Detecting Arctic snow and ice cover with FY-1D global data

Chinese meteorological satellite FY-1D can obtain global data from four spectral channels which include visible channel(0.58-0.68 μm) and infrared channels(0.84-0.89 μm,10.3-11.3 μm,11.5-12.5 μm).2366 snow and ice samples,2024 cloud samples,1602 land samples and 1648 water samples were selected randomly from Arctic imageries.Land and water can be detected by spectral features.Snow-ice and cloud can be classified by textural features.The classifier is Bayes classifier.By synthesizing five d ays classifying result of Arctic snow and ice cover area,complete Arctic snow and ice cover area can be obtained.The result agrees with NOAA/NESDIS IMS products up to 70%.     

Estimation of potential evapotranspiration over the Yellow River basin: reference crop evaporation or Shuttleworth–Wallace?

Potential evapotranspiration (PET) is a key input to hydrological models. Its estimation has often been via the Penman–Monteith (P–M) equation, most recently in the form of an estimate of reference evapotranspiration (RET) as recommended by FAO‐56. In this paper the Shuttleworth–Wallace (S–W) model is implemented to estimate PET directly in a form that recognizes vegetation diversity and temporal change without reference to experimental measurements and without calibration. The threshold values of vegetation parameters are drawn from the literature based on the International Geosphere–Biosphere Programme land cover classification. The spatial and temporal variation of the LAI of vegetation is derived from the composite NOAA‐AVHRR normalized difference vegetation index (NDVI) using a method based on the SiB2 model, and the Climate Research Unit database is used to provide the required meteorological data. All these data inputs are publicly and globally available. Consequently, the implementation of the S–W model developed in this study is applicable at the global scale, an essential requirement if it is to be applied in data‐poor or ungauged large basins. A comparison is made between the FAO‐56 method and the S–W model when applied to the Yellow River basin for the whole of the last century. The resulting estimates of RET and PET and their association with vegetation types and leaf area index (LAI) are examined over the whole basin both annual and monthly and at six specific points. The effect of NDVI on the PET estimate is further evaluated by replacing the monthly NDVI product with the 10‐day product. Multiple regression relationships between monthly PET, RET, LAI, and climatic variables are explored for categories of vegetation types. The estimated RET is a good climatic index that adequately reflects the temporal change and spatial distribution of climate over the basin, but the PET estimated using the S–W model not only reflects the changes in climate, but also the vegetation distribution and the development of vegetation in response to climate. Although good statistical relationships can be established between PET, RET and/or climatic variables, applying these relationships likely will result in large errors because of the strong non‐linearity and scatter between the PET and the LAI of vegetation. It is concluded that use of the implementation of the S–W model described in this study results in a physically sound estimate of PET that accounts for changing land surface conditions. Copyright © 2006 John Wiley & Sons, Ltd.     

Influence of Land Use/Cover Change on Storm Runoff— A Case Study of Xitiaoxi River Basin in Upstream of Taihu Lake Watershed

Land use/cover change (LUCC) is one of the main boundary conditions which influence many hydrologic processes. In view of the importance of Taihu Lake Watershed in China and the urgency of discovering the impacts of LUCC on storm runoff, two flood events under five land cover scenarios in the Xitiaoxi River Basin of the upstream of Taihu Lake watershed were simulated by distributed hydrologic modeling system HEC-HMS. The influences of each land cover on storm runoff were discussed. It was concluded that under the same rainstorm the ascending order of runoff coefficient and peak flow produced by the 5 different land covers were woodland, shrub, grassland, arable land, and built-up land; the descending order of swelling time were woodland, shrub, grassland, arable land, and built-up land. Scenario of built-up land was the first to reach peak flow, then arable land, grassland, shrub, and woodland. There were close relationships between the runoff coefficients produced by the 5 different land covers. The degrees of impacts on runoff coefficient of land cover change modes were sorted by descending: woodland to built-up land, shrub to built-up land, grassland to built-up land, arable land to built-up land, woodland to arable land, shrub to arable land, arable land to grassland, shrub to grassland, grassland to arable land, and woodland to shrub. Urbanization will contribute to flood disaster, while forestation will mitigate flood disaster.     

基于HJ-1A高光谱的黄河口碱蓬和柽柳盖度反演模型研究

碱蓬和柽柳是黄河口湿地典型的盐生植物类型,是多种保护珍禽的主要栖息地,具有景观尺度较小、分布广且多混生的特点。应用覆盖黄河口北部潮滩的HJ-1A高光谱遥感影像,基于现场测量的端元光谱和从遥感影像中使用顺序最大角凸锥法(SAMCC)自动提取的端元光谱,应用线性光谱分解法(LSU)、正交子空间投影法(OSP)、匹配滤波法(MF)、最小能量约束法(CEM)和自适应一致估计法(ACE)5种不同光谱解混方法进行混合像元光谱解混,对比两种方法得到的端元光谱分别对碱蓬和柽柳盖度的反演能力,并给出相应的反演模型。结果显示:(1)现场测量端元光谱取得了较好的碱蓬和柽柳盖度反演结果,其中应用LSU方法的光谱解混结果与现场测量盖度的决定系数对于碱蓬和柽柳分别达到了0.88和0.95;(2)两种端元获取方式的光谱解混结果中,LSU和OSP方法均获得了较高的相关性,ACE解混方法的相关性都最低;(3)SAMCC方法提取端元光谱对柽柳的分解结果与现场测量盖度的相关性远高于碱蓬。     

