Geographic Techniques and Recent Applications of Remote Sensing to Landscape-Water Quality Studies

This article overviews recent advances in studies of landscape-water quality relationships using remote sensing techniques. With the increasing feasibility of using remotely-sensed data, landscape-water quality studies can nowbe more easily performed on regional, multi-state scales. Thetraditional method of relating land use and land cover to waterquality has been extended to include landscape pattern and otherlandscape information derived from satellite data. Three itemsare focused on in this article: 1) the increasing recognition ofthe importance of larger-scale studies of regional water qualitythat require a landscape perspective; 2) the increasingimportance of remotely sensed data, such as the imagery-derivednormalized difference vegetation index (NDVI) and vegetationphenological metrics derived from time-series NDVI data; and 3) landscape pattern. In some studies, using landscape patternmetrics explained some of the variation in water quality notexplained by land use/cover. However, in some other studies, theNDVI metrics were even more highly correlated to certain waterquality parameters than either landscape pattern metrics or landuse/cover proportions. Although studies relating landscape pattern metrics to water quality have had mixed results, thisrecent body of work applying these landscape measures andsatellite-derived metrics to water quality analysis hasdemonstrated their potential usefulness in monitoring watershedconditions across large regions.