基于环境一号卫星多光谱影像数据的三湖一库富营养化状态评价

环境一号卫星是我国2008年自主发射的环境与灾害监测小卫星,其2d的时间分辨率使其成为环境变化监测的重要数据源.根据实测的太湖、巢湖、滇池和三峡水库的水面光谱信息以及水质参数,构建基于环境一号卫星多光谱数据的富营养化评价模型,对太湖、巢湖、滇池和三峡水库2009年水体营养状况进行了评价分析.研究结果表明:利用环境一号卫...     

富营养化水体中黑水团的吸收及反射特性分析

对黑水团水体光学特性进行研究,是利用遥感技术监测和评估黑水团事件的前提.针对2015年7月在太湖发生的黑水团现象,采集了太湖黑水团区(区域一)、蓝藻水华区(区域二)、清水区(区域三)共36个水样,对这3个区域的水体遥感反射率以及吸收特性进行对比分析.结果表明:1区域一水体的总颗粒物、色素颗粒物和非色素颗粒物吸收系数比区域二、区域三高出1~2倍,在400~500 nm之间,区域一CDOM吸收系数相比另外两个区域的水体高出2倍左右.导致黑水团区域水体具有很低的遥感反射率,被人眼感知时呈现为黑色;2黑水团区域水体M值低于滇池、巢湖和太湖的M值变化范围,说明黑水团中CDOM的腐殖酸含量较高.此外,叶绿素a浓度与CDOM在350 nm处吸收系数之间具有很好的相关性,表明蓝藻的降解可能是黑水团中CDOM的一个主要来源;3在380 nm之后,黑水团区域的水体总吸收以色素颗粒物占主导,但在短波350~380 nm处,CDOM对总吸收的贡献率高于色素颗粒物和非色素颗粒物.     

卫星光学反射膜光谱反射率空间综合环境退化研究

对玻璃基底和金属基底的铝反射膜在紫外、低能电子、低能质子的综合环境作用下的光谱反射率退化进行了实验研究。试验结果表明两种铝反射膜的光谱反射率均发生了退化,且光谱反射率的退化主要集中在可见光波段,在近红外波段退化很小;玻璃基底铝反射膜退化在420 nm左右出现峰值点,2种金属基底铝反射膜的退化的峰值点在450 nm左右。由于电荷沉积在玻璃中后会抑制带电粒子入射,因此玻璃基底铝反射膜的退化要小于金属基底铝反射膜。     

基于实测光谱与MODIS数据的太湖悬浮物定量估测

以太湖为研究区域,对太湖水体的水面反射光谱进行实地测试,并取样在实验室进行水质分析;根据光谱分析得到的悬浮物特征波段,估测悬浮物浓度;最后,对比MODIS波段,用最敏感波段及主成分分析法建立悬浮物估测模型.结果表明,576nm附近的反射率峰值、841nm处反射率一阶微分值和808nm附近的反射峰高与悬浮物浓度都有较好的相关性,其中峰高法和一阶微分法对悬浮物浓度的估测精度相当;MODIS波段1与悬浮物浓度相关性最好,经过主成分变化后的第一主成分和第二主成分可以较好地估测悬浮物浓度.因此,可利用MODIS数据对太湖悬浮物进行长期动态监测.     

Particle fluxes above forests: observations, methodological considerations and method comparisons

This paper reports a study designed to test, evaluate and compare micro-meteorological methods for determining the particle number flux above forest canopies. Half-hour average particle number fluxes above a representative broad-leaved forest in Denmark derived using eddy covariance range from -7x10(7) m(-2) s(-1) (1st percentile) to 5x10(7) m(-2) s(-1) (99th percentile), and have a median value of -1.6x10(6) m(-2) s(-1). The statistical uncertainties associated with the particle number flux estimates are larger than those for momentum fluxes and imply that in this data set approximately half of the particle number fluxes are not statistically different to zero. Particle number fluxes from relaxed eddy accumulation (REA) and eddy covariance are highly correlated and of almost identical magnitude. Flux estimates from the co-spectral and dissipation methods are also correlated with those from eddy covariance but exhibit higher absolute magnitude of fluxes.     

