Earth observation metadata ontology model for spatiotemporal-spectral semantic-enhanced satellite observation discovery: a case study of soil moisture monitoring

References

• Al-Hamdan, M., J. Cruise, D. Rickman, and D. Quattrochi. 2010. “Effects of Spatial and Spectral Resolutions on Fractal Dimensions in Forested Landscapes.” Remote Sensing 2 (3): 611–640. doi:10.3390/rs2030611.
   Web of Science ®Google Scholar
• Blanchart, P., and M. Datcu. 2010. “A Semi-Supervised Algorithm for Auto-Annotation and Unknown Structures Discovery in Satellite Image Databases.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 3 (4): 698–717. doi:10.1109/JSTARS.2010.2058794.
   Web of Science ®Google Scholar
• Bratasanu, D., I. Nedelcu, and M. Datcu. 2012. “Interactive Spectral Band Discovery for Exploratory Visual Analysis of Satellite Images.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 5 (1): 207–224. doi:10.1109/JSTARS.2011.2169772.
   Web of Science ®Google Scholar
• Bröring, A., P. Maué, K. Janowicz, D. Nüst, and C. Malewski. 2011. “Semantically-Enabled Sensor Plug & Play for the Sensor Web.” Sensors 11 (8): 7568–7605. doi:10.3390/s110807568. http://www.mdpi.com/1424-8220/11/8/7568
   PubMed Web of Science ®Google Scholar
• Cavalli, R. M., L. Fusilli, S. Pascucci, S. Pignatti, and F. Santini. 2008. “Hyperspectral Sensor Data Capability for Retrieving Complex Urban Land Cover in Comparison with Multispectral Data: Venice City Case Study (Italy).” Sensors 8 (5): 3299–3320. doi:10.3390/s8053299.
   PubMed Web of Science ®Google Scholar
• Chen, N., J. Li, and X. Zhang. 2015. “Quantitative Evaluation of Observation Capability of GF-1 Wide Field of View Sensors for Soil Moisture Inversion.” Journal of Applied Remote Sensing 9 (1): 097097-1–097097-18. doi:10.1117/1.JRS.9.097097.
   Google Scholar
• Chen, N., X. Zhang, and C. Wang. 2015. “Integrated Open Geospatial Web Service enabled Cyber-physical Information Infrastructure for Precision Agriculture Monitoring.” Computers and Electronics in Agriculture 111: 78–91. doi:10.1016/j.compag.2014.12.009.
   Web of Science ®Google Scholar
• Clapp, R. B., and G. M. Hornberger. 1978. “Empirical Equations for Some Soil Hydraulic Properties.” Water Resources Research 14 (4): 601–604. doi:10.1029/WR014i004p00601.
   Web of Science ®Google Scholar
• Compton, M., P. Barnaghi, L. Bermudez, R. Garcia-Castro, O. Corcho, S. Cox, J. Graybeal, et al. 2012. “The SSN Ontology of the W3C Semantic Sensor Network Incubator Group.” Web Semantics: Science, Services and Agents on the World Wide Web 17: 25–32. doi:10.1016/j.websem.2012.05.003.
   Web of Science ®Google Scholar
• Cubaa, N., J. Rogana, Z. Christmanb, C. A. Williamsa, L. C. Schneiderc, D. Lawrenced, and M. Millonesa. 2013. “Modelling Dry Season Deciduousness in Mexican Yucatán Forest Using MODIS EVI Data (2000–2011).” GIScience & Remote Sensing 50 (1): 26–49. doi:10.1080/15481603.2013.778559.
   Web of Science ®Google Scholar
• Darilek, J. L., W. Sun, B. Huang, Z. Wang, Y. Qi, and D. C. Weindorf. 2011. “Effect of Moisture Conditions in Rice Paddies on Phosphorus Fractionation in Agriculture Soils of Rapidly Developing Regions of China.” Communications in Soil Science and Plant Analysis 42 (14): 1752–1764. doi:10.1080/00103624.2011.584599.
   Web of Science ®Google Scholar
• DiGiuseppe, N., L. C. Pouchard, and N. F. Noy. 2014. “SWEET Ontology Coverage for Earth System Sciences.” Earth Science Informatics 7 (4): 249–264. doi:10.1007/s12145-013-0143-1.
