Institute Of Earth Research Articles

NEW APPROACH TO STRONG EARTHQUAKE PREDICTION IN THE SOUTH BAIKAL REGION ON THE BASIS OF ROCK DEFORMATION MONITORING DATA: METHODOLOGY AND RESULTS

The Southern Baikal is located within the actively developing Baikal rift zone (BRZ) that is characterized by a significant seismic potential, and M>7 earthquakes occur periodically with intensive shaking in the epicenters (up to 10 units). The problem of prediction and forecasting of strong earthquakes has always been critical for this region, considering its increasing urbanization, industrial clusters and transport systems. The article describes the methodology based on rock deformation monitoring data, which aims at developing a technology capable of efficient prediction and forecasting of strong earthquakes. In the Institute of Earth’s Crust SB RAS a set of studies is carried out in order to solve this problem, including those associated with the instrumental study of current movements of the lithosphere through GPS geodesy and deformations of rocks by strain gauges. The existing GPS sites and deformation measurements are combined into the Large-Scale Research Facilities "South Baikal instrumental complex for monitoring hazardous geodynamic processes" in frame of the Shared Research Facilities "Geodynamics and Geochronology" at the Institute of the Earth’s Crust, Siberian Branch of the Russian Academy of Science.In this article, the deformation monitoring methodology is described in application to the monitoring sites installed in the study area. The description includes the details of its conceptual basis, technical support and data processing methods. The discussion focuses on the instrumental measurements of rock deformation related to three strong events in the study area – Kultuk (August 27, 2008), Bystrinskoe (September 21, 2020), and Kudara (December 10, 2020) earthquakes. The features of the deformation process before these seismic events are given special attention with account of the structural-geodynamic settings and positions of local monitoring sites relative to the earthquake epicenters.

Editorial on Special Issue “Geo-Information Technology and Its Applications”

Geo-information technology plays a critical role in urban planning and management, land resource quantification, natural disaster risk and damage assessment, smart city development, land cover change modeling and touristic flow management. In particular, the development of big data mining and machine learning techniques (including deep learning) in recent years has expanded the potential applications of geo-information technology and promoted innovation in approaches to mining in different fields. In this context, the International Conference on Geo-Information Technology and its Applications (ICGITA 2019) was held in Nanchang, Jiangxi, China, 11–13 October 2019, co-organized by the Key Laboratory of Digital Land and Resources, East China University of Technology, the Institute of Remote Sensing and Digital Earth (RADI) of the Chinese Academy of Sciences (CAS), which was renamed in 2017 the Aerospace Information Research Institute (AIR), CAS, and the Institute of Space and Earth Information Science of the Chinese University of Hong Kong. The outstanding papers presented at this event and some other original articles were collected and published in this Special Issue “Geo-Information Technology and Its Applications” in the International Journal of Geo-Information. This Special Issue consists of 14 high-quality and innovative articles that explore and discuss the typical applications of geo-information technology in the above-mentioned domains.

Elaborating a scheme for mine methane capturing while developing coal gas seams

The research has been supported by the Ministry of Education and Science of Ukraine via research grant No. 0120U102084 and carried out by Dnipro University of Technology and Technical University of Kosice, Institute of Earth’s Resources (Slovakia). We express gratitude to our colleagues from our institutions who provide us with the required information and helped considerably complete the research.

DISASTER MONITORING AND EMERGENCY RESPONSE SERVICES IN CHINA

Abstract. The Disaster Monitoring and Emergency Response Service(DIMERS) project was kicked off in 2017 in China, with the purpose to improve timely responsive service of the institutions involved in the management of natural disasters and man-made emergency situations with the timely and high-quality products derived from Space-based, Air-based and the in-situ Earth observation. The project team brought together a group of top universities and research institutions in the field of Earth observations as well as the operational institute in typical disaster services at national level. The project will bridge the scientific research and the response services of massive catastrophe in order to improve the emergency response capability of China and provide scientific and technological support for the implementation of the national emergency response strategy. In response to the call for proposal of “Earth Observation and Navigation” of 2017 National Key R&D Program of China, Professor Wu Jianjun, the deputy chairman of Faculty of Geographical Science of Beijing Normal University, submitted the Disaster Monitoring and Emergency Response Service (DIMERS) project, jointly with the experts and scholars from Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Wuhan University, China Institute of Earthquake Forecasting of China Earthquake Administration and China Institute of Water Resources and Hydropower Science. After two round evaluations, the proposal was funded by Ministry of Science and Technology of China.

