1.
Geodata Management in ArcGIS
An Nisaa Citra Hasanah – Pachira Eizza Paramitha

2.
Session Highlights
• Geospatial Data in ArcGIS
• Introduction to ArcGIS Pro
• Vector Data Model
• Raster Data Model
• Geospatial Data Management
• Data Management and Visualization in ArcGIS Pro
• Hands-on
• Assignment

3.
Characteristics of Spatial Data
• Representation on a map of real-world features and phenomena.
• Can also be any information with a location attached to it, whether on a map or not.
• A GIS integrates location and attribute information, storing information about where something is with
information about what something is.

4.
How is GIS Data Structured?
The spatial component of GIS data allows you to
perform many tasks:
• Visualize real-world information and analytical
output.
• Implement analytical functions such as proximity
analysis, buffering, and movement.
• Select and filter features geographically.
• Calculate properties such as length and area.

5.
ArcGIS Data Types Today
Cloud
storage
Enterprise
geodatabases
ArcGIS Data
Store
Files
Spatiotemporal
big data store
Imagery
Raster Real-time
Big data
Demographic
Living Atlas
Utility networks
Field
3D
Vector & tabular
Urban
Unstructured
Indoor
Drone
ArcGIS Platform supports your data workflows
Third party
Cloud

6.
Mining &
Exploration
Freeport Indonesia
Indonesia
Utility Management
One Map Portal
Badan Informasi
Geospasial
Indonesia
Citarum Open Data
Indonesia
PLN (Perusahaan Listrik Negara)
Indonesia
Jakarta Satu
City of Jakarta
Indonesia
Tangerang Live
City of Tangerang
Indonesia
Geoportal Pekanbaru
City of Pekanbaru
Indonesia
Bogor
Indonesia
Boga Peta
Banking
Bank Muamalat Indonesia)
Indonesia
Badan Pusat Statistik
Indonesia
Statistics Indonesia
GIS Taru
Ministry of Agrarian Affairs and
Spatial Planning/National Land
Agency - Indonesia
Demographic Data
Ministry of Home Affairs
Indonesia
Energy One Map
Ministry of Energy and
Mineral Resources
Indonesia
Forestry Geoportal
Ministry ofEnvironment and
Forestry
Indonesia
Indihome
Indonesia
Sales Information System
Portal, Open Data and Citizen Engagement

7.
Esri Indonesia’s Oil and Gas Solution Catalogue
Real-time Assets and
Productivity Monitoring
System
Real-time Fleet
Movement Tracking
and Monitoring
Integration of
G&G and GIS
Data
Comprehensive
Landing Page For
Data Repository
Oil Well Productivity
Visualization And
Analysis
Safety Observation
Reporting System
GIS-based Common
Operating Picture For
Oil Spill Response
Augmented Reality For
Underground Assets
Inspection
Pipeline Risk
Analysis with
Business Intelligence
Real-time Fieldworker
Management System

8.
ArcGIS Pro
ArcGIS Desktop (retired soon)
ArcGIS Online
ArcGIS Enterprise
ArcGIS Apps
Geo-Enabled Systems
ArcGIS for Developers

9.
ArcGIS Pro

10.
ArcGIS Desktop
Desktop Web Device
Server Online Content
and Services
Portal
ArcMap
ArcCatalog
ArcScene
ArcGlobe
ArcGIS Pro

11.
Fusion of Applications
ArcMap / ArcCatalog
ArcGlobe / ArcScene
CityEngine

12.
ArcGIS Pro Features
• 64-bit application (will not run on 32-bit systems)
• Modern interface for easier navigation
• Context-sensitive interface
• Multiple views and multiple layouts in the same project
• Improved ArcGIS Help
• Import capability for MXD, SXD, and 3DD files
• Fast processing (8 GB of RAM is recommended)
• Availability of all key features in 2D and 3D
• Combined 2D and 3D capability in a single project
• Full geoprocessing and extension functionality
• Tasks (which guide users through complex workflows)
• Automatic updates

13.
Continuous phenomena and discrete features
• Discrete data represents real-world features that have well-defined boundaries. A discrete feature is
distinct from the other features around it.
• Continuous data represents real-world phenomena that do not have well-defined boundaries

14.
Vector geometry
• The vector data model represents discrete objects on the surface of the earth, such as
streetlights, roads, and buildings, as point, line, and polygon (area) features, respectively.

15.
Raster Data Model
• In its simplest form, a raster consists
of a matrix of cells (or pixels)
organized into rows and columns
(or a grid) where each cell contains a
value representing information, such
as temperature.
• Rasters are digital aerial photographs,
imagery from satellites, digital
pictures, or even scanned maps.

16.
Raster Data Types
Continuous Raster Discrete Data
Imagery Scanned Maps

17.
Raster Attributes

18.
Geospatial Data Management

19.
Organizing your data

20.
Feature data type
• Shapefile
• Feature Class Geodatabase

21.
Associate Nongeographic Data with Geographic Data
Supplementa
l data
Central data
storage
Spatial
search
Redundancy
Additional
data
Central data
storage
Spatial
search
Performance
Example: Adding media files with attachments

22.
Geodatabase
• The geodatabase (a database or file structure used
primarily to store, query, and manipulate spatial data) is
a powerful data model for storing and managing your
GIS data in one place.
• Through the geodatabase, you can import different
datasets from various sources and use them in your GIS
analysis.

