Pub Date : 2019-07-01DOI: 10.1109/IGARSS.2019.8897929
Jingmei Yang
In this paper, the slow feature analysis (SFA) method is employed to derive driving forces from the long-term monthly mean total ozone time series observed in two ground-based stations in the northern mid-latitudes. The wavelet transformation technique is then used to analyze the time scale structure of the derived driving forces. The slow feature analysis results show that the explosive volcanic eruptions have a significant influence on short-term ozone changes. The wavelet analysis results indicate that the driving forces of total ozone time series exhibit different time scale variations, which are mainly associated with solar activity cycles and quasi-biennial oscillation (QBO) cycles.
{"title":"Driving Force of Total Ozone in the Northern Midlatitudes: An Analysis based on Data from Two Stations","authors":"Jingmei Yang","doi":"10.1109/IGARSS.2019.8897929","DOIUrl":"https://doi.org/10.1109/IGARSS.2019.8897929","url":null,"abstract":"In this paper, the slow feature analysis (SFA) method is employed to derive driving forces from the long-term monthly mean total ozone time series observed in two ground-based stations in the northern mid-latitudes. The wavelet transformation technique is then used to analyze the time scale structure of the derived driving forces. The slow feature analysis results show that the explosive volcanic eruptions have a significant influence on short-term ozone changes. The wavelet analysis results indicate that the driving forces of total ozone time series exhibit different time scale variations, which are mainly associated with solar activity cycles and quasi-biennial oscillation (QBO) cycles.","PeriodicalId":13262,"journal":{"name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","volume":"21 1","pages":"7813-7816"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78151187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IGARSS.2019.8898518
S. Raval, B. Banerjee, S. Singh, I. Canbulat
Accurate and frequent mapping in an underground mine is essential for roadway development as well as rock mass classification and hazard detection. The utilization of traditional mine mapping equipment in underground mines have been difficult due to unavailability of global navigation satellite system (GNSS) signals, limited lighting conditions, restricted accesses, and intrinsic safety (IS) requirements. Recent advances in sensor technology and post-scanning algorithms have led to the development of portable and mobile laser scanning devices that can work without the need for GNSS by using the principles of simultaneous localization and mapping (SLAM) to obtain a relatively registered laser scan (or point cloud). However, commercially available SLAM based systems are mainly designed for indoor urban applications and their utility in an underground mining environment needs to be tested. In this study, a portable SLAM based mobile mapping system (Zeb-Revo) has been used in an underground coal environment to evaluate its potential and identify related challenges.
{"title":"A Preliminary Investigation of Mobile Mapping Technology for Underground Mining","authors":"S. Raval, B. Banerjee, S. Singh, I. Canbulat","doi":"10.1109/IGARSS.2019.8898518","DOIUrl":"https://doi.org/10.1109/IGARSS.2019.8898518","url":null,"abstract":"Accurate and frequent mapping in an underground mine is essential for roadway development as well as rock mass classification and hazard detection. The utilization of traditional mine mapping equipment in underground mines have been difficult due to unavailability of global navigation satellite system (GNSS) signals, limited lighting conditions, restricted accesses, and intrinsic safety (IS) requirements. Recent advances in sensor technology and post-scanning algorithms have led to the development of portable and mobile laser scanning devices that can work without the need for GNSS by using the principles of simultaneous localization and mapping (SLAM) to obtain a relatively registered laser scan (or point cloud). However, commercially available SLAM based systems are mainly designed for indoor urban applications and their utility in an underground mining environment needs to be tested. In this study, a portable SLAM based mobile mapping system (Zeb-Revo) has been used in an underground coal environment to evaluate its potential and identify related challenges.","PeriodicalId":13262,"journal":{"name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","volume":"67 1","pages":"6071-6074"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80015512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IGARSS.2019.8900492
Yang Lan, Hanwen Yu, M. Xing
For the multibaseline (MB) synthetic aperture radar (SAR) interferometry (InSAR), MB phase unwrapping (PU) is an important step. With the rapid development of MB InSAR, the size of the datasets from the MB InSAR system is becoming increasingly larger. Under the situation of "bigdata", MB PU may face new problems with insufficient computing resources, or take too much running time to get the PU result. In order to deal with such case, we propose a convex hull and cluster-analysis based fast large-scale MB PU method (CCFLS) with enlightened by the single baseline (SB) PU method (CHFLS) from H. Yu [1]. CCFLS uses the clustering phenomenon of the MB residues to generate the convex hull of residues set with balance polarity, and avoids spending the computation resources on the area within the convex hull, so that the high-precision PU solution can be quickly obtained. The theoretical analysis and experiment results indicate that CCFLS can effectively reduce memory consumption and calculation time.
