Abstract
Rainfall is one of the most important factors affecting various types of hazards such as: landslides, floods, sea level rise and so on. With the availability of satellite rainfall estimates at fine time and space resolution, it has also become possible to mitigate such problems over the world. But satellite rainfall needs to be monitored before use, because the satellite data does not reflect the strong influences on precipitation of topography in some cases. Relief of study area is very complex including mountain and plain areas. In this paper we present a Decision System and an intelligent geoportal for North Vietnam based on Web Service allowing users to investigate satellite rainfall by means of a direct comparison and of the Revised Universal Soil Loss Equation (RUSLE) model. The comparison method uses data from Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN) and rain gauges (RG) to investigate the interpolation of RG data. Furthermore, we also estimate a correlation and examined a percentage of simultaneous rain or no-rain between them. We realize that correlation between PERSIANN and gauge data meets expectation value when we investigate monthly data. The RUSLE model for computing the soil loss, which requires a huge amount of information and data, was handled for both PERSIANN product and rain gauges data to estimate the difference due to the usage of the two data sources.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Prevention Web [PW], International disaster database (1978), http://www.preventionweb.net/english/countries/statistics/?cid=190. Accessed 06 June 2012
Oxfam, Viet nam climate change, adaptation and poor people. Oxfam International, ISBN 978-1-84814-055-4 (2008), www.oxfam.org.uk/publications
M. Craglia, K. be Bie, D. Jackson, M. Pesaresi, G. Remeyer, C. Wang, A. Annoni, L. Bian, F. Campbell, M. Ehlers, J.van Genderen, M. Goodchildi, H. Guo, A. Lewis, R. Simpson, A. Skidmore, A. Skidmore, P. Woodgate, Digital earth 2020: towards the vision for the next decade. Int. J. Digit. Earth 5(1), 4–21 (2012)
A. Iwaniak, I. Kaczmarek, T. Kubik, J. Lukowicz, W. Paluszyński, D. Kourie, A. Cooper, S. Coetzee, An intelligent Geoportal for spatial planning. 25th International Cartographic Conference, Paris, 4–8 July 2011
J.-Y. Choi, B.A. Engel, R.L. Farnsworth, Web-based GIS and spatial decision support system for watershed management. J. Hydroinform. 7(3), (2005)
J. Bo, T. Xiaxin, L. Ping, W. Yanru, WebGIS based information and decision-marking support system for earth disaster reduction. FSKD’09 Proceedings of the 6th International Conference on Fuzzy Systems and Knowledge Discovery, vol. 7 (IEEE Press, Piscataway, 2009), pp. 397–401
D. Mioc, B. Nickerson, E. MacGillivray, A. Morton, F. Anton, D. Fraser, P. Tang, G. Liang, Early warning and mapping for flood disasters. WebMGS: 1st International Workshop on Pervasive Web Mapping, Geoprocessing and Services, Como, Italy, 26–27 Aug 2010
SWE Common Data Model Encoding Standard 1.0, OGC, http://www.opengeospatial.org/standards/swecommon. Accessed 20 Sept 2012
N. Gross, The Earth will don an electronic skin: Interview with Cherry Murray. Business week online (1999), http://www.businessweek.com/1999/99_35/b3644024.htm. Accessed Oct 2012
M. Botts, A. Robin, Bringing the sensor web together. WWW document (2007a), http://www.brgm.fr/dcenewsFile?ID=473. Accessed Oct 2012
WPS. OGC web processing service 1.0.0, OGC, http://www.opengeospatial.org/standards/wps. 2009
CHRS, Center for hydrometeorology & remote sensing, University of California, Irvine, http://chrs.web.uci.edu. Last Accessed Jun-2012
M. Cannata, M. Antonovic, ISTSOS: investigation of the sensor observation service. WebMGS 1st international workshop on pervasive web mapping, geoprocessing and services, Como, Italy, 26–27 Aug 2010
M. Botts, A. Robin, OpenGIS® sensor model language (SensorML) implementation specification, version 1.0, OGC document 07-000 (2007b), http://www.opengeospatial.org/standards/sensorml
G. Fenoy, N. Bozon, V. Raghavan, ZOO-Project: the open WPS platform. Appl. Geomat. Jan 2012
G.K. Renard, G.R. Foster, G.A. Weesies, J.P. Porter, RUSLE-revised universal soil loss equation. J. Soil Water Conserv. 46, 30–33 (1991)
A.H. Sheikh, S. Palria, A. Alam, Integration of GIS and universal soil loss equation (USLE) for soil loss estimation in a himalayan watershed. Recent Res. Sci. Technol. 3(3), 51–57 (2011)
L. Yaolin, L. Zhijun, A study on estimation of the amount of soil erosion in small watershed based on GIS: A case study in the three gorge area of China, in Proceedings of Geospatial Information, Data Mining, and Applications (2005)
A.A. Millward, J.E. Mersey, Adapting the RUSLE to model soil erosion potential in a mountainous tropical watershed. Catena 38(2), 109–129 (1999)
Agriculture Handbooks [AH], Predicting rainfall erosion losses: a guide to conservation planning, (USA), No. 537 (1978)
H. Mitasova et al, Geographic modeling systems lab website, http://skagit.meas.ncsu.edu/~helena/gmslab/reports/CerlErosionTutorial/denix/denixstart.html. Last Accessed Aug 2012
W.H. Wischmeier, D.D. Smith, Predicting rainfall erosion losses, a guide to conservation planning, Agriculture, (Washington D.C., 1978), pp. 55–57
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Brovelli, M.A., Quang, T.X., Fenoy, G. (2013). Managing Satellite Precipitation Data (PERSIANN) Through Web GeoServices: A Case Study in North Vietnam. In: Zlatanova, S., Peters, R., Dilo, A., Scholten, H. (eds) Intelligent Systems for Crisis Management. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33218-0_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-33218-0_12
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33217-3
Online ISBN: 978-3-642-33218-0
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)