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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

Postal Subscription Code 80-963

2018 Impact Factor: 1.205

Front Earth Sci    2012, Vol. 6 Issue (1) : 75-82    https://doi.org/10.1007/s11707-011-0188-8
RESEARCH ARTICLE
Extraction of palaeochannel information from remote sensing imagery in the east of Chaohu Lake, China
Xinyuan WANG1,2, Zhenya GUO2, Li WU3(), Cheng ZHU3, Hui HE2
1. Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; 2. College of Territorial Resources and Tourism, Anhui Normal University, Wuhu 241000, China; 3. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210093, China
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Abstract

Palaeochannels are deposits of unconsolidated sediments or semi-consolidated sedimentary rocks deposited in ancient, currently inactive river and stream channel systems. It is distinct from the overbank deposits of currently active river channels, including ephemeral water courses which do not regularly flow. We have introduced a spectral characteristics-based palaeochannel information extraction model from SPOT-5 imagery with special time phase, which has been built by virtue of an analysis of remote sensing mechanism and spectral characteristics of the palaeochannel, combined with its distinction from the spatial distribution and spectral features of currently active river channels, also with the establishment of remote sensing judging features of the palaeochannel in remote sensing image. This model follows the process of supervised classification → farmland masking and primary component analysis → underground palaeochannel information extraction → information combination → palaeochannel system image. The Zhegao River Valley in the east of Chaohu Lake was selected as a study area, and SPOT-5 imagery was used as a source of data. The result was satisfactory when this method has been successfully applied to extract the palaeochannel information, which can provide good reference for regional remote sensing archeology and neotectonic research. However, the applicability of this method needs to be tested further in other areas as the spatial characteristics and spectral response of palaeochannel might be different.

