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those not cited during the following year. Ratio of a journal's items, grouped in three years windows, that have been cited at least once vs. those documents other than research articles, reviews and conference papers. coren apicella, Kuaihelani meaning, One ten thousandth of three million. Research on the classification system of digital land geomorphology of 1:1000000 in China. Google Scholar Zhou C H, Cheng W M, Qian J K, Li B Y, Zhang B P (2009). Acta Geodaetica et Cartographica Sinica, 26(3): 228234. Not every article in a journal is considered primary research and therefore "citable", this chart shows the ratio of a journal's articles including substantial research (research articles, conference papers and reviews) in three year windows vs. A study of texture and description for aerial images. journal self-citations removed) received by a journal's published documents during the three previous years.Įxternal citations are calculated by subtracting the number of self-citations from the total number of citations received by the journal’s documents. Journal Self-citation is defined as the number of citation from a journal citing article to articles published by the same journal.Įvolution of the number of total citation per document and external citation per document (i.e. is easy to use and its included in 11 databases (Acta Geodaetica content. The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric.Įvolution of the total number of citations and journal's self-citations received by a journal's published documents during the three previous years. Google Scholar, Scopus, Bibliotheca Cartographica and GEOBASE include most ma. However, both RTK and PPP monitoring techniques have their limitations, such as limited service coverage or long convergence times. The chart shows the evolution of the average number of times documents published in a journal in the past two, three and four years have been cited in the current year. Currently, Global Navigation Satellite System (GNSS) Real-Time Kinematic positioning (RTK) and Precise Point Positioning (PPP) techniques are widely employed for real-time monitoring of landslides. This indicator counts the number of citations received by documents from a journal and divides them by the total number of documents published in that journal. Q1 (green) comprises the quarter of the journals with the highest values, Q2 (yellow) the second highest values, Q3 (orange) the third highest values and Q4 (red) the lowest values.Įarth and Planetary Sciences (miscellaneous) Furthermore, Cross-polarization (HV) images may be more suitable than co-polarization (HH) images for the extraction of green tide due to their lower noise level.The set of journals have been ranked according to their SJR and divided into four equal groups, four quartiles. The study results show that in the case of GF-3 SAR FSII images, the proposed automatic detection method is superior to the multi-scale segmentation method, as it not only improves the accuracy of green tide detection, but also realizes the automation of green tide extraction. In order to verify the proposed method, the multi-scale segmentation method and the proposed method are both used to detect green tide in China Yellow Sea. In this study, firstly, a sliding window is used to segment the image into multiple sub-images of the same size secondly, the iterative threshold method is used to obtain the green tide and seawater samples that have the theoretical bimodal structure from each sub-image then, using the histogram bimodal method, the detection threshold is calculated automatically and finally, using the threshold segmentation, the green tide areas are extracted from the images. Based on the iterative threshold method and the histogram bimodal method, this paper presents a new method for the automatic detection of green tide that uses adaptive thresholds for Gaofen-3 (GF-3) satellite dual polarization SAR remote sensing images. Due to the differences in brightness and noise across the different areas in an image, it is difficult to use the same threshold in order to extract all the green tide information from the image. SAR images are therefore an effective supplementary data for the monitoring of green tide. Synthetic aperture radar (SAR) on the other hand, is able to realize all-day and all-weather observation due to a lower sensitivity to clouds, rain and fog. Traditional optical images are not suitable for the all-weather observation of green tide due to the fact that they are greatly affected by clouds.
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