Overview of GIS

GIS - GIS is an integrated collection of computer software and data used to view and manage information about geographic places, analyse spatial relationships and model spatial processes

Model - A model is a simplification to describe, predict or analyse reality. It is usually done to answer a question or solve a problem.
Issues with models are that they represent a real world problem with several assumptions and simplifications involving compromise, sub-division,  reclassification, generalization and imposition of temporal limits resulting in applying subjective constraints.
GIS was developed in 1963 by Dr. Roger Tomlison who is regarded as the "Father of GIS".
Location data is information that describes the location and properties (attributes) of features. It may be stored as raster or vector data.
A map project references data files but does not contain them. Ex: ArcMap, QGIS
Map document has an extension .mxd in ArcMap
Vector data model defines objects with definite boundaries.
Vector geometries are represented using (x,y,z) coordinate pairs: Point, (poly)line, Polygon
Vector data uses geographic coordinates and attribute information to locate and determine features.
Attribute types are: Nominal, Ordinal, Interval & Ratio.
Nominal : Refers to QUALITY of a feature, NOT QUANTITY
Ordinal : Refers to rank
Interval: Refers to quality measurement that is linear (Ex: Temperature)
Ratio : Quantity measurement that is linear, but has a fixed zero point.
Raster data model: It is a mixture of cells (PIXEL-Picture Element) organized into rows and colmns where each cell contains a value representing information. Size increases exponentially with increasing cell size.
Uses of raster:

• Base map - As a background for vector layers
• Surface map - Representing changing data in a landscape
• Thematic map - Grouping values into classes or categories

Methods to capture data: 

• Primary (mesuring data directly using instruments like GPS or techniques like surveying and remote sensing)
• Secondary (Digitizing maps from physical maps, photographs, using photogrammetry)

Remote sensing refers to images recorded from sensors without direct contact like UAVs (Unmanned Aerial Vehicles), Planes, Satellites. It is useful and economical for large areas.
Photogrammetry is the technology used to make measurements in the real world using photographs
The following are used to consider data quality assessment

• -Resolution
• -Scale
• -Age
• -Author
• -Source
• -Position & attribute
• -Accuracy
• -Completeness
• -Metadata

WFS- Web map service: It is a web mapping data format that represents map images (*.png, *.gif, *.jpg). It shares data online. It is the open geospatial consortium standard protocol for requesting georeferenced map images from a spatial database.
ESRI - Environmental Systems Research Institute is a private organization that created the popular GIS software ArcGIS for desktop and online
ArcMap - It is a software application created by ESRI to display, explore and edit GIS datasets
ArcCatalog- It is a software application created by ESRI to organise and manage geographic information for ArcGIS for desktop.

Vector file formats are those that can be stored as geodatabase classes in geodatabase and shapefile, CAD Ex: shp, shx, dbf, prj, xml.
File geodatabase- Geodatabase is a collection of geographic datasets that is easily managed and scalable depending on the intended use. - IT IS EASIER TO STORE.
It is a collection of files in a folder that can store, query and manage spatial and non-spatial data. It is composed of:

• -Feature classes
• -Feature dataset
• -Raster dataset
• -Non-spatial tables and
• -Toolboxes

Geodatabase is the native data model for ESRI software. It has the ability to handle different data models and datatypes all within one file folder.

Feature class - It is found in geodatabase files and is a collection of vectors with set attributes, but can also refer to annotations, multipoints or multipatches.
Raster file formats- They are saved in geodatabase as mosaic model, and tiff, jpeg, GeoTIFF, jpeg2000, DEM formats. The format determines:

1. -How colours are handled and
2. -How geographic data is stored.

Metadata - Metadata refers to data about data. It provides additional information about a feature and its attribute. For example:

1. - Item description
2. -Who created the data
3. -Usage constraints

Geographic Coordinate system or GCS is a three dimensional surface used to determine locations on the Earth. A point can be referenced by longitude and latitude values measured from Earth's center to a point on the surface.

Spehroid is also known as an ellipsoid. It is a three dimensinal shape created from a two dimensional ellipse. It is a model of the Earth.
NORTH AMERICAN SPHHEROID = NAD83 - is the North American Datum of 1983
It is recommended to use a common datum in a dataset and convert the datum as required.
(x,y) coordinates are used to measure distance North or South of the equator and East or West of the prime meridian
MAP PROJECTIONS:

1. -Conformal projection category preserves local angles. Ex: Mercator projection                       -A PROJECTION CANNOT BE BOTH EQUAL AREA AND CONFORMAL
2. -Equal area projection category preserves area
3. -Equidistant projection category preserves scale in agiven direction
4. -Compromise projection category involves moderate distortion of SHAPE, AREA. DISTANCE, DIRECTION & SCALE.

