The fraction of photosynthetically active radiation （FPAR） is a key variable in the assessment of vegetation productivity and land ecosystem carbon cycles. Based on ground-measured corn hyperspectral reflectance and...The fraction of photosynthetically active radiation （FPAR） is a key variable in the assessment of vegetation productivity and land ecosystem carbon cycles. Based on ground-measured corn hyperspectral reflectance and FPAR data over Northeast China, the correlations between corn-canopy FPAR and hyperspectral reflectance were analyzed, and the FPAR estimation performances using vegetation index （VI） and neural network （NN） methods with different two-band-combination hyperspectral reflectance were investigated. The results indicated that the corn-canopy FPAR retained almost a constant value in an entire day. The negative correlations between FPAR and visible and shortwave infrared reflectance （SWIR） bands are stronger than the positive correlations between FPAR and near-infrared band re- flectance （NIR）. For the six VIs, the normalized difference vegetation index （NDVI） and simple ratio （SR） performed best for estimating corn FPAR （the maximum R2 of 0.8849 and 0.8852, respectively）. However, the NN method esti- mated results （the maximum Rz is 0.9417） were obviously better than all of the VIs. For NN method, the two-band combinations showing the best corn FPAR estimation performances were from the NIR and visible bands; for VIs, however, they were from the SWIR and NIR bands. As for both the methods, the SWIR band performed exceptionally well for corn FPAR estimation. This may be attributable to the fact that the reflectance of the SWIR band were strongly controlled by leaf water content, which is a key component of corn photosynthesis and greatly affects the absorption of photosynthetically active radiation （APAR）, and makes further impact on corn-canopy FPAR.展开更多
We consider differentiated timecritical task scheduling in a N×N input queued optical packet s w itch to ens ure 100% throughput and meet different delay requirements among various modules of data center. Existin...We consider differentiated timecritical task scheduling in a N×N input queued optical packet s w itch to ens ure 100% throughput and meet different delay requirements among various modules of data center. Existing schemes either consider slot-by-slot scheduling with queue depth serving as the delay metric or assume that each input-output connection has the same delay bound in the batch scheduling mode. The former scheme neglects the effect of reconfiguration overhead, which may result in crippled system performance, while the latter cannot satisfy users' differentiated Quality of Service(Qo S) requirements. To make up these deficiencies, we propose a new batch scheduling scheme to meet the various portto-port delay requirements in a best-effort manner. Moreover, a speedup is considered to compensate for both the reconfiguration overhead and the unavoidable slots wastage in the switch fabric. With traffic matrix and delay constraint matrix given, this paper proposes two heuristic algorithms Stringent Delay First(SDF) and m-order SDF(m-SDF) to realize the 100% packet switching, while maximizing the delay constraints satisfaction ratio. The performance of our scheme is verified by extensive numerical simulations.展开更多
This study is aimed at using the Empirical Line Method （ELM） to eliminate atmospheric effects with respect to visible and near infrared bands of advanced spaceborne thermal emission and reflection radiometer （ASTER...This study is aimed at using the Empirical Line Method （ELM） to eliminate atmospheric effects with respect to visible and near infrared bands of advanced spaceborne thermal emission and reflection radiometer （ASTER） and enhanced thematic mapper plus （ETM＋） data. Two targets （Amran limestone as light target and quartz-biotite-sericite-graphite schists as dark target）, which were widely exposed and easy to identify in the imagery were selected. The accuracy of the atmospheric correction method was evaluated from three targets （vegetation cover, Amran limestone and Akbra shale） of the surface reflectance. Analytical spectral devices （ASD） FieldSpec3 was used to measure the spectra of target samples. ETM＋ data were less influenced by the atmospheric effect when compared to ASTER data. Normalized differences vegetation indices （NDVI） displayed good results with reflectance data when compared with digital number （DN） data because it is highly sensitive to ground truth reflectance （GTR）. Most of the differences observed before and after calibration of satellite images （ASTER and ETM＋） were absorbed in the SWlR region.展开更多
