Development And Refinement Of New Products From Multi Angle Remote Sensing To Improve Leaf Area Index Retrieval

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Development and Refinement of New Products from Multi-angle Remote Sensing to Improve Leaf Area Index Retrieval

Author : Jan Pisek
Publisher :
ISBN 13 : 9780494610565
Total Pages : 0 pages
Book Rating : 4.6/5 (15 download)

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Book Synopsis Development and Refinement of New Products from Multi-angle Remote Sensing to Improve Leaf Area Index Retrieval by : Jan Pisek

Download or read book Development and Refinement of New Products from Multi-angle Remote Sensing to Improve Leaf Area Index Retrieval written by Jan Pisek and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Remote sensing provides methods to infer vegetation information over large areas at a variety of spatial and temporal resolutions that is of great use for terrestrial carbon cycle modeling. Understory vegetation and foliage clumping in forests present a challenge for accurate estimates of vegetation structural information. Multi-angle remote sensing was used to derive and refine new information about the vegetation structure for the purpose of improving global leaf area index mapping. The previous first ever global mapping of the vegetation clumping index with a limited eight-month multi-angular POLDER 1 dataset was expanded by integrating new, complete year-round observations from POLDER 3. A simple topographic compensation function was devised to correct negative bias in the data set cause by topographic effects. The clumping index reductions can reach up to 30% from the topographically non-compensated values, depending on terrain complexity and land cover type. The new global clumping index map is compared with an assembled set of field measurements, covering four continents and diverse biomes. Finally, inclusion of the new vegetation structural information, including background reflectivity and clumping index, gained from the multi-angle remote sensing was then shown to improve the performance of LAI retrieval algorithms over forests. A field experiment with multi-angle, high resolution airborne observations over modified and natural backgrounds (understory, moss, litter, soil) was conducted in 2007 near Sudbury, Ontario to test a methodology for the background reflectivity retrieval. The experiment showed that it is feasible to retrieve the background information, especially over the crucial low to intermediate canopy density range where the effect of the understory vegetation is the largest. The tested methodology was then applied to background reflectivity mapping over conterminous United States, Canada, Mexico, and Caribbean land mass using space-borne Multi-angle Imaging SpectroRadiometer (MISR) data. Important seasonal development of the forest background vegetation was observed across a wide longitudinal and latitudinal span of the study area.

Development and Refinement of New Products from Multi-angle Remote Sensing to Improve Leaf Area Index Retrieval

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (68 download)

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Book Synopsis Development and Refinement of New Products from Multi-angle Remote Sensing to Improve Leaf Area Index Retrieval by :

Download or read book Development and Refinement of New Products from Multi-angle Remote Sensing to Improve Leaf Area Index Retrieval written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: PhD.

Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters

Author : Francisco Javier García-Haro
Publisher : MDPI
ISBN 13 : 3039212397
Total Pages : 334 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters by : Francisco Javier García-Haro

Download or read book Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters written by Francisco Javier García-Haro and published by MDPI. This book was released on 2019-09-16 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monitoring of vegetation structure and functioning is critical to modeling terrestrial ecosystems and energy cycles. In particular, leaf area index (LAI) is an important structural property of vegetation used in many land surface vegetation, climate, and crop production models. Canopy structure (LAI, fCover, plant height, and biomass) and biochemical parameters (leaf pigmentation and water content) directly influence the radiative transfer process of sunlight in vegetation, determining the amount of radiation measured by passive sensors in the visible and infrared portions of the electromagnetic spectrum. Optical remote sensing (RS) methods build relationships exploiting in situ measurements and/or as outputs of physical canopy radiative transfer models. The increased availability of passive (radar and LiDAR) RS data has fostered their use in many applications for the analysis of land surface properties and processes, thanks also to their insensitivity to weather conditions and the capability to exploit rich structural and textural information. Data fusion and multi-sensor integration techniques are pressing topics to fully exploit the information conveyed by both optical and microwave bands.

Remote Sensing Technology Applications in Forestry and REDD+

Author : Kim Calders
Publisher : MDPI
ISBN 13 : 3039284703
Total Pages : 244 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Remote Sensing Technology Applications in Forestry and REDD+ by : Kim Calders

Download or read book Remote Sensing Technology Applications in Forestry and REDD+ written by Kim Calders and published by MDPI. This book was released on 2020-03-17 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems, and community-based monitoring of forests. The UNFCCC REDD+ mechanism has advanced the remote sensing community and the development of forest geospatial products that can be used by countries for the international reporting and national forest monitoring. However, an urgent need remains to better understand the options and limitations of remote and close-range sensing techniques in the field of forest degradation and forest change. Therefore, we invite scientists working on remote sensing technologies, close-range sensing, and field data to contribute to this Special Issue. Topics of interest include: (1) novel remote sensing applications that can meet the needs of forest resource information and REDD+ MRV, (2) case studies of applying remote sensing data for REDD+ MRV, (3) timeseries algorithms and methodologies for forest resource assessment on different spatial scales varying from the tree to the national level, and (4) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV. We particularly welcome submissions on data fusion.

