Biomass Estimation Using Satellite Based Data
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Biomass Estimation Using Satellite Based Data
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Author : Patricia Lourenco
language : en
Publisher:
Release Date : 2020
Biomass Estimation Using Satellite Based Data written by Patricia Lourenco and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Electronic books categories.
Comprehensive measurements of global forest aboveground biomass (AGB) are crucial information to promote the sustainable management of forests to mitigate climate change and preserve the multiple ecosystem services provided by forests. Optical and radar sensors are available at different spatial, spectral, and temporal scales. The integration of multi-sources sensor data with field measurements, using appropriated algorithms to identify the relationship between remote sensing predictors and reference measurements, is important to improve forest AGB estimation. This chapter aims to present different types of predicted variables derived from multi-sources sensors, such as original spectral bands, transformed images, vegetation indices, textural features, and different regression algorithms used (parametric and non-parametric) that contribute to a more robust, practical, and cost-effective approach for forest AGB estimation at different levels.
Above Ground Biomass Estimation With High Spatial Resolution Satellite Images
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Author : Adélia M. O.
language : en
Publisher:
Release Date : 2017
Above Ground Biomass Estimation With High Spatial Resolution Satellite Images written by Adélia M. O. and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Technology categories.
Assessment and monitoring of forest biomass are frequently done with allometric functions per species for inventory plots. The estimation per area unit is carried out with an extrapolation method. In this chapter, a review of the recent methods to estimate forest above-ground biomass (AGB) using remote sensing data is presented. A case study is given with an innovative methodology to estimate above-ground biomass based on crown horizontal projection obtained with high spatial resolution satellite images for two evergreen oak species. The linear functions fitted for pure, mixed and both compositions showed a good performance. Also, the functions with dummy variables to distinguish species and compositions adjusted had the best performance. An error threshold of 5% corresponds to stand areas of 8.7 and 5.5 ha for the functions of all species and compositions without and with dummy variables. This method enables the overall area evaluation, and it is easily implemented in a geographic information system environment.
Chapter Above Ground Biomass Estimation With High Spatial Resolution Satellite Images
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Author : Ana Cristina Gonçalves
language : en
Publisher:
Release Date : 2017
Chapter Above Ground Biomass Estimation With High Spatial Resolution Satellite Images written by Ana Cristina Gonçalves and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Assessment and monitoring of forest biomass are frequently done with allometric functions per species for inventory plots. The estimation per area unit is carried out with an extrapolation method. In this chapter, a review of the recent methods to estimate forest above-ground biomass (AGB) using remote sensing data is presented. A case study is given with an innovative methodology to estimate above-ground biomass based on crown horizontal projection obtained with high spatial resolution satellite images for two evergreen oak species. The linear functions fitted for pure, mixed and both compositions showed a good performance. Also, the functions with dummy variables to distinguish species and compositions adjusted had the best performance. An error threshold of 5% corresponds to stand areas of 8.7 and 5.5)ha for the functions of all species and compositions without and with dummy variables. This method enables the overall area evaluation, and it is easily implemented in a geographic information system environment.
Remote Sensing Of Above Ground Biomass
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Author : Lalit Kumar
language : en
Publisher: MDPI
Release Date : 2019-08-20
Remote Sensing Of Above Ground Biomass written by Lalit Kumar and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-20 with Science categories.
Above ground biomass has been listed by the Intergovernmental Panel on Climate Change as one of the five most prominent, visible, and dynamic terrestrial carbon pools. The increased awareness of the impacts of climate change has seen a burgeoning need to consistently assess carbon stocks to combat carbon sequestration. An accurate estimation of carbon stocks and an understanding of the carbon sources and sinks can aid the improvement and accuracy of carbon flux models, an important pre-requisite of climate change impact projections. Based on 15 research topics, this book demonstrates the role of remote sensing in quantifying above ground biomass (forest, grass, woodlands) across varying spatial and temporal scales. The innovative application areas of the book include algorithm development and implementation, accuracy assessment, scaling issues (local–regional–global biomass mapping), and the integration of microwaves (i.e. LiDAR), along with optical sensors, forest biomass mapping, rangeland productivity and abundance (grass biomass, density, cover), bush encroachment biomass, and seasonal and long-term biomass monitoring.
Aboveground Biomass Estimation Using Spaceborne Lidar In Managed Conifer Forests In South Central British Columbia
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Author : Laura Innice Duncanson
language : en
Publisher:
Release Date : 2009
Aboveground Biomass Estimation Using Spaceborne Lidar In Managed Conifer Forests In South Central British Columbia written by Laura Innice Duncanson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.
