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Learning geospatial analysis with Python / / Joel Lawhead
| Learning geospatial analysis with Python / / Joel Lawhead |
| Autore | Lawhead Joel |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Birmingham : , : Packt Publishing, , 2013 |
| Descrizione fisica | 1 online resource (364 p.) |
| Soggetto topico |
Geospatial data
Python (Computer program language) |
| ISBN |
1-68015-354-4
1-306-18859-8 1-78328-114-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910788935703321 |
Lawhead Joel
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||
| Birmingham : , : Packt Publishing, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Learning geospatial analysis with Python / / Joel Lawhead
| Learning geospatial analysis with Python / / Joel Lawhead |
| Autore | Lawhead Joel |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Birmingham : , : Packt Publishing, , 2013 |
| Descrizione fisica | 1 online resource (364 p.) |
| Disciplina | 910.285 |
| Soggetto topico |
Geospatial data
Python (Computer program language) |
| ISBN |
1-68015-354-4
1-306-18859-8 1-78328-114-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Learning Geospatial Analysis with Python -- Table of Contents -- Learning Geospatial Analysis with Python -- Credits -- About the Author -- About the Reviewers -- www.PacktPub.com -- Support files, eBooks, discount offers and more -- Why Subscribe? -- Free Access for Packt account holders -- Preface -- What this book covers -- What you need for this book -- Who this book is for -- Conventions -- Reader feedback -- Customer support -- Downloading the example code -- Errata -- Piracy -- Questions -- 1. Learning Geospatial Analysis with Python -- Geospatial analysis and our world -- Beyond politics -- History of geospatial analysis -- Geographic Information Systems -- Remote sensing -- Elevation data -- Computer-aided drafting -- Geospatial analysis and computer programming -- Object-oriented programming for geospatial analysis -- Importance of geospatial analysis -- Geographic Information System concepts -- Thematic maps -- Spatial databases -- Spatial indexing -- Metadata -- Map projections -- Rendering -- Raster data concepts -- Images as data -- Remote sensing and color -- Common vector GIS concepts -- Data structures -- Buffer -- Dissolve -- Generalize -- Intersection -- Merge -- Point in polygon -- Union -- Join -- Geospatial rules about polygons -- Common raster data concepts -- Band math -- Change detection -- Histogram -- Feature extraction -- Supervised classification -- Unsupervised classification -- Creating the simplest possible Python GIS -- Getting started with Python -- Building SimpleGIS -- Summary -- 2. Geospatial Data -- Data structures -- Common traits -- Geo-location -- Subject information -- Spatial indexing -- Indexing algorithms -- Quad-Tree index -- R-Tree index -- Grids -- Overviews -- Metadata -- File structure -- Vector data -- Shapefiles -- CAD files -- Tag and markup-based formats -- GeoJSON -- Raster data.
TIFF files -- JPEG, GIF, BMP, and PNG -- Compressed formats -- ASCII GRIDS -- World files -- Point cloud data -- Summary -- 3. The Geospatial Technology Landscape -- Data access -- GDAL -- OGR -- Computational geometry -- PROJ.4 -- CGAL -- JTS -- GEOS -- PostGIS -- Other spatially-enabled databases -- Oracle spatial and graph -- ArcSDE -- Microsoft SQL Server -- MySQL -- SpatiaLite -- Routing -- Esri Network Analyst and Spatial Analyst -- pgRouting -- Desktop tools -- Quantum GIS -- OpenEV -- GRASS GIS -- uDig -- gvSIG -- OpenJUMP -- Google Earth -- NASA World Wind -- ArcGIS -- Metadata management -- GeoNetwork -- CatMDEdit -- Summary -- 4. Geospatial Python Toolbox -- Installing third-party Python modules -- Installing GDAL -- Windows -- Linux -- Mac OS X -- Python networking libraries for acquiring data -- Python urllib module -- FTP -- ZIP and TAR files -- Python markup and tag-based parsers -- The minidom module -- ElementTree -- Building XML -- WKT -- Python JSON libraries -- json module -- geojson module -- OGR -- PyShp -- dbfpy -- Shapely -- GDAL -- NumPy -- PIL -- PNGCanvas -- PyFPDF -- Spectral Python -- Summary -- 5. Python and Geographic Information Systems -- Measuring distance -- Pythagorean theorem -- Haversine formula -- Vincenty formula -- Coordinate conversion -- Reprojection -- Editing shapefiles -- Accessing the shapefile -- Reading shapefile attributes -- Reading shapefile geometry -- Changing a shapefile -- Adding fields -- Merging shapefiles -- Splitting shapefiles -- Subsetting spatially -- Performing selections -- Point in polygon formula -- Attribute selections -- Creating images for visualization -- Dot density calculations -- Choropleth maps -- Using spreadsheets -- Using GPS data -- Summary -- 6. Python and Remote Sensing -- Swapping image bands -- Creating histograms -- Performing a histogram stretch -- Clipping images. Classifying images -- Extracting features from images -- Change detection -- Summary -- 7. Python and Elevation Data -- ASCII Grid files -- Reading grids -- Writing grids -- Creating a shaded relief -- Creating elevation contours -- Working with LIDAR -- Creating a grid from LIDAR -- Using PIL to visualize LIDAR -- Creating a Triangulated Irregular Network (TIN) -- Summary -- 8. Advanced Geospatial Python Modelling -- Creating an NDVI -- Setting up the framework -- Loading the data -- Rasterizing the shapefile -- Clipping the bands -- Using the NDVI formula -- Classifying the NDVI -- Additional functions -- Loading the NDVI -- Creating classes -- Creating a flood inundation model -- The flood fill function -- Making a flood -- Least cost path analysis -- Setting up the test grid -- The simple A* algorithm -- Generating the test path -- Viewing the test output -- The real-world example -- Loading the grid -- Defining the helper functions -- The real-world A* algorithm -- Generating a real-world path -- Summary -- 9. Real-Time Data -- Tracking vehicles -- Nextbus agency list -- Nextbus route list -- Nextbus vehicle locations -- Mapping Nextbus locations -- Storm chasing -- Summary -- 10. Putting It All Together -- A typical GPS report -- Working with GPX-Reporter.py -- Stepping through the program -- Initial setup -- Working with utility functions -- Parsing the GPX -- Getting the bounding box -- Downloading OpenStreetMap images -- Creating the hillshade -- Creating maps -- Measuring elevation -- Measuring distance -- Retrieving weather data -- Summary -- Index. |
| Record Nr. | UNINA-9910826994103321 |
|
Lawhead Joel
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| Birmingham : , : Packt Publishing, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Learning R for geospatial analysis : leverage the power of R to elegantly manage crucial geospatial analysis tasks / / Michael Dorman
| Learning R for geospatial analysis : leverage the power of R to elegantly manage crucial geospatial analysis tasks / / Michael Dorman |
| Autore | Dorman Michael |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Birmingham, England : , : Packt Publishing, , 2014 |
| Descrizione fisica | 1 online resource (364 p.) |
| Disciplina | 025.06910285 |
| Collana | Community Experience Distilled |
| Soggetto topico |
Geospatial data
Spatial analysis (Statistics) |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-78398-437-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: The R Environment; Installing R and using the command line; Downloading R; Installing R; Using R as a calculator; Coding with R beyond the command line; Approaches to editing R code; Installation of RStudio; Using RStudio; Evaluating expressions; Using arithmetic and logical operators; Using functions; Dealing with warning and error messages; Getting help; Exploring the basic object types in R; Everything is an object; Storing data in data structures
Calling functions to perform operationsA short sample session; Summary; Chapter 2: Working with Vectors and Time Series; Vectors - the basic data structures in R; Different types of vectors; Using the assignment operator to save an object; Removing objects from memory; Summarizing vector properties; Element-by-element operations on vectors; The recycling principle; Using functions with several parameters; Supplying more than one argument in a function call; Creating default vectors; Creating repetitive vectors; Substrings; Creating subsets of vectors Subsetting with numeric vectors of indicesSubsetting with logical vectors; Dealing with missing values; Missing values and their effect on data; Detecting missing values in vectors; Performing calculations on vectors with missing values; Writing new functions; Defining our own functions; Setting default values for the arguments; Working with dates and time series; Specialized time series classes in R; Reading climatic data from a CSV file; Converting character values to dates; Examining our time series; Creating subsets based on dates; Introducing graphical functions Displaying vectors using base graphicsSaving graphical output; The main graphical systems in R; Summary; Chapter 3: Working with Tables; Using the data.frame class to represent tabular data; Creating a table from separate vectors; Creating a table from a CSV file; Examining the structure of a data.frame object; Subsetting data.frame objects; Calculating new data fields; Writing a data.frame object to a CSV file; Controlling code execution; Conditioning execution with conditional statements; Repeatedly executing code sections with loops Automated calculations using the apply family of functionsApplying a function on separate parts of a vector; Applying a function on rows or columns of a table; Inference from tables by joining, reshaping, and aggregating; Using contributed packages; Shifting between long and wide formats using melt and dcast; Aggregating with ddply; Joining tables with join; Summary; Chapter 4: Working with Rasters; Using the matrix and array classes; Representing two-dimensional data with a matrix; Representing more than two dimensions with an array; Data structures for rasters in the raster package Creating single band rasters |
| Record Nr. | UNINA-9910459757303321 |
|
Dorman Michael
|
||
| Birmingham, England : , : Packt Publishing, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Learning R for geospatial analysis : leverage the power of R to elegantly manage crucial geospatial analysis tasks / / Michael Dorman
| Learning R for geospatial analysis : leverage the power of R to elegantly manage crucial geospatial analysis tasks / / Michael Dorman |
| Autore | Dorman Michael |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Birmingham, England : , : Packt Publishing, , 2014 |
| Descrizione fisica | 1 online resource (364 p.) |
| Disciplina | 025.06910285 |
| Collana | Community Experience Distilled |
| Soggetto topico |
Geospatial data
R (Computer program language) Spatial analysis (Statistics) |
