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Correction to: Navigating tensions in climate change-related planned relocation

Ambio 2024年第9期53卷 1267-1268页

作者： Giovanna Gini Annah Piggott-McKellar Hanne Wiegel Friedrich Nikolaus Neu Ann-Christine Link Claudia Fry Tammy Tabe Olumuyiwa Adegun Cheikh Tidiane Wade Erica Rose Bower Sarah Koeltzow Rachel Harrington-Abrams Carolien Jacobs Kees van der Geest Narjes Zivdar Ryan Alaniz Carolyne Cherop David Durand-Delacre Melanie Pill Himanshu Shekhar Olivia Yates Md Abdul Awal Khan Frank Kwesi Nansam-Aggrey Lauren Grant Danang Aditya Nizar Kwame Nitri Owusu-Daaku Alberto Preato Oana Stefancu Merewalesi Yee School of Geography and the Environment University of Oxford Oxford UK. South American Network for Environmental Migrations (RESAMA) São Paulo Brazil. School of Architecture and Built Environment Queensland University of Technology Brisbane Australia. a.piggottmckellar@qut.edu.au. Geography Earth and Atmospheric Sciences Melbourne University Parkville Australia. a.piggottmckellar@qut.edu.au. Environmental Policy Group and the Sociology of Development and Change Group Wageningen University Wageningen The Netherlands. Chair Group of Geography of Global Change Institute of Environmental Social Sciences and Geography University of Freiburg Freiburg Germany. Department of Social Inquiry La Trobe University Melbourne Australia. United Nations University Institute for Environment and Human Security Bonn Germany. Department of Geography Philipps-Universität Marburg Marburg Germany. Department of Geography University of Exeter Exeter UK. Research Program East-West Centre Honolulu HI USA. Department of Architecture Federal University of Technology Akure Nigeria. School of Architecture and Planning University of the Witwatersrand Johannesburg South Africa. Department of Geography Assane Seck University Ziguinchor Senegal. Doerr School of Sustainability Stanford University Palo Alto CA USA. Platform On Disaster Displacement Secretariat Geneva Switzerland. Department of Geography King's College London London UK. Van Vollenhoven Institute for Law Governance and Society Leiden University Leiden The Netherlands. United Nations High Commissioner for Refugees UNHCR Tehran Iran. Social Sciences Department Cal Poly State University San Luis Obispo CA USA. Climate Desk Parliament of Kenya Nairobi Kenya. Indo-Pacific Development Centre Lowy Institute Sydney Australia. School of Psychology The University of Auckland Auckland New Zealand. Department of Law Independent University Bangladesh Dhaka Bangladesh. Climate Change Department National Disaster Management

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Washington’s ClimeTime: Collaboration and Capacity-Building to Foster Climate Learning Across a State Network

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Connected Science Learning 2024年第4期6卷

作者： Ellen Ebert Johanna Brown Elizabeth Schmitz Deb L. Morrison Philip Bell Cheryl Lydon Luke Matlack a Director of Secondary Education Office of the Superintendent of Public Instruction Olympia WA b Associate Director of Secondary Science Office of the Superintendent of Public Instruction Olympia WA c Program Supervisor Environment and Sustainability Education Office of the Superintendent of Public Instruction Olympia WA d Learning Scientist Institute of Science and Math Education College of Education University of Washington Seattle WA e Professor Learning Sciences & Human Development College of Education University of Washington Seattle WA f Program Manager STEM Puget Sound Educational Service District Renton WA g Regional Science Coordinator Educational Service District 105 Yakima WA

Washington State’s ClimeTime Network is a groundbreaking effort that has been implementing systemic capacity-building around climate science learning, as well as broader scientific literacy, for the past 6 years. This article provides an overview of the ClimeTime Network formation, framing, and implementation strengths and challenges. Additionally, the core commitments that help guide ongoing implementation efforts are detailed. The organization of the network’s ongoing operations are described and further guidance is provided to help others who are engaging in emerging systemic efforts to support climate change education and the required *** AbstractDisplay full size

关键词： Climate science climate change education climate learning professional development networks science learning community-connected learning equity in education

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Urban Trees Mapping Using Multi-Scale Rgb Image and Deep Learning Vision Transformer-Based

