Analyzing Geospatial patterns of syrian refugee flows in southeastern Turkey by use of remote sensing and complementary data


Autoria(s): Machado, Daniel Carlos dos Santos
Contribuinte(s)

Prinz, Torsten

Knoth, Christian

Pla, Filiberto

Data(s)

26/03/2015

26/03/2015

30/01/2015

Resumo

Crisis-affected communities and global organizations for international aid are becoming increasingly digital as consequence geotechnology popularity. Humanitarian sector changed in profound ways by adopting new technical approach to obtain information from area with difficult geographical or political access. Since 2011, turkey is hosting a growing number of Syrian refugees along southeastern region. Turkish policy of hosting them in camps and the difficulty created by governors to international aid group expeditions to get information, made such international organizations to investigate and adopt other approach in order to obtain information needed. They intensified its remote sensing approach. However, the majority of studies used very high-resolution satellite imagery (VHRSI). The study area is extensive and the temporal resolution of VHRSI is low, besides it is infeasible only using these sensors as unique approach for the whole area. The focus of this research, aims to investigate the potentialities of mid-resolution imagery (here only Landsat) to obtain information from region in crisis (here, southeastern Turkey) through a new web-based platform called Google Earth Engine (GEE). Hereby it is also intended to verify GEE currently reliability once the Application Programming Interface (API) is still in beta version. The finds here shows that the basic functions are trustworthy. Results pointed out that Landsat can recognize change in the spectral resolution clearly only for the first settlement. The ongoing modifications vary for each case. Overall, Landsat demonstrated high limitations, but need more investigations and may be used, with restriction, as a support of VHRSI.

Identificador

http://hdl.handle.net/10362/14556

201394022

Idioma(s)

por

Direitos

openAccess

Palavras-Chave #Object-based time-series #Google Earth Engine #Refugee camps monitoring #Retrospective analysis
Tipo

masterThesis