High performance GPU computing based approaches for oil spill detection from multi-temporal remote sensing data

Remote Sensing of Environment ◽

10.1016/j.rse.2017.03.024 ◽

2017 ◽

Vol 202 ◽

pp. 28-44 ◽

Cited By ~ 6

Author(s):

Ujwala Bhangale ◽

Surya S. Durbha ◽

Roger L. King ◽

Nicolas H. Younan ◽

Rangaraju Vatsavai

Keyword(s):

Remote Sensing ◽

Oil Spill ◽

High Performance ◽

Gpu Computing ◽

Remote Sensing Data ◽

Sensing Data ◽

Oil Spill Detection ◽

Multi Temporal

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Modeling Spatio-temporal Drought Events Based on Multi-temporal, Multi-source Remote Sensing Data Calibrated by Soil Humidity

Chinese Geographical Science ◽

10.1007/s11769-021-1250-4 ◽

2021 ◽

Author(s):

Hanyu Li ◽

Hermann Kaufmann ◽

Guochang Xu

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

Soil Humidity ◽

Sensing Data ◽

Multi Temporal ◽

Spatio Temporal

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Wheat Grain Protein Content Estimation Based on Multi-temporal Remote Sensing Data and Generalized Regression Neural Network

Computer and Computing Technologies in Agriculture V - IFIP Advances in Information and Communication Technology ◽

10.1007/978-3-642-27278-3_41 ◽

2012 ◽

pp. 381-389

Author(s):

Cunjun Li ◽

Qian Wang ◽

Jihua Wang ◽

Yan Wang ◽

Xiaodong Yang ◽

...

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Protein Content ◽

Remote Sensing Data ◽

Grain Protein Content ◽

Generalized Regression Neural Network ◽

Grain Protein ◽

Wheat Grain ◽

Sensing Data ◽

Multi Temporal

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A parametric model for classifying land cover and evaluating training data based on multi-temporal remote sensing data

ISPRS Journal of Photogrammetry and Remote Sensing ◽

10.1016/j.isprsjprs.2014.09.004 ◽

2014 ◽

Vol 97 ◽

pp. 219-228 ◽

Cited By ~ 11

Author(s):

Hunter Glanz ◽

Luis Carvalho ◽

Damien Sulla-Menashe ◽

Mark A. Friedl

Keyword(s):

Remote Sensing ◽

Land Cover ◽

Remote Sensing Data ◽

Parametric Model ◽

Training Data ◽

Sensing Data ◽

Multi Temporal

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Application of remote sensing data for oil spill monitoring in the Guanabara Bay, Rio de Janeiro, Brazil

IGARSS 2001. Scanning the Present and Resolving the Future. Proceedings. IEEE 2001 International Geoscience and Remote Sensing Symposium (Cat. No.01CH37217) ◽

10.1109/igarss.2001.976149 ◽

2002 ◽

Cited By ~ 4

Author(s):

C. Bentz ◽

F. Pellon de Miranda

Keyword(s):

Remote Sensing ◽

Oil Spill ◽

Rio De Janeiro ◽

Remote Sensing Data ◽

Guanabara Bay ◽

Sensing Data

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High-performance technology for indexing of high volumes of Earth remote sensing data

High-Performance Computing in Geoscience and Remote Sensing VII ◽

10.1117/12.2278190 ◽

2017 ◽

Cited By ~ 1

Author(s):

Valery V. Strotov ◽

Alexander I. Taganov ◽

Aleksandr N. Kolesenkov ◽

Boris V. Kostrov

Keyword(s):

Remote Sensing ◽

High Performance ◽

Remote Sensing Data ◽

Earth Remote Sensing ◽

Performance Technology ◽

Sensing Data

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Quantitative analysis of land use and land cover changes from the multi-temporal remote sensing data in the Bosten Lake Basin, Chinese Tian Shan

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/74/1/012011 ◽

2017 ◽

Vol 74 ◽

pp. 012011

Author(s):

A Maimaiti ◽

L M Wang ◽

F Yan ◽

J Zhang ◽

Y X Ma

Keyword(s):

Remote Sensing ◽

Land Use ◽

Quantitative Analysis ◽

Land Cover ◽

Remote Sensing Data ◽

Land Cover Changes ◽

Lake Basin ◽

Bosten Lake ◽

Sensing Data ◽

Multi Temporal

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Discharge estimation for medium-sized river using multi-temporal remote sensing data: a case study in Brazil

Hydrological Sciences Journal ◽

10.1080/02626667.2020.1808220 ◽

2020 ◽

Vol 65 (14) ◽

pp. 2402-2418

Author(s):

Évelyn Márcia Pôssa ◽

Philippe Maillard ◽

Lília Maria de Oliveira

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

Sensing Data ◽

Multi Temporal ◽

Discharge Estimation

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Multi-temporal remote sensing data to monitor terrestrial ecosystem responses to climate variations in Ghana

Geocarto International ◽

10.1080/10106049.2020.1723716 ◽

2020 ◽

pp. 1-17 ◽

Cited By ~ 1

Author(s):

Ram Avtar ◽

Ali P. Yunus ◽

Osamu Saito ◽

Ali Kharrazi ◽

Pankaj Kumar ◽

...

Keyword(s):

Remote Sensing ◽

Terrestrial Ecosystem ◽

Remote Sensing Data ◽

Climate Variations ◽

Ecosystem Responses ◽

Sensing Data ◽

Multi Temporal

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An Object-Based Approach for Forest-Cover Change Detection using Multi-Temporal High-Resolution Remote Sensing Data

2009 International Conference on Environmental Science and Information Application Technology ◽

10.1109/esiat.2009.163 ◽

2009 ◽

Cited By ~ 6

Author(s):

Jun Huang ◽

Youchuan Wan ◽

Shaohong Shen

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Change Detection ◽

Forest Cover ◽

Remote Sensing Data ◽

Forest Cover Change ◽

Sensing Data ◽

Object Based ◽

Multi Temporal

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Quantifying different types of urban growth and the change dynamic in Guangzhou using multi-temporal remote sensing data

International Journal of Applied Earth Observation and Geoinformation ◽

10.1016/j.jag.2011.12.012 ◽

2013 ◽

Vol 21 ◽

pp. 409-417 ◽

Cited By ~ 113

Author(s):

Cheng Sun ◽

Zhi-feng Wu ◽

Zhi-qiang Lv ◽

Na Yao ◽

Jian-bing Wei

Keyword(s):

Remote Sensing ◽

Urban Growth ◽

Remote Sensing Data ◽

Sensing Data ◽

Different Types ◽

Multi Temporal ◽

Change Dynamic

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