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International Journal of Remote Sensing is a peer-reviewed journal published by Taylor & Francis, covering Remote Sensing in Agriculture, Remote-Sensing Image Classification, Remote Sensing and LiDAR Applications. Over its lifetime it has published 14,891 papers, which have received 592,431 citations.
| Publisher | Taylor & Francis |
|---|---|
| Reference style | Author–year (Chicago, T&F) Author–year — (Smith, 2023) in the text Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." International Journal of Remote Sensing 12 (3): 45–58.
Formats any DOI in International Journal of Remote Sensing style. No sign-up. |
| Publishes research in | Remote Sensing in Agriculture Remote-Sensing Image Classification Remote Sensing and LiDAR Applications Remote Sensing and Land Use Land Use and Ecosystem Services |
| ISSN | 0143-1161 |
| Citation impact (2-yr) | 2.54 |
| h-index | 267 |
| i10-index | 8,951 |
| Top institutions publishing here | Chinese Academy of Sciences |
| Journal website | www.tandfonline.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Abstract The Normalized Difference Water Index (NDWI) is a new method that has been developed to delineate open water features and enhance their presence in remotely-sensed digital imagery. The NDWI makes use of reflected near-infrared radiation and visible green light to enhance the presence of such features while eliminating the presence of soil and terrestrial…
La presente investigación busca identificar el cambio del cauce del Río Amazonas entre los años 2015 a 2022 y los efectos del mismo mediante análisis y modelamiento de la dinámica del afluente, no solo sobre las riveras y llanuras aledañas, sino especialmente sobre el Municipio de Puerto Nariño. El municipio según lo documentado, desde el…
Abstract A variety of procedures for change detection based on comparison of multitemporal digital remote sensing data have been developed. An evaluation of results indicates that various procedures of change detection produce different maps of change even in the same environment.
Image classification is a complex process that may be affected by many factors. This paper examines current practices, problems, and prospects of image classification. The emphasis is placed on the summarization of major advanced classification approaches and the techniques used for improving classification accuracy. In addition, some important issues affecting classification performance are discussed. This…
Abstract Growing an ensemble of decision trees and allowing them to vote for the most popular class produced a significant increase in classification accuracy for land cover classification. The objective of this study is to present results obtained with the random forest classifier and to compare its performance with the support vector machines (SVMs) in…
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