Snowmelt detection from QuikSCAT and ASCAT satellite radar scatterometer data across the Alaskan North Slope

The timing of seasonal snowmelt in high-latitude tundra has implications ranging from local biological productivity to global atmospheric circulation, yet remains difficult to quantify, particularly at large spatial scales. Snowmelt detection in such remote polar environments is possible using satellite-based microwave scatterometers, such as NASA’s QuikSCAT. QuikSCAT measured scattering in Ku-band, which is sensitive to snowmelt signals, from 1999 until the antenna failed in 2009. The Advanced Scatterometer (ASCAT) (2006–2021 (projected) operational), which operates at C-band, may be able to extend the QuikSCAT record, but existing techniques fail to adequately monitor tundra environments. Here, we designed a departure threshold algorithm to produce a consistent 15-year time series of melt onset for the tundra of the Alaskan North Slope, using the overlap period for the enhanced resolution datasets to calibrate the ASCAT melt detection record against QuikSCAT. We produced a time series of day of year of melt onset for 4.45 km x 4.45 km grid cells on the Alaskan North Slope from 2000–2014. Time series validation with in situ mean daily air temperature produced mean R² values of 0.75 (QuikSCAT) and 0.72 (ASCAT). We qualitatively observed a difference between early-season melt, which occurred rapidly and was driven by strong wind events, and more typical melt, which occurred gradually along a latitudinal gradient. We speculate that future melt timing will have greater frequency of early-season onset as climate change destabilizes the high-latitude atmosphere.     

基于微波辐射计的南极冰盖冻融时空变化分析

基于改进的小波冻融探测算法, 利用SMMR和SSM/I数据对南极冰盖1978年-2010年期间的冻融状况进行监测, 分析了南极冰盖近31年(1978-2010)和近10年(2000-2010)的整体和区域冻融时空变化特征, 结果表明:南极冰盖冻融变化受南极地区温度变化影响比较明显, 两者之间具有一定程度的正相关关系, 而且南极冰盖冻融具有南极东部和南极西部两种不同的冻融变化特征, 南极西部冰盖冻融变化剧烈, 南极东部冰盖冻融变化相对稳定, 甚至有减弱趋势。     

Atmospheric aerosol pollution across China: a spatiotemporal analysis of satellite-based aerosol optical depth during 2000–2016

ABSTRACT

Increasing attention has been paid to the deterioration of air quality in China during the past decade. This study presents the spatiotemporal variations of aerosol concentration across China during 2000–2016 using aerosol optical depth (AOD) from the atmospheric product of Moderate Resolution Imaging Spectroradiometer. Percentile thresholds are applied to define AOD days with different loadings. Temporally, aerosol concentration has increased since 2000 and reached the highest level in 2011; then it has declined from 2011 to 2016. Seasonally, aerosol concentration is the highest in summer and the lowest in winter. Spatially, North China and Sichuan Basin are featured by high aerosol concentration with increasing trends in North China and decreasing trends in Sichuan Basin. North, Southeast and Southwest China have been through increasing days with low AOD loading; however, Northeast China has experienced increasing days with high AOD loading. It is likely that air quality influenced by aerosols has notably improved over North China in spring and summer, over Southwest and Southeast China in autumn, but has degraded over Northeast China in autumn.     

山东地壳运动速度场模型建立与分析

建立高精度的地壳运动速度场模型是实现区域大地基准动态维持,反映地面形变,保障基础设施工程建设的重要途径。针对点位分布密集、精度可靠和多年连续重复观测等准确获取区域地壳运动速度场模型的关键问题,通过对山东及周边省份2010年1月—2015年11月连续近6a的130座连续运行参考站点在ITRF2008框架下进行处理,获取时间序列。首次完整建立了山东省地壳运动速度场模型。通过模型分析表明:水平方向,山东省地壳整体向东南方向运动,平均速率为34.3mm/a,运动方向为SE110.25°;垂直方向,鲁中山区及胶东半岛地区地壳较为稳定,鲁北、鲁西等华北平原地区存在显著沉降,最大沉降量位于广饶漏斗区,年沉降量81.6mm/a。     

Analyzing ice dynamics using Sentinel-1 data at the Solheimajoküll Glacier,Iceland

