Inversion and analysis of leaf area index (LAI) of urban park based on unmanned aerial vehicle (UAV) multispectral remote sensing and random forest (RF).

Autores: Li Y; Department of Architecture, Henan Technical College of Construction, Zhengzhou, China., Wang B; School of Horticulture and Landscape Architecture, Henan Institute of Science and Technology, Xinxiang, China., Zhao X; School of Horticulture and Landscape Architecture, Henan Institute of Science and Technology, Xinxiang, China., Zhang Y; School of Horticulture and Landscape Architecture, Henan Institute of Science and Technology, Xinxiang, China., Qiao L; School of Horticulture and Landscape Architecture, Henan Institute of Science and Technology, Xinxiang, China.

Fonte: PloS one [PLoS One] 2025 Mar 24; Vol. 20 (3), pp. e0320608. Date of Electronic Publication: 2025 Mar 24 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Remote Sensing Technology*/methods , Plant Leaves*/growth & development , Parks, Recreational* , Forests* , Unmanned Aerial Devices*, China ; Environmental Monitoring/methods ; Random Forest

Method for building segmentation and extraction from high-resolution remote sensing images based on improved YOLOv5ds.

Autores: Chang F; Hebei Provincial Communication Planning, Design, and Research Institute Co., Ltd Town Renewal Research Center, Shijiazhuang, China.; School of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, China., Ma T; School of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing, China., Wang D; Hebei Provincial Communication Planning, Design, and Research Institute Co., Ltd Town Renewal Research Center, Shijiazhuang, China., Zhu S; Hangzhou Survey, Design and Research Institute Co., Ltd, New Smart City Research Center, Hangzhou, China., Li D; Department of Safety Supervision, China MCC22 Group Co., Ltd, Tangshan, China., Feng S; China Telecom Digital City Technology Co., Ltd, Intelligent Transport Systems Product Line, Baoding, China., Fan X; Hebei Provincial Communication Planning, Design, and Research Institute Co., Ltd Town Renewal Research Center, Shijiazhuang, China.

Fonte: PloS one [PLoS One] 2025 Mar 18; Vol. 20 (3), pp. e0317106. Date of Electronic Publication: 2025 Mar 18 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Remote Sensing Technology*/methods , Image Processing, Computer-Assisted*/methods, Algorithms

A dynamic and adaptive class-balanced data augmentation approach for 3D LiDAR point clouds.

Autores: Liu B; School of Computer Science and Artificial Intelligence, Chaohu University, Chaohu, China.; School of Computer Science and Engineering, Macau University of Science and Technology, Macau, China., Qi X; Department of Information Technology and Cybersecurity, Shanghai Police College, Shanghai, China.

Fonte: PloS one [PLoS One] 2025 Mar 17; Vol. 20 (3), pp. e0318888. Date of Electronic Publication: 2025 Mar 17 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Algorithms* , Imaging, Three-Dimensional*/methods , Remote Sensing Technology*/methods

High resolution descriptors for UAV mapping in biodiversity conservation - A case study of sandy steppe habitat renewal.

Autores: Arok M; BioSense Institute - Research and Development Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, Republic of Serbia., Brkljač B; Department of Power, Electronic and Telecommunication Engineering, Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Republic of Serbia., Lugonja P; BioSense Institute - Research and Development Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, Republic of Serbia., Ivošević B; BioSense Institute - Research and Development Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, Republic of Serbia., Vukotić M; Ranger service, Public enterprise Palić-Ludaš, Palić, Republic of Serbia., Nikolić Lugonja T; BioSense Institute - Research and Development Institute for Information Technologies in Biosystems, University of Novi Sad, Novi Sad, Republic of Serbia.

