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Radiometric modeling of mechanical d...

Rochester Institute of Technology., Imaging Science.

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Radiometric modeling of mechanical draft cooling towers to assist in the extraction of their absolute temperature from remote thermal imagery.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Radiometric modeling of mechanical draft cooling towers to assist in the extraction of their absolute temperature from remote thermal imagery./
作者:	Montanaro, Matthew.
面頁冊數:	209 p.
附註:	Adviser: Carl Salvaggio.
Contained By:	Dissertation Abstracts International70-04B.
標題:	Remote Sensing. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3354721
ISBN:	9781109118971

Radiometric modeling of mechanical draft cooling towers to assist in the extraction of their absolute temperature from remote thermal imagery.
Montanaro, Matthew.

Radiometric modeling of mechanical draft cooling towers to assist in the extraction of their absolute temperature from remote thermal imagery. - 209 p.

Adviser: Carl Salvaggio.

Thesis (Ph.D.)--Rochester Institute of Technology, 2009.

Determination of the internal temperature of a mechanical draft cooling tower (MDCT) from remotely-sensed thermal imagery is important for many applications that provide input to energy-related process models. The problem of determining the temperature of an MDCT is unique due to the geometry of the tower and due to the exhausted water vapor plume. The radiance leaving the tower is dependent on the optical and thermal properties of the tower materials ( i.e., emissivity, BRDF, temperature, etc.) as well as the internal geometry of the tower. The tower radiance is then propagated through the exhaust plume and through the atmosphere to arrive at the sensor. The expelled effluent from the tower consists of a warm plume with a higher water vapor concentration than the ambient atmosphere. Given that a thermal image has been atmospherically compensated, the remaining sources of error in extracted tower temperature due to the exhausted plume and the tower geometry must be accounted for. A temperature correction factor due to these error sources is derived through the use of three-dimensional radiometric modeling. A range of values for each important parameter are modeled to create a target space (i.e. , look-up table) that predicts the internal MDCT temperature for every combination of parameter values. The look-up table provides data for the creation of a fast-running parameterized model. This model, along with user knowledge of the scene, provides a means to convert the image-derived apparent temperature into the estimated absolute temperature of an MDCT.

ISBN: 9781109118971Subjects--Topical Terms:

1018559
Remote Sensing.

Radiometric modeling of mechanical draft cooling towers to assist in the extraction of their absolute temperature from remote thermal imagery.
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502 $a Thesis (Ph.D.)--Rochester Institute of Technology, 2009.
520 $a Determination of the internal temperature of a mechanical draft cooling tower (MDCT) from remotely-sensed thermal imagery is important for many applications that provide input to energy-related process models. The problem of determining the temperature of an MDCT is unique due to the geometry of the tower and due to the exhausted water vapor plume. The radiance leaving the tower is dependent on the optical and thermal properties of the tower materials ( i.e., emissivity, BRDF, temperature, etc.) as well as the internal geometry of the tower. The tower radiance is then propagated through the exhaust plume and through the atmosphere to arrive at the sensor. The expelled effluent from the tower consists of a warm plume with a higher water vapor concentration than the ambient atmosphere. Given that a thermal image has been atmospherically compensated, the remaining sources of error in extracted tower temperature due to the exhausted plume and the tower geometry must be accounted for. A temperature correction factor due to these error sources is derived through the use of three-dimensional radiometric modeling. A range of values for each important parameter are modeled to create a target space (i.e. , look-up table) that predicts the internal MDCT temperature for every combination of parameter values. The look-up table provides data for the creation of a fast-running parameterized model. This model, along with user knowledge of the scene, provides a means to convert the image-derived apparent temperature into the estimated absolute temperature of an MDCT.
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