The study, published in 2026 in the International Journal of Sustainable Applied Sciences (IJSAS), analyzed a decade of scientific literature to identify how remote sensing technologies have evolved and which innovations are shaping the future of disaster recovery. The findings are significant as climate change continues to increase the frequency and intensity of floods, wildfires, landslides, earthquakes, and other environmental disasters around the world.
Growing Demand for Faster Disaster Assessment
Environmental damage assessment is one of the most critical stages of disaster recovery. Governments, humanitarian agencies, and environmental managers rely on accurate information to identify affected areas, prioritize interventions, and restore ecosystems efficiently.
Traditional field surveys often require substantial time, financial resources, and personnel. Remote sensing technologies, including satellites, drones, radar, and airborne sensors, offer a faster alternative by providing large-scale observations of damaged landscapes.
According to the authors, the growing need for rapid and data-driven decision-making has accelerated global research on remote sensing applications in disaster management.
Mapping a Decade of Scientific Research
To understand this technological transformation, the researchers conducted a bibliometric analysis of 329 peer-reviewed journal articles indexed in Scopus between 2016 and 2025.
The study followed the internationally recognized PRISMA literature-review framework and used Biblioshiny and VOSviewer software to analyze publication trends, research networks, country contributions, and emerging scientific themes.
The dataset was selected from research focusing on remote sensing technologies used for environmental and ecosystem damage assessment following disasters, including floods, earthquakes, landslides, forest fires, and other ecological crises.
Scientific Publications Are Rising Rapidly
One of the clearest findings is the rapid growth of research activity in this field.
Between 2016 and 2019, annual publication output remained relatively stable, averaging around 12 articles per year. The trend changed dramatically after 2020, when global concern over climate-related disasters intensified.
By 2025, annual publication output had reached 75 scientific articles, representing the highest level recorded during the study period.
The authors attribute this growth to increasing global awareness of environmental vulnerability and the need for more effective disaster response technologies.
China, the United States, and India Lead Global Research
The study found that countries with strong space technology capabilities dominate research on post-disaster remote sensing.
The leading contributors were:
- China: 93 publications
- United States: 45 publications
- India: 37 publications
These countries benefit from advanced Earth-observation satellite programs, extensive research funding, and significant exposure to natural disasters.
Meanwhile, Japan demonstrated the highest level of international collaboration. Nearly half of its publications involved cross-border research partnerships, highlighting the importance of global cooperation in transferring disaster-management technologies to vulnerable regions.
Three Technologies Are Driving the Field
The analysis identified three major technological pillars that currently define post-disaster ecological assessment.
1. Optical Satellites for Large-Scale Environmental Monitoring
The first pillar involves optical satellite systems that monitor environmental conditions across extensive geographic areas.
These satellites are widely used to detect burned forests, vegetation loss, land-cover changes, and flood impacts. Vegetation indices such as NDVI help researchers evaluate ecosystem health and recovery over time.
Although cloud cover and weather conditions can limit optical imagery, the technology remains an essential foundation for regional environmental monitoring.
2. Artificial Intelligence and Drones for Automated Damage Detection
The second pillar represents the most significant technological shift identified in the study.
Unmanned Aerial Vehicles (UAVs), commonly known as drones, can capture highly detailed imagery of disaster zones. However, the enormous volume of collected data requires automated processing.
Artificial intelligence and machine-learning algorithms are increasingly used to identify damaged infrastructure, classify affected vegetation, detect landslides, and analyze flood impacts automatically.
The researchers found that AI-related topics experienced rapid growth after 2023 and have become among the most influential trends in remote sensing research.
As the authors note, the field is moving away from manual visual interpretation and toward automated systems capable of delivering near real-time assessments.
3. Radar and LiDAR for Extreme Conditions
The third pillar focuses on active sensing technologies such as Synthetic Aperture Radar (SAR) and LiDAR.
Unlike optical satellites, radar systems can operate through clouds, heavy rain, and darkness. This capability makes them especially valuable during the critical hours immediately after a disaster.
The study highlights the growing use of Sentinel-1 radar satellites for detecting ground deformation after earthquakes and monitoring flood extent with high accuracy.
LiDAR technology adds another dimension by producing detailed three-dimensional representations of terrain changes. When combined with artificial intelligence, LiDAR can help identify unstable slopes and potential landslide zones before secondary disasters occur.
From Observation to Prediction
Perhaps the most important conclusion of the study is the ongoing transition from observation-based disaster assessment to predictive analytics.
Remote sensing is no longer limited to documenting environmental damage after a disaster occurs. Instead, integrated systems that combine satellite imagery, drones, radar, LiDAR, and artificial intelligence are increasingly being used to support forecasting, risk assessment, and proactive decision-making.
The researchers argue that future disaster-management systems should integrate multiple sensor platforms with hybrid analytical algorithms to improve accuracy and reduce dependence on field surveys.
At the same time, they emphasize that artificial intelligence models still require rigorous field validation to ensure that automated interpretations accurately reflect real-world conditions.
Implications for Policymakers and Disaster Management Agencies
The findings have important implications for governments and disaster-response organizations worldwide.
As climate-related disasters become more frequent, investments in geospatial technologies can help authorities respond more quickly, allocate resources more efficiently, and improve ecosystem restoration efforts.
According to Prayudha and colleagues from the Indonesian Defense University and the Geospatial Information Agency, the future of disaster resilience will depend on integrated spatial data infrastructures, open-access geospatial information, and stronger international collaboration in technology development and transfer.
Their analysis suggests that countries vulnerable to environmental disasters should prioritize adopting AI-assisted remote sensing systems to strengthen preparedness and recovery capabilities.
Author Profiles
Raffy Bagus Prayudha is a researcher affiliated with the Indonesian Defense University (Universitas Pertahanan Republik Indonesia), Sentul, Bogor, West Java, Indonesia. His expertise includes remote sensing, geospatial technologies, environmental monitoring, and disaster management.
Trismadi is a researcher affiliated with the Indonesian Defense University (Universitas Pertahanan Republik Indonesia), Sentul, Bogor, West Java, Indonesia
Syachrul Arief is a researcher affiliated with the Indonesian Defense University (Universitas Pertahanan Republik Indonesia), Sentul, Bogor, West Java, Indonesia
Source
Article Title: Mapping the Evolution of Remote Sensing Technologies in Post-Disaster Ecological Assessment: A Bibliometric Analysis
Authors: Raffy Bagus Prayudha, Trismadi, and Syachrul Arief
Journal: International Journal of Sustainable Applied Sciences (IJSAS)
Year: 2026
Volume and Pages: Vol. 4, No. 6, pp. 427–444
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