APPLICATIONS OF SAR DATA TO ESTIMATE FOREST BIOPHYSICAL VARIABLES IN BRAZIL

The use of SAR images has been highlighted in scientific research focused on forest data collection worldwide. Thus, the present work aimed at gathering studies turned to the application of SAR images to obtain biophysical variables of forests in Brazil. Based on studies published in recognized databases, a growing amount of publications over time was observed with more focus on researches made mainly in Amazonian biome, followed by planted forests with eucalyptus destined to wood production. Most works were made based on airborne radar data, followed by ALOS/PALSAR and JERS-1 orbital data. It is remarkable the scientific knowledge produced using radar data from Brazilian forests, demonstrating that this technology is an other tool for studies and applications in Forestry Sciences that can assist in the country’s forestry management. Nevertheless, the need of studies on the several forest typologies across Brazil was evidenced, along with the lack of research related to radar use to estimate biophysical variables in caatinga and Atlantic Forest biomes.

Keywords:
Remote sensing; Synthetic aperture radar; Forest biomass

Authorship

Janisson Batista de Jesus ⁺ + janisson.eng@gmail.com

Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, BrazilFederal University of Rio Grande do SulBrazilPorto Alegre, Rio Grande do Sul, Brazil Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil

http://orcid.org/0000-0001-8372-5557

Tatiana Mora Kuplich

Instituto Nacional de Pesquisas Espaciais, Santa Maria, Rio Grande do Sul, BrazilInstituto Nacional de Pesquisas EspaciaisBrazilSanta Maria, Rio Grande do Sul, Brazil Instituto Nacional de Pesquisas Espaciais, Santa Maria, Rio Grande do Sul, Brazil

http://orcid.org/0000-0003-0657-4024

+ janisson.eng@gmail.com

SCIMAGO INSTITUTIONS RANKINGS

Figures | Tables

Figures (3)
Tables (1)

Thumbnail

FIGURE 1
(a) Penetration of the C and L bands wavelenght in the forest canopy. Source: (OMAR et al., 2017OMAR, H.; MISMAN, M. A.; KASSIM, A. R. Synergetic of PALSAR-2 and Sentinel-1A SAR polarimetry for retrieving aboveground biomass in dipterocarp forest of Malaysia. Applied Sciences, v.7, n. 7, p. 675, 2017. ). (b) Geometry of a forest canopy and scattering components: 1, soil surface scattering; 2, leaf volume scattering; 3, branch volume scattering; 4, trunk volume scattering; 5, leaf-soil interaction; 6, branch-soil interaction; 7, trunk-soil interaction. Source: (WANG and QI, 2008WANG, C.; Qi, J. Biophysical estimation in tropical forests using JERS-1 SAR and VNIR imagery. II. Aboveground woody biomass. International Journal of Remote Sensing , v. 29, n. 23, p. 6827-6849, 2008.).

Thumbnail

FIGURE 2
Quantitative survey of SAR data scientific production over time (a), quantity by: types of forests studied (b) and radar data source (c).

Thumbnail

FIGURE 3
Relationship between observed and estimated values for the variables: Basal area, biomass, DBH (diameter at breast height), and Lorey heights, maximum and average. Source: Cougo et al. (2015COUGO, M.; SOUZA-FILHO, P. W. M.; SILVA, A. Q.; FERNANDES, M. E. B.; SANTOS, J. R.; ABREU, M. R. S.; NASCIMENTO, W. R.; SIMARD, M. Radarsat-2 backscattering for the modeling of biophysical parameters of regenerating mangrove forests. Remote Sensing , v. 7, n. 12, p. 17097-17112, 2015. ).

Thumbnail

TABLE 1
Studies using SAR data for forest biophysical variables estimates in Brazil.

FIGURE 1 (a) Penetration of the C and L bands wavelenght in the forest canopy. Source: (OMAR et al., 2017OMAR, H.; MISMAN, M. A.; KASSIM, A. R. Synergetic of PALSAR-2 and Sentinel-1A SAR polarimetry for retrieving aboveground biomass in dipterocarp forest of Malaysia. Applied Sciences, v.7, n. 7, p. 675, 2017. ). (b) Geometry of a forest canopy and scattering components: 1, soil surface scattering; 2, leaf volume scattering; 3, branch volume scattering; 4, trunk volume scattering; 5, leaf-soil interaction; 6, branch-soil interaction; 7, trunk-soil interaction. Source: (WANG and QI, 2008WANG, C.; Qi, J. Biophysical estimation in tropical forests using JERS-1 SAR and VNIR imagery. II. Aboveground woody biomass. International Journal of Remote Sensing , v. 29, n. 23, p. 6827-6849, 2008.).

