Menu

Szukaj

Zamknij

Zaloguj się

Biblioteka

0,00 zł (0)

Koszyk

ODBIERZ TWÓJ BONUS :: »

Learning ArcGIS for Desktop. Create, analyze, and map your spatial data with ArcGIS for Desktop Daniela C Docan

Język publikacji: angielskim
Learning ArcGIS for Desktop. Create, analyze, and map your spatial data with ArcGIS for Desktop Daniela C Docan - okladka książki

Learning ArcGIS for Desktop. Create, analyze, and map your spatial data with ArcGIS for Desktop Daniela C Docan - okladka książki

Autor:
Daniela C Docan
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
344
Dostępne formaty:
     PDF
     ePub
     Mobi

Ebook 29,90 zł najniższa cena z 30 dni

149,00 zł (-10%)
134,10 zł

Dodaj do koszyka lub Kup na prezent Kup 1-kliknięciem

29,90 zł najniższa cena z 30 dni

Poleć tę książkę znajomemu Poleć tę książkę znajomemu!!

Przenieś na półkę

Do przechowalni

Prezent last minute w ebookpoint.pl
ArcGIS for Desktop is one of the main components of the ESRI ArcGIS platform used to support decision making and solve real-world mapping problems. Learning ArcGIS for Desktop is a tutorial-based guide that provides a practical experience for those who are interested in start working with ArcGIS.

The first five chapters cover the basic concepts of working with the File Geodatabase, as well as editing and symbolizing geospatial data. Then, the book focuses on planning and performing spatial analysis on vector and raster data using the geoprocessing and modeling tools. Finally, the basic principles of cartography design will be used to create a quality map that presents the information that resulted from the spatial analysis previously performed. To keep you learning throughout the chapters, all exercises have partial and final results stored in the dataset that accompanies the book. Finally, the book offers more than it promises by using the ArcGIS Online component in the tutorials as source of background data and for results sharing

Wybrane bestsellery

O autorze książki

Daniela Cristiana Docan is currently a lecturer at the Department of Topography and Cadastre at the Faculty of Geodesy in Bucharest, Romania. She obtained her PhD in 2009 from the Technical University of Civil Engineering, Bucharest, with her thesis Contributions to quality improvement of spatial data in GIS. Formerly, she worked at Esri Romania and National Agency for Cadastre and Land Registration (ANCPI). While working for Esri Romania, she trained teams (as an authorized instructor in ArcGIS for Desktop by Esri) from state- and privately-owned companies, such as the Romanian Aeronautical Authority, the Agency of Payments and Intervention for Agriculture (APIA), and the Institute of Hydroelectric Studies and Design. She also trained and assisted the team in charge of quality data control in the Land Parcel Identification System (LPIS) project, in Romania. For the ANCPI, she created the logical and physical data model for the Romanian National Topographic Dataset at a scale of 1:5,000 (TOPRO5) in 2009. She was a member of the workgroup that elaborated TOPRO5 and its metadata technical specifications and the Report on the implementation of the INSPIRE Directive in Romania in 2010. Prior to this book, Daniela worked on ArcGIS for Desktop Cookbook, Packt Publishing, which covers the following topics: designing a file geodatabase schema, constraining the geometry and attribute values of the data, geocoding addresses, working with routes and events, and using spatial ETL tools.

Packt Publishing - inne książki

Zamknij

Przenieś na półkę
Dodano produkt na półkę
Usunięto produkt z półki
Przeniesiono produkt do archiwum
Przeniesiono produkt do biblioteki

Zamknij

Wybierz metodę płatności

Ebook
134,10 zł
Dodaj do koszyka
Sposób płatności
Zabrania się wykorzystania treści strony do celów eksploracji tekstu i danych (TDM), w tym eksploracji w celu szkolenia technologii AI i innych systemów uczenia maszynowego. It is forbidden to use the content of the site for text and data mining (TDM), including mining for training AI technologies and other machine learning systems.