Water Clarity-trophic Condition Monitoring Using Satellite Remote Sensing Data PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Water Clarity-trophic Condition Monitoring Using Satellite Remote Sensing Data PDF full book. Access full book title Water Clarity-trophic Condition Monitoring Using Satellite Remote Sensing Data by Narumon Wiangwang. Download full books in PDF and EPUB format.
Author: Narumon Wiangwang
Publisher:
ISBN:
Category : Water quality
Languages : en
Pages : 340
Get Book Here
Book Description
Author: Narumon Wiangwang
Publisher:
ISBN:
Category : Water quality
Languages : en
Pages : 340
Get Book Here
Book Description
Author: Steven Michael Kloiber
Publisher:
ISBN:
Category :
Languages : en
Pages : 344
Get Book Here
Book Description
Author: Deepak R. Mishra
Publisher: Elsevier
ISBN: 0128046546
Category : Science
Languages : en
Pages : 334
Get Book Here
Book Description
Bio-optical Modeling and Remote Sensing of Inland Waters presents the latest developments, state-of-the-art, and future perspectives of bio-optical modeling for each optically active component of inland waters, providing a broad range of applications of water quality monitoring using remote sensing. Rather than discussing optical radiometry theories, the authors explore the applications of these theories to inland aquatic environments. The book not only covers applications, but also discusses new possibilities, making the bio-optical theories operational, a concept that is of great interest to both government and private sector organizations. In addition, it addresses not only the physical theory that makes bio-optical modeling possible, but also the implementation and applications of bio-optical modeling in inland waters. Early chapters introduce the concepts of bio-optical modeling and the classification of bio-optical models and satellite capabilities both in existence and in development. Later chapters target specific optically active components (OACs) for inland waters and present the current status and future direction of bio-optical modeling for the OACs. Concluding sections provide an overview of a governance strategy for global monitoring of inland waters based on earth observation and bio-optical modeling. - Presents comprehensive chapters that each target a different optically active component of inland waters - Contains contributions from respected and active professionals in the field - Presents applications of bio-optical modeling theories that are applicable to researchers, professionals, and government agencies
Author: Lori M. Fuller
Publisher: DIANE Publishing
ISBN:
Category : Government publications
Languages : en
Pages : 36
Get Book Here
Book Description
Author: David Phillip Mau
Publisher:
ISBN:
Category : Drinking water
Languages : en
Pages : 432
Get Book Here
Book Description
Author: Prasad S. Thenkabail
Publisher: CRC Press
ISBN: 1351659111
Category : Technology & Engineering
Languages : en
Pages : 1637
Get Book Here
Book Description
Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume I, Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation introduces the fundamentals of hyperspectral or imaging spectroscopy data, including hyperspectral data processes, sensor systems, spectral libraries, and data mining and analysis, covering both the strengths and limitations of these topics. Volume II, Hyperspectral Indices and Image Classifications for Agriculture and Vegetation evaluates the performance of hyperspectral narrowband or imaging spectroscopy data with specific emphasis on the uses and applications of hyperspectral narrowband vegetation indices in characterizing, modeling, mapping, and monitoring agricultural crops and vegetation. Volume III, Biophysical and Biochemical Characterization and Plant Species Studies demonstrates the methods that are developed and used to study terrestrial vegetation using hyperspectral data. This volume includes extensive discussions on hyperspectral data processing and how to implement data processing mechanisms for specific biophysical and biochemical applications such as crop yield modeling, crop biophysical and biochemical property characterization, and crop moisture assessments. Volume IV, Advanced Applications in Remote Sensing of Agricultural Crops and Natural Vegetation discusses the use of hyperspectral or imaging spectroscopy data in numerous specific and advanced applications, such as forest management, precision farming, managing invasive species, and local to global land cover change detection.
