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.

Understanding the evolutionary characteristics of innovation network structure can improve urban innovation and regional construction. Urban innovative development is affected by various factors, which can be analyzed via models of innovation networks. We establish a multi-criteria evaluation system of innovation capability and use an improved gravity model to construct an innovation network for 2015–2018, employing social network methods to analyze structural characteristics and spatial patterns. Results show that: (1) The innovation of cities in the urban agglomeration in the middle reaches of the Yangtze River has gradually increased, with an accompanying increase in the complexity of innovation networks. The cities of Wuhan, Changsha, and Nanchang are located at the absolute core of this network, which exhibits a Matthew effect, and has a triangle integration mode of growth. (2) The attraction of innovative resources and the promotion of individual innovation are increasing every year within the cities. The aggregation pattern of innovation shows a multi-core state in the urban agglomeration in the middle reaches of the Yangtze River, but the innovation radiation pattern has changed from a single center to a double center. (3) Multiple spatial innovation axes are seen in the network, with a location and direction consistent with the urban agglomeration’s development axis in the Yangtze River’s middle reaches and a triangle integration growth mode. Policy implications are proposed for regional innovation and development, and our results can provide future policy guidance and direction for governmental entities and other stakeholders.

The hydrological situations of wetlands are critical to the habitat qualities of wintering migratory birds. It is of great value to evaluate the habitat vulnerabilities within more precise intervals of water levels and quantitatively assess the influences of water level changes. The findings are advantageous for managing wetland ecosystems and for migratory bird habitat protection. This study identified the ideal habitats for wintering Siberian cranes in Poyang Lake wetland within 1-meter water level intervals (from 5 to 16 m) based on the Landsat thematic mapper (TM), enhanced thematic mapper plus (ETM+), and operational land imager (OLI) remote sensing images taken on multiple dates in the past 30 years. Three indicators—sustainability, stability, and variety—were used to evaluate the vulnerabilities of crane habitats within various water level intervals; the spatial variations and distribution patterns of the habitat vulnerabilities were further explored. The explanatory powers of water level intervals (and others) and their paired interactive effects on the habitat vulnerabilities were quantified using the geographical detector method. The results showed that crane habitat vulnerabilities were significantly sensitive to the water level changes of Poyang Lake; the habitat vulnerabilities and their spatial distribution patterns both exhibited specific tendencies with water level increases. A water level of 12 m was identified as the potential upper threshold for the maintenance of sustainable crane habitats and a water level interval of 9–10 m was expected to be the optimal interval for facilitating the aggregation features of crane habitats. The water level interval was identified as the most dominant factor in habitat vulnerability. It explained 14.46%, 42.89%, and 21.78% of the sustainability, stability, and variety of crane habitats; the numbers were expected to increase to 22%, 49.25%, and 25.84%, respectively, with water level intervals interacting with other factors. This article provides a novel perspective in evaluating the habitat vulnerabilities of wintering migratory birds and quantifying the responses to water level changes in wetlands; the proposed approaches are applicable and practicable for habitat vulnerability assessments of other wintering birds in other typical wetlands.