SSRN

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SSRN 2022年

作者： Gomes, Felipe David Georges Furuya, Michelle Taís Garcia Junior, José Marcato Gonçalves, Diogo Nunes Martins, José Augusto Correa Silva, Paulo Antonio Gonçalves, Wesley Nunes Osco, Lucas Prado Ramos, Ana Paula Marques Program of Environment and Regional Development University of Western São Paulo Raposo Tavares km 572SP Presidente Prudente19067-175 Brazil Program of Agronomy University of Western São Paulo Raposo Tavares km 572SP Presidente Prudente19067-175 Brazil Faculty of Engineering and Architecture and Urbanism University of Western São Paulo Raposo Tavares km 572SP Presidente Prudente19067-175 Brazil Federal University of Rio de Janeiro Rua Athos da Silveira Ramos 274RJ Rio de Janeiro21941-916 Brazil Faculty of Computing Federal University of Mato Grosso do Sul Av. Costa e SilvaMS Campo Grande79070-900 Brazil Faculty of Engineering Architecture and Urbanism and Geography Federal University of Mato Grosso do Sul Av. Costa e Silva Campo Grande79070-900 MS Brazil

Despite the fact that deep neural networks performed well in arboreous urban vegetation semantic segmentation, they fell short of expectations. As a result, we evaluate the performance of SegFormer, a vision transformer-based deep learning. We compare the evaluation metrics of SegFormer with the deep learning architecture DeepLabv3+. Two sets of image data, each having a different GSD, were employed (0.2 m and 0.5 m). In the semantic segmentation of tree vegetation in urban environments the SegFormer outperforms the state-of-the-art convolutional neural network, proving its capacity to map urban forests in RGB pictures. The SegFormer reported the best results including when we combined the different GSDs to train the model, which proved to be just as effective as training and testing with only the 0.20 m GSD. © 2022, The Authors. All rights reserved.

关键词： Remote sensing

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Experimental evidence for a universal threshold characterizing wave-induced sea ice break-up

arXiv

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arXiv 2020年

作者： Voermans, J.J. Rabault, J. Filchuk, K. Ryzhov, I. Heil, P. Marchenko, A. Collins, C. Dabboor, M. Sutherland, G. Babanin, A.V. University of Melbourne Australia Norwegian Meteorological Institute Norway University of Oslo Norway Arctic and Antarctic Research Institute Russia Australian Antarctic Division Australian Antarctic Program Partnership University of Tasmania Australia University Centre in Svalbard Norway U.S. Army Engineering Research and Development Center United States Environment and Climate Change Canada Canada Laboratory for Regional Oceanography and Numerical Modeling National Laboratory for Marine Science and Technology Qingdao China

Waves can drastically transform a sea ice cover by inducing break-up over vast distances in the course of a few hours. However, relatively few detailed studies have described this phenomenon in a quantitative manner, and the process of sea ice break-up by waves needs to be further parameterized and verified before it can be reliably included in forecasting models. In the present work, we discuss sea ice break-up parameterization and demonstrate the existence of an observational threshold separating breaking and non-breaking cases. This threshold is based on information from two recent field campaigns, supplemented with existing observations of sea ice break-up. The data used cover a wide range of scales, from laboratory-grown sea ice to polar field observations. Remarkably, we show that both field and laboratory observations tend to converge to a single quantitative threshold at which the wave-induced sea ice break-up takes place, which opens a promising avenue for robust parametrization in operational forecasting models. Copyright © 2020, The Authors. All rights reserved.

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Sustainable river management: Land use, building coverage, and infrastructure typology of the riverbanks

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IOP Conference Series. Earth and environmental Science 2020年第1期447卷

作者： Rini, E F Rahayu, P Sinniah, G K Urban and Regional Planning Program Faculty of Engineering Universitas Sebelas Maret Jl. Ir. Sutami No.36 A Surakarta Indonesia Regional Development Information Center Institute for Research and Community Service Universitas Sebelas Maret Surakarta 57126 Indonesia Department of Urban & Regional Planning Faculty of Built Environment UniversitiTeknologi Malaysia 81310 Skudai Johor Malaysia

Surakarta City is intersected by three major rivers which could become the city’s source of clean water. However, pollution of the rivers makes processing this surface water a necessity to create clean water for domestic uses. This study aims to establish a river typology based on the riverbank characteristics and the potential of the surface water to be discharge into clean water. This paper uses spatial analysis to develop typologies and describe the riverbanks characteristics by using the Pepe River in Surakarta as a case study. This is one of the polluted major rivers that flow through Surakarta City. The study found that the Pepe’s riverbanks are dominated by residential and commercial areas. Due to the lack of waste infrastructure, the community (household and small-scale industries) disposes its untreated wastewater directly into the drainage channel. With regard to this problem, five river typologies were established to function as the basis of recommendations to improve the water quality of the river so that it can be used as an urban clean water source. The result shows that all typologies major problems are the lack of wastewater management. The study proposes interventions in waste management, wastewater treatment system, and land use control.

