عنوان

Population Estimation in a Desert City Using Parameters from Satellite Imagery

شماره

TL50748

زبان متن نوشتاري يا گفتاري و مانند آن

انگلیسی

عنوان اصلي

Population Estimation in a Desert City Using Parameters from Satellite Imagery

نام عام مواد

[Thesis]

نام نخستين پديدآور

Lin, Weiying

نام ساير پديدآوران

Deng, Chengbin

نام ناشر، پخش کننده و غيره

State University of New York at Binghamton

تاریخ نشرو بخش و غیره

2019

متن يادداشت

72 p.

جزئيات پايان نامه و نوع درجه آن

M.A.

کسي که مدرک را اعطا کرده

State University of New York at Binghamton

امتياز متن

2019

متن يادداشت

Increasing population living in urban areas produces huge challenges in urban sustainable development due to its impacts on natural environment and limited public resources. Timely and reliable population information is useful for both public practices and private sectors. With the development of remote sensing techniques, increasing number of studies have attempted to estimate population distribution by using geospatial techniques. However, these studies mainly focused on temperate areas (e.g. America, Australia, and China) dominated by vegetated covers while placed less emphasis on regions with complicated desert landforms. This thesis, therefore, explored the effectiveness of two popular population indicators for mapping population distribution in Dubai, United Arab Emirates (UAE). One is remote-sensing-derived impervious surface fractions from three spectral analytical approaches (i.e. simple spectral mixture analysis, normalized spectral mixture analysis, and random forest) and the other is nighttime light (NTL) radiance imagery. With the four different indicators, population models were built, respectively, at the community level (the smallest unit in UAE) to estimate spatial population distribution. Their performances were then compared. There are three major findings in the thesis. First, random forest outperforms the other two spectral mixture analysis in terms of mapping impervious surface area in the desert environment. Second, the robustness of population estimation model is related to the precision of imperviousness distribution mapping. Finally, when compared to NTL, percent imperviousness is a more suitable indicator to estimate population density at the finer scale in a desert environment.

اصطلاح موضوعی

Geography

اصطلاح موضوعی

Remote sensing

مستند نام اشخاص تاييد نشده

Lin, Weiying

مستند نام اشخاص تاييد نشده

Deng, Chengbin

مستند نام تنالگان تاييد نشده

State University of New York at Binghamton

نام الکترونيکي

فرمت انتشار

p

نوع ماده

[Thesis]

کد کاربرگه

276903

سطح دسترسي

a

تكميل شده

Y