Advances in Remote Sensing

Advances in Remote Sensing

ISSN Print: 2169-267X
ISSN Online: 2169-2688
www.scirp.org/journal/ars
E-mail: ars@scirp.org
"Production of Multi-Features Driven Nationwide Vegetation Physiognomic Map and Comparison to MODIS Land Cover Type Product"
written by Ram C. Sharma, Keitarou Hara, Hidetake Hirayama, Ippei Harada, Daisuke Hasegawa, Mizuki Tomita, Jong Geol Park, Ichio Asanuma, Kevin M. Short, Masatoshi Hara, Yoshihiko Hirabuki, Michiro Fujihara, Ryutaro Tateishi,
published by Advances in Remote Sensing, Vol.6 No.1, 2017
has been cited by the following article(s):
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[5] Characterization of Vegetation Physiognomic Types Using Bidirectional Reflectance Data
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[7] A machine learning and cross-validation approach for the discrimination of vegetation physiognomic types using satellite based multispectral and multitemporal data
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[8] High-Resolution Vegetation Mapping in Japan by Combining Sentinel-2 and Landsat 8 Based Multi-Temporal Datasets through Machine Learning and Cross …
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[9] A machine learning and cross-validation approach for the discrimination of vegetation physiognomic types using satellite based multispectral and …
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[10] Research Article A Machine Learning and Cross-Validation Approach for the Discrimination of Vegetation Physiognomic Types Using Satellite Based …
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[11] İç Anadolu Bölgesi'ndeki Tarım Alanı Değişimlerinin Modis Uydu Verisi ile İzlenmesi
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