Fonte: PloS one [PLoS One] 2025 Mar 13; Vol. 20 (3), pp. e0315399. Date of Electronic Publication: 2025 Mar 13 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Conservation of Natural Resources*/methods , Biodiversity* , Grassland* , Ecosystem* , Unmanned Aerial Devices* , Remote Sensing Technology*, Animals ; Sciuridae/physiology ; Serbia

Utility of UAS-LIDAR for estimating forest structural attributes of the Miombo woodlands in Zambia.

Autores: Shamaoma H; Department of Urban and Regional Planning, Copperbelt University, Kitwe, Zambia., Chirwa PW; Forest Science Postgraduate Programme, Department of Plant and Soil Sciences, University of Pretoria, Pretoria, South Africa., Zekeng JC; Department of Forest Engineering, Advanced Teachers Training School for Technical Education, University of Douala, Douala, Cameroon.; Oliver R Tambo Africa Research Chair Initiative (ORTARChI), Chair of Environment and Development, Department of Environmental and Plant Sciences, Copperbelt University, Kitwe, Zambia., Ramoelo A; Centre for Environmental Studies (CFES), Department of Geography, Geoinformatics and Meteorology after CFES, University of Pretoria, Pretoria, South Africa.; Earth Observation Programme, South African National Space Agency (SANSA), Pretoria, South Africa., Hudak AT; USDA Forest Service, Rocky Mountain Research Station, Forestry Sciences Laboratory, Moscow, Idaho, United States of America., Handavu F; Department of Geography, Environment and Climate Change, Mukuba University, Kitwe, Zambia., Syampungani S; Forest Science Postgraduate Programme, Department of Plant and Soil Sciences, University of Pretoria, Pretoria, South Africa.; Oliver R Tambo Africa Research Chair Initiative (ORTARChI), Chair of Environment and Development, Department of Environmental and Plant Sciences, Copperbelt University, Kitwe, Zambia.

Fonte: PloS one [PLoS One] 2025 Mar 11; Vol. 20 (3), pp. e0315664. Date of Electronic Publication: 2025 Mar 11 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Forests* , Remote Sensing Technology*/methods , Trees*, Zambia ; Biomass

Cough recognition in pneumoconiosis patients based on a flexible patch with an embedded ACC sensor for remote monitoring.

Autores: Wang J; School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou, China., Min C; Department of Pneumoconiosis, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China.; The Fifth People's Hospital of Suzhou, Suzhou, China., Yu F; School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou, China., Chen K; School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou, China. kchen@hdu.edu.cn., Mao L; NHC Key Laboratory of Pneumoconiosis, Taiyuan, China. maoling113@sina.com.; Department of Pneumoconiosis, Shanghai Pulmonary Hospital, Tongji University, Shanghai, China. maoling113@sina.com.

Fonte: BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2025 Jan 27; Vol. 25 (1), pp. 41. Date of Electronic Publication: 2025 Jan 27.

Tipo de Publicación: Journal Article

Información da Revista: Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947 (Electronic) Linking ISSN: 14726947 NLM ISO Abbreviation: BMC Med Inform Decis Mak Subsets: MEDLINE

Termos MeSH: Cough*/diagnosis , Cough*/etiology , Pneumoconiosis*/diagnosis , Pneumoconiosis*/complications , Remote Sensing Technology*/instrumentation , Remote Sensing Technology*/methods, Humans ; Adult ; Male ; Female ; Young Adult ; Monitoring, Physiologic/instrumentation ; Monitoring, Physiologic/methods

TGF-Net: Transformer and gist CNN fusion network for multi-modal remote sensing image classification.

Autores: Wang H; Center for Information and Educational Technology, Southwest Medical University, Luzhou, Sichuan, China.; School of Geophysics, Chengdu University of Technology, Chengdu, Sichuan, China., Wang H; School of Geophysics, Chengdu University of Technology, Chengdu, Sichuan, China., Wu L; College of Health and Intelligent Engineering, Chengdu Medical College, Chengdu, Sichuan, China.