Review: Can Animals Predict Earthquakes?

Review Article| April 17, 2018 Review: Can Animals Predict Earthquakes? Heiko Woith; Heiko Woith aGFZ German Research Centre for Geosciences, Helmholtzstraße 7, 14467 Potsdam, Germany, heiko.woith@gfz-potsdam.de Search for other works by this author on: GSW Google Scholar Gesa M. Petersen; Gesa M. Petersen aGFZ German Research Centre for Geosciences, Helmholtzstraße 7, 14467 Potsdam, Germany, heiko.woith@gfz-potsdam.debAlso at Institute of Earth and Environmental Sciences, University of Potsdam, Golm, Germany. Search for other works by this author on: GSW Google Scholar Sebastian Hainzl; Sebastian Hainzl aGFZ German Research Centre for Geosciences, Helmholtzstraße 7, 14467 Potsdam, Germany, heiko.woith@gfz-potsdam.de Search for other works by this author on: GSW Google Scholar Torsten Dahm Torsten Dahm aGFZ German Research Centre for Geosciences, Helmholtzstraße 7, 14467 Potsdam, Germany, heiko.woith@gfz-potsdam.debAlso at Institute of Earth and Environmental Sciences, University of Potsdam, Golm, Germany. Search for other works by this author on: GSW Google Scholar Bulletin of the Seismological Society of America (2018) 108 (3A): 1031–1045. https://doi.org/10.1785/0120170313 Article history first online: 17 Apr 2018 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Heiko Woith, Gesa M. Petersen, Sebastian Hainzl, Torsten Dahm; Review: Can Animals Predict Earthquakes?. Bulletin of the Seismological Society of America 2018;; 108 (3A): 1031–1045. doi: https://doi.org/10.1785/0120170313 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyBulletin of the Seismological Society of America Search Advanced Search Abstract In public perception, abnormal animal behavior is widely assumed to be a potential earthquake precursor, in strong contrast to the viewpoint in natural sciences. Proponents of earthquake prediction via animals claim that animals feel and react abnormally to small changes in environmental and physico‐chemical parameters related to the earthquake preparation process. In seismology, however, observational evidence for changes of physical parameters before earthquakes is very weak.In this study, we reviewed 180 publications regarding abnormal animal behavior before earthquakes and analyze and discuss them with respect to (1) magnitude–distance relations, (2) foreshock activity, and (3) the quality and length of the published observations. More than 700 records of claimed animal precursors related to 160 earthquakes are reviewed with unusual behavior of more than 130 species. The precursor time ranges from months to seconds prior to the earthquakes, and the distances from a few to hundreds of kilometers. However, only 14 time series were published, whereas all other records are single observations. The time series are often short (the longest is 1 yr), or only small excerpts of the full data set are shown. The probability density of foreshocks and the occurrence of animal precursors are strikingly similar, suggesting that at least parts of the reported animal precursors are in fact related to foreshocks. Another major difficulty for a systematic and statistical analysis is the high diversity of data, which are often only anecdotal and retrospective. The study clearly demonstrates strong weaknesses or even deficits in many of the published reports on possible abnormal animal behavior. To improve the research on precursors, we suggest a scheme of yes and no questions to be assessed to ensure the quality of such claims. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

3rd International Symposium on Earth Observation for Arid and Semi-Arid Environments (ISEO 2016)

PrefaceThe 3rd International Symposium on Earth Observation for Arid and Semi-arid Environments (ISEO 2016) was held in Dushanbe, Tajikistan from September 19 to 21, 2016. The theme of this symposium was "Earth Observation for the Great Silk Road".ISEO 2016 was organized by the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences (RADI) and hosted by the Academy of Sciences of the Republic of Tajikistan (ASRT). More than 80 experts and scholars from nine countries and regions had attended the symposium. This volume contains selected papers contributed by the participants.The purpose of the symposium is to further exchange experiences on the use of Earth observation technologies among the Central Asian and neighboring countries. In 2012, the 1st symposium in this series was initiated in Kashgar by RADI, CAS. The 2nd symposium was held in 2014 in Issyk Kul, Kyrgyzstan. Since then, an international network has been established preliminarily to promote cooperation on Earth observation for arid and semi-arid environment, especially in Central Asia and neighboring regions.ISEO 2016 had provided a scientific platform to discuss and explore better scientific approaches to global sustainable development in the Belt and Road region through Earth observation technologies. I do hope that we could have more bilateral and multi-lateral scientific cooperations among the Belt and Road countries with the ISEO symposia.Huadong GUOCo-Chair, ISEO2016Academician, Chinese Academy of Sciences (CAS)Institute of Remote Sensing and Digital Earth (RADI), CASList of Topics, Editors, Committees, Figures are available in this PDF.

