Soil erosion is characterized by the wearing away or loss of the uppermost layer of soil, driven by water, wind, and human activities. This process constitutes a significant environmental issue, with adverse effects on water quality, soil health, and the overall stability of ecosystems across the globe. This study focuses on the Anuppur district of Madhya Pradesh, India, employing the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS) tools to estimate and spatially analyze soil erosion and fertility risk. The various factors of the model, like rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), conservation practices (P), and cover management factor (C), have been computed to measure annual soil loss in the district. Each factor was derived using geospatial datasets, including rainfall records, soil characteristics, a Digital Elevation Model (DEM), land use/land cover (LULC) data, and information on conservation practices. GIS methods are used to map the geographical variation of soil erosion, providing important information on the area’s most susceptible to erosion. The outcome of the study reveals that 3371.23 km², which constitutes 91% of the district’s total area, is identified as having mild soil erosion; in contrast, 154 km², or 4%, is classified as moderate soil erosion, while 92 km², representing 2.5%, falls under the high soil erosion category. Ad

Mapping land use and land cover (LULC) is essential for comprehending changes in the environment and promoting sustainable planning. To achieve accurate and effective LULC mapping, this work investigates the integration of Geographic Information Systems (GIS) with Machine Learning (ML) methodology. Different types of land covers in the Lucknow district were classified using the Random Forest (RF) algorithm and Landsat satellite images. Since the research area consists of a variety of landforms, there are issues with classification accuracy. These challenges are met by combining supplementary data into the GIS framework and adjusting algorithm parameters like selection of cloud free images and homogeneous training samples. The result demonstrates a net increase of 484.59 km² in built-up areas. A net decrement of 75.44 km² was observed in forest areas. A drastic net decrease of 674.52 km² was observed for wetlands. Most of the wastelands have been converted into urban areas and agricultural land based on their suitability with settlements or crops. The classifications achieved an overall accuracy near 90%. This strategy provides a reliable way to track changes in land cover, supporting resource management, urban planning, and environmental preservation. The results highlight how sophisticated computational methods can enhance the accuracy of LULC evaluations.

Research on zakat has captured the attention of scholars since 1981, exhibiting an increasing trend in publications and citations. This trend presents an opportunity for the author to delve into zakat research. The primary aim of this study is to dissect 10 years of zakat research, spanning from 2013 to 2022, with a focus on evaluating past achievements, current research patterns, and potential future research directions. Utilising bibliometric analysis as the primary tool, this study has formulated seven research questions derived from the primary objective. Key findings indicate a consistent upward trajectory in both publication and citation rates over the past decade, with 2013 being a pivotal year. Notably, Malaysia, Indonesia, and Saudi Arabia emerged as the top three countries actively contributing to zakat research during this period. This study further outlines eight contemporary research trends, exploring various facets of zakat over the past decade. Additionally, this study identifies four prospective areas in zakat for future scholars to explore. This study’s outcomes offer three significant contributions: 1) signalling to scholars that zakat research continues to burgeon; 2) providing inspiration and ideas for current scholars; and 3) motivating future scholars to embark on research ventures in untapped areas within the realm of zakat.

Localization is globally accepted as the strategy towards attaining the Sustainable Development Goals (SDGs). In this article, we put forth the South Indian state of Kerala as a true executor of the localization of SDGs owing to her foundational framework of decentralized governance. We attempt to understand how the course of decentralization acts as a development trajectory and how it has paved the way for the effective assimilation of localization principles post-2015 by reviewing the state documents based on the framework propounded by the United Nations. We theorize that the well-established decentralization mechanism, with delegated institutions and functions thereof, encompasses overlapping mandates with the SDGs. Further, through the tools of development plan formulation, good governance, and community participation at decentralized levels, Kerala could easily adapt to localization, concocting output through innovative measures of convergence, monitoring, and incentivization carried out through the pre-existing platforms and processes. The article proves that constant and concerted efforts undertaken by Kerala through her meticulous and action-oriented decentralized system aided the localization of SDGs and provides an answer to the remarkable feat that the state has achieved through the consecutive four times achievements in the state scores of SDG India Index.

Purpose: The purpose of this paper is to explore the impact of Artificial Intelligence on the performance of Indian Banks in terms of financial metrics. The study focused specifically on the NIFTY Bank Index. The paper also advocates that a greater transparency in disclosing AI related information in a Bank’s annual report is required even if it is voluntary. Design/Methodology/Approach: The paper uses a mixed method approach where quantitative and qualitative analysis is combined. A dynamic panel data model is used to understand the impact of AI of Return on Equity (RoE) of 12 Indian Banks in the NIFTY Bank Index over a five-year period. In addition to that, Content analysis of annual reports of banks was conducted to examine AI related disclosure and transparency. Findings: The paper highlights that the integration of Artificial Intelligence (AI) significantly influences the financial performance of sample banks of India. Return on Equity the specific parameter positively influenced with adoption of AI. The profitability of banks is positively impacted by reduced errors and improved operational efficiency. The content analysis of annual reports of the banks indicates different approach for AI disclosure where some banks give detailed information and some are not transparent about AI initiatives. The findings suggest that a higher level of transparency could enhance confidence of all stakeholders. Theoretical Implications: The positive relation between adoption of AI and financial performance, specifically ROE, gives a foundation for academic research to explore the dynamics of emerging technology and financial systems. The study can be extended to explore the impact on other performance indicators in different sectors. Practical Implications: The findings of this study emphasize the importance of transparent AI related disclosures. A detailed reporting about integration of AI helps in enhanced stakeholders’ confidence in case of banking industry. The regulatory framework of banks may also consider making mandatory AI disclosure practices to ensure due accountability to maximize the benefits of AI in banking.

The transportation sector in India, which is a vital engine for economic growth, is progressively facing challenges related to climate change. Increased temperature, extreme weather conditions, and rising seas threaten physical infrastructure, service delivery, and the economy. This research examines efforts towards improving the climate resilience of India’s transport sector through policy interventions. Strategies encompass broadening the focus to cover the integration of sustainability, innovative technology deployment, and adaptive infrastructure planning. Multi-sectoral measures are proposed to guarantee longevity, equity and environmental protection. National transport infrastructure will be secured, people will be enabled to move sustainably, and India will take its position in the world economy as a climate-resilient country. Long-term resource management and promoting inclusive governance are critical to agri-transportation systems that can withstand the changing climate.