Quantitative assessment of soil salinity using remote sensing data based on the artificial neural network, case study: Sharif Abad Plain, Central Iran

Modeling Earth Systems and Environment ◽

10.1007/s40808-020-01015-1 ◽

2020 ◽

Author(s):

Vahid Habibi ◽

Hasan Ahmadi ◽

Mohammad Jafari ◽

Abolfazl Moeini

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Artificial Neural Network ◽

Soil Salinity ◽

Quantitative Assessment ◽

Remote Sensing Data ◽

Central Iran ◽

Sensing Data ◽

Artificial Neural

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Quantitative assessment of soil salinity using multi-source remote sensing data based on the support vector machine and artificial neural network

International Journal of Remote Sensing ◽

10.1080/01431161.2018.1513180 ◽

2018 ◽

Vol 40 (1) ◽

pp. 284-306 ◽

Cited By ~ 11

Author(s):

Hong Jiang ◽

Yusufujiang Rusuli ◽

Tureniguli Amuti ◽

Qing He

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Artificial Neural Network ◽

Support Vector Machine ◽

Soil Salinity ◽

Quantitative Assessment ◽

Remote Sensing Data ◽

Support Vector ◽

Sensing Data ◽

Artificial Neural

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A Novel Method to Estimate Subpixel Temperature by Fusing Solar-Reflective and Thermal-Infrared Remote-Sensing Data With an Artificial Neural Network

IEEE Transactions on Geoscience and Remote Sensing ◽

10.1109/tgrs.2009.2033180 ◽

2010 ◽

Vol 48 (4) ◽

pp. 2170-2178 ◽

Cited By ~ 43

Author(s):

Guijun Yang ◽

Ruiliang Pu ◽

Wenjiang Huang ◽

Jihua Wang ◽

Chunjiang Zhao

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Artificial Neural Network ◽

Remote Sensing Data ◽

Thermal Infrared ◽

Thermal Infrared Remote Sensing ◽

Sensing Data ◽

Infrared Remote Sensing ◽

Novel Method ◽

Artificial Neural

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Grassland aboveground biomass retrieval from remote sensing data by using artificial neural network in temperate grassland, northern China

2014 The Third International Conference on Agro-Geoinformatics ◽

10.1109/agro-geoinformatics.2014.6910628 ◽

2014 ◽

Author(s):

Y. X. Jin ◽

B. Xu ◽

X. C. Yang ◽

Z. H. Qin ◽

J. Y. Li ◽

...

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Artificial Neural Network ◽

Aboveground Biomass ◽

Remote Sensing Data ◽

Northern China ◽

Temperate Grassland ◽

Sensing Data ◽

Artificial Neural

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Explicit Inverse of Soil Moisture Retrieval with an Artificial Neural Network Using Passive Microwave Remote Sensing Data

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2008.4779086 ◽

2008 ◽

Author(s):

Soo-See Chai ◽

Bert Veenendaal ◽

Geoff West ◽

Jeffrey P. Walker

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Artificial Neural Network ◽

Soil Moisture ◽

Remote Sensing Data ◽

Microwave Remote Sensing ◽

Passive Microwave ◽

Passive Microwave Remote Sensing ◽

Sensing Data ◽

Artificial Neural

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Fast and efficient land-cover classification of multispectral remote sensing data using artificial neural network techniques

Proceedings of 13th International Conference on Digital Signal Processing ◽

10.1109/icdsp.1997.628531 ◽

2002 ◽

Author(s):

N. Vassilas ◽

E. Charou ◽

S. Varoufakis

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Artificial Neural Network ◽

Land Cover ◽

Remote Sensing Data ◽

Land Cover Classification ◽

Sensing Data ◽

Multispectral Remote Sensing ◽

Artificial Neural

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Integrating artificial neural network and classical methods for unsupervised classification of optical remote sensing data

EURASIP Journal on Advances in Signal Processing ◽

10.1186/1687-6180-2012-165 ◽

2012 ◽

Vol 2012 (1) ◽

Cited By ~ 1

Author(s):

Ahmed AK Tahir

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Artificial Neural Network ◽

Remote Sensing Data ◽

Unsupervised Classification ◽

Optical Remote Sensing ◽

Sensing Data ◽

Artificial Neural

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An attempt for development of pavements temperature prediction models based on remote sensing data and artificial neural network

International Journal of Pavement Engineering ◽

10.1080/10298436.2021.1873334 ◽

2021 ◽

pp. 1-10

Author(s):

Ali Rigabadi ◽

Morteza Rezaei Zadeh Herozi ◽

Alireza Rezagholilou

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Artificial Neural Network ◽

Prediction Models ◽

Remote Sensing Data ◽

Temperature Prediction ◽

Sensing Data ◽

Artificial Neural

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Spectral – spatial urban target detection for hyperspectral remote sensing data using artificial neural network

The Egyptian Journal of Remote Sensing and Space Science ◽

10.1016/j.ejrs.2021.01.002 ◽

2021 ◽

Vol 24 (2) ◽

pp. 173-180

Author(s):

Shalini Gakhar ◽

Kailash Chandra Tiwari

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Artificial Neural Network ◽

Target Detection ◽

Remote Sensing Data ◽

Hyperspectral Remote Sensing ◽

Sensing Data ◽

Artificial Neural

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Modeling the potential of Sand and Dust Storm sources formation using time series of remote sensing data, fuzzy logic and artificial neural network (A Case study of Euphrates basin)

Journal of Geospatial Information Technology ◽

10.52547/jgit.8.3.61 ◽

2021 ◽

Vol 8 (3) ◽

pp. 61-82

Author(s):

Ramin Papi ◽

Meysam Argany ◽

Shahab Moradipour ◽

Masoud Soleimani ◽

◽

...

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Time Series ◽

Artificial Neural Network ◽

Fuzzy Logic ◽

Dust Storm ◽

Remote Sensing Data ◽

Sensing Data ◽

Sand And Dust Storm

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Artificial neural network model for identifying taxi gross emitter from remote sensing data of vehicle emission

Journal of Environmental Sciences ◽

10.1016/s1001-0742(07)60071-0 ◽

2007 ◽

Vol 19 (4) ◽

pp. 427-431 ◽

Cited By ~ 15

Author(s):

Jun ZENG ◽

Hua-fang GUO ◽

Yue-ming HU

Keyword(s):

Neural Network ◽

Remote Sensing ◽

Artificial Neural Network ◽

Network Model ◽

Neural Network Model ◽

Artificial Neural Network Model ◽

Remote Sensing Data ◽

Vehicle Emission ◽

Sensing Data ◽

Artificial Neural

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