The workflow developed can be applied to other regions and spatial scales
Research gap analysis derived from 3 earth_science papers in our local library.
The gap
The workflow developed can be applied to other regions and spatial scales. The methodology can be adapted to incorporate higher-resolution climate model outputs. The datasets can be used for further scientific analyses and integration into subsequent modelling workflows.
Evidence profile
Sourced from the future-work section and inline gaps and stated challenges of the source papers, classified as general, spanning 2 journals.
Research trend
Established — well-defined area with open sub-problems.
Supporting evidence — 3 representative gaps
- PROTECT BALTIC - Deliverable 3.8 - Estimates for future abiotic conditions under climate change (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi
The workflow developed can be applied to other regions and spatial scales. The methodology can be adapted to incorporate higher-resolution climate model outputs. The datasets can be used for further scientific analyses and integration into subsequent modelling workflows.
generalfuture-work sectionevidence 5/5Keywords: workflow developed applied other regions spatial scales methodology - Conceptual Framework for AI-Based Prediction of Climate Change Impact on Plant Growth (2026) · Zenodo (CERN European Organization for Nuclear Research) · doi
Future research may focus on integrating predictive models with remote sensing technologies and geographic information systems (GIS). Future research should focus on implementing the proposed framework using large-scale climatic datasets, integrating remote sensing technologies and developing region-specific predictive models.
generalinline gapsevidence 5/5Keywords: future focus integrating predictive models remote sensing technologies geographic information systems implementing proposed framework using - GIS-Integrated Machine Learning for Wildfire Susceptibility Mapping Under Temperature Increase Scenarios: A Bayesian-Optimized ANN Approach (2026) · ISPRS International Journal of Geo-Information · doi
The complexity of integrating multi-source geospatial data within a GIS environment. The challenge of developing a spatially explicit framework for proactive mitigation and climate-resilient land-use planning. The limitation of using historical forest fire data to predict future wildfire susceptibility.
generalstated challengesevidence 5/5Keywords: complexity integrating multi-source geospatial data within gis environment
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