   Web of Science ®Google Scholar
• Electromagnetic spectrum. 2015. Accessed 18 January 2015. http://en.wikipedia.org/wiki/Electromagnetic_spectrum
   Google Scholar
• Fernandez, S., I. Marsa-Maestre, J. R. Velasco, and B. Alarcos. 2013. “Ontology Alignment Architecture for Semantic Sensor Web Integration.” Sensors 13 (9): 12581–12604. doi:10.3390/s130912581.
   PubMed Web of Science ®Google Scholar
• Finn, M. P., M. D. Lewis, D. D. Bosch, M. Giraldo, K. Yamamoto, D. G. Sullivan, R. Kincaid, et al. 2011. “Remote Sensing of Soil Moisture Using Airborne Hyperspectral Data.” GIScience & Remote Sensing 48 (4): 522–540. doi:10.2747/1548-1603.48.4.522.
   Web of Science ®Google Scholar
• Gasperi, J., F. Houbie, A. Woolf, and S. Smolders. 2012. Earth Observation Metadata Profile of Observations & Measurements (Version 1.0). Wayland, MA: Open Geospatial Consortium.
   Google Scholar
• Ghulama, A., Q. M. Qin, T. Teyip, and Z.-L. Li. 2007. “Modified Perpendicular Drought Index (MPDI): A Real-Time Drought Monitoring Method.” ISPRS Journal of Photogrammetry and Remote Sensing 62 (2): 150–164. doi:10.1016/j.isprsjprs.2007.03.002.
   Web of Science ®Google Scholar
• Gray, A. J. G., J. Sadler, O. Kit, K. Kyzirakos, M. Karpathiotakis, J.-P. Calbimonte, K. Page, et al. 2011. “A Semantic Sensor Web for Environmental Decision Support Applications.” Sensors 11 (9): 8855–8887. doi:10.3390/s110908855. http://www.mdpi.com/1424-8220/11/9/8855
   PubMed Web of Science ®Google Scholar
• Hong, S., Z. Zheng, and J. Chen. 2001. “Environmental Geochemical Characteristics of Some Microelements in the Yellow Brown Soil of Hubei Province.” Acta Pedologica Sinica 38 (1): 89–95. (in Chinese).
   Google Scholar
• Hripcsak, G., and A. S. Rothschild. 2005. “Agreement, the F-Measure, and Reliability in Information Retrieval.” Journal of the American Medical Informatics Association 12 (3): 296–298. doi:10.1197/jamia.M1733.
   PubMed Web of Science ®Google Scholar
• Hu, C., Q. Guan, N. Chen, J. Li, X. Zhong, and Y. Han. 2014. “An Observation Capability Metadata Model for EO Sensor Discovery in Sensor Web Enablement Environments.” Remote Sensing 6 (11): 10546–10570. doi:10.3390/rs61110546.
   Web of Science ®Google Scholar
• Jirka, S., A. Bröring, and D. Nüst. 2010. Sensor Observable Registry Discussion Paper. Wayland, MA: Open Geospatial Consortium.
   Google Scholar
• Jirka, S., A. Bröring, and C. Stasch. 2009. “Discovery Mechanisms for the Sensor Web.” Sensors 9 (4): 2661–2681. doi:10.3390/s90402661.
   PubMed Web of Science ®Google Scholar
• Jirka, S., and D. Nuest. 2010. OGC Discussion Paper 10-171: Sensor Instance Registry. Wayland, MA: Open Geospatial Consortium.
   Google Scholar
• Joyce, R. J., J. E. Janowiak, P. A. Arkin, and P. P. Xie. 2004. “CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution.” Journal of Hydrometeorology 5: 487–503. doi:10.1175/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2.
   Web of Science ®Google Scholar
• Kim, D., S. Cha, and K. Cho. 2013. “Ontology-Based Methodology for Managing Heterogeneous Wireless Sensor Networks.” International Journal of Distributed Sensor Networks 2013 (2013): 1–9. doi:10.1155/2013/610684.
   Web of Science ®Google Scholar
• Kim, H.-O., and J.-M. Yeom. 2015. “Sensitivity of Vegetation Indices to Spatial Degradation of Rapideye Imagery for Paddy Rice Detection: A Case Study of South Korea.” GIScience & Remote Sensing 52 (1): 1–17. doi:10.1080/15481603.2014.1001666.
   Web of Science ®Google Scholar
• Komma, J., G. Bloschl, and C. Reszler. 2008. “Soil Moisture Updating by Ensemble Kalman Filtering in Real-Time Flood Forecasting.” Journal of Hydrology 357 (3–4): 228–242. doi:10.1016/j.jhydrol.2008.05.020.
