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1
Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time Series
Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time Series
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Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time Series

PLoS One, Mar 2016, Vol.11(3), p.e0147121 [Peer Reviewed Journal]

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Monitoring Deforestation at Sub-Annual Scales as Extreme Events in Landsat Data Cubes
Monitoring Deforestation at Sub-Annual Scales as Extreme Events in Landsat Data Cubes
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Monitoring Deforestation at Sub-Annual Scales as Extreme Events in Landsat Data Cubes

Remote Sensing, 0, 2016, Vol.8(8), pp.651-651 [Peer Reviewed Journal]

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3
Characterizing Tropical Forest Cover Loss Using Dense Sentinel-1 Data and Active Fire Alerts
Characterizing Tropical Forest Cover Loss Using Dense Sentinel-1 Data and Active Fire Alerts
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Characterizing Tropical Forest Cover Loss Using Dense Sentinel-1 Data and Active Fire Alerts

Remote Sensing, 2018, Vol.10(5), pp.urn:issn:2072-4292 [Peer Reviewed Journal]

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4
Monitoring Forest Phenology and Leaf Area Index with the Autonomous, Low-Cost Transmittance Sensor PASTiS-57
Monitoring Forest Phenology and Leaf Area Index with the Autonomous, Low-Cost Transmittance Sensor PASTiS-57
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Monitoring Forest Phenology and Leaf Area Index with the Autonomous, Low-Cost Transmittance Sensor PASTiS-57

Remote Sensing, 2018, Vol.10(7), pp.urn:issn:2072-4292 [Peer Reviewed Journal]

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5
Using Space-Time Features to Improve Detection of Forest Disturbances from Landsat Time Series
Using Space-Time Features to Improve Detection of Forest Disturbances from Landsat Time Series
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Using Space-Time Features to Improve Detection of Forest Disturbances from Landsat Time Series

Remote Sensing, Jun 2017, Vol.9(6) [Peer Reviewed Journal]

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6
A Bayesian Approach to Combine Landsat and ALOS PALSAR Time Series for Near Real-Time Deforestation Detection
A Bayesian Approach to Combine Landsat and ALOS PALSAR Time Series for Near Real-Time Deforestation Detection
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A Bayesian Approach to Combine Landsat and ALOS PALSAR Time Series for Near Real-Time Deforestation Detection

Remote Sensing, 0, 2015, Vol.7(5), pp.4973-4996 [Peer Reviewed Journal]

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7
Evaluating the Potential of PROBA-V Satellite Image Time Series for Improving LC Classification in Semi-Arid African Landscapes
Evaluating the Potential of PROBA-V Satellite Image Time Series for Improving LC Classification in Semi-Arid African Landscapes
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Evaluating the Potential of PROBA-V Satellite Image Time Series for Improving LC Classification in Semi-Arid African Landscapes

Remote Sensing, 2016, p.987 [Peer Reviewed Journal]

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8
Near real-time disturbance detection using satellite image time series
Near real-time disturbance detection using satellite image time series
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Near real-time disturbance detection using satellite image time series

Remote Sensing of Environment, August 2012, Vol.123, pp.98-108 [Peer Reviewed Journal]

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9
Detecting Leaf Pulvinar Movements on NDVI Time Series of Desert Trees: A New Approach for Water Stress Detection
Detecting Leaf Pulvinar Movements on NDVI Time Series of Desert Trees: A New Approach for Water Stress Detection
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Detecting Leaf Pulvinar Movements on NDVI Time Series of Desert Trees: A New Approach for Water Stress Detection

PLoS One, Sep 2014, p.e106613 [Peer Reviewed Journal]

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10
Consistent forest change maps 1981-2000 from the AVHRR time series: Case studies for South America and Indonesia
Consistent forest change maps 1981-2000 from the AVHRR time series: Case studies for South America and Indonesia
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Consistent forest change maps 1981-2000 from the AVHRR time series: Case studies for South America and Indonesia

2015 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (Multi-Temp), July 2015, pp.1-4

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by this Author/Contributor:

  1. Herold, M
  2. Verbesselt, J
  3. Verbesselt, Jan
  4. Herold, Martin
  5. Reiche, J.

on this subject:

  1. Remote Sensing
  2. Forests
  3. Time Series
  4. Satellites
  5. Deforestation

All text is © British Library Board and is available under a Creative Commons Attribution Licence, except where otherwise stated.

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