Real-time soil erosion detection using satellite imagery and analysis

Abstract

Soil erosion is very hazardous to the global ecosystem. Government aided soil erosion control schemes happen dilatorily with minimal resources. Recognition and identifying the scale and the area of eroded land can be extremely time-consuming and difficult as well. To overcome this problem, a real-time Soil erosion detection system is introduced. The real-time part has been implemented using satellite imagery with the use of RUSLE modelling considering various factors. This was generated with the help of Google Earth Engine (GEE) interface. The RUSLE model offers a straightforward approach to assess soil erosion. By using remote sensing data and GIS, RUSLE effectively evaluates erosion. Researchers have developed various equations to model the five factors of the RUSLE model, considering the diverse variations in the soil erosion process. The system also includes the analysis of satellite imagery with a mapped view of soil erosion. Here, the Unet (EfficientNetb3) model is used giving optimal accuracy for the detection of soil erosion.

Nowcasting Floods in Detailed Scales Considering the Uncertainties Associated with impact-based Practical Applications

Abstract

Impact-based nowcasting systems at detailed scales, to the street level, have become essential in flood risk management. This is achieved by focusing on predicting the impacts of flood events rather than merely forecasting weather conditions. This approach leverages advancements in 2D hydrodynamic modelling, high-performance computing (HPC), and detailed rainfall forecasting to improve the precision of early warning systems. However, its real-world implementation is hindered by challenges such as the coarse temporal resolution of weather forecasts and inherent modelling uncertainties. This study investigates the uncertainties and challenges associated with impact-based nowcasting systems, using the Mandra town (Greece) as a case study. We demonstrate the feasibility of applying a comprehensive framework that integrates 2D hydrodynamic modelling, HPC, and temporally disaggregated rainfall forecasting. Our findings show that the Alternating Block Method (ABM) effectively captures storm dynamics, mitigating significant underestimations that arise from coarser forecast inputs. Additionally, we assess various flood impact indices to manage modelling uncertainties. Our results highlight that similarities exist in the flood indices when storms are mild with short return periods. However, discrepancies between indices increase with storms of longer return periods, underscoring the critical need for careful index selection. This research provides new insights into enhancing flood nowcasting accuracy and effectiveness, particularly in small to medium-sized catchments. Moreover, it offers evidence that the scientific community along with the stakeholders such as Civil Protection, local governments, and others should focus orient their efforts on more reliable flood indices, as the discrepancies between the methodologies investigated increase with the severity of the events.

How mixed messages may be better than avoidance in climate change education

Abstract

Polarization around climate change viewpoints — including climate change concern and commitment to action — continues to be a persistent challenge to collective action in the United States, and across the globe. Multiple studies have found that K-12 science teacher perceptions of climate change reflect that of the general population, raising concerns that education may be replicating among students the polarization found among adults. However, few have examined how approaches to teaching climate change may be linked to climate change concern and behavior among students. We began to address this gap with a pre/post-survey of 354 middle school students from eight science classrooms across North Carolina and their teachers. We measured changes in climate change concern and behavior among students, student-reported frequency of discussing climate change in class, and teacher-reported approach to teaching climate change as consistent with the scientific consensus (climate change is attributed to human activity, 13.2% of students in these classes); mixed messages (scientists think climate change is attributed to both human and natural causes, 53.2% of students); denial (scientists think climate change is attributed to natural causes, none of students); and avoidance (not discussing causes of climate change, 33.5% of students). We also controlled for socioeconomic status (Title I) and location (rural versus urban) of the school. We detected gains in both concern and behavior across all teaching approaches. We also found frequency of school-based discussion about climate change was the most predictive of gains in concern, but no measured factors predicted gains in behavior. Baseline concern and behavior levels did vary across the different treatment approaches, with lower baseline concern and levels found among teachers who take avoidance and mixed messages approaches. Together, these results suggest that cultural contexts may be the drivers of both teaching approaches and student climate change concern and behavior, but variations in teaching approaches are not polarizing forces themselves. Instead, encouraging classroom-based conservations about climate may boost concern levels, even in cultural contexts that do not prioritize scientific consensus about climate change drivers. These findings may provide guidance for teaching climate change as well as other politically fraught topics.

A comparative analysis of the ethics of gene editing: ChatGPT vs. Bard

Abstract

Recently, there has been a growing trend in using large language models (LLMs) to develop diverse applications suitable for a wide range of tasks. These tasks range from solving programming bugs to helping teach elementary school students how to enhance their writing. Even with all these beneficial use cases, researchers worry about the potential bias these tools could produce and their effect on society. In this research, we compared responses that resulted from prompting two chatbots, namely OpenAI ChatGPT and Google Bard, about the issue of gene editing. Twelve prompts that are part of two subgroups were used to generate responses (text) about the issue of gene editing when the political affiliation (Democrat, Republican, and Communist) or geographical areas (United States, China, and Europe) of the prompter is provided. The Twelve responses were then analyzed semantically using three dictionary-based tools, i.e., Linguistic Inquiry and Word Count, the Moral Foundation Theory and Biblical Ethics dictionary, and Google’s Perspective API, to test and analyze the semantic and linguistic differences (measured via the Mann–Whitney U test) in the responses returned from the two chatbots. The results suggest that there are semantic and linguistic differences in responses per chatbots and prompts.