Fonte: PloS one [PLoS One] 2025 Feb 19; Vol. 20 (2), pp. e0316900. Date of Electronic Publication: 2025 Feb 19 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Neural Networks, Computer* , Remote Sensing Technology*/methods , Image Processing, Computer-Assisted*/methods, Deep Learning ; Algorithms

SugarViT-Multi-objective regression of UAV images with Vision Transformers and Deep Label Distribution Learning demonstrated on disease severity prediction in sugar beet.

Autores: Günder M; Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven, Sankt Augustin, Germany.; Institute for Computer Science III, University of Bonn, Bonn, Germany., Yamati FRI; Institute for Sugar Beet Research (IfZ), Göttingen, Germany., Barreto A; Institute for Sugar Beet Research (IfZ), Göttingen, Germany., Mahlein AK; Institute for Sugar Beet Research (IfZ), Göttingen, Germany., Sifa R; Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven, Sankt Augustin, Germany.; Institute for Computer Science III, University of Bonn, Bonn, Germany., Bauckhage C; Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven, Sankt Augustin, Germany.; Institute for Computer Science III, University of Bonn, Bonn, Germany.

Fonte: PloS one [PLoS One] 2025 Feb 13; Vol. 20 (2), pp. e0318097. Date of Electronic Publication: 2025 Feb 13 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Beta vulgaris*/microbiology , Plant Diseases* , Remote Sensing Technology*/methods , Deep Learning* , Unmanned Aerial Devices*, Machine Learning ; Image Processing, Computer-Assisted/methods ; Artificial Intelligence

Distribution of ilmenite minerals in placer deposits along the middle coast of Southern Brazil using spaceborne and ground-based remote sensing.

Autores: Prates Hallal G; Laboratório de Sensoriamento Remoto Geológico, Centro Estadual de Pesquisas em Sensoriamento Remoto e Meteorologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil., Porcher CC; Centro de Estudos em Petrologia e Geoquímica, Instituto de Geologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil., Veettil BK; Laboratory of Ecology and Environmental Management, Science and Technology Advanced Institute, Van Lang University, Ho Chi Minh City, Vietnam.; Faculty of Applied Technology, School of Technology, Van Lang University, Ho Chi Minh City, Vietnam., de Almeida Espinoza JM; Laboratório de Física Experimental,Instituto Federal de Educação Ciência e Tecnologia de Santa Catarina, Caçador, Brasil., Beatriz Alves Rolim S; Laboratório de Sensoriamento Remoto Geológico, Centro Estadual de Pesquisas em Sensoriamento Remoto e Meteorologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brasil.

Fonte: PloS one [PLoS One] 2025 Feb 12; Vol. 20 (2), pp. e0314238. Date of Electronic Publication: 2025 Feb 12 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Titanium*/analysis , Titanium*/chemistry , Remote Sensing Technology*/methods , Minerals*/analysis, Brazil

Land cover classification of high-resolution remote sensing images based on improved spectral clustering.

Autores: Wu S; Jilin Agricultural University, Changchun, China., Cao JM; Jilin Agricultural University, Changchun, China., Zhao XY; Jilin Agricultural University, Changchun, China.

Fonte: PloS one [PLoS One] 2025 Feb 06; Vol. 20 (2), pp. e0316830. Date of Electronic Publication: 2025 Feb 06 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Remote Sensing Technology*/methods , Satellite Imagery*, Algorithms ; Cluster Analysis ; Image Processing, Computer-Assisted/methods

Remote sensing-based maize growth process parameters revel the maize yield: a comparison of field- and regional-scale.

