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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Neste artigo, apresentamos um método de previsão para a visão do Monte. Fuji como uma aplicação de dados de observação da Terra (EOD) obtidos por satélites. Definimos o índice de visualização do Monte Fuji (FVI) que caracteriza a aparência da montanha em um determinado dia, com base em dados fotográficos produzidos por uma observação de ponto fixo. Um preditor de longo prazo do FVI, variando de 0 a 30 dias, foi construído através de regressão de máquina de vetores de suporte em dados climáticos e de observação da Terra. Verificou-se que a concentração de massa de aerossol (AMC) melhora o desempenho da previsão, e tal desempenho é particularmente significativo no intervalo de longo prazo.
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Mitsuru KAKIMOTO, Hisaaki HATANO, Yosoko NISHIZAWA, "Forecasting the View of Mt. Fuji Using Earth Observation Data" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 8, pp. 1551-1560, August 2009, doi: 10.1587/transinf.E92.D.1551.
Abstract: In this paper, we present a forecasting method for the view of Mt. Fuji as an application of Earth observation data (EOD) obtained by satellites. We defined the Mt. Fuji viewing index (FVI) that characterises how well the mountain looks on a given day, based on photo data produced by a fixed-point observation. A long-term predictor of FVI, ranging from 0 to 30 days, was constructed through support vector machine regression on climate and earth observation data. It was found that the aerosol mass concentration (AMC) improves prediction performance, and such performance is particularly significant in the long-term range.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.1551/_p
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@ARTICLE{e92-d_8_1551,
author={Mitsuru KAKIMOTO, Hisaaki HATANO, Yosoko NISHIZAWA, },
journal={IEICE TRANSACTIONS on Information},
title={Forecasting the View of Mt. Fuji Using Earth Observation Data},
year={2009},
volume={E92-D},
number={8},
pages={1551-1560},
abstract={In this paper, we present a forecasting method for the view of Mt. Fuji as an application of Earth observation data (EOD) obtained by satellites. We defined the Mt. Fuji viewing index (FVI) that characterises how well the mountain looks on a given day, based on photo data produced by a fixed-point observation. A long-term predictor of FVI, ranging from 0 to 30 days, was constructed through support vector machine regression on climate and earth observation data. It was found that the aerosol mass concentration (AMC) improves prediction performance, and such performance is particularly significant in the long-term range.},
keywords={},
doi={10.1587/transinf.E92.D.1551},
ISSN={1745-1361},
month={August},}
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TY - JOUR
TI - Forecasting the View of Mt. Fuji Using Earth Observation Data
T2 - IEICE TRANSACTIONS on Information
SP - 1551
EP - 1560
AU - Mitsuru KAKIMOTO
AU - Hisaaki HATANO
AU - Yosoko NISHIZAWA
PY - 2009
DO - 10.1587/transinf.E92.D.1551
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2009
AB - In this paper, we present a forecasting method for the view of Mt. Fuji as an application of Earth observation data (EOD) obtained by satellites. We defined the Mt. Fuji viewing index (FVI) that characterises how well the mountain looks on a given day, based on photo data produced by a fixed-point observation. A long-term predictor of FVI, ranging from 0 to 30 days, was constructed through support vector machine regression on climate and earth observation data. It was found that the aerosol mass concentration (AMC) improves prediction performance, and such performance is particularly significant in the long-term range.
ER -