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Готові списки джерел за темами / RemoteSensing

Добірка наукової літератури з теми "RemoteSensing"

Автор: Grafiati

Опубліковано: 10 грудня 2022

Оновлено: 28 січня 2023

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Статті в журналах з теми "RemoteSensing"

1

Srivastava, Hari Shanker, and Santvana Nigam. "https://www.cloudpublications.org/journals/index.php/RemoteSensing/article/view/508." International Journal of Advanced Remote Sensing and GIS 9, no. 1 (September 29, 2020): 3384–404. http://dx.doi.org/10.23953/cloud.ijarsg.480.

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2

David Mayunga, Selassie. "Monitoring of Land Use/Cover Change Using Remote Sensing and GIS techniques: A case study of Loliondo Game Controlled Area, Tanzania." Trends Journal of Sciences Research 3, no. 1 (July 26, 2018): 36–50. http://dx.doi.org/10.31586/remotesensing.0301.04.

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3

Takahashi, Masayuki, Motoaki Kishino, and Joji Ishizaka. "Organization for Monitoring of Marine Organisms by Remotesensing and its International Collaboration." Oceanography in Japan 4, no. 4 (1995): 355–60. http://dx.doi.org/10.5928/kaiyou.4.355.

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4

MILOVANOVIĆ, Milan. "APPLICATION OF REMOTESENSING FOR WILDFIRES BURN SEVERITY DETECTION - CASESTUDY OF TARA MOUNTAIN." PROCEEDINGS International Scientific Symposium NEW TRENDS IN GEOGRAPHY October 3-4, 2019 Ohrid 2019 (2019): 157–64. http://dx.doi.org/10.37658/procgeo19157m.

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5

Asadi, SS, B. V. T. Vasantha Rao, M. V. Raju, and M. Anand Sagar. "Identification of Ambient Air Pollution Prevention Zones Using Remotesensing and GIS:A Model Study." Current World Environment 6, no. 2 (December 25, 2006): 207–15. http://dx.doi.org/10.12944/cwe.6.2.02.

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6

Lange, M. A., N. Blindow, B. Breuer, K. Grosfeld, T. Kleiner, C. O. Mohrholz, M. Nicolaus, C. Oelke, H. Sandhäger, and M. Thoma. "Numerical model studies of Antarctic ice-sheet–ice-shelf–ocean systems and ice caps." Annals of Glaciology 41 (2005): 111–20. http://dx.doi.org/10.3189/172756405781813186.

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AbstractThe cryosphere is an essential component of the global climate system, equally affecting climate processes significantly and being subject, and particularly sensitive, to changes in climate conditions. Numerical models are an important tool for assessing climate-change impacts on the Antarctic ice–sheet–ice–shelf–ocean system. They not only complement field and satellite remotesensing investigations but are often the only feasible alternative for addressing some of the important parameters and processes. Over the last few years, our group has made significant progress in developing and applying innovative numerical methods. In this paper, we provide a brief overview of some of the methods employed and the major results obtained for a number of case studies in the Atlantic sector of Antarctica.

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7

ZHAO Xiao, 赵晓, 侯晴宇 HOU Qingyu, 梁冰冰 LIANG Bingbing, and 张伟 ZHANG Wei. "A method for cloud detection in high-resolution remotesensing image based on multi-attribute fusion." Optical Technique 40, no. 2 (2014): 145–50. http://dx.doi.org/10.3788/gxjs20144002.0145.

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8

P. Madesh, P. Madesh, and N. Ravikumar N. Ravikumar. "Water Resource Management through Remotesensing and GIS in a Watershed of Gundlupet Taluk, Chamarajanagar District, Karnatak, India." Indian Journal of Applied Research 2, no. 1 (October 1, 2011): 50–52. http://dx.doi.org/10.15373/2249555x/oct2012/16.

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9

Raj, Nithu, and B. Gurugnanam. "STUDIES ON COASTAL GEOMORPHOLOGICAL LANDFORMS IN THE SOUTHEASTCOAST OF THIRUVALLUR COASTAL STRETCH, USING REMOTESENSING AND GIS TECHNIQUES." International Journal of Advanced Research 5, no. 3 (March 31, 2017): 1859–66. http://dx.doi.org/10.21474/ijar01/3702.

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10

Xie, Xiuchuan, Tao Yang, DongDong Li, Zhi Li, and Yanning Zhang. "Hierarchical Clustering-Aligning Framework Based Fast Large-Scale 3D Reconstruction Using Aerial Imagery." Remote Sensing 11, no. 3 (February 5, 2019): 315. http://dx.doi.org/10.3390/rs11030315.