基于GEE的地表覆盖与气候状态关联研究

为探究地表覆盖与气候状态间的关联性,本文选取2019年的Landsat影像数据,结合温度、降水量、PM_2.5浓度3种气候指标,利用GEE平台,结合NDVI、MNDWI、NDBI,采用SVM、RF、CART方法进行地表覆盖分类,探究气候指标与地表覆盖类型分布的关联性;提出了使用3种气候指标构建分类特征进行地表覆盖分类的方法,并通过消融试验分析了气候指标对地表覆盖分类精度的影响。结果表明:①RF有较好的分类结果,总体精度为96.0%;②3种气候指标均能提高地表覆盖分类精度,其中PM_2.5浓度效果最好;③温度与植被、水体关联性较大,PM_2.5浓度与城区、植被关联性较大,降水量与耕地关联性较大。     

大光斑波形数据在土地覆盖分类的适用性分析

针对GLAS地学激光测高系统是冰、云和陆地高程卫星(ICESat)的唯一监测工具,能够记录地表光斑内的地物信息,是否能应用于黄土高原土地覆盖分类的问题进行了研究。利用粒子群和最小二乘法相结合的方法对GLAS波形数据进行高斯分解,获取高斯波个数、波形总能量、波形信号起始和信号结束位置4个波形参数;基于波形自动分类方法对黄土高原水体、森林、城市用地、其他地类(裸地、低矮植被等)进行分类。通过基于覆盖相同研究区域的30 m地表覆盖数据(Globe Land30),验证分类的准确性。结果表明,GLAS大光斑波形数据对黄土高原的4种地类能够很好地进行区分,总分类精度高达87.68%,Kappa系数为65.79%。研究表明,GLAS波形数据可以作为获取土地覆盖信息的有效数据源,为研究黄土高原土地覆盖变化提供更丰富的数据支持。     

刍议《重庆历史地图集》第二卷的编制

以《重庆历史地图集》第二卷编制的具体情况为例,对图集的开本设计、内容结构设计、封面和版式设计、整体设计、创新源,以及图集编制取得的经验进行了论述,为以后类似图集的编制提供参考。     

The Effects of Land Cover Change on Regional Climate over the Eastern Part of Northwest China

A regional climate model(Reg CM4) is employed to investigate the impacts of land use/cover change(LUCC) on the climate over the eastern part of Northwest China(ENW) in the periods of 2001 and 2011. The results indicated that the LUCC in ENW, which was characterized by desert retreat, reforestation, and farmland expansion, led to significant local changes in surface air temperature(within ~0.3°C) and slight regional changes in precipitation(within ~15%) in summer. In the desert retreat area, the net absorbed shortwave radiation had a greater influence than evaporative cooling, leading to increases in the daily mean and maximum temperature. Besides, the daily mean and maximum temperatures increased in the reforestation area but decreased in the farmland expansion area. As surface albedo showed no significant change in these regions, the temperature increase in the reforestation area can be attributed to a decrease in evaporation, while the opposite effect appears to have been the case in the farmland expansion area.     

Interannual and Decadal Variations of Surface Solar Radiation over East China in the First Half of the 20th Century

Variability and long-term trends of sunshine duration(SSD) and total cloud cover(TCC) were studied based on surface observations from 10 meteorological stations over East China in the first half of the 20 th century. The correlation coefficients between SSD and diurnal temperature range(DTR), as well as TCC, were analyzed. SSD experienced a significant increasing trend(0.16 h d-1 per decade) from 1908 to 1936, and the maximum brightening was in autumn(0.33 h d-1 per decade). The good agreement between the variability of SSD and DTR, supported by the correlation coefficient between them of 0.72, implies that the SSD measurements were reliable. TCC showed a decreasing trend(-0.93% per decade) and was significantly inversely related to SSD(-0.74), indicating the variation of SSD was attributable to changes in cloud cover. The result was obviously different to that since the 1960 s, when clouds could not account for the decadal trend of surface solar radiation in China.     

Evaluating the economic damage of climate change on global coral reefs

This paper evaluates the global economic damage arising from the effects of climate change and associated carbon dioxide concentrations on the loss of coral reefs. We do this by first estimating the effects of sea surface temperature and carbon dioxide concentrations on coral cover. We develop a statistical relationship between coral coverage and sea surface temperature that indicates that the effects are dependent on the temperature range. For example, we find that increasing sea surface temperature causes coral coverage to decrease when sea surface temperature is higher than 26.85 °C, with the estimated reduction being 2.3% when sea surface temperature increases by 1%. In addition, we find that a 1% carbon dioxide increase induces a 0.6% reduction in global coral coverage. We also estimate the resultant loss in economic value based on a meta-analysis of the recreational and commercial value of reef coverage and a crude proportional approach for other value factors. The meta-analysis shows that the coral reef value decreases by 3.8% when coral cover falls by 1%. By combining these two steps we find that the lost value in terms of the global coral reef value under climate change scenarios ranges from US$3.95 to US$23.78 billion annually.