Autores: Cheng M; Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Key Laboratory of Crop Cultivation and Physiology, Agricultural College, Yangzhou University, Yangzhou, 225009, People's Republic of China.; Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, 225009, People's Republic of China.; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China., Jin X; Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Key Laboratory of Crop Cultivation and Physiology, Agricultural College, Yangzhou University, Yangzhou, 225009, People's Republic of China. jinxiuliang@caas.cn.; Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Yangzhou University, Yangzhou, 225009, People's Republic of China. jinxiuliang@caas.cn.; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China. jinxiuliang@caas.cn.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China. jinxiuliang@caas.cn., Nie C; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China., Liu K; College of Agricultural Science and Engineering, Hohai University, Nanjing, Jiangsu Province, 210098, People's Republic of China., Wu T; College of Environmental Science and Engineering, Xiamen University of Technology, Xiamen, 361024, People's Republic of China., Lv Y; College of Hydraulic Science and Engineering, Yangzhou University, Yangzhou, 225009, People's Republic of China., Liu S; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China., Yu X; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China., Bai Y; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China., Liu Y; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China., Meng L; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China., Jia X; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China., Liu Y; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China., Zhou L; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China., Nan F; Institute of Crop Sciences, Chinese Academy of Agricultural Sciences/Key Laboratory of Crop Physiology and Ecology, Ministry of Agriculture, Beijing, 100081, People's Republic of China.; National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, 572024, China.

Fonte: BMC plant biology [BMC Plant Biol] 2025 Feb 06; Vol. 25 (1), pp. 154. Date of Electronic Publication: 2025 Feb 06.

Tipo de Publicación: Journal Article; Comparative Study

Información da Revista: Publisher: BioMed Central Country of Publication: England NLM ID: 100967807 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2229 (Electronic) Linking ISSN: 14712229 NLM ISO Abbreviation: BMC Plant Biol Subsets: MEDLINE

Termos MeSH: Zea mays*/growth & development , Remote Sensing Technology*/methods, Agriculture/methods ; Plant Leaves/growth & development ; Crops, Agricultural/growth & development

SAASNets: Shared attention aggregation Siamese networks for building change detection in multispectral remote sensing.

Autores: Pang S; Shandong University of Aeronautics, Binzhou, China., You C; Shandong University of Aeronautics, Binzhou, China., Zhang M; Shandong University of Aeronautics, Binzhou, China., Zhang B; Shandong University of Aeronautics, Binzhou, China., Wang L; Shandong University of Aeronautics, Binzhou, China., Shi X; Shandong University of Aeronautics, Binzhou, China., Sun Y; Zhanhua District Power Supply Company, Binzhou, China.

Fonte: PloS one [PLoS One] 2025 Jan 30; Vol. 20 (1), pp. e0306755. Date of Electronic Publication: 2025 Jan 30 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Remote Sensing Technology*/methods , Neural Networks, Computer*, Algorithms ; Humans

Radar versus optical: The impact of cloud cover when mapping seasonal surface water for health applications in monsoon-affected India.

Autores: Uday G; Ashoka Trust for Research in Ecology and the Environment, Bengalore, India., Purse BV; UK Centre for Ecology and Hydrology, Crowmarsh Gifford, Wallingford, United Kingdom., Kelley DI; UK Centre for Ecology and Hydrology, Crowmarsh Gifford, Wallingford, United Kingdom., Vanak A; Ashoka Trust for Research in Ecology and the Environment, Bengalore, India.; School of Biological Sciences, University of KwaZulu-Natal, Durban, South Africa., Samrat A; Ashoka Trust for Research in Ecology and the Environment, Bengalore, India.; School of Engineering and Computing, University of Central Lancashire, Preston, United Kingdom., Chaudhary A; Ashoka Trust for Research in Ecology and the Environment, Bengalore, India.; Department of Geography, University of Florida, Gainesville, Florida, United States of America., Rahman M; Ashoka Trust for Research in Ecology and the Environment, Bengalore, India., Gerard FF; UK Centre for Ecology and Hydrology, Crowmarsh Gifford, Wallingford, United Kingdom.