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Land, Climate, Energy, Agriculture and development in the Sahel: Synthesis Paper of Case Studies under the Sudano-Sahelian Initiative for regional development, Jobs, and Food Security

SSRN

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SSRN 2021年

作者： Mirzabaev, Alisher Sakketa, Tekalign Gutu Sylla, Mouhamadou Bamba Dimobe, Kangbéni Sanfo, Safietou Admassie, Assefa Abebaw, Degnet Coulibaly, Ousmane Nafolo Rabani, Adamou Ibrahim, Boubacar Bokaney, Abdou Latif Seyni, Abdoul Aziz Idrissa, Mamoudou Olayide, Olawale Emmanuel Faye, Amy Dièye, Mohamadou Diakhaté, Pape Bilal Bèye, Assane Sall, Moussa Diop, Mbaye Osman, Abdelrahman Khidir Ali, Adil M. Garba, Issa Baumüller, Heike Ouedraogo, Souleymane von Braun, Joachim University of Bonn Genscherallee 3 Bonn53113 Germany AIMS Rwanda Kigali Rwanda B.P. 176 Dédougou Burkina Faso WASCAL Competence Centre Ouagadougou Burkina Faso Addis Ababa University College of Business and Economics Addis Ababa Ethiopia Independent Researcher Addis Ababa Ethiopia Bamako Mali Faculté des Sciences et Techniques Université Abdou Moumouni Niamey Niger WASCAL Research Program Climate Change and Energy University Abdou Moumouni Niamey Niger Ministère de l’environnement de la Salubrité Urbaine et du Développement Durable Niamey Niger Cabinet du Premier Ministre Niamey Niger Centre for Sustainable Development Faculty of Multidisciplinary Studies University of Ibadan Ibadan Nigeria Senegalese Institute of Agricultural Research Route des hydrocarbures DakarBP 3120 Senegal University Cheikh Anta Diop of Dakar Dakar Senegal Sudanese Environment Conservation Society Khartoum Sudan Agrhymet Regional Centre Permanent Interstate Committee for drought control in the Sahel Boulevard de l’Universite BP 11011 Niamey Niger

This paper synthesizes a set of national case studies conducted in the Sahelian countries during 2019-2020 as a collaboration between national universities and research institutes, and the Center for development Research (ZEF), University of Bonn, with contributions from the Agrhymet regional Centre, Permanent Interstate Committee for Drought Control in the Sahel (CILSS). These case studies provide up-to-date knowledge and critical insights on the nexus of land degradation, climate change and energy in the Sahel. The current synthesis paper highlights their major findings and provides crosscutting and cross-regional analytical conclusions. First, the synthesis paper explores current trends in the Sahel region on land use and land degradation, energy use and supply, climate change projections and impacts, as well as their interactions and links to agricultural growth, food security, poverty reduction, and peace in the region. Second, technological, socio-economic and policy solutions at the nexus of land, water, energy and climate challenges that enable environmentally sustainable and socially inclusive rural development in the Sahel are discussed, including their interactions and implications for peace and stability in the region. The findings show that such socio-economic solutions as improving access to markets, strengthening social safety nets, increasing investments to transport and energy infrastructures, promoting land tenure security, expanding off-farm employment opportunities can greatly contribute to rural development in the Sahel, particularly by aiding climate change resilience and sustainable land management. Key technological innovations highlighted across the case studies include expanding irrigation and adopting water use efficient irrigation techniques, crop diversification, expanding agricultural mechanization, investing into restoring and rehabilitating degraded lands through reforestation, afforestation and agroforestry practices. The key lessons

关键词： regional planning

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A future for the world's children? A WHO–UNICEF–Lancet Commission

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The Lancet 2020年第10224期395卷 605-658页

