Institution
Michigan Technological University
Education•Houghton, Michigan, United States•
About: Michigan Technological University is a education organization based out in Houghton, Michigan, United States. It is known for research contribution in the topics: Population & Volcano. The organization has 8023 authors who have published 17422 publications receiving 481780 citations. The organization is also known as: MTU & Michigan Tech.
Papers published on a yearly basis
Papers
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TL;DR: In this article, an alternative to the FI-MS technique is presented which offers similar results with a more widely available bench-top electron impact (EI) mass spectrometer.
110 citations
TL;DR: In this paper, a modified expanding cavity model was used to predict the plastic zone size characterized by the shear bands and to identify the stress components responsible for the evolution of various types of shear band.
109 citations
TL;DR: In this article, the authors present results from an investigation of soot formation in turbulent, non-premixed, C{sub 2}H{sub 4}/air jet flames.
109 citations
TL;DR: In this article, the authors pointed out some problems with Simpson et al.'s analysis and re-state the conditions under which the reverse absorption algorithm is likely to succeed in detecting volcanic ash clouds from meteorological clouds.
109 citations
TL;DR: In this article, the authors compared the accuracy and cost of a LiDAR-based inventory summarized at the stand level with traditional stand exams for structural and volume attributes, and found that the accuracy of the summary was comparable to those obtained through traditional exams.
Abstract: Foresters are increasingly interested in remote sensing data because they provide an overview of landscape conditions, which is impractical with field sample data alone. Light Detection and Ranging (LiDAR) provides exceptional spatial detail of forest structure, but difficulties in processing LiDAR data have limited their application beyond the research community. Another obstacle to operational use of LiDAR data has been the high cost of data collection. Our objectives in this study were to summarize, at the stand level, both LiDAR- and Landsat (satellite)-based predictions of some common structural and volume attributes and to compare the cost of obtaining such summaries with those obtained through traditional stand exams. We found that the accuracy and cost of a LiDAR-based inventory summarized at the stand level was comparable to traditional stand exams for structural attributes. However, the LiDAR data were able to provide information across a much larger area than the stand exams alone.
109 citations
Authors
Showing all 8104 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Anil K. Jain | 183 | 1016 | 192151 |
| Marc W. Kirschner | 162 | 457 | 102145 |
| Yonggang Huang | 136 | 797 | 69290 |
| Hong Wang | 110 | 1633 | 51811 |
| Fei Wang | 107 | 1824 | 53587 |
| Emanuele Bonamente | 105 | 219 | 40826 |
| Haoshen Zhou | 104 | 519 | 37609 |
| Nicholas J. Turro | 104 | 1131 | 53827 |
| Yang Shao-Horn | 102 | 458 | 49463 |
| Richard P. Novick | 99 | 295 | 34542 |
| Markus J. Buehler | 95 | 609 | 33054 |
| Martin L. Yarmush | 91 | 702 | 34591 |
| Alan Robock | 90 | 346 | 27022 |
| Patrick M. Schlievert | 90 | 444 | 32037 |
| Lonnie O. Ingram | 88 | 316 | 22217 |