Comparison of Classification Algorithms for Detecting Typical Coastal Reclamation in Guangdong Province with Landsat 8 and Sentinel 2 Images

Coastal reclamation in Guangdong Province is highly concentrated and is growing rapidly. However, intensive reclamation use has resulted in serious influence on the coastal ecosystem, directly and indirectly. The current conditions and spatial distribution of reclamations must be detected for coastal preservation and management using efficient technology. This study aims to find a suitable method and data to map reclamations accurately at a large scale. Pixel-based and object-oriented classification methods were applied in extracting the three typical types of coastal reclamation, namely, ports, aquaculture ponds, and salt pans, in Guangdong Province from Landsat 8 and Sentinel 2 images. The algorithms of a support vector machine, random forest, decision tree, and rule-based algorithm were performed. Classification results were compared with statistical measures to assess the performance of different algorithms. The results indicated that all of the algorithms could obtain classification results with high accuracy, whereas the object-oriented algorithm showed less efficiency than other algorithms in classifying ports with complicated features. High-resolution data were not always superior to lower-resolution data in the reclamation classification. Generally speaking, applying the rule-based object-oriented algorithm in Sentinel 2A MSI images is relatively efficient at detecting the reclamation use in coastal Guangdong considering its actual situation. The mapping of reclamations in the whole of coastal Guangdong shows that they present obvious agglomeration characteristics in the space. The aquaculture ponds are mainly distributed in the coastal zones of western Guangdong and eastern Guangdong, with the largest area of 77,963 ha. The other types of ports are mainly distributed in the coastal zones of the Pearl River Delta, with an area of 8146 ha, while salt pans are mainly distributed in the coastal zones of Jiangmen, Zhuhai, and Zhongshan, with a total area of 4072 ha. The results can provide key supporting data for decision making in coastal management and preservation.

Two new species of the spider genus Sinamma Lin & Li, 2014 (Araneae, Tetrablemmidae) from Guangdong Province, China

Two new species of the genus Sinamma Lin & Li, 2014, Sinamma quadrata Tong & Li, sp. nov. (male, female) and Sinamma yingae Tong & Li, sp. nov. (male, female) are described from Guangdong, China. The geographic distribution of the genus is updated and a key to all known species is provided.

Temporal and Spatial Evolution of Climate Comfort and Population Exposure in Guangdong Province in the Last Half Century

Regional Climatic Comfort Index (CCI) deteriorated significantly due to the climate change and anthropogenic interference. Knowledge regarding the long-term temporal dynamics of CCI in typical regions should be strengthened. In this study, we analyze the temporal and spatial evolution of CCI from 1969 to 2018 in Guangdong Province, based on meteorological indicators, including heat, humidity, wind and cloth loading etc.. Additionally, the population exposure to climate unconformity was examined since 1990 with the help of population data. Our study found that: (1) the warming and humidifying of the summer climate served as the main driving force for the continuous deterioration of CCI, with the comfortable days decreased by 1.06d/10a and the extremely muggy days increased by 2.83d/10a; (2) spatially, the lowest climate comfortability concentrated in southwestern Guangdong with more than 50 uncomfortable days each year, while the climate comfortability in northeastern Guangdong tends to deteriorated whit higher rate, which can reach as high as 6d/10a; (3) in summer, the population exposure to uncomfortable climate highly centralized in the Pearl River Delta, Shantou, Jieyang, and the surrounding areas, and both area and population exposure showed increasing trends. Particularly, Shenzhen held the highest growth rate of population exposure with an increase rate of 2.94 million/10a; (4) although the discomfort distribution and deterioration rate vary across the province, the spatial heterogeneity of comfortability is diminishing in Guangdong Province. This study will provide scientific reference for regional urban planning, thermal environment improvement, local resident health risk analysis, and key strategy implementation, etc.

Evaluation of economic recovery capability under the background of COVID-19: application of a big data information processing model

In order to promote local economic recovery under the COVID-19 pandemic, this paper first constructs a big data information processing model, then measure the growth of GDP and fiscal revenue driven by consumption, investment and export in Guangdong province. The measurement results show that under the stimulus of consumption, investment and export of the same intensity, Guangzhou, Shenzhen and Foshan perform better in the GDP index, while Shenzhen, Shaoguan and Qingyuan perform better in the fiscal revenue index. To this end, local governments should give priority to Guangzhou, Shenzhen, Foshan, Shaoguan and Qingyuan to take effective economic stimulus measures to achieve faster growth in GDP and fiscal revenue. The research results are of practical significance for guiding local governments to implement precise policies to promote the process of economic recovery.

Long-term Variation of Absorption and Total Aerosol Optical Properties over Typical Provinces of China from Satellite Observations

Increase of atmospheric aerosols has a profound impact on the Earth’s climate. It’s also one of the crucial factors that cuasesd more fequent air pollution events in China. Monthly average Aerosol Optical Depth (AOD) from MODIS and UltraViolet Absorbing aerosol Index (UVAI) from OMI during 2011 to 2019 are used to analyse the trend of absorption and total aerosol optical properties over three typical provinces of China, namely Shandong, Gansu and Guangdong provinces. The results show the average annual AOD of the three provinces are all decreasing while UVAI rises during this period. In addition, the monthly variation of AOD and UVAI are also obviously different over these provinces. In particular, the peak value of AOD appeared in July and the trough appeared in December over Shandong Province. And the peak appeared in April over Gansu Province, but AOD decrease slower then over Shandong Province. And there were two peaks in April and August over Guangdong Province. For UVAI, the peaks over Shandong and Gansu provinces both occur in January, while that over Guangdong Province appears in March. Above mentioned differences in the long-term trend and monthly variation of AOD and UVAI might be closely related to the meteorological conditions and aerosol emission of these three provinces.

A New Leaf Blight Disease Caused by Alternaria jacinthicola on Banana in China

A leaf blight disease with an incidence level of about 50% was found on Robusta banana in Guangdong province of China in September 2020. The early symptom appeared as pale gray to black brown, irregular, small, necrotic lesions mainly on the top 3–5 leaves. Severely infected leaves were withered and necrotic. Two representative fungus strains, strain L1 and strain L2, were isolated from affected banana leaves, and morphological and molecular identification analysis confirmed that the two fungi were both Alternaria jacinthicola. Many Alternaria species have been reported to cause wilting, decay, leaf blight and leaf spots on plants and lead to serious economic losses in their production, including A. alternata, causing leaf blight and leaf sport diseases on banana. The Koch’s postulates of A. jacinthicola causing the leaf blight disease was further fulfilled, which confirmed that it is the causal agent of this disease. To our knowledge, this is the first report of A. jacinthicola causing leaf blight on banana in China.

A Study on the Efficiency and Countermeasures of Network-Based Autonomous Learning Platform for Vocational College English Learners

This paper investigates the efficiency of 289 vocational college English learners using the network-based autonomous learning platform in Guangdong province in China. The results show that learners have a positive attitude toward the network-based extracurricular English autonomous learning, and learners with different English foundation have different requirements for extracurricular online autonomous learning. This paper puts forward some countermeasures on how to make full use of the network-based extracurricular English autonomous learning.