针对GEMI(global environment monitoring index)算法和HANDS(hotspot and NDVI differencingSynergy)算法判识过火区存在的缺陷,提出了一种基于GEMI-H(GEMI and HANDS Synergy)的指数合成算法。通过利用MODIS数据进行了验证与分析,发...针对GEMI(global environment monitoring index)算法和HANDS(hotspot and NDVI differencingSynergy)算法判识过火区存在的缺陷,提出了一种基于GEMI-H(GEMI and HANDS Synergy)的指数合成算法。通过利用MODIS数据进行了验证与分析,发现新的算法不但可以减小单纯利用HANDS算法时所受到的气候条件等因子的影响,而且还融合了GEMI算法具有抗大气和土壤背景值等干扰的优点,抽取的过火区精度得到了进一步的提高。展开更多
Burned area mapping is an essential step in the forest fire research to investigate the relationship between forest fire and cli- mate change and the effect of forest fire on carbon budgets. This study proposed an alg...Burned area mapping is an essential step in the forest fire research to investigate the relationship between forest fire and cli- mate change and the effect of forest fire on carbon budgets. This study proposed an algorithm to map forest fire burned area using the Moderate-Resolution Imaging Spectroradiameter （MODIS） time series data in Heilongjiang Province, China. The algorithm is divided into two steps： Firstly, the ＇core＇ pixels were extracted to represent the most possible burned pixels based on the comparison of the tem- poral change of Global Environmental Monitoring Index （GEMI）, Burned Area Index （BAI） and MODIS active fire products between pre- and post-fires. Secondly, a 15-km distance was set to extract the entire burned areas near the ＇core＇ pixels as more relaxed conditions were used to identify the fire pixels for reducing the omission error as much as possible. The algorithm comprehensively considered the thermal characteristics and the spectral change between pre- and post-fires, which are represented by the MODIS fire products and the spectral index, respectively. Tahe, Mohe and Huma counties of Heilongjiang Province, China were chosen as the study area for burned area mapping and a time series of burned maps were produced from 2000 to 2011. The results show that the algorithm can extract burned areas more accurately with the hiehest accuracy of 96.61%.展开更多
According to different applications,the performance parameters of the several Geo-Electromagnetic Magnetic Induction Sensors( GEMISs) which are the most representative in the world are compared. After discussing the s...According to different applications,the performance parameters of the several Geo-Electromagnetic Magnetic Induction Sensors( GEMISs) which are the most representative in the world are compared. After discussing the several key technologies for improving the performance of GEMISs,the main conclusions are as follows: the application bandwidth can be expanded by adopting flux negative feedback( 1 m Hz-10 k Hz);"laminated"core structure is useful for suppressing eddy current loss; the effective permeability of the core has increased observably after adding flux concentrators to the two ends of the core; the chopper amplifier is a useful method to suppress 1/f noise for reducing the GEMIS's output noise; the indoor calibration scheme based on"long straight solenoid"proposed to obtain sensor sensitivity. Accordingly,the problem how to reduce the noise of GEMIS is urgent need to be solved,which will improve the performance of GEMIS. And there is plenty of work requires further study on parameters ' optimization of coil and core. In the future,miniaturization,intelligence and three-axis measurement are the development directions of GEMIS.展开更多
文摘针对GEMI(global environment monitoring index)算法和HANDS(hotspot and NDVI differencingSynergy)算法判识过火区存在的缺陷,提出了一种基于GEMI-H(GEMI and HANDS Synergy)的指数合成算法。通过利用MODIS数据进行了验证与分析,发现新的算法不但可以减小单纯利用HANDS算法时所受到的气候条件等因子的影响,而且还融合了GEMI算法具有抗大气和土壤背景值等干扰的优点,抽取的过火区精度得到了进一步的提高。
基金Under the auspices of Strategic Pilot Science and Technology Projects of Chinese Academic Sciences(No.XDA05090310)
文摘Burned area mapping is an essential step in the forest fire research to investigate the relationship between forest fire and cli- mate change and the effect of forest fire on carbon budgets. This study proposed an algorithm to map forest fire burned area using the Moderate-Resolution Imaging Spectroradiameter （MODIS） time series data in Heilongjiang Province, China. The algorithm is divided into two steps： Firstly, the ＇core＇ pixels were extracted to represent the most possible burned pixels based on the comparison of the tem- poral change of Global Environmental Monitoring Index （GEMI）, Burned Area Index （BAI） and MODIS active fire products between pre- and post-fires. Secondly, a 15-km distance was set to extract the entire burned areas near the ＇core＇ pixels as more relaxed conditions were used to identify the fire pixels for reducing the omission error as much as possible. The algorithm comprehensively considered the thermal characteristics and the spectral change between pre- and post-fires, which are represented by the MODIS fire products and the spectral index, respectively. Tahe, Mohe and Huma counties of Heilongjiang Province, China were chosen as the study area for burned area mapping and a time series of burned maps were produced from 2000 to 2011. The results show that the algorithm can extract burned areas more accurately with the hiehest accuracy of 96.61%.
基金Sponsored by the National Natural Science Foundation of China(Grant No.41274183)the Science and Technology Department of Jilin Province(Grant No.20150520095JH)
文摘According to different applications,the performance parameters of the several Geo-Electromagnetic Magnetic Induction Sensors( GEMISs) which are the most representative in the world are compared. After discussing the several key technologies for improving the performance of GEMISs,the main conclusions are as follows: the application bandwidth can be expanded by adopting flux negative feedback( 1 m Hz-10 k Hz);"laminated"core structure is useful for suppressing eddy current loss; the effective permeability of the core has increased observably after adding flux concentrators to the two ends of the core; the chopper amplifier is a useful method to suppress 1/f noise for reducing the GEMIS's output noise; the indoor calibration scheme based on"long straight solenoid"proposed to obtain sensor sensitivity. Accordingly,the problem how to reduce the noise of GEMIS is urgent need to be solved,which will improve the performance of GEMIS. And there is plenty of work requires further study on parameters ' optimization of coil and core. In the future,miniaturization,intelligence and three-axis measurement are the development directions of GEMIS.
