4.7 Article

3D radiative transfer modelling of fire impacts on a two-layer savanna system

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 115, Issue 8, Pages 1866-1881

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2011.03.010

Keywords

Burn; Savanna; Vegetation; MCRT; 3D modelling; Radiative transfer; Fire impact

Funding

  1. ESA [1428/08/NL/HE]
  2. NERC [earth010003] Funding Source: UKRI
  3. Natural Environment Research Council [earth010003] Funding Source: researchfish

Ask authors/readers for more resources

We present a new, detailed three dimensional (3D) approach to modelling the pre- and post-fire reflectance of a two-layer savanna system modelled as heterogeneous overstory (tree) and understory (grass) layers. The models were developed from detailed field measurements of structural and radiometric properties made at experimental burn plots with varying canopy cover in the Kruger National Park, South Africa. The models were used to simulate 400-2500 rim spectral reflectance at 10-500 m spatial scale for various viewing and solar geometry configurations. The model simulations closely matched pre-fire and post-fire ground-based, helicopter and satellite remote sensing observations (all r(2) values>0.95 except one post-fire case). The largest discrepancies between modelled and observed reflectances occurred typically at wavelengths greater than 1200 nm for the post-fire simulations. The modelling results indicate that representation of overstory and understory structure and scattering properties are required to represent the burn signal in a typical savanna system. The described 3D modelling approach enables separation of the scattering contributions of the different scene components and is suited to testing and validating fire impact assessment algorithms at locations where the difficulty of obtaining both pre- and post-fire observations is a severe constraint. (C) 2011 Elsevier Inc. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Environmental Sciences

An Effective Method for InSAR Mapping of Tropical Forest Degradation in Hilly Areas

Harry Carstairs, Edward T. A. Mitchard, Iain McNicol, Chiara Aquino, Andrew Burt, Medard Obiang Ebanega, Anaick Modinga Dikongo, Jose-Luis Bueso-Bello, Mathias Disney

Summary: This paper investigates the relationship between TanDEM-X InSAR phase height (h phi) and aboveground biomass change in a hilly region of central Gabon. The study shows that minimizing multilooking and selecting appropriate pass directions on a pixel-by-pixel basis can enhance and improve degradation estimates.

REMOTE SENSING (2022)

Editorial Material Ecology

Remote sensing and the UN Ocean Decade: high expectations, big opportunities

Vincent Lecours, Mathias Disney, Kate He, Nathalie Pettorelli, J. Marcus Rowcliffe, Temuulen Sankey, Kylie Scales

REMOTE SENSING IN ECOLOGY AND CONSERVATION (2022)