FIGURE 2 Quantitative survey of SAR data scientific production over time (a), quantity by: types of forests studied (b) and radar data source (c).

FIGURE 3 Relationship between observed and estimated values for the variables: Basal area, biomass, DBH (diameter at breast height), and Lorey heights, maximum and average. Source: Cougo et al. (2015COUGO, M.; SOUZA-FILHO, P. W. M.; SILVA, A. Q.; FERNANDES, M. E. B.; SANTOS, J. R.; ABREU, M. R. S.; NASCIMENTO, W. R.; SIMARD, M. Radarsat-2 backscattering for the modeling of biophysical parameters of regenerating mangrove forests. Remote Sensing , v. 7, n. 12, p. 17097-17112, 2015. ).

TABLE 1 Studies using SAR data for forest biophysical variables estimates in Brazil.

Type of forest	Sensor/Platform	Band	SAR variables	Reference
Amazon	SIR-C/ SRL-1	L, C	backscattering	Foody et al. (1997FOODY, G. M.; GREEN, R. M.; LUCAS, R. M.; CURRAN, P. J.; HONZAK, M.; AMARAL, I. Observations on the relationship between SIR-C radar backscatter and the biomass of regenerating tropical forests. International Journal of Remote Sensing , v. 18, n. 3, p. 687-694, 1997.)
Amazon	SAR/JERS-1, ERS-1, SIR-C	L, C	backscattering	Luckman et al. (1997LUCKMAN, A.; BAKER, J.; KUPLICH, T. M.; YANASSE, C. C. F.; FRERY, A. C. A study of the backscatter and biomass for relationship regenerating spaceborne SAR between radar tropical forest instruments. Remote Sensing of Environment, v. 60, n. 1, p. 1-13, 1997. )
Amazon	SAR/JERS-1	L	backscattering	Luckman et al. (1998LUCKMAN, A.; BAKER, J.; HONZÁK, M.; LUCAS, R. Tropical forest biomass density estimation using JERS-1 SAR: seasonal variation, confidence limits, and application to image mosaics. Remote Sensing of Environment , v. 63, n. 2, p. 126-139, 1998. )
Amazon	JERS-1	L	backscattering	Kuplich et al. (2000KUPLICH, T. M, SALVATORI, V.; CURRAN, P. J. JERS-1/SAR backscatter and its relationship with biomass of regenerating forests. International Journal of Remote Sensing , v. 21, n. 12, p. 2513-2518, 2000. )
Amazon	JERS-1	L	backscattering and texture	Salas et al. (2002SALAS, W. A.; DUCEY, M. J.; RIGNOT, E.; SKOLE, D. Assessment of JERS-1 SAR for monitoring secondary vegetation in Amazonia: II. Spatial, temporal, and radiometric considerations for operational monitoring. International Journal of Remote Sensing , v. 23, n. 7, p. 1381-1399, 2002. )
Amazon (transition zone between cerrado and Amazon forest)	JERS-1	L	backscattering	Santos et al. (2002SANTOS, J. R.; LACRUZ, M. S. P.; ARAUJO, L. S.; KEIL, M. Savanna and tropical rainforest biomass estimation and spatialization using JERS-1 data. International Journal ofRemote Sensing , v. 23, n. 7, p. 1217-1229, 2002. )
Amazon	AeS-1 (AeroSensing Radar Systeme)/Airborne	P, X	backscattering and interferometric height	Neeff et al. (2003NEEFF, T.; DUTRA, L. V.; SANTOS, J. R.; FREITAS, C. C.; ARAUJO, L. S. Tropical forest stand table modelling from SAR data. Forest Ecology and Management, v. 186, p. 159-170, 2003. )
Amazon	AeS-1 (AeroSensing Radar Systeme)/Airborne	P	backscattering	Santos et al. (2003SANTOS, J. R.; FREITAS, C. C.; ARAUJO, L. C.; DUTRA, L. V.; MURA, J. C.; GAMA, F. F.; SOLER, L. S.; SANT’ANNAS, J. S. Airborne P-band SAR applied to the aboveground biomass studies in the Brazilian tropical rainforest. Remote Sensing of Environment , v. 87, n. 4, p. 482-493, 2003. )
