Integrated Resource Management plays a crucial role in sustainable development by ensuring efficient allocation and utilization of natural resources. Remote Sensing (RS) and Geographic Information System (GIS) have emerged as powerful tools for collecting, analyzing, and managing spatial data, enabling comprehensive and integrated decision-making processes. This review article uniquely focuses on Integrated Resource Management (IRM) and its role in sustainable development. It specifically examines the application of RS and GIS in IRM across various resource management domains. The article stands out for its comprehensive coverage of the benefits, challenges, and future directions of this integrated approach.
A total of 25 SSR primers were screened on 37 putative F1s derived from the five different crosses. Identified cross specific highly informative SSRs primers, i.e., 14 for the first cross, 10 for the second, 12 for the third and 6 each for fourth and fifth crosses. For the first cross Bhagwa × Daru 17, four primers (HvSSRT_375, NRCP_SSR9, NRCP_SSR12 and NRCP_SSR92) were found to be highly informative with higher 100% hybrid purity index (HPI), PIC (~0.52), and observed heterozygosity (Ho, range 0.87–0.93) values, and two F1s namely H1 and H2 were found to be highly heterotic with a heterozygosity index (HI) of 92.85%. Similarly, for Bhagwa × Nana, three primers (HvSSRT_375, HvSSRT_605 and NRCP_SSR19) had higher HPI (70%–100%), PIC (0.52–0.69), and Ho (0.75–0.33) values, and three F1s H1, H2, and H4 had 70% (HI). For Bhagwa × IC318712, four SSRs (HvSSRT_254, HvSSRT_348, HvSSRT_826 and NRCP_SSR95) had higher Ho (~0.83), HPI (100%) and PIC (~0.52) values, and four F1s H2, H7, H9, and H10 showed 91.66% (HI). For Bhagwa × Nayana, HvSSRT_605, HvSSRT_826, and HvSSRT_432, and for Ganesh × Nayana, HVSSRT_375, HVSSRT_605, and HvSSRT_826 were found informative. These markers will be highly useful in developing maps of populations.
Madura Island, with more than half of its population, are women encountering socio-economic problems, which eventually create high poverty and unemployment rates. However, the Madurese are also well-known for their resiliency and entrepreneurial characteristics. The effort to solve the issues by empowering the community, women in particular, has been taken seriously primarily by entrepreneurs who were born and raised in the community. Therefore, this research aims to gain insight into the current Madurese entrepreneur’s business pattern and their social concerns in order to propose a strategy to increase productivity as an effort to empower women’s communities. The methodology is qualitative research, which collects data using semi-structured interviews with representatives of the Madurese entrepreneurs in four areas of Madura Island. Their responses are then transcripted and coded for content analysis based on the designed themes. The result shows that they recognise and practise the social entrepreneurship (SE) pattern, although they do not understand the term. Subsequently, the technological application for business operations in general is still limited to the usage of digital technology (DT) for marketing and transaction activities, which helps increase business performance or productivity. Hence, the initiation of technosociopreneurship as a strategy to further develop SE activities with the hope of increasing productivity in empowering women’s communities is proposed. Further research development is advised using quantitative methods for generalisable findings.
Urbanization process affects global socio-economic development. Originally tied to modernization and industrialization, current urbanization policy is focused on productivity, economic activities, and environmental sustainability. This study examines impact of urbanization in various regions of Kazakhstan, focusing on environmental, social, labor, industrial, and economic indicators. The study aims to assess how different indicators influence urbanization trends in Kazakhstan, particularly regarding environmental emissions and pollution. It delves into regional development patterns and identifies key contributing factors. The research methodology is based on classical economic theories of urbanization and modern interpretations emphasizing sustainability and socio-economic impacts and includes two stages. Shannon entropy measures diversity and uncertainty in urbanization indicators, while cluster analysis identifies regional patterns. Data from 2010 to 2022 for 17 regions forms the basis of analysis. Regions are categorized into groups based on urbanization levels leaders, challenged, stable, and outliers. This classification reveals disparities in urban development and its impacts. Findings stress the importance of integrating environmental and social considerations into urban planning and policies. Targeted interventions based on regional characteristics and urbanization levels are recommended to enhance sustainability and socio-economic outcomes. Tailored urban policies accommodating specific regional needs are crucial. Effective management and policy-making demand a nuanced understanding of these impacts, emphasizing region-specific strategies over a uniform approach.
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