Article Ecology

Water table depth modulates productivity and biomass across Amazonian forests

Thaiane R. Sousa, Juliana Schietti, Igor O. Ribeiro, Thaise Emilio, Rafael Herrera Fernandez, Hans ter Steege, Carolina Castilho, Adriane Esquivel-Muelbert, Timothy Baker, Aline Pontes-Lopes, Camila V. J. Silva, Juliana M. Silveira, Geraldine Derroire, Wendeson Castro, Abel Monteagudo Mendoza, Ademir Ruschel, Adriana Prieto, Adriano Jose Nogueira Lima, Agustin Rudas, Alejandro Araujo-Murakami, Alexander Parada Gutierrez, Ana Andrade, Anand Roopsind, Angelo Gilberto Manzatto, Anthony Di Fiore, Armando Torres-Lezama, Aurelie Dourdain, Beatriz Marimon, Ben Hur Marimon, Benoit Burban, Bert van Ulft, Bruno Herault, Carlos Quesada, Casimiro Mendoza, Clement Stahl, Damien Bonal, David Galbraith, David Neill, Edmar A. de Oliveira, Eduardo Hase, Eliana Jimenez-Rojas, Emilio Vilanova, Eric Arets, Erika Berenguer, Esteban Alvarez-Davila, Euridice N. Honorio Coronado, Everton Almeida, Fernanda Coelho, Fernando Cornejo Valverde, Fernando Elias, Foster Brown, Frans Bongers, Freddy Ramirez Arevalo, Gabriela Lopez-Gonzalez, Geertje van der Heijden, Gerardo A. Aymard, Gerardo Flores Llampazo, Guido Pardo, Hirma Ramirez-Angulo, Ieda Leao do Amaral, Ima Celia Guimaraes Vieira, Isau Huamantupa-Chuquimaco, James A. Comiskey, James Singh, Javier Silva Espejo, Jhon Del Aguila-Pasquel, Joeri Alexander Zwerts, Joey Talbot, John Terborgh, Joice Ferreira, Jorcely G. Barroso, Jos Barlow, Jose Luis Camargo, Juliana Stropp, Julie Peacock, Julio Serrano, Karina Melgaco, Leandro Ferreira, Lilian Blanc, Lourens Poorter, Luis Valenzuela Gamarra, Luiz Aragao, Luzmila Arroyo, Marcos Silveira, Maria Cristina Penuela-Mora, Mario Percy Nunez Vargas, Marisol Toledo, Mat Disney, Maxime Rejou-Mechain, Michel Baisie, Michelle Kalamandeen, Nadir Pallqui Camacho, Nallarett Davila Cardozo, Natalino Silva, Nigel Pitman, Niro Higuchi, Olaf Banki, Patricia Alvarez Loayza, Paulo M. L. A. Graca, Paulo S. Morandi, Peter J. van der Meer, Peter van der Hout, Petrus Naisso, Plinio Barbosa Camargo, Rafael Salomao, Raquel Thomas, Rene Boot, Ricardo Keichi Umetsu, Richarlly da Costa Silva, Robyn Burnham, Roderick Zagt, Rodolfo Vasquez Martinez, Roel Brienen, Sabina Cerruto Ribeiro, Simon L. Lewis, Simone Aparecida Vieira, Simone Matias de Almeida Reis, Sophie Fauset, Susan Laurance, Ted Feldpausch, Terry Erwin, Timothy Killeen, Verginia Wortel, Victor Chama Moscoso, Vincent Vos, Walter Huaraca Huasco, William Laurance, Yadvinder Malhi, William E. Magnusson, Oliver L. Phillips, Flavia R. C. Costa

Summary: The study found that both excess and deficit of water availability reduce productivity in Amazon upland forests. Biomass and productivity across the Amazon not only respond to regional climate, but also to its interaction with water table conditions, showing high local differentiation.

GLOBAL ECOLOGY AND BIOGEOGRAPHY (2022)

Article Environmental Sciences

Quantifying tropical forest structure through terrestrial and UAV laser scanning fusion in Australian rainforests

Louise Terryn, Kim Calders, Harm Bartholomeus, Renee E. Bartolo, Benjamin Brede, Barbara D'hont, Mathias Disney, Martin Herold, Alvaro Lau, Alexander Shenkin, Timothy G. Whiteside, Phil Wilkes, Hans Verbeeck

Summary: Accurately quantifying tree and forest structure is crucial for understanding and monitoring the functioning of terrestrial ecosystems in a changing climate. Terrestrial Laser Scanning (TLS) and Unoccupied Aerial Vehicle Laser Scanning (UAV-LS) have advanced the accurate measurement of forest structure. Combining TLS and UAV-LS data can further enhance the 3D structural mapping of dense tropical forests. TLS provides accurate measurements on a smaller scale, while UAV-LS provides comparable measurements on a larger scale. The fusion of TLS and UAV-LS can improve the measurement of structural metrics in these forests.

REMOTE SENSING OF ENVIRONMENT (2022)

Review Ecology

Estimating forest above-ground biomass with terrestrial laser scanning: Current status and future directions

Miro Demol, Hans Verbeeck, Bert Gielen, John Armston, Andrew Burt, Mathias Disney, Laura Duncanson, Jan Hackenberg, Daniel Kukenbrink, Alvaro Lau, Pierre Ploton, Artie Sewdien, Atticus Stovall, Stephane Momo Takoudjou, Liubov Volkova, Christopher Weston, Verginia Wortel, Kim Calders

Summary: Improving global monitoring of above-ground biomass is crucial for effective forest management in mitigating climate change. Terrestrial laser scanning (TLS) data has been developed to estimate above-ground biomass, addressing uncertainties in current methods. A global dataset of TLS scanned and destructively measured trees was assembled, showing close agreement between TLS-derived values and destructive measurements. However, smaller trees and conifers had below-average performances. TLS estimates of above-ground biomass were more accurate than allometric scaling models, especially for larger trees. Further efforts are needed to understand and constrain TLS error sources for better accuracy. TLS-calibrated models can be a powerful tool for scaling above-ground biomass with less effort compared to destructive harvesting.

