Conference PaperPDF Available

Földi eróziós modell alkalmazási lehetősége marsi körülmények között

Authors:
AZ ELMÉLET ÉS A GYAKORLAT TALÁLKOZÁSA
A TÉRINFORMATIKÁBAN
XI.
THEORY MEETS PRACTICE IN GIS
Szerkesztette:
Molnár Vanda Éva

Abriha Dávid,
Nagy Bálint,
Nagy Loránd Attila,
Pataki Angelika,
Szopos Noémi Mária
Lektorálták:
Dr. Négyesi Gábor,
Dr. Túri Zoltán Krisztián
ISBN 978-963-318-886-6
A kötet a 2020. október 29–30. között online megrendezett


A konferenciát szervezte:
A Debreceni Egyetem Földtudományi Intézete, az MTA Természetföldrajzi
Tudományos Bizottság Geoinformatika Albizottsága, az MTA DAB
Földtudományi Bizottsága, a Magyar Földrajzi Társaság, a MAGISZ, a HUNAGI
és az eKÖZIG ZRT.
Debrecen Egyetemi Kiadó
Debrecen University Press
Készült
Kapitális Nyomdaipari Kft.

Debrecen
2020
3
Tartalomjegyzék
Program 7
Előadások
Abriha Dávid – Szabó Loránd – Kwanele Phinzi – Szabó Szilárd: Városi
zöldfelületek osztályozása nagy felbontású PlanetScope és SkySat
felvételek alapján 13

autokorreláció vizsgálata Python programozási környezetben 17
Ashraf AlDabbas – Zoltán Gál: Change Detection of the Cassini Orbit
Based on Data Dissimilarity 23
Árvai László: Beltéri helymeghatározás pontosságának javítása geometriai
kényszerek használatával 31
Ayoub Barkat – György Szabó – Ramzi Benhizia – Tamás Mester –
Zakaria Rahal: Groundwater Quality Assessment of Oued Souf
Valley Using GIS 39

– Schinogl Péter – Holb Imre – Szabó Szilárd: Vetésszerkezet

alkalmazásával 47
Czimbalmos Róbert – Fazekas Mónika Éva – Murányi Eszter – Nagy
Attila – Harangi Attila: Térinformatika a karcagi növénynemesítés
szolgálatában 55

(19602019) 63
 
 

Czigány Szabolcs – Pirkhoffer Ervin – Liptay Zoltán Árpád –
Balogh Richárd – Gradwohl-Valkay Alexandra: A Dráva
hordalékviszonyainak térinformatikai vizsgálata 85

becslése a Gerecse északi részén 93
Gyenizse Péter – Morva Tamás – Ortmanné Ajkai Adrienne – Lóczy
Dénes – Halmai Ákos – Pirkhoffer Ervin: Az Alsó-Dráva-ártér
felszínborításának vizsgálata távérzékelési és geoinformatikai
módszerekkel 101

szuburbanizációjának vizsgálata térinformatikai módszerekkel –
 
Kiss Levente – Eke Zoltán: Árvízi védekezés GIS támogatással 115
4

Krisztián: INTERREG IVC – Az Európai Unió interregionális
 

módszerekkel 127

navigációs felületek 135
Kovács Dániel Márton: Városnövekedés nyomon követése Sentinel-2
 
Kovalcsik Tamás – Boros Lajos: A földrajzi/politikai polarizáció mérési
 

Sándor – Túri Zoltán Krisztián – Benkhard Borbála: Természetjáró
adottságok felmérése a Bükkben turisztikai döntéstámogató
mobilapplikáció fejlesztésének megalapozásához 159

 
Mészáros Márk: Az európai autóipar térszerkezetének vizsgálata
geoinformatikai módszerekkel 173


osztályozásával 181
Ocsovainé Steinbach Cecília: Újgenerációs hiperspektrális kamerák a
Specim kínálatában 189
Pecsmány Péter – Szabó Norbert Péter: Vízfolyások kanyarulat-
fejlettségének vizsgálata feltáró faktoranalízis segítségével 193
Kwanele Phinzi – Szilárd Szabó: NDVI-based land-use/cover change
detection in a mountainous heterogeneous landscape 201