{"title":"A Convex Hull and Cluster-Analysis Based Fast Large-Scale Phase Unwrapping Method for Multibaseline Sar Interferograms","authors":"Yang Lan, Hanwen Yu, M. Xing","doi":"10.1109/IGARSS.2019.8900492","DOIUrl":"https://doi.org/10.1109/IGARSS.2019.8900492","url":null,"abstract":"For the multibaseline (MB) synthetic aperture radar (SAR) interferometry (InSAR), MB phase unwrapping (PU) is an important step. With the rapid development of MB InSAR, the size of the datasets from the MB InSAR system is becoming increasingly larger. Under the situation of \"bigdata\", MB PU may face new problems with insufficient computing resources, or take too much running time to get the PU result. In order to deal with such case, we propose a convex hull and cluster-analysis based fast large-scale MB PU method (CCFLS) with enlightened by the single baseline (SB) PU method (CHFLS) from H. Yu [1]. CCFLS uses the clustering phenomenon of the MB residues to generate the convex hull of residues set with balance polarity, and avoids spending the computation resources on the area within the convex hull, so that the high-precision PU solution can be quickly obtained. The theoretical analysis and experiment results indicate that CCFLS can effectively reduce memory consumption and calculation time.","PeriodicalId":13262,"journal":{"name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","volume":"36 9 1","pages":"1765-1768"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80176732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IGARSS.2019.8900349
C. Vaduva, F. Georgescu, Andreea Griparis, Iulia Coca Neagoe, Alexandru-Cosmin Grivei, M. Datcu
Sentinel 2 (S2) satellite provides a systematic global coverage of land surfaces, measuring physical properties within 13 spectral intervals at a temporal resolution of 5 days. Computer-based data analysis is highly required to extract similarity by processing and assist human understanding and semantic annotation in support of Earth surface mapping. This paper proposes an exploratory search methodology for S2 data underpinning both visual and latent characteristics by means of data visualization and content representation. For optimized results, the authors focus on a detailed assessment of top relevant state-of-the-art algorithms for features extraction and classification to determine which one could handle best the characteristics of S2 data.
{"title":"Exploratory search methodology for sentinel 2 data: a prospect of both visual and latent characteristics.","authors":"C. Vaduva, F. Georgescu, Andreea Griparis, Iulia Coca Neagoe, Alexandru-Cosmin Grivei, M. Datcu","doi":"10.1109/IGARSS.2019.8900349","DOIUrl":"https://doi.org/10.1109/IGARSS.2019.8900349","url":null,"abstract":"Sentinel 2 (S2) satellite provides a systematic global coverage of land surfaces, measuring physical properties within 13 spectral intervals at a temporal resolution of 5 days. Computer-based data analysis is highly required to extract similarity by processing and assist human understanding and semantic annotation in support of Earth surface mapping. This paper proposes an exploratory search methodology for S2 data underpinning both visual and latent characteristics by means of data visualization and content representation. For optimized results, the authors focus on a detailed assessment of top relevant state-of-the-art algorithms for features extraction and classification to determine which one could handle best the characteristics of S2 data.","PeriodicalId":13262,"journal":{"name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","volume":"234 1","pages":"10067-10070"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80300525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Thanks to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. In BFSAR, the compensation of the spatially variant motion errors is of great significance to get a well-focused image. In this paper, a motion compensation method based on keystone transform and modified autofocus back-projection is presented to deal with this problem. Keystone transform is applied to remove the spatial variation of range cell migration (RCM) and the first-order term of RCM errors simultaneously, prepares for the following modified autofocus back-projection, which can eliminate the high-order term of azimuth phase errors. Simulation results verify the validity and efficiency of the presented method.