| ISBN | 1-78398-437-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: The R Environment; Installing R and using the command line; Downloading R; Installing R; Using R as a calculator; Coding with R beyond the command line; Approaches to editing R code; Installation of RStudio; Using RStudio; Evaluating expressions; Using arithmetic and logical operators; Using functions; Dealing with warning and error messages; Getting help; Exploring the basic object types in R; Everything is an object; Storing data in data structures
Calling functions to perform operationsA short sample session; Summary; Chapter 2: Working with Vectors and Time Series; Vectors - the basic data structures in R; Different types of vectors; Using the assignment operator to save an object; Removing objects from memory; Summarizing vector properties; Element-by-element operations on vectors; The recycling principle; Using functions with several parameters; Supplying more than one argument in a function call; Creating default vectors; Creating repetitive vectors; Substrings; Creating subsets of vectors Subsetting with numeric vectors of indicesSubsetting with logical vectors; Dealing with missing values; Missing values and their effect on data; Detecting missing values in vectors; Performing calculations on vectors with missing values; Writing new functions; Defining our own functions; Setting default values for the arguments; Working with dates and time series; Specialized time series classes in R; Reading climatic data from a CSV file; Converting character values to dates; Examining our time series; Creating subsets based on dates; Introducing graphical functions Displaying vectors using base graphicsSaving graphical output; The main graphical systems in R; Summary; Chapter 3: Working with Tables; Using the data.frame class to represent tabular data; Creating a table from separate vectors; Creating a table from a CSV file; Examining the structure of a data.frame object; Subsetting data.frame objects; Calculating new data fields; Writing a data.frame object to a CSV file; Controlling code execution; Conditioning execution with conditional statements; Repeatedly executing code sections with loops Automated calculations using the apply family of functionsApplying a function on separate parts of a vector; Applying a function on rows or columns of a table; Inference from tables by joining, reshaping, and aggregating; Using contributed packages; Shifting between long and wide formats using melt and dcast; Aggregating with ddply; Joining tables with join; Summary; Chapter 4: Working with Rasters; Using the matrix and array classes; Representing two-dimensional data with a matrix; Representing more than two dimensions with an array; Data structures for rasters in the raster package Creating single band rasters |
| Record Nr. | UNINA-9910787230203321 |
|
Dorman Michael
|
||
| Birmingham, England : , : Packt Publishing, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Learning R for geospatial analysis : leverage the power of R to elegantly manage crucial geospatial analysis tasks / / Michael Dorman
| Learning R for geospatial analysis : leverage the power of R to elegantly manage crucial geospatial analysis tasks / / Michael Dorman |
| Autore | Dorman Michael |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Birmingham, England : , : Packt Publishing, , 2014 |
| Descrizione fisica | 1 online resource (364 p.) |
| Disciplina | 025.06910285 |
| Collana | Community Experience Distilled |
| Soggetto topico |
Geospatial data
R (Computer program language) Spatial analysis (Statistics) |
| ISBN | 1-78398-437-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: The R Environment; Installing R and using the command line; Downloading R; Installing R; Using R as a calculator; Coding with R beyond the command line; Approaches to editing R code; Installation of RStudio; Using RStudio; Evaluating expressions; Using arithmetic and logical operators; Using functions; Dealing with warning and error messages; Getting help; Exploring the basic object types in R; Everything is an object; Storing data in data structures
Calling functions to perform operationsA short sample session; Summary; Chapter 2: Working with Vectors and Time Series; Vectors - the basic data structures in R; Different types of vectors; Using the assignment operator to save an object; Removing objects from memory; Summarizing vector properties; Element-by-element operations on vectors; The recycling principle; Using functions with several parameters; Supplying more than one argument in a function call; Creating default vectors; Creating repetitive vectors; Substrings; Creating subsets of vectors Subsetting with numeric vectors of indicesSubsetting with logical vectors; Dealing with missing values; Missing values and their effect on data; Detecting missing values in vectors; Performing calculations on vectors with missing values; Writing new functions; Defining our own functions; Setting default values for the arguments; Working with dates and time series; Specialized time series classes in R; Reading climatic data from a CSV file; Converting character values to dates; Examining our time series; Creating subsets based on dates; Introducing graphical functions Displaying vectors using base graphicsSaving graphical output; The main graphical systems in R; Summary; Chapter 3: Working with Tables; Using the data.frame class to represent tabular data; Creating a table from separate vectors; Creating a table from a CSV file; Examining the structure of a data.frame object; Subsetting data.frame objects; Calculating new data fields; Writing a data.frame object to a CSV file; Controlling code execution; Conditioning execution with conditional statements; Repeatedly executing code sections with loops Automated calculations using the apply family of functionsApplying a function on separate parts of a vector; Applying a function on rows or columns of a table; Inference from tables by joining, reshaping, and aggregating; Using contributed packages; Shifting between long and wide formats using melt and dcast; Aggregating with ddply; Joining tables with join; Summary; Chapter 4: Working with Rasters; Using the matrix and array classes; Representing two-dimensional data with a matrix; Representing more than two dimensions with an array; Data structures for rasters in the raster package Creating single band rasters |
