Wood Volume Estimation in a Semidecidual Seasonal Forest Using MSI and SRTM Data
Anny Francielly Ataide Gonçalves; Márcia Rodrigues de Moura Fernandes; Jeferson Pereira Martins Silva; Gilson Fernandes da Silva; André Quintão de Almeida; Natielle Gomes Cordeiro; Lucas Duarte Caldas da Silva; José Roberto Soares Scolforo
Abstract
Keywords
References
Alba E, Mello EP, Marchesan J, Silva EA, Tramontina J, Pereira RS. Spectral characterization of forest plantations with Landsat 8/OLI images for forest planning and management.
Almeida AQ, Mello AA, Dória AL No, Ferra RC. Relações empíricas entre características dendrométricas da Caatinga Brasileira e dados TM Landsat 5.
Alvares CA, Stape JL, Sentelhas PC, Gonçalves JLM, Sparovek G. Köppen’s climate classification map for Brazil.
Andrade DF, Gama JRV, Melo LO, Ruschel AR. Inventário florestal de grandes áreas na Floresta Nacional do Tapajós, Pará, Amazônia, Brasil.
Archanjo KMPA, Silva GF, Chichorro JF, Soares CPB. Estrutura do componente arbóreo da reserva particular do patrimônio natural cafundó, Cachoeiro de Itapemirim, Espírito Santo, Brasil.
Barros BSX, Guerra SPS, Barros ZX, Catita CMS, Fernandes JCC. Uso de imagens de satélite para cálculo de volume em floresta de eucalipto no Município de Botucatu/SP.
Berra EF, Brandelero C, Pereira RS, Sebem E, Goergen LCG, Benedetti ACP et al. Estimativa do volume total de madeira em espécies de eucalipto a partir de imagens de satélite landsat.
Bispo PC.
Bispo PC.
Bispo PC, Santos JR, Valeriano MM, Graça PMLA, Balzter H, França H et al. Predictive models of primary tropical forest structure from geomorphometric variables based on SRTM in the Tapajo’s region, Brazilian Amazon.
Bispo PC, Valeriano MM, Kuplich TM. Variáveis geomorfométricas locais e sua relação com a vegetação da região do interflúvio Madeira-Purus (AM-RO).
Cabo C, Ordónez C, López-Sánchez CA, Armesto J. Automatic dendrometry: Tree detection, tree height and diameter estimation using terrestrial laser scanning.
Canavesi V, Ponzoni FJ, Valeriano MM. Estimativa de volume de madeira em plantios de Eucalyptus spp. utilizando dados hiperespectrais e dados topográficos.
Castillo JAA, Apan AA, Maraseni TN, Salmo SG 3rd. Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery.
Chrysafis I, Mallinis G, Siachalou S, Patias P. Assessing the relationships between growing stock volume and sentinel-2 imagery in a mediterranean forest ecosystem.
Fassnacht FE, Latifi H, Hartig F. Using synthetic data to evaluate the benefits of large field plots for forest biomass estimation with LiDAR.
Fernández-Manso A, Fernández-Manso O, Quintano C. Sentinel-2A red-edge spectral indices suitability for discriminating burn severity.
Fridman J, Holm S, Nilsson M, Nilsson P, Ringvall AH, Stahl G. Adapting National Forest Inventories to changing requirements - the case of the Swedish National Forest Inventory at the turn of the 20th century.
Hall RJ, Skakun RS, Arsenault EJ, Case BS. Modeling forest stand structure attributes using Landsat ETM+ data: Application to mapping of aboveground biomass and stand volume.
Huete AR. A soil-adjusted vegetation index (SAVI).
Hyyppä J, Hyyppä H, Inkinen M, Engdahl M, Linko S, Zhu YH. Accuracy comparison of various remote sensing data sources in the retrieval of forest stand attributes.
Immitzer M, Vuolo F, Atzberger C. First experience with Sentinel-2 data for crop and tree species classifications in central Europe.
Instituto Brasileiro de Geografia e Estatística – IBGE.
Instituto Brasileiro de Geografia e Estatística – IBGE.
Justice CO, Vermote E, Townshend JRG, Defries R, Roy DP, Hall DK et al. The moderate resolution imaging spectroradiometer (MODIS): Land remote sensing for global change research.
