Comparison of AVHRR measurements of sea surface temperature with surface observations around New Zealand

Multi‐channel Advanced Very‐High Resolution Radiometer (AVHRR) images of sea surface temperature (SST) in the New Zealand region have been archived since 1989. A comparison of these data with conductivity‐temperature‐depth (CTD) and expendable bathythermograph (XBT) data shows that the AVHRR temperatures are about 7% too high (when expressed in °C). Once the AVHRR temperatures have been corrected, they measure SST with an uncertainty of about 0.7°C.     

通用劈窗算法的NOAA-18(N)AVHRR/3数据地表温度遥感反演与验证

本文以NOAA-18(N)AVHRR/3数据,运用通用劈窗技术获得地表温度。首先,利用MODTRAN 4模拟不同地表和大气状况下热红外通道(Ch4,10.3~11.3μm和Ch5,11.5~12.5μm)的星上亮温,并建立模拟数据库。其次,按照地表温度、大气可降水汽含量、地表比辐射率和观测天顶角,对模拟数据库分组,确定出各分组的通用劈窗算法系数。然后,将构建的地表温度反演模型应用到NOAA-18(N)AVHRR/3数据,模型所需的地表比辐射率由NDVI阈值法确定,大气可降水汽含量是利用Li等(2003)提出的一种劈窗的协方差与方差比的方法来估算。反演结果表明:在观测天顶角小于30°或者大气可降水汽含量小于3.5 g/cm2时,地表温度反演的均方根误差小于1.0K;在观测天顶角小于45°并且大气可降水汽含量小于5.5g/cm2情况下,均方根误差小于1.5K。最后,利用美国通量站的实测数据对地表温度反演结果进行了验证,结果表明均方根误差小于1.8K。     

Vegetation cover variation in the Qilian Mountains and its response to climate change in 2000–2011

An understanding 0f variati0ns in vegetati0n c0ver in resp0nse t0 climate change is critical f0r predicting and managing future terrestrial ec0system dynamics. Because scientists anticipate that m0untain ec0systems will be m0re sensitive t0 future climate change c0mpared t0 0thers, 0ur 0bjectives were t0 investigate the impacts 0f climate change 0n variati0n in vegetati0n c0ver in the Qilian M0untains （QLM）, China, between 2000 and 2011. T0 acc0mplish this, we used linear regressi0n techniques 0n 250-m MODIS N0rmalized Difference Vegetati0n Index （NDVI） datasets and mete0r0l0gical rec0rds t0 determine spati0temp0ral variability in vegetati0n c0ver and climatic fact0rs （i.e. temperature and precipitati0n）. Our results sh0wed that temperatures and precipitati0n have increased in this regi0n during 0ur study peri0d. In additi0n, we f0und that gr0wing seas0n mean NDVI was mainly distributed in the vertical z0ne fr0m 2,700 m t0 3,600 m in elevati0n. In the study regi0n, we 0bserved significant p0sitive and negative trends in vegetati0n c0ver in 26.71% and 2.27% 0f the vegetated areas. C0rrelati0n analyses indicated that rising precipitati0n fr0m May t0 August was resp0nsible f0r increased vegetati0n c0ver in areas with p0sitive trends in gr0wing seas0n mean NDVI. H0wever, there was n0 similar significant c0rrelati0n between gr0wing seas0n mean NDVI and precipitati0n in regi0ns where vegetati0n c0ver declined thr0ugh0ut 0ur study peri0d. Using spatial statistics, we f0und that veeetati0n c0ver freauentlvdeclined in areas within the 2,500-3,100 m vertical z0ne, where it has steep sl0pe, and is 0n the sunny side 0f m0untains. Here, the p0sitive influences 0f increasing precipitati0n c0uld n0t 0ffset the drier c0nditi0ns that 0ccurred thr0ugh warming trends. In c0ntrast, in higher elevati0n z0nes （3,900-4,500 m） 0n the shaded side 0f the m0untains, rising temperatures and increasing precipitati0n impr0ved c0nditi0ns f0r vegetati0n gr0wth. Increased precipitati0n als0 facilitated vegetati0n gr0wth in areas experiencing warming trends at l0wer elevati0ns （2,000-2,400 m） and 0n l0wer sl0pes where water was m0re easily c0nserved. We suggest that spatial differences in variati0n in vegetati0n as the result 0f climate change depend 0n l0cal m0isture and thermal c0nditi0ns, which are mainly c0ntr0lled by t0p0graphy （e.g. elevati0n, aspect, and sl0pe）, and 0ther fact0rs, such as l0cal hydr0l0gy.     

