Monitoring Spatiotemporal Changes of Impervious Surfaces in Beijing City Using Random Forest Algorithm and Textural Features

Satellite-Based Monitoring of Coastal Wetlands in Yancheng, Jiangsu Province, China

The dynamic process of the wetland can reflect its impact on the environment, and finding a balance point supporting harmonious coexistence between man and nature has become an issue of increasing concern. On the basis of previous studies that have focused on local coastal wetlands, the temporal and spatial changes and driving forces of wetlands in the Yancheng coastal area from 1991 to 2021 were analyzed over a larger area. According to the study findings: (1) The results of the study of the Yancheng coastal wetland with a larger scope differed significantly from findings resulting from a study of coastal wetland only. This difference was mainly reflected in the relatively stable situation of wetland ecology as a whole, while the changes in local surface features were more significant. (2) Natural wetlands were transformed into artificial wetlands and non-wetland types, and artificial wetlands were transformed into non-wetland types; additionally, reverse transformations and internal transformations of surface features also took place. For instance, the saltpan was transformed into mudflats (86.26 km2), and some mudflats into herbaceous vegetation (193.47 km2). (3) When analyzing the impact intensity of human activities on the Yancheng wetland, it was found that this factor has experienced a process of first rising and then falling. The index was 0.650, 0.653, 0.664, 0.661, and 0.641 in 1991, 2000, 2008, 2016, and 2021, respectively. (4) Lastly, an analysis of factors driving wetland change revealed that human factors were the most critical reasons for wetland landscape change. Our work can play a reference and inspiration role in the monitoring and protection of similar coastal wetlands.

Spatiotemporal Evolution and Relationship between Night Time Light and Land Surface Temperature: A Case Study of Beijing, China

Rapid urbanization has triggered significant changes in urban land surface temperature (LST), which in turn affects urban ecosystems and the health of residents. Therefore, exploring the interrelationship between urban development and LST can help optimize the urban thermal environment and promote sustainable development. Based on remote sensing data from 2004–2019 within the sixth ring road of Beijing, this study investigates the spatiotemporal coupling law of night time light (NTL) and LST using an overall coupling model and analyzes the degree of coordination between them using a coordination model. The spatial response law between them was also analyzed using standard deviation ellipses and bivariate spatial autocorrelation. The results show that, from the perspective of spatiotemporal evolution, the spatial distributions of NTL and LST within the sixth ring road of Beijing were closely related from 2004 to 2019, although the overall coupling of NTL and LST was initially decreased and then continuously increased. From the perspective of coordination types, the main types of coordination between NTL and LST deteriorated over time. The increase in LST lagged behind NTL from 2004 to 2009 (heating hysteresis type), while LST increased ahead of NTL from 2014 to 2019 (heating advance type). This suggests that urban development became less efficient, while LST increases became more significant. In terms of correlation, NTL and LST showed significant positive correlation and spatial positive correlation; the correlation coefficient first decreased significantly and then continued to increase. From 2004 to 2009, the temperature increase caused by urbanization was suppressed due to the 2008 Beijing Olympics and related ecological protection policies, resulting in a significant decrease in the correlation coefficient between NTL and LST. From 2009 to 2019, short-term measures taken by Beijing during the Olympic Games were no longer effective, and the opposition between urban development and related policies made the policies increasingly less effective, thereby increasing the correlation coefficient between NTL and LST, and the increase in LST was more significant. This will greatly affect the urban ecological environment and residents’ health and make the previous government investment to suppress the temperature increase all in vain. This study can provide theoretical and practical support for the development of thermal environment optimization schemes and LST mitigation strategies in Beijing and other cities.

Plant Disease Diagnosis in the Visible Spectrum

A simple and robust methodology for plant disease diagnosis using images in the visible spectrum of plants, even in uncontrolled environments, is presented for possible use in mobile applications. This strategy is divided into two main parts: on the one hand, the segmentation of the plant, and on the other hand, the identification of color associated with diseases. Gaussian mixture models and probabilistic saliency segmentation are used to accurately segment the plant from the background of an image, and HSV thresholds are used in order to achieve the identification and quantification of the colors associated with the diseases. Proper identification of the colors associated with diseases of interest combined with adequate segmentation of the plant and the background produces a robust diagnosis in a wide range of scenarios.

Comparative Study of Factors Contributing to Land Surface Temperature in High-Density Built Environments in Megacities Using Satellite Imagery

In this study, the root sources contributing to the urban heat island (UHI) effect between megacities, such as Hong Kong and Shenzhen, were integrated and compared using satellite remote sensing data. Classification and multilayer perceptron regression tree (CARTMLP) algorithms were used to classify land use. The radiative transfer equation method was applied to retrieve the land surface temperatures (LSTs) in the study area. Multiple linear regression analysis was applied to determine the relationship between land-use types and UHIs. The experimental results show a large area of relatively high temperature dispersed within Shenzhen, and comparatively small areas highly centralized in Hong Kong, with the retrieved LST in Hong Kong lower than that in Shenzhen. In addition, the surface temperature of large complex buildings decorated with high-albedo materials in Hong Kong was higher than in Shenzhen (e.g., Hong Kong International Airport, 25.12 °C; Shenzhen Bao’an International Airport, 23.38 °C), with artificial heat being an important contributor to these differences. These results also imply that high-albedo materials are sufficient to alleviate high temperatures. These findings are integrated to propose an organic combination strategy for reducing UHI effects in urban areas in megacities worldwide, such as Hong Kong and Shenzhen in China.