International Symposium on Earth Observation for One Belt and One Road (EOBAR)

PrefaceThe proceedings were written by participants of the International Symposium on Earth Observation for One Belt and One Road (EOBAR) held 16-17 May, 2016 in Beijing, China. Sponsored by the Division of Earth Sciences of the Chinese Academy of Sciences (CAS) and hosted by the Institute of Remote Sensing and Digital Earth, CAS, the conference has aimed to provide an international platform under the theme “quicker, better, broader understanding of One Belt and One Road (OBOR)” for scientists engaged in OBOR researches and earth observation applications.The main topic of the symposium has been well represented by the 58 papers selected in the peer review. The symposium chairman was Huadong GUO (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences). The Chairs of Scientific Committee was Guanhua XU (Ministry of Science and Technology of the People’s Republic of China), Yong CHEN (China Earthquake Administration) and Valery. G. Bondur (Institute for Scientific Research of Aerospace Monitoring “AEROCOSMOS”, Russian Academy of Sciences). The Organizing Committee was chaired by Bingfang WU (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences) and Yongwei LIU (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences).We appreciate the efforts of all the authors who contributed to this conference, and particularly acknowledge the accepted papers for their high quality. We would like to thank the Division of Earth Sciences of CAS, Bureau of International Cooperation of CAS, Group on Earth Observations (GEO), Chinese Academy of Sciences National Natural Science Foundation, without whose generous support, the symposium could not have taken place. Special thanks also go to the staff at IOP Publishing Ltd., UK.Xinwu LI, Jie Liu, Zhongchang SunInstitute of Remote Sensing and Digital EarthChinese Academy of Sciences, China

Impacts of regional transport on black carbon in Huairou, Beijing, China

The 22nd Asia-Pacific Economic Cooperation (APEC) Conference was held near Yanqi Lake, Huairou, in Beijing, China during November 10-11, 2014. To guarantee haze-free days during the APEC Conference, the Beijing government and the governments of the surrounding provinces implemented a series of controls. Three months of Aethalometer 880 nm black carbon (BC) measurements were examined to understand the hourly fluctuations in BC concentrations that resulted from emission controls and meteorology changes. Measurements were collected at the University of Chinese Academy of Sciences near the APEC Conference site and in Central Beijing at the Institute of Remote Sensing and Digital Earth of the Chinese Academy of Sciences. Synoptic conditions are successfully represented through analysis of backward trajectories in six cluster groups. The clusters are identified based on air mass transport from various areas such as Inner Mongolia, Russia, three northeastern provinces, and Hebei industrial areas, to the measurement sites. Air pollution control measures during the APEC Conference significantly reduced BC at the conference site (Huairou) and in Central Beijing, with greater reductions in BC concentrations at the conference site than in Central Beijing. The highest BC concentrations in Huairou were associated with air masses originating from Central Beijing rather than from the Hebei industrial region. The success of the control measures implemented in Beijing and the surrounding regions demonstrates that BC concentrations can be effectively reduced to protect human health and mitigate regional climate forcing. This study also demonstrates the need for regional strategies to reduce BC concentrations, since urban areas like Beijing are sources as well as downwind receptors of emissions.

