Estimating regional forest cover in East Texas using Advanced Very High Resolution Radiometer (AVHRR) data

This study tested the degree to which single date, near-nadir AVHRR image could provide forest cover estimates comparable to the phase I estimates obtained from the traditional photo-based techniques of the Forest Inventory and Analysis (FIA) program. FIA program is part of the United States Department of Agriculture-Forest Service (USFS). A six-county region in east Texas was selected for this study. Manual identification of ground control points (GCPs) was necessary for geo-referencing this image with higher precision. Through digital image classification techniques forest classes were separated from other non-forest classes in the study area. Classified AVHRR imagery was compared to two verification datasets: photo-center points and the USFS FIA plots. The overall accuracy values obtained were 67 and 71%, respectively. Analyses of the error matrices indicated that the AVHRR image correctly classified more forested areas than non-forested areas; however, most of the errors could be attributed to certain land cover and land use classes. Several pastures with tree cover, which were field-identified as non-forest, were misclassified as forest in the AVHRR image using the image classification system developed in this study. Recently harvested and young pine forests were misclassified as non-forest in the imagery. County-level forest cover estimates obtained from the AVHRR imagery were within the 95% confidence interval of the corresponding estimates from traditional photo-based methods. These results indicate that AVHRR imagery could be used to estimate county-level forest cover; however, the precision associated with these estimates was lower than that obtained through traditional photo-based techniques.     

Comparison of some vegetation indices in seasonal information

With the development of vegetation indices, the reflection capability of vegetation indices to the state of vegetation has been improved in various degrees. Especially, the vegetation index of Terra/MODIS-EVI is believed to have the highest sensitivity to the seasonality of vegetation. This study compares the reflection susceptibility of three vegetation indices （NOAA/AVHRR-NDVI, Terra/MODIS-NDVI and Terra/MODIS-EVI） to the seasonal variations of vegetation in the mid-south of Yunnan Province of China. It has been found that Terra/MODIS-EVI does best in the elimination of external disturbance. Firstly, it obviously improves the linear relationship with vegetation cover degree, especially in the high vegetation coverage area. Secondly, it avoids the emergence of vegetation index saturation. Thirdly, it reduces the environmental influence including both effects of atmosphere and soil. So it is believed that the Terra/MODIS-EVI can offer excellent tool for quantitative research of remote sensing, and has realized to be oriented by data with high quality.     

A simulation study on the eco-environmental effects of 3N Shelterbelt in North China

Based on the Global Land Cover Characteristics Database (GLCCD) generated by the U.S. Geological Survey (USGS) and University of Nebraska-Lincoln (UNL), a new land cover dataset within a domain of 14.1–49.6°N, 84.6–140.5°E is extracted. This dataset is used to identify the achievements of constructing 3N (Northeast, North and Northwest of China) Shelterbelt in North China and to update the lower boundary conditions of the mesoscale model (MM5), a widely used mesoscale meteorological model. The model is then used to simulate the regional climate effects of the 3N Shelterbelt, the largest forestation engineering in the world. The simulation shows that the construction of the 3N Shelterbelt and the corresponding land use and land cover (LULC) variations in China have changed the roughness length in the cited model domain significantly. Consequently, the surface layer wind speed, air temperature, humidity, and the precipitation are all changed. As compared with the control run without the 3N Shelterbelt, the regional climate in North China is improved shown by the decreased wind speed, increased air humidity and precipitation. The paper also stresses that, in meteorological or climatic simulations, the lower boundary conditions related to the land cover has to be updated frequently by the satellite observed database since the LULC vary fast due to the increasing world population and human activities, this is especially true in developing countries like China.     

利用NOAA—AVHRR资料估算积雪参量

本文介绍了利用气象卫星AVHRR资料对青海省青南高原看牧区冬春（10月－4月）积雪进行监测的原理，提出了利用AVHRR资料估算积雪深度和面积的方法，并对其精度进行了检验。     

Analysis of pathfinder SST algorithm for global and regional conditions

As part of the Pathfinder program developed jointly by National Aeronautics and Space Administration (NASA) and National Oceanic and Atmospheric Administration (NOAA) a large database ofin situ sea surface temperature (SST) measurements coincident with satellite data is now available to the user community. The Pathfinder Matchup Database (PMDB) is a multi-year, multi-satellite collection of coincident measurements from the Advanced Very High Resolution Radiometer (AVHRR) and broadly distributed buoy data (matchups). This database allows the user community to test and validate new SST algorithms to improve the present accuracy of surface temperature measurements from satellites. In this paper we investigate the performance of a global Pathfinder algorithm to specific regional conditions. It is shown that for zenith angles less than 45°, the best-expected statistical discrepancy between satellite and buoy data is about ∼ 0.5 K. In general, the bias of the residuals (satellite — buoy) is negative in most regions, except in the North Atlantic and adjacent seas, where the residuals are always positive. A seasonal signal in SST residuals is observed in all regions and is strongest in the Indian Ocean. The channel-difference term used as a proxy for atmospheric water vapor correction is observed to be unresponsive for columnar water vapor values greater than 45 mm and high zenith angles. This unresponsiveness of the channels leads to underestimation of sea surface temperature from satellites in these conditions.     

