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Active Remote Sensing > Topic 6: OBIA > Flashcards

Topic 6: OBIA Flashcards

1
Q

OBIA stand for

A

Object based image analysis

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2
Q

what does OBIA do

A

divides remote sensing imagery into meaningful image objects and assigning characteristics

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3
Q

what is Scale in remote sensing

A

Grain
- spatial resolution
Extent
- swath width
this is a trade off

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4
Q

what is the optimal scale

A

there is no single optimal scale for defining geographic entities

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5
Q

why is scale an issue

A

results and conclusions may only be a result of one specific scale

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6
Q

MAUP stands for

A

Modifiable areal unit problem

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7
Q

what is MAUP

A

is the sensitivity of analytical results to the definition of data collection units.

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8
Q

what are the two components of the MAUP

A
  1. scale problem
  2. aggregation problem
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9
Q

what is the Scale problem in the MAUP

A

variation in results when areal units are aggregated into fewer and larger units for analysis.
eg. resampling to larger pixel sizes

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10
Q

what is the aggregation problem in the MAUP

A

variation in results generated bu alternate zoning schemes at the same resolution.

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11
Q

Whats the relationship between between variance and correlation coefficients

A

lower variance (smoothing) results in stronger correlation

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12
Q

what are solutions to MAUP

A
  1. Abandon traditional statistics
  2. conduct a sensitivity analysis
  3. derive an optimal spatial resolution
  4. identify basic entities or objects
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13
Q

what is an optimal spatial resolution

A

no simple solution, application dependent

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14
Q

what is spectral classification

A

spectral classes are converted into information classes.

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15
Q

what are the three types of classifications

A
  1. supervised
  2. unsupervised
  3. hybrid
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16
Q

what is Pixel mixing

A

one one pixel represents multiple classes with no one clear signal
- composite signatures

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17
Q

what are competing effects of increased spatial resolution?

A
  • less pixel mixing with high spatial resolution
  • greater within-class variability.
18
Q

summarize the MAUP problem

A

whenever a grid is assigned to a physical area there is inherent error in the way the data is aggregated.

19
Q

OBIA as a solution for MAUP

A

provides soltion as features are not only pixel values based

20
Q

what are objects

A

are basic entities within an image that are composed of h-res pixel groups
- we use shape, texture, colour and context to define shapes

21
Q

intigration of Image objects to GIS

A

pixels: raster data model
objects: vector data model

22
Q

OBIA provide what aspects for analysis

A

Spectral Variables
Shape variables
Texture Variables
Context

23
Q

what are spectral variables

A

feautres related to the value of pixels within an object

24
Q

what are Shape variables

A

Features to the shape of an image object, length, width, direction, area

25
Q

texture variables

A

features related to spatial patterns of pixels within an object

26
Q

what is Context in a OBIA

A

Features related to the spatial setting of an object within scene and/or its relationship to other objects in the scene

27
Q

what does one-to-one correspondance in OBIA mean

A

the geographic entity is perfectly selected and the correct spatial scale is being used.

28
Q

what is segmentation

A

pulling discrete regions out of an image

29
Q

how is a segmentation preformed

A
  • using premade algorithms
  • expert knowledge of your image and application
  • calibrate, trial and error
30
Q

what are the two types of segmentation algorthims

A

1 discontinuity based
2 similarity based

31
Q

what is a discontinuity based algorithm

A

image i sbroken based on abrubt changes in intensity, edge detection

32
Q

what is similarity based algorithm

A

image is broken using regions based on pre-defined criteria using spectral or spatial information

33
Q

Laplacian edge detection

A

-discontinuity based Segmentation algo
-directionally invariant edge detection

34
Q

Sobel edge detection

A

another algo for dicontinuity based segmentation

35
Q

thresholding

A

similarity based segmentation.
partioning a histogram

36
Q

region based segmentation

A

similarity based segmentaion that partitions an image based on region growing approach
- seed points
- growing regions

37
Q

what is Trimble

A

a segmentation algorithm that is a region merging technique
- process can be repeated at many scales

38
Q

OBIA workflow

A

depends on purpose

39
Q

partitioning an image into meaningful image objects requires….

A

an effective segmentation technique

40
Q

melt ponds

A

ponds that form on the top of glaciers that increase melting

41
Q

is C-band frequency SAR Capable of providing a seasonal prediction of spring melt ponds?

A

Active Remote Sensing (4 decks)

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