A Multi-sensor Analysis of Vegetation Indices for Leaf Area Index Retrieval in Precision Agriculture

Author : A.T. Areda
Publisher :
ISBN 13 :
Total Pages : 89 pages
Book Rating : 4.:/5 (11 download)

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Book Synopsis A Multi-sensor Analysis of Vegetation Indices for Leaf Area Index Retrieval in Precision Agriculture by : A.T. Areda

Download or read book A Multi-sensor Analysis of Vegetation Indices for Leaf Area Index Retrieval in Precision Agriculture written by A.T. Areda and published by . This book was released on 2013 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters

Author : Hongliang Fang
Publisher :
ISBN 13 : 9783039212408
Total Pages : 1 pages
Book Rating : 4.2/5 (124 download)

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Book Synopsis Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters by : Hongliang Fang

Download or read book Remote Sensing of Leaf Area Index (LAI) and Other Vegetation Parameters written by Hongliang Fang and published by . This book was released on 2019 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monitoring of vegetation structure and functioning is critical to modeling terrestrial ecosystems and energy cycles. In particular, leaf area index (LAI) is an important structural property of vegetation used in many land surface vegetation, climate, and crop production models. Canopy structure (LAI, fCover, plant height, and biomass) and biochemical parameters (leaf pigmentation and water content) directly influence the radiative transfer process of sunlight in vegetation, determining the amount of radiation measured by passive sensors in the visible and infrared portions of the electromagnetic spectrum. Optical remote sensing (RS) methods build relationships exploiting in situ measurements and/or as outputs of physical canopy radiative transfer models. The increased availability of passive (radar and LiDAR) RS data has fostered their use in many applications for the analysis of land surface properties and processes, thanks also to their insensitivity to weather conditions and the capability to exploit rich structural and textural information. Data fusion and multi-sensor integration techniques are pressing topics to fully exploit the information conveyed by both optical and microwave bands.

Remote Sensing of Leaf Area Index

Author :
Publisher :
ISBN 13 : 9789521058721
Total Pages : 66 pages
Book Rating : 4.0/5 (587 download)

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Book Synopsis Remote Sensing of Leaf Area Index by :

Download or read book Remote Sensing of Leaf Area Index written by and published by . This book was released on 2009 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Remote Sensing Application for Precision Agriculture

Author : Matthew McCabe
Publisher : Frontiers Media SA
ISBN 13 : 2832531822
Total Pages : 372 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Remote Sensing Application for Precision Agriculture by : Matthew McCabe

Download or read book Remote Sensing Application for Precision Agriculture written by Matthew McCabe and published by Frontiers Media SA. This book was released on 2023-08-11 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Precision agriculture is used to improve site-specific agricultural decision-making based on data collection and analysis, formulation of site-specific management recommendations, and implementation of management practices to correct for factors that can limit crop growth, yield, and quality. Various approaches for the remote sensing of soil fertility, water stress, diseases and infestations, and crop growth and condition have been developed and applied for precision agricultural purposes. With developments in remote sensing technologies, the spatial and spectral resolution and return frequencies available from both satellite and other remote collection platforms have improved to the point that the promise of precision agriculture can increasingly be realized. Unmanned aerial vehicles (UAV) in particular are providing newer and deeper insights, leveraging their high resolution, sensor-carrying flexibility and dynamic acquisition schedule. This range of remote sensing platforms has been used to estimate comprehensive information related to crop health and dynamics, providing rapid retrievals of leaf area index, canopy cover, chlorophyll, nitrogen, canopy/leaf water content, canopy/leaf temperature, biomass, and yield, amongst many other variables of interest. In combination, they allow for the expansion from local to regional scales and beyond. There has never been a greater opportunity for remote sensing data to enable precision agricultural insights that can be used to better monitor, manage and respond to in-field changes that might impact crop growth, health and yield.

