參考文獻 |
Baatz, M., Schäpe, A., 2000. Multiresolution segmentation: an optimization approach for high quality multi-scale image segmentation, Angewandte Geographische Informationsverarbeitung XII. Beiträge zum AGIT-Symposium Salzburg 2000, Strobl, J., Blaschke, T., Griesebner, G., Eds.; Wichmann: Heidelberg, Germany, pp. 12-23.
Bertin, X. et al., 2014. A modeling-based analysis of the flooding associated with Xynthia, central Bay of Biscay. Coastal Engineering, 94: 80-89.
Bhatt, R.M. et al., 2015. Interspecific grafting to enhance physiological resilience to flooding stress in tomato (Solanum lycopersicum L.). Scientia Horticulturae, 182: 8-17.
Bisquert, M., Bégué, A., Deshayes, M., 2015. Object-based delineation of homogeneous landscape units at regional scale based on MODIS time series. International Journal of Applied Earth Observation and Geoinformation, 37(0): 72-82.
Blaschke, T., 2010. Object based image analysis for remote sensing. ISPRS journal of photogrammetry and remote sensing, 65(1): 2-16.
Chau, V.N., Holland, J., Cassells, S., Tuohy, M., 2013. Using GIS to map impacts upon agriculture from extreme floods in Vietnam. Applied Geography, 41: 65-74.
Dao, P.D., Liou, Y.-A., 2015. Object-Based Flood Mapping and Affected Rice Field Estimation with Landsat 8 OLI and MODIS Data. Remote Sensing, 7(5): 5077-5097.
Dao, P.D., Liou, Y.-A., Chou, C.-W., 2015. Detection of flood inundation regions with Landsat/MODIS synthetic data, International Symposium on Remote Sensing 2015, Tainan, Taiwan.
Definiens, 2007. Definiens Developer 7: User Guide. Definiens AG, Munich, Germany.
Devadas, R., Denham, R.J., Pringle, M., 2012. Support Vector Machine classification of object-based data for crop mapping, using multi-temporal Landsat imagery. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXIX-B7(2012 XXII ISPRS Congress, Melbourne, Australia).
Didan, K., Huete, A., 2006. MODIS vegetation index product series collection 5 change summary, Terrestrial Biophysics and Remote Sensing (TBRS) laboratory, The University of Arizona.
Drăguţ, L., Csillik, O., Eisank, C., Tiede, D., 2014. Automated parameterisation for multi-scale image segmentation on multiple layers. ISPRS Journal of Photogrammetry and Remote Sensing, 88: 119-127.
Drǎguţ, L., Tiede, D., Levick, S.R., 2010. ESP: a tool to estimate scale parameter for multiresolution image segmentation of remotely sensed data. International Journal of Geographical Information Science, 24(6): 859-871.
Dronova, I., Gong, P., Wang, L., 2011. Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China. Remote Sensing of Environment, 115(12): 3220-3236.
Dronova, I., Gong, P., Wang, L., Zhong, L., 2015. Mapping dynamic cover types in a large seasonally flooded wetland using extended principal component analysis and object-based classification. Remote Sensing of Environment, 158: 193-206.
Evans, T.L., Costa, M., Telmer, K., Silva, T.S., 2010. Using ALOS/PALSAR and RADARSAT-2 to map land cover and seasonal inundation in the Brazilian Pantanal. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 3(4): 560-575.
Frohn, R., Autrey, B., Lane, C., Reif, M., 2011. Segmentation and object-oriented classification of wetlands in a karst Florida landscape using multi-season Landsat-7 ETM+ imagery. International Journal of Remote Sensing, 32(5): 1471-1489.
Gao, F., Masek, J., Schwaller, M., Hall, F., 2006. On the blending of the Landsat and MODIS surface reflectance: Predicting daily Landsat surface reflectance. IEEE Transactions on Geoscience and Remote Sensing, 44(8): 2207-2218.
Gao, Y., Mas, J., Niemeyer, I., Marpu, P., Palacio, J., 2007. Object-based image analysis for mapping land-cover in a forest area, 5th International Symposium: Spatial Data Quality, Enschede, The Netherlands, pp. 13-15.
Gao, Y., Mas, J.F., Kerle, N., Navarrete Pacheco, J.A., 2011. Optimal region growing segmentation and its effect on classification accuracy. International Journal of Remote Sensing, 32(13): 3747-3763.
