Journal of Resources and Ecology >
Study on Mountain City Landscape Gradient Characteristics and Urban Construction Coupling: Taking the Yangtze River to the Eastern Ridge Line of Nan Mountain in Chongqing as an Example
Received date: 2020-10-15
Accepted date: 2021-03-03
Online published: 2021-07-30
Supported by
The National Natural Science Foundation of China(51978093)
China has a vast area of mountains that are of great research interest. Chongqing is a typical mountain city in China. In urban construction, a mountain is not only an important limiting condition for urban development, but also an important condition for shaping the urban form. The area from the Yangtze River to the eastern ridge line of Nan Mountain in Nanan District is strongly representative of mountain cities with a complex landform, fragile ecological environment and a long history and culture. In recent years, the construction and optimization of this area are increasingly closely related to the landscape environment. However, due to the special environments of mountain cities, altitude and landform conditions become the key influencing conditions for further development of the cities. Therefore, this paper takes this region as an example, focuses on remote sensing and field measurement data, combines government data with that from scholarly research, and conducts relevant exploration through GIS, ENVI and some chart processing software. At first, from the perspective of the landscape gradient and urban construction, the characteristics of the urban landscape gradient are sorted out, and the developmental status of each urban area is analyzed. Then, the coupling relationships between the landscape features of each gradient and each urban area are analyzed. Finally, based on the analysis results, three major optimization measures are proposed to maintain ecological harmony in the mountainous area, reconstruct the mountain characteristic culture, and create unique mountain aesthetics, all with the hope of providing some guidance for the future development of the study area and similar mountain cities.
Key words: mountainous cities; gradient; landscape; coupling
ZHANG Yuchen , LIU Jun . Study on Mountain City Landscape Gradient Characteristics and Urban Construction Coupling: Taking the Yangtze River to the Eastern Ridge Line of Nan Mountain in Chongqing as an Example[J]. Journal of Resources and Ecology, 2021 , 12(3) : 397 -408 . DOI: 10.5814/j.issn.1674-764x.2021.03.009
Fig. 1 Scope of study area (Satellite images in January 2019) |
Fig. 2 Research framework |
Fig. 3 Geomorphologic analysis of the study area (January 2019) (a) Elevation analysis, (b) slope direction analysis, (c) slope analysis. |
Fig. 4 Land use type analysis (January 2019) |
Fig. 5 Land use changes of each gradient (January 2019) |
Table 1 Plant analysis of each gradient (January 2019) |
Gradient (m) | Natural state | Plant community distribution area | Species diversity | Common plants | Plant community type | Ornamental value |
---|---|---|---|---|---|---|
< 200 | Medium | Water front | Medium | Broussonetia papyrifera (Linnaeus) L'Heritier ex Ventenat, Ficus virens Aiton, Miscanthus sinensis Anderss., Arundo donax L., Duchesnea indica (Andr.) Focke, Humulus scandens (Lour.) Merr. | Mainly composed of grass and shrub, and more diverse wild native plants | Low |
Roads and attached green space | Low | Ginkgo biloba L., Cinnamomum camphora (L.) Presl, Ficus virens Aiton, Osmanthus fragrans (Thunb.) Loureiro, Ligustrum × vicaryi Hort., Loropetalum chinense var. rubrum Yieh, Argyranthemum frutescens (L.) Sch.-Bip | Mainly arbor, with a small amount of grass and shrub plants | Medium | ||
Parks and squares | Medium | Bauhinia purpurea L., Elaeocarpus decipiens Hemsl., Pterocarya stenoptera C. DC., Ficus virens Aiton, Cinnamomum camphora (L.) Presl, Yulania denudata (Desrousseaux) D. L. Fu, Prunus cerasifera f. atropurpurea (Jacq.) Rehd., Acer palmatum ‘Atropurpureum'(Van Houtte) Schwerim, Ligustrum × vicaryi Hort., Loropetalum chinense var. rubrum Yieh, Lantana camara L., Alpinia zerumbet (Pers.) Burtt. et Smith, Iris tectorum Maxim. | The forest belt is luxuriant, and the artificial plant community is rich in grass and shrub | High | ||
