Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems

The objective of this paper is to review research conducted over the past decade on the application of multi-temporal remote sensing for monitoring changes of Arctic tundra lands. Emphasis is placed on results from the National Science Foundation Land-Air-Ice Interactions (LAII) program and on optical remote sensing techniques. Case studies demonstrate that ground-level sensors on stationary or moving track platforms and wide-swath imaging sensors on polar orbiting satellites are particularly useful for capturing optical remote sensing data at sufficient frequency to study tundra vegetation dynamics and changes for the cloud prone Arctic. Less frequent imaging with high spatial resolution instruments on aircraft and lower orbiting satellites enable more detailed analyses of land cover change and calibration/validation of coarser resolution observations.The strongest signals of ecosystem change detected thus far appear to correspond to expansion of tundra shrubs and changes in the amount and extent of thaw lakes and ponds. Changes in shrub cover and extent have been documented by modern repeat imaging that matches archived historical aerial photography. NOAA Advanced Very High Resolution Radiometer (AVHRR) time series provide a 20-year record for determining changes in greenness that relates to photosynthetic activity, net primary production, and growing season length. The strong contrast between land materials and surface waters enables changes in lake and pond extent to be readily measured and monitored.     

Green leaf phenology at Landsat resolution: Scaling from the field to the satellite

Despite the large number of in situ, plot-level phenological measurements and satellite-derived phenological studies, there has been little success to date in merging these records temporally or spatially. In this research, we bridge this scale gap through higher resolution satellite records (Landsat) and quantify the accuracy of satellite-derived metrics with direct field measurements. We compiled fifty-seven Landsat scenes from southern New England (P12 R51) from 1984 to 2002. Green vegetation areal abundance for each scene was derived from spectral mixture analysis and a single set of endmembers. The leaf area signal was fit with a logistic-growth simulating sigmoid curve to derive phenological markers (half-maximum leaf-onset and offset). Spring leaf-onset dates in homogenous stands of deciduous forests displayed significant and persistent local variability. The local variability was validated with multiple springtime ground observations (r² = 0.91). The highest degree of verified small-scale variation occurred where contiguous forests displayed leaf-onset gradients of 10-14 days over short distances (< 500 m). These dramatic gradients occur in of low-relief (< 40 m) upland regions. The patterns suggest that microclimates resulting from springtime cold-air drainage may be influential in governing the start of leaf growth; every 4.16 m loss in elevation delayed spring leaf onset by 1 day. These microclimates may be of crucial importance in interpreting in situ records and interpolating phenology from satellite data. Regional patterns from the Landsat analyses suggest topographic, coastal, and land-use controls on phenology. Our results indicate that deciduous forests in the Providence, RI metropolitan area leaf out 5-7 days earlier than comparable rural areas. The platform-independent curve-fit methodology may be extended across platforms and field data. The methodologically consistent approach, in tandem with Landsat data, allows an effective scaling from plot to satellite phenological observations.     

不同树种组的热带森林植被生物量与遥感地学数据之间的相关性分析

以我国云南省西双版纳的热带森林为例,分别对栎类林、其它阔叶林、其它硬阔叶林的生物量与其对应的Landsat TM数据及其派生数据、气象数据和地形数据进行了相关性分析。首先,利用森林资源连续清查的林业固定样地数据,通过各树种组的各器官生物量估算模型计算出各样地的森林植被的生物量。然后,根据样地的坐标来建立样地GIS数据库。其次,将同期的遥感影像、气象数据和地形数据与GIS数据进行配准,并从遥感影像中产生出一系列的派生数据。最后,在此基础上,分别对栎类林、其它阔叶林、其它硬阔叶林的样地生物量与其遥感数据和派生数据、气象数据和地形数据进行相关性分析。研究表明,栎类林的生物量与TM1、TM2、TM3、TM4、TM5、TM7、缨帽变换的亮度、绿度、湿度、VI3、DVI、PC1和PVI在0.05的水平上显著,而与其它因子在这个水平上相关都不够显著。其它阔叶林的生物量与降雨量在0.05的水平上显著,而与其它因子在这个水平上相关都不够显著。其它硬阔叶林的生物量与降雨量在0.05的水平上显著,而与其它因子在这个水平上,其相关都不够显著。     

杭州市三江汇地区森林植被固碳抵消能源 排放能力评估及情景预测研究

森林植被固碳服务是生态系统服务评估的重要内容之一,在区域碳中和发挥着重要的碳汇作用。以生物量法和CASA模型法相结合,评估杭州市三江汇地区森林植被固碳能力;采用CEADs县级碳排放清单估算三江汇地区的能源碳排放量;综合碳汇和碳排评估该地区森林植被固碳对能源碳排放量的抵消率。从碳减排和增汇2个方面,对森林植被抵消能源碳排放的能力进行未来情景预测。研究结果表明：1)2017年三江汇地区森林植被固碳量为4.98×10⁴t,能源碳排放量为2.07×10⁶t,森林植被能源碳排放的抵消率为2.41%,三江汇森林植被能源碳抵消率呈现出“东低西高、北低南高”的空间格局;2)研究设置9个情景对2030年森林植被碳抵消率进行定量预测,预测结果显示研究区森林植被面积增加有利于提升森林植被对能源碳排放量的抵消能力,森林面积每增加5%,森林植被对能源碳排放量抵消率可提高0.12%～0.29%;减少人均能源碳排放对提高森林植被碳抵消能力的效果更为显著,人均能源碳排由2.77t/人降低为0.90和0.72t/人,森林植被碳抵消率可分别提高2.21%～2.43%和3.36%...     

