Jordan, Thomas M. Simis, Stefan G. H. Selmes, Nick Sent, Giulia Ienna, Federico Martinez-Vicente, Victor
Published in
Frontiers in Remote Sensing
Validation of satellite-derived aquatic reflectance involves relating meter-scale in situ observations to satellite pixels with typical spatial resolution ∼ 10–100 m within a temporal “match-up window” of an overpass. Due to sub-pixel variation these discrepancies in measurement scale are a source of uncertainty in the validation result. Additional...
Menefee, Dorothy Lee, Trey O. Flynn, K. Colton Chen, Jiquan Abraha, Michael Baker, John Suyker, Andy
Published in
Frontiers in Remote Sensing
Introduction: Machine learning methods combined with satellite imagery have the potential to improve estimates of carbon uptake of terrestrial ecosystems, including croplands. Studying carbon uptake patterns across the U.S. using research networks, like the Long-Term Agroecosystem Research (LTAR) network, can allow for the study of broader trends i...
Nassar, Ray MacDonald, Cameron G. Kuwahara, Bruce Fogal, Alexander Issa, Joshua Girmenia, Anthony Khan, Safwan Sioris, Chris E.
Published in
Frontiers in Remote Sensing
For most CO2 and CH4 satellites, only a small percentage (∼10%) of observations yield successful retrievals, with the remaining ∼90% rejected, primarily due to the effects of clouds. Discarding this large fraction of data is an inefficient strategy worth reconsidering due to the costs involved in developing, launching and operating the satellites t...
Imtiaz, Fatima Farooque, Aitazaz Wang, Xander Abbas, Farhat Afzaal, Hassan Esau, Travis Acharya, Bishnu Zaman, Qamar
Published in
Frontiers in Remote Sensing
Soil moisture variability caused by soil erosion, weather extremes, and spatial variations in soil health is a limiting factor for crop growth and productivity. Crop evapotranspiration (ET) is significant for irrigation water management systems. The variability in crop water requirements at various growth stages is a common concern at a global leve...
Foskinis, Romanos Nenes, Athanasios Papayannis, Alexandros Georgakaki, Paraskevi Eleftheriadis, Konstantinos Vratolis, Stergios Gini, Maria I. Komppula, Mika Vakkari, Ville Kokkalis, Panos
...
Published in
Frontiers in Remote Sensing
Remote sensing has been a key resource for developing extensive and detailed datasets for studying and constraining aerosol-cloud-climate interactions. However, aerosol-cloud collocation challenges, algorithm limitations, as well as difficulties in unraveling dynamic from aerosol-related effects on cloud microphysics, have long challenged precise r...
Marujo, Rennan de Freitas Bezerra Carlos, Felipe Menino Costa, Raphael Willian da Arcanjo, Jeferson de Souza Fronza, José Guilherme Soares, Anderson Reis Queiroz, Gilberto Ribeiro de Ferreira, Karine Reis
Published in
Frontiers in Remote Sensing
Clouds and cloud shadows significantly impact optical remote sensing. Combining images from different sources can help to obtain more frequent time series of the Earth’s surface. Nevertheless, sensor differences must be accounted for and treated before combining images from multiple sensors. Even after geometric correction, inter-calibration, and b...
Fickas, Kate C. O’Shea, Ryan E. Pahlevan, Nima Smith, Brandon Bartlett, Sarah L. Wolny, Jennifer L.
Published in
Frontiers in Remote Sensing
Cyanobacteria harmful algal blooms (cyanoHABs) present a critical public health challenge for aquatic resource and public health managers. Satellite remote sensing is well-positioned to aid in the identification and mapping of cyanoHABs and their dynamics, giving freshwater resource managers a tool for both rapid and long-term protection of public ...
Hu, Yongxiang Lu, Xiaomei Zeng, Xubin Gatebe, Charles Fu, Qiang Yang, Ping Weimer, Carl Stamnes, Snorre Baize, Rosemary Omar, Ali
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Published in
Frontiers in Remote Sensing
Lidar multiple scattering measurements provide the probability distribution of the distance laser light travels inside snow. Based on an analytic two-stream radiative transfer solution, the present study demonstrates why/how these lidar measurements can be used to derive snow depth and snow density. In particular, for a laser wavelength with little...
Fontana, Andressa Garcia Nascimento, Victor Fernandez Ometto, Jean Pierre do Amaral, Francisco Hélter Fernandes
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Frontiers in Remote Sensing
This research investigates Land Use and Land Cover (LULC) changes in the Porto Alegre Metropolitan Region (RMPA). A 30-year historical analysis using Landsat satellite imagery was made and used to develop LULC scenarios for the next 20 years using a Multilayer Perceptrons (MLP) model through an Artificial Neural Network (ANN). These maps analyze th...
Aka, Kadio S. R. Akpavi, Semihinva Dibi, N’Da Hyppolite Kabo-Bah, Amos T. Gyilbag, Amatus Boamah, Edward
Published in
Frontiers in Remote Sensing
Land use and land cover (LULC) changes are one of the main factors contributing to ecosystem degradation and global climate change. This study used the Gontougo Region as a study area, which is fast changing in land occupation and most vulnerable to climate change. The machine learning (ML) method through Google Earth Engine (GEE) is a widely used ...