{"title":"Bistatic Forward-Looking SAR Motion Error Compensation Method Based on Keystone Transform and Modified Autofocus Back-Projection","authors":"Q. Yang, Deming Guo, Zhongyu Li, Junjie Wu, Yulin Huang, Haiguang Yang, Jianyu Yang","doi":"10.1109/IGARSS.2019.8898219","DOIUrl":"https://doi.org/10.1109/IGARSS.2019.8898219","url":null,"abstract":"With appropriate geometry configurations, bistatic synthetic aperture radar (SAR) can break through the limitations of monostatic SAR on forward-looking imaging. Thanks to such a capability, bistatic forward-looking SAR (BFSAR) has extensive potential applications. In BFSAR, the compensation of the spatially variant motion errors is of great significance to get a well-focused image. In this paper, a motion compensation method based on keystone transform and modified autofocus back-projection is presented to deal with this problem. Keystone transform is applied to remove the spatial variation of range cell migration (RCM) and the first-order term of RCM errors simultaneously, prepares for the following modified autofocus back-projection, which can eliminate the high-order term of azimuth phase errors. Simulation results verify the validity and efficiency of the presented method.","PeriodicalId":13262,"journal":{"name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","volume":"16 1","pages":"827-830"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80462665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IGARSS.2019.8897884
Yuxue Wang, S. Tian, Changqi Liu
Taking the typical landslide triggered by the 2014 Ms6.5 earthquake in Ludian County of Yunnan Province as an example, the high-resolution remote sensing image of two phases before and after the earthquake is used, and the object-oriented segmentation technique and change detection based ICA transform are combined. Identify the earthquake-triggered landslide, and obtain the information such as the range and scale of the landslide after the earthquake through the superposition analysis of the feature and the change information of NDVI and slope. The results show that the landslide recognition accuracy by using the integrated method can reach 93.3%, and the error extraction and miss extraction rate are low. The integrated method is simple, fast, with less human intervention and a higher degree of automatic extraction, it can meet the needs of post-disaster emergency and rescue work. Compared with traditional change detection and object-oriented classification algorithms, the integrated method further improves the recognition accuracy of new and old landslide, and human activities such as mining, and can be used for risk analysis, disaster management and disaster relief decisions for earthquake-induced landslides.
{"title":"Rapid Identification of Seismic Landslides Combining with Object-Oriented and Independent Component Analysis Transformation :A Case of the Ms6.5 Earthquake in Ludian, Yunnan","authors":"Yuxue Wang, S. Tian, Changqi Liu","doi":"10.1109/IGARSS.2019.8897884","DOIUrl":"https://doi.org/10.1109/IGARSS.2019.8897884","url":null,"abstract":"Taking the typical landslide triggered by the 2014 Ms6.5 earthquake in Ludian County of Yunnan Province as an example, the high-resolution remote sensing image of two phases before and after the earthquake is used, and the object-oriented segmentation technique and change detection based ICA transform are combined. Identify the earthquake-triggered landslide, and obtain the information such as the range and scale of the landslide after the earthquake through the superposition analysis of the feature and the change information of NDVI and slope. The results show that the landslide recognition accuracy by using the integrated method can reach 93.3%, and the error extraction and miss extraction rate are low. The integrated method is simple, fast, with less human intervention and a higher degree of automatic extraction, it can meet the needs of post-disaster emergency and rescue work. Compared with traditional change detection and object-oriented classification algorithms, the integrated method further improves the recognition accuracy of new and old landslide, and human activities such as mining, and can be used for risk analysis, disaster management and disaster relief decisions for earthquake-induced landslides.","PeriodicalId":13262,"journal":{"name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","volume":"163 1","pages":"1570-1573"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79008846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IGARSS.2019.8900197
Diego Brum, Graciela Racolte, F. Bordin, Eduardo Kediamosiko Nzinga, M. Veronez, E. Souza, I. É. Koch, L. G. D. Silveira, I. Klein, M. T. Matsuoka, V. F. Rofatto, A. M. Junior
The Total Electron Content (TEC) derived from Global Navigation Satellite System (GNSS) data processing has been used as a tool for monitoring earthquakes. The purpose of this study is to bring an alternative approach to the prediction of earthquakes and to determine their magnitudes based on Artificial Neural Networks (ANN) and ionospheric disturbances. For this, the Vertical Total Electron Content (VTEC) data from the National Oceanic and Atmosphere Administration (NOAA) were used to train the ANN. Results show that the ANN process achieved an accuracy of 85.71% in validation assessment to predict Tres Picos Mw=8.2 earthquake from 1:30 UTC to 04:00 UTC, approximately 3 hours before the seismic event. For magnitude classification, the ANN achieved an accuracy of 94.60%. The Matthews Correlation Coefficient (MCC) which takes into account all true/false positives and negatives was also evaluated and showed promising results.
