Satellite-derived vegetation index and cover type maps for estimating carbon dioxide flux for arctic tundra regions

The spatial variability and co-variability of two different types of remote sensing derivatives that portray vegetation and geomorphic patterns are analyzed in the context of estimating regional-scale CO₂ flux from land surfaces in the arctic tundra. For a study area encompassing the Kuparuk River watershed of the North Slope of Alaska, we compare satellite-derived maps of the normalized difference vegetation index (NDVI) generated at two different spatial resolutions to a map of vegetation types derived by image classification of data from the Landsat multispectral scanner (MSS). Mean values of NDVI for each cover type stratum are unique (with the exception of moist acidic tundra and shrubland types). Based on analysis of semi-variograms generated for SPOT-NDVI data, most of the vegetation cover and landform features of this arctic tundra landscape have spatial dimensions of less than 1 km. Thaw lakes on the coastal plain and glacial depositional landforms, such as moraines in the foothills, seem to be the largest features, with vegetation units having dimensions no larger than 700 m. Frequency distributions of NDVI and vegetation types extracted for sampling transects flown by an aircraft sensing CO₂ flux, relative to distributions for the entire Kuparuk River watershed, suggest a slight sampling bias towards greater cover of mesic wet sedge tundra and thaw lakes and associated lower NDVI values. The regional pattern of NDVI for the North Slope of Alaska corresponds primarily to differences between the two major physiographic provinces of this region.     

准格尔丘陵沟壑区五分地沟流域土地覆盖分析

以准格尔丘陵沟壑区五分地沟流域为研究区,应用彩红外航片和IKONOS卫星影像,绘制了1987、2002年土地覆盖/植被类型图,并数字化基于地面土地利用调查绘制的1979年土地利用图.利用景观格局指数,评价了研究区土地覆盖/植被空间格局现状及土地覆盖类型动态变化;并以ETM 数据为信息源,绘制了2002年土地覆盖/植被类型图.研究表明:2002年研究区土地覆盖/植被呈现出一个耕地、草地、人工乔木林和人工灌木林以及种植稀疏灌木的草地高度镶嵌的景观格局特征;20年内土地覆盖类型发生了显著的变化,景观异质性增强.基于研究区景观的高度破碎化,绘制小流域精细尺度土地覆盖图,高空间分辨率遥感数据十分必要.     

准格尔丘陵沟壑区五分地沟流域土地覆盖分析(英文)

以准格尔丘陵沟壑区五分地沟流域为研究区,应用彩红外航片和IKONOS卫星影像,绘制了1987、2002年土地覆盖/植被类型图,并数字化基于地面土地利用调查绘制的1979年土地利用图.利用景观格局指数,评价了研究区土地覆盖/植被空间格局现状及土地覆盖类型动态变化;并以ETM 数据为信息源,绘制了2002年土地覆盖/植被类型图.研究表明:2002年研究区土地覆盖/植被呈现出一个耕地、草地、人工乔木林和人工灌木林以及种植稀疏灌木的草地高度镶嵌的景观格局特征;20年内土地覆盖类型发生了显著的变化,景观异质性增强.基于研究区景观的高度破碎化,绘制小流域精细尺度土地覆盖图,高空间分辨率遥感数据十分必要.     

基于NDVI的新疆荒漠地区植被覆盖度遥感估算经验模型研究

新疆荒漠地区植被覆盖度遥感估算模型十分缺乏,给荒漠化监测等相关工作带来很大不便,开展植被覆盖度遥感估算经验模型研究,对于促进和完善相关地区的生态监测及研究工作具有积极的现实意义。通过对阜康市北部沙漠南缘和克拉玛依市中部平原荒漠进行无人机航拍,利用无人机遥感提取（光合）植被信息,并将无人机航拍影像的植被覆盖度统计单元与高分辨率卫星影像像元在空间上直接相对应,获取在高分辨率卫星影像像元尺度上的植被盖度,然后通过植被覆盖度和空间上与其相对应的源自高分辨率卫星影像的NDVI数据的拟合关系,建立基于源自高分二号影像的NDVI的阜康北部沙漠植被覆盖度遥感估算线性模型以及基于源自ZY1-02C影像的NDVI的克拉玛依平原荒漠植被覆盖度遥感估算二次多项式模型。研究中所采用的无人机遥感与卫星遥感相结合、植被覆盖度统计单元与卫星像元在空间上直接对应的方法,可避免以往相关工作中常以点位测量数据代表卫星像元数据所带来的不确定性。由于所用卫星影像的NDVI数据稳定性相对不足等原因,所建立的遥感估算模型的估算精度尚相对偏低,有待于今后进一步的工作加以改进。     