6th Digital Earth Summit

The papers in this proceeding are contributions written by participants at the 6th Digital Earth Summit held 7-8 July, 2016 in Beijing, China. Under the theme "Digital Earth in the Era of Big Data", the 6th Digital Earth Summit aims to provide an international platform to focus on the application and technologies of Digital Earth for new developments and advances in the context of big data. In total, over 184 abstracts were selected for presentations in “Digital Earth Application in the Context of Big Data", “Big Data and Mountain Surface Process", and “The Role of Open Standards in the Era of Big Data" at 13 scientific sessions and 2 poster sessions. The main topics of the Summit are well represented by the papers in this proceeding. The Co-Chairs of the Summit was Huadong GUO (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences) and Alessandro ANNONI (Joint Research Center, European Commission). The Organizing Committee for the Summit was chaired by Yongwei LIU (Chinese National Committee of International Society for Digital Earth) and Xinyuan WANG (Key Laboratory of Digital Earth Sciences, Chinese Academy of Sciences).We would like to thank the International Society for Digital Earth (ISDE), the Institute of Remote Sensing and Digital Earth (RADI) of CAS, the International Centre on Space Technologies for Natural and Cultural Heritage (HIST), under the Auspices of UNESCO, the CAS-TWAS Centre of Excellence on Space Technology for Disaster Mitigation (SDIM), Integrated Research on Disaster Risk (IRDR), Chinese National Committee of ISDE, Key Laboratory of Digital Earth Sciences of CAS, without whose generous support the Summit could not have taken place. Special thanks also go to the staff at IOP Publishing Ltd., UK.

RADI's Airborne X-SAR with High Resolution: Performance, Characterization and Verification

X-SAR is an airborne multi-mode synthetic aperture radar (SAR) system with high- resolution, interferometer and full-polarization, developed by the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), funded by the CAS Large Research Infrastructures. Since 2009, the first developed stage of X-SAR system was successfully implemented to an operational SAR with high resolution (up to 0.5 meter). In May 2013, the imaging verification on flights test was carried out. The data calibration on the laboratory measurements were completed at the end of 2015. Many valuable results of imaging verification and data calibration have emphasized the quantitative microwave measurement capabilities. This paper presents the results of X-SAR system performance, characterization, optimization, and verification as carried out during the flight trials and laboratory measurement. The system performance and calibration parameters are presented such as transmitter amplitude accuracy, phase noise, system gain change with temperature variation, long-term radiometric stability. The imaging verification of the key performance parameters is discussed, including target-response function, target pairs discrimination, image noise and radiometric resolution. The example imagery of radiometric enhanced products for intensity change detection is also described.

Study on atmospheric correction approach of Landsat-8 imageries based on 6S model and look-up table

Atmospheric correction is a necessary step for deriving surface geophysical parameters. The aim of this paper is to study the atmospheric correction of Landsat-8 imageries released by the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences. A look-up table (LUT)-based atmospheric correction method on Landsat-8 OLI is proposed. The LUT is generated with 6S model with inputs including total atmospheric water vapor content, ozone, and aerosol optical thickness (AOT) from MODIS atmospheric level 2 products. The conventional method to build up the atmospheric parameter LUT usually only takes part of the factors (e.g., AOT) into consideration, whereas it is not applicable in the atmospheric correction using per pixel of MODIS products as input atmospheric parameters. Thus, a five-dimensional LUT, which considers most input parameters, is built up and has high universality for the Landsat-8 OLI sensor. Finally, spectral analysis, comparison to U.S. Geological Survey-released surface reflectance (SR) products, and field observations are used to validate the quality of the model-computed SR. The validation results indicate that the proposed method can effectively generate accurate and reliable SR results, although there is an overcorrected problem in the costal blue region when the AOT value is very high.

