Analysis of Forest Cover in the Tumba-Lediima Nature Reserve (RTL-DRC) by Sylvestre Frey, André Musas A Musas, Nestor Anzola Kibamba, Sebastien Kidushi Mboma, Tege Simboni Simboni, Djonive Munene Asidi

“…Using Landsat 7 and 8 satellite imagery, combined with NDVI calculation and supervised classifications validated by a high Kappa coefficient, this study provides an accurate mapping of land cover change. …”
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DAShip: A Large-Scale Annotated Dataset for Ship Detection Using Distributed Acoustic Sensing Technique by Wenjin Huang, Shaoyi Chen, Yichang Wu, Ruihua Li, Tianrui Li, Yihua Huang, Xiaochun Cao, Zhaohui Li

“…Ship monitoring methods based on coastal video surveillance, satellite imagery, and synthetic aperture radar have been well developed. …”
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Synoptic and Mesoscale Atmospheric Patterns That Triggered the Natural Disasters in the Metropolitan Region of Belo Horizonte, Brazil, in January 2020 by Thaís Aparecida Cortez Pinto, Enrique Vieira Mattos, Michelle Simões Reboita, Diego Oliveira de Souza, Paula S. S. Oda, Fabrina Bolzan Martins, Thiago Souza Biscaro, Glauber Willian de Souza Ferreira

“…To achieve this, we analyzed data from various sources, including natural disaster records from the National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), GOES-16 satellite imagery, soil moisture data from the Soil Moisture Active Passive (SMAP) satellite mission, ERA5 reanalysis, reflectivity from weather radar, and lightning data from the Lightning Location System. …”
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Automatic Grape Cluster Detection Combining YOLO Model and Remote Sensing Imagery by Ana María Codes-Alcaraz, Nicola Furnitto, Giuseppe Sottosanti, Sabina Failla, Herminia Puerto, Carmen Rocamora-Osorio, Pedro Freire-García, Juan Miguel Ramírez-Cuesta

“…Precision agriculture has recently experienced significant advancements through the use of technologies such as unmanned aerial vehicles (UAVs) and satellite imagery, enabling more efficient and precise agricultural management. …”
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Utilizing Remote Sensing to Quantify Evapotranspiration: A Case Study of the Saiss Basin (Morocco) by Oumou Abdellah, Essahlaoui Ali, Khrabcha Abdelali, Essahlaoui Narjisse, Alitane Abdennabi, Kassou Amina, El Hafyani Mohammed, Van Rompaey Anton, Gobin Anne

“…In this study, the METRIC model was applied using Landsat satellite imagery and climatic data. This involves resolving the surface energy balance equation by calculating net radiation, soil heat flux, and sensible heat flux. …”
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Alpine vegetation community patterns in the Khumbu region, Nepalese Himalaya by Ruolin Leng, Stephan Harrison, Elizabeth A. Byers, Mahesh Magar, Harkrei Rai, Ram Raj Rijal, Karen Anderson

“…Here we use fine spatial resolution satellite imagery from WorldView-2 (2 m2 per pixel) coupled with elevation model data from the Copernicus GLO-30 product to produce a land cover classification for the HAZ. …”
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Minimizing Seam Lines in UAV Multispectral Image Mosaics Utilizing Irradiance, Vignette, and BRDF by Hoyong Ahn, Chansol Kim, Seungchan Lim, Cheonggil Jin, Jinsu Kim, Chuluong Choi

“…Unmanned aerial vehicle (UAV) imaging provides the ability to obtain high-resolution images at a lower cost than satellite imagery and aerial photography. However, multiple UAV images need to be mosaicked to obtain images of large areas, and the resulting UAV multispectral image mosaics typically contain seam lines. …”
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Introduction to deep learning methods for multi‐species predictions by Yuqing Hu, Sara Si‐Moussi, Wilfried Thuiller

“…Specifically, we introduced four distinct deep learning models that use site × species community data but differ in their internal structure or on the input environmental data structure: (1) a multi‐layer perceptron (MLP) model for tabular data (e.g. in‐situ/raster climate or soil data), (2) a convolutional neural network (CNN) and (3) a vision transformer (ViT) models tailored for image data (e.g. aerial ortho‐photographs, satellite imagery), and a multimodal model that integrates both tabular and image data. …”
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Exploring the feasibility of GF1-WFV data in estimating SPAD using spatiotemporal fusion algorithms by Annan Zeng, Jianli Ding, Jinjie Wang, Lijing Han, Haiyan Han, Shuang Zhao, Xiangyu Ge

“…This study provides comprehensive insights into dynamic and large-scale monitoring of vegetation chlorophyll content, particularly in scenarios in which satellite imagery is unavailable.…”
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Simultaneous Observation of Equatorial Plasma Bubbles and Traveling Ionospheric Disturbances Over Indonesia Following the 15 January 2022 Tonga Volcano Eruption by Asnawi Husin, Varuliantor Dear, Agri Faturahman, Sefria Anggarani, Annis Siradj Mardiani, Adi Purwono, Jiyo Harjosuwito, Rezy Pradipta

“…Observation data from the Indonesian global navigation satellite system (GNSS) CORS network, ionosondes, and GNSS ionospheric scintillation and TEC monitor receivers, in conjunction with the Himawari‐8 satellite imagery, were used in the analysis. The Lamb waves from the eruption, traveling at ∼310 m/s, reached eastern part of Indonesia (∼5,000 km from Tonga) approximately 4 hr after the eruption. …”
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Influence of Land-Use and Landcover on the Nest Distribution and Breeding Success of Grey Crowned Crane (Balearica Regulorum) In Kiyanja- Kaku Wetland Ecosystem. by Tayebwa, Gilbert

