The lockdown of cities to against the COVID-19 epidemic directly decreases urban socioeconomic activities. Remotely sensed night-time light (NTL) provides a macro perspective to capture these variations. Here, taking 20 global megacities as examples, we adopted the NASA’s Black Marble NTL data with a daily resolution to investigate their spatio-temporal changes. We collected daily NTL products for four weeks (one month) before and after the date of lockdown in each city, which were then summarized as weekly and monthly averaged NTL images after pre-processing (cloud removing, outlier detection, etc.). Results show that NTL overall decreased after the lockdown of cities, but with regional disparities and varying spatial patterns. Asian cities experienced the most obvious reduction of NTL. Particularly, the monthly averaged NTL in Mumbai, India, decreased by nearly 20% compared to one month before. However, there were no significant decline in NTL in European cities. African cities also experienced stable changes of NTL. Spatially, city centers darkened more obviously than the urban periphery. Facing emergencies, NTL data has broad applications in monitoring socioeconomic dynamics and assessing public policies in a near real-time manner.

As an important part of coastal wetlands, tidal flat wetlands provide various significant ecological functions. Due to offshore pollution and unreasonable utilization, tidal flats have been increasingly threatened and degraded. Therefore, it is necessary to protect and restore this important wetland by monitoring its distribution. Considering the multiple sizes of research objects, remote sensing images with high resolutions have unique resolution advantages to support the extraction of tidal flat wetlands for subsequent monitoring. The purpose of this study is to propose and evaluate a tidal flat wetland delineation and classification method from high-resolution images. First, remote sensing features and geographical buffers are used to establish a decision tree for initial classification. Next, a natural shoreline prediction algorithm is designed to refine the range of the tidal flat wetland. Then, a range and standard deviation descriptor is constructed to extract the rock marine shore, a category of tidal flat wetlands. A geographical analysis method is considered to distinguish the other two categories of tidal flat wetlands. Finally, a tidal correction strategy is introduced to regulate the borderline of tidal flat wetlands to conform to the actual situation. The performance of each step was evaluated, and the results of the proposed method were compared with existing available methods. The results show that the overall accuracy of the proposed method mostly exceeded 92% (all higher than 88%). Due to the integration and the performance superiority compared to existing available methods, the proposed method is applicable in practice and has already been applied during the construction project of Hengqin Island in China.

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