ABSTRACT

The climate in southern Iceland has warmed over the last 70 years, resulting in accelerated glacier dynamics at the Solheimajoküll glacier. In this study, we compare glacier terminus locations from 1973 to 2018, to changes in climate across the study area, and we derive ice-surface velocities (2015–2018) from satellite remote-sensing imagery (Sentinel-1) using the offset-tracking method. There have been two regional temperature trends in the study period: cooling (1973–1979) and warming (1980–2018). Our results indicate a time lag of about 20 years between the onset of glacier retreat (?53 m/year since 2000) and the inception of the warming period. Seasonally, the velocity time series suggest acceleration during the summer melt season since 2016, whereas glacier velocities during accumulation months were constant. The highest velocities were observed at high elevations where the ice-surface slope is the steepest. We tested several scenarios to assess the hydrological time response to glacier accelerations, with the highest correlations being found between one and 30 days after the velocity estimates. Monthly correlation analyses indicated inter-annual and intra-annual variability in the glacier dynamics. Additionally, we investigate the linkage between glacier velocities and meltwater outflow parameters as they provide useful information about internal processes in the glacier. Velocity estimates positively correlate with water level and negatively correlate with water conductivity between April and August. There is also a disruption in the correlation trend between water conductivity and ice velocity in June, potentially due to a seasonal release of geothermal water.     

X波段测波雷达海流信息反演的影响因素分析

X波段测波雷达海流信息的提取决定着有效浪高结果的准确度。因此,对可能影响X波段测波雷达海流信息提取的各种环境因素以及雷达工作模式等进行了海浪回波成像仿真,然后采用目前测波雷达通用的算法对仿真回波图像进行了海流信息反演。主要研究了海表面风速、雷达天线架设距离海平面高度、天线转速、海流流速、海流流向与海浪方向夹角、所选取的图像帧数以及每帧图像大小对海流信息反演的影响。对比分析设定值与反演结果,可知海表面风速在6~14 m/s之间,天线高度大于20 m并且转速为50~70 r/min,流速小于200 cm/s并且主波浪向与流向夹角不接近90°,图像帧数为128帧并且每帧图像数据点数为128×128时,X波段测波雷达能获得最佳海流信息反演结果。     

An approach for characterizing the distribution of shrubland ecosystem components as continuous fields as part of NLCD

Characterizing and quantifying distributions of shrubland ecosystem components is one of the major challenges for monitoring shrubland vegetation cover change across the United States. A new approach has been developed to quantify shrubland components as fractional products within National Land Cover Database (NLCD). This approach uses remote sensing data and regression tree models to estimate the fractional cover of shrubland ecosystem components. The approach consists of three major steps: field data collection, high resolution estimates of shrubland ecosystem components using WorldView-2 imagery, and coarse resolution estimates of these components across larger areas using Landsat imagery. This research seeks to explore this method to quantify shrubland ecosystem components as continuous fields in regions that contain wide-ranging shrubland ecosystems. Fractional cover of four shrubland ecosystem components, including bare ground, herbaceous, litter, and shrub, as well as shrub heights, were delineated in three ecological regions in Arizona, Florida, and Texas. Results show that estimates for most components have relatively small normalized root mean square errors and significant correlations with validation data in both Arizona and Texas. The distribution patterns of shrub height also show relatively high accuracies in these two areas. The fractional cover estimates of shrubland components, except for litter, are not well represented in the Florida site. The research results suggest that this method provides good potential to effectively characterize shrubland ecosystem conditions over perennial shrubland although it is less effective in transitional shrubland. The fractional cover of shrub components as continuous elements could offer valuable information to quantify biomass and help improve thematic land cover classification in arid and semiarid areas.     

利用SAR数据研究南极Grove山地区冰流运动特征

Grove山地区是我国南极PANDA断面考察的重点研究区域之一。本文利用35 d时间间隔的Envisat ASAR数据,分别采用DInSAR、偏移量跟踪以及两者相结合的方法提取了该区域冰面流速信息,描述了该区域复杂的冰流运动特征,并对Grove山核心区的冰流运动特征进行分析。利用GPS实测数据和MEaSUREs流速进行精度分析,说明了结果的可靠性,并利用2006、2007和2009年三期南极冬季SAR数据提取了Grove山地区冰流速,发现该区域冰流速无明显年际变化。     