Fonte: PloS one [PLoS One] 2025 Jan 24; Vol. 20 (1), pp. e0314033. Date of Electronic Publication: 2025 Jan 24 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Seasons* , Radar* , Remote Sensing Technology*/methods , Environmental Monitoring*/methods , Water*, India ; Humans ; Bayes Theorem

Field-scale detection of Bacterial Leaf Blight in rice based on UAV multispectral imaging and deep learning frameworks.

Autores: Logavitool G; School of Information, Computer and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, Thailand., Horanont T; School of Information, Computer and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, Thailand., Thapa A; Advanced Geospatial Technology Research Unit, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani, Thailand., Intarat K; Department of Geography, Faculty of Liberal Arts, Thammasat University, Pathum Thani, Thailand.; Reserach Unit in Geospatial Applications (Capybara Geo Lab), Faculty of Liberal Arts, Thammasat University, Pathum Thani, Thailand., Wuttiwong KO; Rice Department, Bangkok, Thailand.

Fonte: PloS one [PLoS One] 2025 Jan 17; Vol. 20 (1), pp. e0314535. Date of Electronic Publication: 2025 Jan 17 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Oryza*/microbiology , Plant Diseases*/microbiology , Deep Learning* , Plant Leaves*/microbiology , Unmanned Aerial Devices* , Remote Sensing Technology*/methods, Xanthomonas

Coupling SAR and optical remote sensing data for soil moisture retrieval over dense vegetation covered areas.

Autores: Shi J; North China University of Water Resources and Electric Power, Zhengzhou, China.; Key Laboratory of Conservation and Intensive Use of Water Resources in the Yellow River Basin of Henan Province, Zhengzhou, China., Yang H; North China University of Water Resources and Electric Power, Zhengzhou, China.; Key Laboratory of Conservation and Intensive Use of Water Resources in the Yellow River Basin of Henan Province, Zhengzhou, China., Hou X; North China University of Water Resources and Electric Power, Zhengzhou, China., Zhang H; North China University of Water Resources and Electric Power, Zhengzhou, China., Tang G; North China University of Water Resources and Electric Power, Zhengzhou, China., Zhao H; North China University of Water Resources and Electric Power, Zhengzhou, China.; Key Laboratory of Conservation and Intensive Use of Water Resources in the Yellow River Basin of Henan Province, Zhengzhou, China., Wang F; North China University of Water Resources and Electric Power, Zhengzhou, China.; Key Laboratory of Conservation and Intensive Use of Water Resources in the Yellow River Basin of Henan Province, Zhengzhou, China.

Fonte: PloS one [PLoS One] 2025 Jan 16; Vol. 20 (1), pp. e0315971. Date of Electronic Publication: 2025 Jan 16 (Print Publication: 2025).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Soil*/chemistry , Remote Sensing Technology*/methods , Water*/analysis , Radar* , Environmental Monitoring*/methods, Algorithms ; Models, Theoretical

MIMO and PDM-based intersatellite optical link for high-speed data transfer and remote sensing application.

Autores: Chaudhary S; School of Computer, Guangdong University of Petrochemical Technology, Maoming, China., Meng Y; School of Science, Guangdong University of Petrochemical Technology, Maoming, China., Sharma A; Department of Electronics and Communication Engineering, National Institute of Technology, Hamirpur, India., Naeem MA; School of Science, Guangdong University of Petrochemical Technology, Maoming, China.

Fonte: PloS one [PLoS One] 2024 Nov 12; Vol. 19 (11), pp. e0313342. Date of Electronic Publication: 2024 Nov 12 (Print Publication: 2024).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Wireless Technology*/instrumentation , Remote Sensing Technology*/methods , Remote Sensing Technology*/instrumentation, Satellite Communications

Comprehensive evaluation of nine evapotranspiration products from remote sensing, gauge upscaling and land surface model over China.