200-300 | Low | Roads and attached green space | Low | Old building area: Ficus virens Aiton, Broussonetia papyrifera (Linnaeus) L'Heritier ex Ventenat, Cinnamomum camphora (L.) Presl, Osmanthus fragrans (Thunb.) Loureiro, Mallotus barbatus (Wall.) Muell. Arg. | Simple artificial community dominated by arbors | Low |
New building area: Cinnamomum camphora (L.) Presl, Ginkgo biloba L., Koelreuteria bipinnata Franch., Platanus acerifolia (Aiton) Willdenow, Trachycarpus fortunei (Hook.) H. Wendl., Cerasus serrulata var. lannesiana (Carri.) Makino, Ligustrum ´ vicaryi Hort., Loropetalum chinense var. rubrum Yieh | Road forest belt with high seasonal, color and ornamental effects | Medium | ||||
Parks and squares | Medium | Ficus virens Aiton, Cinnamomum camphora (L.) Presl, Phoebe zhennan S. Lee et F. N. Wei, Metasequoia glyptostroboides Hu et W. C. Cheng | The forest belt is luxuriant, and the artificial plant community is rich in grass and shrub | High | ||
Dwelling district | Medium | Ficus virens Aiton, Cinnamomum camphora (L.) Presl, Celtis sinensis Pers., Pinaceae Spreng. ex F. Rudolphi, Cupressaceae Gray, Viburnum odoratissimum Ker.-Gawl. | The most abundant artificial area of arbor, shrub and grass | Medium | ||
300-400 | High | Agricultural district | Low | Fruits, vegetables, food crops | Crops related to season and market supply and demand | Low |
Factory district | Low | Ficus virens Aiton, Broussonetia papyrifera (Linnaeus) L'Heritier ex Ventenat | Dominated by arbors in the original mountain forest belt, lacking in shrub and grass layer | Low | ||
Mountain district | High | Pinus massoniana Lamb. (constructive species), Cinnamomum camphora (L.) Presl, Cornus controversa Hemsley, Broussonetia papyrifera (Linnaeus) L'Heritier ex Ventenat, Lindera glauca (Sieb. et Zucc.) Bl., Mallotus barbatus (Wall.) Muell. Arg. | Dominated by natural forest belt, mixed with a small amount of artificial forest, and has rich local plants | High | ||
400-500 | High | Mixed area | Medium | Diverse agricultural plants, simple roads and community plants | Multi type and small area interlaced artificial plant communities | Low |
Mountain district | High | Pinus massoniana Lamb.(constructive species), Cinnamomum camphora (L.) Presl, Broussonetia papyrifera (Linnaeus) L'Heritier ex Ventenat, Lindera glauca (Sieb. et Zucc.) Bl., Mallotus barbatus (Wall.) Muell. Arg. | Basically natural forest belt with less artificial interference | High | ||
>500 | High | Mountain district | High | Pinus massoniana Lamb.(constructive species), Cinnamomum camphora (L.) Presl, Broussonetia papyrifera (Linnaeus) L'Heritier ex Ventenat, Lindera glauca (Sieb. et Zucc.) Bl., Mallotus barbatus (Wall.) Muell. Arg. | Dominated by natural forest belt, with complex levels of native plants, without artificial interference | High |
Fig. 6 Voronoi diagram of natural and cultural attractions (January 2019) |
Table 2 Aesthetic evaluation standard |
Project | Quantitative score | Basis of grading |
---|---|---|
Mountainous region | 0-2 | Non-mountain landscape or common mountain, gentle slope, general shape |
2-4 | Beautiful mountain, high mountain, obvious characteristics | |
4-5 | Characteristic mountain, with distinct characteristics, or cliffs, or tall and majestic, or with caves | |
Water body | 0-2 | No water or general water, small area, no special features, general sound, shadow, color, quality |
2-4 | More beautiful dynamic water body, personality is obvious, there is a sense of light or sound | |
4-5 | Magnificent dynamic water features, prominent features, or with other factors to form a wonderful and elegant scenery | |
Flora and fauna | 0-2 | The vegetation structure is simple, the coverage rate is less than 50%, rare wild animals or none |
2-4 | The vegetation structure is complex, with a coverage rate of 50%-80%, many kinds of wild animals and some protected species | |
