geographic data and street view images extracted from drone data, this study comprehensively considers the mechanisms affecting the urban street thermal environment and the human comfort requirements for shading and greening. By proposing quantitative indicators from multiple scales and dimensions, this study thoroughly quantifies the impact of the surrounding environment, greening, shading effects, buildings, and road design on the thermal comfort of summer streets. The results show that increasing tree canopy coverage by 10 m can significantly reduce the surrounding temperature, and a building layout extending 200 m can regulate temperature. The distribution of shadows at different times significantly affects thermal comfort, while the sky view factor negatively correlates with thermal comfort. Environments with a high green view index enhance visual comfort. This study reveals the specific contributions of different environmental characteristics to street thermal comfort and identifies factors that significantly impact thermal comfort. This provides a scientific basis for urban green space planning and thermal comfort improvement, holding substantial practical significance. Full article

Building height (BH) estimation is crucial for urban spatial planning and development. BH estimation using digital surface model data involves obtaining ground and roof elevations. However, vegetation and shadows around buildings affect the selection of the required elevation, resulting in large BH estimation errors. In highly urbanized areas, buildings of similar heights often have similar characteristics and spatial proximity, which have reference significance in BH estimation but are rarely utilized. Herein, we propose a BH estimation method based on BIRCH clustering and a random forest (RF) model. We obtain the initial BH results using a method based on the optimal ground search area and a multi-index evaluation. BIRCH clustering and an RF classification model are used to match buildings of similar heights based on their spatial distance and attribute characteristics. Finally, the BH is adjusted based on the ground elevation obtained from the secondary screening and the BH matching. The validation results from two areas with over 12,000 buildings show that the proposed method reduces the root-mean-square error of the final BH results compared with the initial results. Comparing the obtained height maps shows that the final results produce a relatively accurate BH in areas with high shading and vegetation coverage, as well as in areas with dense buildings. Thus, the proposed method has been validated for its effectiveness and reliability. Full article

This study aimed to evaluate the effects of fruit position, light exposure and fruit surface temperature (FST) on apple fruit colour development and fruit quality at harvest, including sunburn damage severity. This was achieved by undertaking two experiments in a high-density planting of the dark-red apple ANABP 01 in Tatura, Australia. In the 2020–2021 growing season an experiment was conducted to draw relationships between fruit position and fruit quality parameters. Here, sample fruit position and level of light exposure were respectively determined using a static LiDAR system and a portable quantum photosynthetically active radiation (PAR) sensor. At harvest the sample fruit were analysed for percentage red colour coverage, objective colour parameters (L*, a*, b*, hue angle and chroma), sunburn damage, fruit diameter (FD), soluble solids concentration (SSC), flesh firmness (FF) and starch pattern index (SPI). A second experiment was conducted in the 2021–2022 growing season and focused on how fruit shading, light exposure and the removal of ultraviolet (UV) radiation affected the FST, colour development and harvest fruit quality. Five treatments were distributed among sample fruit: fully shaded with aluminium umbrellas, shaded for one month and then exposed to sunlight until harvest, exposed for one month and then shaded until harvest, covered with a longpass UV filter and a control treatment. The development of colour in this dark-red apple cultivar was highly responsive to aspects of fruit position, and the intensity and quality of light exposure. The best-coloured fruit were exposed to higher quantities of PAR, exposed to both PAR and UV radiation simultaneously and located higher in the tree canopy. Fruit that were fully exposed to PAR and achieved better colour development also displayed higher FST and sunburn damage severity. Full article