Amazon	JERS-1	L	texture	Kuplich et al. (2005KUPLICH, T. M.; CURRAN, P. J.; ATKINSON, P. M. Relating SAR image texture to the biomass of regenerating tropical forests. International Journal of Remote Sensing , v. 26, n. 21, p. 4829-4854, 2005. )
Amazon	AeS-1(AeroSensing Radar Systeme)/Airborne	P, X	backscattering and interferometric height	Neeff et al. (2005NEEFF, T.; DUTRA, L. V.; SANTOS, J. R.; FREITAS, C. C.; ARAUJO, L. S. Tropical forest measurement by interferometric height modeling and P-Band radar backscatter. Forest Science, v. 51, n. 6, p. 585-594, 2005. )
Amazon	Airborne	P	backscattering	Santos et al. (2006SANTOS, J. R.; ARAUJO, L. S.; KUPLICH, T. M.; FREITAS, C. C.; DUTRA, L. V.; SANT’ANNA, S. J. S.; GAMA, F. F. Tropical forest biomass and its relationship with P-band SAR data. Revista Brasileira de Cartografia, v. 58, n. 1, p. 37-42, 2006.)
Amazon	R99B/Airborne	L	polarimetric attributes	Narvaes et al. (2010NARVAES, I. S.; SANTOS, J. R.; SILVA, A. Q. Analysis of structural parameters of forest typologies using L-band SAR data. Boletim de Ciências Geodésicas , v. 16, n. 3, p. 475-489, 2010.)
Amazon	R99B/Airborne	L	polarimetric attributes	Gonçalves et al. (2011GONÇALVES, F. G.; SANTOS, J. R.; TREUHAFT, R. N. Stem volume of tropical forests from polarimetric radar. International Journal of Remote Sensing , v. 32, n. 2, p. 503-522, 2011. )
Amazon	JERS-1	L	backscattering and texture	Cutler et al. (2012CUTLER, M. E. J.; BOYD, D. S.; FOODY, G. M.; VETRIVEL, A. Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions. ISPRS Journal of Photogrammetry and Remote Sensing , v.70, p. 66-77, 2012. )
Amazon	OrbiSAR-1/Aircraft	P, X	polarimetric and interferometric data	Sambatti et al. (2012SAMBATTI, J. B. M.; LEDUC, R.; LUBECK, D.; MOREIRA, J. R.; SANTOS, J. R. Assessing forest biomass and exploration in the Brazilian Amazon with airborne InSAR: an alternative for REDD. The Open Remote Sensing Journal, v. 5, p. 21-36, 2012. )
Amazon	ALOS/PALSAR, SRTM	L	polarimetric attributes	Bispo et al. (2014BISPO, P. C.; SANTOS, J. R.; VALERIANO, M. M.; TOUZI, R.; SEIFERT, F. M. Integration of polarimetric PALSAR attributes and local geomorphometric variables derived from SRTM for forest biomass modeling in Central Amazonia. Canadian Journal ofRemote Sensing , v. 40, n. 1, p. 26-42, 2014. )
Amazon	TanDEM-X	X	interferometric coherence	Treuhaft et al. (2015TREUHAFT, R.; GONÇALVES, F. G.; SANTOS, J. R.; KELLER, M. M.; PALACE, M.; MADSEN, S.; SULLIVAN, F.; GRAÇA, P. M. L. A. Tropical-forest biomass estimation at X-Band from the spaceborne TanDEM-X interferometer. IEEE Geoscience and Remote Sensing Letters, v.12, n. 2, p. 239-243, 2015. )
Amazon	SRTM	X	geomorphometric variables	Bispo et al. (2016BISPO, P. C.; SANTOS, J. R.; VALERIANO, M. M.; GRAÇA, P. M. L. A.; BALZTER, H.; FRANÇA, H.; BISPO, P. C. Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajós Region, Brazilian Amazon. Plos One, v. 11, n. 6, p. e0152009, 2016. )
Amazon	ALOS/PALSAR	L	polarimetric attributes	Martins et al. (2016MARTINS, F. S. R. V.; SANTOS, J. R.; GALVÃO, L. S.; XAUD, H. A. M. Sensitivity of ALOS/PALSAR imagery to forest degradation by fire in northern Amazon. International Journal of Applied Earth Observation and Geoinformation, v. 49, p. 163-174, 2016. )
Amazon	TanDEM-X	X	interferometric phase-height	Treuhaft et al. (2017TREUHAFT, R.; LEI, Y.; GONÇALVES, F.; KELLER, M.; SANTOS, J. R.; NEUMANN, M.; ALMEIDA, A. Tropical-Forest structure and biomass dynamics from TanDEM-X radar interferometry. Forests , v. 8, n. 8, p. 277, 2017. )