基于SAR偏移量跟踪法提取岗纳楼冰川流速

冰川动态变化监测有助于反映全球和区域气候演变,保护自然环境和自然资源。近年来,基于SAR数据研究冰川运动已成为主流技术之一。基于SAR提取冰川流速主要包括合成孔径雷达干涉测量、多孔径雷达干涉和偏移量追踪法。本文采用SAR偏移量追踪法中的强度追踪法,提取青海省哈拉湖东北部岗纳楼冰川沿距离向、方位向的冰川流速。试验结果表明,距离向冰川运动速度提取效果较好,最大流速达15.36 m/a,流速从中轴向两侧递减,在冰舌末端趋于0;方位向提取的冰流速最大达18.27 m/a,但因电离层干扰,方位向流速图中存在一些方位向条纹。此外,由于冰流速在方位向分量小等因素的影响,本文研究提取的方位向流速精度低于距离向。     

A multidisciplinary multi-scale framework for assessing vulnerabilities to global change

Terrestrial ecosystems provide a number of vital services for people and society, such as food, fibre, water resources, carbon sequestration, and recreation. The future capability of ecosystems to provide these services is determined by changes in socio-economic factors, land use, atmospheric composition, and climate. Most impact assessments do not quantify the vulnerability of ecosystems and ecosystem services under such environmental change. They cannot answer important policy-relevant questions such as 'Which are the main regions or sectors that are most vulnerable to global change?’ 'How do the vulnerabilities of two regions compare?’ 'Which scenario is the least harmful for a sector?’This paper describes a new approach to vulnerability assessment developed by the Advanced Terrestrial Ecosystem Analysis and Modelling (ATEAM) project. Different ecosystem models, covering biodiversity, agriculture, forestry, hydrology, and carbon sequestration are fed with the same Intergovernmental Panel on Climate Change (IPCC) scenarios based on the Special Report on Emissions Scenarios (SRES). Each model gives insights into specific ecosystems, as in traditional impact assessments. Moreover, by integrating the results in a vulnerability assessment, the policy-relevant questions listed above can also be addressed. A statistically derived European environmental stratification forms a key element in the vulnerability assessment. By linking it to other quantitative environmental stratifications, comparisons can be made using data from different assessments and spatial scales.     

Estimating surface ice velocity on Chhota Shigri glacier from satellite data using Particle Image Velocimetry (PIV) technique

Information about the surface ice velocity is one of the important parameters for Mass balance and Glacier dynamics. This study estimates the surface ice velocity of Chhota Shigri glacier using Landsat (TM/ETM+) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) temporal data-sets from a period of 2009 to 2016 and 2006 to 2007, respectively. A correlation based Particle Image Velocimetry (PIV) technique has been used for the estimation of surface ice velocity. This technique uses multiple window sizes in the same data-set. Four window sizes (low, medium, high, very high) are used for each image pair. Estimated results have been compared with the published data. The outcomes attained from the medium window size closely matches with the published results. The estimated mean surface ice velocities of medium window size are 24 and 28.5 myr^?1 for 2009/2010 and 2006/2007 images pair. Highest velocity is observed in middle part of the glacier while lowest in the accumulation zone of the glacier.     

3D Surface velocity retrieval of mountain glacier using an offset tracking technique applied to ascending and descending SAR constellation data: a case study of the Yiga Glacier

COSMO-SkyMed is a constellation of four X-band high-resolution radar satellites with a minimum revisit period of 12 hours. These satellites can obtain ascending and descending synthetic aperture radar (SAR) images with very similar periods for use in the three-dimensional (3D) inversion of glacier velocities. In this paper, based on ascending and descending COSMO-SkyMed data acquired at nearly the same time, the surface velocity of the Yiga Glacier, located in the Jiali County, Tibet, China, is estimated in four directions using an offset tracking technique during the periods of 16 January to 3 February 2017 and 1 February to 19 February 2017. Through the geometrical relationships between the measurements and the SAR images, the least square method is used to retrieve the 3D components of the glacier surface velocity in the eastward, northward and upward directions. The results show that applying the offset tracking technique to COSMO-SkyMed images can be used to derive the true 3D velocity of a glacier’s surface. During the two periods, the Yiga Glacier had a stable velocity, and the maximum surface velocity, 2.4?m/d, was observed in the middle portion of the glacier, which corresponds to the location of the steepest slope.     

