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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 



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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 



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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 
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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



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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 



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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 



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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. The study results establish a solid design 
that enables policymakers along with researchers and 
practitioners to promote climate-smart agriculture in 
Bangladesh for ensuring future food security together 
with climate resilience.

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