宁夏植被覆盖动态变化及与气候因子的关系

利用1999-2009年的SPOT-VGT NDVI数据,计算出宁夏近11 a来的植被覆盖度,对其变化特征进行了研究,结合同期气象观测资料,从空间上分析了植被覆盖度与区域气候因子之间的关系。结果表明,南部六盘山区和北部引黄灌区植被覆盖度高,而中部干旱带等地区的植被覆盖度较低,但中部干旱带却有较高的绝对变化率;从时间变化来看,近11 a来宁夏大部分地区的植被覆盖度在逐年增加。植被覆盖度的变化与气候因子有关,除引黄灌区和六盘山林区外,中部干旱带等地的植被覆盖度与降水呈正相关,区域气候的干湿波动,影响了植被覆盖度的高低;在有灌溉保障条件的农业垦殖区,植被覆盖度还与气温呈正相关,即有效积温的增加,会促进农作物生长,从而导致区域植被的覆盖度提高。     

Vegetation greenness modeling in response to climate change for Northeast Thailand

In Northeast Thailand, the climate change has resulted in erratic rainfall and tem- perature patterns. The region has experienced both periods of drought and seasonal floods with the increasing severity. This study investigated the seasonal variation of vegetation greenness based on the Normalized Difference Vegetation Index （NDVI） in major land cover types in the region. An assessment of the relationship between climate patterns and vegeta- tion conditions observed from NDVI was made. NDVI data were collected from year 2001 to 2009 using multi-temporal Terra MODIS Vegetation Indices Product （MOD13Q1）. NDVI pro- files were developed to measure vegetation dynamics and variation according to land cover types. Meteorological information, i.e. rainfall and temperature, for a 30 year time span from 1980 to 2009 was analyzed for their patterns. Furthermore, the data taken from the period of 2001-2009, were digitally encoded into GIS database and the spatial patterns of monthly rainfall and temperature maps were generated based on kriging technique. The results showed a decreasing trend in NDVI values for both deciduous and evergreen forests. The highest productivity and biomass were observed in dry evergreen forests and the lowest in paddy fields. Temperature was found to be increasing slightly from 1980 to 2009 while no significant trends in rainfall amounts were observed. In dry evergreen forest, NDVI was not correlated with rainfall but was significant negatively correlated with temperature. These re- sults indicated that the overall productivity in dry evergreen forest was affected by increasing temperatures. A vegetation greenness model was developed from correlations between NDVI and meteorological data using linear regression. The model could be used to observe the change in vegetation greenness and dynamics affected by temperature and rainfall.     

基于MODIS/NDVI的新疆伊犁河谷植被变化

利用2000-2010年16 d合成的MODIS/[NDVI]数据,结合植被异常指数、趋势线分析和Hurst指数等分析方法,对新疆伊犁河谷植被覆盖的时空变化特征进行了分析。结果表明：（1） 伊犁河谷内植被覆盖随海拔增高而先增加后减小,最高植被覆盖区位于2 000～2 500 m的高程带;2000-2010年伊犁河谷各高程带内植被覆盖整体下降趋势明显,但海拔低于1 000 m的高程带除外。（2）受干湿环境影响,伊犁河谷全区平均被植异常指数最高值出现在降水最多的2002年,最低值出现在降水最少的2008年,但不同区域植被异常指数的变化存在较大差异。（3）伊犁河谷内植被覆盖增加和减小的区域分别占总面积的4.09%和19.34%,增加区域主要位于伊犁河两岸的平原区,减小区域主要位于乌孙山两端以及伊犁河谷周围海拔2 000 m左右的低山区域;变标度极差分析结果表明,伊犁河谷内植被覆盖年际变化呈现很强的持续性,未来一定时间内将保持现有变化趋势不变。     

Spatial and temporal variations of vegetation in Qinghai Province based on satellite data