中铝广西分公司赤泥堆场植被护坡试验研究

针对赤泥坡面碱性高、坡度大、植被难度高的特点,试验研究了适合堆场条件的植被护坡工艺技术,试验选择了耐碱、速生的草本植物,实现边坡植被覆盖度80％以上,形成了赤泥筑坝与生态护坡基本同步进行的赤泥坝体安全管理和生态恢复模式。植物护坡有效地控制了坡面水土流失,迅速营造了坝坡景观,改善了坝区生态环境。     

目标红外涂料隐身技术评判标准研究

隐身涂料在红外隐身技术的研究中占据重要位置.从涂料的隐身机理出发,以目标与背景的辐射对比度小于0.02作为红外隐身的评判标准,提出了一种关于涂料红外隐身技术的新的研究方向,并结合红外探测系统作用距离检验了这个评价标准.研究发现,考虑目标红外隐身时,不能盲目降低目标表面发射率.当辐射对比度减小到0.02时,作用距离比原先降低了71.4%.     

基于GIS数据的植被实时虚拟可视化

针对大范围场景的植被实时虚拟可视化问题,提出一种在程序运行过程中实时生成各个体植被分布数据和属性数据的方法。该方法使用WangTiles和植被覆盖的地理信息系统数据。采用几何细节层次模型和基于纹理图像的方法对植被进行实时绘制。实验结果表明,该方法能在包含植被的大范围场景中取得较好的可视化效果,在场景漫游时可以保持交互的帧速率。     

Impacts of Vegetation on the Intraseasonal Oscillation Simulated by the Community Atmosphere Model (CAM3)

The influences of vegetation on intraseasonal oscillation (ISO) were examined using the Community Atmosphere Model version 3 (CAM3). Two 15-year numerical experiments were completed: the first was performed with a realistic vegetation distribution (VEG run),and the second was identical to the VEG run except without land vegetation (NOVEG run). Generally speaking, CAM3 was able to reproduce the spatial distribution of the ISO, but the ISO intensity in the simulation was much weaker than that observed in nature: the ISO has a relatively much stronger signal. A comparison of the VEG run with the NOVEG run revealed that the presence of vegetation usually produces a weak ISO. The vegetation effects on ISO intensity were significant over West Africa and South Asia, especially in the summer half-year.Vegetation also plays an important role in modulating ISO propagation. The eastward propagation of the ISO in the VEG run was clearer than that in the NOVEG run over the West African and Maritime Continent regions. The northward propagation of the ISO in the VEG run was more consistent with observation than that in the NOVEG run.     

城市异质植被的覆盖度估算模型比较研究

植被覆盖度是城市生态环境评价的一个重要指标。针对亚热带城市异质植被覆盖特征,选择像元尺度的植被指数(NDVI)转换模型、亚像元尺度的植被—土壤两端元模型(V-S Model)和植被—高—低反射率三端元模型(V-H-L Model)在TM影像上估算植被覆盖度,并结合野外实地调查对比验证3种模型的估算精度及其适用性。结果表明模型尺度和背景亮度对植被覆盖度估算有着不同程度的影响。NDVI转换模型整体高估覆盖度为27%,V-S模型和V-H-L模型整体低估覆盖度分别为23%和5%;验证结果证明:NDVI转换模型对高密度(60%)植被的估算结果最好,低估4%;V-H-L模型对中密度(40%~60%)和低密度(40%)植被的估算结果最优,仅低估2%,并受背景亮度的影响最小。因此,NDVI转换模型适用于高密度植被覆盖度的估算,亚像元尺度下的V-S模型和V-H-L模型适用于低、中密度植被覆盖度的估算,并以V-H-L模型估算较为准确。     

基于GDAL的遥感图像变化检测技术

由于GDAL（Geospatial Data Abstraction Library）具有快速读取多种格式的遥感图像且能有效解析空间元数据等特点,利用它开发遥感图像处理算法具有明显的优势。结合GDAL及相应算法,开发了一套复杂地形山区植被遥感变化检测的技术,其中包括利用阴影消除植被指数（Shadow Elimination Vegetation Index,SEVI）反演植被长势;利用图像差值法及最大类间方差法（OTSU）来提取植被长势明显变化点位;利用[K]均值聚类自动分割识别变化区域。将该方法用于武夷山自然保护区和闽江源自然保护区2016-2017年Landsat8 OLI遥感图像的植被长势变化检测,结果表明,这套遥感图像变化检测技术切实可行,能够有效识别遥感图像变化区域,并在复杂地形山区的植被长势监测中具有良好的应用价值。