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Author: Ana Cristina Gonçalves
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
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.
Author: Ana Cristina Gonçalves
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
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.
Author: Adélia M. O.
Publisher:
ISBN:
Category : Technology
Languages : en
Pages :
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Book Description
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.
Author: Lalit Kumar
Publisher: MDPI
ISBN: 3039212095
Category : Science
Languages : en
Pages : 264
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Book Description
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.
Author: Jaya Shankar Tumuluru
Publisher: BoD – Books on Demand
ISBN: 9535129376
Category : Technology & Engineering
Languages : en
Pages : 518
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Book Description
This book is the outcome of contributions by many experts in the field from different disciplines, various backgrounds, and diverse expertise. This book provides information on biomass volume calculation methods and biomass valorization for energy production. The chapters presented in this book include original research and review articles. I hope the research presented in this book will help to advance the use of biomass for bioenergy production and valorization. The key features of the book are: Providing information on biomass volume estimation using direct, nondestructive and remote sensing methods Biomass valorization for energy using thermochemical (gasification and pyrolysis) and biochemical (fermentation) conversion processes.
Author: Crismeire Isbaex
Publisher:
ISBN:
Category : Electronic books
Languages : en
Pages : 0
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Book Description
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.
Author: Theresa Katherine Burcsu
Publisher:
ISBN:
Category :
Languages : en
Pages : 226
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Book Description
Author: Erkki Tomppo
Publisher: Springer Science & Business Media
ISBN: 1402087136
Category : Technology & Engineering
Languages : en
Pages : 383
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Book Description
Building on more than a decade of innovative research into multi-source forest inventory (MS-NFI) this book presents full details of the development, outputs and applications of the improved k-NN method. The method, which was pioneered in Finland in 1990, is rapidly becoming a world standard in forest inventory, having been adopted as standard in Finland and Sweden, and recently introduced in Austria and across the US. The book describes in detail the full MS-NFI process, and the input data used – including field data, satellite images, and digital map data, as well as coarse-scale variation of forest variables. It also presents comprehensive information on the types of outputs which can be derived, including maps and statistics, describing, for example, stock volumes and development, dominant tree species, age-class distribution, and large and small-scale variation. The book will provide an invaluable resource for those involved in forest inventory, including government departments and bodies involved in forest policy, management and monitoring, forest managers, and researchers and graduate students interested in forest inventory, modelling and analysis. It will find an additional market among those interested in Earth observation, ecology and broader areas of environmental and natural resource management. Erkki Tomppo was the winner of the 1997 Marcus Wallenberg Prize for his work on the k-NN method.
Author: Dimitris Zianis
Publisher:
ISBN:
Category : Biomass energy
Languages : en
Pages : 70
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Book Description
A review of stem volume and biomass equations for tree species growing in Europe is presented. The mathematical forms of the empirical models, the associated statistical parameters and information about the size of the trees and the country of origin were collated from scientific articles and from technical reports. The collected information provides a basic tool for estimation of carbon stocks and nutrient balance of forest ecosystems across Europe as well as for validation of theoretical models of biomass allocation.
Author: Prem C. Pandey
Publisher: John Wiley & Sons
ISBN: 1119615976
Category : Technology & Engineering
Languages : en
Pages : 528
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Book Description
Sustainable management of natural resources is an urgent need, given the changing climatic conditions of Earth systems. The ability to monitor natural resources precisely and accurately is increasingly important. New and advanced remote sensing tools and techniques are continually being developed to monitor and manage natural resources in an effective way. Remote sensing technology uses electromagnetic sensors to record, measure and monitor even small variations in natural resources. The addition of new remote sensing datasets, processing techniques and software makes remote sensing an exact and cost-effective tool and technology for natural resource monitoring and management. Advances in Remote Sensing for Natural Resources Monitoring provides a detailed overview of the potential applications of advanced satellite data in natural resource monitoring. The book determines how environmental and - ecological knowledge and satellite-based information can be effectively combined to address a wide array of current natural resource management needs. Each chapter covers different aspects of remote sensing approach to monitor the natural resources effectively, to provide a platform for decision and policy. This important work: Provides comprehensive coverage of advances and applications of remote sensing in natural resources monitoring Includes new and emerging approaches for resource monitoring with case studies Covers different aspects of forest, water, soil- land resources, and agriculture Provides exemplary illustration of themes such as glaciers, surface runoff, ground water potential and soil moisture content with temporal analysis Covers blue carbon, seawater intrusion, playa wetlands, and wetland inundation with case studies Showcases disaster studies such as floods, tsunami, showing where remote sensing technologies have been used This edited book is the first volume of the book series Advances in Remote Sensing for Earth Observation.
Author: José Mauricio Galeana
Publisher:
ISBN:
Category : Science
Languages : en
Pages :
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Book Description
Over the past two decades, one of the research topics in which many works have been done is spatial modeling of biomass through synergies between remote sensing, forestry, and ecology. In order to identify satellite-derived indices that have correlation with forest structural parameters that are related with carbon storage inventories and forest monitoring, topics that are useful as environmental tools of public policies to focus areas with high environmental value. In this chapter, we present a review of different models of spatial distribution of biomass and resources based on remote sensing that are widely used. We present a case study that explores the capability of canopy fraction cover and digital canopy height model (DCHM) for modeling the spatial distribution of the aboveground biomass of two forests, dominated by Abies Religiosa and Pinus spp., located in Central Mexico. It also presents a comparison of different spatial models and products, in order to know the methods that achieved the highest accuracy through root-mean-square error. Lastly, this chapter provides concluding remarks on the case study and its perspectives in remote sensing-based biomass estimation.