23.
Geodatabase Elements
Primary dataset types:
• Tables : collection of rows, each containing the
same fields.
• Feature Classes : tables with a shape field containing point,
line, or polygon geometries for geographic
features. Each row is a feature
• Raster Datasets : contains rasters which represent
continuous geographic phenomena

24.
Compare Different Geodatabase Types
Scenario Type of geodatabase
Single user with small project
Multiple users with an ongoing large-scale project
Single user with large datasets and sharing with entire
organization
Multiple users with small projects and only one editor at a time File
geodatabase
Enterprise
geodatabase

25.
Maintaining Data Integrity
Archiving
Data
Topology
Subtypes
Domains

26.
Subtypes and Domains
• Subtypes: a set of features that
share the same attributes.
• Domains: used to describe the
values accepted in a field.

27.
Why use a topology?
• In geodatabases, topology is
the arrangement that
defines how point, line, and
polygon features share
coincident geometry.
• For example, street
centerlines and census blocks
share common geometry, and
adjacent soil polygons share
their common boundaries.
Areas share boundaries Lines share endpoints Lines share segments
Area overlap areas Points fall within polygons
Points share vertices
with lines

28.
Mosaic Dataset
Mosaic datasets are useful for the following
actions:
• Managing, querying, and visualizing
large collections of raster data, including
multidimensional, overlapping, and
temporal data.
• Controlling the display or the ordering
of rasters.
• Performing on-the-fly processing, which
occurs as the rasters are accessed; the
source pixels are not altered or converted.
Collections of
rasters
Mosaic
Dataset
Viewed as
one dataset

29.
Why use a mosaic?
A mosaic dataset reads all the metadata from
the rasters and imagery. It enables the following
capabilities:
• Defining extra metadata
• Defining image-processing functions to be
applied to the imagery when the data is
accessed
• On-the-fly processing that applies all required
processing to the imagery as it is accessed,
removing the requirement to pre-process
imagery
• Dynamic mosaicking that allows overlapping
imagery to be merged and fused

30.
Mosaic Dataset
In ArcGIS Pro, a mosaic dataset becomes a
mosaic layer. In the Contents pane, it displays
as a special group layer of at least three layers:
• A Boundary layer that displays the boundary
of the mosaic dataset,
• A Footprint layer that displays the footprints
for each raster within the mosaic dataset, and
• An Image layer that controls the rendering of
the mosaicked image.

31.
Advantages of using a geodatabase
Advantage Advantages Characteristic
Centralized repository
All data is stored in the same database, as
opposed to in many separate files.
• Feature classes
• Table
Scalable data model
As your GIS needs increase, you can
migrate data from one geodatabase to an
upgraded format that allows for more users
and editors.
• File geodatabase
• Enterprise geodatabase
Shareable data models
You can share data models to be re-used in
other projects
• Feature datasets
• Geodatabase schema template
Increased data integrity
You can create spatial and attribute
behaviors to facilitate editing, help eliminate
data entry errors, and maintain spatial and
attribute relationships between your data.
• Subtypes
• Domains
• Topology
Support for imagery
Mosaic datasets in the geodatabase allow
you to manage multiple images as one.
• Mosaic dataset

32.
Data Management and
Visualization in ArcGIS Pro

33.
Import ArcMap Document to ArcGIS Pro
• Directly import ArcMap document
- *.mxd or *.mpk files
• Clone the project template
• On the ribbon, click the Insert tab. In the Project group, click Import Map

34.
Manage data to Geodatabase
• Export from Content pane
- Right Click on layer > Data > Export Feature
• Using Geoprocessing
- Analysis > Tools > Conversion Tools > To Geodatabase >
Feature class to Feature class

35.
• 2D and 3D editing
• Simplified edit sessions
• Edit shapefiles
• Edit file & enterprise GDBs
• Group templates
• GDB & Map topology
• CAD like editing experience
Editing

36.
Types of layer symbology
Graduated colors
Default symbology
Unique values

37.
Types of layer symbology
Default symbology
Graduated symbols
Heat map

38.
Types of selection queries
Attribute queries
ZONE_DESC Is Equal To Residential

39.
Types of selection queries
Spatial queries
Select all streams that intersect urban areas

40.
Displaying features at different scales

41.
Symbol classes
Smallest scale Largest scale
1:20,000,000 1:10,000,000 1:2,000,000
City
Town
Village
Visible
Scale
Ranges

42.
Create Feature From XY Table
X-coordinate Y-coordinate
1360450.920098 415574.238657
1361269.332175 414898.057266
1364029.323702 409529.628699

43.
Storage Type Infrastructure Typical Uses Common Data format
Key ArcGIS data options available today
• Multi-user editing (versioning)
• Topology, attribute rules, etc.
• Registered data store
• Utility network, parcel mgmt
• Feature class
• Mosaic dataset
• Parcel fabric
Enterprise
Geodatabase
• RDBMS
• Often managed by IT/DBA
• Can be large scale
Hosted layers
• Relational (feature)
• Tile Cache (scene)
• Spatiotemporal big data store
(real-time)
• Accessed as layer item in
the Enterprise portal
• ArcGIS Enterprise component
• Supported three types
• Often on dedicate host
ArcGIS
Data Store
• Imagery/raster store
• Map & Image cache folders
• ArcGIS Data Store backup
• Standard file data formats
• Feature class/Query layer
• CRF (cloud raster format)
• Cache raster format
• IaaS → AWS & Azure
• DbaaS → Azure SQL database
• Amazon → PostgreSQL RDS
Cloud
Storage
• Input to big data GeoAnalytics • Shapefile, delimited text
• ORC (optimized row col)
• Parquet
• Hadoop
• Hive
Big Data
Storage
• Local OS folders
• Often on a network file share
Files/Folders
• Shapefile, CSV, txt
• File geodatabase
• Raster/imagery
• Local data for ArcGIS Pro
• Registered data store
• Project packages

44.
Geodata Management
Hands-on