2001-2015年中国植被覆盖人为影响的时空格局

基于MODIS-NDVI和气温、降水数据,使用基于变异系数的人为影响模型定量计算了2001-2015年中国植被覆盖人为影响,辅以趋势分析、Hurst指数等方法探讨了中国植被覆盖人为影响的时空变化特征及未来演变趋势。研究发现：① 2001-2015年,中国植被覆盖人为影响由南向北空间分异愈发明显,年均值为-0.0102,植被覆盖在人类活动影响下轻微减少,负影响面积占51.59%,略大于正影响面积。② 中国植被覆盖人为影响年际变化特征明显,整体呈负影响波动减少趋势,降速为0.5%/10a,其中正影响、负影响均呈增大趋势,正影响增速（0.3%/10a）远大于负影响（0.02%/10a）。③ 2001-2015年间,中国植被覆盖人为正影响重心向东北方向移动,负影响重心向西南方向移动,东北部植被覆盖在人为影响下不断改善,西南部人类活动对植被破坏程度不断增大。④ 中国植被覆盖人为影响主要呈负影响减少和正影响增大趋势,面积占比分别为28.14%和25.21%,生态环境趋于改善。⑤ Hurst指数分析表明,中国植被覆盖人为影响未来演变趋势的反向特征强于正向特征,主要呈人为负影响先减少后增大趋势,面积占比15.59%。     

基于旅游开发影响的五台山植被景观特征分析

以往旅游对植被影响的评价成果较多,但是旅游影响下植被景观与地理因子之间的关系报道较少。本文利用多种数量生态学方法探讨了五台山旅游开发与植被景观之间的生态关系。结果表明：① 旅游开发影响下五台山植被景观可分为单优乔木区、草本区、差级乔草区、中级乔草区、中级灌草区、良级灌草区、良级乔灌草区、优级乔灌草区、以及寺庙区、商业区或居民区9种类型。② 在除趋势对应分析中,第一轴与所有因子的相关性都较大,第二轴与旅游干扰度和海拔呈显著的负相关性。各植被景观类型的空间分布在一定程度上取决于关键性指标的空间格局。③ 除趋势典范对应分析方法能够大大提高植被景观特征与地理因子间的相关性,并将其直观地表达于排序图中。在植被景观特征与地理因子的关系上,第一轴上的相关系数是0.858_DCCA>0.828_DCA,第二轴上的相关系数是0.583_DCCA>0.501_DCA,这说明除趋势典范对应分析方法更优。     

Spatial associations between NDVI and environmental factors in the Heihe River Basin

Journal of Geographical Sciences - The Heihe River Basin is located in the arid and semi-arid regions of Northwest China. Here, the terrestrial ecosystem is vulnerable, making it necessary to...     

Greenness Index from Phenocams Performs Well in Linking Climatic Factors and Monitoring Grass Phenology in a Temperate Prairie Ecosystem

Near-surface remote sensing (e.g., digital cameras) has played an important role in capturing plant phenological metrics at either a focal or landscape scale. Exploring the relationship of the digital image-based greenness index (e.g., Gcc, green chromatic coordinate) with that derived from satellites is critical for land surface process research. Moreover, our understanding of how well Gcc time series associate with environmental variables at field stations in North American prairies remains limited. This paper investigated the response of grass Gcc to daily environmental factors in 2018, such as soil moisture (temperature), air temperature, and solar radiation. Thereafter, using a derivative-based phenology extraction method, we evaluated the correspondence between key phenological events (mainly including start, end and length of growing season, and date with maximum greenness value) derived from Gcc, MODIS and VIIRS NDVI (EVI) for the period 2015-2018. The results showed that daily Gcc was in good agreement with ground-level environmental variables. Additionally, multivariate regression analysis identified that the grass growth in the study area was mainly affected by soil temperature and solar radiation, but not by air temperature. High frequency Gcc time series can respond immediately to precipitation events. In the same year, the phenological metrics retrieved from digital cameras and multiple satellites are similar, with spring phenology having a larger relative difference. There are distinct divergences between changing rates in the greenup and senescence stages. Gcc also shows a close relationship with growing degree days (GDD) derived from air temperature. This study evaluated the performance of a digital camera for monitoring vegetation phenological metrics and related climatic factors. This research will enable multiscale modeling of plant phenology and grassland resource management of temperate prairie ecosystems.     

Analysis of Spatio-temporal Land Surface Temperature and Normalized Difference Vegetation Index Changes in the Andassa Watershed,Blue Nile Basin,Ethiopia

Analysis of the nexus between vegetation dynamics and climatic parameters like surface temperature is essential in environmental and ecological studies and for monitoring of the natural resources. This study explored the spatio-temporal distribution of land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) and the relationship between them in the Andassa watershed from 1986 to 2016 periods using Landsat data. Monthly average air temperature data of three meteorological sites were used for validating the results. The findings of the study showed that the LST of the Andassa watershed has increased during the study periods. Overall, average LST has been rising with an increasing rate of 0.081°C per year. Other results of this study also showed that there has been a dynamic change in vegetation cover of the watershed in all seasons. There was also a negative correlation between LST and NDVI in all the studied years. From this study we can understand that there has been degradation of vegetation and intensification of LST from 1986 to 2016.     