Detection of Tamarisk Defoliation by the Northern Tamarisk Beetle Based on Multitemporal Landsat 5 Thematic Mapper Imagery

The spread of tamarisk (Tamarix spp., also known as saltcedar) is a significant ecological disturbance in western North America and has long been targeted for control, leading to the importation of the northern tamarisk beetle (Diorhabda carinulata) as a biological control agent. Following its initial release along the Colorado River near Moab, Utah in 2004, the beetle has successfully established and defoliated tamarisk across much of the upper Colorado River Basin. However, the spatial distribution and seasonal timing of defoliation are complex and difficult to quantify over large areas. To address this challenge, we tested and compared two remote sensing approaches to mapping tamarisk defoliation: Disturbance Index (DI) and a decision tree method called Random Forest (RF). Based on multitemporal Landsat 5 TM imagery for 2006-2010, changes in DI and defoliation probability from RF were calculated to detect tamarisk defoliation along the banks of Green, Colorado, Dolores and San Juan rivers within the Colorado Plateau area. Defoliation mapping accuracy was assessed based on field surveys partitioned into 10 km sections of river and on regions of interest created for continuous riparian vegetation. The DI method detected 3711 ha of defoliated area in 2007, 7350 ha in 2008, 10,457 ha in 2009 and 5898 ha in 2010. The RF method detected much smaller areas of defoliation but proved to have higher accuracy, as demonstrated by accuracy assessment and sensitivity analysis, with 784 ha in 2007, 960 ha in 2008, 934 ha in 2009, and 1008 ha in 2010. Results indicate that remote sensing approaches are likely to be useful for studying spatiotemporal patterns of tamarisk defoliation as the tamarisk leaf beetle spreads throughout the western United States.     

福建省植被NPP时空格局及其驱动力分析

以福建省为研究区,以中等分辨率MODIS NDVI遥感数据、气象数据及其他辅助数据为数据源,基于植被净初级生产力(net primary productivity,NPP)光能利用率估算模型——CASA,定量研究了该区域历史序列(2001—2012年)NPP时空变化格局,探索其主要影响因素。结果表明:2001—2012年该区域NPP总体呈现下降趋势,2003年和2005年为历年变化下降率最大的两年;该区域NPP时空分布特征明显,在空间上表现为由南向北递减的空间分布格局,且沿海经济发达区域NPP普遍较低;时间上表现为春秋两季具有相同的空间分布,夏季具有最高的NPP,占全年NPP的56%,冬季平均NPP在120gC·m~(-2)·a~(-1)以下;降水和温度与NPP的线性相关性较小,且线性相关性随空间位置的不同而有所差异;福建省NPP对气候因子的响应随空间位置的变化而变化,在不同的区域,其主要的胁迫因子不同,NPP总体受到辐射量的驱动因素要比其他胁迫因子强。     

The Digital Belt and Road program in support of regional sustainability

The Belt and Road initiative has a significant focus on infrastructure, trade, and economic development across a vast region, and it also provides significant opportunities for sustainable development. The combined pressure of climate variability, intensified use of resources, and the fragility of ecosystems make it very challenging, however, to achieve future sustainability. To develop the path in a sustainable way, it is important to have a comprehensive understanding of these issues across nations and evaluate them in a scientific and well-informed approach. In this context, the Digital Belt and Road (DBAR) program was initiated as an international venture to share expertise, knowledge, technologies, and data to demonstrate the role of Earth observation science and technology and big Earth data applications to support large-scale development. In this paper, we identify pressing challenges, present the research priorities and foci of the DBAR program, and propose solutions where big Earth data can make significant contributions. This paper calls for further joint actions and collaboration to build a digital silk road in support of sustainable development at national, regional and global levels.     

Advanced image processing methods as a tool to map and quantify different types of biological soil crust

Biological soil crusts (BSCs) modify numerous soil surface properties and affect many key ecosystem processes. As BSCs are considered one of the most important components of semiarid ecosystems, accurate characterisation of their spatial distribution is increasingly in demand. This paper describes a novel methodology for identifying the areas dominated by different types of BSCs and quantifying their relative cover at subpixel scale in a semiarid ecosystem of SE Spain. The approach consists of two consecutive steps: (i) First, Support Vector Machine (SVM) classification to identify the main ground units, dominated by homogenous surface cover (bare soil, cyanobacteria BSC, lichen BSC, green and dry vegetation), which are of strong ecological relevance. (ii) Spectral mixture analysis (SMA) of the ground units to quantify the proportion of each type of surface cover within each pixel, to correctly characterize the complex spatial heterogeneity inherent to semiarid ecosystems. SVM classification showed very good results with a Kappa coefficient of 0.93%, discriminating among areas dominated by bare soil, cyanobacteria BSC, lichen BSC, green and dry vegetation. Subpixel relative abundance images achieved relatively high accuracy for both types of BSCs (about 80%), whereas general overestimation of vegetation was observed. Our results open the possibility of introducing the effect of presence and of relative cover of BSCs in spatially distributed hydrological and ecological models, and assessment and monitoring aimed at reducing degradation in these areas.     