{"title":"A Proposed Earthquake Warning System Based on Ionospheric Anomalies Derived From GNSS Measurements and Artificial Neural Networks","authors":"Diego Brum, Graciela Racolte, F. Bordin, Eduardo Kediamosiko Nzinga, M. Veronez, E. Souza, I. É. Koch, L. G. D. Silveira, I. Klein, M. T. Matsuoka, V. F. Rofatto, A. M. Junior","doi":"10.1109/IGARSS.2019.8900197","DOIUrl":"https://doi.org/10.1109/IGARSS.2019.8900197","url":null,"abstract":"The Total Electron Content (TEC) derived from Global Navigation Satellite System (GNSS) data processing has been used as a tool for monitoring earthquakes. The purpose of this study is to bring an alternative approach to the prediction of earthquakes and to determine their magnitudes based on Artificial Neural Networks (ANN) and ionospheric disturbances. For this, the Vertical Total Electron Content (VTEC) data from the National Oceanic and Atmosphere Administration (NOAA) were used to train the ANN. Results show that the ANN process achieved an accuracy of 85.71% in validation assessment to predict Tres Picos Mw=8.2 earthquake from 1:30 UTC to 04:00 UTC, approximately 3 hours before the seismic event. For magnitude classification, the ANN achieved an accuracy of 94.60%. The Matthews Correlation Coefficient (MCC) which takes into account all true/false positives and negatives was also evaluated and showed promising results.","PeriodicalId":13262,"journal":{"name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"9295-9298"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79151357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IGARSS.2019.8900408
Qian-Yu Liao, Wanlai Xue, P. Leng, C. Ren, Zhao‐Liang Li, S. Duan, Maofang Gao, Xiao-Jing Han, Suchuang Di, Yajing Lu
Evapotranspiration (ET) plays a key role for energy transfer and water circulation in the biosphere, lithosphere, hydrosphere, cryosphere and atmosphere. In present study, spatially complete ET over the Heihe river basin, Northwest of China, was estimated from the synergistic use of MODIS (MODerate-resolution Imaging Spectroradiometer) data and CLDAS (China Meteorological Administration Land Data Assimilation) gridded meteorological data from June 1 to September 15 in 2012. For the estimation of ET over clear-sky pixels, a pixel-to-pixel pattern of land surface temperature (LST)-vegetation index (VI) feature space was developed where meteorological data were used to determine the dry and wet edges for each pixel; whereas the traditional Penman-Monteith equation was implemented to obtain ET over clouds pixels. Finally, ground ET measurements collected at two sites (corn and orchard) were used to evaluate the estimated results, root mean square error (RMSE) of 77.2W/m2 and 74.9W/m2 can be obtained for the two sites, respectively, indicating that spatially complete ET can be derived from currently available satellite images and meteorological data.
{"title":"1Estimation of Spatially Complete Land Surface Evapotranspiration Over The Heihe River Basin","authors":"Qian-Yu Liao, Wanlai Xue, P. Leng, C. Ren, Zhao‐Liang Li, S. Duan, Maofang Gao, Xiao-Jing Han, Suchuang Di, Yajing Lu","doi":"10.1109/IGARSS.2019.8900408","DOIUrl":"https://doi.org/10.1109/IGARSS.2019.8900408","url":null,"abstract":"Evapotranspiration (ET) plays a key role for energy transfer and water circulation in the biosphere, lithosphere, hydrosphere, cryosphere and atmosphere. In present study, spatially complete ET over the Heihe river basin, Northwest of China, was estimated from the synergistic use of MODIS (MODerate-resolution Imaging Spectroradiometer) data and CLDAS (China Meteorological Administration Land Data Assimilation) gridded meteorological data from June 1 to September 15 in 2012. For the estimation of ET over clear-sky pixels, a pixel-to-pixel pattern of land surface temperature (LST)-vegetation index (VI) feature space was developed where meteorological data were used to determine the dry and wet edges for each pixel; whereas the traditional Penman-Monteith equation was implemented to obtain ET over clouds pixels. Finally, ground ET measurements collected at two sites (corn and orchard) were used to evaluate the estimated results, root mean square error (RMSE) of 77.2W/m2 and 74.9W/m2 can be obtained for the two sites, respectively, indicating that spatially complete ET can be derived from currently available satellite images and meteorological data.","PeriodicalId":13262,"journal":{"name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","volume":"39 1","pages":"1833-1836"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79289364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Several existing shadow detection methods cannot keep the balance between accuracy and automaticity well. To overcome the weakness, we present a novel method to detect shadow in very high spatial resolution satellite images. First, a new shadow detection index is developed to obtain the shadow ratio map. The initial shadow mask map is then obtained by utilizing the Gaussian mixture mode and the Otsu’s method automatically. Finally, the initial shadow mask map is refined by jointly using the object spectral characteristics and the spatial-correlation relationship between objects. The experimental results performed on different images show that the accuracy and automation of the proposed method are over several state-of-the-art methods.
