Geostatistical techniques for estimating aboveground biomass in eastern Amazonia

doi:10.3832/ifor4789-018

Geostatistical techniques for estimating aboveground biomass in eastern Amazonia

Rafael Lucas Figueiredo De Souza⁽¹⁾ , Emily Ane Dionizio⁽²⁾, Rosane Barbosa Lopes Cavalcante⁽³⁾

iForest - Biogeosciences and Forestry, Volume 19, Issue 2, Pages 85-93 (2026)
doi: https://doi.org/10.3832/ifor4789-018
Published: Mar 13, 2026 - Copyright © 2026 SISEF

Research Articles

PDF Version

Full Text

Citation

The Amazon plays a crucial role in global environmental debates due to its vital ecosystem services, including the carbon stock in its vegetation. Given the challenges of collecting field data in remote areas, remote sensing products such as those provided by the Global Ecosystem Dynamics Investigation (GEDI) mission are a valuable alternative for estimating aboveground biomass and carbon stocks, particularly in regions of high conservation interest. This study aimed to map aboveground biomass (AGB) and estimate carbon stocks in the Carajás Mosaic, a set of protected areas in eastern Amazonia, using geostatistical interpolation methods on GEDI-derived AGB data. We tested four methods: inverse distance weighting, ordinary kriging, regression kriging, and cokriging. Vegetation and terrain indices were evaluated as auxiliary variables. Results revealed high spatial variability in AGB, with significant correlations between AGB and spectral and terrain variables. Among the methods, regression kriging and cokriging showed a good spatial dependence structure, with cokriging providing the most accurate estimates. Overall, the results enabled a precise analysis of AGB estimates in these protected areas, providing insights into carbon distribution and emphasizing the importance of combining geostatistics and remote sensing for effective forest management and conservation planning.

Keywords

Spatial Variability, Remote Sensing, Protected Areas, Interpolation Methods

Authors’ address

(1)

0000-0002-1328-057x
Vale Institute of Technology (ITV), Belém, Pará (Brazil)

(2)

0000-0002-1925-1809
World Resources Institute (WRI), São Paulo, São Paulo (Brazil)

(3)

0000-0002-5941-6460
Vale Institute of Technology (ITV), Belém, Pará (Brazil)

Corresponding author

Rafael Lucas Figueiredo De Souza
rafaelflorestal55@gmail.com

Citation

Figueiredo De Souza RL, Dionizio EA, Lopes Cavalcante RB (2026). Geostatistical techniques for estimating aboveground biomass in eastern Amazonia. iForest 19: 85-93. - doi: 10.3832/ifor4789-018

Academic Editor

Rafael Da Silveira Bueno

Paper history

Received: Jan 07, 2025
Accepted: Oct 06, 2025

First online: Mar 13, 2026
Publication Date: Apr 30, 2026
Publication Time: 5.27 months

Open Access

This article is distributed under the terms of the Creative Commons Attribution-Non Commercial 4.0 International (https://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Breakdown by View Type

(Waiting for server response...)

Article Usage

Total Article Views: 16
(from publication date up to now)

Breakdown by View Type
HTML Page Views: 5
Abstract Page Views: 5
PDF Downloads: 5
Citation/Reference Downloads: 0
XML Downloads: 1

Web Metrics
Days since publication: 1
Overall contacts: 16
Avg. contacts per week: 112.00

Article Citations

Article citations are based on data periodically collected from the Clarivate Web of Science web site
(last update: Mar 2025)

(No citations were found up to date. Please come back later)

(no Plumx Metrics available for this paper)

Publication Metrics

by Dimensions ^©

Articles citing this article

List of the papers citing this article based on CrossRef Cited-by.

(1)

Alvares CA, Stape JL, Sentelhas PC, Gonçalves JLM, Sparovek G (2013)
Köppen climate classification map for Brazil. Meteorologische Zeitschrift 22 (6): 711-728.
CrossRef | Gscholar

(2)

Benítez FL, Anderson LO, Formaggio AR (2016)
Evaluation of geostatistical techniques to estimate the spatial distribution of aboveground biomass in the Amazon rainforest using high-resolution remote sensing data. Acta Amazonica 46: 151-160.
CrossRef | Gscholar

(3)

Brouwer R, Pinto R, Dugstad A, Navrud S (2022)
The economic value of the Brazilian Amazon Rainforest ecosystem services: a meta-analysis of the Brazilian literature. PLoS One 17(5): e0268425.
CrossRef | Gscholar

(4)

Cambardella CA, Moorman TB, Novak JM, Parkin TB, Karlen DL, Turco RF, Konopka AE (1994)
Field-scale variability of soil properties in central lowa soils. Soil Science Society of America Journal 58 (5): 1501-1511.
CrossRef | Gscholar

(5)

