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Humanitarian Satellites : a remote sensing approach to built-up area estimation in refugee camps

Biella, Riccardo LU (2019) In Student thesis series INES NGEK01 20191
Dept of Physical Geography and Ecosystem Science
Abstract (Swedish)
The determination of the built-up area of a refugee camp is an important task as it can be used for estimating the population. While high resolution satellite imagery can be costly, since 2015 Sentinel-2 data has become available through the European Space Agency. Sentinel-2 offers 10 m resolution images with frequents updates. In this paper three methodologies are compared for the purpose of estimating built-up area using Sentinel-2 imagery: Index Based (using the IBI); Supervised classification; and Digitization. The study areas chosen for this study are Nyarugusu Refugee Camp, in Tanzania, and Kutupalong Refugee Camp, in Bangladesh. Of the three methodologies the Digitization offers the best in the accuracy analysis, followed by the... (More)
The determination of the built-up area of a refugee camp is an important task as it can be used for estimating the population. While high resolution satellite imagery can be costly, since 2015 Sentinel-2 data has become available through the European Space Agency. Sentinel-2 offers 10 m resolution images with frequents updates. In this paper three methodologies are compared for the purpose of estimating built-up area using Sentinel-2 imagery: Index Based (using the IBI); Supervised classification; and Digitization. The study areas chosen for this study are Nyarugusu Refugee Camp, in Tanzania, and Kutupalong Refugee Camp, in Bangladesh. Of the three methodologies the Digitization offers the best in the accuracy analysis, followed by the Supervised Classification and, finally, the Index Based Method. Yet, the other two methodologies could still find some specific application such as the delineation of small features. Furthermore, the three methodologies are used in creating a time series analysis to investigate their potentials to track the development of the built-up area of a refugee camp. The built-up area is then correlated to the population of the camp. Once again, the Digitization Method proves itself to be the most accurate of the three methodologies explored. (Less)
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author
Biella, Riccardo LU
supervisor
organization
course
NGEK01 20191
year
type
M2 - Bachelor Degree
subject
keywords
Remote Sensing, Humaitarian, Sentinel 2, Built-Up Area Estimation, IBI, NDBI, Digitization, Time Series
publication/series
Student thesis series INES
report number
480
language
English
id
8983888
date added to LUP
2019-06-14 16:43:28
date last changed
2019-06-14 16:43:28
@misc{8983888,
  abstract     = {The determination of the built-up area of a refugee camp is an important task as it can be used for estimating the population. While high resolution satellite imagery can be costly, since 2015 Sentinel-2 data has become available through the European Space Agency. Sentinel-2 offers 10 m resolution images with frequents updates. In this paper three methodologies are compared for the purpose of estimating built-up area using Sentinel-2 imagery: Index Based (using the IBI); Supervised classification; and Digitization. The study areas chosen for this study are Nyarugusu Refugee Camp, in Tanzania, and Kutupalong Refugee Camp, in Bangladesh. Of the three methodologies the Digitization offers the best in the accuracy analysis, followed by the Supervised Classification and, finally, the Index Based Method. Yet, the other two methodologies could still find some specific application such as the delineation of small features. Furthermore, the three methodologies are used in creating a time series analysis to investigate their potentials to track the development of the built-up area of a refugee camp. The built-up area is then correlated to the population of the camp. Once again, the Digitization Method proves itself to be the most accurate of the three methodologies explored.},
  author       = {Biella, Riccardo},
  keyword      = {Remote Sensing,Humaitarian,Sentinel 2,Built-Up Area Estimation,IBI,NDBI,Digitization,Time Series},
  language     = {eng},
  note         = {Student Paper},
  series       = {Student thesis series INES},
  title        = {Humanitarian Satellites : a remote sensing approach to built-up area estimation in refugee camps},
  year         = {2019},
}