Yi-Hwa Wu

By Yi-Hwa (Eva) Wu and Ming-Chih Hung

Spatial interpolation has been widely and commonly used in many studies to create surface data based on a set of sampled points, such as soil properties, temperature, and precipitation. Currently, there are many commercial Geographic Information System (GIS) or statistics software offering spatial interpolation functions, such as inverse distance weighted (IDW), kriging, spline, and others. To date, there is no “rule of thumb” on the most appropriate spatial interpolation techniques for certain situations, though general suggestions have been published. Many studies rely on quantitative assessment to determine the performance of spatial interpolation techniques. Most quantitative assessment methods provide a numeric index for the overall performance of an interpolated surface. Although it is objective and convenient, there are many facts or trends not captured by quantitative assessments. This study used 2D visualization and 3D visualization to identify trends not evident in quantitative assessment. This study also presented a special case, a closed system in which all interpolated surfaces should sum up to 100%, to demonstrate the interaction between interpolated surfaces that were created separately and independently.

Part of the book: Applications of Spatial Statistics

By Yi-Hwa Wu, Ming-Chih Hung, Jeff Thomas and Maureen Gallagher

Aquatic invasive plants are well known for causing severe impacts to local ecosystems, such as degrading water quality, decreasing biodiversity, consuming natural resources, among other impacts. Major water bodies in US had experienced such impacts. To mitigate such impacts, the U.S. Fish and Wildlife Service and the Ohio River Valley Water Sanitation Commission had put significant amounts of effort toward identifying and removing aquatic invasive plants along the Ohio River shorelines. Field work played a significant role in such identification and removal, but at great expense on labor and time. River systems are dynamic, coupled with similarities between spectral reflectance from submerged plants and background water bodies, limited success was reported from literature regarding the use of remote sensing with selected images on detecting aquatic plants. This study utilized Google Earth historical images between 2003 and 2015 along a section of Ohio River known as the Racine Pool and examined and recorded the appearances of aquatic plants. Visible aquatic plants or suspicious submerged objects were digitized and converted to ESRI shapefiles and grids. Spatial analyses and overlays were then performed between grids to derive a map showing frequency of appearance. Such frequency of appearance may serve the purposes of predicting future sighting and/or guides for directing field work in hopes to save labor and time.

Part of the book: Recent Advances and Applications in Remote Sensing