Big Data Analytics for Climate and Human Impacts on Terrestrial Ecosystems

Dear Colleagues,

Terrestrial ecosystems worldwide face pressure from both climate change and human activities, demanding precise monitoring and mechanistic understanding through advanced remote sensing technologies. This Topic focuses on cutting-edge applications of remote sensing in unraveling ecosystem responses to climate warming, extreme events, and land-use changes while quantifying the ecological effects of anthropogenic activities (e.g., urbanization, agricultural intensification, and deforestation). By integrating multi-source remote sensing and high-throughput sequencing data (including satellites, UAVs, and in situ sensors) with ecological modeling, we aim to establish dynamic assessment frameworks spanning local to global scales, providing scientific support for sustainable ecosystem management and climate adaptation strategies.

With breakthroughs in next-generation remote sensing technologies (e.g., high-spatiotemporal-resolution sensors and AI-driven data analytics), this Topic encourages interdisciplinary research that bridges climate science, ecology, geospatial science, and socioeconomics. We welcome innovative methodologies, case studies, and theoretical advances across diverse ecosystems (including forests, grasslands, wetlands, and croplands), emphasizing synergy between technological innovation, mechanism discovery, and policy implementation to transform remote sensing from an observational tool into a decision-support system.

Four Key Themes and Subtopics

1. Ecosystem Dynamics via Multi-Scale Data Fusion:
   
   • Cross-sensor calibration for vegetation carbon–water flux inversion;
   • Biodiversity loss tracking using airborne LiDAR and eDNA metabarcoding;
   • AI-driven early warning systems for extreme climate events;
   • Data-model assimilation in ecosystem service prediction.
2. Climate Stressors: From Genomics to Geospatial Patterns:
   
   • Thermal stress impacts on plant phenomics via UAV-omics integration;
   • Permafrost methane flux modeling with ground-penetrating radar and microbial genomics;
   • Phenological mismatch analysis using satellite time-series and transcriptomics;
   • Ecological risk mapping in arctic–alpine transition zones.
3. Human Footprint Assessment through Data Convergence:
   
   • Urban sprawl impacts on microclimate and soil microbiomes;
   • Agricultural intensification effects on soil health, namely hyperspectral and metagenomic biomarkers;
   • Blockchain-enabled illegal logging detection with SAR and acoustic sensors;
   • Efficacy of ecological restoration via multi-temporal NDVI and functional trait analysis.
4. Next-Gen Methodologies for Ecosystem Informatics:
   
   • Graph neural networks for cross-domain data harmonization (remote sensing × omics);
   • Quantum computing applications in ecosystem scenario modeling;
   • Crowdsourced data validation platforms with blockchain traceability;
   • SDG-aligned decision systems integrating planetary boundary thresholds.

Prof. Dr. Qing Zhang
Dr. Qingfu Liu
Topic Editors