A framework for fine classification of urban wetlands based on random forest and knowledge rules: taking the wetland cities of Haikou and Yinchuan as examples

Wang, Xiaoya; Jiang, Weiguo; Peng, Kaifeng; Li, Zhuo; Rao, Pinzeng

doi:10.1080/15481603.2022.2152926

Cited by 15 publications

(6 citation statements)

References 32 publications

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“…Compared to the areas with relative-low residents' satisfaction, areas with relative-high residents' satisfaction have a low population density and adequate wetland area. This kind of spatial pattern of wetlands was seen in most cities in the semi-arid region of Western China where urban areas have rapidly expanded over the past few decades [14,26,29]. The results indicated an unbalanced and inadequate supply-demand contradiction between the population capacity of wetlands and the total population of communities locally.…”

Section: Discussionmentioning

confidence: 83%

“…The Yellow River traverses this city, with a historical record of multiple course changes [28], nurturing numerous lakes and marshes. Moreover, the number and area of artificial wetlands have experienced rapid expansion due to urban expansion and population growth over the past few decades [23,29]. Currently, this city has a relatively large wetland area of approximately 578 km 2 compared to other cities in the same region.…”

Section: Case Study Areamentioning

confidence: 99%

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Low Residents’ Satisfaction with Wetland Leisure Demand in Typical Urban Areas of the Semi-Arid Region in Western China: Spatial Variations and Their Causes

Zhang,

Zeng

2024

Land

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Wetlands, as a crucial component of urban green spaces, provide important leisure services for residents. Construction of wetlands has increased with the rapid urban expansion and population growth in China over recent decades, especially in semi-arid regions with scarce water resources. However, the residents’ satisfaction with wetland leisure demand remains unclear. This study evaluated the residents’ satisfaction with wetland leisure demand by a framework of physical calculation, taking Yinchuan City, the capital city of Ningxia Hui Autonomous Region, in the semi-arid region of Western China as a case study area. Spatial variations in residents’ satisfaction and their causes were revealed by a supply–demand relationship between the population capacity of wetlands and the total population of communities under a framework of physical calculation. The results indicated that 4.22% of the study area, which covered 7.38% of the total population, was fully satisfied with wetland leisure demand. Residents’ satisfaction in the urban area as a whole is low at 0.49, with a concentric distribution pattern increasing as the distance from the central urban area increases. The high population density and scanty wetlands mainly induced a relative-low residents’ satisfaction in the central urban area, accounting for 12.02% of the area and 32.70% of the population. Meanwhile, a relative-high residents’ satisfaction in the outer ring of the central urban area accounting for 59.10% of the area and 20.63% of the population was primarily due to the adequate capacity of wetlands. Medium residents’ satisfaction was mainly attributed to the road network density, which partially transferred local wetland leisure demand to adjacent areas. Wetland constructions and internal structural optimization to improve the capacity for leisure in densely populated central urban areas could provide a feasible path to alleviate unbalanced conditions. These results could deepen the understanding of supply–demand dynamics in the wetland leisure service and provide valuable information for optimizing wetland allocation in urban construction in semi-arid regions.

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Section: Discussionmentioning

confidence: 83%

Section: Case Study Areamentioning

confidence: 99%

Low Residents’ Satisfaction with Wetland Leisure Demand in Typical Urban Areas of the Semi-Arid Region in Western China: Spatial Variations and Their Causes

Zhang,

Zeng

2024

Land

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“…Some studies have been done to classify wetlands using rules. For example, Wang et al [18] used the image's compactness ratio, elongation ratio, and related circumscribing circle rules to divide waterbodies into shallow marine water, linear water patch water, and reservoirs. Mao et al [10] used the NDVI, Normalized Difference Built-Up Index (NDBI), and NDWI rules to divide vegetated wetlands into swamplands and marshlands.…”

Section: B Classification Frameworkmentioning

confidence: 99%

“…Pixel-based and object-oriented machine learning methods are two popular approaches for wetland mapping at present. Peng et al [17] effectively mapped wetlands on a large scale by combining pixel-level random forest and decision tree methodologies, and Wang et al [18] proposed a method for automated wetland information extraction using pixel-based random forest algorithms. However, there remains room for improvement in monitoring smaller wetlands effectively.…”

mentioning

confidence: 99%

Fine Extraction of Plateau Wetlands Based on a Combination of Object-Oriented Machine Learning and Ecological Rules: A Case Study of Dianchi Basin

