LEDAPS: Mapping north American disturbance from the landsat record

Robert Wolfe; Jeffrey Masek; Nazmi Saleous; Forrest Hall

LEDAPS: Mapping north American disturbance from the landsat record

Robert Wolfe, Jeffrey Masek, Nazmi Saleous, Forrest Hall

Research output: Contribution to conference › Paper › peer-review

Abstract

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project is creating a record of forest disturbance and regrowth for North America from the Landsat satellite record, in support of the carbon modeling activities. LEDAPS relies on the decadal Landsat GeoCover data set supplemented by dense image time series for selected locations. Imagery is first atmospherically corrected to surface reflectance, and then change detection algorithms are used to extract disturbance area, type, and frequency. Reuse of the MODIS Land processing system (MODAPS) architecture allows rapid throughput of over 1500 MSS, TM, and ETM+ scenes. Initial ("Beta") surface reflectance products are currently available for testing, and initial disturbance products will be available by the end of 2004.

Original language	English
Pages	1-4
Number of pages	4
Publication status	Published - 2004
Externally published	Yes
Event	2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 - Anchorage, AK, United States Duration: Sept 20 2004 → Sept 24 2004

Other

Other	2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004
Country/Territory	United States
City	Anchorage, AK
Period	9/20/04 → 9/24/04

Keywords

Atmospheric correction
Carbon
Component
Disturbance
Ecosystems
Landsat
Remote sensing

ASJC Scopus subject areas

Computer Science Applications
General Earth and Planetary Sciences

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

LEDAPS: Mapping north American disturbance from the landsat record. / Wolfe, Robert; Masek, Jeffrey; Saleous, Nazmi et al.
2004. 1-4 Paper presented at 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004, Anchorage, AK, United States.

Research output: Contribution to conference › Paper › peer-review

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title = "LEDAPS: Mapping north American disturbance from the landsat record",

abstract = "The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project is creating a record of forest disturbance and regrowth for North America from the Landsat satellite record, in support of the carbon modeling activities. LEDAPS relies on the decadal Landsat GeoCover data set supplemented by dense image time series for selected locations. Imagery is first atmospherically corrected to surface reflectance, and then change detection algorithms are used to extract disturbance area, type, and frequency. Reuse of the MODIS Land processing system (MODAPS) architecture allows rapid throughput of over 1500 MSS, TM, and ETM+ scenes. Initial ({"}Beta{"}) surface reflectance products are currently available for testing, and initial disturbance products will be available by the end of 2004.",

keywords = "Atmospheric correction, Carbon, Component, Disturbance, Ecosystems, Landsat, Remote sensing",

author = "Robert Wolfe and Jeffrey Masek and Nazmi Saleous and Forrest Hall",

year = "2004",

language = "English",

pages = "1--4",

note = "2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 ; Conference date: 20-09-2004 Through 24-09-2004",

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T2 - 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004

AU - Wolfe, Robert

AU - Masek, Jeffrey

AU - Saleous, Nazmi

AU - Hall, Forrest

PY - 2004

Y1 - 2004

N2 - The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project is creating a record of forest disturbance and regrowth for North America from the Landsat satellite record, in support of the carbon modeling activities. LEDAPS relies on the decadal Landsat GeoCover data set supplemented by dense image time series for selected locations. Imagery is first atmospherically corrected to surface reflectance, and then change detection algorithms are used to extract disturbance area, type, and frequency. Reuse of the MODIS Land processing system (MODAPS) architecture allows rapid throughput of over 1500 MSS, TM, and ETM+ scenes. Initial ("Beta") surface reflectance products are currently available for testing, and initial disturbance products will be available by the end of 2004.

AB - The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project is creating a record of forest disturbance and regrowth for North America from the Landsat satellite record, in support of the carbon modeling activities. LEDAPS relies on the decadal Landsat GeoCover data set supplemented by dense image time series for selected locations. Imagery is first atmospherically corrected to surface reflectance, and then change detection algorithms are used to extract disturbance area, type, and frequency. Reuse of the MODIS Land processing system (MODAPS) architecture allows rapid throughput of over 1500 MSS, TM, and ETM+ scenes. Initial ("Beta") surface reflectance products are currently available for testing, and initial disturbance products will be available by the end of 2004.

KW - Atmospheric correction

KW - Carbon

KW - Component

KW - Disturbance

KW - Ecosystems

KW - Landsat

KW - Remote sensing

UR - http://www.scopus.com/inward/record.url?scp=15944419224&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=15944419224&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:15944419224

SP - 1

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Y2 - 20 September 2004 through 24 September 2004

ER -

LEDAPS: Mapping north American disturbance from the landsat record

Abstract

Other

Keywords

ASJC Scopus subject areas

UN SDGs

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