A Modified Becker''s Split-Window Approach for Retrieving Land Surface Temperature from AVHRR and VIRR

In order to provide a long time-series, high spatial resolution, and high accuracy dataset of land surface temperature (LST) for climatic change research, a modified Becker and Li's split-window approach is pro- posed in this paper to retrieve LST from the measurements of Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA)-7 to -18 and the Visible and InfraRed Radiometer (VIRR) onboard FY-3A. For this purpose, the Moderate Resolution Transmittance Model (MODTRAN) 4.1 was first employed to compute the spectral radiance at the top of atmosphere (TOA) under a variety of surface and atmosphere conditions. Then, a temperature dataset consists of boundary temperature Ts (which is one of the input parameters to MODTRAN), and channels 4 and 5 brightness temperatures (T4 and T5) were constructed. Note that channels 4 and 5 brightness tempera- tures were simulated from the MODTRAN output spectral radiance by convolving them with the spectral response functions (SRFs) of channels 4 and 5 of AVHRRs and VIRR. The coefficients of modified Becker and Li's split-window approach for various AVHRRs and VIRR were subsequently regressed based on this temperature dataset using the least square method. As an example of validation, one AVHRR satellite image over Beijing acquired at 0312 UTC 27 April 2008 by AVHRR onboard NOAA-17 was selected to retrieve the LST image using the modified Becker and Li's approach. The comparison between this LST image and that from the MODIS level-2 LST product provided by the University of Tokyo in Japan indicates that the correlation coefficient is 0.88, the bias is 0.6 K, and the root mean square deviation (RMSD) is 2.1 K. Furthermore, about 70% and 37% pixels in the LST difference image, which is the result of retrieved LST image from AVHRR minus the corresponding MODIS LST image, have the values within ±2 and ±1 K, respectively.     

基于NOAA/AVHRR的中亚地区荒漠化动态变化监测

本文通过对影像特征的荒漠化解译,监测荒漠化土地面积和荒漠化程度,分析探讨1989年至2009年中亚地区荒漠化的变化趋势。结果表明本文所采用的监测方法,具有一定可靠性和实用性,能够对中亚地区进行快速地荒漠化的宏观实时监测。     

Vegetation change in the Mt. Qomolangma Nature Reserve from 1981 to 2001

Based on the NOAA AVHRR-NDVI data from 1981 to 2001, the digitalized China Vegetation Map (1:1,000,000), DEM, temperature and precipitation data, and field investiga-tion, the spatial patterns and vertical characteristics of natural vegetation changes and their influencing factors in the Mt. Qomolangma Nature Reserve have been studied. The results show that: (1) There is remarkable spatial difference of natural vegetation changes in the Mt. Qomolangma Nature Reserve and stability is the most common status. There are 5.04% of the whole area being seriously degraded, 13.19% slightly degraded, 26.39% slightly im-proved, 0.97% significantly improved and 54.41% keeping stable. The seriously and slightly degraded areas, which mostly lie in the south of the reserve, are along the national bounda-ries. The areas of improved vegetation lie in the north of the reserve and the south side of the Yarlung Zangbo River. The stable areas lie between the improved and degraded areas. Degradation decreases with elevation. (2) Degeneration in the Mt. Qomolangma Nature Re-serve mostly affects shrubs, needle-leaved forests and mixed forests. (3) The temperature change affects the natural vegetation changes spatially while the integration of temperature changes, slopes and aspects affects the natural vegetation change along the altitude gradi-ents. (4) It is the overuse of resources that leads to the vegetation degeneration in some parts of the Mt. Qomolangma Nature Reserve.     

