Percent tree cover estimation using regression tree method: A case study of Africa with very-high resolution QuickBird images as training data

Daisuke Nitto; Hussam Al Bilbisi; Ryutaro Tateishi

doi:10.1109/IGARSS.2005.1526445

Percent tree cover estimation using regression tree method: A case study of Africa with very-high resolution QuickBird images as training data

Rokhmatuloh, Daisuke Nitto, Hussam Al Bilbisi, Ryutaro Tateishi

Department of Geography

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

10 Citations (Scopus)

Abstract

Different percent tree covers store different amounts of carbon. Regression tree is more robust than linear regression method, primarily due to its capability of approximating complex non-linear relationships using a set of linear equations. To cover large area with daily acquisition, the coarse resolution MODIS data were used. As the training data for this regression tree method, 11 scenes of very-high resolution QuickBird satellite were employed. The explanatory variables acquired from MODIS data such as surface reflectance, NDVI, EVI, NDSI and thermal data were used as predictor. The tree proportions from QuickBird and MODIS-derived variables were then used to produce tree cover percentage layer for Africa. From prediction error measurement, the results were in good agreement with ground truth data.

Original language	English
Title of host publication	25th Anniversary IGARSS 2005
Subtitle of host publication	IEEE International Geoscience and Remote Sensing Symposium
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2157-2160
Number of pages	4
ISBN (Print)	0780390504, 9780780390508
DOIs	https://doi.org/10.1109/IGARSS.2005.1526445
Publication status	Published - 1 Jan 2005
Event	2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005 - Seoul, Korea, Republic of Duration: 25 Jul 2005 → 29 Jul 2005

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	3

Conference

Conference	2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005
Country/Territory	Korea, Republic of
City	Seoul
Period	25/07/05 → 29/07/05

Keywords

MODIS
Percent tree covers
QuickBird
Regression tree
Training data

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10.1109/IGARSS.2005.1526445

Cite this

Rokhmatuloh, Nitto, D., Al Bilbisi, H., & Tateishi, R. (2005). Percent tree cover estimation using regression tree method: A case study of Africa with very-high resolution QuickBird images as training data. In 25th Anniversary IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium (pp. 2157-2160). Article 1526445 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 3). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2005.1526445

Rokhmatuloh ; Nitto, Daisuke ; Al Bilbisi, Hussam et al. / Percent tree cover estimation using regression tree method : A case study of Africa with very-high resolution QuickBird images as training data. 25th Anniversary IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium. Institute of Electrical and Electronics Engineers Inc., 2005. pp. 2157-2160 (International Geoscience and Remote Sensing Symposium (IGARSS)).

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abstract = "Different percent tree covers store different amounts of carbon. Regression tree is more robust than linear regression method, primarily due to its capability of approximating complex non-linear relationships using a set of linear equations. To cover large area with daily acquisition, the coarse resolution MODIS data were used. As the training data for this regression tree method, 11 scenes of very-high resolution QuickBird satellite were employed. The explanatory variables acquired from MODIS data such as surface reflectance, NDVI, EVI, NDSI and thermal data were used as predictor. The tree proportions from QuickBird and MODIS-derived variables were then used to produce tree cover percentage layer for Africa. From prediction error measurement, the results were in good agreement with ground truth data.",

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Rokhmatuloh, Nitto, D, Al Bilbisi, H & Tateishi, R 2005, Percent tree cover estimation using regression tree method: A case study of Africa with very-high resolution QuickBird images as training data. in 25th Anniversary IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium., 1526445, International Geoscience and Remote Sensing Symposium (IGARSS), vol. 3, Institute of Electrical and Electronics Engineers Inc., pp. 2157-2160, 2005 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2005, Seoul, Korea, Republic of, 25/07/05. https://doi.org/10.1109/IGARSS.2005.1526445

Percent tree cover estimation using regression tree method: A case study of Africa with very-high resolution QuickBird images as training data. / Rokhmatuloh; Nitto, Daisuke; Al Bilbisi, Hussam et al.
25th Anniversary IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium. Institute of Electrical and Electronics Engineers Inc., 2005. p. 2157-2160 1526445 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 3).

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

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Rokhmatuloh, Nitto D, Al Bilbisi H, Tateishi R. Percent tree cover estimation using regression tree method: A case study of Africa with very-high resolution QuickBird images as training data. In 25th Anniversary IGARSS 2005: IEEE International Geoscience and Remote Sensing Symposium. Institute of Electrical and Electronics Engineers Inc. 2005. p. 2157-2160. 1526445. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS.2005.1526445

Percent tree cover estimation using regression tree method: A case study of Africa with very-high resolution QuickBird images as training data

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Keywords

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