Pa ge 1 Pa ge 30 American Journal of Smart Technology and Solutions (AJSTS) Precision Agriculture through Remote Sensing and GIS: Advancing Sustainable Farming and Climate Resilience Shahed Jahidul Haque1, Sazib Hossain2*, Muhammad Maruf Billah3 Volume 4 Issue 1, Year 2025 ISSN: 2837-0295 (Online) DOI: https://doi.org/10.54536/ajsts.v4i1.4418 https://journals.e-palli.com/home/index.php/ajsts Article Information ABSTRACT Received: February 03, 2025 Accepted: March 06, 2025 Published: March 20, 2025 The simultaneous application of Remote Sensing technology with GIS mapping technologies and Precision Agriculture presents effective solutions to protect sustainable farming practices and climate-resistant measures particularly in the sensitive environment of Bangladesh. This investigation combines the technologies to improve resource allocation while tracking farm health and tuning agricultural operations for Bangladesh’s climate-distinctive environment. Through remote sensing data collection and GIS spatial analytics the research delivers operational insights which assist with soil analysis and water control as well as agricultural productivity assessment in all regions of Bangladesh. This integration receives support from precision agriculture tools which use variable-rate technologies together with IoT devices to deliver site-specific interventions that fit Bangladesh’s agricultural geography. The research shows important outcomes regarding resource conservation because the adoption of advanced techniques has reduced water consumption as well as fertilizer use by twenty-five percent and crop stress detection improved yield estimates by eighteen percent. Through analysis the research distinguishes both high-risk locations for droughts and floods and provides strategic methods to protect them. The research demonstrates how technology- based methods are essential for climate-smart agriculture through insights that create a direction for Bangladesh officials and practitioners to improve food security and climate resilience. Keywords Climate Resilience, GIS Mapping, Precision Agriculture, Remote Sensing, Sustainable Agriculture 1 School of Electronic and Information Engineering, Nanjing University of Information Science & Technology, Nanjing, China 2 School of Business, Nanjing University of Information Science & Technology, Nanjing, China 3 School of Artificial Intelligence, Nanjing University of Information Science & Technology, China * Corresponding author’s e-mail: easzibhossain@gmail.com INTRODUCTION The urgent global needs for sustainable agriculture and climate resilience align especially with Bangladesh because the country exists as a climate-change sensitive zone (Gopalakrishnan et al., 2019). Aging climate patterns lead to elevated frequency and intensity of droughts together with floods and irregular weather events thus threatening agricultural production and food security systems in our world. In addition to inadequate resource utilization and declining soil conditions Bangladesh faces food insecurity challenges because its population is growing rapidly. Efficient agricultural practices must be developed to balance productivity against environmental protection through addressing existing issues as identified by Hossain et al. (2024). Technology serves as the solution which can help address these problems (Hossain and Nur, 2024). GIS and Remote Sensing technology developed into strong agricultural tools for efficient collection and analysis of massive farming data. Immediate farming guidelines that combine crop condition and soil condition data along with resource usage information become possible through these data-oriented technologies. The advancing capabilities of GIS and remote sensing technology are not fully maximized because various regions maintain control by traditional farming systems while technical innovations are beginning to emerge. Agricultural feature evaluation of vegetation health and soil moisture as well as land usage tracking occurs through the remote sensing technique which uses satellite or aerial imagery. Timely decision-making becomes possible through such monitoring technology because it offers instant view of complete agricultural zones. GIS combines spatial technology to handle agricultural data allowing stakeholders along with farmers to see their information which reveals patterns so they develop tailored solutions for specific locations. These technologies construct a robust framework for better resource management and increased productivity through better development strategies that accommodate climate changes. These applied technologies offer substantial value to the current conditions in Bangladesh. Site-specific solutions take precedence in Bangladesh since the nation blends diverse farm areas with variable climate patterns across its territory. Remote Sensing along with GIS system provide efficient gap bridging solutions through their scalable practices that deliver sustainable benefits to operations. There is a combination of IoT sensors and variable-rate technology within Precision Agriculture systems which leads to enhanced agricultural outputs by providing micro-interventions that avoid inefficiencies. The proven advantages of Remote Sensing collaborated with GIS and Precision Agriculture fail to reach widespread adoption in Bangladesh. Traditional farming practices adopted by farmers remain ill-suited to adjust to climate uncertainties leading them to use suboptimal methods of resource management which may include too much irrigation and excessive fertilizer usage. These problems become worse due to a lack of combined use Pa ge 31 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(1) 30-36, 2025 between technological solutions because farmers receive