   Web of Science ®Google Scholar
• Koster, R. D., P. A. Dirmeyer, Z. Guo, G. Bona, E. Chan, P. Cox, C. T. Gordon, et al. 2004. “Regions of Strong Coupling between Soil Moisture and Precipitation.” Science 305: 1138–1140. doi:10.1126/science.1100217.
   PubMed Web of Science ®Google Scholar
• Kuhn, W. 2009. “A Functional Ontology of Observation and Measurement.” In GeoSpatial Semantics, Lecture Notes in Computer Science, Vol. 5892, edited by K. Janowicz, M. Raubal, and S. Levashkin, 26–43. Berlin: Springer-Verlag. doi:10.1007/978-3-642-10436-7_3.
   Google Scholar
• Kulkarni, A., and S. McCaslin. 2004. “Knowledge Discovery from Multispectral Satellite Images.” IEEE Geoscience and Remote Sensing Letters 1 (4): 246–250. doi:10.1109/LGRS.2004.834593.
   Web of Science ®Google Scholar
• Lekshmi, S. U. S., D. N. Singh, and M. S. Baghini. 2014. “A Critical Review of Soil Moisture Measurement.” Measurement: A Review 54: 92–105. doi:10.1016/j.measurement.2014.04.007.
   Web of Science ®Google Scholar
• Li, M., and Z. Ma. 2013. “Soil Moisture-Based Study of the Variability of Dry-Wet Climate and Climate Zones in China.” Chinese Science Bulletin 58 (4–5): 531–544. doi:10.1007/s11434-012-5428-0.
   Web of Science ®Google Scholar
• Li, M., Z. Ma, and G. Niu. 2011. “Modeling Spatial and Temporal Variations in Soil Moisture in China.” Chinese Science Bulletin 56 (17): 1809–1820. doi:10.1007/s11434-011-4493-0.
   Web of Science ®Google Scholar
• Li, Y. K., and T. R. Bretschneider. 2007. “Semantic-Sensitive Satellite Image Retrieval.” IEEE Transactions on Geoscience and Remote Sensing 45 (4): 853–860. doi:10.1109/TGRS.2007.892008.
   Web of Science ®Google Scholar
• Li, Y. K., S. W. Yang, T. Liu, and X. Y. Dong. 2012. “Comparative Assessment of Semantic-Sensitive Satellite Image Retrieval: Simple and Context-Sensitive Bayesian Networks.” International Journal of Geographical Information Science 26 (2): 247–263. doi:10.1080/13658816.2011.585138.
   Web of Science ®Google Scholar
• Lienou, M., H. Maitre, and M. Datcu. 2010. “Semantic Annotation of Satellite Images Using Latent Dirichlet Allocation.” IEEE Geoscience and Remote Sensing Letters 7 (1): 28–32. doi:10.1109/LGRS.2009.2023536.
   Web of Science ®Google Scholar
• Luo, W., H. Li, G. Liu, and L. Zeng. 2014. “Semantic Annotation of Satellite Images Using Author–Genre–Topic Model.” IEEE Transactions on Geoscience and Remote Sensing 52 (2): 1356–1368. doi:10.1109/TGRS.2013.2250978.
   Web of Science ®Google Scholar
• Ma, S., and L. Tian. 2015. “Ontology-Based Semantic Retrieval for Mechanical Design Knowledge.” International Journal of Computer Integrated Manufacturing 28 (2): 226–238. doi:10.1080/0951192X.2013.874593.
   Web of Science ®Google Scholar
• Madin, J., S. Bowers, M. Schildhauer, S. Krivov, D. Pennington, and F. Villa. 2007. “An Ontology for Describing and Synthesizing Ecological Observation Data.” Ecological Informatics 2 (3): 279–296. doi:10.1016/j.ecoinf.2007.05.004.
   Web of Science ®Google Scholar
• Motohka, T., K. N. Nasahara, A. Miyata, M. Mano, and S. Tsuchida. 2009. “Evaluation of Optical Satellite Remote Sensing for Rice Paddy Phenology in Monsoon Asia Using a Continuous in Situ Dataset.” International Journal of Remote Sensing 30 (17): 4343–4357. doi:10.1080/01431160802549369.
