Beginning Google Maps Applications with PHP and Ajax: From Novice to Professional

Beginning Google Maps Applications with PHP and Ajax: From Novice to Professional

Jeffrey Sambells, Michael Purvis, Cameron Turner

Language: English

Pages: 384

ISBN: 1590597079

Format: PDF / Kindle (mobi) / ePub


Until recently, building interactive web-based mapping applications has been a cumbersome affair. This changed when Google released its powerful Maps API. Beginning Google Maps Applications with PHP and Ajax was written to help you take advantage of this technology in your own endeavorswhether you’re an enthusiast playing for fun or a professional building for profit. This book covers version 2 of the API, including Google’s new Geocoding service.

Authors Jeffrey Sambells, Cameron Turner, and Michael Purvis get rolling with examples that require hardly any code at all, but you’ll quickly become acquainted with many facets of the Maps API. They demonstrate powerful methods for simultaneously plotting large data sets, creating your own map overlays, and harvesting and geocoding sets of addresses. You’ll see how to set up alternative tile sets and where to access imagery to use for them. The authors even show you how to build your own geocoder from scratch, for those high-volume batch jobs.

As well as providing hands-on examples of real mapping projects, this book supplies a complete reference for the Maps API, along with the relevant aspects of JavaScript, CSS, PHP, and SQL. Visit the authors' website for additional tips and advice.

Computer Networks: A Systems Approach (5th Edition) (The Morgan Kaufmann Series in Networking)

Principles of Transaction Processing for the Systems Professional (1st Edition)

Automatic Design of Decision-Tree Induction Algorithms (Springer Briefs in Computer Science)

Fundamentals of Database Systems (7th Edition)

Advanced Operating Systems and Kernel Applications: Techniques and Technologies

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

7079ch04FINAL.qxd 7/28/06 12:48 PM Page 89 CHAPTER 4 ■ GEOCODING ADDRESSES Sunrise FL 33323 (954) 846-1880 store 26.156292 -80.316945 Ron Jon Surf Shop - Orlando

5160 International Drive

Orlando FL 32819 (407) 481-2555 store 28.469972

Address varchar(35) 15 PO Box varchar(20) 16 City varchar(20) 17 State char(2) Yes 18 Zip Code char(9) Yes 19 Attention varchar(35) Yes Yes Yes ■Note In the Entity Name column of the EN.dat file, there is often an equal sign (=). If you are going to build a map that has ownership search features (say for cellular carriers), you might want to import only the part after the equal sign, so that you can more accurately display results to your users. Table 5-3. CO.dat: Physical

. . . . . . . . . 324 class GMapOptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 GMapOptions Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 enum GMapPane . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328 GMapPane Constants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 class GKeyboardHandler . . . . . . . . . . . . . . . . .

know for sure what type of computer your users are going to have, so remember that not everyone is going to experience a map in the same way. For this chapter, we’ll focus on the limitations related to plotting larger than normal data sets on an average home computer. These issues are mainly performance-related and occur when there are too many GOverlay objects on the map at one time. Overlays are objects that build on the API’s GOverlay class and include any items added to the map using the

you’ll see the whole world at once, so plotting the data set using markers is still is going to go beyond the suggested 100 marker limit and cause problems, as shown in Figure 7-1. At closer zoom levels, say 5 or higher, you’ll have a smaller portion of the markers on the map at one time, and this method will work great, as shown in Figure 7-2. The same would apply for localized data dispersed across a smaller area or large, less dispersed data, but you’ll need to zoom in much closer to have

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