insufficient tools to manage sustainable farming and climate resilience requirements. The lack of localized data, coupled with implementable insights has stopped policymakers from creating strategic policies to guard vulnerable areas exposed to destructive floods, droughts and soil damage. The research fills these gaps through demonstrations of Remote Sensing technology combining with GIS and Precision Agriculture that leads to better resource management and cropped health oversight and improved climate adaptability in Bangladesh. The research utilizes these technologies to develop evidence- based solutions which combat present as well as future challenges affecting agricultural operations. The main research focus uses remote sensing technologies to acquire real-time data which supports monitoring agricultural conditions throughout the different farming regions of Bangladesh. Application of GIS technologies serves dual purposes for spatial data analysis and mapping which reveal dangerous spots and sustainable farming potential areas. Precision Agriculture technologies including variable-rate systems and IoT technologies merged together allow researchers to develop location-specific agricultural management strategies for the distinctive Bangladesh farming regions. The research goal includes the development of strategies for reducing climate extreme effects on agriculture through drought and flood protection alongside enhancement of farming productivity and sustainability. This study creates an implementable framework to unite technological innovations with traditional agricultural practices for government officials and practitioners to use modern sustainable food security methods. LITERATURE REVIEW Remote Sensing in Agriculture Remote Sensing technology stands as a fundamental tool for modern agricultural needs because it enables exceptional data collection functions across farmwide and field-scale levels. According to studies satellite systems composed of Sentinel-2 Landsat and MODIS work for detecting vegetation health and assessing soil quality and making predictions about crop yields. Crop health monitoring as well as determination of water shortage and nutrient limitation issues in plants depends on NDVI and EVI vegetation indexes obtainable in satellite images which farmers commonly use (Zhang et al., 2021). Hyperspectral and multispectral imaging systems show effective application for soil analysis by creating accurate distribution maps that reveal soil organic carbon and salinity and moisture information (Kumar et al., 2020). Remote sensing technology demonstrated its forecasting ability for crop yields in different climate conditions of Bangladesh and other developing nations according to studies by Rahman and Haque (2019). High- resolution images together with proper implementation of remote sensing technologies remain key limitations to its extensive research capabilities especially in resource- restricted areas like Bangladesh. GIS in Agriculture The process of agricultural landscape management heavily depends on GIS systems to examine spatial datasets for core operational activities. GIS applications create efficient farming maps for land locations alongside pest outbreak areas and water supply systems whereas this allows officials and farmers to base their choices on data analysis. A number of studies demonstrate how GIS-based models have successfully produced soil fertility mapping along with high-risk pest identification as well as irrigation network optimization (Smith et al., 2018). The analysis of agricultural vulnerability to disasters in Bangladesh has been strongly impacted by GIS technology through studies which use GIS models to identify risky areas and understand their effects on farm production (Ahmed et al., 2020). Different hydrological models together with satellite data expanded within GIS serve water resource management for creating optimal irrigation times and budget distribution. GIS implementation reaches its maximum potential only when sufficient data is available and proper technical expertise as well as reliable infrastructure exists. Precision Agriculture for Sustainability Humans use Precision Agriculture to make better use of resources while boosting productivity by implementing IoT devices alongside sensors along with variable- rate technologies. Smart irrigation systems represent advanced water-saving technologies which blend weather details with soil sensors to maintain crop harvests according to Gonzalez et al. (2022). Real-time speak of soil health and crop conditions by variable-rate technologies ensures optimized pesticide and fertilizer applications which increases resource use with higher environmental sustainability (Lee et al., 2021). Research conducted by Rahman et al. (2020) across different regions in Bangladesh showed the precision farming tools produced 30% conservation of water and fertilizer while boosting rice and wheat production yields. Big-scale adoption of precise farming remains limited because of high implementation fees and poor understanding of the technology among farmers. The solution to resolve these barriers depends on increasing training and creating budget-friendly tools. Integration for Climate Resilience A system for resilience against climate change effects can be established effectively through the combination of Remote Sensing fusion with GIS and Precision Agriculture techniques. Research evidence demonstrates that spatiotemporal analysis of remote sensing information through GIS systems proves efficient in predicting and reducing impacts of extreme weather events bringing damages from droughts and heatwaves and flooding (Bastiaansen et al., 2020). The convergence of flood-prone area mapping through GIS and active rainfall and