“…To collect data, we used a combination of satellite imagery, GPS ground truthing, and field observations. …”
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Delineating urban flooding when incorporating community stormwater knowledge by Madeline Scolio, Peleg Kremer, Virginia Smith, Achira Amur, Bridget Wadzuk, Kate Homet, Eric Devlin, Md Abdullah Al Mehedi, Laura Moore

“…An array of data, including remotely sensed satellite imagery after major flooding events, Federal Emergency Management Agency’s Special Flood Hazard Areas, First Street Foundation’s Flood Factor, road closures, National Flood Insurance Program claims, and community surveys, were compared for the study areas. …”
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Lake Iriqui’s Remarkable Revival: Field Observations and a Google Earth Engine Analysis of Its Recovery After over Half a Century of Desiccation by Adil Moumane, Tarik Bahouq, Ahmed Karmaoui, Dahmane Laghfiri, Mohamed Yassine, Jamal Al Karkouri, Mouhcine Batchi, Mustapha Faouzi, Mohamed Boulakhbar, Ali Ait Youssef

“…The revival was monitored using satellite imagery from Landsat 8 and 9 and Sentinel-2A, processed through Google Earth Engine (GEE), with the Normalized Difference Water Index (NDWI) applied to detect water presence. …”
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A Comparative Analysis of Spatial Resolution Sentinel-2 and Pleiades Imagery for Mapping Urban Tree Species by Fabio Recanatesi, Antonietta De Santis, Lorenzo Gatti, Alessio Patriarca, Eros Caputi, Giulia Mancini, Chiara Iavarone, Carlo Maria Rossi, Gabriele Delogu, Miriam Perretta, Lorenzo Boccia, Maria Nicolina Ripa

“…This study evaluates and compares the efficacy of Sentinel-2 and Pléiades satellite imagery in classifying tree species within historic urban parks in Rome—Villa Borghese, Villa Ada Savoia, and Villa Doria Pamphilj. …”
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Quantification of Soil–Water Erosion Using the RUSLE Method in the Mékrou Watershed (Middle Niger River) by Rachid Abdourahamane Attoubounou, Hamidou Diawara, Ralf Ludwig, Julien Adounkpe

“…Land use and land cover data were extracted from satellite imagery, enabling the analysis of vegetation cover and anthropogenic impacts over four decades. …”
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Temperature Is a Key Factor Affecting Total Phosphorus and Total Nitrogen Concentrations in Northeastern Lakes Based on Sentinel-2 Images and Machine Learning Methods by Haoming Qin, Chong Fang, Ge Liu, Kaishan Song, Zhuoshi Li, Sijia Li, Hui Tao, Zhaojiang Yan

“…This study utilized machine learning algorithms based on Sentinel-2 satellite imagery for remote estimation of TP and TN concentrations in Lake Xingkai, Chagan and Songhua. …”
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Phosphorus transitions driven by cyclone biparjoy linked middle east North Africa (MENA) and Indian Thar Desert dust storm pathways in Asia’s largest grassland by Rupak Dey, Seema B. Sharma, Mahesh G. Thakkar, Ranjit Kumar Sarangi, Abhiroop Chowdhury, Aliya Naz

“…To examine the long-range transport of dust-borne phosphorus and its subsequent deposition in the target grassland, we employed an interdisciplinary approach that integrated satellite imagery and ground-based measurements. Spatial and temporal variations in dust emissions were assessed using satellite remote sensing data, while ground truthing was performed for phosphorus content analysis using standard protocols. …”
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Groundwater Potential Assessment Using Integrated Geospatial and Analytic Hierarchy Process Techniques (AHP) in Chemoga Watershed, Upper Blue Nile Basin, Ethiopia by Samuel Berihun Kassa, Fasikaw Atanaw Zimale, Arega Mulu, Tadege Aragaw Worku, Mindesilew Lakew Wossene, Taye Minichil Meshesha, Yoseph Buta Hailu, Tadele F. Aman, Mekash S. Kifelew, Habtamu Asrat Mekonnen

“…Data was gathered from satellite imagery, existing thematic maps, local water offices, and national meteorological agencies. …”
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Using OCO-2 Observations to Constrain Regional CO₂ Fluxes Estimated with the Vegetation, Photosynthesis and Respiration Model by Igor B. Konovalov, Nikolai A. Golovushkin, Evgeny A. Mareev

“…In this study, we investigate the feasibility of inferring reliable regional estimates of the net ecosystem exchange (NEE) using column-averaged dry-air mole fractions of CO₂ (XCO₂) retrieved from Orbiting Carbon Observatory-2 (OCO-2) observations as constraints on parameters of the widely used Vegetation Photosynthesis and Respiration model (VPRM), which predicts ecosystem fluxes based on vegetation indices derived from multispectral satellite imagery. We developed a regional-scale inverse modeling system that applies a Bayesian variational optimization algorithm to optimize parameters of VPRM coupled to the CHIMERE chemistry transport model and which involves a preliminary transformation of the input XCO₂ data that reduces the impact of the CHIMERE boundary conditions on inversion results. …”
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Modeling the tropical fish community related to land uses and environmental determinants by N. Takarina, O. Chuan, M. Afifudin, L. Tristan, I. Arif, A. Adiwibowo

“…Land uses at the sites were interpreted using satellite imagery. Fish diversity was determined using the Shannon–Wiener index, rarefaction curve, and Lorenz graph. …”
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