基于遥感技术对黄河口水色与岸线季相变化特征研究

使用Landsat-5 TM 2004年11月24日与2005年5月13日黄河口遥感影像,配合准同期外业实测资料,进行黄河口水体水色物质叶绿素a与悬浮泥沙的动态反演与河口岸线解译.研究表明由于秋末与春初黄河上游来水物质含量的差异,上述悬浮指标值存在显著的季相差异.根据样值与光谱特征建立的反演模型得出的反演值与实测值有平均在0.85以上的相关关系,具有很好的反演效果.岸线解译成果表明,黄河口岸线演变迅速,在河流平枯水量时期仍然具有较强的变化,岸线推进尤以新河口附近显著.这表明,使用遥感手段是进行河口生态环境质量监测的有效手段,是进行岸线动态变化研究的一种基本技术支撑手段.     

FARMLAND AND URBAN AREA DYNAMICS MONITORING INCHINA USING REMOTE SENSING AND SPATIALSTATISTICS METHODOLOGY

1 INTRODUCTIONGlobal change research involves much geo-objectsand geo-process, such as climate and environmentalchange, substance and energy cycling, land-use/land-cover change (LUCC), interactivity between human and nature, etc.. So it need cooperation frommany research communities including international research programs groups such as IGBP (InternationalGeosphere-Biosphere Programme IPCC (Intergovemmental Panel on Climate Change), IHDP (InternationalHuman Dimension Program o…     

STUDY ON GIS FOR YIELD ESTIMATION BY REMOTE SENSING IN JILIN MAIZE BELT

ＳＴＵＤＹ　ＯＮ　ＧＩＳ　ＦＯＲ　ＹＩＥＬＤ　ＥＳＴＩＭＡＴＩＯＮ　ＢＹ　ＲＥＭＯＴＥ　ＳＥＮＳＩＮＧ　ＩＮ　ＪＩＬＩＮ　ＭＡＩＺＥ　ＢＥＬＴＳＴＵＤＹＯＮＧＩＳＦＯＲＹＩＥＬＤＥＳＴＩＭＡＴＩＯＮＢＹＲＥＭＯＴＥＳＥＮＳＩＮＧＩＮＪＩＬＩＮＭＡＩＺ...     

REMOTE SENSING FOREST BIOMASS: AN EVALUATION USING HIGH RESOLUTION REMOTE SENSOR DATA AND LOBLOLLY PINE PLOTS

Eight-year-old Loblolly pine (Pinus taeda) plots located in South Carolina were evaluated using high resolution aircraft multispectral scanner data to determine if biomass could be accurately measured. Sixteen pine plots located on both sandy and clay soils were treated with 0, 180, or 360 kg. (approximately 0, 400, or 800 lb.) of nitrogen per plot. Indices of biomass from remote sensing data were significantly correlated with in situ biomass measurements made in each plot. A ratio of infrared (.9–1.1 μm) and red (.65–.70 μm) channels yielded the best correlation. The indices were not sensitive to differences in soil type (sandy or clay).     

Using bright ellipticals as dark energy cosmic clocks

The age of the Universe has been increasingly constrained by different techniques, such as the observations of type Ia supernovae (SNIa) at high redshift or dating the stellar populations of globular clusters. In this paper, we present a complementary approach using the colours of the brightest elliptical galaxies in clusters over a wide redshift range  ( z ≲ 1)  . We put new and independent bounds on the dark energy equation of state parametrized by a constant pressure-to-density ratio   w _Q  and by a parameter (ξ) which determines the scaling between the matter and dark energy densities. We find that accurate estimates of the metallicities of the stellar populations in moderate and high-redshift cluster galaxies can pose stringent constraints on the parameters that describe dark energy. Our results are in good agreement with the analysis of dark energy models using SNIa data as a constraint. Accurate estimates of the metallicities of stellar populations in cluster galaxies at   z ≲ 2  will make this approach a powerful complement to studies of cosmological parameters using high-redshift SNIa.     

Estimation of snow water equivalent using microwave radiometry over Arctic first‐year sea ice

The magnitude and spatial distribution of snow on sea ice are both integral components of the ocean–sea‐ice–atmosphere system. Although there exists a number of algorithms to estimate the snow water equivalent (SWE) on terrestrial surfaces, to date there is no precise method to estimate SWE on sea ice. Physical snow properties and in situ microwave radiometry at 19, 37 and 85 GHz, V and H polarization were collected for a 10‐day period over 20 first‐year sea ice sites. We present and compare the in situ physical, electrical and microwave emission properties of snow over smooth Arctic first‐year sea ice for 19 of the 20 sites sampled. Physical processes creating the observed vertical patterns in the physical and electrical properties are discussed. An algorithm is then developed from the relationship between the SWE and the brightness temperature measured at 37 GHz (55°) H polarization and the air temperature. The multiple regression between these variables is able to account for over 90% of the variability in the measured SWE. This algorithm is validated with a small in situ data set collected during the 1999 field experiment. We then compare our data against the NASA snow thickness algorithm, designed as part of the NASA Earth Enterprise Program. The results indicated a lack of agreement between the NASA algorithm and the algorithm developed here. This lack of agreement is attributed to differences in scale between the Special Sensor Microwave/Imager and surface radiometers and to differences in the Antarctic versus Arctic snow physical and electrical properties. Copyright © 2003 John Wiley & Sons, Ltd.     

利用高光谱数据进行植被生化成分反演方法研究

高光谱数据包含着丰富光谱信息,能够定量地分析物质成分^[1]。由高光谱数据,可以运用多元逐步线性回归方法反演植被生化组分含量,从而达到监测植被生长状况的目的^[2]。本文具体介绍了多元逐步线性回归方法,及其在氮、木质素和纤维素含量估算中的应用。