| Record Nr. | UNINA-9910812811303321 |
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Dorman Michael
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||
| Birmingham, England : , : Packt Publishing, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
LENS 2019 : proceedings of the 3rd ACM SIGSPATIAL International Workshop on Analytics for Local Events and News (LENS 2019) : November 5, 2019, Chicago, Illinois, USA / / Association for Computing Machinery
| LENS 2019 : proceedings of the 3rd ACM SIGSPATIAL International Workshop on Analytics for Local Events and News (LENS 2019) : November 5, 2019, Chicago, Illinois, USA / / Association for Computing Machinery |
| Pubbl/distr/stampa | New York, NY : , : The Association for Computing Machinery, , [2019] |
| Descrizione fisica | 1 online resource : illustrations |
| Disciplina | 006.312 |
| Soggetto topico |
Data mining
Digital media Geospatial data Journalism - Data processing Online social networks |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910412061603321 |
| New York, NY : , : The Association for Computing Machinery, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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A linked geodata map for enabling information access / / by Logan J. Powell and Dalia E. Varanka
| A linked geodata map for enabling information access / / by Logan J. Powell and Dalia E. Varanka |
| Autore | Powell Logan J. |
| Pubbl/distr/stampa | Reston, Virginia : , : U.S. Department of the Interior, U.S. Geological Survey, , 2018 |
| Descrizione fisica | 1 online resource (iv, 6 pages) : color maps |
| Collana | Open-file report |
| Soggetto topico |
Geospatial data
Linked data RDF (Document markup language) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910707100203321 |
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Powell Logan J.
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| Reston, Virginia : , : U.S. Department of the Interior, U.S. Geological Survey, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Linking DHS household and SPA facility surveys : data considerations and geospatial methods / / Clara R. Rurgert, Debra Prosnitz
| Linking DHS household and SPA facility surveys : data considerations and geospatial methods / / Clara R. Rurgert, Debra Prosnitz |
| Autore | Burgert-Brucker Clara R. |
| Pubbl/distr/stampa | Rockville, Mayland, USA : , : ICF International, , 2014 |
| Descrizione fisica | 1 online resource (xi, 30 pages) : color illustrations, color maps |
| Collana | DHS spatial analysis reports |
| Soggetto topico |
Spatial analysis (Statistics)
Geospatial data Household surveys - Statistical methods Health surveys - Statistical methods |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Linking DHS household and SPA facility surveys |
| Record Nr. | UNINA-9910713074403321 |
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Burgert-Brucker Clara R.
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| Rockville, Mayland, USA : , : ICF International, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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LocalRec 2019 : proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising : November 5, 2019, Chicago, IL, USA / / Association for Computing Machinery
| LocalRec 2019 : proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising : November 5, 2019, Chicago, IL, USA / / Association for Computing Machinery |
| Pubbl/distr/stampa | New York, NY : , : The Association for Computing Machinery, , [2019] |
| Descrizione fisica | 1 online resource : illustrations |
| Disciplina | 910.285 |
| Collana | ACM International Conference Proceedings Series |
| Soggetto topico |
Geospatial data
Location-based services Recommender systems (Information filtering) Social networks |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910412061403321 |
| New York, NY : , : The Association for Computing Machinery, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Metadata in action [[electronic resource] ] : expanding the utility of geospatial metadata / / Lynda Wayne
| Metadata in action [[electronic resource] ] : expanding the utility of geospatial metadata / / Lynda Wayne |
| Autore | Wayne Lynda |
| Pubbl/distr/stampa | [Reston, Va.] : , : [Federal Geographic Data Committee], , 2005 |
| Descrizione fisica | 6 pages : digital, DOC file |
| Soggetto topico | Geospatial data |
| Soggetto genere / forma | Geospatial data |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Metadata in action |
| Record Nr. | UNINA-9910696674003321 |
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Wayne Lynda
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| [Reston, Va.] : , : [Federal Geographic Data Committee], , 2005 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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