– Krausz Nikol: Térképi formátumok értékelése az önvezetés
szempontjából 207
 György Szabó: Exploring urban sustainability
dimension through land use optimization 217
Schneck Tamás – Telbisz Tamás – Zsuffa István – Magyari Sándor István:
Radarmérésen alapuló csapadékadatok földfelszíni állomásokkal
 
Soltész Emese – Gyenizse Péter: Pécs lakott területének részletes
fényszennyezés térképe 229
Steinmann Vilmos: 
körülmények között 237

torzulás vizsgálata geodéziai módszerekkel 243
5
Szabó Andrea – Odunayo Adeniyi David – Nagy Attila:

 
Szabó Gergely – Schlosser Aletta Dóra – Nagy Loránd Attila: RTK-

felszínborításoknál 257
Szabó Loránd – Szabó Szilárd: Városi területek felszínborításának

felhasználásával debreceni mintaterületen 263

félelem térbeli elemzése, valamint az elkövetett tényleges

szinten 269
 
 
Utasi Zoltán: Szakterületek és országok közötti adatszabványosítás
 
Orsolya Gyöngyi Varga – Zoltán Kovács – Szilárd Szabó: Comparison
of characteristics of CLC2018 categories concerning NDVI and
SAVI values derived from Sentinel-2 images 297

mintaterületen 305
Poszterek

geoinformatikai módszerekkel a bükkábrányi mintaterületen 1990-
 

háromdimenziós modellezése hagyományos geodéziai módszerekkel 312
Pál Márton – Albert Gáspár: Térképi kommunikáció a földtudományokban 313

Kunhegyesi síkon 314

 
Mellékletek 317
Szponzorok és kiállítók 323
237
Földi eróziós modell alkalmazási lehetősége marsi
körülmények között
,
1 Eötvös Loránd Tudományegyetem, Természettudományi Kar, Természetföldrajzi Tanszék
2 Csillagászati és Földtudományi Kutatóközpont, Konkoly Thege Miklós Csillagászati Intézet
A Földön kívüli geomorfológiai elemzések sokat segítenek az égitestek
       

    ). A Mars esetében az egyik leginkább vizsgált
témakör az egykori (.

       2012) - bár
napjainkban csak rövid ideig és kis mennyiségben várható ( 2017)



            
), mivel a folyóvíz felszínformáló
hatása és a felszínmorfológia közötti kapcsolat sok vonatkozása már ismert (

  
. 2016).
   

alakzatok, mint a földi sivatagos, félsivatagos területek folyóvölgyei, a vádik. Az

nemzetközi kutatásokban az ilyen irányú kutatások egyre nagyobb szerepet kapnak.
A kapcsolódó munkák alapja a marsi és mars-analóg mintaterületek összehasonlítása,
valamint a felszínformák morfológiájának vizsgálata, mivel ez segíthet rekonstruálni
a Mars korai állapotát és az akkori uralkodó viszonyát. Emellett az eróziós-
akkumulációs modelleket segíthetnek még célzottabbá tenni a Mars missziókat.
Ezen kutatás során használt marsi mintaterületet a Palos kráter és Tinto Vallis

modell segítségével elemeztem (  
hivatkozás miatt a Tinto-B nevet kapta. A Tinto-B (2°55’ Dél és 111°53’ Kelet) egy
238


északi irányból két kráter határolja, a legmagasabb pont +689 m-en, a legmélyebb


Többféle elfogadott eróziós modell van földi körülményekre. A leggyakrabban
használt modell model az USLE (. 2016) (Universal Soil Loss Equation),
         



        
kísérleti adaptációja történt a már említett Tino-B völgyhálózatra.

