Regional forest above-ground biomass retrieval by optimized k-NN algorithm in Northeast China

Xin Tian*, Erxue Chen, Zengyuan Li, Z. Bob Su, Lina Bai, C. Van Der Tol

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

This study explores retrieval of wall-to-wall forest above-ground biomass (AGB) over Jilin province in Northeast China, using the optimized non-parametric k-NN method, the 7th National Forest Inventory (NFI) data, and the remote sensing data: Landsat-TM/ETM+ images. For pixel-based validation, the estimated result was compared to the NFI data by leave-one-out process and R2 = 0.40 and RMSE = 54.29 tons/hm2. For county-scale validation, the result was verified by the intensive forest sub-compartment data of eight county and R2 = 0.80 and RMSE = 34.26 tons/hm2.

Original languageEnglish
Title of host publication2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings
Place of PublicationPiscataway, NJ
PublisherIEEE
Pages979-982
Number of pages4
ISBN (Electronic)978-1-4799-1114-1
DOIs
Publication statusPublished - 1 Dec 2013
Event33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013: Building a Sustainable Earth through Remote Sensing - Melbourne, Australia
Duration: 21 Jul 201326 Jul 2013
Conference number: 33
http://www.igarss2013.org/

Publication series

NameIEEE International Geoscience and Remote Sensing Symposium - IGARSS
PublisherIEEE
Volume2013
ISSN (Print)2153-6996
ISSN (Electronic)2153-7003

Conference

Conference33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013
Abbreviated titleIGARSS
CountryAustralia
CityMelbourne
Period21/07/1326/07/13
Internet address

Fingerprint

aboveground biomass
Remote sensing
Biomass
Pixels
forest inventory
Landsat thematic mapper
pixel
remote sensing
county

Keywords

  • Forest above-ground biomass
  • k-NN method
  • Optimized configuration

Cite this

Tian, X., Chen, E., Li, Z., Su, Z. B., Bai, L., & Van Der Tol, C. (2013). Regional forest above-ground biomass retrieval by optimized k-NN algorithm in Northeast China. In 2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings (pp. 979-982). [6721326] (IEEE International Geoscience and Remote Sensing Symposium - IGARSS; Vol. 2013). Piscataway, NJ: IEEE. https://doi.org/10.1109/IGARSS.2013.6721326
Tian, Xin ; Chen, Erxue ; Li, Zengyuan ; Su, Z. Bob ; Bai, Lina ; Van Der Tol, C. / Regional forest above-ground biomass retrieval by optimized k-NN algorithm in Northeast China. 2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings. Piscataway, NJ : IEEE, 2013. pp. 979-982 (IEEE International Geoscience and Remote Sensing Symposium - IGARSS).
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abstract = "This study explores retrieval of wall-to-wall forest above-ground biomass (AGB) over Jilin province in Northeast China, using the optimized non-parametric k-NN method, the 7th National Forest Inventory (NFI) data, and the remote sensing data: Landsat-TM/ETM+ images. For pixel-based validation, the estimated result was compared to the NFI data by leave-one-out process and R2 = 0.40 and RMSE = 54.29 tons/hm2. For county-scale validation, the result was verified by the intensive forest sub-compartment data of eight county and R2 = 0.80 and RMSE = 34.26 tons/hm2.",
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Tian, X, Chen, E, Li, Z, Su, ZB, Bai, L & Van Der Tol, C 2013, Regional forest above-ground biomass retrieval by optimized k-NN algorithm in Northeast China. in 2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings., 6721326, IEEE International Geoscience and Remote Sensing Symposium - IGARSS, vol. 2013, IEEE, Piscataway, NJ, pp. 979-982, 33rd IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013, Melbourne, Australia, 21/07/13. https://doi.org/10.1109/IGARSS.2013.6721326

Regional forest above-ground biomass retrieval by optimized k-NN algorithm in Northeast China. / Tian, Xin; Chen, Erxue; Li, Zengyuan; Su, Z. Bob; Bai, Lina; Van Der Tol, C.

2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings. Piscataway, NJ : IEEE, 2013. p. 979-982 6721326 (IEEE International Geoscience and Remote Sensing Symposium - IGARSS; Vol. 2013).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AU - Van Der Tol, C.

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N2 - This study explores retrieval of wall-to-wall forest above-ground biomass (AGB) over Jilin province in Northeast China, using the optimized non-parametric k-NN method, the 7th National Forest Inventory (NFI) data, and the remote sensing data: Landsat-TM/ETM+ images. For pixel-based validation, the estimated result was compared to the NFI data by leave-one-out process and R2 = 0.40 and RMSE = 54.29 tons/hm2. For county-scale validation, the result was verified by the intensive forest sub-compartment data of eight county and R2 = 0.80 and RMSE = 34.26 tons/hm2.

AB - This study explores retrieval of wall-to-wall forest above-ground biomass (AGB) over Jilin province in Northeast China, using the optimized non-parametric k-NN method, the 7th National Forest Inventory (NFI) data, and the remote sensing data: Landsat-TM/ETM+ images. For pixel-based validation, the estimated result was compared to the NFI data by leave-one-out process and R2 = 0.40 and RMSE = 54.29 tons/hm2. For county-scale validation, the result was verified by the intensive forest sub-compartment data of eight county and R2 = 0.80 and RMSE = 34.26 tons/hm2.

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Tian X, Chen E, Li Z, Su ZB, Bai L, Van Der Tol C. Regional forest above-ground biomass retrieval by optimized k-NN algorithm in Northeast China. In 2013 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2013 - Proceedings. Piscataway, NJ: IEEE. 2013. p. 979-982. 6721326. (IEEE International Geoscience and Remote Sensing Symposium - IGARSS). https://doi.org/10.1109/IGARSS.2013.6721326