塔城地区西北部低山草甸植被指数变化及其驱动力

以新疆塔城地区西北部低山草甸植被为研究对象,利用2001—2020年归一化植被指数（NDVI）、气象数据（年均气温和降水量）及社会经济发展数据（年末牲畜存栏数、肉类总产量和农牧民人均纯收入）,运用ArcGIS 10.5软件、R语言和matlab等语言,运用相关分析法和趋势分析法,研究了不同时段低山草甸植被NDVI、气象因子和社会经济发展数据的时空变化特征,从气候变化和人类活动角度探讨了影响低山草甸植被NDVI变化的驱动力,揭示了以往采取的草地恢复措施的有效性和时效性。结果表明：2001—2008年低山草甸植被处于“绿化”状态,“绿化”现象主要分布在研究区的西南、南部和东部,但存在“褐化”趋势,NDVI的降幅在夏季最大;2009—2020年处于“褐化”状态,“褐化”现象分布在除了研究区西南部的其他区域,但存在微弱的“绿化”趋势,NDVI的增幅在夏季最大;2001—2020年生长季总体呈“暖干”趋势,但2009年以来“暖干”趋势有所减缓,低山草甸的南部经历了一个降水减少的暖化过程,而西北和东北部则表现出降水增加的冷却过程;过去20年年末牲畜存栏数和肉类总产量都呈现先急速增加后平缓增加而又急...     

Ecological Sensitivity Assessment of the Southeastern Qinghai-Tibet Plateau using GIS and AHP—A Case Study of the Nyingchi Region

This paper took the Nyingchi area in southeastern Tibet Autonomous Region of China as the research area, and selected five indicators of elevation, slope, slope direction, normalized difference vegetation index (NDVI) and water body as the evaluation system based on the current situation of domestic and foreign research and field investigation. The indicators were analyzed by the AHP method for weighting, and then an ArcGIS overlay analysis was applied. The results show that the ecological sensitivity of the Nyingchi region is generally increasing from the south of Nyingchi to the north of Nyingchi. The northern, western and southwestern parts of Nyingchi are extremely sensitive or highly sensitive, while the southern part is mostly insensitive or mildly sensitive ecologically. The proportions of areas for each sensitivity level are: not sensitive 54.81%, light sensitive 11.97%, moderately sensitive 10.34%, highly sensitive 8.65%, and extremely sensitive 14.23%. The results indicate that the overall ecological sensitivity of the Nyingchi region is low and this region is performing well with respect to ecological environmental protection. This study can provide some suggestions for targeted improvements of the ecological environmental protection in the Nyingchi region and even in the Tibetan Plateau region.     

近70年珠江水沙变化特征及人类活动影响因素分析

收集1954—2019年珠江流域的3个主要水文站:高要站(西江)、石角站(北江)和博罗站(东江)的径流量与输沙量资料,运用Mann-Kendall非参数检验法和累积距平法,分析了珠江流域水沙近70年来的年际变化特征。结果表明,1954—2019年珠江年径流量变化趋势不明显,年输沙量呈下降趋势,高要站与博罗站年输沙量分别于2003年和1991年发生突变,多年平均输沙量较突变前分别减少了71.30%和48.88%,石角站未发生明显突变。2000—2019年珠江流域归一化植被指数(Normalized Difference Vegetation Index,NDVI)整体呈上升趋势,植被覆盖改善区域占流域总面积的89.27%,但NDVI与水沙变化的相关性不显著。运用双累积曲线法对不同时期人类活动对珠江输沙量的影响进行分析,20世纪80年代以来,森林砍伐、水库建设、水土保持等人类活动对输沙量造成显著影响,2000年以后龙滩水库建设是西江输沙量下降的主要原因,植被改善对于珠江流域输沙量的影响不明显。     

中国第二、三级阶梯地形过渡带山前植被物候时空变化探析

基于1982—2015年GIMMS NDVI 3g V1.0数据、3小时温度、逐日降水和日太阳辐射数据集、数字高程模型、中国植被区划数据及实测物候验证数据,利用季节性植被物候提取法、Theil-Sen median趋势分析法和偏最小二乘回归分析等方法,研究中国第二、三级阶梯地形过渡带植被物候的时空变化规律,探讨植被物候对海拔、经纬度和气候变化的响应。结果表明：① 34 a间过渡带山前植被物候时空变化显著。时间上,植被物候呈返青期（Start Of Season, SOS）提前（-0.3187 d/a, p<0.01）、枯黄期（End Of Season, EOS）推迟（0.1171 d/a, p>0.1）和生长季长度（Length Of Growing Season, LOS）延长（0.4358 d/a, p<0.01）趋势;空间上,按SOS像元的86.24%提前、EOS像元的69.66%推迟和LOS像元的84.42%延长分布。② 34 a间过渡带山前植被物候地带性特征明显。垂直地带性方面,在中低纬度地区的物候始末期受以400 m等高线为界的海拔梯度影响,由平原到山地产生SOS平均提前8d,EOS提前25~36 d的分段式变化;水平地带性方面,低纬度和中高纬度地区的植被物候以35°N（秦岭-淮河一线,中国南北方的分界线）、43.5°N（暖温带落叶阔叶林区与温带草原区的分界）为转折点,由南向北SOS以-0.78 d/°、4.89 d/°和-1.56 d/°分段变化,EOS以-3.96 d/°、-1.85 d/°和0.89 d/°分段变化。③ 34 a间过渡带植被物候受气象因素驱动。对于植被返青期,气温对中纬度地区SOS的影响最大,降水的贡献随着纬度的降低而增大,太阳辐射在中纬度地区的贡献力大于低纬度地区;对于植被枯黄期,中纬度地区对EOS的多因素贡献力为太阳辐射>气温>降水（太阳辐射对草原区无贡献力）,低纬度地区贡献力排序与之相反;本研究对宏观地理带中不同植被区划的物候变化认知有学术意义,也为地理因素与气候因素共同影响的植被物候变化提供了新的认识。     

