用EOS MODIS和MISR数据计算全球BRDF和反照率(英文)

用空间分辨率为１ｋｍ的ＭＯＤＩＳ和ＭＩＳＲ数据可计算１６天ＢＲＤＦ和反照率产品，该文证明了在多数采样条件下，用ＭＯＤＩＳ／ＭＩＳＲ角度采样的ＢＲＤＦ和反照率反演精度在５到１０个百分点以内。     

MODIS与NCEP大气可降水量资料的比较分析

利用中国大陆地区2001年4个季节(1、4、7、10月)中8d和4m的NCEP资料，对整层大气的比湿进行积分得到大气可降水量。选用了同时同地的MODIS大气可降水量资料，然后对两者进行了对比分析。结果发现：在中国西北、内蒙地区MODIS大气可降水量资料要比NCEP资料普遍偏大，而在东南和华南部分地区则普遍偏小。如果对上述两个地区的MODIS资料分别乘以修正系数0．933983和1．07686，则两者的差别可控制在0．2cm以内。因此，MODIS大气可降水量资料经过修正后，可以为卫星反演模式提供同化性较好的输入资料。     

MODIS数据在黄河凌汛监测中的应用

对MODIS数据的特性及其在黄河凌汛监测中的应用情况进行了探讨和总结。试验结果表明 ,MODIS数据在冰雪检测方面具有很大的潜力     

一种改进的MODIS影像BRDF辐射校正方法

针时二向性造成的辐射失真，在核驱动模型的基础上提出了一种改进的二向性反射分布模型，并通过时MODIS影像的试验，得到了减弱辐射差异的较好效果，并对试验结果进行了分析和评价。     

MODIS 1B影像几何纠正方法研究及软件实现

MODIS影像是一种新型和重要的数据。对MODIS 1B影像几何畸变原因进行了深入分析，选择了一种合适的纠正方法。对于1km分辨率MODIS 1B影像，直接采用1km分辨率的空间坐标进行几何纠正；对于250m和500m分辨率的MODIS 1B影像，先用三次样条曲线对坐标进行插值生成同分辨率的坐标，然后利用坐标插值结果对其进行几何纠正。由于MODIS影像在空问分布上的特殊性，采用前向和后向映射相结合的方式确定纠正后某一像素点在原始影像中的位置。根据该位置的条带重叠度，可以确定参与计算像素个数、搜索窗口的大小以及窗口的精确位置；采用归一化反距离加权插值法计算纠正后像素点的属性值。上述优化算法不仅保证了纠正后影像的质量，而且提高了数据处理速度。作者在Visual C 6．0环境下开发实现了上述算法。从坐标插值和几何纠正结果分析，无论是数据处理速度还是纠正后的影像质量和精度均达到要求。     

The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing satellite data

Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect.     

基于2002-2018年MODIS数据的黄海叶绿素a时空变化研究

浮游植物作为食物链的基础,对海洋生态系统具有重要影响。黄海作为我国重要的渔场,渔业资源面临枯竭的危险,因此对该区浮游植物进行研究具有重要意义。叶绿素a浓度是反映浮游植物生物量的重要指标。利用谷歌地球引擎平台对2002-2018年的MODIS Aqua叶绿素a浓度数据进行处理,并研究其时空分布与变化特征,然后结合区域气候、水文与地理特征以及海洋表面温度、风速、盐度、光合有效辐射和混合层厚度数据分析了其分布与变化的原因。研究发现:受陆源营养物质输入、近岸上升流以及黄海中央冷水团影响,叶绿素a浓度分布呈现由近岸向黄海中部递减特征;在季风、气候、水文的控制下,受风速、海洋表面温度、光合有效辐射、中央冷水团的影响,叶绿素a浓度的最大值出现在4月份,而最小值出现在6、7月份;受苏北沿岸海域海水污染和水体富营养化影响,沿岸海域盐度明显增加,海州湾叶绿素a浓度增速较大;影响黄海叶绿素a浓度变化的环境因子较复杂,除了部分月份存在显著的相关影响因子外,在全年和各季中不存在主导影响因子。     

Snow model sensitivity analysis to understand spatial and temporal snow dynamics in a high‐elevation catchment

In this paper, we addressed a sensitivity analysis of the snow module of the GEOtop2.0 model at point and catchment scale in a small high‐elevation catchment in the Eastern Italian Alps (catchment size: 61 km²). Simulated snow depth and snow water equivalent at the point scale were compared with measured data at four locations from 2009 to 2013. At the catchment scale, simulated snow‐covered area (SCA) was compared with binary snow cover maps derived from moderate‐resolution imaging spectroradiometer (MODIS) and Landsat satellite imagery. Sensitivity analyses were used to assess the effect of different model parameterizations on model performance at both scales and the effect of different thresholds of simulated snow depth on the agreement with MODIS data. Our results at point scale indicated that modifying only the “snow correction factor” resulted in substantial improvements of the snow model and effectively compensated inaccurate winter precipitation by enhancing snow accumulation. SCA inaccuracies at catchment scale during accumulation and melt period were affected little by different snow depth thresholds when using calibrated winter precipitation from point scale. However, inaccuracies were strongly controlled by topographic characteristics and model parameterizations driving snow albedo (“snow ageing coefficient” and “extinction of snow albedo”) during accumulation and melt period. Although highest accuracies (overall accuracy = 1 in 86% of the catchment area) were observed during winter, lower accuracies (overall accuracy < 0.7) occurred during the early accumulation and melt period (in 29% and 23%, respectively), mostly present in areas with grassland and forest, slopes of 20–40°, areas exposed NW or areas with a topographic roughness index of ?0.25 to 0 m. These findings may give recommendations for defining more effective model parameterization strategies and guide future work, in which simulated and MODIS SCA may be combined to generate improved products for SCA monitoring in Alpine catchments.     

基于MODIS积雪产品的高亚洲融雪末期雪线高度遥感监测

以2001—2016年逐日MODIS积雪产品为主要数据源,在高亚洲区域发展了大尺度融雪末期雪线高度的遥感提取方法,并对其2001—2016年的时空变化特征进行了分析。提取方法首先对逐日的MODIS积雪覆盖率产品进行去云处理,获得积雪覆盖日数（SCD）数据集;并用冰川年物质平衡观测数据、融雪末期Landsat数据对提取终年积雪的MODIS SCD阈值进行率定;最后以MODIS SCD提取的终年积雪面积结合地形“面积—高程”曲线实现大尺度融雪末期雪线高度信息的提取。结果表明：① 高亚洲融雪末期雪线高度的空间异质性较强,总体上呈南高北低的纬度地带性分布规律;并因受山体效应的影响,雪线高度由高海拔地区向四周呈环形逐渐降低的特点。② 高亚洲2001—2016年融雪末期雪线高度总体上表现为明显的增加趋势。在744个30 km的监测格网中,24.2%的格网雪线高度呈显著增加,而仅0.9%的格网呈显著下降。除兴都库什、西喜马拉雅外,其他地区雪线高度均表现为升高趋势,显著上升的地区主要分布在天山、喜马拉雅中东部和念青唐古拉山等,其中以东喜马拉雅升高最为显著（8.52 m yr ^-1）。③ 夏季气温是影响高亚洲融雪末期雪线高度变化的主要因素,两者具有显著的正相关关系（R = 0.64,P < 0.01）。