Author: Prasad S. Thenkabail
Publisher: CRC Press
ISBN: 1351673289
Category : Technology & Engineering
Languages : en
Pages : 578
Get Book Here
Book Description
Written by leading global experts, including pioneers in the field, the four-volume set on Hyperspectral Remote Sensing of Vegetation, Second Edition, reviews existing state-of-the-art knowledge, highlights advances made in different areas, and provides guidance for the appropriate use of hyperspectral data in the study and management of agricultural crops and natural vegetation. Volume I, Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for Vegetation introduces the fundamentals of hyperspectral or imaging spectroscopy data, including hyperspectral data processes, sensor systems, spectral libraries, and data mining and analysis, covering both the strengths and limitations of these topics. This book also presents and discusses hyperspectral narrowband data acquired in numerous unique spectral bands in the entire length of the spectrum from various ground-based, airborne, and spaceborne platforms. The concluding chapter provides readers with useful guidance on the highlights and essence of Volume I through the editors’ perspective. Key Features of Volume I: Provides the fundamentals of hyperspectral remote sensing used in agricultural crops and vegetation studies. Discusses the latest advances in hyperspectral remote sensing of ecosystems and croplands. Develops online hyperspectral libraries, proximal sensing and phenotyping for understanding, modeling, mapping, and monitoring crop and vegetation traits. Implements reflectance spectroscopy of soils and vegetation. Enumerates hyperspectral data mining and data processing methods, approaches, and machine learning algorithms. Explores methods and approaches for data mining and overcoming data redundancy; Highlights the advanced methods for hyperspectral data processing steps by developing or implementing appropriate algorithms and coding the same for processing on a cloud computing platform like the Google Earth Engine. Integrates hyperspectral with other data, such as the LiDAR data, in the study of vegetation. Includes best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, crop productivity and water productivity mapping, and modeling.
Author: Prasad S. Thenkabail
Publisher: CRC Press
ISBN: 1439845387
Category : Science
Languages : en
Pages : 766
Get Book Here
Book Description
Hyperspectral narrow-band (or imaging spectroscopy) spectral data are fast emerging as practical solutions in modeling and mapping vegetation. Recent research has demonstrated the advances in and merit of hyperspectral data in a range of applications including quantifying agricultural crops, modeling forest canopy biochemical properties, detecting crop stress and disease, mapping leaf chlorophyll content as it influences crop production, identifying plants affected by contaminants such as arsenic, demonstrating sensitivity to plant nitrogen content, classifying vegetation species and type, characterizing wetlands, and mapping invasive species. The need for significant improvements in quantifying, modeling, and mapping plant chemical, physical, and water properties is more critical than ever before to reduce uncertainties in our understanding of the Earth and to better sustain it. There is also a need for a synthesis of the vast knowledge spread throughout the literature from more than 40 years of research. Hyperspectral Remote Sensing of Vegetation integrates this knowledge, guiding readers to harness the capabilities of the most recent advances in applying hyperspectral remote sensing technology to the study of terrestrial vegetation. Taking a practical approach to a complex subject, the book demonstrates the experience, utility, methods and models used in studying vegetation using hyperspectral data. Written by leading experts, including pioneers in the field, each chapter presents specific applications, reviews existing state-of-the-art knowledge, highlights the advances made, and provides guidance for the appropriate use of hyperspectral data in the study of vegetation as well as its numerous applications, such as crop yield modeling, crop and vegetation biophysical and biochemical property characterization, and crop moisture assessment. This comprehensive book brings together the best global expertise on hyperspectral remote sensing of agriculture, crop water use, plant species detection, vegetation classification, biophysical and biochemical modeling, crop productivity and water productivity mapping, and modeling. It provides the pertinent facts, synthesizing findings so that readers can get the correct picture on issues such as the best wavebands for their practical applications, methods of analysis using whole spectra, hyperspectral vegetation indices targeted to study specific biophysical and biochemical quantities, and methods for detecting parameters such as crop moisture variability, chlorophyll content, and stress levels. A collective "knowledge bank," it guides professionals to adopt the best practices for their own work.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 7
Get Book Here
Book Description
Water clarity controls the loss of sunlight reaching the underwater habitats. Because many organisms living in estuarine and coastal waters rely on photosynthesis, water clarity needs to be incorporated into protective water quality standards for these valued ecosystems. To develop the protective standards, a better understanding of causes and effects of water clarity variability at local and regional scales is needed. To that end, NASA remote sensing data are being used to monitor water clarity (measured by light attenuation) and the constituents that decrease water clarity (chlorophyll a, total suspended solids, and colored dissolved organic matter) in the estuarine and coastal systems of the northern Gulf of Mexico. The NASA measurements are intended to augment and extend temporal and spatial coverage of water clarity monitoring conducted by the Federal and State environmental agencies in the same areas. The main objective is to develop a methodology for and to demonstrate the feasibility of producing long-term (1984 to present) time series of the water clarity parameters based on combined satellite measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments deployed on the Aqua and Terra spacecraft and from the Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) instruments from the Landsat 4/5 and Landsat 7 spacecraft, respectively. Aqua and Terra MODIS provide daily coverage dating from 2000, while Landsat TM/ETM+ data extend back to 1984, although with frequency of only once per 8 to 16 days. NASA Earth science research results that improved instrument calibration and data processing techniques have enabled merging the time series of observations from Landsat and MODIS. Algorithms for the retrieval of water clarity parameters from satellite data selected for this project are based on the inherent optical properties of water.