Straw covering is a protective tillage measure in agricultural production, but there is relatively little research on the allelopathic effects of corn straw on weeds and foxtail millet. This experiment studied the allelopathic effects of corn straw on four weeds (Chenopodium album, Setaria viridis, Echinochloa crus-galli and Amaranthus retroflexus) in foxtail millet fields, and also measured the growth indicators of foxtail millet. The study consisted of Petri dish and field experiments. Five treatments were used in the Petri dish experiment: clear water as control (0 g/L, TCK) and four types of corn straw water extracts. They were, respectively, the stock solution (100 g/L, T1), 10 X dilution (10 g/L, T2), 50 X dilution (2 g/L, T3), and 100 X dilution (1 g/L, T4) of corn straw water extracts. Additionally, seven treatments were set up in the field experiment, consisting of three corn straw covering treatments, with covering amounts of 3000 (Z1), 6000 (Z2) and 12,000 kg/ha (Z3), and four control treatments—one treatment with no corn straw cover (CK) and three treatments involving the use of a black film to create the same shading area as the corn straw covered area, with black film coverage areas of 50% (PZ1), 70% (PZ2), and 100% (PZ3), respectively. The results showed that the corn straw water extract reduced the germination rate of the seeds of the four weeds. The T1 treatment resulted in the allelopathic promotion of C. album growth but the inhibition of S. viridis, E. crus-galli, and A. retroflexus growth. Treatments T2, T3, and T4 all induced the allelopathic promotion of the growth of the four weeds. The order of the effects of the corn straw water extracts on the comprehensive allelopathy index of the four weed seeds was as follows: C. album > S. viridis > A. retroflexus > E. crus-galli. With an increase in the corn straw mulching amount, the density and total coverage of the four weeds showed a gradual downward trend, whereas the plant control effect and fresh weight control effect showed a gradual upward trend. All indices showed the best results under 12,000 kg/ha of mulching and returning to the field. Overall, corn straw coverage significantly impacted the net photosynthetic rate and transpiration rate of foxtail millet and increased the yield of foxtail millet. Under coverages of 6000 and 12,000 kg/ha, the growth of foxtail millet is better. Based on our findings, we recommend a corn straw coverage of 12,000 kg/ha for the allelopathic control of weeds in foxtail millet fields. Full article

Land desertification is a key environmental problem in China, especially in Northwest China, where it seriously affects the sustainable development of natural resources. In this paper, we combine high-resolution satellite remote sensing images and UAV (unmanned aerial vehicle) visible light images to extract desert vegetation data and quickly locate and accurately monitor land desertification in relevant areas according to changes in vegetation coverage. Due to the strong light and dry climate of deserts in Northwest China, which results in deeper vegetation shadow texture and mostly dry shrubs with fewer stems and leaves, the accuracy of the vegetation index commonly used in visible remote sensing image classification is not able to meet the requirements for monitoring and evaluating land desertification. For this reason, in this paper, we took the Hangjin Banner in Bayannur as an example and constructed a new vegetation index, the HSVGVI (hue–saturation–value green enhancement vegetation index), based on the HSV (hue–saturation–value) color space using channel enhancement that can improve the extraction accuracy of desert vegetation and reduce misclassification. In addition, in order to further test the extraction accuracy, samples of densely vegetated and multi-shaded areas were divided in the study area according to the accuracy-influencing factors. At the same time, the HSVGVI was compared with the vegetation indices EXG (excess green index), RGBVI (red–green–blue vegetation index), MGRVI (modified green–red vegetation index), NGBDI (normalized green–red discrepancy index), and VDVI (visible-band discrepancy vegetation index) constructed based on the RGB (red–green–blue) color space. The experimental results show that the extraction accuracy of the EXG and other vegetation indices constructed in RGB color space can only reach 70%, while the extraction accuracy of the HSVGVI can reach more than 95%. In summary, the HSVGVI proposed in this paper can better realize the extraction of desert vegetation data and can provide a reliable technical tool for monitoring and evaluating land desertification. Full article