Castilho CV, Magnusson WE, Araújo RNO, Luizão RC, Luizão FJ, Lima AP, Higuchi N (2006)
Variation in aboveground tree live biomass in a central Amazonian forest: effects of soil and topography. Forest Ecology and Management 234: 85-96.
CrossRef | Gscholar

(6)

Cavalcante RB, Dionizio EA, Gastauer M, Barbosa-Silva RG, Andrino CO, Nunes S (2023)
O estoque de carbono na floresta [Carbon stock in the forest]. In: “O capital natural das florestas de Carajás” (Giannini TC ed). Instituto Tecnológico Vale, Belém, Brasil, pp. 119-130. [in Portuguese]
CrossRef | Gscholar

(7)

Cavalheiro-Filho SL, Gestinari LM, Konno TU, Santos MP, Calderon EN, Marques MC, dos Santos FM, Castilho A, Martins RL, Esteves FA, Campos NV (2021)
Morphological plasticity in the endemic Isoëtes species from Serra dos Carajás, Amazonia, Brazil. American Fern Journal 111 (3): 174-195.
CrossRef | Gscholar

(8)

Chen M, Dong W, Yu H, Iain W, Ryan CM, Liu H, Georgiou S, Mitchard ETA (2023)
Multimodal deep learning for mapping forest dominant height by fusing GEDI with Earth observation data. Arxiv 2311.11777.
CrossRef | Gscholar

(9)

Clark DB, Clark DA (2000)
Landscape-scale variation in forest structure and biomass in a tropical rain forest. Forest Ecology and Management 137 (1-3): 185-198.
CrossRef | Gscholar

(10)

Dubayah R, Blair JB, Goetz S, Fatoyinbo L, Hansen M, Healey S, Hofton M, Hurtt G, Kellner J, Luthcke S, Armston J, Tang H, Duncanson L, Hancock S, Jantz P, Marselis S, Patterson PL, Qi W, Silva C (2020)
The global ecosystem dynamics investigation: high-resolution laser ranging of the earth’s forests and topography. Science of Remote Sensing 1: 100002.
CrossRef | Gscholar

(11)

Dubayah RO, Armston J, Kellner JR, Duncanson L, Healey SP, Patterson PL, Hancock S, Tang H, Hofton MA, Blair JB, Luthcke SB (2021)
Gedi l4a footprint level above ground biomass density. Science of Remote Sensing 1: 100003.
CrossRef | Gscholar

(12)

Destan S, Yilmaz OY, Sahin A (2013)
Making objective forest stand maps of mixed managed forest with spatial interpolation and multi-criteria decision analysis. iForest 6: 268-277.
CrossRef | Gscholar

(13)

Duncanson L, Kellner JR, Armston J, Dubayah R, Minor DM, Hancock S, Healey SP, Patterson PL, Saarela S, Marselis S, Silva CE, Bruening J, Goetz SJ, Tang H, Hofton M, Blair B, Luthcke S, Fatoyinbo L, Abernethy K, Alonso A, Zgraggen C (2021)
Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission. Remote Sensing of Environment. 270: 112845.
CrossRef | Gscholar

(14)

Flores BM, Montoya E, Sakschewski B, Nascimento N, Staal A, Betts RA, Levis C, Lapola DM, Esquível-Muelbert A, Jakovac C, Nobre CA, Oliveira RS, Borma LS, Nian D, Boers N, Hecht SB, Steege HT, Arieira J, Lucas IL, Berenguer E, Marengo JA, Gatti LV, Mattos CRC, Hinota M (2024)
Critical transitions in the Amazon forest system. Nature 626 (7999): 555-564.
CrossRef | Gscholar

(15)

Ferraz AS, Soares VP, Soares CPB, Ribeiro CAAS, Binoti DHB, Leite HG (2014)
Estimativa do estoque de biomassa em um fragmento florestal usando 42 imagens orbitais [Estimation of biomass stock in a forest using 42 orbital images]. Floresta and Ambiente 21 (3): 286-296. [in Portuguese]
CrossRef | Gscholar

(16)

Harris RMB, Loeffer F, Rumm A, Fischer C, Horchler P, Scholz M, Foeckler F, Henle K (2020)
Biological responses to extreme weather events are detectable but difficult to formally attribute to anthropogenic climate change. Scientific Reports 10: 14067.
CrossRef | Gscholar

(17)

Hengl T, Heuvelink GB, Stein A (2004)
A generic framework for spatial prediction of soil variables based on regression-kriging. Geoderma 120 (1-2): 75-93.
CrossRef | Gscholar

(18)

Hofhansl F, Chacón-Madrigal E, Fuchslueger L, Jenking D, Morera-Beita A, Plutzar C, Silla F, Andersen KM, Buchs DM, Dullinger S, Fiedler K, Franklin O, Hietz P, Huber W, Quesada CA, Rammig A, Schrodt F, Vincent AG, Weissenhofer A, Wanek W (2020)
Climatic and edaphic controls over tropical forest diversity and vegetation carbon storage. Scientific Reports 10: 5066.
CrossRef | Gscholar

