Abstract： Change detection is a standard tool to extract and analyze the earth＇s surface features from remotely sensed data. Among the different change detection techniques, change vector analysis （CVA） have an ex...Abstract： Change detection is a standard tool to extract and analyze the earth＇s surface features from remotely sensed data. Among the different change detection techniques, change vector analysis （CVA） have an exceptional advantage of discriminating change in terms of change magnitude and vector direction from multispectral bands. The estimation of precise threshold is one of the most crucial task in CVA to separate the change pixels from unchanged pixels because overall assessment of change detection method is highly dependent on selected threshold value. In recent years, integration of fuzzy clustering and remotely sensed data have become appropriate and realistic choice for change detection applications. The novelty of the proposed model lies within use of fuzzy maximum likelihood classification （FMLC） as fuzzy clustering in CVA. The FMLC based CVA is implemented using diverse threshold determination algorithms such as double-window flexible pace search （DFPS）, interactive trial and error （T＆E）, and 3x3-pixel kernel window （PKW）. Unlike existing CVA techniques, addition of fuzzy clustering in CVA permits each pixel to have multiple class categories and offers ease in threshold determination process. In present work, the comparative analysis has highlighted the performance of FMLC based CVA overimproved SCVA both in terms of accuracy assessment and operational complexity. Among all the examined threshold searching algorithms, FMLC based CVA using DFPS algorithm is found to be the most efficient method.展开更多
In order to monitor malt quality in the malting industry, despite yearly variations in the barley quality, 394 barley samples were analysed using conventional （moisture, protein and B-glucan content） and mid-infrare...In order to monitor malt quality in the malting industry, despite yearly variations in the barley quality, 394 barley samples were analysed using conventional （moisture, protein and B-glucan content） and mid-infrared Fourier transform spectroscopy FT-IR. The experimental dataset included barley from three harvest years, two barley species, 77 barley varieties, and two-row and six-row barley, from 16 cultivation sites. For each sample, the malt quality indices were also assessed according to European Brewing Convention （EBC） standards. Principal component analysis （PCA） was carried out on mean-centred, normalized and derivative spectra using 200/cm width spectral bands. The most informative spectral bands were observed in the 800-1,000/cm and 1,000-1,200/cm ranges. PCA revealed that barley harvested in 2010 and in 2011 had bands that were very close together, while 2009 harvest clearly displayed a difference in its quality. PCA made it possible to distinguish two species and confirmed that two-row winter barley quality was closer to two-row spring barley quality than to six-row winter barley. Results indicate that mid-infrared spectrometry （MIR） could be a very useful and rapid analytical tool to assess barley qualitative quality.展开更多
Black carbon （BC） aerosols can strongly absorb solar radiation in very broad spectral wavebands, from the visible to the infrared. As a potential factor contributing to global warming, BC aerosols not only directly ...Black carbon （BC） aerosols can strongly absorb solar radiation in very broad spectral wavebands, from the visible to the infrared. As a potential factor contributing to global warming, BC aerosols not only directly change the radiation balance of the earth-atmosphere system, but also indirectly affect global or regional climate by acting as cloud conden- sation nuclei or ice nuclei to alter cloud mierophysical properties. Here, recent progresses in the studies of radiative forcing due to BC and its climate effects are reviewed. The uncertainties in current researches are discussed and some suggestions are provided for future investigations.展开更多
