A Digital Framework to Predict the Sunshine Requirements of Landscape Plants
Knowledge of the sunshine requirements of landscape plants is important information for the adaptive selection and configuration of plants for urban greening, and is also a basic attribute of plant databases. In the existing studies, the light compensation point (LCP) and light saturation point (LSP...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/5/2098 |
| _version_ | 1797417598878482432 |
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| author | Heyi Wei Wenhua Jiang Xuejun Liu Bo Huang |
| author_facet | Heyi Wei Wenhua Jiang Xuejun Liu Bo Huang |
| author_sort | Heyi Wei |
| collection | DOAJ |
| description | Knowledge of the sunshine requirements of landscape plants is important information for the adaptive selection and configuration of plants for urban greening, and is also a basic attribute of plant databases. In the existing studies, the light compensation point (LCP) and light saturation point (LSP) have been commonly used to indicate the shade tolerance for a specific plant; however, these values are difficult to adopt in practice because the landscape architect does not always know what range of solar radiation is the best for maintaining plant health, i.e., normal growth and reproduction. In this paper, to bridge the gap, we present a novel digital framework to predict the sunshine requirements of landscape plants. First, the research introduces the proposed framework, which is composed of a black-box model, solar radiation simulation, and a health standard system for plants. Then, the data fitting between solar radiation and plant growth response is used to obtain the value of solar radiation at different health levels. Finally, we adopt the LI-6400XT Portable Photosynthetic System (Li-Cor Inc., Lincoln, NE, USA) to verify the stability and accuracy of the digital framework through 15 landscape plant species of a residential area in the city of Wuhan, China, and also compared and analyzed the results of other researchers on the same plant species. The results show that the digital framework can robustly obtain the values of the healthy, sub-healthy, and unhealthy levels for the 15 landscape plant species. The purpose of this study is to provide an efficient forecasting tool for large-scale surveys of plant sunshine requirements. The proposed framework will be beneficial for the adaptive selection and configuration of urban plants and will facilitate the construction of landscape plant databases in future studies. |
| first_indexed | 2024-03-09T06:21:10Z |
| format | Article |
| id | doaj.art-ba93e62cb463472a9f31635945700973 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T06:21:10Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-ba93e62cb463472a9f316359457009732023-12-03T11:47:58ZengMDPI AGApplied Sciences2076-34172021-02-01115209810.3390/app11052098A Digital Framework to Predict the Sunshine Requirements of Landscape PlantsHeyi Wei0Wenhua Jiang1Xuejun Liu2Bo Huang3Geodesign Research Centre, Jiangxi Normal University, Nanchang 330022, ChinaGeodesign Research Centre, Jiangxi Normal University, Nanchang 330022, ChinaSchool of Urban Design, Wuhan University, Wuhan 430072, ChinaDepartment of Geography and Resource Management, Chinese University of Hong Kong, Hong Kong, ChinaKnowledge of the sunshine requirements of landscape plants is important information for the adaptive selection and configuration of plants for urban greening, and is also a basic attribute of plant databases. In the existing studies, the light compensation point (LCP) and light saturation point (LSP) have been commonly used to indicate the shade tolerance for a specific plant; however, these values are difficult to adopt in practice because the landscape architect does not always know what range of solar radiation is the best for maintaining plant health, i.e., normal growth and reproduction. In this paper, to bridge the gap, we present a novel digital framework to predict the sunshine requirements of landscape plants. First, the research introduces the proposed framework, which is composed of a black-box model, solar radiation simulation, and a health standard system for plants. Then, the data fitting between solar radiation and plant growth response is used to obtain the value of solar radiation at different health levels. Finally, we adopt the LI-6400XT Portable Photosynthetic System (Li-Cor Inc., Lincoln, NE, USA) to verify the stability and accuracy of the digital framework through 15 landscape plant species of a residential area in the city of Wuhan, China, and also compared and analyzed the results of other researchers on the same plant species. The results show that the digital framework can robustly obtain the values of the healthy, sub-healthy, and unhealthy levels for the 15 landscape plant species. The purpose of this study is to provide an efficient forecasting tool for large-scale surveys of plant sunshine requirements. The proposed framework will be beneficial for the adaptive selection and configuration of urban plants and will facilitate the construction of landscape plant databases in future studies.https://www.mdpi.com/2076-3417/11/5/2098digital frameworkSolar Analystshade tolerancesolar radiation responselandscape plantsgeographic information systems (GIS) |
| spellingShingle | Heyi Wei Wenhua Jiang Xuejun Liu Bo Huang A Digital Framework to Predict the Sunshine Requirements of Landscape Plants Applied Sciences digital framework Solar Analyst shade tolerance solar radiation response landscape plants geographic information systems (GIS) |
| title | A Digital Framework to Predict the Sunshine Requirements of Landscape Plants |
| title_full | A Digital Framework to Predict the Sunshine Requirements of Landscape Plants |
| title_fullStr | A Digital Framework to Predict the Sunshine Requirements of Landscape Plants |
| title_full_unstemmed | A Digital Framework to Predict the Sunshine Requirements of Landscape Plants |
| title_short | A Digital Framework to Predict the Sunshine Requirements of Landscape Plants |
| title_sort | digital framework to predict the sunshine requirements of landscape plants |
| topic | digital framework Solar Analyst shade tolerance solar radiation response landscape plants geographic information systems (GIS) |
| url | https://www.mdpi.com/2076-3417/11/5/2098 |
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