Analysis of snow-vegetation interactions in the low Arctic-Subarctic transition zone (northeastern Canada)

Abstract

Recent studies have shown that northern vegetation has been growing in relation to a warming climate over the last four decades, especially across the transition zone between tundra and taiga. Shrub growth affects snow properties and the surface energy budget, which must be better studied to quantify shrub-snow-climate feedbacks. The objective of this research is to improve the characterization of the impact of shrubs on snow evolution, from its accumulation to its melt, using in-situ and satellite measurements. The research is presented for the Umiujaq site, Nunavik, representative of the low Arctic–Subarctic transition zone. Snow depth, measured along numerous transects spanning different land cover types is found to increase by a factor 2.5–3 between tundra and forest, while snow density decreases. This illustrates the trapping effect of vegetation well. Complementary, continuous snow depth measurements using weather stations from two sites (tundra with low shrubs and a small clearing with shrubs within the forest) show different site-dependent behaviors. Spatial analysis from high-resolution Pleiades images combined with Landsat (Normalized Difference Snow Index) and MODIS (Fractional Snow Cover) images suggest a slight delay in melt over open and dense forest areas compared to tundra and dense high shrubs.     

Erosion-reducing cover in semi-arid shrubland

Vegetation and small features of ground cover are known to affect erosion, but the areal extent of small features is rarely studied because they are difficult to estimate for large areas. We studied the variation in components of cover, with 67 sites representing the regional variation of vegetation and topography, in northwestern México. Surface-level cover, mostly by litter and gravel, was skewed to higher values than canopy cover, and only about one third of inter-plant points had bare soil. However, litter mass was not closely related to the spatial measure of ground cover. Drip height for intercepted precipitation was always <0.5 m and most obstructions were branches, not leaves. Soil roughness increased with slope gradient, suggesting it resulted from erosion. Neither land form (elevation, exposure and slope) nor species associations were strong factors in determining cover. However, the height of the vegetation was a good predictor of surface cover, drip height and canopy cover. Applied to erosion with the RUSLE model, this ground study estimated cover was better by more than an order of magnitude compared to a remote perception index. The dynamics of cover at surface level in arid and semi-arid shrublands warrants more attention.     

Intra-annual variability of satellite observed surface albedo associated with typical land cover types in China

Surface albedo is a primary causative variable associated with the process of surface energy exchange. Numerous studies have examined diurnal variation of surface albedo at a regional scale; however, few studies have analyzed the intra-annual variations of surface albedo in concurrence with different land cover types. In this study, we amalgamated surface albedo product data (MCD43) from 2001 to 2008, land-use data (in 2000 and 2008) and land cover data (in 2000); quantitative analyses of surface albedo variation pertaining to diverse land cover types and the effect of the presence/absence of ground snow were undertaken. Results indicate that intra-annual surface albedo values exhibit flat Gaussian or triangular distributions depending upon land cover types. During snow-free periods, satellite observed surface albedo associated with the non-growing season was lower than that associated with the growing season. Satellite observed surface albedo during the presence of ground snow period was 2-4 times higher than that observed during snow-free periods. Surface albedo reference values in typical land cover types have been calculated; notably, grassland, cropland and built-up land were associated with higher surface albedo reference values than barren while ground snow was present. Irrespective of land cover types, the lowest surface albedo reference values were associated with forested areas. Proposed reference values may prove extremely useful in diverse research areas, including ecological modeling, land surface process modeling and radiation energy balance applications.     