德国空间中心(DLR)与Teledyne公司共同研发的地球遥感成像光谱仪DESIS工作在可见光(400nm)至近红外(1000nm)波段。它共有235个光谱波段,光谱采样间隔为2.5nm,地面采样间距为30m(400 km轨道高度)。DESIS于2018年6月搭载SpaceX-15火箭进...德国空间中心(DLR)与Teledyne公司共同研发的地球遥感成像光谱仪DESIS工作在可见光(400nm)至近红外(1000nm)波段。它共有235个光谱波段,光谱采样间隔为2.5nm,地面采样间距为30m(400 km轨道高度)。DESIS于2018年6月搭载SpaceX-15火箭进入囯际空间站(ISS),并于2018年8月与MUSES (Multi-User System for Earth Sensing)平台对接成功。随后DESIS进入调试和在轨测试阶段,2019年初开始业务运行。文中对该仪器的设计过程与关键指标、地面测试和定标的过程等作了较为详尽的阐述。DESIS将在农业、生物多样性、地质和矿物学、海岸带、水生态系统和土壤荒漠化等众多领域有广泛的应用前景。展开更多
文摘Abstract： Change detection is a standard tool to extract and analyze the earth＇s surface features from remotely sensed data. Among the different change detection techniques, change vector analysis （CVA） have an exceptional advantage of discriminating change in terms of change magnitude and vector direction from multispectral bands. The estimation of precise threshold is one of the most crucial task in CVA to separate the change pixels from unchanged pixels because overall assessment of change detection method is highly dependent on selected threshold value. In recent years, integration of fuzzy clustering and remotely sensed data have become appropriate and realistic choice for change detection applications. The novelty of the proposed model lies within use of fuzzy maximum likelihood classification （FMLC） as fuzzy clustering in CVA. The FMLC based CVA is implemented using diverse threshold determination algorithms such as double-window flexible pace search （DFPS）, interactive trial and error （T＆E）, and 3x3-pixel kernel window （PKW）. Unlike existing CVA techniques, addition of fuzzy clustering in CVA permits each pixel to have multiple class categories and offers ease in threshold determination process. In present work, the comparative analysis has highlighted the performance of FMLC based CVA overimproved SCVA both in terms of accuracy assessment and operational complexity. Among all the examined threshold searching algorithms, FMLC based CVA using DFPS algorithm is found to be the most efficient method.
文摘In order to monitor malt quality in the malting industry, despite yearly variations in the barley quality, 394 barley samples were analysed using conventional （moisture, protein and B-glucan content） and mid-infrared Fourier transform spectroscopy FT-IR. The experimental dataset included barley from three harvest years, two barley species, 77 barley varieties, and two-row and six-row barley, from 16 cultivation sites. For each sample, the malt quality indices were also assessed according to European Brewing Convention （EBC） standards. Principal component analysis （PCA） was carried out on mean-centred, normalized and derivative spectra using 200/cm width spectral bands. The most informative spectral bands were observed in the 800-1,000/cm and 1,000-1,200/cm ranges. PCA revealed that barley harvested in 2010 and in 2011 had bands that were very close together, while 2009 harvest clearly displayed a difference in its quality. PCA made it possible to distinguish two species and confirmed that two-row winter barley quality was closer to two-row spring barley quality than to six-row winter barley. Results indicate that mid-infrared spectrometry （MIR） could be a very useful and rapid analytical tool to assess barley qualitative quality.
基金financially supported by the National Basic Research Program of China(2011CB403405 and 2010CB955608)the Public Meteorology Special Foundation of MOST(GYHY200906020)
文摘Black carbon （BC） aerosols can strongly absorb solar radiation in very broad spectral wavebands, from the visible to the infrared. As a potential factor contributing to global warming, BC aerosols not only directly change the radiation balance of the earth-atmosphere system, but also indirectly affect global or regional climate by acting as cloud conden- sation nuclei or ice nuclei to alter cloud mierophysical properties. Here, recent progresses in the studies of radiative forcing due to BC and its climate effects are reviewed. The uncertainties in current researches are discussed and some suggestions are provided for future investigations.
文摘德国空间中心(DLR)与Teledyne公司共同研发的地球遥感成像光谱仪DESIS工作在可见光(400nm)至近红外(1000nm)波段。它共有235个光谱波段,光谱采样间隔为2.5nm,地面采样间距为30m(400 km轨道高度)。DESIS于2018年6月搭载SpaceX-15火箭进入囯际空间站(ISS),并于2018年8月与MUSES (Multi-User System for Earth Sensing)平台对接成功。随后DESIS进入调试和在轨测试阶段,2019年初开始业务运行。文中对该仪器的设计过程与关键指标、地面测试和定标的过程等作了较为详尽的阐述。DESIS将在农业、生物多样性、地质和矿物学、海岸带、水生态系统和土壤荒漠化等众多领域有广泛的应用前景。