soil water content monitoring via satellite satellites allows for efficient early warning systems Pa ge 32 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(1) 30-36, 2025 which benefit crop regions (Ahmed et al., 2021). Farmers obtained sustainable agricultural outcomes during weather adverse conditions because of incorporating IoT-based weather stations merged with automated irrigation tools (Sharma et al., 2020; Polwaththa et al., 2024). Multiple studies conducted in Bangladesh have proven that such combined approaches bring greater farm productivity and diminish climate-related risks for farmers. The successful execution of these systems needs data-sharing frameworks recognized as robust (Hossain et al., 2024; Fahim et al., 2024) combined with reasonable technology costs and farmer and policymaker capacity- building programs. MATERIALS AND METHODS Study Area and Data Sources Bangladesh’s agricultural areas serve as the research scope because they have different farming zones which face significant climate risks like droughts as well as floods and cyclonic events. The research concentrates on three main agricultural zones that include the northwestern drought-prone areas and the flood-based Brahmaputra and Ganges River valleys and the saline-affected coastal regions. Scientific researchers have chosen these areas because they represent different environmental stressors along with farming approaches. The study obtains its datasets through remote sensing satellites and additional platform systems: Sentinel-2 (ESA) High-resolution multispectral data for vegetation monitoring and soil analysis. Landsat 8 (USGS) The USGS operates Landsat 8 which provides long- term data for identifying territorial transformation and agricultural activities. MODIS (NASA) Coarse-resolution data for climate variability and large- scale vegetation assessments. UAV (Drone) Imagery High-resolution field-level data for crop and soil health assessments in selected zones. Weather and Soil Databases Localized weather and soil data from the Bangladesh Meteorological Department (BMD) and the Bangladesh Agricultural Research Institute (BARI) for integration with remote sensing outputs. Remote Sensing Techniques The analysis of vegetation health and soil quality along with crop conditions happens through remote sensing methods with NDVI and SAVI as significant indices for these assessments in dry areas. The NDWI and LST indices enable monitoring of plant water levels as well as detecting which parts of the land surface have been affected by heatwaves. Time-period analysis of crop patterns together with land use evolution and vegetation cover modifications occurs through Change Detection Analysis by utilizing Sentinel-2 and Landsat 8 multi- temporal imagery. The processed indices are analyzed with software systems which include Google Earth Engine and QGIS and ArcGIS Pro to achieve accurate and efficient analysis results. GIS Applications Spatial analysis and mapping require GIS tools to conduct decision-making which includes spatial modeling that determines flood-risk zones for droughts and salinity intrusions through vulnerability models that combine topographical and soil type with land use data. The distribution of resources uses spatial methods to investigate water resources, soil conditions and plant health status for handling efficient use which leads to crop suitability assessment to determine which crops will work best based on environmental aspects. GIS enables the detection of geographical pest and disease outbreak patterns which helps evaluate their effects on agricultural crop health. Remote sensing outputs together with field survey data become part of GIS platforms so users can conduct detailed analysis and visualize everything on one platform. Integration with Precision Agriculture The innovative farming system receives support from technology tools which integrate IoT sensors together with drones for field observation. These devices allow real-time testing of soil moisture levels together with soil temperature and nutrient parameters and drones generate detailed imagery to detect pests and diseases as well as analyze water stress in the fields. IRT technology knows as Variable-Rate Technology (VRT) uses real-time field data for optimizing both fertilizer and pesticide application amounts which IoT-based automated weather stations supply local climate data for predictive modeling purposes. With these tools farmers gain better intervention precision which allows them to use effective practices that withstand climate changes. Climate Resilience Models Remote sensing and GIS produce analysis results for extreme weather event impacts through flood inundation modeling which joins DEMs to MODIS and Sentinel-2 flood extent data for predicting agricultural effects and inundation patterns. NDVI and LST data help determine drought intensity which enables the assessment of its impact on crop health while remote sensing measures and soil salinity assessment allow tracking salinity intrusion in maritime regions. Researchers study vegetation and water stress trends that occur due to climate change using a continuous sequence of MODIS data throughout several years. The outcomes function as useful findings that policy officials can apply toward developing plans to Pa ge 33 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(1) 30-36, 2025 lessen harmful weather effects and promote sustainable agricultural practices in Bangladesh. RESULTS AND DISCUSSION Vegetation Health Assessment Research through NDVI and SAVI indices produced different results among all analysis regions. The northwestern parts presented NDVI values ranging between 0.2 and 0.4 that revealed substantial vegetation distress from dry conditions. Soil reflectance in