Publication2024
UAV Databased Temperature Patterns Analysis with Carbon Emission Detection Using Deep Neural Network
- Climate Action
- Partnerships for the Goals
- Thriving and Sustainable Economy
The record
- Type
- Publication
- Date
- 1 December 2024
- Level
- International — held abroad
- Journal
- Remote Sensing in Earth Systems Sciences
- Volume
- 7
- Issue
- 4
- Pages
- 512-523
- Published
- 1 December 2024
- DOI
- 10.1007/s41976-024-00143-x
- Scopus ID
- 85205395075
- ISSN
- 25208195
- Authors
- 7
- Open access
- No
- Citations
- 1
- International co-authorship
- Yes
- Co-author countries
- IN, MY
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
13 Take urgent action to combat climate change and its impacts
UAV-based deep learning for temperature pattern analysis and carbon emission detection achieves 96% accuracy, supporting climate change monitoring and quantification of environmental impact.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-2 Thriving and Sustainable Economy
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 13 label. UAV-based deep learning for temperature pattern analysis and carbon emission detection achieves 96% accuracy, supporting climate change monitoring and quantification of environmental impact.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “UAV Databased Temperature Patterns Analysis with Carbon Emission Detection Using Deep Neural Network”. Kortex.