Gianinetto, M., Villa, P., Lechi, G., 2006. Postflood damage evaluation using Landsat TM and ETM+ data integrated with DEM. IEEE Transactions on Geoscience and Remote Sensing, 44(1): 236-243.
Gusso, A., Formaggio, A.R., Rizzi, R., Adami, M., Rudorff, B.F.T., 2012. Soybean crop area estimation by Modis/Evi data. Pesquisa Agropecuária Brasileira, 47(3): 425-435.
Hall, D., Bouapao, L., 2010. Social Impact Monitoring and Vulnerability Assessment. 1683-1489, Vientiane, Lao.
Hansen, J., Ruedy, R., Sato, M., Lo, K., 2010. Global surface temperature change. Reviews of Geophysics, 48(4).
Happ, P., Ferreira, R., Bentes, C., Costa, G., Feitosa, R., 2010. Multiresolution segmentation: a parallel approach for high resolution image segmentation in multicore architectures, Proceeding of the 3rd International Conference on Geographic Object-Based Image Analysis, Ghent, Belgium.
Henry, J.B., Chastanet, P., Fellah, K., Desnos, Y.L., 2006. Envisat multi‐polarized ASAR data for flood mapping. International Journal of Remote Sensing, 27(10): 1921-1929.
Heumann, B.W., 2011. An object-based classification of mangroves using a hybrid decision tree—Support vector machine approach. Remote Sensing, 3(11): 2440-2460.
Hussaina, E., Urala, S., Malikb, A., Shana, J., 2011. Mapping Pakistan 2010 floods using remote sensing data, Proceeding of ASPRS Annual Conference, Milwaukee, Wisconsin, USA.
ITT Visual Information Solutions, 2009. Atmospheric Correction Module: QUAC and FLAASH User’s Guide, Version 4.7. ITT Visual Information Solutions, Boulder, CO, USA.
Kamal, A.H.M., Rashid, H., Sakata, K., Komatsu, S., 2015. Gel-free quantitative proteomic approach to identify cotyledon proteins in soybean under flooding stress. Journal of proteomics, 112: 1-13.
Knight, E.J., Kvaran, G., 2014. Landsat-8 operational land imager design, characterization and performance. Remote Sensing, 6(11): 10286-10305.
le Maire, G., Dupuy, S., Nouvellon, Y., Loos, R.A., Hakamada, R., 2014. Mapping short-rotation plantations at regional scale using MODIS time series: Case of eucalypt plantations in Brazil. Remote Sensing of Environment, 152: 136-149.
Liou, Y.-A. et al., 2012. Assessment of Disaster Losses in Rice Paddy Field and Yield after Tsunami Induced by the 2011 Great East Japan Earthquake. Journal of Marine Science and Technology, 20(6): 618-623.
Mallinis, G., Gitas, I.Z., Giannakopoulos, V., Maris, F., Tsakiri-Strati, M., 2011. An object-based approach for flood area delineation in a transboundary area using ENVISAT ASAR and LANDSAT TM data. International Journal of Digital Earth(ahead-of-print): 1-13.
Matinfar, H., Sarmadian, F., AlaviPanah, S., Heck, R., 2007. Comparisons of object-oriented and pixel-based classification of land use/land cover types based on Lansadsat7, ETM+ spectral bands (case study: arid region of Iran). American-Eurasian Journal of Agricultural & Environmental Sciences, 2(4): 448-456.
Men, S. et al., 2001. Description of rice varieties released by the varietal recommendation committee of Cambodia (1999–2000), Cambodian Agricultural Research and Development Institute, Phnom Penh, Cambodia.
Metz, B., Davidson, O., Bosch, P., Dave, R., Meyer, L., 2007. Climate Change 2007: Mitigation: Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change: Summary for Policymakers and Technical Summary. Cambridge University Press.
Nesbitt, H.J., 1997. Rice production in Cambodia. International Rice Research Institute, Laguna, Philippines.
Nussbaum, S., Menz, G., 2008. Object-based image analysis and treaty verification, 1. Springer, Berlin, Germany.
Oh, M., Komatsu, S., 2015. Characterization of proteins in soybean roots under flooding and drought stresses. Journal of proteomics, 114(0): 161-181.