基金Under the auspices of National Key Research Program of Global Change Research (No.2010CB951302)National Natural Science Fundation of China (No.40771146)China Postdoctoral Science Foundation Funded Project (No.07Z7601MZ1)
文摘The fraction of photosynthetically active radiation （FPAR） is a key variable in the assessment of vegetation productivity and land ecosystem carbon cycles. Based on ground-measured corn hyperspectral reflectance and FPAR data over Northeast China, the correlations between corn-canopy FPAR and hyperspectral reflectance were analyzed, and the FPAR estimation performances using vegetation index （VI） and neural network （NN） methods with different two-band-combination hyperspectral reflectance were investigated. The results indicated that the corn-canopy FPAR retained almost a constant value in an entire day. The negative correlations between FPAR and visible and shortwave infrared reflectance （SWIR） bands are stronger than the positive correlations between FPAR and near-infrared band re- flectance （NIR）. For the six VIs, the normalized difference vegetation index （NDVI） and simple ratio （SR） performed best for estimating corn FPAR （the maximum R2 of 0.8849 and 0.8852, respectively）. However, the NN method esti- mated results （the maximum Rz is 0.9417） were obviously better than all of the VIs. For NN method, the two-band combinations showing the best corn FPAR estimation performances were from the NIR and visible bands; for VIs, however, they were from the SWIR and NIR bands. As for both the methods, the SWIR band performed exceptionally well for corn FPAR estimation. This may be attributable to the fact that the reflectance of the SWIR band were strongly controlled by leaf water content, which is a key component of corn photosynthesis and greatly affects the absorption of photosynthetically active radiation （APAR）, and makes further impact on corn-canopy FPAR.
基金supported by the Major State Basic Research Program of China (973 project No. 2013CB329301 and 2010CB327806)the Natural Science Fund of China (NSFC project No. 61372085, 61032003, 61271165 and 61202379)+1 种基金the Research Fund for the Doctoral Program of Higher Education of China (RFDP project No. 20120185110025, 20120185110030 and 20120032120041)supported by Tianjin Key Laboratory of Cognitive Computing and Application, School of Computer Science and Technology, Tianjin University, Tianjin, P. R. China
文摘We consider differentiated timecritical task scheduling in a N×N input queued optical packet s w itch to ens ure 100% throughput and meet different delay requirements among various modules of data center. Existing schemes either consider slot-by-slot scheduling with queue depth serving as the delay metric or assume that each input-output connection has the same delay bound in the batch scheduling mode. The former scheme neglects the effect of reconfiguration overhead, which may result in crippled system performance, while the latter cannot satisfy users' differentiated Quality of Service(Qo S) requirements. To make up these deficiencies, we propose a new batch scheduling scheme to meet the various portto-port delay requirements in a best-effort manner. Moreover, a speedup is considered to compensate for both the reconfiguration overhead and the unavoidable slots wastage in the switch fabric. With traffic matrix and delay constraint matrix given, this paper proposes two heuristic algorithms Stringent Delay First(SDF) and m-order SDF(m-SDF) to realize the 100% packet switching, while maximizing the delay constraints satisfaction ratio. The performance of our scheme is verified by extensive numerical simulations.
文摘This study is aimed at using the Empirical Line Method （ELM） to eliminate atmospheric effects with respect to visible and near infrared bands of advanced spaceborne thermal emission and reflection radiometer （ASTER） and enhanced thematic mapper plus （ETM＋） data. Two targets （Amran limestone as light target and quartz-biotite-sericite-graphite schists as dark target）, which were widely exposed and easy to identify in the imagery were selected. The accuracy of the atmospheric correction method was evaluated from three targets （vegetation cover, Amran limestone and Akbra shale） of the surface reflectance. Analytical spectral devices （ASD） FieldSpec3 was used to measure the spectra of target samples. ETM＋ data were less influenced by the atmospheric effect when compared to ASTER data. Normalized differences vegetation indices （NDVI） displayed good results with reflectance data when compared with digital number （DN） data because it is highly sensitive to ground truth reflectance （GTR）. Most of the differences observed before and after calibration of satellite images （ASTER and ETM＋） were absorbed in the SWlR region.
