Water resource applications with RADARSAT-2 – a preview

Abstract

Fresh water is arguably the most vital resource for many aspects of a healthy and stable environment. Monitoring the extent of surface water enables resource managers to detect perturbations and long term trends in water availability, and set consumption guidelines accordingly. Potential end-users of water-related observations are numerous and reflect society as a whole. They encompass scientists and managers at all levels of government, aboriginal groups, water/power utility managers, farmers, planners, engineers, hydrologists, medical researchers, climate scientists, recreation enthusiasts, public school to post-graduate students, many special interest groups and the general public. Water data and analyses generate information products that benefit water resources planning and management, engineering design, plant operations, navigation activities, health research, water quality assessments and ecosystem management. As well, they serve as inputs for flood and drought warnings and weather and climate prediction models. Radar data in general, and RADARSAT in particular, are very good for detecting open surface water and have been used operationally for flood monitoring in many countries. Significant radar data archives now exist to analyse seasonal, annual and decadal trends, in order to attain a better understanding of the freshwater cycle. Radar data are also useful for wetland classification and soil moisture estimation. With the increasing pressure on water resources, both from a quality as well as a quantity perspective, the need will continue to increase for reliable information.

RADARSAT-2 has several innovations that will enhance the ability to provide useful information about water resources. This paper provides an overview of the use of radar in general, and RADARSAT-2 in particular, for the generation of information products useful to water resource managers.     

Improving georeferencing accuracy of Very High Resolution satellite imagery using freely available ancillary data at global coverage

ABSTRACT

While impressive direct geolocation accuracies better than 5.0?m CE90 (90% of circular error) can be achieved from the last DigitalGlobe’s Very High Resolution (VHR) satellites (i.e. GeoEye-1 and WorldView-1/2/3/4), it is insufficient for many precise geodetic applications. For these sensors, the best horizontal geopositioning accuracies (around 0.55?m CE90) can be attained by using third-order 3D rational functions with vendor’s rational polynomial coefficients data refined by a zero-order polynomial adjustment obtained from a small number of very accurate ground control points (GCPs). However, these high-quality GCPs are not always available. In this work, two different approaches for improving the initial direct geolocation accuracy of VHR satellite imagery are proposed. Both of them are based on the extraction of three-dimensional GCPs from freely available ancillary data at global coverage such as multi-temporal information of Google Earth and the Shuttle Radar Topography Mission 30?m digital elevation model. The application of these approaches on WorldView-2 and GeoEye-1 stereo pairs over two different study sites proved to improve the horizontal direct geolocation accuracy values around of 75%.     

Automatic sub-pixel co-registration of Landsat-8 Operational Land Imager and Sentinel-2A Multi-Spectral Instrument images using phase correlation and machine learning based mapping

ABSTRACT

This study investigates misregistration issues between Landsat-8/ Operational Land Imager and Sentinel-2A/ Multi-Spectral Instrument at 30?m resolution, and between multi-temporal Sentinel-2A images at 10?m resolution using a phase-correlation approach and multiple transformation functions. Co-registration of 45 Landsat-8 to Sentinel-2A pairs and 37 Sentinel-2A to Sentinel-2A pairs were analyzed. Phase correlation proved to be a robust approach that allowed us to identify hundreds and thousands of control points on images acquired more than 100 days apart. Overall, misregistration of up to 1.6 pixels at 30?m resolution between Landsat-8 and Sentinel-2A images, and 1.2 pixels and 2.8 pixels at 10?m resolution between multi-temporal Sentinel-2A images from the same and different orbits, respectively, were observed. The non-linear random forest regression used for constructing the mapping function showed best results in terms of root mean square error (RMSE), yielding an average RMSE error of 0.07?±?0.02 pixels at 30?m resolution, and 0.09?±?0.05 and 0.15?±?0.06 pixels at 10?m resolution for the same and adjacent Sentinel-2A orbits, respectively, for multiple tiles and multiple conditions. A simpler 1st order polynomial function (affine transformation) yielded RMSE of 0.08?±?0.02 pixels at 30?m resolution and 0.12?±?0.06 (same Sentinel-2A orbits) and 0.20?±?0.09 (adjacent orbits) pixels at 10?m resolution.     