MAP PROJECTION CLASS:

1. -CONIC
2. -CYLINDRICAL
3. -PLANAR

MAP PROJECTION CASE is a form of intersection that can be:

1. -TANGENT or
2. -SECANT

MAP PROJECTION is a mathematically described technique of representing the Earth's surface on a flat map. Projection can be described by:

1. -Class
2. -Projection case
3. -Aspect and
4. -Category

A UTM projection is composed of

1. -60 zones that are divided by North or South
2. -Each zone is a secant cylindrical mercator projection
3. -Standard lines are approximately 180 km to eah side of the centrall meridian

GCS is used to:

1. -store data in a central database where users can project them as needed.
2. -make a quick map
3. -when distortion of shape, area and distance are irrelevant
4. -when spatial queies based on location and distance will not be performed.

Map projections are used to preserve a property

Ex:

1.  -Distance queries
2. -To measure areas
3. -GIS analysis
4. -Editing GIS features
5. -Correct visualisation

Transormation function can update the display without changing the dataset resulting in inaccurate measurement and data calculation

ArcScene and ArcGlobe  are 3D visualization applications
Georeferencing is a method of assigning real world spatial coordinates. It integrates new data into a GIS or assigns control points to reconizable features. It is used only for raster and CAD.
Measuring dimensions in GIS refers to quantifying characteristics of a feature by length, perimeter and area.
Measuring distance involves capturing the distance between two or more spatial entities (point, line, polygon)
Distance relationships can be drawn in a straight line on a map in the form of euclidean or great circle with consideration of time, perception and barrier distance.
Measuring density involves consideration of feature distribution in a landscape.
Standarzitaion refers to attribute data. It should be divided by a dimension of the spatial entity it relates to.
Summary statistics are statistical measurements of attribute data. Ex;

1. Mean, 
2. Median, 
3. Variance and 
4. Count

3D measurements refer to measurement of spatial data that uses (x,y,z) coordinates including surface area and volume.

Surface area refers to 3D measurement that measures along slopes and it is always bigger than 2D surface area.
Categorical measurement refers to comparing categories of different factors using a common criteria.
Ex:

1. Suitability analysis, 
2. Weighted site selection. 

Metaphorically speaking, it allows analysts to compare "apples to oranges"
Following are the issues with data quality:

1. -Accuracy
2. -Source &
3. -Metadata

SQL - Structured Query Language is a set of operators strung together to form a request. It is based on the input layer and a query is defined that searches for and selects records that satisfy the query.
Comparison operators used are:

1. -Equal to (=)
2. -Greater than (>)
3. -Less than (<)
4. -Greater than or equal to (>=)
5. -Less than or equal to (<=)
6. -Not equal to (<>)

Logical operators used are:

1. -AND
2. -OR
3. -NOT
4. -XOR

Wildcard search symbols

1. -LIKE
2. -'-'
3. -'%'
4. Null values
5. -IS
6. -IS NOT operators are used to identify NULL values

Spatial selection

1. -Accessing spatial data to select records that meet a set of spatial criteria Ex: Test relationship of different datasets
2. -Intersection
3. -Adjacency
4. -Containment
5. -Distance
6. Joining data
7. -Combining data from multiple input tables into a single output table using a common key in the table

Types of relationships:

1. ONE-TO-MANY
2. MANY-TO-ONE

• Attribute join involves appending the fields of one table to those of another through a field common to both tables
• Benefit of attribute join is that all the data does not have to be stored in one table. NON-SPATIAL DATA can be mappable

SPATIAL JOIN
This operation joins the attributes of two layers based on the location of the features in the layers. This is possible ONLY if BOTH the layers have the SAME COORDINATE SYSTEM
The purpose of spatial join is:

• -To find the nearest feature
• -Contents of a polygon &
• -Use as a measurement tool

-THIS IS DONE USING SPATIAL JOIN TOOL (in the OVERLAY toolkit) or Join data by location
Web map Vs Digital map
Advantages of spatial join:

1. -Cheaper and less time-intensive to produce
2. -Wide audience (accessible by anyone with internet access)
3. -Easier to update
4. -Interactive
5. -Can be used to link to related information

Vector classification

• -Feature level classification to explore and display existing trends in data

Thematic classification

• -It conveys information about a single topic or theme

Chloropleth

• -It is a thematic map in which vector areas are distinctly colored or shaded to represent classed values of a particular phenomenon.

Classification techniques:

1. -Equal interval, Defined interval
2. -Quantile
3. -Natural breaks (in ArcMap)
4. -Petty breaks (in QGIS)
5. -Standard deviation (How much a feature's attribute value varies from the mean)
6. -Subjective (Manual)
7. -Unclassified (Unique values)

Geographical standardization refers to standardization across different areas where the absolute data is divided by a dimension of the spatial entity. (For example: Using density instead of population)

Raster classification involves:

• -Reclassifying cells to genaralize existing trends
• -Creating themes in raster models. Ex: Chloropleth

Classification problems:

• -Confirmation bias
• -Ecological fallacy
• -Modifiable Areal Unit Problem (MAUP)

Components of geodatabase

• -VECTOR -Feature classes
• -RASTER -Raster datasets (A gridded spatial data model)
• -NON-SPATIAL -Tables made-up of rows and columns

Feature subtype : Geodatabase behaviour that represents a subset of features as a method to categorise data with same characteristics

TOPOLOGY

• -Topology is defined as a set of geographic relationships of one or more feature classes with common geometries in a geodatabase.
• -Topology describes how features are spatially related
• -Shared features between feature classes can be managed using topology, nodes, edges and faces. Their relationship to one another and their features can be effectively discovered and assembled.
• -Topology provides a mechanism to perform integrity checks on associated data thereby validating and maintaining better feature representations.