全球及区域模式中陆面过程的地表植被覆盖分类方法

全球和区域尺度上陆面生态系统与气候密切相关。全球和区域模式的发展对于我们认识气候与陆地生态的变化起到重要作用。在这些模型中,植被覆盖是影响大气-植被间热量、水分和CO2等交换的重要陆面参数。在分析了陆地植被覆盖分类原理基础上,介绍了目前全球不同植被覆盖分类方案,包括基于地基观测的植被分布、基于生物气候特征的分类方案（如：Holdridge的方案）;特别近年来陆面过程试验表明,各种遥感数据源（如：NOAA—AVHRR,EOS—MODIS,Landsat—TM）等为我们提供了有利的工具来监测全球植被动态,完善植被分类,并且采用高时空分辨率的全球土地覆盖状况特征,在不同时空尺度揭示植被-大气相互作用。本文分析了代表性的3种基于卫星遥感技术的陆面植被分类方案,分别是BATS（18类）、SIB（9类）、SIB2（12类）和BIOME—BGC（31类）陆地模式的植被覆盖分类方案．最后分析了目前可用于全球植被覆盖分类的新的遥感数据库。     

基于遥感时序特征的地表覆被信息提取

地表覆被作为自然过程和人类活动共同作用的重要地表景观特征,对全球或局地气候、水热循环、物质传输及陆面生态系统多样性等影响深远.利用年内时序遥感影像自动提取不同地表覆被类型的方法,以新疆阜康地区为研究目标,组织2016年植被全生长季的Landsat 8 OLI地表反射时序影像,研究不同物候期植被冠层的纹理响应信息,考察研...     

黄土高原植被覆盖度变化的地形分异及土地利用/覆被变化的影响

基于16 d合成MODIS NDVI数据提取的时间序列植被覆盖度数据,采用一元线性回归趋势分析,对黄土高原2000-2008年植被覆盖度的时空变化及其地形分异、土地利用/覆被变化的影响进行了定量分析。结果表明：（1）研究时段黄土高原植被覆盖度整体呈快速上升趋势,局部下降;（2）黄土高原植被覆盖度变化存在明显的地形分异,陡坡等植被恢复、重建和保育的主要区域植被覆盖度增速显著;（3）土地利用/覆被变化对植被覆盖度的增加影响突出,土地利用/覆被类型变更区植被覆盖度增速显著高于未变化区域,退耕还林还草区增速尤其突出;（4）土地利用/覆被类型未变化区域植被覆盖度总体上也呈增加趋势,但因植被覆盖度水平相对较高,增速明显低于土地利用/覆被类型变化区。上述结果表明,黄土高原植被保育、植被恢复和重建在植被覆盖度提升方面取得了明显成效。     

Reconstructing pre-agricultural expansion vegetation cover of Ethiopia

Landscape reconstructions can be used to define a reference condition from which to assess the magnitude of land changes caused by human influence. Since the beginning of the last century, the population of Ethiopia has increased drastically with large effects on the natural vegetation and biodiversity. However, the original land cover patterns in Ethiopia have not been precisely mapped, which hinder the identification of the biophysical and socio-economic factors that contributed to the current landscape patterns. The objective of this study was to reconstruct the past century vegetation landscapes of Ethiopia (i.e. vegetation cover before agricultural expansion) and identify which ecosystems have been most affected by land changes. First, the net primary productivity (NPP) was modelled based on the climatic constraints of natural vegetation growth (water availability, solar radiation and minimum temperature) derived from remote sensing and climate data. This analysis showed that water availability is the most critical constraint for vegetation growth for all regions and land cover types in Ethiopia. Then, the past vegetation was mapped based on predicted NPP. Our results show that i) the extent of broadleaved evergreen or semi-deciduous forest, open broadleaved deciduous forest, closed to open shrubland, mosaic forest-shrubland/grassland, sparse vegetation and grassland was 18.8%, 12.4%, 20.6%, 31.5%, and 16.8%, respectively, and ii) current agricultural landscapes were previously covered mainly by broadleaved evergreen and deciduous forest, which encompassed 38.9%. The least affected by agricultural expansion were sparse vegetation and grassland. Our study provides novel insights on pre-agricultural expansion landscapes in Ethiopia with critical information for scientists and other stakeholders working on the restoration and rehabilitation of degraded areas.     

