Author: Shital Dhakal Publisher: ISBN: Category : Artificial satellites in remote sensing Languages : en Pages : 136
Book Description
"Remote sensing based quantification of semiarid rangeland vegetation provides the large scale observations required for monitoring native plant distribution, estimating fuel loads, modeling climate and hydrological dynamics, and measuring carbon storage. Fine scale 3-dimensional vertical structural information from airborne lidar and improved signal to noise ratio and radiometric resolution of recent satellite imagery provide opportunities for refined measurements of vegetation structure. In this study, we leverage a large number of time series Landsat 8 vegetation indices and lidar point cloud - based vegetation metrics with ground validation for scaling aboveground shrub and herb biomass and cover from small scale plot to large, regional scales in the Morley Nelson Snake River Birds of Prey National Conservation Area (NCA), Idaho. The Landsat vegetation indices were trained and linked to in-situ measurements (n = 141) with the random forest regression to impute vegetation biomass and cover across the NCA. We also validated our model with an independent dataset (n = 44), explaining up to 63% and 53% of variation in shrub cover and biomass, respectively. Forty six of the in-situ plots were used in a model to compare the performance of lidar and Landsat data in estimating vegetation characteristics. Our results demonstrate that Landsat performs better in estimating both herb (R2 ~ 0.60) and shrub cover (R2 ~ 0.75) whereas lidar performs better in estimating shrub and total biomass (R2 ~ 0.75 and 0.68, respectively). Using the lidar only model, we demonstrate that lidar metrics based on shrub height have a strong correlation with field-measured shrub biomass (R2 ~ 0.76). We also compare processing the lidar data with raster-based and point cloud-based approaches. The results are scale-dependent, with improved results of biomass estimation at coarser scales with point cloud processing. Overall, the results of this study indicate that Landsat and lidar can be efficiently utilized independently and together to estimate biomass and cover of vegetation in this semi-arid rangeland environment."--Boise State University ScholarWorks.
Author: Lalit Kumar Publisher: MDPI ISBN: 3039212095 Category : Science Languages : en Pages : 264
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: Gary Lee Publisher: Springer Science & Business Media ISBN: 3642279570 Category : Technology & Engineering Languages : en Pages : 377
Book Description
2012 International Conference on Environment Science and 2012 International Conference on Computer Science (ICES 2012/ICCS 2012) will be held in Australia, Melbourne, 15‐16 March, 2012.Volume 1 contains some new results in computational environment science. There are 47 papers were selected as the regular paper in this volume. It contains the latest developments and reflects the experience of many researchers working in different environments (universities, research centers or even industries), publishing new theories and solving new technological problems on computational environment science. The purpose of volume 1 is interconnection of diverse scientific fields, the cultivation of every possible scientific collaboration, the exchange of views and the promotion of new research targets as well as the further dissemination, the dispersion, the diffusion of the environment science, including but not limited to Ecology, Physics, Chemistry, Biology, Soil Science, Geology, Atmospheric Science and Geography We are sure that the efforts of the authors as well as the reviewers to provide high level contributions will be appreciated by the relevant scientific community. We are convinced that presented volume will be a source of knowledge and inspiration for all academic members, researchers and practitioners working in a field of the topic covered by the book.
Author: Guangxing Wang Publisher: CRC Press ISBN: 1466556935 Category : Nature Languages : en Pages : 565
Book Description
Highlighting new technologies, Remote Sensing of Natural Resources explores advanced remote sensing systems and algorithms for image processing, enhancement, feature extraction, data fusion, image classification, image-based modeling, image-based sampling design, map accuracy assessment and quality control. It also discusses their applications for
Author: Hisham El-Amir Publisher: Apress ISBN: 1484253493 Category : Computers Languages : en Pages : 563
Book Description
Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets. You'll also develop a deep learning project by preparing data, choosing the model that fits that data, and debugging your model to get the best fit to data all using Tensorflow techniques. Enhance your skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution or entering a Kaggle contest, Deep Learning Pipeline is for you! What You'll LearnDevelop a deep learning project using dataStudy and apply various models to your dataDebug and troubleshoot the proper model suited for your data Who This Book Is For Developers, analysts, and data scientists looking to add to or enhance their existing skills by accessing some of the most powerful recent trends in data science. Prior experience in Python or other TensorFlow related languages and mathematics would be helpful.
Author: Laura Innice Duncanson Publisher: ISBN: Category : Languages : en Pages :
Book Description
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.
Author: Caryl L. Elzinga Publisher: DIANE Publishing ISBN: 9780788148378 Category : Languages : en Pages : 190
Book Description
This annotated bibliography documents literature addressing the design and implementation of vegetation monitoring. It provides resources managers, ecologists, and scientists access to the great volume of literature addressing many aspects of vegetation monitoring: planning and objective setting, choosing vegetation attributes to measure, sampling design, sampling methods, statistical and graphical analysis, and communication of results. Over half of the 1400 references have been annotated. Keywords pertaining to the type of monitoring or method are included with each bibliographic entry. Keyword index.
Author: Paulo Pereira Publisher: CSIRO PUBLISHING ISBN: 1486308155 Category : Science Languages : en Pages : 400
Book Description
Wildland fires are occurring more frequently and affecting more of Earth's surface than ever before. These fires affect the properties of soils and the processes by which they form, but the nature of these impacts has not been well understood. Given that healthy soil is necessary to sustain biodiversity, ecosystems and agriculture, the impact of fire on soil is a vital field of research. Fire Effects on Soil Properties brings together current research on the effects of fire on the physical, biological and chemical properties of soil. Written by over 60 international experts in the field, it includes examples from fire-prone areas across the world, dealing with ash, meso and macrofauna, smouldering fires, recurrent fires and management of fire-affected soils. It also describes current best practice methodologies for research and monitoring of fire effects and new methodologies for future research. This is the first time information on this topic has been presented in a single volume and the book will be an important reference for students, practitioners, managers and academics interested in the effects of fire on ecosystems, including soil scientists, geologists, forestry researchers and environmentalists.
Author: Lalit Kumar Publisher: MDPI ISBN: 3038978841 Category : Science Languages : en Pages : 420
Book Description
In a rapidly changing world, there is an ever-increasing need to monitor the Earth’s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth’s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.
Author: Shital Dhakal
Author: Lalit Kumar
Author: 
Author: Gary Lee
Author: Guangxing Wang
Author: Hisham El-Amir
Author: Laura Innice Duncanson
Author: Caryl L. Elzinga
Author: Paulo Pereira
Author: Lalit Kumar