In the context of growing concerns regarding global climatic change, developing methods to assess the carbon storage of various ecosystems has become important. This research attempts to develop low or no cost methods to estimate carbon stock in forests using satellite-based data. More specifically, this research explores the utility of spaceborne Light Detection and Ranging (LiDAR) data for forest canopy height and aboveground biomass estimation. High-resolution (sub meter) airborne LiDAR data were collected and validated for a 75 000 ha area near Clearwater, British Columbia. Airborne LiDAR has been widely demonstrated to yield accurate aboveground biomass estimates. 110 temporally coincident Geospatial Laser Altimeter System (GLAS) waveforms from the study site were used in this research. First, I demonstrate that airborne LiDAR can be manipulated to represent waveform curves with a high degree of similarity to GLAS waveform curves. Based on the relationship between the GLAS and simulated waveforms I am able to visualize the ground contribution to GLAS waveforms. Second, I calculate a suite of novel GLAS waveform metrics and develop models of terrain relief, canopy height, and terrain adjusted canopy height. These models compare favourably to other GLAS studies (terrain relief R2=0.76, canopy height R2= 0.75-0.88) and indicate that terrain relief should be included in GLAS derived canopy height models. Third, I attempt to extrapolate the spatially discrete GLAS estimates to spatially continuous estimates using Landsat TM data. Landsat data have been used extensively for AGBM estimation, although they are known to have limitations for studies in high biomass or structurally complex forests. I develop models to predict GLAS AGBM estimates from Landsat bands and indices (R2=0.6). I then use an airborne LiDAR derived AGBM map to generate a map of over and under prediction of AGBM, and evaluate the success of the model in areas of differing forest species and structure. I conclude that GLAS data is appropriate for AGBM estimation in forests over a wide range of biomass values, but that GLAS and Landsat integration for AGBM estimation should only be conducted in forests with less than approximately 120 Mg/ha of AGBM, 60 years of age, or 60% canopy cover.
Applications Of The New Remote Sensing Method To The Forest Biomass Estimation In An Old Growth Chamaecyparis Obtusa Stand In The Akazawa Forest Reserve
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Author : Nan Wang
language : en
Publisher:
Release Date : 2017
Applications Of The New Remote Sensing Method To The Forest Biomass Estimation In An Old Growth Chamaecyparis Obtusa Stand In The Akazawa Forest Reserve written by Nan Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
For accurate measurement of forest biomass in the Akazawa Forest Reserve, this study analyzed texture measures derived from GeoEye-1 satellite data using the individual tree crown (ITC) method. On this basis, canopy area, tree tops and tree species of individual trees were delineated. Canopy area was used to calculate the DBH of trees in canopy layer based on canopy-DBH curve in this stand. In this study, the estimation models, between DBH and height, and between canopy area and DBH were developed by linear regression using forest survey data. Then according to the results of satellite data interpreted the biomass of every tree was calculated by biomass expansion factor (BEF). This method was verified against the survey data from old-growth Chamaecyparis obtusa stand composed of various cover types. For Chamaecyparis obtusa, the accuracy of biomass estimation was higher than 84%. However, the accuracy of Chamaecyparis pisifera was less than 60%, because some Chamaecyparis pisifera trees were misidentified as Chamaecyparis obtusa, and canopy area of Chamaecyparis pisifera was underestimated in the high-density stand. For Thujopsis dolabrata, the accuracy ranged from 22.4 % to 78.9%, and from 63.4% to 84.6% for broad-leaved trees, because many of them were understory. These results indicated that estimation of old-growth forest biomass based on high resolution satellite data, might be validated for estimating biomass at the individual tree level improved by developing and applying forest stratum-specific models with the ITC-survey data as a bridging reference in addition to spectral information. This approach is useful for biomass estimation whether is used to calculate biomass of individual tree or forest.
The Potential Of Sentinel 2 Satellite Images For Land Cover Land Use And Forest Biomass Estimation
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Author : Crismeire Isbaex
language : en
Publisher:
Release Date : 2019
The Potential Of Sentinel 2 Satellite Images For Land Cover Land Use And Forest Biomass Estimation written by Crismeire Isbaex and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Electronic books categories.
Mapping land-cover/land-use (LCLU) and estimating forest biomass using satellite images is a challenge given the diversity of sensors available and the heterogeneity of forests. Copernicus program served by the Sentinel satellites family and the Google Earth Engine (GEE) platform, both with free and open services accessible to its users, present a good approach for mapping vegetation and estimate forest biomass on a global, regional, or local scale, periodically and in a repeated way. The Sentinel-2 (S2) systematically acquires optical imagery and provides global monitoring data with high spatial resolution (10,Äì60¬†m) images. Given the novelty of information on the use of S2 data, this chapter presents a review on LCLU maps and forest above-ground biomass (AGB) estimates, in addition to exploring the efficiency of using the GEE platform. The Sentinel data have great potential for studies on LCLU classification and forest biomass estimates. The GEE platform is a promising tool for executing complex workflows of satellite data processing.
Applications Of Remote Sensing Data In Mapping Of Forest Growing Stock And Biomass
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Author : José Aranha
language : en
Publisher: MDPI
Release Date : 2021-09-01
Applications Of Remote Sensing Data In Mapping Of Forest Growing Stock And Biomass written by José Aranha and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-01 with Science categories.
