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

M. C. Zhou  H. Ishidaira  K. Takeuchi 《水文研究》2007,21(14):1860-1874

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.  相似文献   

NOAA卫星沙尘暴光谱特征分析及信息提取研究   总被引：12，自引：5，他引：7  

郭铌  倾继祖 《高原气象》2004,23(5):643-647,i001,i002

通过对2000—2002年多次沙尘暴过程NOAA卫星AVHRR资料的分析,研究了沙尘、云、沙漠、戈壁、积雪、裸地、植被等不同目标物的光谱特性,发现沙尘暴在AVHRR-2中各通道均有不同程度的反映。1,2通道中沙尘的反射率较高(介于云和沙漠之间);4,5通道的亮温低于晴空地表高于云;在3通道中沙尘表现的很独特,其亮度温度为所有研究目标物中最高的,表明通道3包含较多的沙尘信息,AVHRR-3取代AVHRR-2后对监测沙尘有不利影响。在此基础上提出定量提取沙尘信息的两种沙尘判识指数,并利用沙尘判识指数成功地提取多次沙尘暴过程的沙尘信息。结果表明：利用多通道组合沙尘判识指数能够对沙尘信息进行有效提取。  相似文献   

Effect of NOAA satellite orbital drift on AVHRR-derived phenological metrics     

《International Journal of Applied Earth Observation and Geoinformation》2017

The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center routinely produces and distributes a remote sensing phenology (RSP) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) 1-km data compiled from a series of National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-11, −14, −16, −17, −18, and −19). Each NOAA satellite experienced orbital drift during its duty period, which influenced the AVHRR reflectance measurements. To understand the effect of the orbital drift on the AVHRR-derived RSP dataset, we analyzed the impact of solar zenith angle (SZA) on the RSP metrics in the conterminous United States (CONUS). The AVHRR weekly composites were used to calculate the growing-season median SZA at the pixel level for each year from 1989 to 2014. The results showed that the SZA increased towards the end of each NOAA satellite mission with the highest increasing rate occurring during NOAA-11 (1989–1994) and NOAA-14 (1995–2000) missions. The growing-season median SZA values (44°–60°) in 1992, 1993, 1994, 1999, and 2000 were substantially higher than those in other years (28°–40°). The high SZA in those years caused negative trends in the SZA time series, that were statistically significant (at α = 0.05 level) in 76.9% of the CONUS area. A pixel-based temporal correlation analysis showed that the phenological metrics and SZA were significantly correlated (at α = 0.05 level) in 4.1–20.4% of the CONUS area. After excluding the 5 years with high SZA (>40°) from the analysis, the temporal SZA trend was largely reduced, significantly affecting less than 2% of the study area. Additionally, significant correlation between the phenological metrics and SZA was observed in less than 7% of the study area. Our study concluded that the NOAA satellite orbital drift increased SZA, and in turn, influenced the phenological metrics. Elimination of the years with high median SZA reduced the influence of orbital drift on the RSP time series.  相似文献   

The role of the International Maritime Organization in reducing vessel threat to whales: Process,options, action and effectiveness     

Gregory K. Silber  Angelia S.M. Vanderlaan  Ana Tejedor Arceredillo  Lindy Johnson  Christopher T. Taggart  Moira W. Brown  Shannon Bettridge  Ricardo Sagarminaga 《Marine Policy》2012

  相似文献   

黄淮海平原耕地转移对植被碳储量的影响   总被引：8，自引：0，他引：8  

姜群鸥  邓祥征  战金艳  刘兴权 《地理研究》2008,27(4):839-847

应用GLO-PEM模型和1988年NOAA/AVHRR遥感数据,估算了黄淮海平原植被净初级生产力(NPP),并根据NPP和植被凋落物产生量计算了不同土地利用类型的植被碳密度。通过对1988年与2000年土地利用图的叠置分析,统计了耕地与其他土地利用类型之间的转移量,并估算了耕地转移对植被碳储量的影响。研究发现,耕地转移对植被碳储量变化的影响在不同区域与不同土地利用类型上存在显著差异。1988~2000年间,耕地转移导致全区植被碳储量下降了0.24%,其中耕地转为建设用地是植被碳储量减少的主要原因。这一研究结论为正确把握耕地转移对区域植被碳储量的影响,并据此制订碳汇管理措施具有重要的参考价值。  相似文献   

应用NOAA/AVHRR数据测算局地水稻种植面积方法研究   总被引：29，自引：3，他引：29  

李郁竹  曾燕 《遥感学报》1998,2(2):125-130

本文采用在模糊监督分类中增加迭代过程的方法－－模糊监督分类一迭代法,在分解混合像元的基础上,利用ＡＶＨＲＲ数据求算水稻种植面积。根据稻田与旱地存在温度差异的特点,在分析ＡＶＨＲＲ数据统计特征的基础上,增加了第３和４两通道参加模糊监督分类,从而增加了分类橡元值矢量维数,增强了对水稻的鉴别能力。反采用的迭代法是收敛具有效的,经本方法输出的水稻种植面积百分含量图与实际水稻分布十分吻合,测算出的面积值与Ｔ  相似文献   

