東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Chlorophyll concentration estimates ...

Kouba, Eric.

FindBook

Google Book

Amazon

博客來

Chlorophyll concentration estimates for coastal water using pixel-based atmospheric correction of Landsat images.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Chlorophyll concentration estimates for coastal water using pixel-based atmospheric correction of Landsat images./
作者:	Kouba, Eric.
面頁冊數:	155 p.
附註:	Source: Masters Abstracts International, Volume: 53-06.
Contained By:	Masters Abstracts International53-06(E).
標題:	Remote sensing. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1565186
ISBN:	9781321194753

Chlorophyll concentration estimates for coastal water using pixel-based atmospheric correction of Landsat images.
Kouba, Eric.

Chlorophyll concentration estimates for coastal water using pixel-based atmospheric correction of Landsat images. - 155 p.

Source: Masters Abstracts International, Volume: 53-06.

Thesis (M.S.)--The University of Texas at San Antonio, 2014.

This item must not be sold to any third party vendors.

Ocean color analysis is more challenging for coastal regions than the global ocean due the effects of optical brightness, shallow and turbid water, higher phytoplankton growth rates, and the complex geometry of coastal bays and estuaries. Also, one of the key atmospheric correction assumptions (zero water leaving radiance in the near infrared) is not valid for these complex conditions. This makes it difficult to estimate the spectral radiance noise caused by atmospheric aerosols, which can vary rapidly with time and space.

ISBN: 9781321194753Subjects--Topical Terms:

535394
Remote sensing.

Chlorophyll concentration estimates for coastal water using pixel-based atmospheric correction of Landsat images.
LDR:02746nmm a2200325 4500 001 2061484
005 20151006081809.5
008 170521s2014 ||||||||||||||||| ||eng d
020 $a 9781321194753
035 $a (MiAaPQ)AAI1565186
035 $a AAI1565186
040 $a MiAaPQ $c MiAaPQ
100 1 $a Kouba, Eric. $3 3175750
245 1 0 $a Chlorophyll concentration estimates for coastal water using pixel-based atmospheric correction of Landsat images.
300 $a 155 p.
500 $a Source: Masters Abstracts International, Volume: 53-06.
500 $a Adviser: Hongjie Xie.
502 $a Thesis (M.S.)--The University of Texas at San Antonio, 2014.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a Ocean color analysis is more challenging for coastal regions than the global ocean due the effects of optical brightness, shallow and turbid water, higher phytoplankton growth rates, and the complex geometry of coastal bays and estuaries. Also, one of the key atmospheric correction assumptions (zero water leaving radiance in the near infrared) is not valid for these complex conditions. This makes it difficult to estimate the spectral radiance noise caused by atmospheric aerosols, which can vary rapidly with time and space.
520 $a This study conducts pixel-based atmospheric correction of Landsat-7 ETM+ images over the Texas coast. Precise satellite orbit data, operational weather data, and climate data are combined to create interpolated arrays of viewing angles and atmospheric profiles. These arrays vary with time and location, allowing calculation of the Rayleigh and aerosol radiances separately for all pixels. The resulting normalized water-leaving radiances are then compared with in situ chlorophyll fluorescence measurements from five locations inside a set of Texas coastal bays: the Mission-Aransas National Estuarine Research Reserve.
520 $a Curve-fitting analysis shows it is possible to estimate chlorophyll-a surface area concentrations by using ETM+ water-leaving radiance values and a third-order polynomial equation. Two pairs of ETM+ bands are identified as inputs (Bands 1 and 3, and the Log10 values of Bands 3 and 4), both achieving good performance (R2 of 0.69). Further research efforts are recommended to obtain additional data, identify better curve fitting equations, and potentially extend the radiative transfer model into the water column.
590 $a School code: 1283.
650 4 $a Remote sensing. $3 535394
650 4 $a Atmospheric sciences. $3 3168354
690 $a 0799
690 $a 0725
710 2 $a The University of Texas at San Antonio. $b Geological Sciences. $3 3173841
773 0 $t Masters Abstracts International $g 53-06(E).
790 $a 1283
791 $a M.S.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1565186