Cai,

Tang,

Sima

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Wetland ecosystems are essential to the preservation of biodiversity. Plateau wetland ecosystems are vital components of wetland ecosystems, characterized by diverse wetland types and fragmented land distribution. In the extraction of plateau wetlands, there are such issues as inaccuracy in classification, inadequately fine categories, and difficulty in extracting vegetated wetlands. The aim of this study was to establish a new classification framework for extracting detailed information about plateau wetlands, and the Dianchi Basin was used as the study area. Using Gaofen-2 (GF-2) imagery from 2019-2021, land cover information was extracted by applying nearest neighbor classification and random forest classification. Wetlands were then extracted from the land cover data using ecological rule classification, and a detailed wetland map of the Dianchi Basin was obtained in 2020 with a 1 m resolution. Results showed that the production accuracies of forest wetlands, shrub wetlands, meadow wetlands, rivers, ponds, reservoirs, and lakes in the Dianchi Basin were 89.4%, 87.9%, 91.4%, 90.7%, 89.9%, 92.9%, and 95.9%, respectively, and the user accuracies were 94.9%, 92.4%, 92.6%, 95.4%, 94.2%, 91.0%, and 99.4%, respectively. Compared to the CAS_Wetlands, this study categorized the five categories of plateau wetlands into seven types with greater specificity and increased the spatial resolution of wetland mapping from 30 m to 1 m. This study can provide a new reference framework for wetland extraction and support the conservation of plateau wetland ecosystems.

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“…These statistics simply classify wetlands into broad groups without providing a more in-depth classification [25]. For this situation, Wang et al [26] successfully mapped international wetland cities using RF method paired with GEE. This study conducted wetland mapping for two international wetland cities, Wuhan and Nanchang, drawing on Wang's research concepts.…”

mentioning

confidence: 99%

Wetland Mapping and Landscape Analysis for Supporting International Wetland Cities: Case Studies in Nanchang City and Wuhan City

Zhong

Jiang

Peng

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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As the second batch of international wetland cities, Wuhan and Nanchang, both provincial capital cities in China, have abundant wetland resources. An important sign of the achievement of protecting urban wetland areas is the international wetland city designation. Understanding the growth and changes of wetlands in international wetland cities is necessary for wetland protection and management. Thus, it is crucial to conduct proper wetland mapping in these international wetland cities. By studying wetland cities, sustainable planning can be provided to promote the coordinated development of wetlands and cities. In this research, Google Earth Engine and random forest machine learning were used. According to the "Data-Information-Knowledge-Wisdom" research framework, we carried out mapping of diverse wetlands in Wuhan and Nanchang with a resolution of 10 m in 2015 and 2020. Then, using the findings of wetland mapping, we examined changes in the wetland landscapes of the two cities. Finally, this study examined changes in international wetland city indicators over this time frame. The research results showed that (1) our wetland mapping results in 2015 and 2020 achieved good accuracy, with overall accuracy over 0.90 and kappa coefficient over 0.85. (2) The total wetland area in both cities increased. Nanchang grew by 91.11 km 2 , while Wuhan grew by 290.68 km 2 . Most restored wetland areas were far from urban construction areas. In the two cities, the fragmentation of wetlands decreased, the diversity of wetlands increased, and the growth rate of wetlands was high. (3) Wetland rates rose from 17.79 to 19.07% in Nanchang and from 19.74 to 23.12% in Wuhan, according to mapping results between 2015 and 2020. The wetland protection rate in Nanchang remained unchanged, but the wetland protection rate in Wuhan decreased. Wuhan needs to strengthen the protection of increased wetlands. In addition, the study found that most of the increased areas of wetlands were previously cultivated land. The international wetland mapping framework of this study can be easily implemented in other regions of the world.

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A framework for fine classification of urban wetlands based on random forest and knowledge rules: taking the wetland cities of Haikou and Yinchuan as examples

Cited by 15 publications

References 32 publications

Low Residents’ Satisfaction with Wetland Leisure Demand in Typical Urban Areas of the Semi-Arid Region in Western China: Spatial Variations and Their Causes

Low Residents’ Satisfaction with Wetland Leisure Demand in Typical Urban Areas of the Semi-Arid Region in Western China: Spatial Variations and Their Causes

Fine Extraction of Plateau Wetlands Based on a Combination of Object-Oriented Machine Learning and Ecological Rules: A Case Study of Dianchi Basin

Wetland Mapping and Landscape Analysis for Supporting International Wetland Cities: Case Studies in Nanchang City and Wuhan City

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