{"title":"Object-Oriented Automatic and Accurate Shadow Detection for Very High Spatial Resolution Satellite Images","authors":"Yuwei Jin, Wenbo Xu, Donghang Shao, Xixu He, Xueru Zhang","doi":"10.1109/IGARSS.2019.8899763","DOIUrl":"https://doi.org/10.1109/IGARSS.2019.8899763","url":null,"abstract":"Several existing shadow detection methods cannot keep the balance between accuracy and automaticity well. To overcome the weakness, we present a novel method to detect shadow in very high spatial resolution satellite images. First, a new shadow detection index is developed to obtain the shadow ratio map. The initial shadow mask map is then obtained by utilizing the Gaussian mixture mode and the Otsu’s method automatically. Finally, the initial shadow mask map is refined by jointly using the object spectral characteristics and the spatial-correlation relationship between objects. The experimental results performed on different images show that the accuracy and automation of the proposed method are over several state-of-the-art methods.","PeriodicalId":13262,"journal":{"name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","volume":"5 1","pages":"1458-1461"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79493176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/IGARSS.2019.8898084
Zengfeng Zhang, Lian Song, Shulin Deng, Qian Zhang, Ji Jian
The changes of climate variables due to climate change have a great impact on agricultural practices and finally will affect global food security. Thus, it is of great significance to study the responses of crops to climate change, especially for the winter wheat in the North China Plain (NCP), which accounts for about 75% of wheat production in China and is vulnerable to climate change. Knowledge of current changes and responses of crops to climate changes are critical for developing strategies to address climate change challenges. In this paper, the long-term Global Inventory Modelling and Mapping Studies (GIMMS) normalized difference vegetation indices (NDVI) was used to study wheat coverage changes and its responses to heatwave events in the NCP. The results indicate that the NDVI show significant increasing trends for most of the wheat planting areas during 1983-2014. In addition, as indicated by the SHI heatwave index, the heatwave days of almost all the study region show significant increasing trends. The increase of the heatwave days during wheat growing season would strikingly decrease the annual NDVI at a rate of -0.33% when heatwave days increase one day per year.
{"title":"NDVI-Based Winter Wheat Responses to Heatwave in the North China Plain","authors":"Zengfeng Zhang, Lian Song, Shulin Deng, Qian Zhang, Ji Jian","doi":"10.1109/IGARSS.2019.8898084","DOIUrl":"https://doi.org/10.1109/IGARSS.2019.8898084","url":null,"abstract":"The changes of climate variables due to climate change have a great impact on agricultural practices and finally will affect global food security. Thus, it is of great significance to study the responses of crops to climate change, especially for the winter wheat in the North China Plain (NCP), which accounts for about 75% of wheat production in China and is vulnerable to climate change. Knowledge of current changes and responses of crops to climate changes are critical for developing strategies to address climate change challenges. In this paper, the long-term Global Inventory Modelling and Mapping Studies (GIMMS) normalized difference vegetation indices (NDVI) was used to study wheat coverage changes and its responses to heatwave events in the NCP. The results indicate that the NDVI show significant increasing trends for most of the wheat planting areas during 1983-2014. In addition, as indicated by the SHI heatwave index, the heatwave days of almost all the study region show significant increasing trends. The increase of the heatwave days during wheat growing season would strikingly decrease the annual NDVI at a rate of -0.33% when heatwave days increase one day per year.","PeriodicalId":13262,"journal":{"name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","volume":"3 1","pages":"7156-7159"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81559730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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