10 research outputs found
Sentinel-2/MSI applications for European Union Water Framework Directive reporting purposes
EL veepoliitika raamdirektiiv kohustab seirata jĂ€rvi, mille suurus on vĂ€hemalt 50 ha ja hinnata nende ökoloogilist seisundit. EesmĂ€rgiks on saavutada vee ökoloogiline seisund vĂ€hemalt âheaâ, vajadusel rakendada meetmeprogramme selle saavutamiseks. S2/MSI-l on sobiv ruumiline lahutus 10, 20, 60 m, mis vĂ”imaldab uute rakenduste arendamist jĂ€rvedes, et tĂ€ita EL veepoliitika raamdirektiivi nĂ”udeid. MĂ”lema satelliidi, S2A ja S2B, korral on ajaline lahutus kesklaiustel 2-3 pĂ€eva, mis annab vĂ”imaluse analĂŒĂŒsida rohkem andmeid, et testida ja arendada uusi rakendusi S2/MSI satelliitidele. Veelgi enam, suur ajaline lahutus annab vĂ”imaluse koostada aegridu ja hinnata chl-a dĂŒnaamikat jĂ€rvedes ja rannikualadel.
S2/MSI on taimkatte kaugseire satelliit, mistĂ”ttu on oluline vĂ”rrelda erinevaid atmosfÀÀrikorrektsiooni protsessoreid, et leida parim vee kaugseireks. Kuna edukas atmosfÀÀrikorrektsioon on oluline eeldus chl-a algoritmide arendamisel, siis töö kĂ€igus testiti nelja erinevat atmosfÀÀrikorrektsiooni: ACOLITE, C2RCC, Polymer ja Sen2Cor. Töö ĂŒheks eesmĂ€rgiks oli leida parim atmosfÀÀrikorrektsioon, siis pĂ”hinedes 6-le kontaktmÔÔtmiste ja satelliidiandmete vĂ”rdlusele, osutus valituks C2RCC, millel oli kĂ”ige kĂ”rgem vee peegeldusteguri korrelatsioon pĂ”hilistel chl-a algoritmi arendamise kanalitel vĂ”rreldes in situ vee peegeldusteguriga.
Chl-a on pÔhiline parameeter vee ökoloogilise seisundiklassi hindamisel, seetÔttu teine osa uurimistööst hÔlmas chl-a algoritmide testimist ja arendamist S2/MSI kanalite jaoks. Kuna S2/MSI kanal (665 nm) chl-a neeldumispiigi lÀhedal on laiem (38 nm) kui S3/OLCI (7.5 nm) kanal, siis uurimistöö kÀigus viidi lÀbi vÔrdlus chl-a kanalite vahel, mis nÀitas, et S2/MSI on vÔimeline tuvastama chl-a erinevate kontsentratsioonide korral.. Edasine uurimine selgitas, et C2RCC ei ole vÔimeline andma tÀpseid tulemusi vÀikeste, kitsaste jÀrvede korral, kus naabrusefekt mÔjutab kaldaÀÀrseid piksleid. SeetÔttu on vÀga oluline arendada korrektsioone ka naabrusefekti eemaldamise jaoks, mis aitaksid vÀltida segupiksleid. Madalates jÀrvedes, mÀngib olulist rolli ka pÔhjaefekt, mis mÔjutab piksleid kaldaÀÀrsetes alades ja segab vee peegeldustegurit pÔhjast tuleva peegeldusega. Kuna atmosfÀÀrikorrektsioon on vÀga tÀhtis protseduur, siis kÀib pidev algoritmide testimine ja arendamine, et tagada parim Level-2 piltide informatsioon, et oleks vÔimalik arendada vÀlja uusi rakendusi.