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With extensive applications of Unmanned Aircraft Vehicle (UAV) in the field of remotesensing, 3D reconstruction using aerial images has been a vibrant area of research. However,fast large-scale 3D reconstruction is a challenging task. For aerial image datasets, large scale meansthat the number and resolution of images are enormous, which brings significant computationalcost to the 3D reconstruction, especially in the process of Structure from Motion (SfM). In thispaper, for fast large-scale SfM, we propose a clustering-aligning framework that hierarchicallymerges partial structures to reconstruct the full scene. Through image clustering, an overlappingrelationship between image subsets is established. With the overlapping relationship, we proposea similarity transformation estimation method based on joint camera poses of common images.Finally, we introduce the closed-loop constraint and propose a similarity transformation-based hybridoptimization method to make the merged complete scene seamless. The advantage of the proposedmethod is a significant efficiency improvement without a marginal loss in accuracy. Experimentalresults on the Qinling dataset captured over Qinling mountain covering 57 square kilometersdemonstrate the efficiency and robustness of the proposed method.

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Більше джерел

Дисертації з теми "RemoteSensing"

1

Unal, Alper. "Measurement, analysis, and modeling of on-road vehicle emissions using remotesensing." Raleigh, NC : North Carolina State University, 1999. http://www.lib.ncsu.edu/etd/public/etd-1142102749941461/etd.pdf.

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2

Yang, Bo. "Assimilation of multi-scale thermal remote sensing data using spatio-temporal cokriging method." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1377868463.

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3

Гаврись, Андрій Петрович, and Роксолана Моренюк. "Method of fire areas localization on the basis of remotesensing data." Thesis, 2019. http://sci.ldubgd.edu.ua:8080/jspui/handle/123456789/8429.

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4

Ho-ChinYu and 游和親. "Development of a solar powered wireless remotesensing system for oil leakage." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/05594413208996007346.

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Книги з теми "RemoteSensing"

1

Bangkok), International Symposium on Remote Sensing of Environment (23rd 1990. Proceedings of the twenty-third Symposium on RemoteSensing of Environment, 18-25 April 1990. Ann Arbor: Environmental Research Institute of Michigan, 1990.

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2

Sandroni, S. Sulphur dioxide mass-flow evaluations in the Fos-Berre industrial area: 6th CEC campaign on remotesensing - June 1983. Luxembourg: Commission of the European Communities, 1985.

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3

International Geoscience and Remote Sensing Symposium (1989 Vancouver). Special issue on the 1989 International Geoscience and RemoteSensing Symposium (IGARSS '89): Quantitative remote sensing : an economic tool for the nineties. New York: IEEE, 1990.

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Тези доповідей конференцій з теми "RemoteSensing"

1

Yuan, Kai-guo, and Tan Liu. "A study of natural recovery of vegetation in Wenchuan Earthquake affected zone via remotesensing." In 2014 3rd International Workshop on Earth Observation and Remote Sensing Applications (EORSA). IEEE, 2014. http://dx.doi.org/10.1109/eorsa.2014.6927871.

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2

Carbonell-Rivera, Juan Pedro, Javier Estornell, Luis Á. Ruiz, Alfonso Abad, Bettina Felten, and Jesús Torralba. "A REVIEW OF THE USE OF REMOTE SENSING FOR MONITORING AND QUANTIFYING CARBON SEQUESTRATION IN MARGINAL LANDS." In 3rd Congress in Geomatics Engineering. Valencia: Universitat Politècnica de València, 2021. http://dx.doi.org/10.4995/cigeo2021.2021.12694.

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In recent years, Remote Sensing (RS) and its derived products have been used as a key tool for the detection, monitoring,management and future use of Marginal Lands (ML). Currently, there is no single, universally accepted definition of theterm and there is a wide variety of synonyms. In this paper, we conduct a compilation of synonyms and meanings thatencompass the term, as well as propose a definition. To reach this objective, an overview of the state of the art of ML isdone, visualising trends by science maps, based on bibliographic data of established research journals, found in GoogleScholar, Web of Science (WoS) and Scopus search engines. The bibliographic review carried out shows that the study ofML has traditionally been carried out with an ad hoc basis focused on the objective to be achieved, this aspect and otherknowledge gaps are discussed to analyse the global study of ML. Due to the broad spectrum of uses in which ML havebeen studied, the work has been focused on RS for monitoring and characterizing ML, focusing on two different aspects:(i) satellite monitoring of marginal lands; and (ii) determining carbon sequestration potential of marginal lands using remotesensing.

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