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CARBON-AWARE TREE MANAGEMENT BY INTEGRATING AI AND REMOTE SENSING TO MINIMIZE GREENHOUSE GAS EMISSIONS WITH ENHANCED TREE PRODUCTIVITY IN VULNERABLE CLIMATE-SENSITIVE AGROFORESTRY ECOSYSTEMS

Domaine:

agricultureclimate
Créateur:
Researcher
Éditeur:
Dr.
Éditeur:
Zenodo
Hôte:avatar
Climate change poses an acute threat to agroforestry ecosystems, particularly in vulnerable, climate-sensitive regions. Integrating artificial intelligence (AI) with remote sensing offers a transformative approach to carbon-aware tree management, enabling optimized resource allocation, predictive modeling, and greenhouse gas (GHG) monitoring. This paper presents a strategic framework combining AI and satellite-based technologies for precision tree productivity enhancement while minimizing emissions. The system evaluates carbon sequestration potential, detects degradation patterns, and facilitates real-time ecological interventions. Results underscore significant emission reductions and productivity gains compared to traditional practices, highlighting the role of digital intelligence in sustainable land use and climate resilience.

Tags

optimized resource allocation, predictive modeling, sustainable land use, carbon sequestration potential, Climate Resilience

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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