Contributing to the United Nations 2030 Sustainable Development Goals (SDGs) within Target 11.4 “Strengthen efforts to protect and safeguard the world’s cultural and natural heritage”, it is critical to monitor the spatial and temporal stabilities of cultural heritages. The study of the interactive relationship between earthquakes and the protection of cultural heritages needs to be strengthened. On 27 September 2021, the destructive Mw 5.9 Arkalochori earthquake occurred ~25 km away from the city of Heraklion (Greece) where the Heraklion City Wall (HCW), a representative cultural heritage of Greece and Europe, was located. This offered a proper case to investigate the shortcomings aforementioned. Here, we intend to set up and answer the following three questions (Whether, Where and What, 3Ws): Whether there were impacts on the HCW caused by the Arkalochori earthquake? Where did the maximum deformation occur? What was the relationship between seismic deformation between the epicenter and the HCW over time? We performed two-dimensional (2D) InSAR measurements for both co-seismic and post-seismic deformations using the ascending and descending Sentinel-1A SAR images. The spatial-temporal characteristics of Up–Down (UD) and East–West (EW) were revealed. The 2D co-seismic deformation field showed that the near-filed deformations were dominating compared with the deformations at the HCW, the UD deformation was mainly featured with subsidence with a maximum value of ~21 cm, the EW deformation was ~9 cm westward and ~10 cm eastward. The time-series measurements showed that: (1) temporally, the HCW responded quickly to the Arkalochori earthquake, and the accumulative deformations at the seven different bastions of the HCW showed the same trend as the near-field area over time. (2) Spatially, the closer to the Mw 5.9 epicenter, the larger the deformations that occurred. (3) The EW and UD deformation trends of the HCW that were consistent with the Mw 5.9 epicenter were interrupted at the middle time spot (22 January 2022), indicating the influence of another earthquake sequence consisting of eight earthquakes with magnitudes larger than 3.5 that happened on 16–18 January 2022. Respectively, to summarize and address the aforementioned 3Ws based on the post-seismic analysis accomplished by the MSBAS method, the Arkalochori earthquake did affect the HCW; besides, the influences of the ~13 km earthquake sequence were also detected; the nearest part to the epicenter suffered the most; the deformation trends of the HCW were approximately the same with the epicenter area of the Arkalochori earthquake both in the UD and EW directions.

The landscape of the Poyang Lake wetland is significantly influenced by changes in water levels, impacting the distribution of habitats for migratory birds. While long-term effects of water level variations have been extensively studied, short-term impacts on Siberian crane habitats and their ecological vulnerability remain poorly understood. This study utilized 35 years (1987–2022) of Landsat remote sensing data and daily water level records from Poyang Lake to examine the effects of short-term water level fluctuations on the spatial distribution and ecological vulnerability of Siberian crane habitats. The geographic detector method was employed to quantify the explanatory power and interaction effects of factors, including short-term water level fluctuations, on ecological vulnerability. The findings reveal significant differences in the habitats of wintering Siberian cranes across various water level intervals and short-term fluctuation patterns. Short-term water level fluctuations can result in the largest suitable wintering habitat area for Siberian cranes, reaching 1856.41 km² in this study. These habitats are highly sensitive to short-term water level changes, with rising and falling trends potentially leading to habitat loss. Oscillating water levels in the short term create broader and more concentrated habitats. Notably, fluctuations at low water levels support the sustainability and stability of crane habitats. Furthermore, short-term water level trends and nature reserves play a critical role in maintaining habitat ecological vulnerability; well-managed and protected nature reserves exhibit significant explanatory power, both in single-factor analysis and in their interaction with other environmental factors. Specifically, these protected areas show explanatory power exceeding the 20% threshold for both water level fluctuations and ranges, highlighting the crucial role of anthropogenic management in mitigating ecological vulnerability. This study emphasizes the necessity of scientifically informed regulation of short-term water level fluctuations to protect Siberian crane habitats and provides a strong scientific basis for decision-making support.

The imbalance between supply and demand is a pressing issue in the development of the tourism industry. Understanding the coupling coordination relationship and impact mechanism of supply-demand in the tourism system can help achieve high-quality tourism development. This study focuses on the Yangtze River Economic Belt (YREB) as the research area, quantifies the tourism supply index (TSI) and tourism demand index (TDI) from 2011 to 2020 using the tourism development index model, calculates the coupling coordination degree (CCD) of TSI and TDI based on the coupling coordination model, and explores the factors influencing the CCD using the geographic detector. The findings indicate that: (1) The TSI and TDI in various provinces show fluctuation but exhibit an overall upward trend. (2) There were apparent spatial disparities of the CCD, with a distribution characteristic of high in the east and low in other regions. The CCD gradually improved, with its gravity center slowly shifting toward the southwest. All provinces entered the intermediate stage of tourism development since 2014. (3) Basic service guarantee, consumption drive, and innovation drive are identified as the dominant factors influencing the CCD. The study can provide valuable insights for tourism coordination and sustainable development.