Keywords palaeochannel      remote sensing      information extraction      spectral characteristic      Chaohu Lake     
Corresponding Author(s): WU Li,Email:jedi-wuli@163.com   
Issue Date: 05 March 2012
 Cite this article:   
Xinyuan WANG,Zhenya GUO,Li WU, et al. Extraction of palaeochannel information from remote sensing imagery in the east of Chaohu Lake, China[J]. Front Earth Sci, 2012, 6(1): 75-82.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-011-0188-8
https://academic.hep.com.cn/fesci/EN/Y2012/V6/I1/75
Fig.1  Location map of the study area
SensorSpectral wavebandGround resolution/mWavelength range/μm
SPOT-5Panchromatic100.48–0.71
B1: green100.50–0.59
B2: red100.61–0.68
B3: near infrared100.78–0.89
B4: short-wave infrared (SWIR)201.58–1.75
Tab.1  Spectral wavelength and resolution of SPOT-5
Fig.2  Supervised classification map of the Zhegao River Valley
Reference imageEvaluated image
Land use typeWater bodyResidential areaMassif and woodlandCultivated landTotal
Water body17090001709
Residential area721890363912416
Massif and woodland04166521671
Cultivated land18520417326743236
Total19662098220127679032
Tab.2  Classification error matrices
Land use typeMapping accuracyOmission errorUser accuracyMisclassification error
Water body1709/1709= 100%01709/1966= 86.93%13.07%
Residential area1890/2416= 78.23%21.77%1890/2098= 90.09%9.91%
Massif and woodland1665/1671= 99.64%0.36%1665/2201= 75.65%24.35%
Cultivated land2674/3236= 82.63%3.36%2674/2767= 96.64%17.37%
Tab.3  Basic accuracy index
PCA of original imagePCA of farmland masking
NO.EigenvalueNO.Eigenvalue
PC10.839091PC10.839091
PC20.134602PC20.134602
PC30.019263PC30.019263
PC40.007044PC40.007044
Tab.4  Characteristic values from principal components analysis
Fig.3  Planar scatter plot of original image
Fig.4  Planar scatter plot of masking image
Fig.5  Endmember selection of masking image
Fig.6  Distribution of palaeochannels in the Zhegao River Valley
1 Bai Z P (1994). Remote sensing study on the changes in Tarim River system. Journal of Capital Normal University (Natural Science Edition) , 15(3): 105-111 (in Chinese with English abstract)
2 Bridge J S (1985). Palaeochannel patterns inferred alluvial deposits: A critical evaluation. Journal of Sedimentary Research , 55(4): 579-589
3 Brown A G, Ellis C, Roseff R (2010). Holocene sulphur-rich palaeochannel sediments: Diagenetic conditions, magnetic properties and archaeological implications. Journal of Archaeological Science , 37(1): 21-29
4 Chen D C, Liu S R, Chen Z Y, Chen J (2002). Remote sensing study on ancient sites in Shanghai Region. Journal of East China Normal University (Natural Science Edition) , 3: 83-87 (in Chinese with English abstract)
5 Chorography Compiling Commission of Chaohu City (1992). Chaohu Chorography. Hefei: Huangshan Publishing House, 112-113 (in Chinese)
6 Du J K, Huang Y S, Feng X Z, Wang Z L (2001). Study on water bodies extraction and classification from SPOT image. Journal of Remote Sensing , 5(3): 214-219 (in Chinese with English abstract)
7 Du Y Y, Zhou C H (1998). Automatically extracting remote sensing information for water bodies. Journal of Remote Sensing , 2(4): 265-269 (in Chinese with English abstract)
8 Gao C, Wang X Y, Qian Y C, Wu W H, He L (2008). Research on distribution of relics of Zhegao River Basin. Journal of Chinese Historical Geography , 23(2): 46-51 (in Chinese with English abstract)
9 Guo H D, Liu H, Wang X Y, Shao Y, Sun Y (2000a). Subsurface old drainage detection and paleoenvironment analysis using spaceborne radar images in Alxa Plateau. Science in China (Series D) , 43(4): 439-448
doi: 10.1007/BF02959455
10 Guo H D, Wang X Y, Liu H, Wang C L (2000b). Paleodrainage detection with shuttle imaging radar and radarsat data in Alxa Plateau in China. In: Proceedings of Geoscience and Remote Sensing Symposium. IEEE 2000 International , 7: 3222-3224
11 He Y H, Sun Y J (2001). The application of satellite remote sensing to answer the riddle of Loulan’s disappearance. Remote Sensing for Land & Resources , 2: 64-67 (in Chinese with English abstract)
12 Kalickl T (1987). Late glacial paleochannel of the Vistula River in Kraków-Nowa Huta. Studia Geomorphologica Carpatho-Balcanica , 21: 93-108
13 Kemp J, Rhodes E J (2010). Episodic fluvial activity of inland rivers in southeastern Australia: Palaeochannel systems and terraces of the Lachlan River. Quaternary Science Reviews , 29(5-6): 732-752
14 Khan Z A (1987). Paleodrainage and paleochannel morphology of a Barakar River (Early Permian) in the Rajmahal Gondwana Basin, Bihar, India. Palaeogeography, Palaeoclimatology, Palaeoecology , 58(3-4): 235-247
doi: 10.1016/0031-0182(87)90063-0
15 McCauley J F, Breed C S, Schaber G G, Mchugh W, Issawi B, Haynes C, Grolier M, Kilani A (1986). Paleodrainages of the Eastern Sahara-The Radar Rivers Revisited (SIR A/B Implications for a Mid-Tertiary trans-African Drainage System). IEEE Transactions on Geoscience and Remote Sensing , GE-24(4): 624-648
doi: 10.1109/TGRS.1986.289678
16 Parcak S H (2009). Satellite Remote Sensing for Archaeology. New York: Routledge, Taylor & Francis e-Library
17 Rathore V S, Nathawat M S, Champatiray P K (2010). Palaeochannel detection and aquifer performance assessment in Mendha River catchment, Western India. Journal of Hydrology , 395(3-4): 216-225
18 Smedt P D, Meirvenne M V, Meerschman E, Saey T, Bats M, Court-Picon M, Reu J D, Zwertvaegher A, Antrop M, Bourgeois J, Maeyer P D, Finke P A, Verniers J, Crombé P (2011). Reconstructing palaeochannel morphology with a mobile multicoil electomagnetic induction sensor. Geomorphology , 130(3-4): 136-141
19 Smith D N, Fletcher M, Head K, Smith W, Howard A J (2010). Environmental reconstruction of a later prehistoric palaeochannel record from Burrs Countryside Park, Bury, Greater Manchester. Environmental Archaeology , 15(1): 16-31
20 Wang X Y, Guo H D, Chang Y M, Zha L S (2004). On paleodrainage evolution in mid-late Epipleistocene based on radar remote sensing in northeastern Ejin Banner, Inner Mongolia of China. Journal Geograpical Sciences , 14(2): 235-241
doi: 10.1007/BF02837539
21 Wang X Y, Guo H D, Shao Y, Wang C L, Wang C Z, Liu H (2002). Analysis of shallow ground-water based on SIR-C data in North Ejin County of Inner Mongolia. Journal of Remote Sensing , 6(6): 523-527 (in Chinese with English abstract)
22 Wang X Y, He H, Zhou Y Q, Gao C, Han S (2006). Analysis of remote sensing archaeology on traffic function transformation of Tongji Grand Canal in Sui and Tang Dynasty. Chinese Geographical Science , 16(2): 95-101
doi: 10.1007/s11769-006-0001-x
23 Wu A Q, Zhao H J, Yang R X, Liu C Y, Guo Y S, Wang C (2002). Test study on remote sensing archaeology of ancient river course and city in Kaifeng. Areal Research and Development , 21(3): 85-88 (in Chinese with English abstract)
24 Wu C (2002). The object, content and methods of studying cultural “Ancient River Science”. Geography and Territorial Research , 18(4): 82-85 (in Chinese with English abstract)
25 Wu C (2008). New problems and countermeasures in utilizing the ancient river channels of North China Plain. Geography and Geo-Information Science , 24(3): 83-85 , 99 (in Chinese with English abstract)
26 Wu C, Xu Q H, Zhang X Q, Ma Y H (1996). Palaeochannels on the North China Plain: Types and distribution. Geomorphology , 18(1): 5-14
doi: 10.1016/0169-555X(95)00147-W
27 Xu Q H, Wu C, Zhu X Q, Yang X L (1996). Palaeochannels on the North China Plain: Stage division and palaeoenvironments. Geomorphology , 18(1): 15-26
doi: 10.1016/0169-555X(95)00148-X
28 Yin N, Wang C L, Nie Y P, Yang L (2005). Extraction of the Great Wall information from remote sensing imagery. Journal of Remote Sensing , 9(1): 87-92 (in Chinese with English abstract)
29 Zhang L, Han G H, Yan D K (2004). Changes of Santun River and Hutubi River (Xinjiang, China) in the past 300 years. Acta Scicentiarum Naturalum Universitis Pekinesis , 40(6): 956-970 (in Chinese with English abstract)
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