Data mining, GIS and remote sensing: Application in wetland hydrological investigation

The Prairie Pothole Region in the United States contains millions of seasonal, semipermanent, or permanent lakes and wetlands that typically range in size from 0.1 to 10 hectares. These lakes and wetlands are vulnerable to climate change, especially in our study area of South Dakota, in which a period of deluge following a sharp drought considerably expanded the areal extent of prairie pothole lakes during the last decade of the twentieth century. Preliminary estimates of lake areas, determined using Landsat 5 and 7 images, had appreciable errors especially for the smallest of these lakes. We developed a new sub-pixel approach integrated with a Classification and Regression Tree (CART) model using a Geographical Information System (GIS) to quantify mixed water pixels along lake boundaries to improve the area estimations for pothole lakes. Errors in estimated area were typically 10 percent or less for lakes greater than 1 hectare in size.;An analysis of lakes in our study area using GIS and remote sensing technologies demonstrates how total areas and numbers of lakes and wetlands in different sizes changed with the transition from drought to deluge. Small lakes exhibited a distinct seasonal variation in contrast to large lakes that tended to follow longer trends more broadly. The total areas and numbers of small lakes and wetlands are mostly related with the 6-month evaportranspiration (ET) variation, while the variables of large lakes are highly correlated with the mean Palmer Drought Severity Index (PDSI) of a 48-month time period. We also examine the response of a complex lake/wetland system to variations in climate. The focus is on lakes and wetlands within the Prairie Coteau Region, which is part of the larger Prairie Pothole region of the Central Plains of North America. Information on lake size was enumerated from satellite images and aerial photos and yielded power-law relationships for different hydrological conditions. Of particular interest was a recent drought and deluge sequence, 1988-1992 and 1993-1998. Results showed that the pothole lakes followed well-defined power laws that changed annually and interannually as a function of climate. The power laws for spring seasons in years 1987, 1990, 1992, 1997, and 2002 yielded a relatively constant slope. However, slopes changed with time within each year. The lines produced from Landsat images and aerial photos indicated scale independence for lakes with a size from 100 m2 to more than 40,000 m2. This fractal tendency and aerial photos taken in 1939/7/29 provides an approach to reconstructing the distribution of pothole lakes back to 1939, the end of the "Dustbowl" drought. The study shows that smaller lakes are profoundly affected seasonally by the strength of the spring snow melt and evapotranspiration. Larger lakes are influenced more slowly by longer term periods of drought and deluge.;Using the TOPEX radar altimeter for land cover studies has been of great interest due to the TOPEX near global coverage and its consistent availability of waveform data for about one and a half decades from 1992 to 2005. However, the complexity of the TOPEX Sensor Data Records (SDRs) makes the Classification of land cover using particularly difficult. In this study, regression tree and artificial neural networks as the most powerful algorithms in data mining are investigated for water proportion assessment over Lake of the Woods area using TOPEX SDR waveform data. Results demonstrate that these data mining technologies have provided insight into identifying water proportion from the TOPEX radar waveforms, with predicted errors controlled in a reasonable range. The distinct tailing pattern of radar echoes from water plays an important role in water ratio regression.