作者： Clark, Helen Coll-Seck, Awa Marie Banerjee, Anshu Peterson, Stefan Dalglish, Sarah L Ameratunga, Shanthi Balabanova, Dina Bhan, Maharaj Kishan Bhutta, Zulfiqar A Borrazzo, John Claeson, Mariam Doherty, Tanya El-Jardali, Fadi George, Asha S Gichaga, Angela Gram, Lu Hipgrave, David B Kwamie, Aku Meng, Qingyue Mercer, Raúl Narain, Sunita Nsungwa-Sabiiti, Jesca Olumide, Adesola O Osrin, David Powell-Jackson, Timothy Rasanathan, Kumanan Rasul, Imran Reid, Papaarangi Requejo, Jennifer Rohde, Sarah S Rollins, Nigel Romedenne, Magali Singh Sachdev, Harshpal Saleh, Rana Shawar, Yusra R Shiffman, Jeremy Simon, Jonathon Sly, Peter D Stenberg, Karin Tomlinson, Mark Ved, Rajani R Costello, Anthony The Helen Clark Foundation Auckland New Zealand Partnership for Maternal Newborn & Child Health Geneva Switzerland Senegal Presidency Dakar Senegal Department of Maternal Newborn Child and Adolescent Health WHO Geneva Switzerland Department of Health Systems Governance and Financing WHO Geneva Switzerland Health Division HIV Data and Analytics Division UNICEF New York NY United States HIV Data and Analytics Division UNICEF New York NY United States Department of International Health Johns Hopkins School of Public Health Baltimore MD United States School of Population Health University of Auckland Auckland New Zealand Department of Global Health and Development London School of Hygiene and Tropical Medicine London United Kingdom Health Systems Transformation Platform Tata Trusts Mumbai India Centre for Global Child Health Hospital for Sick Children Toronto OT Canada Global Financing Facility World Bank Washington DC United States Health Systems Research Unit South African Medical Research Council Cape Town South Africa Department of Health Management and Policy Beirut Lebanon Knowledge to Policy Center American University of Beirut Beirut Lebanon School of Public Health University of Western Cape Bellville South Africa Financing Alliance for Health Nairobi Kenya Institute for Global Health London United Kingdom Department of Economics London United Kingdom University College London London United Kingdom Health Policy and Systems Research Consultant Accra Ghana China Center for Health Development Studies Peking University Beijing China Program of Social Sciences and Health Latin American School of Social Sciences Buenos Aires Argentina Centre for Science and Environment New Delhi India Department of Maternal and Child Health Uganda Ministry of Health Kampala Uganda Institute of Child Health University of Ibadan Ibadan Nigeria Department of Health Systems WHO Phnom Penh Cambodia West and Central Regional Office UNICEF Dakar Senegal P

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African leadership in brain diplomacy: The Yaoundé declaration advances the global brain economy playbook for better brain health

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Neuroscience 2025年 577卷 161-174页