2001—2020年黄河流域植被覆盖变化及其影响因素

基于MODIS NDVI植被指数和气象数据集,以集合经验模态分解、趋势分析和随机森林回归分析等方法,分析了黄河流域2001—2020年植被覆盖时空变化特征,并对其气候驱动因素进行探讨。结果表明：（1）2001—2020年黄河流域植被覆盖整体呈显著增长趋势,增速为0.055/10a （P<0.05）,2010年之前增速（0.067/10a）大于2010年之后的增速（0.051/10a）。（2）空间上,植被覆盖增加区域主要分布在陕北黄土高原、甘肃省东南部、内蒙古自治区河套平原等退耕还林还草生态工程实施区域,而植被覆盖显著下降区域则集中在关中平原城市群、黄淮海平原以及青藏高原等区域。（3）气温、降水和CO₂浓度等对黄河流域植被生长起到正向促进作用,且绝对敏感性依次降低,而大气饱和水汽压差、太阳辐射等对植被生长起到抑制作用。本研究结果可为评估气候变化对黄河流域植被覆盖变化的综合影响提供参考依据。     

Modelling patterned ground distribution in Finnish Lapland: an integration of topographical, ground and remote sensing information

New data technologies and modelling methods have gained more attention in the field of periglacial geomorphology during the last decade. In this paper we present a new modelling approach that integrates topographical, ground and remote sensing information in predictive geomorphological mapping using generalized additive modelling (GAM) . First, we explored the roles of different environmental variable groups in determining the occurrence of non‐sorted and sorted patterned ground in a fell region of 100 km2 at the resolution of 1 ha in northern Finland. Second, we compared the predictive accuracy of ground‐topography‐ and remote‐sensing‐based models. The results indicate that non‐sorted patterned ground is more common at lower altitudes where the ground moisture and vegetation abundance is relatively high, whereas sorted patterned ground is dominant at higher altitudes with relatively high slope angle and sparse vegetation cover. All modelling results were from good to excellent in model evaluation data using the area under the curve (AUC) values, derived from receiver operating characteristic (ROC) plots. Generally, models built with remotely sensed data were better than ground‐topography‐based models and combination of all environmental variables improved the predictive ability of the models. This paper confirms the potential utility of remote sensing information for modelling patterned ground distribution in subarctic landscapes.     

植被指数-地面温度特征空间的生态学内涵及其应用

植被指数与地面温度是描述土地覆盖特征的重要参数 ,对两种数据的综合分析 ,可以衍生出更丰富、更清晰的地表信息 ,有助于更加准确、有效地认知土地覆盖 /土地利用的时空变化规律。本文探讨了植被指数与地面温度构成的二维向量空间的物理意义与生态学内涵 ,以基于 NOAA AVHRR的时间序列数据为本底 ,分析了不同土地覆盖类型在该特征空间上的时序变化规律 ,并以黄淮海地区主要农作物冬小麦为例 ,研究了植被指数-地面温度指标与干旱、半干旱地区农作物产量之间的响应关系。     

基于Landsat 8 OLI数据与面向对象分类的昆嵛山地区土地覆盖信息提取

利用2015年Landsat 8 OLI遥感影像和DEM作为分类数据源,结合野外调查数据,采用面向对象的分类方法对昆嵛山地区土地覆盖信息进行提取,并对分类结果进行精度评价与比较分析。研究表明：面向对象分类方法提取的各地类连续且边界清晰,分类效果与实际情况基本吻合。昆嵛山地区占主导地位的土地覆盖类型是针叶林,面积为1 546.81 km²。研究区土地覆盖分类的总体精度和Kappa系数分别为91.5%和0.88,其中针叶林、草地、水体和建设用地的生产者精度均达到87%以上。相对于监督分类方法,本研究提出的土地覆盖信息提取方法的总体分类精度和Kappa系数分别提高14.7%和0.17。基于面向对象的中分辨率遥感影像,能够获取较高精度的土地覆盖信息,为大范围土地覆盖分类研究提供方法参考。     

基于多时相Landsat影像的中亚地区植被覆盖遥感监测

针对中亚地区的强生态脆弱性、高敏感性特征,有必要开展广域、长期的植被覆盖监测以匹配“绿色丝绸之路”的可持续发展目标。鉴于此,联合Landsat 5和Landsat 8卫星数据集,利用Google Earth Engine（GEE）地理空间数据云计算平台,估算了中亚地区1993—2018年间共12期的植被覆盖度。结果表明：（1）中亚地区植被覆盖总体水平较低,但也具有较为显著的空间异质性。（2）中亚地区1993—2018年间多数区域植被覆盖趋势较为稳定,哈萨克斯坦丘陵、费尔干纳盆地等区域植被覆盖度呈增加趋势,乌拉尔河流域和锡尔河流域等区域植被覆盖趋势为负。（3）植被覆盖度时序特征上,中亚地区1993—2018年间总体植被覆盖度累积增加3%,其中吉尔吉斯斯坦和塔吉克斯坦植被覆盖分别增加3.96%和5.86%。（4）裸土区呈退缩趋势,面积总计减少25.9×10⁴ km²,低植被覆盖区、中植被覆盖区和高植被覆盖区范围在呈现出的振荡式增加。研究结合遥感大数据和地理云计算对中亚地区进行区域尺度的植被覆盖动态监测,能对中亚地区生态评估和演替分析提供技术支持和定量数据。     