Amazon	ALOS/PALSAR, Sentinel-1	L, C	backscattering and texture	Bourgoin et al. (2018BOURGOIN, C.; BLANC, L.; BAILLY, J.-S.; CORNU, G.; BERENGER, E.; OSZWALD, J.; TRITSCH, I.; LAURENT, F.; HASAN, A. F.; SIST, P.; GOND, V. The Potential of Multisource Remote Sensing for Mapping the Biomass of a Degraded Amazonian Forest. Forests, v. 9, n. 6, 303, 2018.)
Amazon	ALOS/PALSAR, RADARSAT-2, TerraSAR-X	L, C, X	polarimetric attributes	Pereira et al. (2018PEREIRA, L. O.; FURTADO, L. F. A.; NOVO, E. M. L. M.; SANT’ANNA, S. J. S.; LIESENBERG, V.; SILVA, T. S. F. Multifrequency and full-polarimetric SAR assessment for estimating above ground biomass and Leaf Area Index in the Amazon Várzea Wetlands. Remote Sensing , v. 10, n. 9, p. 1355, 2018. )
Amazon	TanDEM-X	X	interferometric data	Bispo et al. (2019BISPO, P. C.; PARDINI, M.; PAPATHANASSIOUC, K. P.; KUGLER, F.; BALZTER, H.; RAINS, D.; SANTOS, J. R.; RIZAEV, I. G.; TANSEY, K.; SANTOS, M. N.; ARAUJO, L. S. Mapping forest successional stages in the Brazilian Amazon using forest heights derived from TanDEM-X SAR interferometry. Remote Sensing of Environment, v. 232, p. 111194, 2019.)
Amazon	ALOS/PALSAR-2	L	polarimetric attributes	Cassol et al. (2019CASSOL, H. L. G.; CARREIRAS, J. M. B.; MORAES, E. C.; ARAGÃO, L. E. O. C.; SILVA, C. V. J.; QUEGAN, S.; SHIMABUKURO, Y. Retrieving Secondary Forest Aboveground Biomass from Polarimetric ALOS-2 PALSAR-2 Data in the Brazilian Amazon. Remote Sensing , v.11, n. 1, p. 1-32, 2019. )
Amazon	Sentinel-1	C	backscattering and texture	Debastiani et al. (2019DEBASTIANI, A.; SANQUETTA, C.; CORTE, A.; PINTO, N.; REX, F. Evaluating SAR-optical sensor fusion for aboveground biomass estimation in a Brazilian tropical forest. Annal of Forest Research, v. 62, n. 1, p. 109-122, 2019.)
Amazon	SRTM	X	terrain variables	Silveira et al. (2019SILVEIRA, E. M. O.; CUNHA, L. I. F.; GALVÃO, L. S.; WITHEY, K. D.; ACERBI JÚNIOR, F. W.; SCOLFORO, J. R. S. Modelling aboveground biomass in forest remnants of the Brazilian Atlantic Forest using remote sensing, environmental and terrain-related data. Geocarto International, 36 p., 2019.)
Amazon	ALOS/PALSAR	L	backscattering	Huggannavar and Shetty (2020HUGGANNAVAR, V.; SHETTY, A. Biomass Estimation Using Synergy of ALOS-PALSAR and Landsat Data in Tropical Forests of Brazil. In: GHOSH, J.; SILVA, I. Applications of Geomatics in Civil Engineering. Switzerland: Springer, 2020. p. 593-603. )
Cerrado	JERS-1	L	backscattering	Bitencourt et al. (2007BITENCOURT, M. D.; MESQUITA JUNIOR, H. N.; KUNTSCHIK, G.; ROCHA, H. R.; FURLEY, P. A. Cerrado vegetation study using optical and radar remote sensing: two Brazilian case studies. Canadian Journal ofRemote Sensing , v. 33, n; 6, p. 468-480, 2007. )
Mangrove	RADARSAT-2	C	backscattering	Cougo et al. (2015COUGO, M.; SOUZA-FILHO, P. W. M.; SILVA, A. Q.; FERNANDES, M. E. B.; SANTOS, J. R.; ABREU, M. R. S.; NASCIMENTO, W. R.; SIMARD, M. Radarsat-2 backscattering for the modeling of biophysical parameters of regenerating mangrove forests. Remote Sensing , v. 7, n. 12, p. 17097-17112, 2015. )
Mangrove	ALOS/PALSAR	L	backscattering e incoherent attributes	Pereira et al. (2016PEREIRA, F. R. S.; KAMPEL, M.; CUNHA-LIGNON, M. Mangrove vegetation structure in Southeast Brazil from phased array L-band synthetic aperture radar data. Journal of Applied Remote Sensing , v. 10, n. 3, p. 036021, 2016. )