Explaining NDVI trends in northern Burkina Faso

Many studies have shown a ‘greening of the Sahel’ on the basis of analysis of time series of satellite images and this has shown to be, at least partly, explained by changes in rainfall. In northern Burkina Faso, an area stands out as anomalous in such analysis, since it is characterized by a distinct spatial pattern and strongly dominated by negative trends in Normalized Difference Vegetation Index (NDVI). The aim of the paper is to explain this distinct pattern. When studied over the period 2000–2012, using NDVI data from the MODIS sensor the spatial pattern of NDVI trends indicates that non-climatic factors are involved. By relating NDVI trends to landscape elements and land use change we demonstrate that NDVI trends in the north-western parts of the study area are mostly related to landscape elements, while this is not the case in the south-eastern parts, where rapidly changing land use, including. expansion of irrigation, plays a major role. It is inferred that a process of increased redistribution of fine soil material, water and vegetation from plateaus and slopes to valleys, possibly related to higher grazing pressure, may provide an explanation of the observed pattern of NDVI trends. Further work will focus on testing this hypothesis.     

红树林湿地植被生物量的雷达遥感估算

根据雷达后向散射系数建立了红树林湿地植被生物量的估算模型,并运用遗传算法确定其中非线性模型的最优参数.对比分析表明,雷达后向散射系数模型比NDVI模型在植被生物量估算中有更高的精度.使用NDVI指数有可能导致某些植被类型的生物量估算出现较大的误差.这是因为一些具有密集冠层的草本植被（例如互花米草等）有比红树林高得多的NDVI值.而雷达遥感所具有的侧视特点及一定的穿透能力能有效地获取植被的垂直信息,大大减低植被生物量估算的误差.     

Spatiotemporal analysis of vegetation index after typhoons in the mountainous watershed

An extensive land cover change was triggered by a series of typhoons, especially Typhoon Morakot in 2009 in Taiwan. The normalized difference vegetation index (NDVI) series from multiple satellite images were applied to monitor the change processes of land cover. This study applied spatiotemporal analysis tools, including empirical orthogonal functions (EOF), and multiple variograms in analyzing space–time NDVI data, and detected the effects of large chronological disturbances in the characteristics of land cover changes. Spatiotemporal analysis delineated the temporal patterns and spatial variability of NDVI caused by these large typhoons. Results showed that mean of NDVI decreased but spatial variablity of NDVI increased after typhoons in the study area. The EOF can clarify the major component of NDVI variations and identify the core area of the NDVI changes. Various approaches showed consistent results that Typhoon Morakot significantly lowered the NDVI in land cover change process. Furthermore, the spatiotemporal analysis is an effective monitoring tool, which advocates the use of the index for the quantification of land cover change and resilience.     

用于时间序列聚类分析的小波变换和特征量提取方法

利用小波变换的多尺度分辨功能,对时间序列数据进行多次Haar小波变换,将时间序列分解为尺度分量和细节分量;通过保留尺度分量,提取时间序列的趋势信息,并结合统计特征量计算,将时间序列的趋势信息与几种统计特征量组合在一起,构成SOM神经网络的输入向量,对时间序列进行聚类分析。通过在几类模拟时间序列数据上进行实验分析,取得了较好的实验效果。并将此方法应用到基于MODIS遥感影像的林地植被提取中,获得了较高的提取精度。     

Spatial analysis of human-induced vegetation productivity decline over eastern Africa using a decade (2001–2011) of medium resolution MODIS time-series data

Climate variation and land transformations related to exploitative land uses are among the main drivers of vegetation productivity decline and ongoing land degradation in East Africa. We combined analysis of vegetation trends and cumulative rain use efficiency differences (CRD), calculated from 250-m MODIS NDVI time-series data, to map vegetation productivity loss over eastern Africa between 2001 and 2011. The CRD index values were furthermore used to discern areas of particular severe vegetation productivity loss over the observation period. Monthly 25-km Tropical Rainfall Measuring Mission (TRMM) data metrics were used to mask areas of rainfall declines not related to human-induced land productivity loss. To provide insights on the productivity decline, we linked the MODIS-based vegetation productivity map to land transformation processes using very high resolution (VHR) imagery in Google Earth (GE) and a Landsat-based land-cover change map. In total, 3.8 million ha experienced significant vegetation loss over the monitoring period. An overall agreement of 68% was found between the rainfall-corrected MODIS productivity decline map and all reference pixels discernable from GE and the Landsat map. The CRD index showed a good potential to discern areas with ‘severe’ vegetation productivity losses under high land-use intensities.     

三江源地区基于MODIS数据地表温度与土地覆盖定量关系研究

以三江源自然保护区为研究区,基于MODIS L1 B数据,采用劈窗算法反演地表温度,分析了地表温度空间分布的特征,与计算得到的归一化植被指数进行回归分析。结果表明地表温度与归一化植被指数存在很好的负相关性。分析讨论了地表温度的空间分布与土地覆盖及其他影响因子之间存在的定量关系,探讨了植被生产力与气候变化之间的相互作用以及发展趋势。研究结果有利于三江源湿地的生态保护,可为土地覆盖的动态监测提供有力的科学参考。