MTSAT-2静止气象卫星中国区域雪盖监测

利用MTSAT-2静止气象卫星数据开展了中国区域的雪盖监测研究,结合MODIS雪盖产品及站点雪深观测数据对判识结果进行对比分析和验证。首先,根据MTSAT-2静止气象卫星数据特点,进行角度效应校正及多时相数据合成,以减少云对图像的影响;其次,根据多个雪盖判识因子建立中国区域雪盖判识算法;最后,对比分析2011年1月份MTSAT-2和MODIS雪盖判识结果,并使用站点观测数据进行精度验证。研究表明:(1)MTSAT-2雪盖判识受云影响比例约30%,MODIS雪盖产品受云影响比例约60%,MTSAT-2去云效果明显。(2)无云情况下,MTSAT-2雪盖判识和MODIS雪盖产品判识精度均高于92%;有云覆盖时,MTSAT-2判识精度约65%,优于MODIS雪盖产品35%的判识精度。(3)MTSAT-2静止气象卫星在保持高积雪判识精度的前提下,可以更有效减少云对雪盖判识影响,实时获取更多地表真实信息。该研究对中国区域雪盖信息准确监测、气候变化研究以及防灾减灾等具有重要意义。     

A rule-based parameter aided with object-based classification approach for extraction of building and roads from WorldView-2 images

Roads and buildings constitute a significant proportion of urban areas. Considerable amount of research has been done on the road and building extraction from remotely sensed imagery. However, a few of them have been concentrating on using only spectral information. This study presents a comparison between three object-based models for urban features’ classification, specifically roads and buildings, from WorldView-2 satellite imagery. The three applied algorithms are support vector machines (SVMs), nearest neighbour (NN) and proposed rule-based system. The results indicated that the proposed rules in this study, despite the spectral complexity of land cover types, performed a satisfactory output with an overall accuracy of 92.92%. The advantages offered by the proposed rules were not provided by other two applied algorithms and it revealed the highest accuracy compared to SVM and NN. The overall accuracy for SVM was 76.76%, which is almost similar to the result achieved by NN (77.3%).     

含富锂(钾)卤水断陷盆地的深部构造特征: 以中国华南吉泰盆地为例

中国华南吉泰盆地在白垩纪?古近纪发育大量蒸发岩,其中含富锂卤水矿床,由于盆地深部构造特征认识不清,导致富锂卤水矿勘查评价明显滞后.基于盆地东北部泰和坳陷二维地震数据和钻孔资料,经过精细保幅处理和综合构造解释,总结了含富锂卤水矿断陷盆地的深部构造特征.地震剖面和构造属性表明,盆地深部发育错断白垩系的NE-SW走向、NW倾...     

The First Global Carbon Dioxide Flux Map Derived from TanSat Measurements

Space-borne measurements of atmospheric greenhouse gas concentrations provide global observation constraints for top-down estimates of surface carbon flux.Here,the first estimates of the global distribution of carbon surface fluxes inferred from dry-air CO_2 column (XCO_2) measurements by the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite (Tan Sat) are presented.An ensemble transform Kalman filter (ETKF) data assimilation system coupled with the GEOS-Chem global chemistry transport model is used to optimally fit model simulations with the Tan Sat XCO_2 observations,which were retrieved using the Institute of Atmospheric Physics Carbon dioxide retrieval Algorithm for Satellite remote sensing (IAPCAS).High posterior error reduction (30%–50%) compared with a priori fluxes indicates that assimilating satellite XCO_2 measurements provides highly effective constraints on global carbon flux estimation.Their impacts are also highlighted by significant spatiotemporal shifts in flux patterns over regions critical to the global carbon budget,such as tropical South America and China.An integrated global land carbon net flux of 6.71±0.76 Gt C yr~(-1) over12 months (May 2017–April 2018) is estimated from the Tan Sat XCO_2 data,which is generally consistent with other inversions based on satellite data,such as the JAXA GOSAT and NASA OCO-2 XCO_2 retrievals.However,discrepancies were found in some regional flux estimates,particularly over the Southern Hemisphere,where there may still be uncorrected bias between satellite measurements due to the lack of independent reference observations.The results of this study provide the groundwork for further studies using current or future Tan Sat XCO_2 data together with other surfacebased and space-borne measurements to quantify biosphere–atmosphere carbon exchange.     

