衛星リモートセンシングを用いた琵琶湖におけるクロロフィル<i>a</i>濃度の推定
書誌事項
- タイトル別名
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- An Assessment of Chlorophyll <i>a </i>Concentration using Satellite Remote Sensing in Lake Biwa
- 小論文 衛星リモートセンシングを用いた琵琶湖におけるクロロフィルa濃度の推定
- ショウロンブン エイセイ リモートセンシング オ モチイタ ビワコ ニ オケル クロロフィル a ノウド ノ スイテイ
この論文をさがす
説明
<p>Recently, several issues involving phytoplankton communities have emerged in Lake Biwa. However, it is difficult to estimate detailed dynamics of phytoplankton distribution by only ship observation in Lake Biwa, the largest lake in Japan. Therefore, in this study, Moderate-resolution Imaging Spectroradiometer (MODIS) satellite data were used to estimate chlorophyll a concentrations in Lake Biwa. Moreover, we developed a method for improving the accuracy of chlorophyll a concentration (Chlsate) estimates using MODIS data. In-situ chlorophyll a concentrations and remote sensing reflectance values were measured from the littoral zone to offshore in the northern basin of Lake Biwa from 2012 to 2018. Remote sensing reflectance data (Rrssate: Level-2) from the MODIS instrument aboard the Aqua platform were used to estimate Chlsate. The Chlsate data obtained using the ocean chlorophyll three-band algorithm for MODIS (OC3M) tended to be overestimated and inaccurate (NMB: 708.7%, RMSE: 76.7mgm-3), mainly because Rrssate tended to be underestimated in the short-wavelength region. These results indicated that the standard NASA atmospheric correction algorithm could not be employed to estimate the chlorophyll a concentrations in the inland water body of Lake Biwa. Further, the reduced accuracy of the Chlsate estimates could also be attributed to an error in the OC3M algorithm. We therefore developed a correction method for Rrssate (488) and Rrssate (547) and optimized the coefficients of the OC3M algorithm using in-situ data. Consequently, the accuracy of the corrected Chlsate (NMB: 0.79%, RMSE: 2.14mgm-3) values estimated using our method were greatly improved compared to the uncorrected Chlsate values.</p>
収録刊行物
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- 日本リモートセンシング学会誌
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日本リモートセンシング学会誌 39 (2), 103-111, 2019-04-20
一般社団法人 日本リモートセンシング学会
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詳細情報 詳細情報について
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- CRID
- 1390282752348154880
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- NII論文ID
- 130007731747
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- NII書誌ID
- AN10035665
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- ISSN
- 18831184
- 02897911
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- NDL書誌ID
- 029744243
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- 本文言語コード
- ja
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- 資料種別
- journal article
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- データソース種別
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- JaLC
- IRDB
- NDLサーチ
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可