Estimation of the Spatial Variation in Evapotranspiration based on Landsat TM and NOAA Satellite Imagery     

Henrik Søgaard M.Sc. 《Geografisk tidskrift / udgivet af Bestyrelsen for Det Kongelige danske geografiske selskab》2013,113(1):80-85

Søgaard, Henrik: Estimation of the Spatial Variation in Evapotranspiration based on Landsat TM and NOAA Satellite Imagery. Geografisk Tidsskrift 92: 80–85. Copenhagen 1992.

During the last decade, the use of satellite imagery for monitoring water and energy budgets has gained increasing interest. Based on ground reference data collected above a barley field located near Viborg in Jutland, the so-called simplified relationship between net radiation, temperature, and evapotranspiration was examined. It was found that the difference between evapotranspiration and net radiation depends on both the temperature difference between the surface and the air, and the surface roughness. The derived relationship was applied for monitoring evapotranspiration on the basis of surface temperature measured by the NOAA- satellites. This paper will present this study and examine the resolution problem caused by the field size being less in area than the 1 km by 1 km covered by a single NOAA picture element. For a selected day in July, this was done by comparing the NOAA data with Landsat TM-data which has a 120 m resolution in the thermal band.  相似文献   

Auto-identification of forest fire-points in NOAA images based on neural network     

Liang Yitong  Hu Jianglin  Liu Liangming  Xie Ping 《地球空间信息科学学报》2013,16(3):68-72

Identification of forest fire-points in NOAA images in the basis of monitoring forest fire using NOAA satellite data. Traditional visual interpretation is difficult to settle for auto identification with computer. The artificial neural network technique provides a new means for solving this problem. In this paper, the principles and method of using neural network technique to automatically identify fire-points in NOAA images are discussed and the test in the range of Hubei province is presented. The result of the test shows that the disciplined neural network has collected the character of fire-points and has ability to identify fire-points in NOAA images. Comparing neural network with visual interpretation, the conclusion is drawn that by using neural network the purpose of auto-identification of forest fire-points in NOAA images can be realized with the almost same precision.  相似文献   

基于多轨道卫星观测数据分析尼泊尔地震长波辐射特征          下载免费PDF全文

孙珂  单新建  Dimitar Ouzounov  申旭辉  荆凤 《地球物理学报》2017,60(9):3457-3465

综合已经在红外异常提取中应用的涡度和RST(Robust Satellite Technique)算法优点,提出了红外异常指数算法.并基于长时间尺度的中国静止卫星FY-2D和美国极轨卫星NOAA长波辐射数据,应用RST和异常指数算法,分别对2015年4月25日尼泊尔M_s8.1和5月12日M_s7.5地震前后卫星长波辐射变化特征进行了分析,开展了多轨道、多时空分辨率长波辐射同步地震热红外特征研究.结果表明,运用RST算法,两次地震前后,未能在震中周围发现明显的长波辐射异常.运用异常指数算法:(1)对于NOAA卫星,4月15日在M_s8.1地震震中以西出现热红外异常,到4月24日震中以西约100 km处出现异常最大值,随后逐渐消失.5月10日在M_s7.5地震震中以东约200 km发现异常;(2)在NOAA卫星长波辐射异常发现最大值当日,采用FY-2D卫星每3 h的数据分析可发现红外异常的动态演化过程,弥补NOAA卫星分辨率不足.以上结果为利用多轨道卫星监测地震热辐射变化提供了依据.  相似文献   

大气散射对采用归一化植被指数进行赤潮遥感监测的影响研究   总被引：3，自引：0，他引：3  

唐军武  丁静  王其茂  马超飞 《海洋学报》2004,26(3):136-142

1　引言近年来赤潮灾害在我国海域频繁发生,对沿海环境、经济和人民生产生活都造成一定的影响,因此对赤潮进行实时监测并业务化运行就显得尤其重要.赤潮遥感监测是目前常用手段之一,在实践中取得了一定的效果,但到目前为止还没有一种成熟的算法能用于业务化监测赤潮的发生.很多研究人员借鉴归一化植被指数(NDVI)阈值法、海表温度(SST)异常等来判断赤潮的发生,但归一化植被指数阈值法经常会出现误判或无法区分正常与异常水体的情况.该阈值范围由先验知识得到,没有定量的理论依据.归一化植被指数是陆地遥感中用以表征地表植物覆盖程度和健…  相似文献