2018
DOI: 10.5194/isprs-archives-xlii-5-749-2018
|View full text |Cite
|
Sign up to set email alerts
|

Object Oriented Classification and Feature Extraction for Parts of East Delhi Using Hybrid Approach

Abstract: <p><strong>Abstract.</strong> Rapid urbanization of Indian cities requires a focused attention with respect to preparation of Master Plans of cities. Urban land use/land cover from very high resolution satellite data sets is an important input for the preparation of the master plans of the cities along with extraction of transportation network, infrastructure details etc. Conventional classifiers, which are pixel based do not yield reasonably accurate urban land use/land cover classification … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
2

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 9 publications
0
1
0
Order By: Relevance
“…In eCognition Developer 9.2, we used the nearest neighbor fuzzy (Equation ( 1)) classification. It is used in eCognition automatically by generating multidimensional membership functions [47][48][49][50][51][52][53][54]. Based on Table 2, we created eight LULC groups (cultivated, bar, built up, grazing, plantation, shrub-bush, water body, and forest land).…”
Section: Sources and Analyses Of Data For Lulc Change Detection And P...mentioning
confidence: 99%
“…In eCognition Developer 9.2, we used the nearest neighbor fuzzy (Equation ( 1)) classification. It is used in eCognition automatically by generating multidimensional membership functions [47][48][49][50][51][52][53][54]. Based on Table 2, we created eight LULC groups (cultivated, bar, built up, grazing, plantation, shrub-bush, water body, and forest land).…”
Section: Sources and Analyses Of Data For Lulc Change Detection And P...mentioning
confidence: 99%