A METHODOLOGY TO SELECT PHENOLOGICALLY SUITABLE LANDSAT SCENES FOR FOREST CHANGE DETECTION

IGARSS 2011 , Jul, 27, 2011

Do-Hyung Kim, Raghuram Narashiman, Joseph O. Sexton, Chengquan Huang, John R. Townshend

Global Land Cover Facility, University of Maryland - College Park

CONTENT• 1. Background• 2. DATA• 3. METHOD• 4. RESULT• 5. DISCUSSION• 6. REFERENCE

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Background• Influence of phenology on forest change detection

– example of path 116/ row 32 (Korea)

• Profile based techniques by time series data can resolve the issue of influence of phenology on change detection performance (Coppin et. al., 2004)

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Sep 2 1999

Oct 7 2006

Aug 28 2006

Change detection

Original Scene

Replacement Scene

Change detection

Aug 28 2006

False forest change by seasonality

Background• Global Land Survey

– Global, orthorectified, typically cloud-free Landsat imagery centered on the years 1975, 1990, 2000 and 2005 with a preference for leaf-on conditions(Gutman, 2008).

• LARGE AREA SCENE SELECTION INTERFACE (LASSI)– Global Land Survey 2005 is a dataset which is selected using such an

automated method, LARGE AREA SCENE SELECTION INTERFACE (LASSI) (Franks, 2002).

• An automated scene selection method which specialized for forest cover change detection is needed– Seasonality is not the only one parameter for LASSI.– GLS is not only for forest cover change analysis.

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DATA• MODIS data

– MOD13C1 : 5km NDVI dataset for the years 2000-2009 (Huete et. al., 2002)• Land cover data

– MOD12C1 : 5km Land Cover dataset (Friedl el. al., 2002) consists of the IGBP classification system from which the % forest, % evergreen, % deciduous and % crop layers were extracted.

• Landsat METADATA– Metadata of globally available Landsat scenes dating back from the 1970s to

present(http://landsat.usgs.gov/consumer.php )

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Spatial TemporalData Resolution Resolution Extent

MODIS NDVI(MOD13C1) 5 km 16 d 2000-2009

MODIS Land Cover(MOD12C1) 5 km 1 yr 2001

METHOD

• DATA process

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S = pixels > 40% deciduous & number of samples > 15 from MOD13C1

When I = composite (1<= i <=23) and j = year (2000 <= j <= 2009)

Median value of the above samples for each ith composite at jth year

NDVIij = Median(S)

10 year norm, NORM at each i composite

NORMi = Median (NDVIij)

METHOD

• Filtering

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NDVIij value which is greater or smaller than NORMi +- σ(NDVIij) is replaced by NORMi

NDVI

Composites

METHOD

• Peak growing season selection• SOP and EOP

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METHOD

• Scene selection – web based app

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User input

Perform Search Metadata

Search results

Search Conditions – Date/Month/Year, Quality, Cloud, Path/Row

UNZIP

Shown as Table

Landsat 7 ETM+ (SLC-on)Landsat 7 ETM+ (SLC-off)Landsat 1-5 TMLandsat 4-5 MSSLandsat 1-3 MSS

Data Base update

tool

Data Base

SOP, EOPSOP, EOP for each WRS2 tiles

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Deciduous forest Path/Rows

15467836

Number of Path/row

Legend

bad_2000

Deciduous forest

gls2005_coverage

Deciduous

GLS

RESULT

• SOP, EOP

• Temporal consistency

• Trend compared to latitude and biome

• GLS replacement scene

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SOP of 10 year norm

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EOP of 10 year norm

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SOP variation from 1999 to 2007

Variation (date)

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EOP variation from 1999 to 2007

Variation (date)

Start of Peak by latitude and by BiomesTemperate Broad Leaf

Tropical Dry Broad Leaf

End of Peak by latitude

GLS 2000 scenes need to be replaced

15467836

Number of Scenes

424

15467836

Numbers of Scenes

435

GLS 2005 scenes need to be replaced

Replacement scene selection

• Browse through available scene list• Pick the best image based on visual observation

• Criteria: Minimal cloud cover and within phenology bounds

P17 R28: Canada Peak Season Range: 5/25/2002 – 9/30/2002

GLS2000 date: 5/15/2002 Replacement scene date: 8/24/2001

GLS Replacement scene

P22R49 (Guatemala)Peak Season Range: 6/10/1999 – 11/17/1999

GLS date is just out of date range. Replacement scene has clouds. This is an example of replacement scene not being a better choice.

GLS image: 12/4/1999 Replacement image: 8/6/1999

Replacement Scenes

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GLS 2000284 Replacement / 424 scenes need to be replaced

GLS 2005252 Replacement /435 scenes need to be replaced

DISCUSSION• 1. Snow effect• 2. Scale issue• 3. Selection of path/row with seasonality• 4. Threshold selection• 5. Validation against ground measurement

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Acknowledgement

• This work has been carried out as part of the Global Forest Cover Change project, funded by the NASA MEaSUREs

program (NNH06ZDA001N-MEASURES)

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Reference• A. Huete, et al., “Overview of the radiometric and biophysical performance of the MODIS vegetation

indices,” Remote Sensing of Environment, vol. 83, no.1-2, pp. 195-213, Nov., 2002.

• Friedl, M.A., et al., “The MODIS land cover product: multi-attribute mapping of global vegetation and land cover properties from time series MODIS data,” Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS), vol. 4, pp. 3199-3201, 2002

• Coppin et. al., "Digital change detection methods in ecosystem monitoring: a review, “ IN T. J. REMOTE SENSING, 10 MAY, 2004, VOL. 25, NO. 9, 1565–1596

• U.S. Geological Survey (2010, Dec. 30), Landsat Bulk Metadata Service. Available: http://landsat.usgs.gov/consumer.php

• Gutman, G., Byrnes, R., Masek, J., Covington, S., Justice, C., Franks, S., and R. Headley, Towards monitoring land cover and land-use changes at a global scale: The Global Land Survey 2005, Photogrammetric Engineering and Remote Sensing, 74, 6-10, 2008.

• Franks, S., Masek, J.G., Headley, R.M.K., Gasch, J., and Arvidson, T., Large Area Scene Selection Interface (LASSI). Methodology for selecting Landsat imagery for the Global Land Survey 2005, in press Photogrammetric Engineering and Remote Sensing.

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