Autores: Wang D; Overseas Expertise Introduction Center for Discipline Innovation of Watershed Ecological Security in the Water Source Area of the Middle Route of South-to-North Water Diversion, College of Water Resources and Modern Agriculture, Nanyang, China., Wang D; School of Geography and Planning, Sun Yat-sen University, Guangzhou, China., Liu S; Overseas Expertise Introduction Center for Discipline Innovation of Watershed Ecological Security in the Water Source Area of the Middle Route of South-to-North Water Diversion, College of Water Resources and Modern Agriculture, Nanyang, China., Huang Y; State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, China., Yang Q; School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, United States of America., Ma X; Overseas Expertise Introduction Center for Discipline Innovation of Watershed Ecological Security in the Water Source Area of the Middle Route of South-to-North Water Diversion, College of Water Resources and Modern Agriculture, Nanyang, China., Lin Z; School of Geography and Planning, Sun Yat-sen University, Guangzhou, China.

Fonte: PloS one [PLoS One] 2024 Nov 13; Vol. 19 (11), pp. e0313762. Date of Electronic Publication: 2024 Nov 13 (Print Publication: 2024).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Remote Sensing Technology*/methods, China ; Environmental Monitoring/methods ; Models, Theoretical ; Climate

Participatory science methods to monitor water quality and ground truth remote sensing of the Chesapeake Bay.

Autores: Neale P; Smithsonian Institution, Smithsonian Environmental Research Center, Edgewater, Maryland, United States of America., Brown S; Smithsonian Institution, Smithsonian Environmental Research Center, Edgewater, Maryland, United States of America., Sill T; Smithsonian Institution, Smithsonian Environmental Research Center, Edgewater, Maryland, United States of America., Cawood A; Smithsonian Institution, Smithsonian Environmental Research Center, Edgewater, Maryland, United States of America., Tzortziou M; The City College of New York, City University of New York, New York, New York, United States of America., Park J; The City College of New York, City University of New York, New York, New York, United States of America., Lee MS; The City College of New York, City University of New York, New York, New York, United States of America.; National Institute of Fisheries Science, Busan, South Korea., Paquette B; Independent researcher, Edgewater, Maryland, United States of America.

Fonte: PloS one [PLoS One] 2024 Oct 31; Vol. 19 (10), pp. e0305505. Date of Electronic Publication: 2024 Oct 31 (Print Publication: 2024).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Water Quality* , Bays* , Environmental Monitoring*/methods , Remote Sensing Technology*/methods , Chlorophyll*/analysis, Humans

Enhancing wind erosion risk assessment through remote sensing techniques.

Autores: Boali A; Department of Arid Zone Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran., Kariminejad N; Department of Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran., Hosseinalizadeh M; Department of Arid Zone Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.

Fonte: PloS one [PLoS One] 2024 Oct 31; Vol. 19 (10), pp. e0308854. Date of Electronic Publication: 2024 Oct 31 (Print Publication: 2024).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Wind* , Remote Sensing Technology*/methods, Risk Assessment/methods ; Iran ; Environmental Monitoring/methods ; Support Vector Machine ; Machine Learning ; Models, Theoretical ; Conservation of Natural Resources/methods

Spatio-temporal variations of energy carbon emissions in Xinjiang based on DMSP-OLS and NPP-VIIRS nighttime light remote sensing data.

Autores: Song J; College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, China., He X; College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, China., Zhang F; College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua, China., Wang W; College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi, China., Chan NW; GeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, Penang, Malaysia., Shi J; Departments of Earth Sciences, The University of Memphis, Memphis, TN, United States of America., Tan ML; GeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, Penang, Malaysia.

Fonte: PloS one [PLoS One] 2024 Oct 25; Vol. 19 (10), pp. e0312388. Date of Electronic Publication: 2024 Oct 25 (Print Publication: 2024).

Tipo de Publicación: Journal Article

Información da Revista: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE

Termos MeSH: Carbon*/analysis , Carbon*/metabolism , Remote Sensing Technology* , Environmental Monitoring*/methods, China ; Air Pollutants/analysis ; Spatio-Temporal Analysis