波浪溢流作用下海堤内坡高性能加筋草皮护坡防侵蚀特征研究

基于1∶1的大型水槽试验结果,分析了波浪溢流过程中位于海堤内坡的高性能加筋草皮护面的侵蚀特征。试验观察表明试验期间有一定土壤的损失,但护坡无明显的破坏;土面高度测量表明,当土壤流失发展到一定深度后,如果水动力强度变化不大,侵蚀趋于逐渐停止,这种现象称为侵蚀上限;结合试验现象对侵蚀上限进行了初步解释,并讨论了侵蚀上限达到前的侵蚀速率特征;植株密度监测表明,试验期间的草茎密度基本不变,草叶密度在开始几次试验期间持续减小,而后达到一个稳定值,这对于海堤的可持续防护有重要意义。研究成果能够为波浪溢流期间海堤内坡防御的相关研究和工程措施提供参考依据。     

博尔塔拉蒙古自治州植被覆盖度估算

针对传统植被覆盖度估算方法只能估算高密度覆盖的绿色光合植被的问题,该文提出了一种可进行绿色光合植被、非绿色光合植被和裸地覆盖度估算的方法,选取博尔塔拉蒙古自治州2010年和2016年的LandsatTM/OLI影像,通过构建NDVI-DFI特征空间提取端元特征值,运用像元三分模型估算,并与像元二分模型估算结果和实地采样估算结果对比。结果表明:像元三分模型估算与实际情况相符,且精度较好。2016年博州地区植被覆盖度较2010年增长显著,生态环境得到明显改善。像元三分模型能够较好地估算光合/非光合植被覆盖度,提高遥感获取植被信息的能力,为科学评估生态环境质量提供参考。     

基于Landsat遥感数据武汉地区植被覆盖度动态变化监测分析

旨在研究受人类经济活动影响的植被资源及其动态变化趋势的程度,采用基于归一化植被指数的像素二分模型,利用2002—2010年(武汉市每年8月)的卫星遥感数据,对武汉地区6年间的植被覆盖变化进行监测分析。结果表明,植被覆盖度变化与武汉GDP增长率有着紧密联系:2002—2007年,武汉经济较缓慢上升,植被覆盖度基本维持在55%左右;而2007—2008年武汉GDP总值增长率高达26.06%,但随之而来的是植被覆盖度由高峰期的61.68%下降到49.18%,是历年来的最低水准; 2008—2010年经济发展放缓,植被指数有小幅度回升。人类经济活动是影响植被资源的重要因素。     

利用Sentinel-2A多光谱成像仪与Landsat8陆地成像仪影像进行普陀山岛植被分类效果比较

卫星遥感技术可用于海岛资源调查。Sentinel-2A与Landsat 8两颗卫星都可免费提供空间分辨率较高的多光谱遥感影像,在海岛调查中的应用潜力较大。本文以浙江舟山普陀山岛为例开展了针对这两种影像在海岛植被分类中的应用效果的研究,分别利用Sentinel-2A多光谱成像仪（MSI）和Landsat 8陆地成像仪（OLI）影像基于最大似然法分类获得了该岛阔叶林、针阔混交林、针叶林、灌丛、草丛等植被及其他地物的分布情况,并进行了精度检验,结果表明MSI的总体分类精度略高于OLI。     

GF-2支持下的干旱区稀疏植被区植被覆盖度估算

现有像元二分模型MODIS植被覆盖度模型因其形式简单、适用性较强的特点被广泛应用于区域植被覆盖度（FVC）的估算。然而,研究表明在沙漠和低植被覆盖的西部干旱区,从250 m的影像上很难精准地获取NDVI_veg（全植被覆盖植被指数）和NDVI_soil（全裸土区植被指数）参数。利用常用的直方图累计法获取模型所需参数NDVI_veg和NDVI_soil,估算结果存在普遍高估现象。为此,本文首先引入同期获取的GF-2号卫星数据,从GF-2号影像上提取植被覆盖像元;然后,利用Pixel Aggregate方法重采样至250 m分辨率,获取250 m空间分辨率下纯植被和纯裸土像元;最后,将纯植被和纯裸土像元各自空间位置相对应的MODIS NDVI数据最大值作为模型所需NDVI_veg和NDVI_soil参数,实现研究区内植被覆盖度的估算。试验通过与线性回归法、多项式回归法和直方图累计像元二分模型法估算结果进行精度对比,结果表明：利用GF-2影像辅助的像元二分模型,精准地获取了低植被覆盖区NDVI_veg和NDVI_soil模型参数,提高了干旱区植被覆盖度的估算精度,并有效地抑制了受稀疏植被影响NDVI在干旱区普遍偏高问题导致的FVC高估的现象。