izpis_h1_title_alt

Spremljanje migracij na morju in analiza vpliva izbranih begunskih centrov na okolje z daljinskim zaznavanjem : doktorska disertacija
ID Kanjir, Urška (Author), ID Oštir, Krištof (Mentor) More about this mentor... This link opens in a new window, ID Kralj, Ana (Co-mentor)

.pdfPDF - Presentation file, Download (14,64 MB)
MD5: 6284C4DC9391C8B81B773A8A10257F9D

Abstract
Migracije so stalnica človekovega obstoja. V zadnjih letih so se v Evropi drastično povečale migracije prebežnikov čez Sredozemsko morje. Njihova pot se pogosto zaključi v begunskih taboriščih, kjer so nastanjeni v slabih razmerah. V nalogi se z uporabo daljinsko zaznanih podatkov navezujemo na širšo tematiko migracij. Osredotočamo se na zaznavanje plovil prebežnikov po morju in na opazovanje vplivov, ki jih lahko povečane migracije povzročijo na okolje v okolici begunskih centrov. Za pridobitev podatkov o gibanju prebežnikov na morju raziskujemo možnosti uporabe raznovrstnih (zelo) visoko ločljivih optičnih satelitskih posnetkov. V ta namen smo razvili metodo za samodejno zaznavanje plovil, ki je v grobem sestavljena iz štirih zaporednih korakov: ločevanje kopnega in morja, določanje kandidatov za plovila, ločevanje plovil od neplovil in klasifikacija plovil. Rezultati kažejo, da z omenjenim algoritmom zaznavamo plovila najbolj natančno s posnetkov z ugodnejšimi vremenskimi razmerami. Večji problem pri zaznavi predstavljajo lažni pozitivi kot nezaznana plovila. Za odkrivanje sprememb površine taborišč sprememb smo uporabili analizo časovnih vrst BFAST (Breaks For Additive Season and Trend) Monitor, s katero spremljamo motnje v časovnih vrstah na podlagi modela stabilnega zgodovinskega vedenja. Analizo smo naredili na posnetkih Sentinel-2 na območjih begunskih taborišč na sredozemskih otokih, ki se že dlje časa srečujejo s pritokom migracij. Opazovane so bile negativno zaznane spremembe NDVI (normirani diferencialni vegetacijski indeks) v letu 2019. Ugotovili smo, da so podatki Sentinel-2 primerni za analizo časovnih vrst zaradi njihove goste časovne vrste. Ocena verjetnih vplivov v okolici begunskih taborišč je določena na podlagi treh verjetnostnih razredov glede na velikost negativne magnitude zaznanih sprememb.

Language:Slovenian
Keywords:Daljinsko zaznavanje, migracije, zaznavanje in klasifikacija plovil, optični satelitski posnetki, časovne vrste, širjenje begunskih taborišč
Work type:Doctoral dissertation (mb31)
Typology:2.08 - Doctoral Dissertation
Organization:FGG - Faculty of Civil and Geodetic Engineering
Year:2021
Publisher:[U. Kanjir]
Place:Ljubljana
PID:20.500.12556/RUL-128391 This link opens in a new window
UDC:502.1:314.151.3:352:528.8(043.3)
COBISS.SI-ID:70681347 This link opens in a new window
Publication date in RUL:10.07.2021
Views:566
Downloads:92
Metadata:XML RDF-CHPDL DC-XML DC-RDF
:
Kopiraj citat
Share:AddThis
AddThis uses cookies that require your consent. Edit consent...

Secondary language

Language:English
Title:Monitoring migrations by sea and analysis of refugee camps’ environmental impact with remote sensing : doctoral dissertation
Abstract:
Migrations have been a feature of human existence for centuries. The migrations of migrants who risk their lives to reach Europe via the Mediterranean have increased dramatically in recent times. Their journey often ends in refugee camps where they are housed in poor conditions. In this dissertation we use remote sensing data in the context of the broader issue of migration. We focus on the detection of migrant vessels at sea and the environmental impact that increased migration can have around refugee centers. In order to obtain data on the movement of migrants at sea, we investigate the possibilities of using a variety of (very) high-resolution optical satellite images. We have developed a method for automatic vessel detection consisting of four consecutive steps: sea-land separation, candidate detection, vessel discrimination and vessel classification. The results show that the developed algorithm more accurately detects vessels from images with more favourable weather conditions. False positives are a greater problem in detection than undetected vessels. To detect changes in the vicinity of the refugee camps, we used the time series analysis BFAST (Breaks For Additive Season and Trend) Monitor, which monitors disturbances in time series based on a model for stable historical behaviour. The analysis was applied on Sentinel-2 images in areas of refugee camps on the Mediterranean islands that have been experiencing long term influxes of migrants. We observed negatively detected changes in the NDVI (normalised difference vegetation index) in 2019. Sentinel-2 data proved to be suitable for time series analysis due to their dense time series. The assessment of potential environmental impacts in the vicinity of refugee camps are further determined on the basis of probability classes defined according to the negative magnitude of the observed changes.

Keywords:Remote sensing, migration, ship detection and classification, optical satellite data, time series, refugee camp sprawl

Similar documents

Similar works from RUL:
Similar works from other Slovenian collections:

Back