Land cover in Norway based on an area frame survey of vegetation types

The Norwegian area frame survey of land cover and outfield land resources (AR18X18), completed in 2014, provided unbiased statistics of land cover in Norway. The article reports the new statistics, discusses implications of the data set, and provides potential value in terms of research, management, and monitoring. A gridded sampling design for 1081 primary statistical units of 0.9 km² at 18?km intervals was implemented in the survey. The plots were mapped in situ, aided by aerial photos, and all areas were coded following a vegetation type system. The results provide new insights into the cover and distribution of vegetation and land cover types. The statistic for mire and wetlands, which previously covered 5.8%, has since been corrected to 8.9%. The survey results can be used for environmental and agricultural management, and the data can be stratified for regional analyses. The survey data can also serve as training data for remote sensing and distribution modelling. Finally, the survey data can be used to calibrate vegetation perturbations in climate change research that focuses on atmospheric–vegetation feedback. The survey documented novel land cover statistics and revealed that the national cover of wetlands had previously been underestimated.     

Impacts of land use and climate change on regional net primary productivity

Combined with recent historical climate data and two periods of land use data sets from remote sensing data, we test the net primary productivity (NPP) data sets in North China modelled by the satellite data-driven Global Production Efficiency Model (GLO-PEM) for detecting the widespread spatial and temporal characteristics of the impacts of climate and land use change on the regional NPP. Our results show that over the past 20 years, the mean annual temperature in the study region has remarkably increased by more than 0.064 oC, but over the same period, there has been a 1.49 mm decrease in annual precipitation and decrease in NPP by an annual rate of 6.9 TgC. The NPP changes in the study region were greatly affected by the average temperature and precipitation by ten-day periods as well as the seasonal temperature and precipitation in the study region. The correlation between seasonal NPP and seasonal precipitation and temperature is highly consistent with land cover spatially, and the correlation coefficient changes with the changes of vegetation types. The analysis reveals that the related areas in land use change only take up 5.45% of the whole studied region, so the climate changes dominate the impacts on the NPP in the whole study region (90% of the total). However, land use plays an absolute dominative role in areas with land cover changes, accounting for 97% of the total. From 1981 to 2000, the NPP in the whole study region remarkably reduced due to obvious precipitation decrease and temperature rise. Between two periods of land use (about 10 years), the changes in climate are predicted to promote a decrease in NPP by 78 (±0.6) TgC, and integrated impacts of climate changes and land use to promote a decrease in NPP by 87(±0.8) TgC.     

基于MODIS NDVI的新疆土地覆盖类型划分与潜在荒漠化区域探测

采用2002年MODIS 1km的全年NDVI时序数据对新疆及周边地区进行了土地覆盖分类,在分类的过程中重点强调了稀疏植被覆盖区域,这些区域具有潜在荒漠化的趋势。介绍了一种针对不同土地覆盖类型并能重点突出稀疏植被的分类方法,这种方法较好地综合了季节性影响因素和多变的自然条件影响因素。从16天合成的优化过的时序NDVI图像上,通过分析物候变化,可以获得较好的分类结果。将具有潜在荒漠化趋势的区域模型化研究以后,研究结果表明新疆及周边地区40万km2的土地有潜在荒漠化的趋势。由于MODIS NDVI数据覆盖范围较大,并且对植被的生长变化有较高的敏感度,所以它可以被有效地应用于监测大尺度环境变化和荒漠化进程。     

土地利用和气候变化对区域净初级生产力影响

1IntroductionThe global change caused by the continuous increasing concentration of atmospheric greenhouse gases has threatened the existence of human beings, and the importance of carbon dioxide emissions as a major environmental issue of international concern has grown substantially in the world (IPCC, 2000). At the same time, the Kyoto Protocol, the first and only realistic plan for achieving a worldwide reduction in greenhouse gas emissions, has been passed. Since there are many uncertai…