Abstract
Urban forests are vitally important for sustainable urban development and the well-being of urban residents. However, there is, as yet, no country-level urban forest spatial dataset of sufficient quality for the scientific management of, and correlative studies on, urban forests in China. At present, China attaches great importance to the construction of urban forests, and it is necessary to map a high-resolution and high-accuracy dataset of urban forests in China. The open-access Sentinel images and the Google Earth Engine platform provide a significant opportunity for the realization of this work. This study used eight bands (B2–B8, B11) and three indices of Sentinel-2 in 2016 to map the urban forests of China using the Random Forest machine learning algorithms at the pixel scale with the support of Google Earth Engine (GEE). The 7317 sample points for training and testing were collected from field visits and very high resolution images from Google Earth. The overall accuracy, producer’s accuracy of urban forest, and user’s accuracy of urban forest assessed by independent validation samples in this study were 92.30%, 92.27%, and 92.18%, respectively. In 2016, the percentage of urban forest cover was 19.2%. Nearly half of the cities had an urban forest cover between 10% and 20%, and the average percentage of large cities whose urban populations were over 5 million was 24.8%. Cities with less than half of the average were mainly distributed in northern and western parts of China, which should be focused on in urban greening planning.
Highlights
Between 1980 and 2018, the proportion of China’s urban population increased from 19.4% to59.6% [1,2], the rapidity of which has led to many urban problems, such as reduced biodiversity within cities [3], deterioration of air quality [4], and the heat island effect [5]
Urban forests are defined as all woodlands, groups of trees, and individual trees located in urban areas, including forests, trees in parks, gardens, commercial areas, and dwelling districts, and street trees, according to the Food and Agriculture Organization (FAO) [15]
The data input into the Random Forest (RF) model included Sentinel bands (B2-B8, B11), NDVI, Normalized Difference Water Index (NDWI), and NDBI [26]
Summary
Between 1980 and 2018, the proportion of China’s urban population increased from 19.4% to59.6% [1,2], the rapidity of which has led to many urban problems, such as reduced biodiversity within cities [3], deterioration of air quality [4], and the heat island effect [5]. Urban forests are defined as all woodlands, groups of trees, and individual trees located in urban areas, including forests, trees in parks, gardens, commercial areas, and dwelling districts, and street trees, according to the Food and Agriculture Organization (FAO) [15]. It has raised concerns about protecting and increasing the urban forests around the world: The theme of the International Day of Forests in 2018 was “Forests and Sustainable Cities” [6]. In China, Forests 2019, 10, 729; doi:10.3390/f10090729 www.mdpi.com/journal/forests
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