Tributes to colleagues

Editorial board of the collection (journal) thanks the organizers of the International Conference “Modern problems of hydrogeology, geology engineering and hydrogeoecology of Eurasia”:S.L. Shvartsev - Plenary session co-Chairman, Dr. of Science, Professor, TPU, Tomsk, RussiaG.N. Kopylova - Plenary session co-Chairman, Dr. of Science, Kamchatka Branch of the Geophysical Service RAS, Petropavlovsk-Kamchatsky, RussiaV.G. Kondrat'ev - Plenary session co-Chairman, Dr. of Science, Transbaikal State UniversityE.M. Dutova - Plenary session co-Chairman, Dr. of Science, Professor, TPU, Tomsk, RussiaE.Yu. Pasechnik - Plenary Section Secretary, PhD, associate Professor, TPU, Tomsk, RussiaO.E. Lepokurova - Plenary Section Secretary, PhD, associate Professor, TPU, Tomsk, RussiaS.O. Grinevskiy - 1th Section co-Chairman, Dr. of Science, Professor, MSU, Moscow, RussiaD.S. Pokrovskiy - 1th Section co-Chairman, Dr. of Science, Tomsk State University of Architecture and Building, Tomsk, RussiaE.A. Soldatova - 1th Section Secretary, PhD, assistant, TPU, Tomsk, RussiaO.N. Grjaznov - 2th Section co-Chairman, Dr. of Science, Professor, Ural State Mining University, Yekaterinburg, RussiaV.E. Olkhovatenko - 2th Section co-Chairman, Dr. of Science, Professor, Tomsk State University of Architecture and Building, Tomsk, RussiaV.V. Kramarenko - 2th Section Secretary, PhD, associate Professor, TPU, Tomsk, RussiaS.V. Alekseev - 3th Section co-Chairman, Dr. of Science, Professor, Institute of Earth's Crust SB RAS, Tomsk, RussiaV.K. Popov - 3th Section co-Chairman, Dr. of Science, Professor, TPU, Tomsk, RussiaN.V. Guseva - 3th Section Secretary, PhD, associate Professor, TPU, Tomsk, RussiaL.V. Zamana - 4th Section co-Chairman, PhD, Institute of Natural Resources, Ecology and Cryology SB RAS, Chita, RussiaO.G. Savichev - 4th Section co-Chairman, Dr. of Science, Professor, TPU, Tomsk, RussiaA.A. Hvaschevskaya - 4th Section Secretary, PhD, associate Professor, TPU, Tomsk, RussiaB.N. Ryzhenko - Youth School Section co-Chairman, Dr. of Science, Vernadsky Institute of Geochemistry and Analytical Chemistry, Moscow, RussiaL.A. Strokova - Youth School Section co-Chairman, Dr. of Science, Professor, TPU, Tomsk, RussiaYu.G. Kopylova - Youth School Section co-Chairman, phd, TPU, Tomsk, RussiaO.G. Tokarenko - Secretary of the Conference, PhD, associate Professor, TPU, Tomsk, RussiaM.N. Kolpakova - Secretary of the Conference, PhD, assistant, TPU, Tomsk, RussiaI.G. Sharkov - Department for development of publication activities, TPU, Tomsk, Russia

Satellite Observation of Atmospheric Compositions for Air Quality and Climate Study

1NOAA Center for Satellite Applications and Research, College Park, MD 20740, USA 2State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China 3Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA 4Istituto di Fisica Applicata “Nello Carrara” del Consiglio Nazionale delle Ricerche (IFAC-CNR), Sesto Fiorentino, 50019 Firenze, Italy 5Universities Space Research Association, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA

