This study applies machine learning methods such as Decision Tree (CART) and Random Forest to classify drought intensity based on meteorological data. The goal of the study was to evaluate the effectiveness of these methods for drought classification and their use in water resource management and agriculture. The methodology involved using two machine learning models that analyzed temperature and humidity indicators, as well as wind speed indicators. The models were trained and tested on real meteorological data to assess their accuracy and identify key factors affecting predictions. Results showed that the Random Forest model achieved the highest accuracy of 94.4% when analyzing temperature and humidity indicators, while the Decision Tree (CART) achieved an accuracy of 93.2%. When analyzing wind speed indicators, the models’ accuracies were 91.3% and 93.0%, respectively. Feature importance revealed that atmospheric pressure, temperature at 2 m, and wind speed are key factors influencing drought intensity. One of the study’s limitations was the insufficient amount of data for high drought levels (classes 4 and 5), indicating the need for further data collection. The innovation of this study lies in the integration of various meteorological parameters to build drought classification models, achieving high prediction accuracy. Unlike previous studies, our approach demonstrates that using a wide range of meteorological data can significantly improve drought classification accuracy. Significant findings include the necessity to expand the dataset and integrate additional climatic parameters to improve models and enhance their reliability.

This study delves into the nuanced impact of leadership styles on state-owned enterprises (SOEs) performance in Northeast China. It aims to discern how transformational, transactional, and authoritative leadership approaches influence organizational outcomes, framed within the context of sustainable leadership theory. Employing a quantitative methodology, the research analyzes survey data from employees across various SOEs to assess the relationship between leadership styles and company performance, including aspects such as job satisfaction, employee motivation, and operational efficiency. The findings reveal a clear dichotomy: transformational and transactional leadership styles positively correlate with improved performance metrics, fostering an environment of innovation, motivation, and job satisfaction. Conversely, authoritative leadership is shown to detrimentally affect these same metrics, potentially hindering organizational growth and employee morale. This research contributes to the broader discourse on leadership and organizational performance by highlighting the critical role of leadership style in enhancing the sustainable development of SOEs, particularly within China’s socio-political and economic fabric. Practical implications suggest a shift towards more adaptive, employee-centered leadership approaches to spur performance and sustainability in SOEs. The originality of this study lies in its specific focus on the Chinese context, offering insights into the leadership dynamics within SOEs and proposing actionable strategies for fostering leadership that align with sustainability and organizational excellence principles.

The contradiction between the ability of forestry that provides high-quality and abundant forestry products and good ecological services, and the demand for high-quality and diversified forestry products and service in order to meet the people’s rapid growing, has become the main contradiction faced by forestry development in new era. Since the area of forest resources in China is restricted by the expansion space, expanding the effective supply of forestry must mainly depends on the improvement of the quality and structure of forestry resources. Therefore, the focus of promoting forestry development is to comprehensively improve the level of forest management in the new era. Based on the analysis of the causes for the low level of forest management, it is proposed that forestry development in the new era should focus on the positively stimulating and strengthening the human capital development, etc., which come from the current following aspects: innovating forest management theory and model, clarifying the relationship between government and market.

The detection of urban expansion through digital processing of satellite images provides valuable information for understanding the dynamics of land use change and its spatial relationship with environmental factors. In order to apply or generate effective land-use planning policies, it is essential to have a historical record of the regional distribution of human settlements, an element that is practically non-existent in our country. For this reason, this text aims to determine the urban growth rate during the period 2000–2014 in the state of Hidalgo, Mexico, and to identify potential expansion zones from Landsat images. Six Landsat scenes were used for the spatial analysis of the state urban coverage and their relationship with the road influence area was evaluated. Two maps were obtained as cartographic products: one of urban coverage distribution and another of the municipalities with the greatest expansion, whose areas are located in the Valle del Mezquital region. However, Mineral de la Reforma, Tetepango, Tizayuca and Pachuca de Soto stand out for their growth rates during the study period: 183.44%, 102%, 94% and 68.5%, respectively. In total, the state urban area in-creased 72.3 km² from 2000 to 2014 with an average growth rate of 1.8% per year. Such growth was associated with the areas of influence of important road infrastructure, such as the Libramiento Arco Norte in Hidalgo. Therefore, the Mezquital Valley and the Mexico Basin are considered as potential regions for urban expansion in the state.

Conflicts are inevitable in any human community, despite the fact that they are never desirable. One of the characteristics of the contemporary world is conflict. Different parties participate in disputes (individuals, organizations, and states). When disputes arise, interventionist methods are put into action. Conflicts arise in a variety of ways, such as disagreement, rage, quarrelling, hatred, destruction, killing, or war, because human requirements are diverse. Conflict takes many different shapes, and so do interventions. Individuals, groups (both local and foreign), and governments can all intervene in a conflict. The media and its functions are up for debate among those who mediate disputes. Can the media be seen as intervening in a dispute, or are they merely performing their mandated duties? The diversity of opinions is what drives conversations in peace journalism. In addition, peace journalism promotes media engagement and intervention in conflict situations in order to lessen and end conflict. Media intervention, according to some critics, is not objective journalism because those in charge of educational information management and journalists are not expected to make decisions about the news; rather, they should just tell it as they see it. Therefore, the purpose of this article is to examine the idea of conflict, the stages of conflict development, interventions in conflicts, and the contentious position of the media in conflicts from an educational information management perspective. Hence, this paper will contribute to the role of educational information management via social media and other new media platforms, which have occasionally been used to hold governments responsible, unite people in protest of violence, plan relief operations, empower people, dissipate tensions via knowledge sharing, and create understanding across boundaries.