The Segmentation of Reflectances from Moderate Resolution Remote Sensing Data for the Retrieval of Land Cover Specific Leaf Area Index

Download The Segmentation of Reflectances from Moderate Resolution Remote Sensing Data for the Retrieval of Land Cover Specific Leaf Area Index PDF Online Free

Author : Marko Braun
Publisher :
ISBN 13 :
Total Pages : 223 pages
Book Rating : 4.:/5 (229 download)

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Book Synopsis The Segmentation of Reflectances from Moderate Resolution Remote Sensing Data for the Retrieval of Land Cover Specific Leaf Area Index by : Marko Braun

Download or read book The Segmentation of Reflectances from Moderate Resolution Remote Sensing Data for the Retrieval of Land Cover Specific Leaf Area Index written by Marko Braun and published by . This book was released on 2007 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Hyperspectral Remote Sensing Algorithms for Retrieving Forest Chlorophyll Content

Author : Yongqin Zhang
Publisher :
ISBN 13 : 9780494279649
Total Pages : 388 pages
Book Rating : 4.2/5 (796 download)

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Book Synopsis Hyperspectral Remote Sensing Algorithms for Retrieving Forest Chlorophyll Content by : Yongqin Zhang

Download or read book Hyperspectral Remote Sensing Algorithms for Retrieving Forest Chlorophyll Content written by Yongqin Zhang and published by . This book was released on 2007 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: The effects of canopy structure on optical remote sensing signals were investigated using the geometrical-optical model 4-Scale. A look-up-table approach was developed to provide the probabilities of viewing sunlit foliage and background components, and a spectral multiple scattering factor as functions of LAI, and solar and view zenith angle. Leaf reflectance spectra and chlorophyll content were retrieved from the hyperspectral Compact Airborne Spectrographic Imager (CASI) images with a root mean square error of 4.34 mug/cm 2 for needleleaf species. LAI was retrieved and chlorophyll content was mapped using CASI imagery. Quantitative estimates of forest chlorophyll content from hyperspectral remote sensing are of great use for terrestrial carbon cycle modeling and sustainable forest management. Open forest canopies present a big challenge for the separation of the effects from canopy structure and leaf optical properties, and thus the retrieval of biochemical parameters. Process-based algorithms were developed to estimate the chlorophyll content of broadleaves and needleleaves from hyperspectral measurements. Field experiments were conducted from 2003 to 2004 near Sudbury and Haliburton, Ontario, to collect canopy structural, leaf biophysical and biochemical data. Experiments show that optical properties and biochemical contents of broadleaves change with the growing season and canopy height. Needleleaves from different sites, age classes, and branch orientations demonstrate different visible optical properties in relation to their chlorophyll contents. A process-based radiative transfer model PROSPECT was modified to retrieve leaf chlorophyll content from measured leaf spectra. For broadleaves, leaf thickness was introduced to consider the seasonal and canopy-gradient variation in light absorption. The accuracy of chlorophyll retrieval is increased from 67% to 91%. For needleleaves, the effects of needleleaf width and thickness, and geometrical effects of leaf-holding devices on spectra measurements were taken into account. These modifications improve the accuracy of chlorophyll retrieval from 31% to 59%. Correct exposure for digital hemispherical photographs is crucial for estimating canopy structural parameters. A photographic exposure theory was tested for different forest types with various canopy closures and under different sky conditions. The exposure method improves the estimates of leaf area index by 40% in comparison with commonly used automatic exposure.

Instrumentation for Studying Vegetation Canopies for Remote Sensing in Optical and Thermal Infrared Regions

Author : Narendra S. Goel
Publisher : Routledge
ISBN 13 :
Total Pages : 380 pages
Book Rating : 4.:/5 (319 download)

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Book Synopsis Instrumentation for Studying Vegetation Canopies for Remote Sensing in Optical and Thermal Infrared Regions by : Narendra S. Goel

Download or read book Instrumentation for Studying Vegetation Canopies for Remote Sensing in Optical and Thermal Infrared Regions written by Narendra S. Goel and published by Routledge. This book was released on 1990 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: First Published in 1991. Routledge is an imprint of Taylor & Francis, an informa company.