基于中高分辨率遥感的植被覆盖度时相变换方法

PDF HTML阅读 XML下载 导出引用 引用提醒 基于中高分辨率遥感的植被覆盖度时相变换方法 DOI: 10.5846/stxb201305020904 作者: 作者单位: 黄河中下游数字地理技术教育部重点实验室,中国科学院遥感与数字地球研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 中国科学院知识创新工程重大项目(KZCX1-YW-08-03);水利部-官厅密云水库上游水土保持遥感监测二期工程(HW-STBC2004-03);中国博士后科学基金资助项目(20100470994) A temporal transformation method of fractional vegetation cover derived from high and moderate resolution remote sensing data Author: Affiliation: Institute of Remote Sensing Applications,Chinese Academy of Sciences,Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:植被覆盖度是衡量地表植被状况、指示生态环境变化的一个重要指标,也是许多学科的重要参数。传统的测量方法难以获取时间连续的面状数据,且耗时、耗力,很难大范围推广。遥感估算方法虽然可以弥补传统方法的不足,但由于云覆盖等天气条件的影响,获得同一时相覆盖整个研究区的遥感影像非常困难,时相的差异必然导致研究结果产生误差。针对植被覆盖度这一重要生态参数,结合低分辨率遥感数据的时间优势和中高分辨率遥感数据的空间优势,提出一种时相变换方法,将源于中高分辨率影像的植被覆盖度变换到研究需要的时相上。首先,利用像元二分模型计算MODIS尺度的时间序列植被覆盖度,并利用已经获得的SPOT影像计算其获取时相上的植被覆盖度;其次,利用土地利用图划分植被覆盖类型,并利用MODIS数据和土地利用数据之间的空间对应关系制作MODIS像元内各类植被覆盖的面积百分比数据;再次,利用面积百分比数据提取各类植被覆盖的纯像元,结合MODIS植被覆盖度时间序列,从而提取各类植被覆盖纯像元的植被覆盖度时间序列曲线;最后利用像元分解的方法提取MODIS像元内各类植被覆盖组分的植被覆盖度的变化规律,将其应用到该组分对应位置上SPOT像元的植被覆盖度上,从而将其变换到所需要的时相上。在密云水库上游进行试验,将覆盖研究区的10 景SPOT5多光谱影像计算的植被覆盖度统一变换到7 月上旬,结果显示:视觉效果上明显好转,且空间上连续一致;变换前后植被覆盖度的统计量对比结果也符合植被生长规律;利用外业样点数据与对应位置的植被覆盖度变换结果进行回归分析,结果发现各植被覆盖类型的R2均在0.8左右,表明变换结果与实测值非常接近,时相变换的效果较好,从而可以很好地促进相关研究精度的提高。 Abstract:Fractional vegetation cover (FVC) is an important index of land surface vegetation status. It is also an indicator of ecological environment changes and an important spatial parameter for various ecological modeling. The traditional methods of FVC measurement are time-consuming and labor-intensive, and thus difficult to obtain large-scale time series FVC data. Remote sensing technique is an effective approach to estimate FVC, but it is very difficult to acquire high and moderate resolution remote sensing images covering the entire study area during the same period because of the cloud cover and other weather conditions. Consequently, the FVC data derived from multi-temporal images inevitably lead to uncertain research results. To address the problem, this paper proposes a novel method to eliminate the impact of acquisition time differences on FVC from high and moderate resolution remote sensing images. For FVC data derived from images with different resolutions and acquisition dates, this proposed temporal transformation method is used to estimate high resolution FVC combined with a low-resolution time series FVC. Firstly, low and high resolution FVC data can be calculated from time series MODIS images and acquired SPOT images respectively using the dimidiate pixel model. Secondly, the vegetation cover is divided into different vegetation types based on the land use map derived from these SPOT images. And for each MODIS pixel, the area percentages of various types of vegetation cover are calculated based on the spatial overlay of MODIS image and land use data. As a result, the area percentage data represent that the area ratio of the different vegetation types within each MODIS pixel. Thirdly, the pure pixels of various types of vegetation cover can be extracted based on the area percentage data where the ratio is equal to 1, and the FVC time series curve of each type of vegetation cover can be generated based on these pure pixels and time series MODIS FVC data. Finally, the sub-pixel FVC variation of each type of vegetation cover can be extracted from MODIS pixels based on the pixel unmixing technique, and then apply them to the same location of SPOT FVC. Thus, the SPOT FVC can be transformed from its acquisition date to the specific date, which satisfies the need of our research. The feasibility of this temporal transformation method is examined in the upstream of Miyun Reservoir. The FVC data derived from 10 SPOT images are transformed to the same date of early July. The case study results show that: (1)The visual effects of the transformed FVC are significantly improved and consistent with the spatial patterns of vegetation cover; (2)The changes of FVC statistics information before and after the transformation are also in line with the laws of vegetation growth; (3) The linear regression of the FCV data on field measurement samples shows strong positive correlations between them, and the R2 is about 0.8 for each vegetation cover indicating the transformation results is close to the field measured values. The transformation results with higher precision can promote the accuracy of related researches. This method has also a certain reference value for the transformation of other parameters. 参考文献 相似文献 引证文献

The Woodhen: A Flightless Island Bird Defying Extinction. By Clifford B. Frith. Collingwood (Australia): CSIRO Publishing. AU $59.95. xiv + 225 p.; ill.; index. ISBN: 978-0-643-10870-7. 2013.

Previous articleNext article No AccessReviews and Brief NoticesThe Woodhen: A Flightless Island Bird Defying Extinction. By Clifford B. Frith. Collingwood (Australia): CSIRO Publishing. AU $59.95. xiv + 225 p.; ill.; index. ISBN: 978-0-643-10870-7. 2013.Barry W. BrookBarry W. BrookEnvironment Institute and School of Earth & Environmental Sciences, University of Adelaide, Adelaide, South Australia, Australia Search for more articles by this author PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by The Quarterly Review of Biology Volume 89, Number 4December 2014 Published in association with Stony Brook University Article DOIhttps://doi.org/10.1086/678662 Views: 7Total views on this site Copyright © 2014 by The University of Chicago Press. All rights reserved.PDF download Crossref reports no articles citing this article.