Jordan CF. Derivation of leaf-area index from quality of light on the forest floor.
Knapp N, Fischer R, Huth A. Linking lidar and forest modeling to assess biomass estimation across scales and disturbance states.
Korhonen L, Hadi, Packalen P, Rautiainen M. Comparison of Sentinel-2 and Landsat 8 in the estimation of boreal forest canopy cover and leaf area index.
Laurin GV, Puletti N, Hawthome W, Liesenberg V, Corona P, Papale D et al. Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data.
Maack J, Lingenfelder M, Weinacker H, Koch B. Modelling the standing timber volume of Baden-Württemberg - A large-scale approach using a fusion of Landsat, airborne LiDAR and National Forest Inventory data.
Magnussen S, Nord-Larsen T, Riis-Nielsen T. Lidar supported estimators of wood volume and aboveground biomass from the Danish national forest inventory (2012–2016).
Mäkelä H, Pekkarinen A. Estimation of forest stand volumes by Landsat TM imagery and stand-level field-inventory data.
Matasci G, Hermosilla T, Wulder MA, White JC, Coops NC, Hobart GW et al. Large-area mapping of Canadian boreal forest cover, height, biomass and other structural attributes using Landsat composites and lidar plots.
Mello JM, Diniz FS, Oliveira AD, Scolforo JRS, Acerbi FW Jr, Thiersch CR. Métodos de amostragem e geoestatística para estimativa do número de fustes e volume em plantios de
Miguel EP, Rezende AV, Leal FA, Matricardi EAT, Vale AT, Pereira RS. Redes neurais artificiais para a modelagem do volume de madeira e biomassa do cerradão com dados de satélite.
Mohammadi J, Shataee Joibary S, Yaghmaee F, Mahiny AS. Modelling forest stand volume and tree density using landsat ETM+ data.
Mura M, Bottalico F, Giannetti F, Bertani R, Giannini R, Mancini M et al. Exploiting the capabilities of the Sentinel-2 multi spectral instrument for predicting growing stock volume in forest ecosystems.
Pandit S, Tsuyuki S, Dube T. Estimating above-ground biomass in sub-tropical buffer zone community forests, Nepal, using Sentinel 2 data.
Plowright AA, Coops NC, Chance CM, Sheppard SRJ, Aven NW. Multi-scale analysis of relationship between imperviousness and urban tree height using airborne remote sensing.
Qi J, Chehbouni A, Huete AR, Kerr YH, Sorooshian S. A modified soil adjusted vegetation index.
Rajashekar G, Fararoda R, Reddy RS, Jha CS, Ganeshaiah KN, Singh JS et al. Spatial distribution of forest biomass carbon (Above and below ground) in Indian forests.
Rouse JW, Hass RH, Schell JA, Deering DW. Monitoring vegetation systems in the great plains with ERTS. In:
Saarela S, Grafstrom A, Stahl G, Kangas A, Holopaonen M, Tuominen S et al. Model-assisted estimation of growing stock volume using different combinations of LiDAR and Landsat data as auxiliary information.
Santos MM, Machado IES, Carvalho EV, Viola MR, Giongo M. Estimativa de parâmetros florestais em área de Cerrado a partir de imagens do sensor Oli Landsat 8.
Silva EM, Santana AC. Modelos de regressão para estimação do volume de árvores comerciais, em florestas de Paragominas.
Takagi K, Yone Y, Takahashi H, Sakai R, Hojyo H, Kamiura T et al. Forest biomass and volume estimation using airborne LiDAR in a cool-temperate forest of northern Hokkaido, Japan.
Varvia P, Rautiainen M, Seppänen A. Bayesian estimation of seasonal course of canopy leaf area index from hyperspectral satellite data.
Vibrans AC, Sevgnani L, Lingner DV, Gasper AL, Sabbagh S. Inventário florístico florestal de Santa Catarina (IFFSC): aspectos metodológicos e operacionais.
Wang R, Chen JM, Liu Z, Arain A. Evaluation of seasonal variations of remotely sensed leaf area index over five evergreen coniferous forests.
Watzlawick LF, Kirchner FF, Sanquetta CR. Estimativa de biomassa e carbono em floresta com araucaria utilizando imagens do satélite IKONOS II.