Abstract
In landscape design, the text of landscape design plays an important role. However, in practice, designers are often faced with an industry situation where they need to complete a large ...number of design tasks in a short period. If language models are used to assist in the writing of design texts, it will be of great help not only to designers but also to the landscape design industry. A pre-trained language model trained on collected landscape design texts and used for landscape text-assisted authoring. It is better than the existing models in terms of perplexity, readability and manual evaluation. It has great potential to be used to improve the landscape design industry.
This book presents an evidence-based approach to landscape planning and design for urban blue spaces that maximises the benefits to human health and well-being while minimising the risks. Based on ...applied research and evidence from primary and secondary data sources stemming from the EU-funded BlueHealth project, the book presents nature-based solutions to promote sustainable and resilient cities. Numerous cities around the world are located alongside bodies of water in the form of coastlines, lakes, rivers and canals, but the relationship between city inhabitants and these water sources has often been ambivalent. In many cities, water has been polluted, engineered or ignored completely. But, due to an increasing awareness of the strong connections between city, people, nature and water and health, this paradigm is shifting. The international editorial team, consisting of researchers and professionals across several disciplines, leads the reader through theoretical aspects, evidence, illustrated case studies, risk assessment and a series of validated tools to aid planning and design before finishing with overarching planning and design principles for a range of blue-space types. Over 200 full-colour illustrations accompany the case-study examples from geographic locations all over the world, including Portugal, the United Kingdom, China, Canada, the US, South Korea, Singapore, Norway and Estonia. With green and blue infrastructure now at the forefront of current policies and trends to promote healthy, sustainable cities, Urban Blue Spaces is a must-have for professionals and students in landscape planning, urban design and environmental design. Open Access for the book was funded by the European Union's Horizon 2020 research and innovation programme under grant agreement No 666773
Plant diseases significantly impact landscape design, necessitating comprehensive consideration and effective management measures to ensure the health, aesthetics, and sustainability of landscapes. ...Early detection and timely control of plant diseases are crucial, but traditional monitoring methods, which rely on manual observation and sample collection, are inadequate for covering large garden areas and may delay necessary treatments. This study addresses these challenges by constructing a small Rosa chinensis disease dataset through field collection and data augmentation techniques. We propose MixResCoAtNet, an improved model based on the lightweight MixNet framework, to identify and categorize diseases from plant leaf images using convolutional neural networks (CNNs). Comparison experiments with various classical convolutional network models demonstrate that MixResCoAtNet outperforms these models, offering more competitive performance. Additionally, due to its lighter structure, MixResCoAtNet shows greater potential for deployment on mobile devices, facilitating real-time and efficient plant disease monitoring and management in landscape design.
•Constructing a Rosa chinensis disease dataset via field collection and augmentation.•Enhancing disease identification performance using the MixNet framework.•Comparing MixResCoAtNet with various models to verify its validity and superior performance.
Context
A background assumption of landscape approaches is that some landscape patterns are more sustainable than others, and thus searching for these patterns should be a unifying theme for all ...landscape-related studies. We know much about biodiversity, ecosystems, and human wellbeing in our landscapes, but much less about how their interactions influence, and are influenced by, landscape patterns. To help fill this knowledge gap, landscape sustainability science (LSS) has emerged. However, the core research questions and key approaches of this new field still need to be systematically articulated.
Objectives
The main objectives of this paper were: (1) to propose a set of core research questions for LSS, and (2) to identify key cross-disciplinary approaches that can help address these questions.
Methods
I took a qualitative and subjective approach to review and synthesize the literature relevant to landscape sustainability, based on which I developed core questions and identified key cross-disciplinary approaches.
Results
Eight core questions were proposed to focus on understanding the relationships among landscape pattern, biodiversity, ecosystem function, ecosystem services, and human wellbeing, assessing the impacts of environmental and socio-institutional changes on these relationships, and fusing knowledge and action through landscape design/planning and governance processes. Ten inter- and trans-disciplinary approaches were identified, and their key characteristics were discussed in relation to landscape sustainability.
Conclusions
LSS has emerged as an interdisciplinary and transdisciplinary research field that aims to understand and improve sustainability by focusing on landscape scales, while considering local and global scales in the same time. To advance LSS, future research not only needs to emphasize the relationships among landscape pattern, ecosystem services, and human wellbeing, but also to proactively integrate complementary approaches across natural and social sciences. Landscape sustainability is inevitably connected to the broader regional and global context; but if global sustainability is to be achieved, our landscapes must be sustained first. It is not the other way around.