The operational slowness in the execution of direct methods for estimating forage mass, an important variable for defining the animal stocking rate, gave rise to the need for methods with faster responses and greater territorial coverage. In this context, the aim of this study was to evaluate a method to estimate the mass of Urochloa brizantha cv. BRS Piatã in shaded and full sun systems, through proximal sensing applied to the Simple Algorithm for Evapotranspiration Retrieving (SAFER) model, applied with the Monteith Radiation Use Efficiency (RUE) model. The study was carried out in the experimental area of Fazenda Canchim, a research center of Embrapa Pecuária Sudeste, São Carlos, SP, Brazil (21°57′S, 47°50′W, 860 m), with collections of forage mass and reflectance in the silvopastoral systems animal production and full sun. Reflectance data, as well as meteorological data obtained by a weather station installed in the study area, were used as input for the SAFER model and, later, for the radiation use efficiency model to calculate the fresh mass of forage. The forage collected in the field was sent to the laboratory, separated, weighed and dried, generating the variables of pasture total dry mass), total leaf dry mass, leaf and stalk dry mass and leaf area index. With the variables of pasture, in situ, and fresh mass, obtained from SAFER, the training regression model, in which 80% were used for training and 20% for testing the models. The SAFER was able to promisingly express the behavior of forage variables, with a significant correlation with all of them. The variables that obtained the best estimation performance model were the dry mass of leaves and stems and the dry mass of leaves in silvopastoral and full sun systems, respectively. It was concluded that the association of the SAFER model with the proximal sensor allowed us to obtain a fast, precise and accurate forage estimation method. Full article

Urban street shadows can provide essential information for many applications, such as the assessment and protection of ecology and environment, livability evaluation, etc. In this research, we propose an effective and rapid method to quantify the diurnal and spatial changes of urban street shadows, by taking Beijing city as an example. In the method, we explore a novel way of transferring street characteristics to semantically segment street-level panoramic images of Beijing by using DeepLabv3+. Based on the segmentation results, the shading situation is further estimated by projecting the path of the sun in a day onto the semantically segmented fisheye photos and applying our firstly defined shading coverage index formula. Experimental results show that in several randomly selected sampling regions in Beijing, our method can successfully detect more than 83% of the shading changes compared to the ground truth. The results of this method contribute to the study of urban livability and the evaluation of human life comfort. The quantitative evaluation method of the shading coverage index proposed in this research has certain promotion significance and can be applied to shading-related research in other cities. Full article

Under the influence of the urban heat island effect, the thermal environments of urban built-up areas are poor, leading to the loss of urban vitality and the extreme deterioration of thermal comfort. In this paper, the outdoor thermal environment in Wuhan’s main urban area is studied via the use of field measurements. From June to August in the years 2015 to 2017, 20 measurement points were selected for monitoring from 08:00 to 19:00 h, which were located in spaces such as residential areas, parklands, commercial streets, and college/university campuses. The measurements for the same types of land and different types of land use are analyzed. A comprehensive thermal environment index is used to quantitatively evaluate the overall situations of thermal environments. The results showed that the cooling effect of vegetation shading was stronger than the effect of water evaporation and the maximum temperature difference between the two cooling methods reached 6.1 °C. The cooling effect of the canopy shading of tall trees was stronger than the effect of grassland transpiration and the maximum temperature difference was 2.8 °C. The streets with higher aspect ratios might improve the ventilation, but the wind speeds remained low, which did not provide a strong cooling effect. This study helps urban planners understand the thermal environment of Wuhan or similar cities with hot summer and diversified urban areas, and puts forward suggestions to reduce the heat island effect from the aspect of building layout, green coverage, shading mode, and street aspect ratio, so as to establish sustainable cities that are climate adaptable and environmentally friendly. Full article

(1) Background: school travel is an important part of a child’s daily activities. A comfortable walking environment can encourage children to walk to school. The existing methods of evaluating walking environments are not specific to children’s walks to school. (2) Methods: this study proposes a method of evaluating walking comfort in children traveling to school at street scale. Related indexes were selected that reflect children’s school travel behavior and their needs in street environments based on walking environment audit tools. Factor analysis was then used to calculate the relative weight of each index. (3) Results: the new evaluation method was tested in the neighborhoods around the First Central Primary School in Hedong District, Tianjin, China. The walking comfort for children’s school travel was evaluated in eight indexes: effective street width; street flatness; street cleanliness; interface diversity; buffer; shade coverage; green looking ratio; and sound decibels. Different classes and types of streets were found to have various vulnerabilities. (4) Conclusions: this evaluation method can accurately locate the weak spots in streets to improve the local policymakers’ perception of street environments, which can greatly facilitate the implementation of precise measures to promote children walking to school. Full article