56
MĂ”nedel juhtudel, kus naabrusefekt on vĂ€iksem, eriti suuremates jĂ€rvedes (ĂŒle 90 ha) ja kus jĂ€rv on ĂŒmmargune, seal on vĂ”imalik hinnata chl-a vees, kasutades empiirilisi algoritme. Standard C2RCC algoritm hindas jĂ€rjepidevalt chl-a, kas liiga kĂ”rgeks vĂ”i liiga madalaks, kuid siiski sĂ€ilitas chl-a dĂŒnaamika sarnaselt in situ mÔÔtmistega. MCI-l pĂ”hinev algoritm nĂ€itas hĂ€id tulemusi kĂ”rge chl-a jĂ€rvedes, koos Three-Band NIR Red Model (1/R665-1/R705)*R740 ja R705 - ((R665 + R740)/2) algoritmiga. Madala chl-a ja kĂ”rge TSM sisaldusega jĂ€rvedes töötas hĂ€sti Four-Band NIR Red Model algoritm (1/R665-1/R705)/(1/R740-1/R705), mis eemaldab TSM segava mĂ”ju, ning lisaks eelnevalt nimetatud Three-Band NIR Red Model algoritm.
Veelgi enam, atmosfÀÀrikorrektsioon C2RCC ei ole vÀga tundlik hindamaks chl-a neeldumist 665 nm kanali juures, sest chl-a neeldumispiik ei ole vÀga hÀsti nÀha vee peegeldustegurilt tÀnu naabrusefektile vÀikestes jÀrvede. See tÀhendab, et vajalikud on valideerimisandmed optiliselt keerukatest jÀrvedest, et arendada atmosfÀÀrikorrektsioone. Siiski on satelliidi andmetelt saadud chl-a arv kaks korda suurem kui in situ mÔÔtmistelt saadud arv, mis annab vÔimaluse koguda kaks korda rohkem andmeid jÀrvedest.
S2/MSI-l on palju eeliseid, et tuletada veekvaliteedi parameetreid vÀikejÀrvedel, et tÀita EU veepoliitika raamdirektiivi. AtmosfÀÀrikorrektsioonide parandused ja tÀiustused on vÀga vajalikud, et oleks vÔimalik kasutada S2/MSI eeliseid in situ mÔÔtmiste ees ja tagada regulaarne seire vÀikejÀrvedes
Landscape changes in Karula National Park over the last 100 years
Maastikud meie ĂŒmber on pidevas muutumises ja tĂ€napĂ€evane maastik on minevikus
toimunud protsesside tulemus. Ajalooliste kaartide vĂ”rdlemine annab vĂ”imaluse analĂŒĂŒsida
maastike muutumist ajas ning saada vajalikku informatsiooni traditsiooniliste ja
pÀrandmaastike kaitse ja tegevuste planeerimiseks. KÀesoleva bakalaureusetöö
uurimisĂŒlesanneteks on kirjeldada Karula rahvuspargi ala maakasutust viimase saja aasta
jooksul (1913-2010) ning seda mÔjutanud tegureid. Selgitada Karula rahvuspargi
maakattetĂŒĂŒpide pindala ja osakaalu muutuseid perioodil 1913-2010 ning selgitada
olulisemate maakattetĂŒĂŒpide ĂŒleminekud ja pĂŒsivus.
Bakalaureusetöö uurimismeetodiks oli kaardianalĂŒĂŒs (7 eri kaardi pĂ”hjal) GIS-programmis ja
andmeid töödeldi statistiliselt tabelarvutusprogrammis. UurimisĂŒlesannete lahendamisel
lÀhtuti Matsalu ja Vilsandi rahvuspargi ajaloolise maakasutuse uuringus kasutatud
metoodikast ning algandmetena kasutati Keskonnainvesteeringute Keskuse (KIK) projekti
kÀigus loodud andmestikku.
Tulemustest selgus, et viimase saja aasta jooksul on Karula rahvuspargi maastike avatus
vĂ€henenud kuni kolm korda â pĂ”llu- ja rohumaade arvelt. Maastike avatust on vĂ€hendanud
metsasuse suurenemine II maailmasÔja ajal ja jÀrgselt. Olulist rolli mÀngib ka Karula reljeefne
maastik, mis on muutnud maaharimise keerulisemaks. PĂ”lised pĂ”llud on pĂŒsima jÀÀnud
endistele talumaastikele, kuhu on koondunud ka tÀnapÀevane asustus.
