Monitoring changes of fluvial gravel bars with remote sensing : doctoral dissertation

Stančič, Liza (author), Oštir, Krištof (mentor), Kokalj, Žiga (comentor)

Gravel bars are dynamic areas of bedload deposition in rivers. They perform important ecological functions and are considered indicators of changes in the hydrological characteristics of rivers. Satellite images with a frequent revisit period and a large area of simultaneous coverage are an ideal data source for monitoring many natural features including gravel bars. Openly and freely available remote sensing data from the Sentinel-2 and Landsat systems have a spatial resolution that may be too coarse for accurate detection of gravel bars, especially in mountainous areas where rivers and related features are narrow. We therefore developed a sub-pixel mapping method based on spectral mixture analysis. Very high resolution aerial orthophotos and satellite images, as well as field mapping, were used as reference. Sentinel-2 and Landsat spectral bands were supplemented with spectral indices to increase the separability between land cover classes of interest. Automatically selected endmembers led to results with similar accuracy as when manually selected endmembers were used. Endmembers selected on one image of the study area during the leaf-on season could be used to analyse another image of the same study area acquired with the same remote sensing system at a different time. The fraction maps were found to be more accurate than maps produced by hard classification with Spectral Angle Mapper using the same input data. Considering these findings, we produced fraction maps of gravel, vegetation, and water presence for the Soča and Sava rivers in Slovenia, and the Vjosa river in Albania for a period of over 30 years. The thematic accuracy of the maps was within 90%. We also tested the ability of fraction maps for change detection and found that changes of at least 400 m2 could be accurately detected. The time series plots can also be used to detect gravel removal as demonstrated at known excavation sites near the Dolje settlement on Soča and near Kranj on Sava. The dissertation contributes to science with new insights about the application of sub-pixel mapping for monitoring natural processes. The developed method can be applied to study areas where less in situ data are available. More informed management decisions can be made based on newly acquired knowledge.

• Language: English
• Keywords: Environmental Protection, civil engineering, doctoral thesis, bedload, gravel bars, monitoring, mountainous areas, multispectral data, optical images, remote sensing, rivers, soft classification, spectral mixture analysis, sub-pixel mapping
• Work type: Doctoral dissertation
• Typology: 2.08 - Doctoral Dissertation
• Organization: FGG - Faculty of Civil and Geodetic Engineering
• Place of publishing: Ljubljana
• Publisher: [L. Stančič]
• Year: 2022
• Number of pages: XXXIII, 152 str., [88] str. pril.
• PID: 20.500.12556/RUL-141966-530c9e1b-1da2-1138-e448-222415b0ea70
• UDC: 528.8:33.055:553.624(282)(043)
• COBISS.SI-ID: 126290947
• Publication date in RUL: 13.10.2022

Secondary language

• Language: Slovenian
• Title: Ugotavljanje sprememb rečnih prodišč z daljinskim zaznavanjem : doktorska disertacija

Abstract

Prodišča so dinamična območja odlaganja plavin v rekah. Opravljajo pomembne ekološke funkcije in veljajo za pokazatelje sprememb hidroloških značilnosti rek. Satelitski posnetki s kratkim časom ponovnega obiska in velikim območjem hkratne pokritosti so idealen vir podatkov za spremljanje številnih naravnih značilnosti, vključno s prodišči. Prosto dostopni podatki daljinskega zaznavanja sistemov Sentinel-2 in Landsat imajo prostorsko ločljivost, ki je lahko preveč groba za natančno odkrivanje prodišč, zlasti na gorskih območjih, kjer so reke in z njimi povezane značilnosti ozke. Zato smo razvili podpikselsko metodo kartiranja, ki temelji na analizi vsebnosti spektralnega signala. Za referenco smo uporabili letalske ortofote, satelitske posnetke zelo visoke ločljivosti in terensko kartiranje. Poleg spektralnih pasov Sentinel-2 in Landsat smo za boljše ločevanje med izbranimi razredi pokrovnosti uporabili spektralne indekse. Samodejno izbrani končni piksli so omogočili kartiranje s podobno natančnostjo kot ročno izbrani končni piksli. Končne piksle, izbrane na enem posnetku študijskega območja med sezono olistanja, lahko uspešno uporabimo za SMA drugih posnetkov istega območja, pridobljene z istim sistemom daljinskega zaznavanja na drugi točki sezone olistanosti. Karte deležev pokrovnosti so natančnejše od kart, izdelanih s trdo klasifikacijo s Spectral Angle Mapper z uporabo istih vhodnih podatkov. Ob upoštevanju teh ugotovitev smo izdelali karte deležev proda, vegetacije in vode za Sočo, Savo in Vjoso (Albanija) za obdobje več kot 30 let. Tematska natančnost kart je znotraj 90%. Preizkusili smo tudi sposobnost kart deležev pokrovnosti za zaznavanje sprememb in ugotovili, da je mogoče natančno zaznati spremembe v obsegu vsaj 400 m2 . Časovne vrste lahko uporabimo tudi za zaznavanje odstranjevanja proda, kot je vidno na znanih območjih odvzema proda pri naselju Dolje na Soči in pri Kranju na Savi. Disertacija prispeva k znanosti z novimi spoznanji o uporabi podpikselskega kartiranja za spremljanje naravnih procesov. Razvito metodo lahko uporabimo za proučevanje območij, kjer je na voljo manj terenskih podatkov. Na podlagi novo pridobljenega znanja je mogoče sprejemati boljše odločitve o upravljanju z vodami in varstvu habitatov.

• Keywords: Varstvo okolja, disertacije, analiza vsebnosti spektralnega signala, a, daljinsko zaznavanje, mehka klasifikacija, optični posnetki, plavine, podpikselsko kartiranje, prodiščaa, reke, spremljanje, večspektralni podatki