There is growing concern about remote sensing of vertical vegetation density in rapidly expanding peri-urban interfaces. A widely used parameter for such density, i.e., leaf area index （LAI）, was measured in situ in...There is growing concern about remote sensing of vertical vegetation density in rapidly expanding peri-urban interfaces. A widely used parameter for such density, i.e., leaf area index （LAI）, was measured in situ in Nanjing, China and then correlated with two vegetation indices （VI） derived from multiple radiometric correction levels of a SPOT5 imagery. The VIs were a normal- ized difference vegetation index （NDVI） and a ratio vegetation index （RVI）, while the four radiometric correction levels were i） post atmospheric correction reflectance （PAC）, ii） top of atmosphere reflectance （TOA）, iii） satellite radiance （SR） and iv） digital number （DN）. A total of 157 LAI-VI relationship models were established. The results showed that LA! is positively correlated with VI （r varies from 0.303 to 0.927, p 〈 0.001）. The R： values of＂pure＂ vegetation were generally higher than those of mixed vegetation. The average R2 values of about 40 models based on DN data （0.688） were higher than that of the routinely used PAC （0.648）. Independent variables of the optimal models for different vegetation quadrats included two vegetation indices at three radiometric correction lev- els, indicating the potential of vegetation indices at multiple radiometric correction levels in LAI inversion. The study demonstrates that taking heterogeneities of vegetation structures and uncertainties of radiometric corrections into account may help full mining of valuable information from remote sensing images, thus improving accuracies of LAI estimation.展开更多
The main payload on CBERS-01/02 of China-Brazil Earth Resources Satellite (CBERS) is a push-broom CCD camera with moderate spatial and radiant resolution. Because at lab the data for calibration at satellite assembly ...The main payload on CBERS-01/02 of China-Brazil Earth Resources Satellite (CBERS) is a push-broom CCD camera with moderate spatial and radiant resolution. Because at lab the data for calibration at satellite assembly stage were unable to be collected, and also because the onboard calibrator after launch was in a different state from imaging, the calibration of CCD image got a series of difficulties involved. In practice, two methods are used in the processing on the ground station: One is extracting calibration data by statistics from the image itself, and the other is the method of histogram match. It was proved that the latter can calibrate the image much better, because it can remove the effect of unstable response of the camera largely and also can overcome the nonlinearity of the camera basically by using Look-Up Table (LUT) calculated from histogram statistics of different temporal images. Considering the problems of CBERS-01, a lot of calibration tests were done before the launch of CBERS-02, in which a set of lab coefficients for relative calibration was formulated after the data collection by using integration-hemisphere in the stage of satellite assembly test. During the on-orbit test, it was found that the calibration result from such coefficients was not satisfying, especially there being response difference between 3 detector arrays, which was attributed to the unstable dark currents of the CCD camera. This paper comes up with a statistic method to remove such response difference. In this method the middle detector array was used as reference to find the response differences of adjacent similar features between these arrays and it was proved to have a broad adaptability.展开更多
基金funded by the National Natural Science Foundation of China(Grant No.41071281)
文摘There is growing concern about remote sensing of vertical vegetation density in rapidly expanding peri-urban interfaces. A widely used parameter for such density, i.e., leaf area index （LAI）, was measured in situ in Nanjing, China and then correlated with two vegetation indices （VI） derived from multiple radiometric correction levels of a SPOT5 imagery. The VIs were a normal- ized difference vegetation index （NDVI） and a ratio vegetation index （RVI）, while the four radiometric correction levels were i） post atmospheric correction reflectance （PAC）, ii） top of atmosphere reflectance （TOA）, iii） satellite radiance （SR） and iv） digital number （DN）. A total of 157 LAI-VI relationship models were established. The results showed that LA! is positively correlated with VI （r varies from 0.303 to 0.927, p 〈 0.001）. The R： values of＂pure＂ vegetation were generally higher than those of mixed vegetation. The average R2 values of about 40 models based on DN data （0.688） were higher than that of the routinely used PAC （0.648）. Independent variables of the optimal models for different vegetation quadrats included two vegetation indices at three radiometric correction lev- els, indicating the potential of vegetation indices at multiple radiometric correction levels in LAI inversion. The study demonstrates that taking heterogeneities of vegetation structures and uncertainties of radiometric corrections into account may help full mining of valuable information from remote sensing images, thus improving accuracies of LAI estimation.
文摘The main payload on CBERS-01/02 of China-Brazil Earth Resources Satellite (CBERS) is a push-broom CCD camera with moderate spatial and radiant resolution. Because at lab the data for calibration at satellite assembly stage were unable to be collected, and also because the onboard calibrator after launch was in a different state from imaging, the calibration of CCD image got a series of difficulties involved. In practice, two methods are used in the processing on the ground station: One is extracting calibration data by statistics from the image itself, and the other is the method of histogram match. It was proved that the latter can calibrate the image much better, because it can remove the effect of unstable response of the camera largely and also can overcome the nonlinearity of the camera basically by using Look-Up Table (LUT) calculated from histogram statistics of different temporal images. Considering the problems of CBERS-01, a lot of calibration tests were done before the launch of CBERS-02, in which a set of lab coefficients for relative calibration was formulated after the data collection by using integration-hemisphere in the stage of satellite assembly test. During the on-orbit test, it was found that the calibration result from such coefficients was not satisfying, especially there being response difference between 3 detector arrays, which was attributed to the unstable dark currents of the CCD camera. This paper comes up with a statistic method to remove such response difference. In this method the middle detector array was used as reference to find the response differences of adjacent similar features between these arrays and it was proved to have a broad adaptability.