作者： Njamnshi, Alfred Kongnyu Fame Ndongo, Jacques Ngoh Ngoh, Ferdinand Mbella Mbella, Lejeune Ghogomu, Paul M. Fouda, Séraphin M. Ondoa Obama, Marie-Thérèse A. Tchuinte, Madeleine Ousmane Mey, Alamine Manaouda, Malachie Beti Assomo, Joseph Sadi, René E. Motaze, Louis-Paul Nganou Djoumessi, Emmanuel Li Likeng, Minette Libom Nalova Lyonga, Pauline E. Etoundi Ngoa, Laurent S. Foutsou, Mounouna Mouelle Kombi, Narcisse Tchiroma, Bakary Issa Owona, Grégoire Ayissi, Henri Eyebe Balungeli, Confiance Ebune Hele, Pierre Fuh, Calistus G. Fomundam Mbah Acha, Rose N. Bidoung Kpwatt, Pierre I. Mbayu, Felix Tasong, Paul N. Momo, Jean de Dieu Doh, Jérôme P. Bayaola, Boniface Kilo, Vivian A. Abouem à Tchoyi, David Njeuma, Dorothy L. Tamfu, Simon F. Angwafo III, Fru F. Chumbow, Sammy B. Etoua, Remy M. Omgba, Richard L. Ngomo Manga, Horace Tsafack Nanfosso, Roger Chan, Andrew Etoa, François-Xavier Zambo, Joseph Marie B. Mah, Evelyn M. Tommo Monthe, Michel Eheth, Salomon Monono, Churchill Biffot, Paul P. Gabsa, Wilfred Cheka, Cosmas Echu, George Bella, Achille E. Njock, Louis Richard Fongod, Augustina G.N. Ndongo, Daniel U. Leke, Rose F.G. Pondi, Jean E. Fieggen, Graham Shehu, Bello B. Ayadi, Rym Merali, Zul Yusuf, Sadiq Apeagyei, Angela Esi Ranchod, Kirti Salama, Mohamed Atangana, Abdon Ngokeu, Eddy Ndifon, Wilfred Tiahou, Georges Tchoua, Romain Korsten, Lise Ibanez, Agustin Singh, Gagandeep Abdullah, Jafri M. Dhamija, Rajinder K. Ihunwo, Amadi O. Mbarika, Victor W.A. Mbah, David Njamnshi, Wepnyu Y. Ngarka, Leonard Ahidjo, Nene Njitung, Caleb Siewe Fodjo, Joseph N. Seke Etet, Paul F. Tsiagadigui, Jean Gustave Bissek, Anne-Cécile Z.K. Bella, Assumpta L. Mbanya, Jean Claude Ndjolo, Alexis Djientcheu, Vincent de Paul Ntone, Felicien E. Luma, Henry N. Mboudou, Emile Kasia, Jean Marie Leke, Robert J.I. Um Meka, Esther Ngo Ashuntantang, Gloria Ngaroua Bum, Elizabeth Ngo Njoya, Oudou Mbacham, Wilfred F. Ongolo-Zogo, Pierre Chabwine, Joelle N. Fongang, Bernard Vulliemoz, Serge Perrig, Stephen Sztajzel, Roman Annoni, Jean Marie Chakraborty, Sar Brain Research Africa Initiative (BRAIN) Cameroon & Geneva Switzerland Society of Cameroonian Neurologists (SCAN) The University of Yaoundé I Yaoundé Cameroon World Federation of Neurology Delegate for Cameroon Cameroon Office of the Minister of State Minister of Higher Education Yaoundé Cameroon Office of the Minister of State Secretary General Presidency of The Republic of Cameroon Yaoundé Cameroon Office of the Minister of External Relations Yaoundé Cameroon Office of the Minister i/c of Special Duties Presidency of The Republic of Cameroon Yaoundé Cameroon Office of the Minister Secretary General Prime Minister's Office Yaoundé Cameroon Office of the Minister of Women's Empowerment and the Family Yaoundé Cameroon Office of the Minister of Scientific Research and Innovation Yaoundé Cameroon Office of the Minister of the Economy Planning and Regional Development Yaoundé Cameroon Office of the Minister of Public Health Yaoundé Cameroon Office of the Minister Delegate i/c of Defense Presidency of The Republic of Cameroon Yaoundé Cameroon Office the Minister of Communication Yaoundé Cameroon Office the Minister of Finance Yaoundé Cameroon Office the Minister of Public Works Yaoundé Cameroon Office the Minister of Post and Telecommunication Yaoundé Cameroon Office the Minister of Secondary Education Yaoundé Cameroon Office the Minister of Basic Education Yaoundé Cameroon Office the Minister of Youth and Civic Education Yaoundé Cameroon Office the Minister of Sports and Physical Education Yaoundé Cameroon Office the Minister of Professional Training Yaoundé Cameroon Office the Minister of Employment and Social Security Yaoundé Cameroon Office the Minister of State Property and Land Tenure Yaoundé Cameroon Office of the Minister Director of Cabinet Prime Minister's Office Yaoundé Cameroon Office the Minister of Environment Nature Protection and Sustainable Development Yaoundé Cameroon Office the Minister of Mines Energy and Technological Development

Africa, the world's second-largest continent is home to 1.5 billion people, accounting for nearly 20% of the global population, (60% under age 25). By 2050, Africa's population will be 2.5 billion, and by 2035, more young Africans will be entering the workforce each year than in the rest of the world combined. Africa also hosts a rich social, cultural, and geopolitical diversity across its 5 geopolitical zones covering 54 countries. It is the most genetically, culturally, and linguistically diverse region on the planet. However, Africa's contribution to the global economy could be more significant if it urgently embraces the brain economy and leads in the development of new methodologies and approaches which can be exported around the world. In this paper, we explain our strategy to advance the Yaoundé Declaration for the Brain Economy, Brain Health, and Brain Capital. The Declaration has been endorsed by Cameroon's President, His Excellency Paul Biya, and demonstrates African leadership in global brain and society innovations, laying out a roadmap for how Africa can outcompete other economies by deftly deploying brain science-inspired policies and investments. We outline a new economic approach for African jobs, economic growth, sustainability, resilience, health, and well-being. The brain economy offers a broader framework than the current sustainable development goals (SDG) agenda. The Yaoundé Declaration is trans-disciplinary and cross-cutting across sectors: 32 sitting members of government from different sectors having co-authored this paper. It aligns with many aspects of the United Nations Pact for the Future and can accelerate the SDG. © 2025

