American Journal of Applied Science and Technology
12
https://theusajournals.com/index.php/ajast
VOLUME
Vol.05 Issue 05 2025
PAGE NO.
12-15
10.37547/ajast/Volume05Issue05-04
Using GIS And Remote Sensing in Assessing the Impact
of Drought on Forest Cover Changes Around the Aral Sea
Asiya Tureniyazova
PhD, Head of Computer Engineering Department, Nukus State Technical University, Uzbekistan
Timur Berdimbetov
PhD, Dean of Computer Science Faculty, Nukus State Technical University, Uzbekistan
Karimullaeva Ayzada
2nd-year master's student in Computer Engineering specialty, Nukus State Technical University, Uzbekistan
Received:
08 March 2025;
Accepted:
05 April 2025;
Published:
07 May 2025
Abstract:
The Aral Sea region has experienced significant ecological changes due to prolonged droughts and
unsustainable water use, resulting in the degradation of forest ecosystems. This study utilizes Geographic
Information Systems (GIS) and remote sensing techniques to analyze the impact of drought on forest cover changes
from 2000 to 2024. Using satellite imagery (Landsat and Sentinel-2) and climate indicators such as the Standardized
Precipitation Index (SPI), temporal and spatial trends in vegetation health and forest loss were assessed. The
findings reveal a strong correlation between increasing drought severity and the decline of forest cover, particularly
in the Amu Darya delta and surrounding areas. The study underscores the importance of integrating high-resolution
satellite monitoring with adaptive forest management strategies to mitigate the effects of environmental
degradation in arid regions.
Keywords:
Aral Sea, drought, forest degradation, GIS, remote sensing, NDVI, SPI, vegetation monitoring,
environmental change, climate impact.
Introduction:
Over the past several decades, the Aral Sea region has
undergone dramatic environmental changes. Once
the world’s fourth
-largest inland lake, the Aral Sea has
now shrunk to a fraction of its original size. This
transformation has not only affected water
availability but also significantly altered surrounding
ecosystems
—
particularly forested areas. As a result,
the need to assess environmental degradation has
become more urgent than ever [2, 471].
Consequently,
understanding
the
relationship
between drought and forest cover change is essential
for developing effective mitigation and adaptation
strategies. To this end, Geographic Information
Systems (GIS) and remote sensing (RS) offer valuable
tools for analyzing large-scale environmental changes
across time and space. Through these methods, it
becomes possible to observe, quantify, and predict
forest loss patterns in relation to climatic variables [3,
445-453].
Droughts have become more frequent and severe in
Central Asia, largely due to climate change and
unsustainable water management practices. As a
result, forest ecosystems that once thrived near the
Aral Sea
—
such as tugai and saxaul forests
—
are now
under significant threat.
In particular, forests located in the Amu Darya delta
have shown marked signs of stress due to diminishing
water flow. Moreover, without seasonal flooding,
these ecosystems lose their natural replenishment
cycles, leading to soil salinization, tree mortality, and
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American Journal of Applied Science and Technology (ISSN: 2771-2745)
increased desertification [5, 40-55].
In order to analyze the impact of drought on forest
cover, satellite imagery from 2000 to 2024 was
utilized. Specifically, data from Landsat (5, 7, 8, 9) and
Sentinel-2 satellites were used to calculate vegetation
indices such as NDVI. Meanwhile, climatic data was
analyzed using the Standardized Precipitation Index
(SPI), allowing the identification of drought periods.
Additionally, GIS tools were used to classify and map
forest cover across different time periods. This
approach allowed for both temporal and spatial
analysis, revealing long-term patterns and hotspots of
degradation.
Table 1. Remote Sensing Datasets Used in the Study
Sensor
Spatial
Resolution
Temporal
Coverage
Purpose
Landsat 5 TM
30 m
2000–2011
Historical forest monitoring
Landsat
8
OLI
30 m
2013–2024
Current land cover analysis
Sentinel-2
MSI
10 m
2015–2024
High-resolution
vegetation
detection
Temporal Coverage: The data spans 24 years (2000
–
2024), allowing for long-term trend analysis of
vegetation and forest cover.
