Toward operational monitoring of forest cover change in California using multitemporal remote sensing data

John Rogan; Janet Franklin; Doug Stow; Lisa Levien; Chris Fischer

Toward operational monitoring of forest cover change in California using multitemporal remote sensing data

John Rogan, Janet Franklin, Doug Stow, Lisa Levien, Chris Fischer

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper presents preliminary results of research to improve upon an existing operational forest change detection monitoring strategy in California. Comparisons were made between Landsat 5 TM and Landsat 7 ETM scene normalization techniques (absolute versus, relative). Prior to normalization, scenes containing wildfire smoke plumes were successfully corrected using a space-varying haze equalization algorithm. Simple dark object subtraction provided improved performance over relative (pseudo-invariant feature) approaches. A decision tree classifier produced high change map overall accuracy (86%) for five categories of forest cover change.

Original language	English (US)
Title of host publication	International Geoscience and Remote Sensing Symposium (IGARSS)
Pages	3090-3092
Number of pages	3
Volume	7
State	Published - 2001
Externally published	Yes
Event	2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001) - Sydney, NSW, Australia Duration: Jul 9 2001 → Jul 13 2001

Other

Other	2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001)
Country/Territory	Australia
City	Sydney, NSW
Period	7/9/01 → 7/13/01

ASJC Scopus subject areas

Software
Geology

Cite this

@inproceedings{0f7e73fceca341f08704b92a9f529455,

title = "Toward operational monitoring of forest cover change in California using multitemporal remote sensing data",

abstract = "This paper presents preliminary results of research to improve upon an existing operational forest change detection monitoring strategy in California. Comparisons were made between Landsat 5 TM and Landsat 7 ETM scene normalization techniques (absolute versus, relative). Prior to normalization, scenes containing wildfire smoke plumes were successfully corrected using a space-varying haze equalization algorithm. Simple dark object subtraction provided improved performance over relative (pseudo-invariant feature) approaches. A decision tree classifier produced high change map overall accuracy (86%) for five categories of forest cover change.",

author = "John Rogan and Janet Franklin and Doug Stow and Lisa Levien and Chris Fischer",

year = "2001",

language = "English (US)",

volume = "7",

pages = "3090--3092",

booktitle = "International Geoscience and Remote Sensing Symposium (IGARSS)",

note = "2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001) ; Conference date: 09-07-2001 Through 13-07-2001",

}

TY - GEN

T1 - Toward operational monitoring of forest cover change in California using multitemporal remote sensing data

AU - Rogan, John

AU - Franklin, Janet

AU - Stow, Doug

AU - Levien, Lisa

AU - Fischer, Chris

PY - 2001

Y1 - 2001

N2 - This paper presents preliminary results of research to improve upon an existing operational forest change detection monitoring strategy in California. Comparisons were made between Landsat 5 TM and Landsat 7 ETM scene normalization techniques (absolute versus, relative). Prior to normalization, scenes containing wildfire smoke plumes were successfully corrected using a space-varying haze equalization algorithm. Simple dark object subtraction provided improved performance over relative (pseudo-invariant feature) approaches. A decision tree classifier produced high change map overall accuracy (86%) for five categories of forest cover change.

AB - This paper presents preliminary results of research to improve upon an existing operational forest change detection monitoring strategy in California. Comparisons were made between Landsat 5 TM and Landsat 7 ETM scene normalization techniques (absolute versus, relative). Prior to normalization, scenes containing wildfire smoke plumes were successfully corrected using a space-varying haze equalization algorithm. Simple dark object subtraction provided improved performance over relative (pseudo-invariant feature) approaches. A decision tree classifier produced high change map overall accuracy (86%) for five categories of forest cover change.

UR - http://www.scopus.com/inward/record.url?scp=0035570779&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0035570779&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0035570779

VL - 7

SP - 3090

EP - 3092

BT - International Geoscience and Remote Sensing Symposium (IGARSS)

T2 - 2001 International Geoscience and Remote Sensing Symposium (IGARSS 2001)

Y2 - 9 July 2001 through 13 July 2001

ER -

Toward operational monitoring of forest cover change in California using multitemporal remote sensing data

Abstract

Other

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this