Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SAR
Different rice crop information can be derived from different remote sensing sources to provide information for decision making and policies related to agricultural production and food security. The objective of this study is to generate complementary and comprehensive rice crop information from hyp...
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| Format: | Article |
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MDPI AG
2014-12-01
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| Series: | Remote Sensing |
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| Online Access: | http://www.mdpi.com/2072-4292/6/12/12789 |
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| author | Sonia Asilo Kees de Bie Andrew Skidmore Andrew Nelson Massimo Barbieri Aileen Maunahan |
| author_facet | Sonia Asilo Kees de Bie Andrew Skidmore Andrew Nelson Massimo Barbieri Aileen Maunahan |
| author_sort | Sonia Asilo |
| collection | DOAJ |
| description | Different rice crop information can be derived from different remote sensing sources to provide information for decision making and policies related to agricultural production and food security. The objective of this study is to generate complementary and comprehensive rice crop information from hypertemporal optical and multitemporal high-resolution SAR imagery. We demonstrate the use of MODIS data for rice-based system characterization and X-band SAR data from TerraSAR-X and CosmoSkyMed for the identification and detailed mapping of rice areas and flooding/transplanting dates. MODIS was classified using ISODATA to generate cropping calendar, cropping intensity, cropping pattern and rice ecosystem information. Season and location specific thresholds from field observations were used to generate detailed maps of rice areas and flooding/transplanting dates from the SAR data. Error matrices were used for the accuracy assessment of the MODIS-derived rice characteristics map and the SAR-derived detailed rice area map, while Root Mean Square Error (RMSE) and linear correlation were used to assess the TSX-derived flooding/transplanting dates. Results showed that multitemporal high spatial resolution SAR data is effective for mapping rice areas and flooding/transplanting dates with an overall accuracy of 90% and a kappa of 0.72 and that hypertemporal moderate-resolution optical imagery is effective for the basic characterization of rice areas with an overall accuracy that ranged from 62% to 87% and a kappa of 0.52 to 0.72. This study has also provided the first assessment of the temporal variation in the backscatter of rice from CSK and TSX using large incidence angles covering all rice crop stages from pre-season until harvest. This complementarity in optical and SAR data can be further exploited in the near future with the increased availability of space-borne optical and SAR sensors. This new information can help improve the identification of rice areas. |
| first_indexed | 2024-12-20T23:37:19Z |
| format | Article |
| id | doaj.art-fdb0428c5d0747808ed69b626fa9e8f8 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-12-20T23:37:19Z |
| publishDate | 2014-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-fdb0428c5d0747808ed69b626fa9e8f82022-12-21T19:23:10ZengMDPI AGRemote Sensing2072-42922014-12-01612127891281410.3390/rs61212789rs61212789Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SARSonia Asilo0Kees de Bie1Andrew Skidmore2Andrew Nelson3Massimo Barbieri4Aileen Maunahan5Faculty of Geo-Information and Earth Observation (ITC), University of Twente, Enschede 7500 AE, The NetherlandsFaculty of Geo-Information and Earth Observation (ITC), University of Twente, Enschede 7500 AE, The NetherlandsFaculty of Geo-Information and Earth Observation (ITC), University of Twente, Enschede 7500 AE, The NetherlandsInternational Rice Research Institute (IRRI), Los Baños 4031, Philippinessarmap, Purasca 6989, SwitzerlandInternational Rice Research Institute (IRRI), Los Baños 4031, PhilippinesDifferent rice crop information can be derived from different remote sensing sources to provide information for decision making and policies related to agricultural production and food security. The objective of this study is to generate complementary and comprehensive rice crop information from hypertemporal optical and multitemporal high-resolution SAR imagery. We demonstrate the use of MODIS data for rice-based system characterization and X-band SAR data from TerraSAR-X and CosmoSkyMed for the identification and detailed mapping of rice areas and flooding/transplanting dates. MODIS was classified using ISODATA to generate cropping calendar, cropping intensity, cropping pattern and rice ecosystem information. Season and location specific thresholds from field observations were used to generate detailed maps of rice areas and flooding/transplanting dates from the SAR data. Error matrices were used for the accuracy assessment of the MODIS-derived rice characteristics map and the SAR-derived detailed rice area map, while Root Mean Square Error (RMSE) and linear correlation were used to assess the TSX-derived flooding/transplanting dates. Results showed that multitemporal high spatial resolution SAR data is effective for mapping rice areas and flooding/transplanting dates with an overall accuracy of 90% and a kappa of 0.72 and that hypertemporal moderate-resolution optical imagery is effective for the basic characterization of rice areas with an overall accuracy that ranged from 62% to 87% and a kappa of 0.52 to 0.72. This study has also provided the first assessment of the temporal variation in the backscatter of rice from CSK and TSX using large incidence angles covering all rice crop stages from pre-season until harvest. This complementarity in optical and SAR data can be further exploited in the near future with the increased availability of space-borne optical and SAR sensors. This new information can help improve the identification of rice areas.http://www.mdpi.com/2072-4292/6/12/12789ricebackscattercharacterizationcrop calendarsphenologyfloodingX-bandCOSMO-SkyMedTerraSAR-XMODIS |
| spellingShingle | Sonia Asilo Kees de Bie Andrew Skidmore Andrew Nelson Massimo Barbieri Aileen Maunahan Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SAR Remote Sensing rice backscatter characterization crop calendars phenology flooding X-band COSMO-SkyMed TerraSAR-X MODIS |
| title | Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SAR |
| title_full | Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SAR |
| title_fullStr | Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SAR |
| title_full_unstemmed | Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SAR |
| title_short | Complementarity of Two Rice Mapping Approaches: Characterizing Strata Mapped by Hypertemporal MODIS and Rice Paddy Identification Using Multitemporal SAR |
| title_sort | complementarity of two rice mapping approaches characterizing strata mapped by hypertemporal modis and rice paddy identification using multitemporal sar |
| topic | rice backscatter characterization crop calendars phenology flooding X-band COSMO-SkyMed TerraSAR-X MODIS |
| url | http://www.mdpi.com/2072-4292/6/12/12789 |
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