Over the past three decades, spatial information has become prevalent in numerous applications. To meet the demands of these applications, Spatial Information Management Systems have achieved greatly in storing, retrieving and processing spatial information. The continuing advancement of technologies, however, pushes the need for accessing spatial information in drastically different environments. At one end of the spectrum, the widely popular Google Map and associated Cloud Computing technologies demonstrate the power of accessing spatial information in resource-rich environments. At the other end, the growing location-based applications in Apple iPhone and Google G1 phone platforms highlight the huge potential of accessing spatial information in resource-constrained environments. This monograph is the first of its kind in analyzing spatial index structures from both energy and performance angles in resource-constrained environments. In addition to developing effective techniques to address general selectivity problems, this monograph also examines issues in accessing spatial information in resource-rich environments including clusters and the Web.