| Title |
Space Level Planning Method Of Urban Green Belt Based On Digital Image Processing |
| ID_Doc |
62223 |
| Authors |
Zeng, HH |
| Title |
Space Level Planning Method Of Urban Green Belt Based On Digital Image Processing |
| Year |
2020 |
| Published |
Fresenius Environmental Bulletin, 29, 9 |
| DOI |
|
| Abstract |
The concept of building a new type of green environmentally friendly modern city has been accepted globally. However, due to the wide coverage of urban green belts, people have found that the effect of space level planning is not satisfactory. However, digital image processing technology can comprehensively divide the green belt space, and solve the problem of low space utilization of the original method. Traditional planning solutions performed poorly on three indicators: space utilization, environmental harmony index, and residents' satisfaction. Based on this, in this paper. we propose a method for space level planning of urban green belts based on digital image processing. Digital image processing technology is used to collect remote sensing images. At the same time, the K nearest neighbor search method is used to extract the target characteristics of remote sensing images, and the remote sensing image functional area is divided to realize the spatial functional division of urban green belts, A green amount algorithm model was constructed to obtain the green amount of plants. Combined with GIS technology, the urban green belt was planned, and finally the spatial level planning of the urban green belt was realized. This study shows that the proposed method is better than traditional methods in terms of space utilization. environmental harmony index. and residents' satisfaction, which shows that the proposed method has better planning performance. |
| Author Keywords |
Environmental protection; digital image processing technology; urban green belt; space level planning |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000629178300038 |
| WoS Category |
Environmental Sciences |
| Research Area |
Environmental Sciences & Ecology |
| PDF |
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