A comprehensive review on computer vision analysis of aerial data

Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 156, С. 111206 - 111206

Опубликована: Май 31, 2025

Язык: Английский

---

Assessing urban river landscape visual quality with extreme learning machines: A case study of the yellow river in ningxia hui autonomous region, china

Ecological Indicators, Год журнала: 2024, Номер 165, С. 112173 - 112173

Опубликована: Май 27, 2024

A picturesque on-water landscape can yield favorable outcomes in terms of improving urban quality and boosting the tourism sector. The vantage point from water offers a distinctive recreational experience serves as bridge connecting environment with nature. Nevertheless, existing research pertaining to management utilization strategies has predominantly centered on perspective riverbanks, relatively few studies dedicated assessing visual unique viewpoint being water. In this research, system for measuring characteristics numerically was introduced, employing deep convolutional generative adversarial network (DCGAN) semantic segmentation, assess human perception. An extreme learning machine model employed investigate non-linear relationships between quantitative metrics public ratings. This approach led development an effective testing forecasting evaluating aesthetic appeal waterfront river. Our case study Yellow River Ningxia Hui Autonomous Region, China. we obtained indicate that introduced yielded strong predictive precision allowed us establish hierarchy importance different influencing factors. Additionally, found be significantly impacted by factors such degree construction, destruction level index, visibility hard revetments, index green clarity. It's worth noting that, except clarity, other three exhibited negative correlation quality. Moreover, our suggested method provides highly efficient way evaluate how landscapes are visually perceived their overall It also holds potential serve valuable upcoming waterscapes fresh innovative perspective.

Язык: Английский

---

Using Social Media and Multi-Source Geospatial Data for Quantifying and Understanding Visitor’s Preferences in Rural Forest Scenes: A Case Study from Nanjing

Forests, Год журнала: 2023, Номер 14(10), С. 1932 - 1932

Опубликована: Сен. 22, 2023

Rapid urbanization has made urban forest scenes scarce resources, leading to a surge in the demand for high-quality rural as alternative outdoor recreation spaces. Previous studies mainly applied survey methods, focusing on visitors’ feedback different types of from perspective visual quality evaluation. Nevertheless, explanations relationships between various factors and preferences are relatively superficial. This study sought explore distribution characteristics preferred based visitor reviews social media, using Geodetector, geospatial statistics tool, quantitatively analyzed reasons terms obtained multi-source data. The findings that (1) visitors already satisfied with natural environment but expect reflect culture tea; (2) spatial factor more robust interpretation preference, although Normalized Difference Vegetation Index (NDVI) non-consumption indicators barely explain preference solely when each them is combined other indicators, they can produce non-linear enhancement effects. Consequently, this synthesizes understand preferences, thus providing insights into human-centered planning.

Язык: Английский

---

Research on Evaluating the Characteristics of the Rural Landscape of Zhanqi Village, Chengdu, China, Based on Oblique Aerial Photography by Unmanned Aerial Vehicles

Sustainability, Год журнала: 2024, Номер 16(12), С. 5151 - 5151

Опубликована: Июнь 17, 2024

To achieve the transition of rural areas from traditional to modern, visualization landscape data and feature evaluations are essential. Landscape character assessment (LCA) is a well-established tool that was developed assess understand features. In recent years, drones have become increasingly attractive for various applications services due their low costs relative ease operation. Unlike most previous studies relied solely on drone-based remote sensing or visual esthetic evaluations, this study proposes an innovative method based characteristic oblique drone photography technology, supported by specific survey results. These include metrics, such as Shannon diversity index (SHDI), evenness (SHEI), vegetation coverage, zoning, delineations ecologically sensitive areas. This applied Zhanqi Village in Chengdu, Sichuan Province, China revealed some unique characteristics village. By categorizing describing features, makes judgments decisions about them. beneficial attempt apply scientific methods assessments production management aerial surveys. provides comprehensive framework evaluating features demonstrates combination LCA technology feasible research. Additionally, emphasizes need further research explore potential application continuously evolving urban environments future.

Язык: Английский

---

Artificial intelligence-based smart agricultural systems for saffron cultivation with integration of Unmanned Aerial Vehicle imagery and deep learning approaches

Computers & Electrical Engineering, Год журнала: 2024, Номер 119, С. 109542 - 109542

Опубликована: Авг. 13, 2024

Язык: Английский

---