   Web of Science ®Google Scholar
• Ochsner, T. E., M. H. Cosh, R. H. Cuenca, W. A. Dorigo, C. S. Draper, Y. Hagimoto, Y. H. Kerr, E. G. Njoku, E. E. Small, and M. Zreda. 2013. “State of the Art in Large-Scale Soil Moisture Monitoring.” Soil Science Society of America Journal 77 (6): 1888–1919. doi:10.2136/sssaj2013.03.0093.
   Web of Science ®Google Scholar
• Owe, M., R. de Jeu, and J. Walker. 2001. “A Methodology for Surface Soil Moisture and Vegetation Optical Depth Retrieval Using the Microwave Polarization Difference Index.” IEEE Transactions on Geoscience and Remote Sensing 39 (8): 1643–1654. doi:10.1109/36.942542.
   Web of Science ®Google Scholar
• Parida, B. R., W. B. Collado, R. Borah, M. K. Hazarika, and L. Samarakoon. 2008. “Detecting Drought-Prone Areas of Rice Agriculture Using a MODIS-Derived Soil Moisture Index.” GIScience & Remote Sensing 45 (1): 109–129. doi:10.2747/1548-1603.45.1.109.
   Web of Science ®Google Scholar
• Petitjean, F., J. Inglada, and P. Gancarski. 2014. “Assessing the Quality of Temporal High-Resolution Classifications with Low-Resolution Satellite Image Time Series.” International Journal of Remote Sensing 35 (7): 2693–2712. doi:10.1080/01431161.2014.883092.
   Web of Science ®Google Scholar
• Roda, F., and E. Musulin. 2014. “An Ontology-Based Framework to Support Intelligent Data Analysis of Sensor Measurements.” Expert Systems with Applications 41 (17): 7914–7926. doi:10.1016/j.eswa.2014.06.033.
   Web of Science ®Google Scholar
• Rueda, C., L. Bermudez, and J. Fredericks. 2009. “The MMI Ontology Registry and Repository: A Portal for Marine Metadata Interoperability.” OCEANS 2009, MTS/IEEE Biloxi – Marine Technology for Our Future: Global and Local Challenges, Biloxi, MS, October 26–29, 1854–1859.
   Google Scholar
• W3C. 2011. “DUL Ssn.” World Wide Web Consortium. Accessed January 14, 2015. http://www.w3.org/2005/Incubator/ssn/wiki/DUL_ssn
   Google Scholar
• Wang, F., Z. Qin, W. Li, C. Song, A. Karnieli, and S. Zhao. 2015. “An Efficient Approach for Pixel Decomposition to Increase the Spatial Resolution of Land Surface Temperature Images from MODIS Thermal Infrared Band Data.” Sensors 15 (1): 304–330. doi:10.3390/s150100304.
   Web of Science ®Google Scholar
• Wardlow, B. D., and K. Callahan. 2014. “A Multi-Scale Accuracy Assessment of the MODIS Irrigated Agriculture Data-Set (Mirad) for the State of Nebraska, USA.” GIScience & Remote Sensing 51 (5): 575–592. doi:10.1080/15481603.2014.952546.
   Web of Science ®Google Scholar
• WMO. 2015. “Measurement Timeline for Soil Moisture at Surface.” World Meteorological Organization. Accessed May 11, 2015. http://www.wmo-sat.info/oscar/gapanalyses?view=149
   Google Scholar
• Xu, Z., X. Luo, S. Zhang, X. Wei, L. Mei, and C. Hu. 2014. “Mining Temporal Explicit and Implicit Semantic Relations between Entities Using Web Search Engines.” Future Generation Computer Systems 37: 468–477. doi:10.1016/j.future.2013.09.027.
   Web of Science ®Google Scholar
• Zeng, J. Y., Z. Li, Q. Chen, H. Y. Bi, J. X. Qiu, and P. F. Zou. 2015. “Evaluation of Remotely Sensed and Reanalysis Soil Moisture Products over the Tibetan Plateau Using In-Situ Observations.” Remote Sensing of Environment 163: 91–110. doi:10.1016/j.rse.2015.03.008.
   Web of Science ®Google Scholar
• Zhang, X., N. Chen, and Z. Chen. 2014. “Spatial Pattern and Temporal Variation Law-Based Multi-Sensor Collaboration Method for Improving Regional Soil Moisture Monitoring Capabilities.” Remote Sensing 6 (12): 12309–12333. doi:10.3390/rs61212309.
   Web of Science ®Google Scholar