Author: Sachini Madhusha Ranasinghe
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
The Neuse River Estuary is a shallow open estuary located at the southern margin of the Albemarle-Pamlico Sound complex in North Carolina. Nutrient oversaturation due to the delivery of excessive nutrient-rich alluvial flux, weak tidal activity, and long water residence times have led to eutrophication and the growth of seasonal algal blooms. The problem has become more severe over the past few decades leading to many environmental and social health concerns. These outcomes emphasize the need for regular monitoring of phytoplankton, growth rate, water quality change, and control strategies. Satellite remote sensing studies provide a great solution for continuous water quality monitoring as a relatively cost-effective tool with high spatial and weekly to daily cloud-free temporal resolution. This research applies the Kent State University (KSU) Varimax-rotated Principal Component Analysis (VPCA) developed by Ortiz et al. (2013) to study the seasonal succession of phytoplankton and water quality parameters in the Neuse River Estuary by using Sentinel - 2 A/B Multi-Spectral Instrument (MSI) images from 2019 to 2021. The spectral signals in the water column were decomposed into six components using coherent, linearly correlated information in the visible and near-infrared spectral ranges. The components are then identified by comparing their spectral shape against standard spectral libraries. The study collaborated with the Neuse River Estuary Modeling and Monitoring program for the field-based water quality and cell count data, which was used in conjunction with remote sensing observations. We evaluated the applicability of the KSU VPCA method through a three-day average model. It identified two phytoplankton assemblages (Diatoms/Dinoflagellates/Chlorophytes and Cryptophytes) and two minerals (Goethite and Muscovite) that are successfully matched with the field observations. Secondly, we separated three phytoplankton-related (Dinoflagellates, Diatoms, and Chlorophyllide-b) and three mineral-based (Gypsum, Hematite, Chlorite) components by averaging multiple images over three years from 2019 to 2021 showing the fall to spring succession of phytoplankton in the Neuse Estuary. Results showed a dominant dinoflagellate population in the upper estuary, while diatoms dominated the lower estuary. Overall, phytoplankton density was low in winter but increased with the spring rainfall in response to nutrient flux delivered with alluvial input. The seasonal succession of the phytoplankton population was mainly controlled by the primary Neuse River channel input, while isolated small-scale blooms were influenced by nutrient input from tributaries. In conclusion, the KSU VPCA method was successful in identifying major phytoplankton groups, suspended minerals, and algal blooms with high spatial sensitivity. The temporal resolution of Sentinel- 2 derived products was significantly affected in summer due to intense cloud cover and the sun glint. The three-year averaging model showed a higher sensitivity to component identification than the three-day average model with greater statistical significance. We identified six critical factors that determine the output quality of remote sensing and KSU VPCA derived component identification in this optically complex coastal water body: cloud cover, sun glint, radiometric resolution, spatial resolution, the temporal resolution of the satellite sensor and the radiometric resolution of standard spectral libraries. With the hyperspectral sensors and detailed spectral standards, the KSU VPCA method can develop further as a powerful tool in aquatic remote sensing.
