Başkurt, Nur Didem

Profile URL
https://hdl.handle.net/20.500.14411/8261
Name Variants
Baskurt,N.D. N.D.Baskurt N.,Başkurt Başkurt,N.D. Nur Didem, Başkurt Baskurt, Nur Didem B.,Nur Didem B., Nur Didem Başkurt, Nur Didem N., Baskurt N.D.Başkurt Nur Didem, Baskurt Baskurt, Didem Ozisik
Job Title
Araştırma Görevlisi
Email Address
Main Affiliation
Software Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
No research topics data found.

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
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GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
0
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QUALITY EDUCATION4
QUALITY EDUCATION
0
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GENDER EQUALITY5
GENDER EQUALITY
0
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CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
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AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
0
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DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
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INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
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REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
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SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
0
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RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
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CLIMATE ACTION13
CLIMATE ACTION
0
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LIFE BELOW WATER14
LIFE BELOW WATER
0
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LIFE ON LAND15
LIFE ON LAND
1
Research Products
PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
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PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
No records found in other affiliations.
Scholarly Output

3

Articles

0

Views / Downloads

1/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

8

Scopus Citation Count

12

Patents

0

Projects

0

WoS Citations per Publication

2.67

Scopus Citations per Publication

4.00

Open Access Source

0

Supervised Theses

0

JournalCount
Conference on Image and Signal Processing for Remote Sensing XXII -- SEP 26-28, 2016 -- Edinburgh, SCOTLAND1
Conference on Image and Signal Processing for Remote Sensing XXI -- SEP 21-23, 2015 -- Toulouse, FRANCE1
Conference on Next-Generation Spectroscopic Technologies VIII -- APR 20-22, 2015 -- Baltimore, MD1
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Scopus Quartile Distribution

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2015 - 20163

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Author of Publication: search.filters.isAuthorOfPublication.4da359db-c3ad-4d13-b65c-92b19562ce21

Scholarly Output Search Results

Now showing 1 - 3 of 3
  • Conference Object
    Citation - WoS: 6
    Citation - Scopus: 9
    Shadow Removal From Vnir Hyperspectral Remote Sensing Imagery With Endmember Signature Analysis
    (Spie-int Soc Optical Engineering, 2015) Omruuzun, Fatih; Baskurt, Didem Ozisik; Daglayan, Hazan; Cetin, Yasemin Yardimci
    This study aims to develop an effective regional shadow removal algorithm using rich spectral information existing in hyperspectral imagery. The proposed method benefits from spectral similarity of shadow and neighboring nonshadow pixels regardless of the intensity values. Although the shadow area has lower reflectance values due to inadequacy of incident light, it is expected that this area contains similar spectral characteristics with nonshadow area. Using this assumption, the endmembers in both shadowed and nonshadow area are extracted by Vertex Component Analysis (VCA). On the other hand, HySime algorithm overcomes estimating number of endmembers, which is one of the challenging parts in hyperspectral unmixing. Therefore, two sets of endmembers are extracted independently for both shadowed and nonshadow area. The proposed study aims at revealing the relation between these two endmember sets by comparing their pairwise similarities. Finally, reflectance values of shadowed pixels are re-calculated separately for each spectral band of hyperspectral image using this information.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 1
    A Novel Method To Detect Shadows on Multispectral Images
    (Spie-int Soc Optical Engineering, 2016) Sevim, Hazan Daglayan; Cetin, Yasemin Yardimci; Baskurt, Didem Ozisik; Yardlmcl Çetin, Yasemin; Özlşlk Başkurt, Didem; Daǧlayan Sevim, Hazan
    Shadowing occurs when the direct light coming from a light source is obstructed by high human made structures, mountains or clouds. Since shadow regions are illuminated only by scattered light, true spectral properties of the objects are not observed in such regions. Therefore, many object classification and change detection problems utilize shadow detection as a preprocessing step. Besides, shadows are useful for obtaining 3D information of the objects such as estimating the height of buildings. With pervasiveness of remote sensing images, shadow detection is ever more important. This study aims to develop a shadow detection method on multispectral images based on the transformation of C-1 C-2 C-3 space and contribution of NIR bands. The proposed method is tested on Worldview-2 images covering Ankara, Turkey at different times. The new index is used on these 8-band multispectral images with two NIR bands. The method is compared with methods in the literature.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 2
    Utilizing Hyperspectral Remote Sensing Imagery for Afforestation Planning of Partially Covered Areas
    (Spie-int Soc Optical Engineering, 2015) Omruuzun, Fatih; Baskurt, Didem Ozisik; Daglayan, Hazan; Cetin, Yasemin Yardimci; Yardimci Cetin, Yasemin; Ozisik Baskurt, Didem
    In this study, a supportive method for afforestation planning process of partially forested areas using hyperspectral remote sensing imagery has been proposed. The algorithm has been tested on a scene covering METU campus area that is acquired by high resolution hyperspectral push-broom sensor operating in visible and NIR range of the electromagnetic spectrum. The main contribution of this study to the literature is segmentation of partially forested regions with a semi-supervised classification of specific tree species based on chlorophyll content quantified in hyperspectral scenes. In addition, the proposed method makes use of various hyperspectral image processing algorithms to improve identification accuracy of image regions to be planted.