Karula maastike sÀilimisel on oluline koht pÔllumajanduslikul eluviisil ja selle jÀtkumisel, et
tagada Karula maastike traditsioonilisus. Koostatud andmebaas ja koostatav pÀrandmaastike
tsoneering vÔimaldavad paremini mÀÀrata pÀrandmaastike asukohta, hinnata looduskaitse- ja
kultuurivÀÀrtuste paiknemist ning tÔhustada kaitseala kaitsekorraldust.Landscapes around us are constantly changing and the landscape we have today is a result of
different past processes. Comparing historical maps gives the opportunity to analyse the change of
landscapes in time and accumulate crucial information so we can better plan activities for the
protection of traditional and heritage landscapes. The aim of this thesis is to describe the land use
of Karula National Park, and influential factors behind it, over the last hundred years (1913â2010).
Also, examine the territories of different landscapes of Karula National Park and the changes in
their proportions between 1913 and 2010, and describe the transformations of the most significant
land cover types and their stability.
The research method of the thesis was map analysis (on the basis of seven different maps) in a
GIS-programme and a statistical grid calculation programme was used for data processing. The
methodology used in the study of the historic land-use of Matsalu and Vilsandi National Parks was
utilized for completing the research assignments and initial data was obtained through a project of
the Environmental Investment Centre.
The results showed that the openness of the landscapes of Karula National Park has decreased
three times over the last hundred years â mainly due to the decrease in arable land and grasslands.
The increase in forestation, during and after Second World War, has decreased the openness of
landscapes. Relief landscape of Karula has played a significant role as it has made farming more
complicated. Indigenous fields have persevered on former farmlands where modern settlement has
also now converged.
Agricultural lifestyle and its perseverance has an important role to play in maintaining the
traditional landscape of Karula. Compiled data-base, and the zoning of traditional landscapes that
will be completed in the future, will enable us to locate traditional landscapes more easily,
evaluate the positioning of natural protection and cultural objects and make the management of the
natural park more effective
Satellite-assisted monitoring of water quality to support the implementation of the Water Framework Directive
The EU Water Framework Directive1 (WFD) is an ambitious legislation framework to achieve good ecological and chemical status for all surface waters and good quantitative and chemical status for groundwater by 2027.âA total of 111,062 surface waterbodies are presently reported on under the Directive, 46% of which are actively monitored for ecological status.âOf these waterbodies 80% are rivers, 16% are lakes, and 4% are coastal and transitional waters.âIn the last assessment, 4% (4,442) of waterbodies still had unknown ecological status, while in 23% monitoring did not include in situ water sampling to support ecological status assessment2.âFor individual (mainly biological) assessment criteria the proportion of waterbodies without observation data is much larger; the full scope of monitoring under the WFD is therefore still far from being realised.âAt the same time, 60% of surface waters did not achieve âgoodâ status in the second river basin management plan and waterbodies in Europe are considered to be at high risk of having poor water quality based on combined microbial, physical and physicochemical indicators3
Retrieval of Chlorophyll a from Sentinel-2 MSI Data for the European Union Water Framework Directive Reporting Purposes
The European Parliament and The Council of the European Union have established the Water Framework Directive (2000/60/EC) for all European Union member states to achieve, at least, “good” ecological status of all water bodies larger than 50 hectares in Europe. The MultiSpectral Instrument onboard European Space Agency satellite Sentinel-2 has suitable 10, 20, 60 m spatial resolution to monitor most of the Estonian lakes as required by the Water Framework Directive. The study aims to analyze the suitability of Sentinel-2 MultiSpectral Instrument data to monitor water quality in inland waters. This consists of testing various atmospheric correction processors to remove the influence of atmosphere and comparing and developing chlorophyll a algorithms to estimate the ecological status of water in Estonian lakes. This study shows that the Sentinel-2 MultiSpectral Instrument is suitable for estimating chlorophyll a in water bodies and tracking the spatial and temporal dynamics in the lakes. However, atmospheric corrections are sensitive to surrounding land and often fail in narrow and small lakes. Due to that, deriving satellite-based chlorophyll a is not possible in every case, but initial results show the Sentinel-2 MultiSpectral Instrument could still provide complementary information to in situ data to support Water Framework Directive monitoring requirements
