Improving capacity for large-area monitoring of forest disturbance and recovery

Dissertationes Forestales ◽

10.14214/df.272 ◽

2019 ◽

Vol 2019 (272) ◽

Author(s):

Joanne White

Keyword(s):

Forest Disturbance ◽

Disturbance And Recovery ◽

Area Monitoring

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Remote Sensing Characterization of Upper Great Lakes Forest Disturbance and Recovery to Improve Modeled Impacts on Land Surface Energetic and Hydrologic Fluxes

10.13031/cc.20152143978 ◽

2015 ◽

Keyword(s):

Remote Sensing ◽

Great Lakes ◽

Land Surface ◽

Forest Disturbance ◽

Upper Great Lakes ◽

Disturbance And Recovery

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Design and development of wireless mesh test-bed for large area monitoring

2016 International Conference on Circuits, Controls, Communications and Computing (I4C) ◽

10.1109/cimca.2016.8053295 ◽

2016 ◽

Author(s):

Moirangthem Sailash Singh ◽

Pramod Jayaram ◽

Viswanath Talasila

Keyword(s):

Test Bed ◽

Design And Development ◽

Wireless Mesh ◽

Area Monitoring

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Moths at tropical forest margins — how mega-diverse insect assemblages respond to forest disturbance and recovery

Stability of Tropical Rainforest Margins - Environmental Science and Engineering ◽

10.1007/978-3-540-30290-2_3 ◽

2007 ◽

pp. 37-58 ◽

Author(s):

Konrad Fiedler ◽

Nadine Hilt ◽

Gunnar Brehm ◽

Christian H. Schulze

Keyword(s):

Tropical Forest ◽

Forest Disturbance ◽

Disturbance And Recovery

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Large area monitoring with a MODIS-based Disturbance Index (DI) sensitive to annual and seasonal variations

Remote Sensing of Environment ◽

10.1016/j.rse.2009.02.015 ◽

2009 ◽

Vol 113 (6) ◽

pp. 1250-1261 ◽

Author(s):

Nicholas C. Coops ◽

Michael A. Wulder ◽

Donald Iwanicka

Keyword(s):

Seasonal Variations ◽

Disturbance Index ◽

Area Monitoring

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Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms

Remote Sensing of Environment ◽

10.1016/j.rse.2010.07.008 ◽

2010 ◽

Vol 114 (12) ◽

pp. 2897-2910 ◽

Author(s):

Robert E. Kennedy ◽

Zhiqiang Yang ◽

Warren B. Cohen

Keyword(s):

Time Series ◽

Forest Disturbance ◽

Temporal Segmentation ◽

Segmentation Algorithms ◽

Disturbance And Recovery

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CNT Enabled Fabric Sensors for Highly Sensitive and Large-area Monitoring of Polymeric Composites

Structural Health Monitoring 2017 ◽

10.12783/shm2017/14067 ◽

2017 ◽

Author(s):

YONG WANG ◽

YUJIANG ZHAI ◽

GUANTAO WANG ◽

SIDA LUO

Keyword(s):

Polymeric Composites ◽

Highly Sensitive ◽

Area Monitoring

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A System for Rapid Large-area Monitoring of Gamma Dose Rates in the Environment Based on MCP-N (LiF:Mg,Cu,P) TL Detectors

Radiation Protection Dosimetry ◽

10.1093/oxfordjournals.rpd.a005968 ◽

2002 ◽

Vol 101 (1) ◽

pp. 205-210 ◽

Author(s):

M. Budzanowski ◽

P. Olko ◽

E. Ryba ◽

U. Wo_nicka

Keyword(s):

Gamma Dose Rates ◽

Area Monitoring

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A. G. Marshall & M. D. Swaine (eds). 1992. Tropical rain forest: disturbance and recovery. Proceedings of Royal Society discussion meeting 18/19 091991. The Royal Society, London. 132 (325–457) pages. ISBN 0-85403-458-7. Price: £19.95.

Journal of Tropical Ecology ◽

10.1017/s0266467400007185 ◽

1993 ◽

Vol 9 (2) ◽

pp. 211-212

Author(s):

Thomas T. Struhsaker

Keyword(s):

Rain Forest ◽

Tropical Rain Forest ◽

Royal Society ◽

Forest Disturbance ◽

Disturbance And Recovery

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Tropical rain forest: Disturbance and recovery

Trends in Ecology & Evolution ◽

10.1016/0169-5347(93)90167-n ◽

1993 ◽

Vol 8 (2) ◽

pp. 72-73

Author(s):

Robert J.A. Goodland

Keyword(s):

Rain Forest ◽

Tropical Rain Forest ◽

Forest Disturbance ◽

Disturbance And Recovery

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Examining Forest Disturbance and Recovery in the Subtropical Forest Region of Zhejiang Province Using Landsat Time-Series Data

Remote Sensing ◽

10.3390/rs9050479 ◽

2017 ◽

Vol 9 (5) ◽

pp. 479 ◽

Author(s):

Shanshan Liu ◽

Xinliang Wei ◽

Dengqiu Li ◽

Dengsheng Lu

Keyword(s):

Time Series ◽

Time Series Data ◽

Forest Disturbance ◽

Subtropical Forest ◽

Zhejiang Province ◽

Series Data ◽

Forest Region ◽

Disturbance And Recovery

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