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Irem Ayhan

Bio: Irem Ayhan is an academic researcher from Dokuz Eylül University. The author has contributed to research in topics: Spatial analysis & Urban planning. The author has an hindex of 2, co-authored 2 publications receiving 28 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, the historical spatial development of a large-size city can be approximated using historical geographical and categorical data pertaining to its places of worship, including temples, churches, synagogues and mosques.

30 citations

01 Jun 2007
TL;DR: Suc farkli donemlerde as mentioned in this paperarkli bolgeler tarafindan Farkli sekillerde tanimlanmistir, suca etki eden faktorlerin tespitine yonelik olarak yakin gecmiste yapilmis olan ampirik calismalarin taramasi niteligindedir.
Abstract: Suc farkli donemlerde, farkli bolgeler tarafindan farkli sekillerde tanimlanmistir. Bu nedenle evrensel bir tanimini yapmak zordur. Suc islemeyi onleme calismalari icin suca neden olan faktorlerin tespit edilmesi esastir. Bu calisma, suca etki eden faktorlerin tespitine yonelik olarak yakin gecmiste yapilmis olan ampirik calismalarin taramasi niteligindedir. Burada amac faktorleri gruplandirarak kent ve suc arasindaki olculebilir iliskileri ortaya koymaktir. Calismada once sucun tanimi uzerinde durulmus, sonra konu kapsaminda yapilmis ampirik calismalar, yapildiklari cografya ve icerikleri hakkinda kisa bilgi verilmis ve icerdikleri suca denen olan faktorler tespit edilmistir. Tarama sonucunda suca neden olan faktorler dort ana baslik altinda gruplandirilmistir: (1) sosyal ve kulturel, (2) ekonomik, (3) demografik, (4) mekansal faktorler. Bu ana basliklarin alt basliklari taranarak faktorlerin sayisal olarak gecmis calismalarda nasil olculdugunu ve degiskenlere donusturuldugu ortaya konmustur. Calisma bu yonuyle ileride kent ve suc arasindaki iliskiyi irdeleyecek ampirik calismalar icin kaynak niteligindedir

6 citations


Cited by
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Journal ArticleDOI
TL;DR: This study is the first to use remote sensing data to examine the decadal land cover changes in Saudi Arabia’s eastern coastal city of Al-Khobar between 1990 and 2013 and shows a high rate of urban sprawl and the city dispersing near the outskirts and towards the neighboring cities of Dhahran and Dammam.
Abstract: While several studies examined land use and land cover changes in the central and western parts of Saudi Arabia, this study is the first to use remote sensing data to examine the decadal land cover changes in Saudi Arabia’s eastern coastal city of Al-Khobar between 1990 and 2013. Specifically, it utilized ISODATA classification method to classify Landsat TM, ETM+, and OLI data collected from 1990, 2001, and 2013 and then detected changes in the land cover within the study area. It then measured urban sprawl by calculating the relative Shannon’s entropy index values for the three years. With overall classification accuracies greater than 85%, the results show that urban built-up areas increased by 117% between 1990 and 2001 and 43.51% from 2001 to 2013. Vegetation increased by 110% from 1990 to 2001 and by 52% between 2001 and 2013. The entropy index values of 0.700 (1990), 0.779 (2001), and 0.840 (2013) indicates a high rate of urban sprawl and the city dispersing near the outskirts and towards the neighboring cities of Dhahran and Dammam. Future studies should examine the current challenges faced by the city’s residents due to urban expansion and attempt to find ways to resolve them in the near future.

114 citations

Journal ArticleDOI
01 May 2018-Energy
TL;DR: Wang et al. as discussed by the authors investigated spatiotemporal patterns of electric power consumption (EPC) in the Belt and Road countries from multiple perspectives, and found that the EPC growth mainly occurs in the developing countries, especially in China.

84 citations

Journal ArticleDOI
01 Nov 2020-Land
TL;DR: Wang et al. as mentioned in this paper explored the spatiotemporal characteristics of traditional villages at the city, province, and geographic zone scales by a series of Geographic Information System (GIS)-based methods.
Abstract: Traditional villages are important carriers of traditional cultural heritage, and they have strong historical, cultural, aesthetic and tourism value for all countries and the international community. In China, the number of traditional villages is currently decreasing each year, and the precious material and non-material heritage is at risk of disappearing in the process of urbanization. A comprehensive understanding of the spatiotemporal patterns of traditional villages on multiple scales has important significance in protecting traditional culture, revitalizing traditional villages and achieving sustainable urbanization. Therefore, the spatiotemporal characteristics of traditional villages at the city, province, and geographic zone scales are explored by a series of Geographic Information System(GIS)-based methods in this article. Specifically, the analysis units are multi-scale, the applied methods are multi-variate, and the identified patterns are multi-perspective. The results demonstrate that the distribution of traditional villages in China is unbalanced over space and time. Moreover, the different spatiotemporal distributions of traditional villages are sensitive to scales. These findings clarify differences in the corresponding geographic and environmental factors, the level of economic development and local policy support. We further suggest that exploring the effective and suitable modes of protection and rural development is necessary. The results of this article revealing the unbalanced spatiotemporal distribution of traditional villages can provide valuable suggestions and insights into alleviating regional inequality in China.

23 citations

Journal ArticleDOI
TL;DR: Results demonstrate that the decrease in the intensity of SUHI was mainly guided by a stronger warming in daytime and nighttime LST in the neighborhood of urban localities, accompanied by a decrease in surface albedo and diurnal temperature range (DTR) over these areas.
Abstract: We also would like to thank the ORNL DAAC for providing MODIS/VIIRS LST data. A. El Kenawy, M. Hereher, Talal Al-Awadhi, Ali Al-Buloshi, Noura Al Nasiri, and Salim Al-Hatroushi are administratively supported by Sultan Qaboos University, Oman. MFM was supported by the King Abdullah University of Science and Technology (KAUST).

13 citations