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Identification of hydrologically act...

Cornell University.

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Identification of hydrologically active areas in the landscape using satellite imagery.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Identification of hydrologically active areas in the landscape using satellite imagery./
作者:	de Alwis, Dilkushi Anuja.
面頁冊數:	128 p.
附註:	Adviser: Tammo Steenhuis.
Contained By:	Dissertation Abstracts International68-03B.
標題:	Environmental Sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3254659

Identification of hydrologically active areas in the landscape using satellite imagery.
de Alwis, Dilkushi Anuja.

Identification of hydrologically active areas in the landscape using satellite imagery. - 128 p.

Adviser: Tammo Steenhuis.

Thesis (Ph.D.)--Cornell University, 2007.

The reduction of non-point source (NPS) pollution is a focus of many watershed management programs. In temperate humid climates most NPS pollution originates from Hydrologically Active Areas (HAAS) which are wetter areas in the landscape that saturate during rainstorms and generate most surface runoff. Successful implementation of best management practices for reducing NPS pollution requires knowledge of the locations of the HAAs. Remotely sensed data is a source of spatial information and could be used to identify HAAs, but there is not a satisfactory procedure for doing so. The objective of this dissertation is to develop such a procedure by first determining landcovers types and then using the temporal variability within a landcover type to identify HAAs.Subjects--Topical Terms:

676987
Environmental Sciences.

Identification of hydrologically active areas in the landscape using satellite imagery.
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100 1 $a de Alwis, Dilkushi Anuja. $3 1057806
245 1 0 $a Identification of hydrologically active areas in the landscape using satellite imagery.
300 $a 128 p.
500 $a Adviser: Tammo Steenhuis.
500 $a Source: Dissertation Abstracts International, Volume: 68-03, Section: B, page: 1522.
502 $a Thesis (Ph.D.)--Cornell University, 2007.
520 $a The reduction of non-point source (NPS) pollution is a focus of many watershed management programs. In temperate humid climates most NPS pollution originates from Hydrologically Active Areas (HAAS) which are wetter areas in the landscape that saturate during rainstorms and generate most surface runoff. Successful implementation of best management practices for reducing NPS pollution requires knowledge of the locations of the HAAs. Remotely sensed data is a source of spatial information and could be used to identify HAAs, but there is not a satisfactory procedure for doing so. The objective of this dissertation is to develop such a procedure by first determining landcovers types and then using the temporal variability within a landcover type to identify HAAs.
520 $a In the first two chapters a landcover map was developed for three small watersheds under 50 km2 and one larger (approximately 15,170 km2) area using greenness variation expressed as NDVI values in seven remotely-sensed Landsat 7 ETM+ images. Each image represented a distinct plant growth stage. The NDVI data were clustered into homogeneous regions having similar NDVI patterns over time and assigned to a landcover type. The derived landcover map for the three small watersheds compared well with existing landcover maps and low-altitude air-borne imagery. The same method was then applied to the larger area. After clouds and lakes were taken out, a landcover map was produced with an accuracy of 69% when compared to field data.
520 $a In the last chapter the temporal variability within a landcover type of a remotely sensed wetness index was employed to determine the HAAS by grouping areas that behaved alike. The resulting HAA map agreed well with both observed and spatially distributed computer simulated moisture contents. In summary, the procedure for finding HAAS is a promising tool for delineating runoff producing areas in the landscape.
590 $a School code: 0058.
650 4 $a Environmental Sciences. $3 676987
650 4 $a Hydrology. $3 545716
650 4 $a Remote Sensing. $3 1018559
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791 $a Ph.D.
792 $a 2007
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