METHODS IN ECOLOGY AND EVOLUTION (2022)

Article Environmental Sciences

A Machine Learning Approach to Waterbody Segmentation in Thermal Infrared Imagery in Support of Tactical Wildfire Mapping

Jacqueline A. Oliver, Frederique C. Pivot, Qing Tan, Alan S. Cantin, Martin J. Wooster, Joshua M. Johnston

Summary: This study focuses on using a random forest classifier to segment waterbodies in thermal infrared images. The results show that this method achieves high accuracy in different situations and can be used for more complex deep learning approaches.

REMOTE SENSING (2022)

Article Biodiversity Conservation

Toward a forest biomass reference measurement system for remote sensing applications

Nicolas Labriere, Stuart J. Davies, Mathias Disney, Laura Duncanson, Martin Herold, Simon L. Lewis, Oliver L. Phillips, Shaun Quegan, Sassan S. Saatchi, Dmitry G. Schepaschenko, Klaus Scipal, Plinio Sist, Jerome Chave

Summary: This study aims to establish a global forest biomass reference measurement system. To successfully implement this system, uniform data collection and processing standards, inclusive and equitable system establishment and management, as well as mandatory training and involvement of site partners in downstream activities are emphasized.

GLOBAL CHANGE BIOLOGY (2023)

Article Environmental Sciences

Linking Remote Sensing with APSIM through Emulation and Bayesian Optimization to Improve Yield Prediction

Hamze Dokoohaki, Teerath Rai, Marissa Kivi, Philip Lewis, Jose L. Gomez-Dans, Feng Yin

Summary: The study explores the use of Earth Observations (EOs) to constrain agricultural system models and improve parameter estimation and system representation. The results demonstrate the potential practicality of EOs in constraining crop models and show comparable results to model calibration exercises using field measurements alone.

REMOTE SENSING (2022)

Article Ecology

Analysing individual 3D tree structure using the R package ITSMe

Louise Terryn, Kim Calders, Markku Akerblom, Harm Bartholomeus, Mathias Disney, Shaun Levick, Niall Origo, Pasi Raumonen, Hans Verbeeck

Summary: Detailed 3D quantification of tree structure is crucial for understanding tree- and plot-level biophysical processes. Our ITSMe toolbox, which works with LiDAR tree point clouds and quantitative structure models, provides a robust framework for obtaining individual tree structural metrics from 3D data. It is open-source and aims to make the use of 3D data more straightforward and transparent for researchers interested in tree structure information.

METHODS IN ECOLOGY AND EVOLUTION (2023)

Article Environmental Sciences

Reconstructing the digital twin of forests from a 3D library: Quantifying trade-offs for radiative transfer modeling

Chang Liu, Kim Calders, Niall Origo, Mathias Disney, Felicien Meunier, William Woodgate, Jean -Philippe Gastellu-Etchegorry, Joanne Nightingale, Eija Honkavaara, Teemu Hakala, Lauri Markelin, Hans Verbeeck

Summary: This study evaluated the trade-offs involved in two main subsampling approaches when reconstructing 3D-explicit forest scenes for radiative transfer modeling. The results showed that both subplot subsampling and tree library subsampling can effectively reconstruct the forest scenes, with the normalized mean BRF deviation decreasing as the sampling fraction increased. Sampling 20% of the forest area using the subplot subsampling method was found to be an effective reconstruction strategy for the temperate deciduous forest.

REMOTE SENSING OF ENVIRONMENT (2023)

Article Geosciences, Multidisciplinary

Location, biophysical and agronomic parameters for croplands in northern Ghana

Jose Luis Gomez-Dans, Philip Edward Lewis, Feng Yin, Kofi Asare, Patrick Lamptey, Kenneth Kobina Yedu Aidoo, Dilys Sefakor MacCarthy, Hongyuan Ma, Qingling Wu, Martin Addi, Stephen Aboagye-Ntow, Caroline Edinam Doe, Rahaman Alhassan, Isaac Kankam-Boadu, Jianxi Huang, Xuecao Li

Summary: Smallholder agriculture is essential for food production in sub-Saharan Africa, but yields are below their potential and are vulnerable to climate change impacts. This paper presents data collected in Ghana on crop locations, biophysical parameters, crop yield, and biomass. The data is used to evaluate cropland masks, develop an LAI retrieval method, create a maize classification dataset, and explore the relationship between LAI and crop yield. This dataset contributes to understanding crop evolution and distribution in smallholder farming systems.

