Geographic information systems (GIS) have become increasingly important in helping us understand complex social, economic, and natural dynamics where spatial components play a key role. The critical algorithms used in GIS, however, are notoriously difficult to both teach and understand, in part due to the lack of a coherent representation. GIS Algorithms attempts to address this problem by combining rigorous formal language with example case studies and student exercises. Using Python code throughout, Xiao breaks the subject down into three fundamental areas: • Geometric Algorithms • Spatial Indexing • Spatial Analysis and Modelling With its comprehensive coverage of the many algorithms involved, GIS Algorithms is a key new textbook in this complex and critical area of geography.
Chapter 4: Indexing
Erase the Root – no Tree –
Thee – then – no me –
The Heavens stripped –
Eternity’s vast pocket, picked –
There are many cases when we need to find a subset of spatial information for various purposes. For example, to interpolate the measure of a variable at a location where we do not have the observation, we need to borrow the observed values from a number of nearby locations. More generally, this can be done when we want to know about the points near any given location. In another example, to quickly pull up information about the polygon we clicked on the map, we need to find the polygon that contains the click point and ignore the many other polygons that ...