(19)

Journel AG, Huijbregts CJ (1978)
Mining geostatistics. Academic Press, London and New York, pp. 600.
Gscholar

(20)

Mabunda IR, Guasselli LA, Nhongo EJS, Bandeira B (2021)
Estimation of forest biomass for energy purposes using vegetation and field data indices, district of Mabalane - Mozambique. Revista Brasileira de Cartografia 73 (1): 313-328.
CrossRef | Gscholar

(21)

Macedo FL, Sousa AMO, Gonçalves AC, Silva HR, Rodrigues RAF (2018)
Função alométrica de biomassa com imagens de satélite de alta resolução espacial [Biomass allometric function using high spatial resolution satellite images]. Ciência Florestal 28 (3): 960-969. [in Portuguese]
CrossRef | Gscholar

(22)

Malhi Y, Grace J (2006)
Tropical forests and atmospheric carbon dioxide. Trends Ecology and Evolution 15: 332-337.
CrossRef | Gscholar

(23)

MapBiomas Project (2019)
Collection 8 of the annual land use and land cover maps of Brazil. Website. [online]
Online | Gscholar

(24)

Marengo JA, Liebmann B, Grimm AM, Misra V, Silva Dias PL, Cavalcanti IFA, Alves LM (2010)
Recent developments on the South American monsoon system. International Journal of Climatology 32 (1): 1-21.
CrossRef | Gscholar

(25)

Mello CR, Viola MR, Beskow S, Norton LD (2013)
Multivariate models for annual rainfall erosivity in Brazil. Geoderma 202-203 (7): 88-102.
CrossRef | Gscholar

(26)

Miguel EP, Rezende AV, Leal FA, Matricardi EAT, Vale AT, Pereira RS (2015)
Redes neurais artificiais para a modelagem do volume de madeira e biomassa do cerradão com dados de satélite [Artificial neural networks for modeling wood volume and biomass in Cerradão using satellite data]. Pesquisa Agropecuária Brasileira 50 (9): 829-839. [in Portuguese]
CrossRef | Gscholar

(27)

Mutanga O, Masenyama A, Sibanda M (2023)
Spectral saturation in the remote sensing of high-density vegetation traits: a systematic review of progress, challenges, and prospects. ISPRS Journal of Photogrammetry and Remote Sensing 198: 297-309.
CrossRef | Gscholar

(28)

Odeh IOA, McBratney AB, Chittleborough DJ (1994)
Spatial prediction of soil properties from landform attributes derived from a digital elevation model. Geoderma 63: 197-214.
CrossRef | Gscholar

(29)

Ometto JP, Gorgens EB, Pereira FRS, Sato L, Lúcio M, Assis R, Cantinho R, Longo M, Jacon AD, Keller M (2023)
A biomass map of the Brazilian Amazon from multisource remote sensing. Scientific Data 10: 668.
CrossRef | Gscholar

(30)

Péllico-Netto S, Pelissari AL, Cysneiros VC, Bonazza M, Sanquetta CR (2017)
Sampling procedures for the inventory of commercial volume tree species in the Amazon forest. Academia Brasileira De Ciências 89 (3): 1829-1840.
CrossRef | Gscholar

(31)

Pelissari AL, Figueiredo Filho A, Sanquetta CR, Ebling AA, Roveda M, Cysneiros VC (2016)
Estrutura espacial arbórea de um remanescente natural de floresta ombrófila mista [Spatial tree structure of a natural remnant of mixed ombrophilous forest]. Biofix Scientific Journal 1 (1): 27-32. [in Portuguese]
CrossRef | Gscholar

(32)

Pelissari AL, Figueiredo Filho A, Péllico Netto S, Ebling AA, Roveda M, Sanquetta CR (2017)
Geostatistical modeling applied to spatiotemporal dynamics of successional tree species groups in a natural mixed tropical forest. Ecological Indicators 78: 1-7.
CrossRef | Gscholar

(33)

R Core Team (2021)
R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
Online | Gscholar

(34)

Reis AA, Diniz JMFS, Acerbi Júnior FW, Mello JM, Batista APB, Ferraz Filho AC (2020)
Modeling the spatial distribution of wood volume in a cerrado sensu stricto remnant in Minas Gerais State, Brazil. Scientia Forestalis 48 (125): E2844.
CrossRef | Gscholar

(35)

Roquette JG (2018)
Distribuição da biomassa no Cerrado e a sua importncia na armazenagem do carbono [Biomass distribution in the Cerrado and its importance in carbon storage]. Ciência Florestal 28 (3): 1350-1363. [in Portuguese]
CrossRef | Gscholar