An Open Source Software and Web-GIS Based Platform for Airborne SAR Remote Sensing Data Management, Distribution and Sharing

With more and more Earth observation data available to the community, how to manage and sharing these valuable remote sensing datasets is becoming an urgent issue to be solved. The web based Geographical Information Systems (GIS) technology provides a convenient way for the users in different locations to share and make use of the same dataset. In order to efficiently use the airborne Synthetic Aperture Radar (SAR) remote sensing data acquired in the Airborne Remote Sensing Center of the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), a Web-GIS based platform for airborne SAR data management, distribution and sharing was designed and developed. The major features of the system include map based navigation search interface, full resolution imagery shown overlaid the map, and all the software adopted in the platform are Open Source Software (OSS). The functions of the platform include browsing the imagery on the map navigation based interface, ordering and downloading data online, image dataset and user management, etc. At present, the system is under testing in RADI and will come to regular operation soon.

Playback system designed for X-Band SAR

SAR(Synthetic Aperture Radar) has extensive application because it is daylight and weather independent. In particular, X-Band SAR strip map, designed by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, provides high ground resolution images, at the same time it has a large spatial coverage and a short acquisition time, so it is promising in multi-applications. When sudden disaster comes, the emergency situation acquires radar signal data and image as soon as possible, in order to take action to reduce loss and save lives in the first time. This paper summarizes a type of X-Band SAR playback processing system designed for disaster response and scientific needs. It describes SAR data workflow includes the payload data transmission and reception process. Playback processing system completes signal analysis on the original data, providing SAR level 0 products and quick image. Gigabit network promises radar signal transmission efficiency from recorder to calculation unit. Multi-thread parallel computing and ping pong operation can ensure computation speed. Through gigabit network, multi-thread parallel computing and ping pong operation, high speed data transmission and processing meet the SAR radar data playback real time requirement.

Calibration and Validation of Airborne InSAR Geometric Model

The image registration or geo-coding is a very important step for many applications of airborne interferometric Synthetic Aperture Radar (InSAR), especially for those involving Digital Surface Model (DSM) generation, which requires an accurate knowledge of the geometry of the InSAR system. While the trajectory and attitude instabilities of the aircraft introduce severe distortions in three dimensional (3-D) geometric model. The 3-D geometrical model of an airborne SAR image depends on the SAR processor itself. Working at squinted model, i.e., with an offset angle (squint angle) of the radar beam from broadside direction, the aircraft motion instabilities may produce distortions in airborne InSAR geometric relationship, which, if not properly being compensated for during SAR imaging, may damage the image registration. The determination of locations of the SAR image depends on the irradiated topography and the exact knowledge of all signal delays: range delay and chirp delay (being adjusted by the radar operator) and internal delays which are unknown a priori. Hence, in order to obtain reliable results, these parameters must be properly calibrated. An Airborne InSAR mapping system has been developed by the Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS) to acquire three-dimensional geo-spatial data with high resolution and accuracy. To test the performance of the InSAR system, the Validation/Calibration (Val/Cal) campaign has carried out in Sichun province, south-west China, whose results will be reported in this paper.

New indicators for global crop monitoring in CropWatch -case study in North China Plain

CropWatch is a monitoring system developed and operated by the Institute of Remote Sensing and Digital Earth (Chinese Academy of Sciences) to provide global-scale crop information. Now in its 15th year of operation, CropWatch was modified several times to be a timely, comprehensive and independent global agricultural monitoring system using advanced remote sensing technology. Currently CropWatch is being upgraded with new indicators based on new sensors, especially those on board of China Environmental Satellite (HJ-1 CCD), the Medium Resolution Spectral Imager (MERSI) on Chinese meteorological satellite (FY-3A) and cloud classification products of FY-2. With new satellite data, CropWatch will generate new indicators such as fallow land ratio (FLR), crop condition for irrigated (CCI) and non-irrigated (CCNI) areas separately, photosynthetically active radiation (PAR), radiation use efficiency for the photosynthetically active radiation (RUEPAR) and cropping index (CI) with crop rotation information (CRI). In this paper, the methods for monitoring the new indicators are applied to the North China Plain which is one of the major grain producing areas in China. This paper shows the preliminary results of the new indicators and methods; they still need to be thoroughly validated before being incorporated into the operational CropWatch system. In the future, the new and improved indicators will help us to better understand the global situation of food security.

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