关键词： Brain capital Brain economy Brain Health Green, digital care and bioeconomy transitions Neurodiplomacy Policy

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Retraction notice to "A deep learning approach based on graphs to detect plantation lines" [Heliyon Volume 10, Issue 11, 15 June 2024, e31730]

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Heliyon 2024年第23期10卷 e40689页

作者： Diogo Nunes Gonçalves José Marcato Junior Mauro Dos Santos de Arruda Vanessa Jordão Marcato Fernandes Ana Paula Marques Ramos Danielle Elis Garcia Furuya Lucas Prado Osco Hongjie He Lucio André de Castro Jorge Jonathan Li Farid Melgani Hemerson Pistori Wesley Nunes Gonçalves Faculty of Computer Science Federal University of Mato Grosso do Sul Av. Costa e Silva Campo Grande 79070-900 MS Brazil. Faculty of Engineering Architecture and Urbanism and Geography Federal University of Mato Grosso do Sul Av. Costa e Silva Campo Grande 79070-900 MS Brazil. Faculty of Agricultural Sciences Federal University of Grande Dourados Av. Costa e Silva Dourados 79070-900 MS Brazil. Faculty of Science and Technology São Paulo State University (UNESP) R. Roberto Simonsen 305 Presidente Prudente 19060-900 SP Brazil. Program of Environment and Regional Developement University of Western São Paulo Raposo Tavares km 572 Presidente Prudente 19067-175 SP Brazil. Department of Geography and Environmental Management University of Waterloo Waterloo ON N2L 3G1 Canada. National Research Center of Development of Agricultural Instrumentation Brazilian Agricultural Research Agency (EMBRAPA) 13560-970 R. XV de Novembro 1452 São Carlos SP Brazil. Department of Information Engineering and Computer Science University of Trento Trento 38122 Italy. INOVISAO Dom Bosco Catholic University Avenida Tamandaré 6000 Campo Grande 79117-900 MS Brazil.

[This retracts the article DOI: 10.1016/***.2024.e31730.].

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A deep learning approach based on graphs to detect plantation lines

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Heliyon 2024年第11期10卷 e31730页

Identifying plantation lines in aerial images of agricultural landscapes is re-quired for many automatic farming processes. Deep learning-based networks are among the most prominent methods to learn such patterns and extract this type of information from diverse imagery conditions. However, even state-of-the-art methods may stumble in complex plantation patterns. Here, we propose a deep learning approach based on graphs to detect plantation lines in UAV-based RGB imagery, presenting a challenging scenario containing spaced plants. The first module of our method extracts a feature map throughout the backbone, which consists of the initial layers of the VGG16. This feature map is used as an input to the Knowledge Estimation Module (KEM), organized in three concatenated branches for detecting 1) the plant positions, 2) the plantation lines, and 3) the displacement vectors between the plants. A graph modeling is applied considering each plant position on the image as vertices, and edges are formed between two vertices (i.e. plants). Finally, the edge is classified as pertaining to a certain plantation line based on three probabilities (higher than 0.5): i) in visual features obtained from the backbone; ii) a chance that the edge pixels belong to a line, from the KEM step; and iii) an alignment of the displacement vectors with the edge, also from the KEM step. Experiments were conducted initially in corn plantations with different growth stages and patterns with aerial RGB imagery to present the advantages of adopting each module. We assessed the generalization capability in the other two cultures (orange and eucalyptus) datasets. The proposed method was compared against state-of-the-art deep learning methods and achieved superior performance with a significant margin considering all three datasets. This approach is useful in extracting lines with spaced plantation patterns and could be implemented in scenarios where plantation gaps occur, generating lines with few-to-no

关键词： Aerial imagery Convolutional neural networks Object detection Remote sensing UAV

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