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Python Geospatial Development
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This is a tutorial style book that will teach usage of Python tools for GIS using simple practical examples and then show you how to build a complete mapping application from scratch. The book assumes basic knowledge of Python. No knowledge of Open Source GIS is required. This book is useful for Python developers who want to get up to speed with Open Source GIS in order to build GIS applications or integrate Geo-Spatial features into their applications.
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10 von 11 Kunden fanden die folgende Rezension hilfreich
Superficial Coverage with Many Errors
28. September 2011
Format:Taschenbuch|Von Amazon bestätigter Kauf
If you know nothing at all about geographic information systems, this book will probably teach you something. If you know even a little bit, you'll be disappointed.
First, a serious problem with the Kindle edition needs mention. The book is written using Python code almost exclusively. But the Kindle doesn't format this code properly. There is no indentation - crucial for Python both in terms of readability and syntactically. Reading through examples that are more than two or three lines long is painfully awkward; longer examples are impossible to follow. You can download most of the code, but the code as found in the Kindle edition is worse than worthless.
Coverage of topics is, at best, superficial. Most of the chapters claiming to provide background on the foundations of geospatial science are very weak, and consist of nothing more than a listing of tools and libraries, with web site addresses offered along with advice to go there for any actual information.
A disturbing number of the Python examples, even the short ones that don't suffer from the aforementioned formatting problems, contain gross errors and will not run as written. Function names are spelled incorrectly, scoping qualifiers are omitted where they are required or are simply wrong. Claims of the author's expertise with Python are questionable, given the low quality of the examples. A comparison between Python and C++ early on in the book, purporting to show Python's superiority, clearly demonstrates the author's lack of knowledge about C++ - the example is written in C - and the difference between a language and its support libraries.
Overall, you can gain far more knowledge on just about any geospatial topic with a few minutes worth of web searching than you ever will from reading this book. Spend your money elsewhere.
First, a serious problem with the Kindle edition needs mention. The book is written using Python code almost exclusively. But the Kindle doesn't format this code properly. There is no indentation - crucial for Python both in terms of readability and syntactically. Reading through examples that are more than two or three lines long is painfully awkward; longer examples are impossible to follow. You can download most of the code, but the code as found in the Kindle edition is worse than worthless.
Coverage of topics is, at best, superficial. Most of the chapters claiming to provide background on the foundations of geospatial science are very weak, and consist of nothing more than a listing of tools and libraries, with web site addresses offered along with advice to go there for any actual information.
A disturbing number of the Python examples, even the short ones that don't suffer from the aforementioned formatting problems, contain gross errors and will not run as written. Function names are spelled incorrectly, scoping qualifiers are omitted where they are required or are simply wrong. Claims of the author's expertise with Python are questionable, given the low quality of the examples. A comparison between Python and C++ early on in the book, purporting to show Python's superiority, clearly demonstrates the author's lack of knowledge about C++ - the example is written in C - and the difference between a language and its support libraries.
Overall, you can gain far more knowledge on just about any geospatial topic with a few minutes worth of web searching than you ever will from reading this book. Spend your money elsewhere.
12 von 15 Kunden fanden die folgende Rezension hilfreich
A solid starter and a fine reference
31. Dezember 2010
Format:Taschenbuch
Erik Westra did an excellent job here: delivering a book that is both comprehensive and easy to read. Of course you already need to know a bit of Python to start, but all topics are explained very well and the book is very hands-on and task oriented.
The integration of Google maps in almost everything from telephone directories to pizza ordering services and on-line news services shows that there is a huge appeal to providing relevant geographical information in all sorts of contexts. But where do you start if you want to develop such functionality in Python? This book is certainly an excellent starting point.
Erik covers basically any subject from necessary geometrical concepts like units, datums and projections, just to get you started, to where to get the needed Python libraries and more importantly where to source good basic data like maps, positions of cities, shapes of countries and shorelines, etc, preferably from free sources. As geographical information used to be hard to get and often expensive, this attention to data sources is a very valuable part of the book. I particularly liked his extensive coverage of the collaborative Open Streetmap project ([...]), an extensive source of geographical data collected by a host of people around the world.