Resolution: Sentinel-2, with its 10 m resolution, is
especially valuable for detecting finer-scale changes
in vegetation that older sensors (like Landsat 5) might
miss.
Complementary Use: Landsat is useful for historical
trends, while Sentinel-2 provides detailed, recent
snapshots
—
together they offer a robust multi-
resolution dataset.
Purpose-Driven Selection: The sensors were chosen
with specific objectives in mind
—
namely, change
detection and vegetation health monitoring
—
which
supports a methodologically sound approach.
The variety and continuity of satellite data ensure
high reliability of the study’s fi
ndings and enable the
detection of both gradual and abrupt changes in
forest dynamics over time.
Over the 24-year period, the region experienced a
sharp decline in forest cover. For instance, the Amu
Darya delta, which had 12,500 hectares of forest in
2000, now retains less than 6,500 hectares. This
represents a reduction of nearly 50%, directly
correlating with periods of extended drought.
Figure 1. SPI Trends Indicating Drought Severity (2000–2024)
American Journal of Applied Science and Technology
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American Journal of Applied Science and Technology (ISSN: 2771-2745)
This graph shows increasing frequency and intensity
of droughts over the study period.
This graph highlights years with drought conditions
(SPI < 0), helping to visually connect drought severity
with forest degradation in the Aral Sea region.
Table 2. Forest Cover Change in Key Ecological Zones
Ecological Zone
Forest Area 2000
(ha)
Forest Area 2024
(ha)
%
Change
Amu Darya Delta
12,500
6,200
-50.4%
Moynaq Plateau
4,800
2,300
-52.1%
Ustyurt
Plateau
(South)
2,100
1,400
-33.3%
Amu Darya Delta: Once the richest in forest cover, it
experienced the most significant absolute loss (6,300
ha), likely due to its reliance on riverine flooding,
which has drastically declined.
Moynaq Plateau: The highest relative loss (-52.1%)
suggests high vulnerability to both drought and
anthropogenic pressures (e.g., livestock grazing,
fuelwood collection).
Ustyurt Plateau (South): Although still affected, this
zone showed the smallest loss in percentage, possibly
due to its native drought-adapted saxaul forests,
indicating slightly better resilience.
All zones show severe degradation, but varying
degrees of loss highlight differences in local
hydrology, vegetation type, and exposure to human
activity. These patterns support the need for zone-
specific conservation strategies.
It is evident that drought plays a central role in forest
degradation. Not only does it limit soil moisture and
groundwater levels, but it also weakens tree
resilience, making them more susceptible to pests,
fires, and human disturbance. Moreover, the SPI
analysis confirms an increase in both the frequency
and intensity of droughts since 2000.
Figure 2. NDVI Trends Showing Vegetation Decline (2000–2024)
NDVI values have steadily declined, especially during severe drought years, indicating loss of vegetation
health.
American Journal of Applied Science and Technology
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American Journal of Applied Science and Technology (ISSN: 2771-2745)
The chart illustrates a gradual decline in vegetation
health over time, with noticeable dips during drought
years
—
reinforcing the connection between drought
intensity and forest degradation.
In addition to temporal changes, GIS analysis
highlighted distinct spatial patterns. Specifically,
forests near the deltas and lakebeds showed the
highest rates of loss. On the other hand, upland
saxaul forests were relatively more stable, though not
immune to long-term degradation.
Given the extent of degradation, immediate
interventions are necessary. Firstly, drought-tolerant
reforestation strategies must be implemented,
focusing on native species like Haloxylon and Tamarix.
Secondly, water management must be improved to
simulate natural flood regimes in deltas.
Furthermore, integrating satellite monitoring with
local
ecological
surveys
can
enhance
the
effectiveness of restoration projects. This would
ensure that changes are tracked continuously,
allowing for adaptive management.
CONCLUSION
In conclusion, the combined use of GIS and remote
sensing provides a powerful and efficient means of
analyzing drought-induced forest loss in the Aral Sea
region. Through detailed temporal and spatial data, it
becomes possible to understand patterns of
degradation and to support sustainable restoration
efforts.
Ultimately,
such
technologies
are
indispensable for responding to the environmental
challenges of a drying world.
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