Resolution Stereo Camera – Mars Express) 50 méter/pixel (m/px) felbontású digitális
terepmodellen (DTM-en) és a THEMIS TI (Thermal Emission Imaging System
    
). A mintaterület korbecslése
         
         
adatok közös koordináta rendszere a GCS_MARS, a DTM és a THEMIS TI egységes
felbontása 100 m/px lett, ami a spektrális adat felbontása. A kutatás során ArcMap
      
modell futtatása), Craterstat (kormeghatározás) szoftverek kerültek felhasználásra.

Az  utasítás lemodellezi a pixelenkénti vízmélységet (m) és vízhozamot

239

(m3x és irányú deriváltja
( utasítás) alapján. A modell teljes lefutásához meg kell adni egy

(min). A modell másik modulja az r.sim.sediment határozza meg az erózió és
akkumuláció értékét (kg/ms), a szediment koncentrációját (szemcse/m), szállítási
         
        
      

        
        
        
        
(     2008) a QGIS-ben készült az alábbi
raszteres egyenlettel:  , ahol x és
az osztály minimum és maximum értéke, z az új érték. A erodálási együttható a
meghatározására a DG-formula (. 2016) került felhasználásra, amely csak



formula egyenlete: fac      ,
240
ahol fac az erodálhatósági együttható, Dg meghatározható az alábbi egyenlettel:
ni  i), ahol fi a szemcsék tömegszázaléka, mi a szemcsék

      
         
egyenlettel: Dcfac  c, ahol nyírófeszültség, c kritikus nyírófeszültség A
       
( 2007): crscr 
, ahol és cr a normál és kritikus Shield-féle paraméter, s



241
 , és A
 gM, ahol gM a marsi gravitáció. A lefuttatott teszt model 5
mm/hr csapadék intenzitással számolt, mely 5 percig tartott.
A modell végeredménye segít pontosítani a vizsgált terület morfológiájának
kialakulását. A eróziós-akkumulációs térkép segítségével pontosítani lehet a korábbi
      



erózió a vízfolyás alján. A második típus esetében a az erózió a vízfolyások falán
).
A modell teljes adaptálása a marsi körülményekre még fejlesztés alatt van,

         
kapcsolva a morfológiájához.
Köszönetnyilvánítás

tekintve a GINOP-2.3.2-15-2016-00003 projekt és az NKFIH támogatta.
Referenciák
           

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, L.(
 
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         
         
1479–1490.
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

. (2018): Grid mapping the Northern Plains

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The numerical model PSEM_2D is applied to reproduce the rill experiments described by Elliot et al. (1989) for five different textured soils. PSEM_2D is a two-dimensional water flow and erosion model incorporating the first-order detachment-transport coupling model. The infiltration parameters and the friction factor are calibrated to reproduce both the flow discharges and the flow velocities measured by Elliot et al. (1989). Values of the determined friction factors are higher for the cohesive soils compared to the noncohesive soils. Four sediment transport capacity formulae for rills are tested: the Yalin, the Low, the unit stream power (Govers USP), and the effective stream power (Govers ESP) equations. These equations do not require any calibration. The erosion parameters for the first-order detachment-transport coupling model come from the Water Erosion Prediction Project (WEPP) database. They were calibrated by Elliot et al. (1989) using observed data and the rill component of WEPP. The Govers USP formula gives the best results for the cohesive soils. Nevertheless, none of the equations performs well for the noncohesive soils. The study also focuses on the results obtained for the Barnes_ND, the Bonifay, and the Collamer soils to explore the implication of the detachment-transport coupling model on the spatial erosion patterns along the rills. A detachment-limiting regime is produced over the whole rill for the Barnes_ND soil, a transport-limiting regime is reached over a very short flow distance for the Bonifay soil, and a detachment-limiting regime in the upper part along with a transport-limiting regime in the lower part of the rills is experienced for the Collamer soil.