With these resources at hand the next steps are directed to manipulating geospatial data and generating all sorts of maps. The storage of data in databases with specific geospatial extensions to handle large datasets is covered in depth with specific examples for PostGIS, MySQL ans Sqlite. Also the rendering of maps is explained in a detailed manner focusing on the Mapnik library ([...]).
The final part of the book is dedicated to developing a web application to work interactively with map data. As performance is a key issue when working with large maps, even the implementation of a caching tile server (a server that generates small parts of a map on demand as you browse and zoom over the map) is implemented and explained in detail.
All in all a near perfect book for everybody who wants to start developing map based applications. Its solid coverage, excellent reference material and detailed explanations certainly make it a five out five for me.
The integration of Google maps in almost everything from telephone directories to pizza ordering services and on-line news services shows that there is a huge appeal to providing relevant geographical information in all sorts of contexts. But where do you start if you want to develop such functionality in Python? This book is certainly an excellent starting point.
Erik covers basically any subject from necessary geometrical concepts like units, datums and projections, just to get you started, to where to get the needed Python libraries and more importantly where to source good basic data like maps, positions of cities, shapes of countries and shorelines, etc, preferably from free sources. As geographical information used to be hard to get and often expensive, this attention to data sources is a very valuable part of the book. I particularly liked his extensive coverage of the collaborative Open Streetmap project ([...]), an extensive source of geographical data collected by a host of people around the world.
With these resources at hand the next steps are directed to manipulating geospatial data and generating all sorts of maps. The storage of data in databases with specific geospatial extensions to handle large datasets is covered in depth with specific examples for PostGIS, MySQL ans Sqlite. Also the rendering of maps is explained in a detailed manner focusing on the Mapnik library ([...]).
The final part of the book is dedicated to developing a web application to work interactively with map data. As performance is a key issue when working with large maps, even the implementation of a caching tile server (a server that generates small parts of a map on demand as you browse and zoom over the map) is implemented and explained in detail.
All in all a near perfect book for everybody who wants to start developing map based applications. Its solid coverage, excellent reference material and detailed explanations certainly make it a five out five for me.
4 von 5 Kunden fanden die folgende Rezension hilfreich
Not just for Python programmers
24. Juli 2011
Format:Taschenbuch
Last year I had a project in which I had to develop a GIS application.
I did it in Qt with C++. There is so much free software out there it was very hard to find the right api's and approach.
This book has arrived in the meantime and most of the Python libraries it refers to have their C++ counterpart, so the
book is also useful to C++ programmers.
I would have used MapNik as suggested by the book instead of developing my own map-drawing routines.
I would have also probably attempted a more ambitious project instead of what I did: for example I would have considered
a web application, as explained in the book.
I would have had a better understanding of spatial databases.
In short this book would have been a godsend.
Of course I might have been tempted to write the whole thing in Python, but either way this book is a tremendously helpful introduction to building your own GIS, but also to a lot of GIS concepts. The only niggle I have is that I think it could
explain the notion of datum a little better (but if you work your way through the book it sinks in anyway).
The author spends a fair deal of time explaining some of the traps in the field, or warning you about software that is badly documented.
This is an extremely useful book for someone who needs to build an application that is focused on some
features.
It starts off assuming you just know Python and you want to dive into GIS with no prior knowledge.
I cant think of anything that comes close to being that useful.
I did it in Qt with C++. There is so much free software out there it was very hard to find the right api's and approach.
This book has arrived in the meantime and most of the Python libraries it refers to have their C++ counterpart, so the
book is also useful to C++ programmers.
I would have used MapNik as suggested by the book instead of developing my own map-drawing routines.
I would have also probably attempted a more ambitious project instead of what I did: for example I would have considered
a web application, as explained in the book.
I would have had a better understanding of spatial databases.
In short this book would have been a godsend.
Of course I might have been tempted to write the whole thing in Python, but either way this book is a tremendously helpful introduction to building your own GIS, but also to a lot of GIS concepts. The only niggle I have is that I think it could
explain the notion of datum a little better (but if you work your way through the book it sinks in anyway).
The author spends a fair deal of time explaining some of the traps in the field, or warning you about software that is badly documented.
This is an extremely useful book for someone who needs to build an application that is focused on some
features.
It starts off assuming you just know Python and you want to dive into GIS with no prior knowledge.
I cant think of anything that comes close to being that useful.
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