Mobile-based image interpretation and geotagging using artificial intelligence and open-source geospatial technology

Paul, Arati; Chauhan, Sakshi; Dutta, Dibyendu

doi:10.1007/s12518-023-00522-x

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Cited by 4 publications

References 28 publications

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Spectral Feature Extraction Using Pooling

Paul,

Chaki

2023

Dimensionality Reduction of Hyperspectral Imagery

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Spectral Feature Extraction Using Pooling

Paul,

Chaki

2023

Dimensionality Reduction of Hyperspectral Imagery

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Concluding Remarks and Way Forward

Paul,

Chaki

2023

Dimensionality Reduction of Hyperspectral Imagery

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Improving the role of communities in participatory forest management through artificial intelligence: the case of Nairobi city park community forest association

Chisika,

Yeom

2024

int. forest. rev.

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The integration of artificial intelligence (AI) into participatory forest management (PFM) is emerging as a promising strategy for promoting sustainable forest management in developing countries. Using a case study approach from Kenya involving 85 respondents from the Nairobi City Park Community Forest Association, this study explored the potential for AI implementation in PFM to improve community roles in data acquisition and management. The study results show that the current data management system for executing community roles in PFM is inefficient, time-consuming, and susceptible to errors. However, there are substantial gains and opportunities in implementing community roles through AI. AI utilization could be fostered through the existing Information Communication Technology (ICT) resources such as smartphones for efficient and transparent data processes. Notably, 90% of respondents express confidence in AI’s potential to enhance PFM efficiency. Despite this optimism, 67.1% emphasize the necessity of a comprehensive AI policy that emphasizes continuous community engagement and adaptation of AI to local contexts.

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Mobile-based image interpretation and geotagging using artificial intelligence and open-source geospatial technology

Cited by 4 publications

References 28 publications

Spectral Feature Extraction Using Pooling

Spectral Feature Extraction Using Pooling

Concluding Remarks and Way Forward

Improving the role of communities in participatory forest management through artificial intelligence: the case of Nairobi city park community forest association

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