This paper used five years (2001-2006) time series of MODIS NDVI images with a 1-km spatial resolution to produce a land cover map of Qinghai Province in China. A classi-fication approach for different land cover types with special emphasis on vegetation, espe-cially on sparse vegetation, was developed which synthesized Decision Tree Classification, Supervised Classification and Unsupervised Classification. The spatial distribution and dy-namic change of vegetation cover in Qinghai from 2001 to 2006 were analyzed based on the land cover classification map and five grade elevation belts derived from Qinghai DEM. The result shows that vegetation cover in Qinghai in recent five years has been some improved and the area of vegetation was increased from 370,047 km2 in 2001 to 374,576 km2 in 2006. Meanwhile, vegetation cover ratio was increased by 0.63%. Vegetation cover ratio in high mountain belt is the largest (67.92%) among the five grade elevation belts in Qinghai Prov-ince. The second largest vegetation cover ratio is in middle mountain belt (61.80%). Next, in the order of the decreasing vegetation cover ratio, the remaining grades are extreme high mountain belt (38.98%), low mountain belt (25.55%) and flat region belt (15.46%). The area of middle density grassland in high mountain belt is the biggest (94,003 km2), and vegetation cover ratio of dense grassland in middle mountain belt is the highest (32.62%), and the in-creased area of dense grassland in high mountain belt is the greatest (1280 km2). In recent five years the conversion from sparse grass to middle density grass in high mountain belt has been the largest vegetation cover variation and the converted area is 15931 km2.     

城市植被覆盖变化可预测性及其空间格局的定量递归分析——以深圳市为例

由于人口的快速增加和经济要素的大量聚集,城市是下垫面性质改变最为显著的区域。本文应用定量递归分析技术对1999~2006年逐旬的1km SPOT-VEGETATION NDVI数据进行分析,以期揭示NDVI时间系列的非线性动态特征及其空间格局。研究结果表明,深圳市的NDVI时间系列的RQA特征值居于随机系列和确定性系列之间,属于含有随机成分的确定性系列。不同覆被类型下NDVI系列的特性不同,林地区的NDVI系列规则性最高,农地区次之,建设用地区最差,表明人类活动作为一种噪声对于NDVI系列性质的扰动。用二阶Rényi熵作为NDVI系列的可预测性指标,其空间格局表现为海拔高、坡度大、林地分布集中的西北和东南部可预测性高,而海拔相对低、建设用地相对集中的中南部地区可预测性低。     

人类活动和气候变化对红碱淖植被覆盖变化的影响

利用GIMMS NDVI、SPOT VGT两种归一化植被指数(NDVI)数据和气候资料对红碱淖地区植被覆盖变化、气候变化进行了研究, 从气候变化和人类活动的角度分析了植被覆盖变化的原因。结果表明,1957—2007年期间红碱淖地区温度上升趋势显著,降水经历了由少许的增加转向减少的过程,进入了一个相对干旱气候态。1982—2007年期间红碱淖地区植被覆盖变化趋势是在波动中逐渐增加,大致经历了4个阶段：①1982—1988年植被覆盖持续增加;②1989—1998年小幅波动,相对稳定;③1999年植被覆盖迅速下降,1999—2001年维持较低值;④2002年快速增加到较高水平,2007年达最大值。气候变暖使春季生长季节提前、秋季生长期延长。春季的降水量对春季的植被覆盖影响明显,春夏之交降水量对NDVI的影响存在一个月的滞后现象。生长季的降水量变化趋势与植被覆盖的变化趋势相一致。夏季温度上升加速了地表蒸散发过程,同时降水具有减少的趋势,干旱对植被生长有抑制作用,夏季的植被覆盖却在显著增加。     

Vegetation change of ecotone in west of Northeast China plain using time-series remote sensing data

Multi-temporal series of satellite SPOT-VEGETATION normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) data from 1998 to 2007 were used for analyzing vegetation change of the ecotone in the west of the Northeast China Plain. The yearly and monthly maximal values,anomalies and change rates of NDVI and NDWI were calculated to reveal the interannual and seasonal changes in vegetation cover and vegetation water content. Linear regression method was adopted to characterize the trends in vegetation change. The yearly maximal NDVI decreased from 0.41 in 1998 to 0.37 in 2007,implying the decreasing trend of vegetation activity. There was a significant decrease of maximal NDVI in spring and summer over the study period,while an increase trend was observed in autumn. The vegetation-improved regions and vegetation-degraded regions occupied 17.03% and 20.30% of the study area,respectively. The maximal NDWI over growing season dropped by 0.027 in 1998–2007,and about 15.15% of the study area showed a decreasing trend of water content. Vegetation water stress in autumn was better than that in spring. Vegetation cover and water content variations were sensitive to annual precipitation,autumn precipitation and summer temperature. The vegetation degradation trend in this ecotone might be induced by the warm-drying climate especially continuous spring and summer drought in the recent ten years.