Dian Zhou

Coastal wetland ecosystems around the world are facing serious challenges due to rapid economic development, climate change, and sea level rise. These factors have a great influence on the tidal creek network and vegetation ecosystem. Accordingly, based on long-term time-series remote sensing images, the evolution characteristics of tidal creeks and vegetation in silting muddy flats on the Yellow Sea were analyzed, and different quantitative methods were used to describe the relationship between tidal creeks and vegetation. The results showed that the total number of tidal creeks exhibited a downward trend, while the number of small creeks increased over time. The total length of the tidal creeks decreased at a rate of 16.1 km per year during the study period. The length of three-grade tidal creeks, the patch area ratio of Suaeda salsa, and a low vegetation coverage had a great influence on the average return flow length (L_OP). L_OP was negatively correlated with the patch area ratio of S. salsa, but positively correlated with the reclamation area, both significantly. With the increase in the patch area ratio of S. salsa, the total length of the tidal creeks increased by 12.95 km, and L_OP decreased by 35.35 m.

This study aimed to investigate the feasibility of using imaging spectroscopy (IS) to predict soil organic carbon density (SOCD) either directly or indirectly through soil organic carbon (SOC). Three methods, partial least square regression (PLSR), support vector machine (SVM), and random forest (RF), were utilized to calibrate the models and map the SOCD. The results showed that direct prediction was better than indirect prediction and the best model SVM had high R ² of 0.94 and 0.93 for calibration and validation, respectively. The measured SOCD was mainly concentrated in the surface soil layer from 0 to 40 cm, and the deeper layer tended to be gentle. The continuous depth variation trend of SOCD in the topsoil (0-40 cm) was relatively close to the measured values, while in the deeper layers (below 40 cm), it was much higher than the measured values. The study also found that the best fitting function of measured SOC stocks over time varied from linear to power and then to logarithmic with increasing depth, indicating less efficient accumulation of SOC in deep soil compared to topsoil, resulting in an overall decrease in SOC accumulation rate across soil depth. The best temporal functions for the predicted values differed from the measured values at each depth, but the changing trends of the three functions were basically consistent. It suggests that IS technology has the potential to quantitatively reveal the process of coastal soil evolution and offers a new insight for the rapid monitoring of soil property changes.

Studies on urban climatic mapping and local climate zones are urgently needed due to rapid urbanisation in China, to identify and predict serious air pollution problems and occurrence of urban heat islands, for sustainable urban planning. The study of wind environment, especially measurements of wind data on the urban scale, is important to the climate mapping and investigation of air pollution and heat island events. In this paper, we introduce a measurement method for the urban-scale wind environment, which combines measurements conducted at the stationary reference station with those at portable/mobile stations. Data collected from portable/mobile stations were normalised with respect to wind data measured at the stationary reference station. Three criteria for the selection of the stationary reference station were compared according to the land-use and distance to the portable/mobile stations. The background meteorological station was selected as the stationary reference station for data normalisation and was found to be the most appropriate. The normalisation method for wind data was used to analyse the measured wind data at portable/mobile stations. Clear differences were observed between measured and normalised average wind speeds. The normalised wind was used in the urban wind environment mapping. The objective of the mapping is to assess the ventilation potential of the urban canopy layer, to help the urban climate mapping and to inform future sustainable urban planning.