Wetland vegetation is an important component of wetland ecosystems and plays a crucial role in the ecological functions of wetland environments. Accurate distribution mapping and dynamic change monitoring of vegetation are essential for wetland conservation and restoration. The development of unoccupied aerial vehicles (UAVs) provides an efficient and economic platform for wetland vegetation classification. In this study, we evaluated the feasibility of RGB imagery obtained from the DJI Mavic Pro for wetland vegetation classification at the species level, with a specific application to Honghu, which is listed as a wetland of international importance. A total of ten object-based image analysis (OBIA) scenarios were designed to assess the contribution of five machine learning algorithms to the classification accuracy, including Bayes, K-nearest neighbor (KNN), support vector machine (SVM), decision tree (DT), and random forest (RF), multi-feature combinations and feature selection implemented by the recursive feature elimination algorithm (RFE). The overall accuracy and kappa coefficient were compared to determine the optimal classification method. The main results are as follows: (1) RF showed the best performance among the five machine learning algorithms, with an overall accuracy of 89.76% and kappa coefficient of 0.88 when using 53 features (including spectral features (RGB bands), height information, vegetation indices, texture features, and geometric features) for wetland vegetation classification. (2) The RF model constructed by only spectral features showed poor classification results, with an overall accuracy of 73.66% and kappa coefficient of 0.70. By adding height information, VIs, texture features, and geometric features to construct the RF model layer by layer, the overall accuracy was improved by 8.78%, 3.41%, 2.93%, and 0.98%, respectively, demonstrating the importance of multi-feature combinations. (3) The contribution of different types of features to the RF model was not equal, and the height information was the most important for wetland vegetation classification, followed by the vegetation indices. (4) The RFE algorithm effectively reduced the number of original features from 53 to 36, generating an optimal feature subset for wetland vegetation classification. The RF based on the feature selection result of RFE (RF-RFE) had the best performance in ten scenarios, and provided an overall accuracy of 90.73%, which was 0.97% higher than the RF without feature selection. The results illustrate that the combination of UAV-based RGB imagery and the OBIA approach provides a straightforward, yet powerful, approach for high-precision wetland vegetation classification at the species level, in spite of limited spectral information. Compared with satellite data or UAVs equipped with other types of sensors, UAVs with RGB cameras are more cost efficient and convenient for wetland vegetation monitoring and mapping.

Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 °C and 2.6 °C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.

In China, the Lower Jingjiang Reach (LJR) of the Yangtze River could be one of the most complicated areas in terms of channel migration. The river had undergone many channel changes in the reach since the 18th century. Intensive human activities in recent decades, such as the construction of upstream dams and revetments, had directly affected the channel migration characteristics. The revetment would significantly diminish migration, whereas the reduced sediment caused by dams would increase bank erosion and bank failure risks. Satellite imageries of Landsat Multi Spectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) were employed to quantify the planform migration of the reach from 1983 to 2013 and to investigate the possible effect of human activities on the LJR channel evolution. Apart from the commonly used planform morphometric parameters, the migration direction was introduced to predict the future migration trends. Results showed that the LJR was gradually changing to a straighter channel, with sinuosity reducing from 2.09 to 1.9 and river length decreasing from 125.32 km to 113.31 km in the past 30 years. Planform morphometric parameters, such as migration rate of the channel centerline and erosion and deposition areas and rates, also decreased drastically in the past 30 years. The migration rate of the channel centerline decreased from 31.05 m·year⁻¹ in 1983–1988 to 11.62 m·year⁻¹ in 2009–2013. The lateral erosion and deposition areas decreased from 21.32 and 25.73 km² in 1983–1988 to 4.83 and 5.83 km² in 2009–2013. All of these findings indicate that the LJR tended to be in a steady state from 1983 to 2013 and was totally controlled by the bank revetments. However, the undercutting was strengthened because of the restrictive effect of revetments on lateral migration in the LJR. Moreover, the channel migrated to the left bank with a visible tendency as the total migration area to the left bank was approximately two times that of the right bank during the period. Consequently, the left bank of the LJR should be the focus of more attention in future migrations, and bank revetments of the left bank should be kept reinforced and adjusted with the change of water and sediment conditions.