Improving the Estimation of Leaf Area Index from Multispectral Remotely Sensed Data

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (175 download)

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Book Synopsis Improving the Estimation of Leaf Area Index from Multispectral Remotely Sensed Data by :

Download or read book Improving the Estimation of Leaf Area Index from Multispectral Remotely Sensed Data written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Remote Sensing for Field-based Crop Phenotyping

Author : Jiangang Liu
Publisher : Frontiers Media SA
ISBN 13 : 2832544304
Total Pages : 274 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Remote Sensing for Field-based Crop Phenotyping by : Jiangang Liu

Download or read book Remote Sensing for Field-based Crop Phenotyping written by Jiangang Liu and published by Frontiers Media SA. This book was released on 2024-02-12 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic monitoring of crop phenotypic traits (e.g., LAI, plant height, biomass, nitrogen, yield et al.) is essential for exploring crop growth patterns, breeding new varieties, and determining optimized strategies for crop management. Traditional methods for determining crop phenotypic traits are mainly based on field sampling, handheld instrument measurement, and mechanized high-throughput platforms, which are time-consuming, and have low efficiency and incomplete spatial coverage. The development of crop science requires more rapid and accurate access to field-based crop phenotypes. Remote sensing provides a novel solution to quantify crop structural and functional traits in a timely, rapid, non-invasive and efficient manner. With the development of burgeoning remote sensing sensors and diversified algorithms, a range of crop phenotypic traits have been determined, including morphological parameters, spectral and textural characteristics, physiological traits, and responses to abiotic/biotic stresses in different environments. In addition, research advances in varying disciplines beyond agricultural sciences, such as engineering, computer science, molecular biology, and bioinformatics, have brought new opportunities for further development of remote sensing-based methods and technologies to gain more quantitative information on crop structure and function in complex environments

Applications of Remote Sensing and Geographic Information Systems in Vegetation Science

Author : Stephen J. Walsh
Publisher :
ISBN 13 :
Total Pages : 156 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Applications of Remote Sensing and Geographic Information Systems in Vegetation Science by : Stephen J. Walsh

Download or read book Applications of Remote Sensing and Geographic Information Systems in Vegetation Science written by Stephen J. Walsh and published by . This book was released on 1994 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt:

A Multispectral Remote Sensing Investigation of Leaf Area Index at Black Rock Forest, NY

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (171 download)

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Book Synopsis A Multispectral Remote Sensing Investigation of Leaf Area Index at Black Rock Forest, NY by :

Download or read book A Multispectral Remote Sensing Investigation of Leaf Area Index at Black Rock Forest, NY written by and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Using Remote Sensing Data to Estimate Leaf Area Index and Foliar Notrogen of Loblolly Pine Plantations

Author : Francisco Jose Flores
Publisher :
ISBN 13 :
Total Pages : 102 pages
Book Rating : 4.:/5 (527 download)

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Book Synopsis Using Remote Sensing Data to Estimate Leaf Area Index and Foliar Notrogen of Loblolly Pine Plantations by : Francisco Jose Flores

Download or read book Using Remote Sensing Data to Estimate Leaf Area Index and Foliar Notrogen of Loblolly Pine Plantations written by Francisco Jose Flores and published by . This book was released on 2003 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keywords: Landsat7, foliar nitrogen concentration, remote sensing, LAI, loblolly pine, HyMap.

Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing

Author : Ni-Bin Chang
Publisher : CRC Press
ISBN 13 : 1351650637
Total Pages : 627 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing by : Ni-Bin Chang

Download or read book Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing written by Ni-Bin Chang and published by CRC Press. This book was released on 2018-02-21 with total page 627 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years the scientific community has realized that obtaining a better understanding of interactions between natural systems and the man-made environment across different scales demands more research efforts in remote sensing. An integrated Earth system observatory that merges surface-based, air-borne, space-borne, and even underground sensors with comprehensive and predictive capabilities indicates promise for revolutionizing the study of global water, energy, and carbon cycles as well as land use and land cover changes. The aim of this book is to present a suite of relevant concepts, tools, and methods of integrated multisensor data fusion and machine learning technologies to promote environmental sustainability. The process of machine learning for intelligent feature extraction consists of regular, deep, and fast learning algorithms. The niche for integrating data fusion and machine learning for remote sensing rests upon the creation of a new scientific architecture in remote sensing science that is designed to support numerical as well as symbolic feature extraction managed by several cognitively oriented machine learning tasks at finer scales. By grouping a suite of satellites with similar nature in platform design, data merging may come to help for cloudy pixel reconstruction over the space domain or concatenation of time series images over the time domain, or even both simultaneously. Organized in 5 parts, from Fundamental Principles of Remote Sensing; Feature Extraction for Remote Sensing; Image and Data Fusion for Remote Sensing; Integrated Data Merging, Data Reconstruction, Data Fusion, and Machine Learning; to Remote Sensing for Environmental Decision Analysis, the book will be a useful reference for graduate students, academic scholars, and working professionals who are involved in the study of Earth systems and the environment for a sustainable future. The new knowledge in this book can be applied successfully in many areas of environmental science and engineering.