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[SCI]Comparative Analysis of GF-1 WFV, ZY-3 MUX, and HJ-1 CCD Sensor Data for Grassland Monitoring..
2015年06月28日   审核人:   (点击数:)

Lei Wang, Ranran Yang, Qingjiu Tian, et al.ComparativeAnalysisofGF-1WFV,ZY-3MUX, andHJ-1CCD SensorDataforGrasslandMonitoringApplications. Remote Sensing, 2014, (6)(SCI,IF=3.257)

DOI:10.3390/rs70202089

Abstract

The increasing numberofChinese sensor types usedforterrestrial remote sensing has necessitated an additional effort to evaluate and standardize thedatathey acquire. In this study, we assessed the potential useofGF-1WFV (Wild Field Camera),ZY-3MUX (Multi-spectral camera), andHJ-1CCD (Charge Coupled Device) sensordataforgrasslandmonitoringby comparing spectral field measurements, vegetation coverage, and the leaf area index (LAI)ofgrasslandstands with reflectance in the red and near-infrared bands and the Normalized Difference Vegetation Index (NDVI). Based on spectral field measurements, the characteristic differencesofspectral response functionsofthe sensors were analyzed. Based on simulations using the SAIL bidirectional canopy reflectance model coupled with the PROSPECT leaf optical properties model (PROSAIL), we investigated the effectsofchanges in the sensors' zenith angle caused by side sway. The following conclusions were drawn. (1) Differences in the adjusted coefficientsofdetermination (R-2) exist when comparing correlations between the reflectances from the three sensor types in different bands. The valuesofR-2 are 0.556-0.893 and 0.819-0.850forthe infrared and red bands, respectively, and thesedatashow a better correlationforthe red band thanforthe infrared band. Fitted slope equations revealed inconsistencies in thedatabetween the different sensor types. In the red band,GF-1WFV andHJ-1CCDdataare the most consistent, but in the near-infrared band,GF-1WFV andZY-3MUXdataare the most consistent; (2) The correlationofNDVIs obtained from the different sensor types is high (R-2 between 0.758 and 0.852); however, the consistency is low in that the NDVI based onGF-1WFVdatais significantly higher than that based onZY-3MUX andHJ-1CCDdata. In contrast, the mean difference is small between the NDVIs based onZY-3MUX andHJ-1CCD; (3) Correlationanalysisbetween ground grass-coverage and measured LAIdatashows that the three sensor types are better at estimating coverage than the LAI, and that theGF-1WFV sensor gave the best performance; (4) Changes in the sensors' zenith angle caused by side sway were proven to have greater impact on reflectance and NDVI than the spectral response function; (5)ForLAI valuesof0-3, the NDVI changes significantly with increasing LAI, and differences between the three sensor types are obvious.ForLAI >3.5, the NDVI appears to experience a saturated tendency, which greatly reduces the differences between the sensors.

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