Special issue of the asian journal of business ethics on global survey of business ethics (GSBE) reports 2022–2024 from Asia, Australia and Russia – Indonesia

Abstract

This article aims to explore the main topics in business ethics in Indonesia by reviewing manuscripts and conducting focus discussion groups. We adopt Harzing’s PoP application to review 995 manuscripts and VOS Viewer to draw a bibliometric figure, followed by a series of focus discussion groups. This article explores the main topics in business ethics in Indonesia by reviewing manuscripts and conducting focus discussion groups. The results show that the primary business ethics literature in Indonesia focuses on four topics: (1) ethics in the financial market, (2) ethics in education, (3) ethics in the workplace, and (4) Sharia ethics. These key trends of business ethics literature are different from the global literature. The main reason may come from the cultural gap, in which the local cultural diversity provides various terminologies and key recurring concepts. The results present the central local wisdom that comes from the significant ethnicity in this country. In addition, this report also provides future ethical topics at the intersection between business and political ethics by involving digital technological turbulence. In addition, future ethical topics need to address the intersection between business and political ethics by involving digital technological turbulence to explain how Indonesian tech companies strive to integrate ethical practices and strengthen data protection, especially in the gig economy and e-commerce sectors. Hence, the business ethics curriculum should encourage responsible consumers and producers by promoting awareness of false information, cyberbullying, and political manipulation.

Evaluation of temporal spatial changes of reference evapotranspiration under the influence of climate change in Gorganroud watershed in northern Iran

Abstract

Reference evapotranspiration (ET0), as one of the main components of the hydrological cycle, plays an important role in water resources management and agricultural planning. This study was conducted with the aim of predicting the temporal and spatial changes of ET0 in the Gorganroud watershed in northern Iran. The minimum and maximum temperatures were predicted using the output of five CMIP6 climate models under two climate scenarios of SSP2-4.5 and SSP5-8.5 for the historical base (1985–2014), near future (2025–2054) and far future (2071–2100) periods. The bias correction of the simulation data was performed using the linear scaling method. To reduce the uncertainty of climate models, a multi-model ensemble based on the application of Bayesian Model Averaging (BMA) was created and the reference evapotranspiration was calculated using the Hargreaves-Samani method. The results showed that under the SSP2-4.5 scenario, the minimum and maximum temperatures will increase by 1.65 and 1.8 ºC, respectively, whereas under the SSP5-8.5 scenario, the minimum and maximum temperatures will increase by 2.5 and 2.7 ºC, respectively. Similarly, the projections show that the reference evapotranspiration will increase on seasonal and annual scales in the future climate compared to the base period. The largest increase in ET0 is estimated to be 12.4% under the SSP5-8.5 scenario in the period 2071–2100 compared to the base period. The largest increase in evapotranspiration is in summer with values of 5.8–8% and 7.8–13.3% for the SSP2-4.5 and SSP5-8.5 scenarios, respectively. Analysis of the zonation of changes in evapotranspiration showed that most of the changes occur in the eastern regions and at Gharehbil and Cheshmehkhan stations. Our results indicate that future climate change will cause a significant increase in ET0 at high altitudes.

Climate change denial theories, skeptical arguments, and the role of science communication

Abstract

Climate change has become one of the most pressing problems that can threaten the existence and development of humans around the globe. Almost all climate scientists have agreed that climate change is happening and is caused mainly by greenhouse gas emissions induced by anthropogenic activities. However, some groups still deny this fact or do not believe that climate change results from human activities. This article examines climate change denialism and its skeptical arguments, as well as the roles of scientists and science communication in addressing the issues. Through this article, we call for the active participation of scientists in science communication activities with the public, the initiation of new science communication sectors specified for climate change, and more attention to social sciences and humanities in addressing climate change issues.

AI content detection in the emerging information ecosystem: new obligations for media and tech companies

Abstract

The world is about to be swamped by an unprecedented wave of AI-generated content. We need reliable ways of identifying such content, to supplement the many existing social institutions that enable trust between people and organisations and ensure social resilience. In this paper, we begin by highlighting an important new development: providers of AI content generators have new obligations to support the creation of reliable detectors for the content they generate. These new obligations arise mainly from the EU’s newly finalised AI Act, but they are enhanced by the US President’s recent Executive Order on AI, and by several considerations of self-interest. These new steps towards reliable detection mechanisms are by no means a panacea—but we argue they will usher in a new adversarial landscape, in which reliable methods for identifying AI-generated content are commonly available. In this landscape, many new questions arise for policymakers. Firstly, if reliable AI-content detection mechanisms are available, who should be required to use them? And how should they be used? We argue that new duties arise for media and Web search companies arise for media companies, and for Web search companies, in the deployment of AI-content detectors. Secondly, what broader regulation of the tech ecosystem will maximise the likelihood of reliable AI-content detectors? We argue for a range of new duties, relating to provenance-authentication protocols, open-source AI generators, and support for research and enforcement. Along the way, we consider how the production of AI-generated content relates to ‘free expression’, and discuss the important case of content that is generated jointly by humans and AIs.

The State and Complex Threat Syndrome in the Sahel: Conflict, Crime, and Terror

Abstract

This study examines the phenomena of complex threat syndrome (CTS) in the Sahel from the standpoint of the increasing dysfunctionality of the states in this area. The study posits that the CTS in the Sahel reflects the logic of a conflict-crime-terror conundrum in the context of rising state fragility. The crisis of legitimacy and governability in the Sahel, instantiated by the weaknesses of the states to facilitate governance, security, and development effectively and sustainably, has brought about conditions that exacerbate anti-state militantism and extremism. The inability of governments to demonstrate requisite competencies in the face of these threats bolsters and reproduces widespread criminal indulgence, impunity, and opportunism. Critical indicators of this include rising jihadist insurgencies, banditry, communal conflicts, and other forms of violence. The consequence has been a complex threat situation where violent conflicts and crimes reinforce each other to engender an enduring climate of insecurity and crisis. Mitigating such a complex security scenario requires a deliberate effort by the authorities in the Sahel to optimize statecraft through effective state-building, security governance reforms, and functional state-society synergy.