Optical closure of parameterized bio-optical relationships

An optical closure study on bio-optical relationships was carried out using radiative transfer model matrix operator method developed by Freie Universitt Berlin.As a case study,the optical closure of bio-optical relationships empirically parameterized with in situ data for the East China Sea was examined.Remote-sensing refl ectance(R rs)was computed from the inherent optical properties predicted by these biooptical relationships and compared with published in situ data.It was found that the simulated R rs was overestimated for turbid water.To achieve optical closure,bio-optical relationships for absorption and scattering coeffi cients for suspended particulate matter were adjusted.Furthermore,the results show that the Fournier and Forand phase functions obtained from the adjusted relationships perform better than the Petzold phase function.Therefore,before bio-optical relationships are used for a local sea area,the optical closure should be examined.     

Evaluation of suitability area by ground source heat pump system in Baotou plain

According to the elements of hydrogeological conditions,lithology,stratigraphic thermal physical parameters,construction technology and economic rational elements,the evaluation system of ground source heat pump( GSHP) were established in Baotou plain. The factor weights were determined by using analytic hierarchy process,and the comprehensive element method was selected to evaluate the region suitability of GSHP system. The results show that the suitable area is 559. 63 km2 for utilizing GSHP in the studied area,accounting for 62. 58% of the total area; while the unsuitable area is 334. 60 km2,accounting for37.42%. The evaluating results can provide not only a scientific basis for development and utilization rationally of shallow geothermal heat in Baotou,but also offer an important reference to the other areas.     

江苏沿海滩涂利用模式遥感影像解译和时空变化分析

为了弄清江苏沿海滩涂利用模式分布情况,定量分析其时空变化趋势,本文基于Google Earth Engine云计算平台和Landsat卫星遥感影像数据,结合随机森林分类方法,通过机器学习建立了滩涂利用模式自动识别分类方法,样本训练后识别准确率达93％以上.利用该方法提取了2002年、2014年和2019年江苏沿海的土地...     

遥感信息与作物模型结合在冬小麦区域模拟中的应用

遥感数据与作物模型结合是当前农业信息技术应用研究的重要内容和发展趋势之一,能够解决单独利用遥感或作物模型无法解决的问题。为了开展大范围、区域性作物生长过程的模拟和产量预测,首先对作物模型WOFOST进行了订正和验证,使得调整后的模型适于模拟河南新乡县冬小麦生长;根据实际生产分三类情形模拟新乡县2002—2003年度冬小麦的生长发育状况;利用全生育期内能获取的Landsat-7 ETM+数据反演叶面积指数,结合WOFOST模型的模拟情况,确定每个像元对应的冬小麦的生长状况,从而在像元上实现了WOFOST模型对冬小麦生长的模拟;最后对照比较本研究方法的结果与当年新乡县冬小麦的统计情况,结果相近,验证了本文研究方法的技术可行性。     

星载激光雷达卫星海面风场反演算法研究

The principal purpose of this paper is to extract entire sea surface wind＇s information from spaceborne lidar, and particularly to utilize a appropriate algorithm for removing the interference information due to white caps and subsurface water. Wind speeds are obtained through empirical relationship with sea surface mean square slopes. Wind directions are derived from relationship between wind speeds and wind directions im plied in CMOD5n geophysical models function （GMF）. Whitecaps backscattering signals were distinguished with the help of lidar depolarization ratio measurements and rectified by whitecaps coverage equation. Subsurface water backscattering signals were corrected by means of inverse distance weighted （IDW） from neighborhood non-singular data with optimal subsurface water backscattering calibration parameters. To verify the algorithm reliably, it selected NDBC＇s TAO buoy-laying area as survey region in camparison with buoys＇ wind field data and METOP satellite ASCAT of 25 km single orbit wind field data after temporal-spa tial matching. Validation results showed that the retrieval algorithm works well in terms of root mean square error （RMSE） less than 2m/s and wind direction＇s RMSE less than 21 degree.     

The use of ocean color remote sensing in integrated coastal zone management—A case study from Himmerfjärden,Sweden

In this study the use of ocean color data as a diagnostic tool in integrated coastal zone management was investigated as part of the Science Policy Integration for Coastal Systems Assessment (SPICOSA) project. Parallel to this, an operational coastal monitoring system has been set up in close collaboration with end-users. The core work of the bio-optical part in the project was to develop Secchi depth and attenuation of light as indicators for coastal zone management, by linking remote sensing with the socio-economic and ecological model developed in SPICOSA. The article emphasizes the benefits of stakeholder involvement and end-user feedback for efficient and improved system development. Furthermore, conceptual models were developed on how to integrate remote sensing data into coastal zone management and into a physical-biological model of the Baltic Sea. One of the work packages in the SPICOSA project was academic training. In this work package, on-line teaching material in the field of remote sensing and bio-optics was developed and disseminated on the SETnet web page. The article presented here may act as supportive material for training in bio-optics and remote sensing.     

