It is of great significance to understand the extent and distribution of bamboo for its valuable ecological services and economic benefits. However, it is challenging to map bamboo using remote sensing images over a large area because of the similarity between bamboo and other vegetation types, the availability of clear optical images, huge workload of image processing, and sample collection. In this study, we use the Landsat 8 times series images archive to map bamboo forests in China via the Google Earth engine. Several spectral indices were calculated and used as classification features, including the normalized difference vegetation index (NDVI), the normalized difference moisture index (NDMI) and textural features of the gray-level co-occurrence matrix (GLCM). We found that the bamboo forest covered an area of 709.92 × 10⁴ hectares, with the provinces of Fujian, Jiangxi, and Zhejiang containing the largest area concentrations. The bamboo forest map was accurate and reliable with an average producer’s accuracy of 89.97%, user’s accuracy of 78.45% and kappa coefficient of 0.7789. In addition, bamboo was mainly distributed in forests with an elevation of 300–1200 m above sea level, average annual precipitation of 1200–1500 mm and average day land surface temperature of 19–25 °C. The NDMI is particularly useful in differentiating bamboo from other vegetation because of the clear difference in canopy moisture content, whilst NDVI and elevation are also helpful to improve the bamboo classification accuracy. The bamboo forest map will be helpful for bamboo forest industry planning and could be used for evaluating the ecological service of the bamboo forest.

Mangroves play a crucial role in improving the water quality of mangrove wetlands. However, current research faces challenges, such as the difficulty in quantifying the impact of mangroves on water quality and the unclear pathways of influence. This study utilized remote sensing imagery to investigate the long-term changes in mangrove forests in the Futian Mangrove National Nature Reserve and constructed a water quality index based on water quality data. Finally, structural equation modeling was employed to explore the pathways of influence and quantify the impact effects of mangroves, climate, and water quality. The study findings revealed several key points: (1) The mangrove forests in the Futian Mangrove National Nature Reserve exhibited a trend of expansion towards the ocean during this period. (2) The seasonal and annual characteristics of water quality in Shenzhen Bay indicated a significant improvement in water quality from 2000 to 2020. (3) Mangroves have significant direct and indirect impacts on water quality, which are more pronounced than the effects of climate factors. These findings not only offer insights for the environmental management and conservation of Shenzhen Bay but also provide support for future comprehensive studies on the response relationships between the morphology, species, and physiological characteristics of mangroves and water quality.

Mapping bamboo forest dynamics is essential for forest resource management and understanding vegetation succession, but it is hindered by the lack of historical samples. To address this challenge, this study developed a percentile-based head/tail break (P-HTB) method to reconstruct historical samples and produced bamboo forest maps for Jiangxi Province at five-year intervals from 1990 to 2020. Compared with the OTSU and original head/tail breaks (HTB) methods, P-HTB performed better in automatic threshold determination across most target years. Using the migrated samples and random forest algorithm, bamboo forest dynamics in Jiangxi Province from 1990 to 2020 were mapped at 5-year intervals. The results showed that the bamboo forest area more than doubled over the 30-year period, from 57.74 × 10⁴ ha to 120.78 × 10⁴ ha. Expansion was most pronounced in hilly and lower-elevation areas, driving the elevation centroid of bamboo forests downward by 89 m, yet increases were also observed at high elevations. This expansion came largely at the expense of evergreen broadleaved forests. This study provides a reliable long-term bamboo forest dataset for Jiangxi Province and a transferable methodology for large-scale vegetation monitoring, thereby offering support for sustainable forest management and improved land cover mapping.