Oruc, M., Marangoz, A., Buyuksalih, G., 2004. Comparison of pixel-based and object-oriented classification approaches using Landsat-7 ETM spectral bands, Proceedings of the ISRPS 2004 Annual Conference, Istabul, Turkey, pp. 19-23.
Peng, D., Huete, A.R., Huang, J., Wang, F., Sun, H., 2011. Detection and estimation of mixed paddy rice cropping patterns with MODIS data. International Journal of Applied Earth Observation and Geoinformation, 13(1): 13-23.
Rogger, M. et al., 2012. Runoff models and flood frequency statistics for design flood estimation in Austria–Do they tell a consistent story? Journal of Hydrology, 456: 30-43.
Royal Government of Cambodia, 2014. Post-flood early recovery need assessment report, Royal Government of Cambodia report. Royal Government of Cambodia, Phnom Penh, Cambodia.
Rudari, R., Gabellani, S., Delogu, F., 2014. A simple model to map areas prone to surface water flooding. International Journal of Disaster Risk Reduction, 10(0): 428-441.
Sakamoto, T. et al., 2007. Detecting temporal changes in the extent of annual flooding within the Cambodia and the Vietnamese Mekong Delta from MODIS time-series imagery. Remote sensing of environment, 109(3): 295-313.
Sakamoto, T., Van Nguyen, N., Ohno, H., Ishitsuka, N., Yokozawa, M., 2006. Spatio–temporal distribution of rice phenology and cropping systems in the Mekong Delta with special reference to the seasonal water flow of the Mekong and Bassac rivers. Remote Sensing of Environment, 100(1): 1-16.
Sanyal, J., Lu, X., 2004. Application of remote sensing in flood management with special reference to monsoon Asia: a review. Natural Hazards, 33(2): 283-301.
Solano, R., Didan, K., Jacobson, A., Huete, A., 2010. MODIS vegetation index user’s guide (MOD13 series). The University of Arizona.
Tapia-Silva, F.-O., Itzerott, S., Foerster, S., Kuhlmann, B., Kreibich, H., 2011. Estimation of flood losses to agricultural crops using remote sensing. Physics and Chemistry of the Earth, Parts A/B/C, 36(7): 253-265.
Thompson, J.A., Lees, B.G., 2014. Applying object-based segmentation in the temporal domain to characterise snow seasonality. ISPRS Journal of Photogrammetry and Remote Sensing, 97: 98-110.
Trimble, 2011. eCognition Developer 8.7 user guide, Trimble Documentation, München, Germany, pp. 258.
Uddin, K., Gurung, D.R., Giriraj, A., Shrestha, B., 2013. Application of Remote Sensing and GIS for Flood Hazard Management: A Case Study from Sindh Province, Pakistan. American Journal of Geographic Information System, 2(1): 1-5.
USGS, 2013. Landsat 8 Fact Sheet. 2013-3060, Earth Resources Observation and Science (EROS) Center, Reston, VA.
Vang, S., 2011. Country report on rice cultivation pratice, Proceedings of Expert meeting, Bandkok, Thailand.
Vermote, E., Kotchenova, S., Ray, J., 2011. MODIS surface reflectance user’s guide, version 1.3, MODIS Land Surface Reflectance Science Computing Facility.
Vintrou, E. et al., 2012. Crop area mapping in West Africa using landscape stratification of MODIS time series and comparison with existing global land products. International journal of applied earth observation and geoinformation, 14(1): 83-93.
Williams, D., 2008. Landsat 7 science data users handbook, General Interest Publication. NASA, pp. 186.
Woodcock, C.E., Strahler, A.H., 1987. The factor of scale in remote sensing. Remote sensing of Environment, 21(3): 311-332.
Xiao, X. et al., 2005. Mapping paddy rice agriculture in southern China using multi-temporal MODIS images. Remote Sensing of Environment, 95(4): 480-492.
Zhang, F., Zhu, X., Liu, D., 2014. Blending MODIS and Landsat images for urban flood mapping. International Journal of Remote Sensing, 35(9): 3237-3253.
Zhu, X., Chen, J., Gao, F., Chen, X., Masek, J.G., 2010. An enhanced spatial and temporal adaptive reflectance fusion model for complex heterogeneous regions. Remote Sensing of Environment, 114(11): 2610-2623.
|