Quantification and reduction of erroneous differences between images in remote sensing

The reliability of image data, along with the difficulty of accurately comparing images acquired at different times or from different sensors, is a generic problem in remote sensing. Measurement repeatability errors occur frequently and can substantially reduce the system’s ability to reliably quantify real spectral and spatial change in a target. This paper outlines methodologies for quantifying and reducing erroneous differences between monochrome and multispectral or hyperspectral images. [Each of these image types is acquired by an instrument that collects light photons across a variable range of the electromagnetic spectrum (often referred to as an image band). The hyperspectral image is often referred to as a hyperspectral cube with XY spatial dimensions and many Z bands (spectral demotions)]. In this paper, we specifically discuss the Pixel Block Transform (PBT), the Spectral Averaging Transform (SAT), and the Wavelet Transform (WAVEL). We briefly address sensor fusion. Results indicate that the PBT is a powerful cross-noise and repeatability error reducing tool, applicable to monochrome, multispectral, and hyperspectral images. The SAT is as powerful as the PBT in reducing error but is suitable only for hyperspectral imagery. WAVEL can reduce some of the finer scale noise, but it is not as powerful in reducing cross-noise as PBT or SAT and it requires some trial and error for selecting the appropriate wavelet function. It is important that those involved in developing statistically sound relationships between remotely sensed imagery and other data sources understand the problems and their solutions to prevent wasting time or developing relationships that are statistically insignificant or unstable, or that lead to faulty conclusions.     

基于水体固有光学特性的太湖浮游植物色素的定量反演

基于2005-05～2005-08对太湖全湖不同湖区92个样点吸收系数、光束衰减系数、后向散射系数等固有光学特性测定与计算,选择色素浓度反演的最佳波段组合,利用反射率比建立了太湖叶绿素a,叶绿素a与脱镁叶绿素的定量反演模型.结果表明,全湖4次采样叶绿素a、脱镁叶绿素的变化范围分别为3.9～149.8μg·L^-1、均值为(38.14±28.89)μg·L^-1;0～45.8μg·L^-1、均值为(8.49±7.24)μg·L^-1,存在很大空间差异,湖心区和草型湖区的东太湖、胥口湾、贡湖湾色素浓度一般要低于其他湖区.同样吸收系数和后向散射系数也存在很大的空间差异,a_t(440)的变化范围为0.86～23.25 m^-1、均值为(6.21±3.31)m^-1,b_t(550)的变化范围0.05～2.25m^-1、均值为(0.72±0.52)m^-1,东太湖、胥口湾、贡湖湾的值要低于其他湖区.400～650nm随波长增加总吸收系数大致呈下降趋势,680nm附近存在1个峰值,峰值的强弱与水体中色素浓度有关,而到720nm以后则逐渐增加,后向散射系数随波长增加则逐渐降低.反射率比R(706)/R(682)能较好地用于太湖色素浓度的反演,叶绿素a、叶绿素a与脱镁叶绿素之和幂函数反演的决定系数R²分别达0.823、0.864 5.模型能用于包括湖面反射率受湖底和沉水植物影响的全太湖.     

巢湖水体悬浮物含量与光谱反射率的关系

利用高光谱地物光谱仪在巢湖进行了反射光谱测量和同步水质采样分析，在分析巢湖水体反射光谱特征的基础上，分别研究了悬浮物浓度与水体光谱反射率和光谱反射率的一阶微分之间的关系，结果表明在近红外波段范围，单波段反射率和一阶微分光谱反射率都与悬浮物的浓度有较好的相关性，而且利用微分光谱估算内陆水体悬浮物浓度有较大潜力。     

Use of Landsat Thematic Mapper Data to Assess Seasonal Rangeland Changes in the Southeast Kalahari, Botswana

/ Management problems arise in semiarid rangeland that are characterized by marked wet and dry seasons because of forage deficiencies in the dry season. These natural vegetation rangelands can sustain livestock all year long when forage and senesced grass are available into the dry season. Seasonal range condition data are required to provide a basis for pasture management to help locate dry season cover and thereby minimize overstocking and degradation. The generation of seasonal data using Thematic Mapper (TM) imagery was undertaken to assess changes in natural vegetation cover in the southern Botswana Kalahari. Visual analysis of spectral reflectance curves, the development of spectral separability indexes, and conventional classification analysis techniques were used to identify and differentiate rangeland features. Results from reflectance curves indicated that most rangeland cover types could be preferentially distinguished using mainly wet season data, especially on the longer TM wavebands, and that range feature differentiation was more problematic on darker soils than on lighter soils. Spectral separability indexes (SSIs) confirmed that range feature separation varied considerably as a function of waveband and was more effective in the wet than the dry season. The SSIs also showed that range feature differentiation in both seasons was most effective using a combination of the chlorophyll absorpance band (TM3) and two mid-infrared bands (TM5 and TM7). Wet season data were more effectively classified in terms of range features than dry season data although some class similarity was inferred across the two classified data sets. The work shows that overall trends may be generated by comparing seasonal data sets, thereby providing an overall basis for dry season decision making. However, particular problems arise within the dry season data sets probably because of spectral similarities between shadow and darkened vegetation cover, thereby implying that further work is needed. KEY WORDS: Semiarid rangelands; Botswana; Kalahari; Spectral differentiation; Seasonal change; Darkened vegetation cover