<b>Guide to Geospatial Searching on Amazon CloudSearch</b>

Geospatial Searching is a specialized form of search operation, usually performed within a geographical context or in other words, ‘space.’ This form of search is an important aspect of AWS Solution Architect’s / Amazon CloudSearch because it allows you to filter and sort your search results based on location data. It uses a geospatial point type that represents a location in a 2-dimensional space.

Why it is important: It is crucial as it helps in locating the physical address, objects or occurrences in an area, helps in determining the routes and paths, and aids in resource management, among other uses. In the larger scheme of things, it can assist in disaster management, security, climate change studies, and other spatial dependent studies.

How it works: It indexes documents that have a specified 'latlon' field type which stores a location. You can perform three types of geo queries including: a bbox (bounding box) query that matches all the documents within a specified rectangular area, a distance query that matches every document within a certain distance from a specific point, and a polygon query that matches every document within a specified polygon.

Exam Tips - Answering Questions on Geospatial Searching: Always relate your answers with practical, real-world scenarios. For example, explaining how geospatial searching can be used in mapping applications to locate nearby places or objects. Understand the types of geo queries and when to use them. Lastly, be sure to familiarize yourself with how to index 'latlon' fields and how to work with geospatial data in CloudSearch.
Remember, effective application and understanding of the concepts distinguishes a simple test-taker from a solution architect.