Ecological design and smart landscapes: Boosting the connection between scientific findings and design approaches with smart technologies

Zhang, Le

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https://hdl.handle.net/2142/116239 Copy

Description

Title

Ecological design and smart landscapes: Boosting the connection between scientific findings and design approaches with smart technologies

Author(s)

Zhang, Le

Issue Date

2022-07-15

Director of Research (if dissertation) or Advisor (if thesis)

Deal, Brian

Doctoral Committee Chair(s)

Deal, Brian

Committee Member(s)

• Sullivan, William
• Wilson, Bev
• Fang, Fang

Department of Study

Landscape Architecture

Discipline

Landscape Architecture

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Ecological Design
• Ecosystem Services
• Planning Support Systems (PSSs)
• Impact Analysis
• Carbon Sequestration

Abstract

Landscape architecture is considered to be a highly comprehensive discipline that has been absorbing knowledge from many different disciplines since its establishment. Exponential growth in digitized information, a narrowing field of study, and a lack of interdisciplinary communication, however, are making it difficult for contemporary designers to keep up with the newest scientific concepts and technologies. Concepts in the life sciences such as biological control and ecosystem services, for example, have the potential to improve the performance of built environments, yet have not gained the full attention of landscape designers. Similarly, while the smart city has been a popular concept and environmental sensors have been installed in many parks and public spaces, we have yet to see how the data can help at the level of landscape design. Limitations inherent in scientific reductionism and an ability to analyze complex systems are also inhibiting designer interactions with complex bio-ecological information. To overcome these obstacles and connect ecological theories with landscape design, this dissertation aims to develop a “smart” system that integrates various data sources and scientific models. The purpose of the smart system is to ease the transition between scientific findings, design principles, and actions – in the form of landscape designs or plans. The dissertation will present the following research projects that have applied smart tools to support landscape design, and how the conceptual framework of smart landscapes has evolved over the course of these studies. • Assessing the Impacts of City Developments on Urban Green Spaces and Natural Areas Using the Landuse Evolution and Impact Assessment Model (LEAM) (Chapters 3 and 4). LEAM is a dynamic model and planning support system that forecasts future land use changes based on various socioeconomic, sociophysical, and geographic variables. Projecting potential patterns of urban change in the near future, I was able to evaluate the stresses posed by these changes on green spaces and the impacts on the provisioning of ecosystem services. A comparative study was also conducted to investigate how the same data processing approach can be applied in different cities. • Delivery of Ecosystem Services from Urban Parks and Green Spaces (Chapter 5): A Supply-and-Demand Analysis in Stockholm, SE. While urban parks can provide ecosystem services to the residents, the services can only be received when they are accessible to the residents. In this study, I combined a transportation model with multiple ecological indicators to evaluate the delivery of ecosystem services in the city of Stockholm, Sweden. The model is based on both the quality of ecosystems and their accessibility to the broader urban population. The work demonstrates the power of a combined ecological and transportation model in extracting information from fragmented data, and presents the results in easy-to-understand visual representations. • Estimating Carbon Sequestration in Illinois: A Forest Structure Approach (Chapter 6). Forests make critically important contributions to the carbon pool. In Illinois, forests make up only 14.9% of all land cover in 2016, down from approximately 42.3% in the early 20th century. Still, understanding the sequestration potential of all lands and in particular, forested lands is vital to developing a carbon-neutral plan for the state. In this study, I analyzed forested structures in Illinois using data from the Critical Trends Assessment Program (CTAP). Carbon sequestration potential from the forests was estimated and projected based on the forest stand structure. One observation result of this study is that the state has been losing younger trees over the last two decades, meaning a long-term reduction of sequestration is potential. Action is needed to ensure the survivability of the younger trees and preserve their sequestration potential. This study has highlighted the predictive power of the smart framework. • Disease Vector Control with Landscape Integrated Pest Management: the Predatory Landscape (Chapter 7). This is a conceptual project that proposes a landscape design philosophy that issues landscape-based structure to reduce the threat of pest-borne disease vectors. A predatory landscape is proposed that creates habitats that accommodate the proliferation of natural predators of mosquitos. This project includes a literature review, a model simulation, and a case study to explore which of the landscape design features may most effectively reduce mosquito-borne threats. A data collection, data processing, and feedback framework is proposed based on the analysis. With lessons and experiences learned from the above research, a more complex and sophisticated smart framework is introduced in Chapter 8. This framework is characterized by six features: sentience, incisiveness, comprehensibleness, reasonableness, predictiveness, and adaptiveness. It includes elements of data collection, information extraction, visualization and presentation, design/management decisions, and data feedback.

Graduation Semester

2022-08

Type of Resource

Thesis

Copyright and License Information

Copyright 2022 Le Zhang

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