Characterization of Regional Combustion Efficiency using ΔXCO: ΔXCO2 Observed by a Portable Fourier-Transform Spectrometer at an Urban Site in Beijing

Measurements of column-averaged dry-air mole fractions of carbon dioxide and carbon monoxide, CO₂ (XCO₂) and CO (XCO), were performed throughout 2019 at an urban site in Beijing using a compact Fourier Transform Spectrometer (FTS) EM27/SUN. This data set is used to assess the characteristics of combustion-related CO₂ emissions of urban Beijing by analyzing the correlated daily anomalies of XCO and XCO₂ (e.g., ΔXCO and ΔXCO₂). The EM27/SUN measurements were calibrated to a 125HR-FTS at the Xianghe station by an extra EM27/SUN instrument transferred between two sites. The ratio of ΔXCO over ΔXCO₂ (ΔXCO:ΔXCO₂) is used to estimate the combustion efficiency in the Beijing region. A high correlation coefficient (0.86) between ΔXCO and ΔXCO₂ is observed. The CO:CO₂ emission ratio estimated from inventories is higher than the observed ΔXCO:ΔXCO₂ (10.46 ± 0.11 ppb ppm^?1) by 42.54%–101.15%, indicating an underestimation in combustion efficiency in the inventories. Daily ΔXCO:ΔXCO₂ are influenced by transportation governed by weather conditions, except for days in summer when the correlation is low due to the terrestrial biotic activity. By convolving the column footprint [ppm (μmol m^–2 s^–1)^–1] generated by the Weather Research and Forecasting-X-Stochastic Time-Inverted Lagrangian Transport models (WRF-X-STILT) with two fossil-fuel emission inventories (the Multi-resolution Emission Inventory for China (MEIC) and the Peking University (PKU) inventory), the observed enhancements of CO₂ and CO were used to evaluate the regional emissions. The CO₂ emissions appear to be underestimated by 11% and 49% for the MEIC and PKU inventories, respectively, while CO emissions were overestimated by MEIC (30%) and PKU (35%) in the Beijing area.     

利用中国静止气象卫星资料估算黄河源区蒸散发量

以黄河源区为研究区域,选取2009年9月该区域的中国静止气象卫星(FY-2D)观测资料,结合地面气象观测资料,基于能量平衡原理,估算了研究区域的逐时陆面蒸散发量。结果表明:在晴天条件下,利用陆表能量平衡系统模型求出蒸散发量的大小;在阴天条件下,利用FY-2D云顶反照率资料,根据太阳辐射在大气中的衰减过程,得出地表太阳辐射收支,进而求出蒸散发量的大小。卫星遥感估算的逐时蒸散发量与地面观测值相比,平均相对误差15.2%,估算误差在可接受的合理范围内,为实现陆面蒸散发量的业务化奠定了一定的基础。     

利用地震属性分析沉积环境的误区:以辽河盆地滩海东部凹陷东二段为例

为了解辽河盆地滩海地区东二段沉积相类型,通过现代河流沉积调研以及岩心、测井、地震相综合分析,结果证明:滩海地区东二段沉积相类型主要以滨浅湖-滩坝相为主,而非地震属性图所反映的河流相沉积,地震属性解释存在误区。古沉积环境解释最重要的因素就是如何理解"保存"的概念。河流在自身演化过程中迁移、改道时常发生,在漫长的地质时间内,难以保存一个完整的河道。沉积环境分析中,应当遵循从岩心相—测井相—地震相的分析过程,而不是单纯依据地震属性直接进行沉积相研究。