基于ENVI 的唐山湾三岛土地利用遥感分类方法的比较分析

对唐山湾三岛2010年10月10 m分辨率的SPOT5多光谱数据源,采用不同分类方法进行识别和判断,并对比不同分类器在遥感影像分类中的应用效果和分类精度。有针对性地探究海岛土地利用遥感分类过程中不同方法的优劣,获取最适于岛陆地区土地利用的遥感分类方法。根据土地利用现状分类标准(GB/T21010-2007)和海岛陆域土地利用类型划分的相关规定,将唐山湾三岛主要分为滩涂、裸地、林地、草地、居住区、内陆水体和潮间带(潮水覆盖区)6类。并分别构建结合人为控制的非监督分类、监督分类和基于专家知识的决策树分类系统,参照更高分辨率影像、先验知识和野外调查资料,评价分类结果与实地调查结果的吻合程度,最终通过总体分类精度和Kappa系数等指标对各分类器精度进行评价和对比分析。     

中国区域滨海湿地固碳能力研究现状与提升

对我国滨海湿地的固碳能力进行了评估,同时,对其固碳能力的遥感监测和评估方法进行了总结和分析,最后提出了滨海湿地固碳能力的提升技术。全球看来,我国滨海湿地的固碳能力总体上不高。国内看来,在北方泥炭地和植被覆盖率高,生长茂盛的区域,尤其是有红树林生长的区域固碳能力相对较高。滨海湿地主要分布在潮间带,人为监测困难,卫星遥感的出现为滨海湿地的监测带来很大方便,遥感监测已成为评估湿地固碳能力的一种高时效方法。滨海湿地固碳蕴藏着巨大潜力,提升滨海湿地的固碳能力可以大大降低全球CO2含量,对于改善全球温室效应有不可替代的作用。     

因子分析在海河流域石油类污染综合评价中的应用(英文)

基于因子分析对2012~2013年海河流域pH、DO、COD、BOD5、氨态氮和总石油烃等6项水质指标的监测数据进行统计,并对其中四项指标进行水污染综合指数评估,旨在对海河水质进行较为系统的评价。结果显示,BJ1和HB2两个站位水质属于Ⅳ类标准,其余各站位均为Ⅴ类;各站位综合评价结果得到海河流域指数为1.44,说明海河流域处于污染状态,其污染程度超过该流域功能区的标准。因子分析发现,COD、DO和NH3-N之间差异显著(P0.05);主成分分析显示,除pH和BOD5外,其余指标都在0.70以上;COD、DO、NH3-N和TPH的贡献率较高,其中总石油烃的贡献率为100%,因此可以认为该海域的污染类型属于有机污染,且石油烃污染较为突出。     

Soil respiration mapped by exclusively use of MODIS data for forest landscapes of Saskatchewan,Canada

Soil respiration (R_s) is of great importance to the global carbon balance. Remote sensing of R_s is challenging because of (1) the lack of long-term R_s data for model development and (2) limited knowledge of using satellite-based products to estimate R_s. Using 8-years (2002–2009) of continuous R_s measurements with nonsteady-state automated chamber systems at a Canadian boreal black spruce stand (SK-OBS), we found that R_s was strongly correlated with the product of the normalized difference vegetation index (NDVI) and the nighttime land surface temperature (LSTn) derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The coefficients of the linear regression equation of this correlation between R_s and NDVI × LSTn could be further calibrated using the MODIS leaf area index (LAI) product, resulting in an algorithm that is driven solely by remote sensing observations. Modeled R_s closely tracked the seasonal patterns of measured R_s and explained 74–92% of the variance in R_s with a root mean square error (RMSE) less than 1.0 g C/m²/d. Further validation of the model from SK-OBS site at another two independent sites (SK-OA and SK-OJP, old aspen and old jack pine, respectively) showed that the algorithm can produce good estimates of R_s with an overall R² of 0.78 (p < 0.001) for data of these two sites. Consequently, we mapped R_s of forest landscapes of Saskatchewan using entirely MODIS observations for 2003 and spatial and temporal patterns of R_s were well modeled. These results point to a strong relationship between the soil respiratory process and canopy photosynthesis as indicated from the greenness index (i.e., NDVI), thereby implying the potential of remote sensing data for detecting variations in R_s. A combination of both biological and environmental variables estimated from remote sensing in this analysis may be valuable in future investigations of spatial and temporal characteristics of R_s.