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Monitoring Regional Riparian Forest Cover Change Using Stratified Sampling and Multiresolution Imagery 1
Author(s) -
Claggett Peter R.,
Okay Judy A.,
Stehman Stephen V.
Publication year - 2010
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.2010.00424.x
Subject(s) - riparian zone , riparian buffer , watershed , riparian forest , environmental science , hydrology (agriculture) , sampling (signal processing) , land cover , bay , stratified sampling , streams , physical geography , geography , land use , geology , ecology , archaeology , computer science , computer network , statistics , geotechnical engineering , filter (signal processing) , mathematics , machine learning , habitat , computer vision , biology
Claggett, Peter R., Judy A. Okay, and Stephen V. Stehman, 2010. Monitoring Regional Riparian Forest Cover Change Using Stratified Sampling and Multiresolution Imagery. Journal of the American Water Resources Association (JAWRA) 46(2):334‐343. DOI: 10.1111/j.1752‐1688.2010.00424.x Abstract: The Chesapeake Bay watershed encompasses 165,760 km 2 of land area with 464,098 km of rivers and streams. As part of the Chesapeake Bay restoration effort, state and federal partners have committed to restoring 26,000 miles (41,843 km) of riparian forest buffers. Monitoring trends in riparian forest buffers over large areas is necessary to evaluate the efficacy of these restoration efforts. A sampling approach for estimating change in riparian forest cover from 1993/1994 to 2005 was developed and implemented in Anne Arundel County, Maryland, to exemplify a method that could be applied throughout the Bay watershed. All stream reaches in the county were stratified using forest cover change derived from Landsat imagery. A stratified random sample of 219 reaches was selected and forest cover change within the riparian buffer of each sampled reach was interpreted from high‐resolution aerial photography. The estimated footprint of gross change in riparian forest cover (i.e., the sum of gross gain and gross loss) for the county was 1.83% (SE = 0.22%). Stratified sampling taking advantage of a priori knowledge of locations of change proved to be a practical and efficient protocol for estimating riparian forest buffer change at the county scale and the protocol would readily extend to much broader scale monitoring.