For example:

1. -Navigating along features
2. -Finding adjacent features

Features share geometry in a topology in the following ways:

1. -Adjacent
2. -Polygon topology
3. Edge node topology

Geoprocessing is a GIS operation used to manipulate GIS data and derive new information

Useful geoprocessing tools are:

1. -Clip
2. -Merge
3. -Append
4. -Dissolve
5. -Buffer

Buffers may be:

1. - Fixed
2. -Concentric or
3. -Data derived

Geodesic buffer is an alternateive for large scale buffers

Types of Overlay analysis:

1. -intersect
2. -union
3. -difference

The following are the problems with physical overlays:

1. -Poor precision
2. -Time consuming
3. -Manual rescaling
4. -Hard to make changes to analysis
5. Plenty of error propogation
6. Problems with overlays:
7. -Error propogation
8. -Computationally intensive
9. -Sliver creation
10. -Scale

A Model builder consists of:

1. -Tools
2. -Input variables and
3. -Connectors

• Accuracy is defined as the closeness to true or known value
• Precision is defined as closeness of two or more values to  each other

REMOTE SENSING
Types of sensors:

1. -ACTIVE Ex: LiDAR, RaDAR
2. -PASSIVE Ex: Visible panchromatic, Visible multispectral, InfraRed, Thermal

Reflectance is defined as the radiation that is given off by objects. Different classes of features reflect a different band of radiation at different rates.
Image band is also known as raster band that is represented by a single matrix of cell values. It can also be a raster with multiple bands stored as a Digital Number(DN).
Landsat8 spectral bands:
-11 bands in total. Each band is good in reading specific features.

1. -BAND-1 useful for mapping coastal & aerosol studies
2. -BLUE Bathymetric mapping to distinguish soil from vegetation
3. -GREEN Emphasizes peak vegetation to assess plant vigour
4. -RED Discrimitaes vegetatin slopes
5. -NIR Emphasizes biomass content and shorelines
6. -SWIR-1 Emphasizes moisture content of soil and vegetation; penetrates thin clouds
7. -SWIR-2 Improved SWIR-1
8. -BAND-8 Panchromatic - 15 m resolution, sharper image definition
9. -BAND-9 Improved detection of cirrus cloud contamination
10. -BAND-10 TIRS-1 100m resolution, thermal imaging and estimated soil moisture
11. -BAND-11 TIRS-2 Improved TIRS-1

TIRS - Thermal Infra Red Sensor

NVDI - Normalized Difference Varience Index

1. - It uses NIR and Red bands ratio to read vegetative density more clearly (NIR-Red)/(NIR+Red)

Aerial photography - Data is colleted (multi-spectral, elevation) by a plane flying over the study area.

1. - The study area is usually small
2. - It has high resolution and is expensive

Satellite imagery - Data (multispectral, panchromatic, elevation) is collected by a satellite in orbit with 0.5 to 1 km resolution
Unmanned Aerial Vehicle (UAV) - Data (photographic, LiDAR, InfraRed, Thermal) is collected by unmanned aircraft controlled fro ground for a small area
Spatial resolution - Raster resolution that covers areas in pixel. Smaaller areas give higher resolution which implies larger file and more expensive data.
Spectral resolution - It is the ability of a sensor to define fine wavelength ranges to separate them
Radiometric resolution - In terms of raster resolution, it is the ability of an imaging system to discriminate slight differences in energy using reflectance values
Temporal resolution - It is defined as the frequency with which a sensor can collect imagery of the same area (revisit period)
Surface analysis - This involves capturing and analysing the physical structure of the Earth in 3D. In raster, it forms DEM.
Examples of surface analysis are:

1. -Surface interpretation
2. -Hydrological analysis
3. -Statisticl analysis
4. -Image classification

Suitability analysis-Raster layers can be combined (overlay analysis) to model suitable area.

The steps involved in Suitability analysis are:

1. -Using an established criteria
2. -Reclassification into common values
3. -Assigning weights to criteria
4. -Overlay and
5. -Evaluation

Components of raster resolution:

1. -Spatial resolution
2. -Spectral resolution
3. -Radiometric resolution
4. -Temporal resolution

History of GIS

- I generation (1993-99)

1. - Zoom-in, Zoom-out
2. - Not continuous surface
3. - Layers cannot be toggled

- II generation (1999-2004)

1. - GIS vendors developed server based softwares
2. - Users could publish interactive maps on the web using GIS sofwares with interactivity and performance
3. - In 1996 mapquest launched web service, users got directions but it was slow to load

- III generation (2005-present)

1. - In 2005 google maps developed tiles
2. - Tiles load faster than one big map.
3. -Maps are prepared at multiple scales. More data presented at each scale and web map loads only tiles needed by user.