This Special Issue (SI), entitled "Applications of Remote Sensing Data in Mapping of Forest Growing Stock and Biomass”, resulted from 13 peer-reviewed papers dedicated to Forestry and Biomass mapping, characterization and accounting. The papers' authors presented improvements in Remote Sensing processing techniques on satellite images, drone-acquired images and LiDAR images, both aerial and terrestrial. Regarding the images’ classification models, all authors presented supervised methods, such as Random Forest, complemented by GIS routines and biophysical variables measured on the field, which were properly georeferenced. The achieved results enable the statement that remote imagery could be successfully used as a data source for regression analysis and formulation and, in this way, used in forestry actions such as canopy structure analysis and mapping, or to estimate biomass. This collection of papers, presented in the form of a book, brings together 13 articles covering various forest issues and issues in forest biomass calculation, constituting an important work manual for those who use mixed GIS and RS techniques.
A Comparative Analysis Of Satellite Based Approaches For Aboveground Biomass Estimation In The Brazilian Amazon
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Author : Dengsheng Lu Lu
language : en
Publisher:
Release Date : 2008
A Comparative Analysis Of Satellite Based Approaches For Aboveground Biomass Estimation In The Brazilian Amazon written by Dengsheng Lu Lu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
The moist tropical forest in the Amazon has been regarded as an important part in global carbon budget. Deforestation since the 1970s has made it an important carbon source, but the rapid growth of secondary vegetation may compensate its negative role to a certain degree. In order to reduce the uncertainty in carbon estimation at regional or global scale, it is critical to timely provide the carbon spatial distribution with high accuracy. Remotely sensed data have become the primary source for mapping carbon storage at local or regional scale. Thanks to the NASA LBA-ECO funded projects (1998 - 2008), we have explored aboveground biomass (AGB) estimation in the eastern and western Brazilian Amazon with Landsat Thematic Mapper (TM) images. Different TM spectral responses and textures were examined for improving the AGB estimation performance. Subpixel information extracted from the spectral mixture analysis of TM multispectral images was also examined. Entropy was used to analyze the complexity of forest stand structure and to examine impacts of different stand structures on TM reflectance data. This research indicates that estimating AGB is still a challenge task, especially for the sites with complicated biophysical environments. The TM spectral responses are more suitable for AGB estimation in the sites with relatively simple forest stand structure than for the sites with complicated forest stand structure. Conversely, textures appear more important than spectral responses in AGB estimation in the sites with complicated forest stand structure. A combination of spectral responses and textures improves AGB estimation performance. Using fraction images perform better for successional vegetation AGB estimation than using TM spectral signatures. However, both models based on TM spectral signatures and fractions provided poor performance for primary forest AGB estimation. The complex stand structure and associated canopy shadow greatly reduced relationships between AGB and TM reflectance or fraction images. Different study areas having various biophysical conditions affect AGB estimation performance. More research is needed to focus on the integration of optical and radar data, the use of multisource data, and the selection of suitable variables and algorithms for AGB estimation at different scales. The AGB estimates at local scale may be used as a reference data for calibrating or validating the model-based carbon estimates at regional or global scale. Sessão: 3. Integrando fluxos de carbono para a regi?o a partir de medidas em pontos de coleta, torres e aeronaves. Tipo de Apresentação: Oral.
Secondary Forest Age And Tropical Forest Biomass Estimation Using Tm
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Author : National Aeronautics and Space Administration (NASA)
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-06-11
Secondary Forest Age And Tropical Forest Biomass Estimation Using Tm written by National Aeronautics and Space Administration (NASA) and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-11 with categories.
The age of secondary forests in the Amazon will become more critical with respect to the estimation of biomass and carbon budgets as tropical forest conversion continues. Multitemporal Thematic Mapper data were used to develop land cover histories for a 33,000 Square kM area near Ariquemes, Rondonia over a 7 year period from 1989-1995. The age of the secondary forest, a surrogate for the amount of biomass (or carbon) stored above-ground, was found to be unimportant in terms of biomass budget error rates in a forested TM scene which had undergone a 20% conversion to nonforest/agricultural cover types. In such a situation, the 80% of the scene still covered by primary forest accounted for over 98% of the scene biomass. The difference between secondary forest biomass estimates developed with and without age information were inconsequential relative to the estimate of biomass for the entire scene. However, in futuristic scenarios where all of the primary forest has been converted to agriculture and secondary forest (55% and 42% respectively), the ability to age secondary forest becomes critical. Depending on biomass accumulation rate assumptions, scene biomass budget errors on the order of -10% to +30% are likely if the age of the secondary forests are not taken into account. Single-date TM imagery cannot be used to accurately age secondary forests into single-year classes. A neural network utilizing TM band 2 and three TM spectral-texture measures (bands 3 and 5) predicted secondary forest age over a range of 0-7 years with an RMSE of 1.59 years and an R(Squared) (sub actual vs predicted) = 0.37. A proposal is made, based on a literature review, to use satellite imagery to identify general secondary forest age groups which, within group, exhibit relatively constant biomass accumulation rates.Nelson, R. F. and Kimes, D. S. and Salas, W. A. and Routhier, M.Goddard Space Flight CenterAGE FACTOR; AMAZON REGION (SOUTH AMERICA); CARBON; TROPICAL REGIONS; DEFORESTATION; RAIN