4-5 | The vegetation structure is very rich, covering more than 80%, famous ancient trees, a wide variety of wild animals, key protected species | |
Ambience | 0-2 | There is no good ecological environment, some pollution, single color, lack of seasonal phase |
2-4 | Better ecological environment, comfortable and pleasant, less pollution, with more obvious color contrast and four season landscape | |
4-5 | High quality ecological environment, rich color, obvious seasonal phases, quiet and comfortable, fresh air, up to the national level | |
Specificity | 0-2 | No attractions or general attractions, no specificity |
2-4 | Has a certain specificity and popularity | |
4-5 | Has landforms, weather or other wonders, high visibility and popularity | |
Artificial landscape | 0-2 | Simple and common building streets, lack of characteristic resources and quality scenic spots |
2-4 | With a certain science, art, religion and other details, with certain local characteristics and reputation | |
4-5 | With a long history, it has typical local characteristics and inheritance, and has high values of science, art and religion. It is the key object of regional protection | |
Folk custom and culture | 0-2 | Rigid and boring, high homogeneity, lack of local customs and cultural festivals |
2-4 | Has certain characteristics, but the inheritance is limited, the influence is low or only belongs to the characteristic culture affected area | |
4-5 | Has a long heritage (soft and hard culture) and is located in the core area or origin area of the culture and customs, with high popularity |
Table 3 Aesthetic evaluation results for each gradient (January 2019) |
Gradient (m) | Mountainous region | Water body | Flora and fauna | Ambience | Specificity | Artificial landscape | Folk customs and culture | Total points |
---|---|---|---|---|---|---|---|---|
<200 | 1.3 | 4.6 | 1.7 | 2.2 | 3.5 | 4.4 | 4.2 | 21.9 |
200-300 | 1.1 | 0.5 | 1.4 | 2.4 | 1.6 | 2.5 | 0.9 | 10.4 |
300-400 | 2.6 | 0.6 | 3.3 | 3.2 | 1.3 | 0.8 | 0.4 | 12.2 |
400-500 | 3.8 | 0.7 | 4.1 | 3.8 | 3.2 | 3.8 | 4.3 | 23.7 |
>500 | 4.1 | 0.7 | 4.8 | 4.2 | 3.1 | 1.4 | 0.8 | 19.1 |
Fig. 7 Urban construction in the study area (January 2019) |
Fig. 8 Landscape relationships (January 2019) |
Table 4 Air quality statistics of the research area (2016-2018) |
Year | 2016 | 2017 | 2018 | ||||||
---|---|---|---|---|---|---|---|---|---|
Month | AQI | Range | Quality grade | AQI | Range | Quality grade | AQI | Range | Quality grade |
Jan. | 96 | 43-202 | Fine | 117 | 42-220 | Light pollution | 79 | 35-190 | Fine |
Feb. | 96 | 32-205 | Fine | 87 | 45-164 | Fine | 78 | 32-156 | Fine |
Mar. | 82 | 30-148 | Fine | 69 | 43-113 | Fine | 59 | 37-93 | Fine |
Apr. | 71 | 40-122 | Fine | 65 | 35-97 | Fine | 62 | 29-108 | Fine |
May | 77 | 35-141 | Fine | 77 | 36-145 | Fine | 67 | 29-130 | Fine |
Jun. | 75 | 29-158 | Fine | 76 | 41-131 | Fine | 69 | 36-172 | Fine |
Jul. | 69 | 35-140 | Fine | 93 | 38-193 | Fine | 70 | 32-126 | Fine |
Aug. | 72 | 35-116 | Fine | 85 | 30-163 | Fine | 93 | 40-138 | Fine |
Sep. | 95 | 52-186 | Fine | 56 | 28-100 | Fine | 54 | 32-111 | Fine |
Oct. | 61 | 39-94 | Fine | 52 | 25-111 | Fine | 61 | 38-108 | Fine |
Nov. | 78 | 35-123 | Fine | 80 | 47-132 | Fine | 67 | 32-100 | Fine |
Dec. | 100 | 52-152 | Light pollution | 109 | 49-202 | Light pollution | 73 | 33-178 | Fine |
Average | 81 | 38-149 | Fine | 81 | 38-148 | Fine | 69 | 34-134 | Fine |
Table 5 Statistics of riverside buildings in the study area (January 2019) |
Building type | Low-rise buildings | Multi-storey building | High-rise buildings | Super tall building | Combination of low-rise and multi-storey buildings | Combination of low-rise and high-rise buildings | Combination of multi-storey and high-rise buildings | Combination of mountains and multi-storey buildings | Mountain and high-rise building combination | No construction |
---|---|---|---|---|---|---|---|---|---|---|
Proportion (%) | 3.3 | 15.3 | 17.0 | 15.7 | 4.0 | 4.8 | 18.0 | 13.3 | 4.0 | 4.6 |
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