https://journaljgeesi.com/index.php/JGEESI <p style="text-align: justify;"><strong>Journal of Geography, Environment and Earth Science International (ISSN: 2454-7352)</strong> aims to publish high quality papers (<a href="https://journaljgeesi.com/index.php/JGEESI/general-guideline-for-authors">Click here for Types of paper</a>) in all areas of ‘Geography, Environment and Earth Sciences’. By not excluding papers based on novelty, this journal facilitates the research and wishes to publish papers as long as they are technically correct and scientifically motivated. The journal also encourages the submission of useful reports of negative results. This is a quality controlled, OPEN peer-reviewed, open-access INTERNATIONAL journal.</p> <p style="text-align: justify;">This is an open-access journal which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of open access.</p> <p style="text-align: justify;"><strong>NAAS Score: 5.10 (2025)</strong></p> SCIENCEDOMAIN international en-US Journal of Geography, Environment and Earth Science International 2454-7352 https://journaljgeesi.com/index.php/JGEESI/article/view/964 <p>In this climate change era, agriculture is the most threatened sector because of its dependency on local weather conditions. Farming communities in India have still not been able to align with mainstream development process and, therefore, the threat of climate change vulnerability looms larger on them. But planned adaptation, right kind of technologies and policies for farming areas and communities is highly essential to increase the resilience of agricultural production to climate change. The present study was carried out all districts of Bundelkhand region of Uttar Further, one block from each district and from each selected block, two villages were randomly selected. Total 375 households were selected for the collection of data. The survey was conducted for primary data collection during months February, 2025 to May, 2025. The findings revealed that the farming community had a medium to high level of perception about the climate change. The fact that nearly two-thirds of respondents were in the medium category suggests that most farmers are aware and perceived of changes in temperature, rainfall variability, and their influence on farming practices, but may not fully grasp the broader implications or scientific causes. Overall, the study suggested the need for targeted awareness and capacity-building programs for farmers.</p> Pawan Kumar Gupta Harish Chandra Singh Uma Sah Munish Kumar Shivam Singh Dileep Vyas Copyright (c) 2025 Author(s). The licensee is the journal publisher. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2025-10-17 2025-10-17 29 11 1 11 10.9734/jgeesi/2025/v29i11964 https://journaljgeesi.com/index.php/JGEESI/article/view/965 <p>Accurate and efficient pre-census mapping is crucial for reliable population enumeration, particularly in regions with complex geographic and security constraints. This study presents a semi-automated Geographic Information System (GIS) approach for developing a detailed digital geodatabase to support Mali’s fifth pre-census, with a rigorous validation process ensuring methodological reliability. Using high-resolution satellite imagery and geospatial techniques, Enumeration Sections (ES) were delineated based on estimated population and visible boundaries such as roads and waterways. The method integrates Google Satellite imagery with geospatial data to generate ES polygons aligned with administrative limits and population thresholds. Validation in the cercles of Macina and Niono demonstrated strong accuracy, with correlation coefficients of 0.97 and 0.94, and Root Mean Square Errors (RMSE) of 37.46 and 42.79, respectively. The Mean Absolute Errors (MAE) of 26.63 and 29.58 indicate minimal deviation between estimated and field-measured populations, confirming high model consistency. While the approach enhances mapping accuracy and efficiency, limitations include dependence on satellite image quality and challenges in updating rapidly changing regions. Compared with similar GIS-based census mapping initiatives in Nigeria and Kenya, the proposed method shows comparable performance and adaptability. Beyond Mali, this scalable and cost-effective framework offers a practical solution for pre-census and population mapping in other low- and middle-income countries.</p> Mahamadou CAMARA Souleymane BENGALY Oumar COULIBALY Copyright (c) 2025 Author(s). The licensee is the journal publisher. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 2025-10-18 2025-10-18 29 11 12 26 10.9734/jgeesi/2025/v29i11965