Youtube daily Jan 15 2017

hi .. Im Baraah Amer from birzeit university today I will explain for you accuracy assessment

Collect reference data: "ground truth" • Determination of class types at specific locations Compare reference to classified map •

accuracy should be at least 85%

Accuracy Assessment dtermind on The nature of the region , The aim of the study, choosing reference source .. size of reference plots ..position and number of samples... sampling method

Open Erdas ERDAS IMAGINE 2014 program

open a viewer and display the supervised image from open raster

open a viewer then open raster and display an "un-classified" image from different satellite such as spot if u are using landsate

fit to frame

from raster icon we choose supervised then accuracy assessment

from file icon we choose open

we get our supervised image

okay

select edit then CREATE/ADD RANDOMM POINTS

number of points set it to 100 or set it as u want

Select the distribution you want

either "random", "stratified random", or "equalized random"

RANDOM which observations are randomly placed.

Stratified Random Sampling : a minimum number of observations are randomly placed in each category

I will select the distribution parameters to RANDOM

we have different numbers it depends on your classifications ID

We don't want 0 so I will delete them

right click select Criteria

Class == 0

select Close right click delete selection

select VIEW then SELECT VIEWER

the image you select is the reference

then select VIEW | SHOW ALL.

All of the random points will be displayed as WHITE in the viewer that you have selected earlier as a reference

in REFERENCE column, enter your best guess of a class VALUE for the pixel covered by each reference point "the numeric value"

As you do this the color of the point in the viewer will change to yellow

to see the numeric value you assigned to each class display attribute table for ur supervised image

ten select REPORT | ACCURACY REPORT .

it isn't that difficult to understand most of the report.

The error matrix simply compares the reference points to the classified points. The Kappa coefficient

expresses the proportionate reduction in error generated by a classification process compared with the error of a completely random classification

if u want more information look at the link in the description box.

For more infomation >> Accuracy assessment erdas imagine 2014 eng sub - Duration: 35:16.

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