Synergy between satellite altimetry and optical water quality data towards improved estimation of lakes ecological status
European countries are obligated to monitor and estimate ecological status of lakes under European Union Water Framework Directive (2000/60/EC) for sustainable lakesâ ecosystems in the future. In large and shallow lakes, physical, chemical, and biological water quality parameters are influenced by the high natural variability of water level, exceeding anthropogenic variability, and causing large uncertainty to the assessment of ecological status. Correction of metric values used for the assessment of ecological status for the effect of natural water level fluctuation reduces the signal-to-noise ratio in data and decreases the uncertainty of the status estimate. Here we have explored the potential to create synergy between optical and altimetry data for more accurate estimation of ecological status class of lakes. We have combined data from Sentinel-3 Synthetic Aperture Radar Altimeter and Cryosat-2 SAR Interferometric Radar Altimeter to derive water level estimations in order to apply corrections for chlorophyll a, phytoplankton biomass, and Secchi disc depth estimations from Sentinel-3 Ocean and Land Color Instrument data. Long-term in situ data was used to develop the methodology for the correction of water quality data for the effects of water level applicable on the satellite data. The study shows suitability and potential to combine optical and altimetry data to support in situ measurements and thereby support lake monitoring and management. Combination of two different types of satellite data from the continuous Copernicus program will advance the monitoring of lakes and improves the estimation of ecological status under European Union Water Framework Directive
Optical Water Type Guided Approach to Estimate Optical Water Quality Parameters
Currently, water monitoring programs are mainly based on in situ measurements; however, this approach is time-consuming, expensive, and may not reflect the status of the whole water body. The availability of Multispectral Imager (MSI) and Ocean and Land Colour Instrument (OLCI) free data with high spectral, spatial, and temporal resolution has increased the potential of adding remote sensing techniques into monitoring programs, leading to improvement of the quality of monitoring water. This study introduced an optical water type guided approach for boreal regions inland and coastal waters to estimate optical water quality parameters, such as the concentration of chlorophyll-a (Chl-a) and total suspended matter (TSM), the absorption coefficient of coloured dissolved organic matter at a wavelength of 442 nm (aCDOM(442)), and the Secchi disk depth, from hyperspectral, OLCI, and MSI reflectance data. This study was based on data from 51 Estonian and Finnish lakes and from the Baltic Sea coastal area, which altogether were used in 415 in situ measurement stations and covered a wide range of optical water quality parameters (Chl-a: 0.5–215.2 mg·m−3; TSM: 0.6–46.0 mg·L−1; aCDOM(442): 0.4–43.7 m−1; and Secchi disk depth: 0.2–12.2 m). For retrieving optical water quality parameters from reflectance spectra, we tested 132 empirical algorithms. The study results describe the best algorithm for each optical water type for each spectral range and for each optical water quality parameter. The correlation was high, from 0.87 up to 0.93, between the in situ measured optical water quality parameters and the parameters predicted by the optical water type guided approach
Veetaseme seire, ĂŒleujutuste kaardistamine ja mĂ€rgalae niiskusreĆŸiim
Projekti RITA1 KAUGSEIRE kĂ€igus töötati vĂ€lja kaugseire andmete töötlemise metoodid/prototĂŒĂŒbid, mis vĂ”imaldavad parandada mitmeid jĂ€rgmisi seirerakendusi ja riiklike teenuseid: (1) ĂŒleujutuste seire satelliitpiltidel sisemaal ja rannikul; (2) veetaseme seire kasutades altimeetria andmeid; (3) veetaseme prognoosi tĂ€psustamine satelliitaltimeetria andmetega; (4) veekogu ökoloogilise klassi korrektsioon vastavalt veetaseme sesoonsele muutusele; (5) soode niiskus reĆŸiimi jĂ€lgimine kaugseire meetodiga; (6) maardlate (s.h. turbamaardlate) seire satelliitpiltidelt