南海东北部冬季表面环流的卫星红外遥感观测研究

根据 1 989～ 1 993年美国 NOAA系列卫星 (NOAA- 1 1、 1 2 )经过南海上空时所获取的数幅较完整的 AVHRR传感器映像资料 ,并结合 1 992年 3月 8日～ 2 7日在南海东北部海域现场观测所获的 CTD资料 ,揭示并讨论了发生在该海域的一些物理海洋学现象。结果表明 ,利用卫星映像和现场观测资料来分析和研究南海中的物理海洋学问题有着较好的互补性。卫星映像产生的海面温度场的分布基本上反映了现场观测的结果。通过对两者的综合分析 ,给出了一幅南海东北部冬季表面环流的形势图     

近岸流系与长江入海悬浮泥沙输移扩散

通过两年较完整的序列 NOAA/AVHRR 数据和实测含沙量资料,利用考虑近岸Ⅱ类水体大气校正的泥沙定量反演算法,获得了较高精度的河口高浓度泥沙遥感反演模式;利用泥沙浓度分级图和反映流系特征的温度图象,系统分析了长江口悬浮泥沙扩散途径、范围及其与近岸流系的关系。影响长江入海悬浮泥沙扩散的近岸流系主要包括台湾暖流、黄海混合水、苏北沿岸流及浙江沿岸流等。冬季,近岸流系比较稳定,其配置状况在一定程度上影响着苏北沿岸泥沙流向长江口的扩散,并制约着入海悬浮泥沙的扩散途径;洪季,长江入海径流量是影响悬浮泥沙扩散的重要因子。同时,长江冲淡水、浙江沿岸流共同形成的冷水区与台湾暖流水之间锋面的强度,也对悬浮泥沙和冲淡水的扩散方向和范围有重要影响;春、秋两季入海悬浮泥沙的扩散型式分别向夏、冬季的分布格局过渡。此外,风应力显著影响着浑水区的扩散方向和范围。风浪掀沙引起的河口泥沙再悬浮,可使近岸泥沙扩散范围增大。     

基于变分理论的AVHRR海表温度反演应用及效果评估

基于变分理论算法实现了METOP-A卫星AVHRR传感器探测数据的海洋表面温度变分反演,进行了连续1个月的海表温度反演试验,并分别从全球、分纬度带和天气系统活跃区域3个方面,将变分反演结果（VAR SST）与利用统计回归方法反演相同卫星得到的海表温度产品（GBL SST）、其他海温融合产品（OISST）及实际浮标观测数据等进行一系列评估。从全球评估指标看出,以OISST为参照,VAR SST要优于GBL SST;以浮标观测为参照,VAR SST略逊于GBL SST,而且VAR SST还改进了GBL SST随时间波动大的缺点;从分纬度带对比看出,在与OISST对比时,VAR SST在低纬度地区和北半球中纬度地区的质量要优于GBL SST,海温反演精度较高。研究还表明,由于变分方法考虑了大气状态的变化,能够更加有效订正卫星遥感过程中大气的削弱作用,从而反演出精度更高的海表温度,尤其在天气系统较为复杂的区域效果明显。     

Modelling snowpack surface temperature in the Canadian Prairies using simplified heat flow models

Three practical schemes for computing the snow surface temperature T_s, i.e. the force–restore method (FRM), the surface conductance method (SCM), and the Kondo and Yamazaki method (KYM), were assessed with respect to T_s retrieved from cloud‐free, NOAA‐AVHRR satellite data for three land‐cover types of the Paddle River basin of central Alberta. In terms of R², the mean T_s, the t‐test and F‐test, the FRM generally simulated more accurate T_s than the SCM and KYM. The bias in simulated T_s is usually within several degrees Celsius of the NOAA‐AVHRR T_s for both the calibration and validation periods, but larger errors are encountered occasionally, especially when T_s is substantially above 0 °C. Results show that the simulated T_s of the FRM is more consistent than that of the SCM, which in turn was more consistent than that of the KYM. This is partly because the FRM considers two aspects of heat conduction into snow, a stationary‐mean diurnal (sinusoidal) temperature variation at the surface coupled to a near steady‐state ground heat flux, whereas the SCM assumes a near steady‐state, simple heat conduction, and other simplifying assumptions, and the KYM does not balance the snowpack heat fluxes by assuming the snowpack having a vertical temperature profile that is linear. Copyright © 2005 John Wiley & Sons, Ltd.     

基于RS和GIS的中国西北不同生态类型区生态环境时空变化研究

采用定性与定量相结合的方法,在遥感（RS）和地理信息系统（GIS）支持下,利用1982-2000年的空间分辩率为8 km×8 km的NDVI数据（由NOAA-AVHRR提供）和地面气象资料,联合分析西北不同生态类型区生态环境的变化过程,得出中国西北地区NDVI的年平均值及其历年变化曲线、NDVI年平均值分布图和每隔10 a的差值变化图。由此可以看出,生态环境变化时空特点明显:20世纪80年代生态环境的变化波动不大,90年代以来波动变化明显,而且从1998年以后生态环境总体呈下降趋势;不同生态类型区植被指数年际变化的驱动因子不同,黄土高原区植被指数年际变化与降水量的相关性显著,而青藏高原高寒区与气温的相关性显著,其他分区与降水量和气温的相关性都不显著;生态环境变化的地域差异性明显,西北不同生态类型区中生态环境由好到差依次是陕南-陇南湿润半湿润区、黄土高原区、青藏高原高寒区、干旱区。四个分区1990年比1982年生态环境有所提高,但干旱区退化面积较大,2000年与1990年相比,生态环境都出现不同程度的退化,其中,陕南-陇南湿润半湿润区退化面积最大,其次是黄土高原区。整体生态环境状况不佳,而且近年的退化应该引起重视。