EARTH SYSTEM SCIENCE DATA (2022)

Article Ecology

Laser scanning reveals potential underestimation of biomass carbon in temperate forest

Kim Calders, Hans Verbeeck, Andrew Burt, Niall Origo, Joanne Nightingale, Yadvinder Malhi, Phil Wilkes, Pasi Raumonen, Robert G. H. Bunce, Mathias Disney

Summary: Accurate assessment of forest above-ground biomass is crucial for quantifying climate mitigation benefits. However, the current allometric models used for estimation are biased and result in substantial errors. Testing the underlying assumptions of these models and improving measurement methods are urgent priorities to address this issue.

ECOLOGICAL SOLUTIONS AND EVIDENCE (2022)

Article Geosciences, Multidisciplinary

Bayesian atmospheric correction over land: Sentinel-2/MSI and Landsat 8/OLI

Feng Yin, Philip E. Lewis, Jose L. Gomez-Dans

Summary: This work presents a Sensor Invariant Atmospheric Correction (SIAC) approach for mitigating atmospheric effects on medium resolution optical remote sensing data. By using a probabilistic framework, the method provides per-pixel uncertainty estimates for aerosol optical thickness (AOT), total column water vapour (TCWV), and surface reflectance. The experimental results demonstrate the effectiveness of SIAC in estimating AOT, TCWV, and surface reflectance accurately, and the method also provides viable uncertainty estimates.

GEOSCIENTIFIC MODEL DEVELOPMENT (2022)

Article Environmental Sciences

Improving estimates of sub-daily gross primary production from solar-induced chlorophyll fluorescence by accounting for light distribution within canopy

Ruonan Chen, Liangyun Liu, Xinjie Liu, Zhunqiao Liu, Lianhong Gu, Uwe Rascher

Summary: This study presents methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale.

REMOTE SENSING OF ENVIRONMENT (2024)

Article Environmental Sciences

Evaluating the spatial patterns of US urban NOx emissions using TROPOMI NO2

Daniel L. Goldberg, Madankui Tao, Gaige Hunter Kerr, Siqi Ma, Daniel Q. Tong, Arlene M. Fiore, Angela F. Dickens, Zachariah E. Adelman, Susan C. Anenberg

Summary: A novel method is applied in this study to directly use satellite data to evaluate the spatial patterns of urban NOx emissions inventories. The results show that the 108 spatial surrogates used by NEMO are generally appropriate, but there may be underestimation in areas with dense intermodal facilities and overestimation in wealthy communities.

REMOTE SENSING OF ENVIRONMENT (2024)

Article Environmental Sciences

Wide-swath and high-resolution whisk-broom imaging and on-orbit performance of SDGSAT-1 thermal infrared spectrometer

Zhuoyue Hu, Xiaoyan Li, Liyuan Li, Xiaofeng Su, Lin Yang, Yong Zhang, Xingjian Hu, Chun Lin, Yujun Tang, Jian Hao, Xiaojin Sun, Fansheng Chen

Summary: This paper proposes a whisk-broom imaging method using a long-linear-array detector and high-precision scanning mirror to achieve high-resolution and wide-swath thermal infrared data. The method has been implemented in the SDGs satellite and has shown promising test results.

REMOTE SENSING OF ENVIRONMENT (2024)

Article Environmental Sciences

Simulation of urban thermal anisotropy at remote sensing pixel scales: Evaluating three schemes using GUTA-T over Toulouse city

Dandan Wang, Leiqiu Hu, James A. Voogt, Yunhao Chen, Ji Zhou, Gaijing Chang, Jinling Quan, Wenfeng Zhan, Zhizhong Kang

Summary: This study evaluates different schemes for determining model coefficients to quantify and correct the anisotropic impact from remote sensing LST for urban applications. The schemes have consistent results and accurately estimate parameter values, facilitating the broadening of parametric models.

REMOTE SENSING OF ENVIRONMENT (2024)

Article Environmental Sciences

Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar

Jamie Tolan, Hung - Yang, Benjamin Nosarzewski, Guillaume Couairon, Huy V. Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie

Summary: Vegetation structure mapping is crucial for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. This study presents the first high-resolution canopy height maps for California and Sao Paulo, achieved through the use of very high resolution satellite imagery and aerial lidar data. The maps provide valuable tools for forest structure assessment and land use monitoring.

