Andsera Adugna Mekonen | Climate Change Mitigation | Women Researcher Award Published on 14/11/202514/11/2025 by Environmental Scientists Mrs. Andsera Adugna Mekonen | Climate Change Mitigation | Women Researcher Award Mrs. Andsera Adugna Mekonen | University of Naples | Italy Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.