Remote sensing technologies have revolutionized forestry analysis by providing valuable information about forest ecosystems on a large scale. This review article explores the latest advancements in remote sensing tools that leverage optical, thermal, RADAR, and LiDAR data, along with state-of-the-art methods of data processing and analysis. We investigate how these tools, combined with artificial intelligence (AI) techniques and cloud-computing facilities, enhance the analytical outreach and offer new insights in the fields of remote sensing and forestry disciplines. The article aims to provide a comprehensive overview of these advancements, discuss their potential applications, and highlight the challenges and future directions. Through this examination, we demonstrate the immense potential of integrating remote sensing and AI to revolutionize forest management and conservation practices.

Urban morphologies in the global south are shaped by a complex interplay of historical imprints, from colonial legacies and ethnic tensions to waves of modernization and decolonization efforts. This study delves into the urban morphology of Hangzhou during the late 19th and early 20th centuries, unraveling its transformative patterns steered by a convergence of spatial politics, economic forces, and cultural dynamics. Drawing upon a unique blend of historical map restoration techniques, we unearth pivotal morphological nuances that bridge Hangzhou’s transition from its pre-modern fabric to its modern-day urban layout. We uncover key shifts such as the movement from intricate street layouts to systematic grids, the strategic integration of public spaces like West Lakeside Park, and the city’s evolving urban epicenter mirroring its broader socio-political and economic narratives. These insights not only spotlight Hangzhou’s distinct urban journey in the context of ethnic conflicts, Western influences, and decolonization drives but also underscore the value of context-sensitive urban morphological research in the global south. Our findings emphasize the criticality of synergizing varied methodologies and theoretical perspectives to deepen our comprehension of urban transitions, sculpt place identities, and invigorate public imagination in global urban planning.

To gain a deep understanding of maintenance and repair planning, investigate the weak points of the distribution network, and discover unusual events, it is necessary to trace the shutdowns that occurred in the network. Many incidents happened due to the failure of thermal equipment in schools. On the other hand, the most important task of electricity distribution companies is to provide reliable and stable electricity, which minimal blackouts and standard voltage should accompany. This research uses seasonal time series and artificial neural network approaches to provide models to predict the failure rate of one of the equipment used in two areas covered by the greater Tehran electricity distribution company. These data were extracted weekly from April 2019 to March 2021 from the ENOX incident registration software. For this purpose, after pre-processing the data, the appropriate final model was presented with the help of Minitab and MATLAB software. Also, average air temperature, rainfall, and wind speed were selected as input variables for the neural network. The mean square error has been used to evaluate the proposed models’ error rate. The results show that the time series models performed better than the multi-layer perceptron neural network in predicting the failure rate of the target equipment and can be used to predict future periods.

While the rapid development of artificial intelligence has affected people's daily lives, it has also brought huge challenges to high school mathematics teaching, such as restructuring the classroom teaching structure, transforming the role of teachers, and selecting classroom teaching methods. Based on this, the article explores the application strategies of AI technology in improving knowledge introduction, improving mathematics classroom efficiency and stimulating students' learning interest, with a view to optimizing classroom teaching links, improving students' core discipline quality, and promoting the development of high school mathematics teaching informatization.

In the era of rapid information technology development, artificial intelligence (AI) and virtual reality (VR) technologies have gradually infiltrated the field of university English teaching, brought significant applications and impacted to English language learning in listening, speaking, writing, translation, and personalized learning. AI plays a vital role as an auxiliary teaching method in university English instruction, and the integration of VR technology further enhances teaching efficiency. This research will propose relevant recommendations to provide theoretical references for university English education in the age of AI, while also offering insights and guidance to educators in the education industry during the informatization reform of education.

In the teaching of graphic design, students' learning state and learning effect are poor due to the lack of attractiveness of teaching materials. In order to fully display the graphic design knowledge contained in totem patterns, a model based on the pattern elements of totem patterns was constructed. Through Marvelous Designer software, the display of totem visual effects under different pattern element configurations was realized, providing a basis for the comparative explanation of graphic design teaching. When designing the teaching content, based on the totem art culture, it has constructed three parts of teaching methods of plane composition, teaching contents of plane composition and teaching concepts of plane composition, which correspond to the material selection, composition and freehand brushwork skills of totem patterns in modeling creativity and expression techniques, and the range of material selection, composition form and connotation of plane design teaching, the specific application is realized through knowledge transfer.