REMOTE SENSING OF ENVIRONMENT (2024)

Article Environmental Sciences

Spatially constrained atmosphere and surface retrieval for imaging spectroscopy

Regina Eckert, Steffen Mauceri, David R. Thompson, Jay E. Fahlen, Philip G. Brodrick

Summary: In this paper, a mathematical framework is proposed to improve the retrieval of surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. Experimental results show that this framework can reduce the surface reflectance retrieval error and surface-related biases.

REMOTE SENSING OF ENVIRONMENT (2024)

Article Environmental Sciences

A vehicle imaging approach to acquire ground truth data for upscaling to satellite data: A case study for estimating harvesting dates

Chongya Jiang, Kaiyu Guan, Yizhi Huang, Maxwell Jong

Summary: This study presents the Field Rover method, which uses vehicle-mounted cameras to collect ground truth data on crop harvesting status. The machine learning approach and remote sensing technology are employed to upscale the results to a regional scale. The accuracy of the remote sensing method in predicting crop harvesting dates is validated through comparison with satellite data.

REMOTE SENSING OF ENVIRONMENT (2024)

Article Environmental Sciences

Low-amplitude brittle deformations revealed by UAV surveys in alluvial fans along the northwest coast of Lake Baikal: Neotectonic significance and geological hazards

Oksana V. Lunina, Anton A. Gladkov, Alexey V. Bochalgin

Summary: In this study, an unmanned aerial vehicle (UAV) was used to detect and map surface discontinuities with displacements of a few centimeters, indicating the presence of initial geological deformations. The study found that sediments of alluvial fans are susceptible to various tectonic and exogenous deformational processes, and the interpretation of ultra-high resolution UAV images can help recognize low-amplitude brittle deformations at an early stage. UAV surveys are critical for discerning neotectonic activity and its related hazards over short observation periods.

REMOTE SENSING OF ENVIRONMENT (2024)

Article Environmental Sciences

Global retrieval of the spectrum of terrestrial chlorophyll fluorescence: First results with TROPOMI

Feng Zhao, Weiwei Ma, Jun Zhao, Yiqing Guo, Mateen Tariq, Juan Li

Summary: This study presents a data-driven approach to reconstruct the terrestrial SIF spectrum using measurements from the TROPOMI instrument on Sentinel-5 precursor mission. The reconstructed SIF spectrum shows improved spatiotemporal distributions and demonstrates consistency with other datasets, indicating its potential for better understanding of the ecosystem function.

REMOTE SENSING OF ENVIRONMENT (2024)

Article Environmental Sciences

Choosing a sample size allocation to strata based on trade-offs in precision when estimating accuracy and area of a rare class from a stratified sample

Stephen Stehman, John E. Wagner

Summary: This article investigates optimal sample allocation in stratified random sampling for estimation of accuracy and proportion of area in applications where the target class is rare. The study finds that precision of estimated accuracy has a stronger impact on sample allocation than estimation of proportion of area, and the trade-offs among these estimates become more pronounced as the target class becomes rarer. The results provide quantitative evidence to guide sample allocation decisions in specific applications.

REMOTE SENSING OF ENVIRONMENT (2024)

Article Environmental Sciences

Use of a new Tibetan Plateau network for permafrost to characterize satellite-based products errors: An application to soil moisture and freeze/ thaw

Jingyao Zheng, Tianjie Zhao, Haishen Lu, Defu Zou, Nemesio Rodriguez-Fernandez, Arnaud Mialon, Philippe Richaume, Jianshe Xiao, Jun Ma, Lei Fan, Peilin Song, Yonghua Zhu, Rui Li, Panpan Yao, Qingqing Yang, Shaojie Du, Zhen Wang, Zhiqing Peng, Yuyang Xiong, Zanpin Xing, Lin Zhao, Yann Kerr, Jiancheng Shi

Summary: Soil moisture and freeze/thaw (F/T) play a crucial role in water and heat exchanges at the land-atmosphere interface. This study reports the establishment of a wireless sensor network for soil moisture and temperature over the permafrost region of Tibetan Plateau. Satellite-based surface soil moisture (SSM) and F/T products were evaluated using ground-based measurements. The results show the reliability of L-band passive microwave SSM and F/T products, while existing F/T products display earlier freezing and later thawing, leading to unsatisfactory accuracy.

REMOTE SENSING OF ENVIRONMENT (2024)