Results 131 to 140 of about 2,560 (196)

Modelación hidrológica de una cuenca en los Andes del sur del Ecuador utilizando datos estimados por sensores remotos [PDF]

, 2017
El objetivo de esta investigación fue modelar los escurrimientos diarios en una cuenca hidrográfica utilizando datos de sensores remotos (SR) en el modelo CEQUEAU a 0.05°/~5 km, 0.125°/~13.5 km y 0.25°/~27.5 km de resolución espacial.
BALCAZAR ORDOÑEZ, LUIS EDUARDO, BALCAZAR ORDOÑEZ, LUIS EDUARDO   +1 more
core  

Unveiling four decades of intensifying precipitation from tropical cyclones using satellite measurements. [PDF]

Sci Rep, 2022
Shearer EJ, Afzali Gorooh V, Nguyen P, Hsu KL, Sorooshian S.   +4 more
europepmc   +1 more source

Soil and vegetation water content identify the main terrestrial ecosystem changes. [PDF]

Natl Sci Rev, 2023
Bueso D, Piles M, Ciais P, Wigneron JP, Moreno-Martínez Á, Camps-Valls G.   +5 more
europepmc   +1 more source

Padrões de precipitação no Sul da Amazônia baseado no PERSIANN-CDR: Características e tendências

, 2017
Precipitation is a key climatic parameter for many anthropogenic activities, especially agriculture. Yet, its homogeneous and continuous monitoring remains challenging. That is particularly true for the Amazon region, which is sparsely inhabited and has a low density of ground-based rain gauge network.
Arvor, Damien, Funatsu, Beatriz M., Michot, Véronique, Dubreuil, Vincent   +3 more
openaire   +1 more source

Rising ecosystem water demand exacerbates the lengthening of tropical dry seasons. [PDF]

Nat Commun, 2022
Xu H, Lian X, Slette IJ, Yang H, Zhang Y, Chen A, Piao S.   +6 more
europepmc   +1 more source

PERSIANN-CNN: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks - Convolutional Neural Networks PERSIANN-CNN: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks - Convolutional Neural Networks

, 2019
Accurate and timely precipitation estimates are critical for monitoring and forecasting natural disasters such as floods. Despite having highŠresolution satellite information, precipitation estimation from remotely sensed data still suffers from methodological limitations.
Sadeghi, Mojtaba, Asanjan, Ata Akbari, Faridzad, Mohammad, Nguyen, Phu, Hsu, Kuolin, Sorooshian, Soroosh, Braithwaite, Dan   +6 more
openaire   +2 more sources

Temporal Monitoring and Predicting of the Abundance of Malaria Vectors Using Time Series Analysis of Remote Sensing Data through Google Earth Engine. [PDF]

Sensors (Basel), 2022
Youssefi F, Zoej MJV, Hanafi-Bojd AA, Dariane AB, Khaki M, Safdarinezhad A, Ghaderpour E.   +6 more
europepmc   +1 more source

Development of Variogram Models Retrieved from PERSIANN Family and TRMM 3B47 V. 7 Satellite-Derived Datasets in Fars Province

مهندسی منابع آب
Introduction: Precipitation data plays a crucial role in hydrological models, and it is important to have a good understanding of its spatial and temporal distribution before incorporating it into these models.
Keyvan Khojand, Mahmood Reza Shaghaghian, Zahra Ghampour, Tooraj Sabzevari   +3 more
doaj  

Combining Geostatistics and Remote Sensing Data to Improve Spatiotemporal Analysis of Precipitation. [PDF]

Sensors (Basel), 2021
Varouchakis EA, Kamińska-Chuchmała A, Kowalik G, Spanoudaki K, Graña M.   +4 more
europepmc   +1 more source

Evaluating the accuracy of gridded precipitation datasets and CMIP6 GCM ensemble means against gauge observations in South Wollo, Ethiopia. [PDF]

Sci Rep
Assamnew AD, Gobie BG, Habtemicheal BA.
europepmc   +1 more source