Gemini 2.0 Deep Research just came out. Deep Research is means that the LLM will do a long (5-10 min) web crawl researching the topic of your choice and summarize the finding in a report. Free users get up to 10, I think, reports per month.
You can access DR here - use the drop down box to pick the model with Deep Research.
Here are the results for the following prompt:
Analyze recent (last 5 years) research themes in remote sensing. Where do you see large unaddressed gaps that could benefit from more attention, either for scientific reasons to analyze interesting phenomena or due to practical demands? Suggest some realistic sample paper titles and abstracts that could start to address these gaps (avoiding overly broad “let’s model all the ecosystems” ideas).
The resulting report is not as deep as this topic deserves, but it’s not obviously wrong. It hits many important points - ML, new sensors, data fusion, novel applications. It’s a bit too technical, but you can ask Gemini to tune it for a different audience.
“Specific Gaps in Application Domains” are interesting to read, though why specifically “precision olive growing” got top billing is a bit of a mystery.
Some paper titles proposed there to address research gaps:
1. Spatial Characteristics and Modeling
Sample Paper Title: “Mapping Fine-Scale Urban Green Space Connectivity Using High-Resolution Satellite Imagery and Network Analysis.”
2. Temporal Dynamics and Forecasting
Sample Paper Title: “Forecasting Short-Term Changes in Coastal Water Quality Using High-Frequency Satellite Data and Time Series Analysis.”
3. Spatiotemporal Change and Impact Assessment
Sample Paper Title: “Spatiotemporal Dynamics of Wildfire Impacts on Forest Structure and Composition: A Multi-Sensor Remote Sensing Approach.”
4. Interventions and Management Strategies
Sample Paper Title: “Evaluating the Effectiveness of Reforestation Efforts Using Time-Series Satellite Imagery and Change Detection Analysis.”
5. Risk and Opportunity Assessment
Sample Paper Title: “Mapping Urban Heat Island Intensity and Vulnerability Using Thermal Remote Sensing and Socioeconomic Data.”
6. Future Evolution and Predictive Modeling
Sample Paper Title: “Predicting the Future Distribution of Invasive Plant Species Under Climate Change Scenarios Using Species Distribution Models and Remote Sensing Data.”
7. Generalizability and Contextual Adaptation
Sample Paper Title: “Adapting Machine Learning Models for Crop Type Classification Across Diverse Agricultural Landscapes and Satellite Sensors.”
8. Ethical Considerations in Remote Sensing
Sample Paper Title: “Navigating the Ethical Landscape of AI-Powered Remote Sensing: Implications for Privacy and Data Security.”
9. Improving Methodology for Complex Ecological Interactions
Sample Paper Title: “Integrating Agent-Based Modeling with Remote Sensing Data to Simulate Forest Ecosystem Dynamics Under Climate Change.”
10. Enhancing Data Fusion for Subsurface Analysis
Sample Paper Title: “Multi-Modal Fusion of Airborne Electromagnetic and Hyperspectral Data for Enhanced Subsurface Geological Mapping.”
This is just a brief example that in our new LLM-enhanced world it’s easier than ever to get a broad, if not very deep, overview of a topic. The frontier models know some of this out of the box already, but Deep Research provides them with more grounding.
Try researching another topic that you know well (or that you don’t but are curious about) and post the results! I’m curious what works and what doesn’t.