Evaluating the Impact of Drought Using Remote Sensing in a Mediterranean,Semi-arid Region

This paper analyses monthly differences in drought impact on vegetation activity in a semi-arid region in the north-east of the Iberian Peninsula between 1987 and 2000. The study determines spatial differences in the effects of drought on the natural vegetation and agricultural crops by means of the joint use of vegetation indexes derived from AVHRR images, a drought index (standardized precipitation index), and Geographic Information Systems. The results show that the effect of drought on vegetation varies noticeably between areas, a pattern that is determined mainly by the location of land-cover types. The influence also varies each month and, in general, is higher during the spring and summer. Aridity and vegetation characteristics similarly account, in part, for spatial differences in the impact of drought on vegetation. In general, the most arid areas, where vegetation cover and activity are low, are those in which the interannual variability of vegetation activity is more determined by the drought occurrence. In assessing drought impact, this analysis takes into account the effects of drought on the vegetation and also considers spatial and seasonal differences. The results should be useful for the management of natural vegetation and crops and for the development of better drought mitigation strategies.     

Monitoring drought dynamics in the Aravalli region (India) using different indices based on ground and remote sensing data

The hard-rock hilly Aravalli terrain of Rajasthan province of India suffers with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. In the present study, detailed analysis of meteorological and hydrological data of the Aravalli region has been carried out for the years 1984–2003. Standardised Precipitation Index (SPI) has been used to quantify the precipitation deficit. Standardised Water-Level Index (SWI) has been developed to assess ground-water recharge-deficit. Vegetative drought indices like Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) and Vegetation Health Index (VHI) have been computed using NDVI values obtained from Global Vegetation Index (GVI) and thermal channel data of NOAA AVHRR satellite. Detailed analyses of spatial and temporal drought dynamics during monsoon and non-monsoon seasons have been carried out through drought index maps generated in Geographic Information Systems (GIS) environment. Analysis and interpretation of these maps reveal that negative SPI anomalies not always correspond to drought. In the Aravalli region, aquifer-stress shifts its position time to time, and in certain pockets it is more frequent. In comparison to hydrological stress, vegetative stress in the Aravalli region is found to be slower to begin but quicker to withdraw.     

利用NOAA/AVHRR资料监测云南大面积干旱的业务流程

介绍了利用NOAA／AVHRR资料进行云南大面积干旱监测的方法和业务流程，讨论了干旱指标、面积估算方法、作物干旱识别、产品制作等关键问题，并对1999年春季的曲靖市监测结果作了详细分析。结果表明，在云南利用卫星遥感技术对大范围干旱的面积、程度、空间分布等动态变化监测是可行的。     

大型水体在干旱遥感监测业务中的应用

应用NOAA极轨气象卫星AVHRR资料，通过遥感图像分析和计算洪泽湖、高邮湖、骆马湖以及微山湖等大型河湖水体面积的变化，来监测苏北干旱的发生、发展和旱情严重程度，并及时应用于气象业务和服务中，取得了较好的社会经济效益。     

The temporal and spatial relationship between NDVI and climatological parameters in Colorado

This paper describes the spatial and temporal relationship between AVHRR/NDVI (Normalized Difference Vegetation Index) and climatological parameters (temperature and precipitation), which, in some sense, is influenced by topographical factors and land-cover types in Colorado. The correlation coefficients and partial correlation coefficients have been computed pixel by pixel over Colorado in order to analyze the relationship. The temporal variation and correlation of AVHRR/NDVI, temperature and precipitation were analyzed with a sampling method. The study reveals that there exists a close correspondence between monthly NDVI and temperature, which has strong impact from temperature on the changes of NDVI in Colorado. The spatial changes of NDVI are not influenced obviously by the precipitation since these two variables are different from each other in time series in Colorado. The study clearly revealed the spatial variation and its distribution patterns of relationship between NDVI and climatic parameters (temperature and precipitation) in Colorado.     

The temporal and spatial relationship between NDVI and climatological parameters in Colorado

1 Introduction In recent years, many researchers have demonstrated that there are essential and evident correlations between NDVI and climatological parameters (temperature and precipitation). The analysis of correlation between climate forces and time-integrated NDVI over US Northern and Central Great Plains suggested that spatial and temporal variation of precipitation and potential evapotranspiration and growing degree days in growing season are the most important control on grassland…