Comparative spatio-spectral heterogeneity analysis using multispectral and hyperspectral airborne images

Knowledge of spatio-spectral heterogeneity within multisensor remote sensing images across visible, near-infrared and short wave infrared spectra is important. Till now, little comparative research on spatio-spectral heterogeneity has been conducted on real multisensor images, especially on both multispectral and hyperspectral airborne images. In this study, four airborne images, Airborne Thematic Mapper, Compact Airborne Spectrographic Imager, Specim AISA Eagle and AISI Hawk hyperspectral airborne images of woodland and heath landscapes at Harwood, UK, were applied to quantify and evaluate the differences in spatial heterogeneity through semivariogram modelling. Results revealed that spatial heterogeneity of multisensor airborne images has a close relationship with spatial and spectral resolution and wavelength. Within the visible, near-infrared spectra and short wave infrared spectra, greater spatial heterogeneity is generally observed from the relatively longer wavelength in short wave infrared spectra. There are dramatic changes across the red and red edge spectra, and the peak value is generally examined in the red middle or red edge wavelength across the visible and near-infrared spectra for vegetation or non-vegetation landscape respectively. In all, for real multisensor airborne images, the change in spatial heterogeneity with spatial resolution will accord with the change of support theory depending on whether dramatic change exists across the corresponding wavelength. Besides, if with close spatial resolution, the spatial heterogeneity of multispectral images might be far from the overall integration of these bands from the hyperspectral images involved. A comparative assessment of spatio-spectral heterogeneity using real hyperspectral and multispectral airborne images provides practical guidance for designing the placement and width of a spectral band for different applications and also makes a contribution to the understanding of how to reconcile spatial patterns generated by multisensors.     

Measuring and monitoring linear woody features in agricultural landscapes through earth observation data as an indicator of habitat availability

The loss of natural habitats and the loss of biological diversity is a global problem affecting all ecosystems including agricultural landscapes. Indicators of biodiversity can provide standardized measures that make it easier to compare and communicate changes to an ecosystem. In agricultural landscapes the amount and variety of available habitat is directly correlated with biodiversity levels. Linear woody features (LWF), including hedgerows, windbreaks, shelterbelts as well as woody shrubs along fields, roads and watercourses, play a vital role in supporting biodiversity as well as serving a wide variety of other purposes in the ecosystem. Earth observation can be used to quantify and monitor LWF across the landscape. While individual features can be manually mapped, this research focused on the development of methods using line intersect sampling (LIS) for estimating LWF as an indicator of habitat availability in agricultural landscapes. The methods are accurate, efficient, repeatable and provide robust results. Methods were tested over 9.5 Mha of agricultural landscape in the Canadian Mixedwood Plains ecozone. Approximately 97,000 km of LWF were estimated across this landscape with results useable both at a regional reporting scale, as well as mapped across space for use in wildlife habitat modelling or other landscape management research. The LIS approach developed here could be employed at a variety of scales in particular for large regions and could be adapted for use as a national scale indicator of habitat availability in heavily disturbed agricultural landscape.     

A continuous velocity field for Norway

In Norway, as in the rest of Fennoscandia, the process of Glacial Isostatic Adjustment causes ongoing crustal deformation. The vertical and horizontal movements of the Earth can be measured to a high degree of precision using GNSS. The Norwegian GNSS network has gradually been established since the early 1990s and today contains approximately 140 stations. The stations are established both for navigation purposes and for studies of geophysical processes. Only a few of these stations have been analyzed previously. We present new velocity estimates for the Norwegian GNSS network using the processing package GAMIT. We examine the relation between time-series length and precision. With approximately 3.5 years of data, we are able to reproduce the secular vertical rate with a precision of 0.5 mm/year. To establish a continuous crustal velocity field in areas where we have no GNSS receivers or the observation period is too short to obtain reliable results, either interpolation or modeling is required. We experiment with both approaches in this analysis by using (i) a statistical interpolation method called Kriging and (ii) a GIA forward model. In addition, we examine how our vertical velocity field solution is affected by the inclusion of data from repeated leveling. Results from our geophysical model give better estimates on the edge of the network, but inside the network the statistical interpolation method performs better. In general, we find that if we have less than 3.5 years of data for a GNSS station, the interpolated value is better than the velocity estimate based on a single time-series.