Eucalyptus forest plantation	Airborne, OrbiSAR-1	P, X	polarimetric and interferometric data	Gama et al. (2006GAMA, F. F.; SANTOS, J. R.; MURA, J. C.; RENNÓ, C. D. Estimativa de parâmetros biofísicos de povoamentos de Eucalyptus através de dados SAR. Ambiência , v. 2, n. 3, p. 29-42, 2006.)
Eucalyptus	Airborne	P, X	polarimetric and interferometric data	Gama et al. (2010aGAMA, F. F.; MURA, J. C.; SANTOS, J. R.; ALBUQUERQUE, P. C. G. Avaliação do potencial da interferometria SAR para o mapeamento altimétrico de áreas reflorestadas por Eucalyptus sp. Boletim de Ciências Geodésicas, v. 16, n. 4, p. 519-537, 2010a.)
Eucalyptus	Airborne, OrbiSAR-1	P, X	polarimetric and interferometric data	Gama et al. (2010bGAMA, F. F.; SANTOS, J. R.; MURA, J. C. Eucalyptus biomass and volume estimation using interferometric and polarimetric SAR data. Remote Sensing , v. 2, n. 4, p. 939-956, 2010b. )
Eucalyptus	ALOS/PALSAR	L	backscattering	Baghdadi et al. (2015BAGHDADI, N.; MAIRE, G.; BAILLY, J.-S.; NOUVELLON, Y.; OSE, K.; ZRIBI, M.; LEMOS, C.; HAKAMADA, R. Evaluation of ALOS/PALSAR L-band data for the estimation of Eucalyptus plantations aboveground biomass in Brazil. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 8, n. 8, p. 3802-3811, 2015. )
Eucalyptus	Airborne, OrbiSAR-1	P, X	polarimetric and interferometric data	Gama et al. (2016GAMA, F. F.; SANTOS, J. R.; MURA, J. C. Continuous monitoring of biophysical Eucalyptus sp. parameters using interferometric synthetic aperture radar data in P and X bands. Journal of Applied Remote Sensing , v. 10, n. 2, p. 026002, 2016. )
Eucalyptus	Sentinel-1B, ALOS/PALSAR DEM	C, L	backscattering, terrain atributes and texture	Reis et al. (2019REIS, A. A.; FRANKLIN, S. E.; MELLO, J. M.; ACERBI JUNIOR, F. W. Volume estimation in a Eucalyptus plantation using multi-source remote sensing and digital terrain data: a case study in Minas Gerais State, Brazil. International Journal of Remote Sensing , v. 40, n. 7, p. 2683-2702, 2019.)
Eucalyptus	ALOS/PALSAR	L	backscattering	Souza et al. (2019SOUZA, G. S. A.; SOARES, V. P.; LEITE, H. G.; GLERIANI, J. M.; AMARAL, C. H.; FERRAZ, A. S.; SILVEIRA, M. V. F.; SANTOS, J. F. C.; VELLOSO, S. G. S.; DOMINGUES, G. F.; SILVA, S. Multi-sensor prediction of Eucalyptus stand volume: A support vector approach. ISPRS Journal of Photogrammetry and Remote Sensing , v. 156, p. 135-146, 2019.)

How to cite

copy

UFLA - Universidade Federal de Lavras Universidade Federal de Lavras - Departamento de Ciências Florestais - Cx. P. 3037, 37200-000 Lavras - MG Brasil, Tel.: (55 35) 3829-1706, Fax: (55 35) 3829-1411 - Lavras - MG - Brazil
E-mail: cerne@dcf.ufla.br

Acompanhe os números deste periódico no seu leitor de RSS

Versão para download de PDF

PDF

Inglês

Versões e tradução automática

Versão original do texto

English

Tradução automática

Google Translator
Microsoft Translator

Como citar

RIS

BIBTEX

Outros formatos de citação e exportação:

SciELO - Scientific Electronic Library Online
Rua Dr. Diogo de Faria, 1087 – 9º andar – Vila Clementino 04037-003 São Paulo/SP - Brasil
E-mail: scielo@scielo.org

Leia a Declaração de Acesso Aberto

Métricas

APPLICATIONS OF SAR DATA TO ESTIMATE FOREST BIOPHYSICAL VARIABLES IN BRAZIL

PlumX

Mensagem

[1] + janisson.eng@gmail.com