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

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
PublisherIEEE
Pages979-982
Number of pages4
ISBN (Print)9781479911141
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/

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. 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. IEEE, 2013. pp. 979-982
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title = "Regional forest above-ground biomass retrieval by optimized k-NN algorithm in Northeast China",
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.",
keywords = "forest above-ground biomass, k-NN method, optimized configuration",
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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, 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. IEEE, 2013. p. 979-982 6721326.

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

TY - GEN

T1 - Regional forest above-ground biomass retrieval by optimized k-NN algorithm in Northeast China

AU - Tian, Xin

AU - Chen, Erxue

AU - Li, Zengyuan

AU - Su, Z. Bob

AU - Bai, Lina

AU - Van Der Tol, C.

PY - 2013/12/1

Y1 - 2013/12/1

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. IEEE. 2013. p. 979-982. 6721326 https://doi.org/10.1109/IGARSS.2013.6721326