(36)

Saatchi SS, Harris NL, Brown S, Lefsky M, Mitchard ET, Salas W, Zutta BR, Buermann W, Lewis SL, Hagen S, Petrova S, White L, Silman M, Morel A (2011)
Benchmark map of forest carbon stocks in tropical regions across three continents. Proceedings of the National Academy of Sciences 108 (24): 9899-9904.
CrossRef | Gscholar

(37)

Schaefer CEGR, Netto EL, Corrêa GR, Simas FNB, Campos JF, Mendonça BAF, Nunes JA (2016)
Geoambientes, solos e estoques de carbono na Serra Sul de Carajás, Pará, Brasil [Geoenvironments, soils and carbon stock in the Southern Serra de Carajás, Pará, Brazil]. Boletim do Museu Paraense Emílio Goeldi-Ciências Naturais 11 (1): 85-101. [in Portuguese]
CrossRef | Gscholar

(38)

Scolforo HF, Scolforo JRS, Mello CR, Mello JM, Ferraz Filho A (2015)
Spatial distribution of aboveground carbon stock of the arboreal vegetation in Brazilian biomes of savanna, Atlantic forest, and semi-arid woodland. PLoS One 10(6): E0128781.
CrossRef | Gscholar

(39)

Sena KKK, Campos PSS, Rodrigues HCT, Chase AO, Marques GT, Moraes RIR, Morais EC, Santos Júnior PC, Soares JAC, Galate RS (2019)
Análise geoestatística em povoamento de floresta nativa no município de Paragominas - Pará [Geostatistical analysis in a native forest stand in the municipality of Paragominas, Pará]. Brazilian Journal of Development 5 (10): 18695-18713. [in Portuguese]
CrossRef | Gscholar

(40)

Silva ASA, Stosic B, Menezes R, Singh V (2019)
Comparison of interpolation methods for spatial distribution of monthly precipitation in the State of Pernambuco, Brazil. Journal of Hydrology Engineering 24: 04018068.
CrossRef | Gscholar

(41)

Silva TT, Lima RB, Souza RLF, Moonlight PW, Cardoso D, Santos HKV, Oliveira CP, Veenendaal E, Queiroz LP, Rodrigues PMS, Santos RM, Sarkinen T, Paula A, Barreto-Garcia PAB, Pennington T, Phillips OL (2023)
Mapping wood volume in seasonally dry vegetation of caatinga in Bahia State, Brazil. Scientia Agricola 80: E20220161.
CrossRef | Gscholar

(42)

Silva Junior CHL, Heinrich VHA, Freire ATG, Broggio IS, Rosan TM, Doblas J, Anderson LO, Rousseau GX, Shimabukuro YE, Silva CA, House JL, Aragão LEOC (2020)
Benchmark maps of 33 years of secondary forest age for Brazil. Scientific Data 7: 269.
CrossRef | Gscholar

(43)

Silveira EMO, Mello JM, Acerbi Júnior FW, Reis AA, Withey KD, Ruiz LA (2017)
Characterizing landscape spatial heterogeneity using semivariogram parameters derived from ndvi images. Cerne 23 (4): 413-422.
CrossRef | Gscholar

(44)

Souza GS, Lima JSS, Xavier AC, Rocha WSD (2010)
Ordinary kriging and inverse-square-distance in spatialization in the chemical attributes of the ultisol. Scientia Agraria 11 (1): 73-81.
CrossRef | Gscholar

(45)

Sun Z, Sonsuthi A, Jucker T, Ali A, Cao M, Liu F, Cao G, Hu T, Ma Q, Guo Q, Lin L (2023)
Top canopy height and stem size variation enhance aboveground biomass across spatial scales in seasonal tropical forests. Plants 12.
CrossRef | Gscholar

(46)

Viana HKS, Lima RB, Souza RLF, Cardoso D, Moonlight Pw Silva TT, Oliveira CP, Alves Júnior FT, Veenendaal E, Queiroz LP, Rodrigues PMS, Santos RM, Sarkinen T, Paula A, Barreto-Garcia PAB, Pennington T, Phillips O (2023)
Spatial distribution of aboveground biomass stock in tropical dry forest in Brazil. iForest 16: 116-126.
CrossRef | Gscholar

(47)

Watanabe J, Yamanoto JK, Rocha MM, Fonseca PP (2009)
Estudo da influência da correlação inicial entre variáveis nos resultados de coestimativas [Study of the influence of initial correlation between variables on co-estimation results]. Geociências 28 (4): 467-484. - [in Portuguese]
Online | Gscholar

iForest - Biogeosciences and Forestry

Contents

Search

Journal Info

Journal Subjects and Fields

For Authors

For Reviewers

For Readers

SISEF Publishing

Search iForest Contents