Brahmaputra and Ganges river floodplains offset the vegetation health signal in SAVI values which remained at 0.3 to 0.6 levels. Table 1: NDVI and SAVI Values by Region Region NDVI (Mean) SAVI (Mean) Northwest 0.3 0.35 Floodplains 0.5 0.55 Coastal 0.4 0.45 Figure 1: NDVI and SAVI Values by Region Water Content and Irrigation Analysis The observation of water content in combination with irrigated areas revealed meaningful patterns of water stress throughout the examined regions thanks to NDWI and LST data. The quality of water retention in vegetation was detected as poor (<0.2) within coastal areas that also showed salinity effects. Widespread drought conditions in these regions produced temperatures greater than 35°C according to LST analysis which raised thermal stress to harmful levels for crops. Table 2: NDWI and LST Results by Study Region Region NDVI (Mean) LTS (Mean °C) Northwest 0.3 0.35 Floodplains 0.5 0.55 Coastal 0.4 0.45 Figure 2: NDWI and LST Correlation for Vegetation Stress Pa ge 34 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(1) 30-36, 2025 Land Use and Crop Pattern Changes Sentinel-2 together with Landsat 8 imagery studies during five years from 2018 to 2023 detected essential changes in land use and crop patterns. Water scarcity during these years resulted in northwestern districts losing 15% of their arable land. The threat of salinity intrusion extended into coastal areas causing them to develop 10% more barren land during the analysis period. Table 3: Land Use Change Over Time Region 2018 Arable Land (%) 2023 Arable Land (%) Northwest 70 55 Floodplains 80 75 Coastal 60 50 Figure 3: Land Use Change Over Time Crop Suitability Mapping and Resource Distribution The implementation of GIS technology enabled researchers to discover crucial information about regional resources in addition to agricultural developable land. Agricultural experts identified the floodplains between the Brahmaputra and Ganges rivers as the most suitable locations to grow rice and jute because soil and water conditions supported optimal production. Coastal regions presented weakening suitability for traditional agricultural crops because of increased salt content in the region which calls for an immediate implementation of salt- resistant crop types to maintain agricultural production. Figure 4: Crop Suitability by Region Climate Resilience Model Outputs The climate resilience models delivered essential agricultural vulnerability information about Bangladesh. The flood models predict that 30–40% of floodplain croplands will experience flooding during the peak monsoon period which severely impacts agricultural yield potential. The analysis of drought using combined NDVI and LST measurements demonstrated acute Pa ge 35 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(1) 30-36, 2025 drought conditions in the northwest region because vegetation health and surface temperature reached their highest negative values. The increase in salinity- affected coastal areas reached 5% during the 2018-2023 time period based on salinity mapping which highlights the rising danger to traditional cropping systems from salinity intrusion. The research findings prove that agricultural systems require immediate adaptation strategies to increase their resistance against climate- related catastrophic events. Figure 5: Salinity Intrusion Trend Over Time Integration of Precision Agriculture Precision agriculture tools created better opportunities to examine both field composition and its unique difficulties. Image data from UAV systems and IoT sensors demonstrated the existence of major variations in soil nutritional content which enabled the implementation of Variable-Rate Technology (VRT) to use resources efficiently. The analysis of aerial imagery from UAVs found pest-infected areas to cover 12–15% of all cultivated field areas thus helping farmers to respond quickly and protect their crops better. Figure 6: Pest-Affected Area in Northwest Region CONCLUSION The study confirms how Remote Sensing and Geographic Information Systems (GIS) combined with Precision Agriculture create substantial changes which resolve agricultural sustainability problems and climate adaptation needs mostly in climate-sensitive circumstances like Bangladesh. This research utilized Sentinel-2 along with Landsat and MODIS satellites in conjunction with GIS-based methods to monitor vital vegetation patterns alongside water stress and land-use alterations that occurred in different agricultural zones. People achieved better crop production rates through localized intervention solutions developed by combining UAV imaging systems with live IoT sensors. The main research findings demonstrate significant success in sustainable farming because farmers experience 25% less water and fertilizer usage and obtain more accurate yield prediction through early stress detection systems by 18%. Researchers utilized the study findings to chart areas at high risk of droughts floods and salinity intrusions which Pa ge 36 https://journals.e-palli.com/home/index.php/ajsts Am. J. Smart. Technol. Solutions 4(1) 30-36, 2025 then received specific prevention strategies. The obtained results validate technology and site-based methodologies for improving resource management while minimizing environmental harm and climate adaptation performance. Large-scale adoption of these achievements faces obstacles because farmers cannot easily obtain high- resolution data and solutions cost high amounts and many farmers remain unaware of using these technologies. The complete achievement of integrated approaches requires solving essential challenges by developing capacity programs and affordable technology while obtaining policy support. 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