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Erik Lindquist

Researcher at Food and Agriculture Organization

Publications -  21
Citations -  2246

Erik Lindquist is an academic researcher from Food and Agriculture Organization. The author has contributed to research in topics: Land cover & Earth observation. The author has an hindex of 13, co-authored 19 publications receiving 1758 citations. Previous affiliations of Erik Lindquist include South Dakota State University.

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Dynamics of global forest area: Results from the FAO Global Forest Resources Assessment 2015

TL;DR: The Global Forest Resources Assessment 2015 (FRA 2015) of the Food and Agriculture Organization of the United Nations FRA 2015 was based on responses to surveys by individual countries using a common reporting framework, agreed definitions and reporting standards as discussed by the authors.
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Global forest area disturbance from fire, insect pests, diseases and severe weather events

TL;DR: A global analysis of forest area affected by fire, significant insect pest outbreaks, diseases and severe weather reported by countries as part of the Global Forest Resources Assessment 2015 is presented in this paper.
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Assessing change in national forest monitoring capacities of 99 tropical countries

TL;DR: In this paper, the authors assess the current status and recent changes in national forest monitoring and reporting capacities in 99 tropical countries, using the Food and Agriculture Organization of the United Nations (FAO) Forest Resources Assessment (FRA) 2015 data, complemented with FRA 2010 and FRA 2005 data.
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Time-series analysis of multi-resolution optical imagery for quantifying forest cover loss in Sumatra and Kalimantan, Indonesia

TL;DR: This paper analyzed all Landsat 7 imagery with <50% cloud cover and data and products from the Moderate Resolution Imaging Spectroradiometer (MODIS) to quantify forest cover loss for Sumatra and Kalimantan from 2000 to 2005 and demonstrated that time-series approaches examining all good land observations are more accurate in mapping forest cover change in Indonesia than change maps based on image composites.
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Pre-processing of a sample of multi-scene and multi-date Landsat imagery used to monitor forest cover changes over the tropics

TL;DR: In this article, the TREES-3 project has processed more than 12,000 Landsat TM and ETM+ data subsets systematically distributed over the tropics, and the results show that the haze correction algorithm has improved the visual appearance of the image and significantly corrected the digital numbers for the red band.