The two most common land cover types in urban areas, artificial surface (AS) and urban blue-green space (UBGS), interact with land surface temperature (LST) and exhibit competitive effects, namely, heating and cooling effects. Understanding the variation of these effects along the AS ratio gradient is highly important for the healthy development of cities. In this study, we aimed to find the critical point of the joint competitive effects of UBGS and AS on LST, and to explore the variability in different climate zones and cities at different development levels. An urban land cover map and LST distribution map were produced using Sentinel-2 images and Landsat-8 LST data, respectively, covering 28 major cities in China. On this basis, the characteristics of water, vegetation, and LST in these cities were analyzed. Moreover, the UBGS (water or vegetation)–AS–LST relationship of each city was quantitatively explored. The results showed that UBGS and AS have a competitive relationship and jointly affect LST; this competition has a critical point (threshold). When the proportion of UBGS exceeds this value, UBGS replaces AS as the dominant variable for LST, bringing about a cooling effect. In contrast, when AS dominates LST, it causes a warming effect. The critical points between AS and water and between AS and vegetation in 28 major cities in China were 80% and 70%, respectively. The critical point showed an obvious zonal difference. Compared with cities in subtropical and temperate climate regions, the critical point of arid cities is higher, and UBGS exhibited better performance at alleviating the urban thermal environment. The critical point of cities with higher development levels is lower than that of cities with lower development levels. Even areas with relatively low AS coverage are prone to high temperatures, and more attention should be paid to improving the coverage of UBGS. Our research results provide a reference for the more reasonable handling of the relationship between urban construction, landscape layout, and temperature control.

The hydrological pattern changes have a great influence on the wetland environment. However, some important wetland areas often lack historical observations due to economic and physical conditions. The Tian-e-Zhou oxbow lake wetland is an important habitat for two endangered species and also has very little historical hydrological data. Remote sensing images can be used to explore the historical water area fluctuation of lakes. In addition, remote sensing can also be used to obtain historical water levels based on the water boundary elevation integrated with a topographic data (WBET) method or the level-surface area relationship curve (LRC) method. In order to minimize the uncertainty of the derived results, both methods were introduced in the extraction of the water level of Tian-e-Zhou during 1992–2015. The results reveal that the hydrological regime of the oxbow lake has experienced a significant change after the Shatanzi Levee construction in 1998. With the impact of the levee, the mean annual water surface area of the lake was reduced by 5.8 km2 during the flood season, but, during the non-flood season, it was increased by 1.35 km2. For the same period, the water level of the lake during the flood season also showed a 1.47 m (WBET method) or 3.21 m (LRC method) decrease. The mean annual water level increased by 1.12 m (WBET method) or 0.75 m (LRC method). Both results had a good accuracy with RMSE (root-mean-square errors) of less than 0.4 m. Furthermore, the water level differences between the Yangtze River channel and the oxbow lake increased by at least 0.5 m. It is found that the hydrological pattern of the oxbow lake changed significantly after the levee construction, which could bring some disadvantages to the habitats of the two endangered species.

Riverine sediment transport plays an important role in the global geochemical cycle. With a growing interest in global riverine environmental changes, a better understanding of water-sediment relationship dynamics and their driving forces is crucial for basin management, which is particularly associated with cascade dam construction. In this contribution, a simple and effective sediment load reduction factor analysis is used to attribute the changes in river sediment load to different drivers. The Mann–Kendall (MK) trend test and the double-mass curve (DMC) method were combined to reveal the trends and causes of change in the water-sediment relationship from 1965 to 2015 in the middle reaches of the Hanjiang River. We found that sediment load trend decreased significantly, which was caused by a decrease in water yield (5.05%), and the relative contributions of precipitation decrease (1.66%). Furthermore, only one mutation could be identified in 1974 at Huangzhuang station. Evapotranspiration and vegetation coverage had slight decreasing effects on sediment load. The impact of human activities on the water-sediment relationship has intensified over the past 15 years. We therefore propose the establishment of an integrated basin-wide ecosystem and optimized reservoir operation rule for sustainable water use and sediment regulation.