Remote sensing of animals

2001 ◽  
Vol 25 (3) ◽  
pp. 355-362 ◽  
Author(s):  
Thomas W. Gillespie
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
First Century ◽  
Future Research ◽  
Species Dispersal ◽  
Biogeographic Patterns ◽  
Environmental Correlates ◽  
Accuracy And Precision ◽  
Gis Data ◽  
Improved Accuracy

The improved accuracy and precision of animal tracking via satellites has made a significant impact on quantifying large-scale biogeographic patterns for a variety of taxa with important implications for conservation and natural resource management. This paper reviews research undertaken from 1995 to 1999 to provide an overview of advances in the remote sensing of animal movements in both terrestrial and marine environments and to identify promising trends for biogeographic research in the twenty-first century. Remote sensing of animals by satellite provides a new method to test a number of biogeographic hypotheses related to migration and can identify a number of environmental correlates associated with the distributions of species. Tracking of smaller species and increases in sample size are sure to occur as transmitter size and cost continue to decrease in the next decade. Geographers can significantly contribute to the understanding of species dispersal and distributional patterns by combining real-time and archived global and regional datasets with existing data from past studies and future research projects. Only four studies used GIS data or remote sensed imagery in this review, while the remaining studies cited used simple digital line graphs of countries, topography, land and sea boundaries.

scholarly journals Linking Information Sharing And Supplier Network Responsiveness With Delivery Dependability Of A Firm

2011 ◽  
Vol 25 (3) ◽  
Author(s):  
Ashish A. Thatte ◽  
Vikas Agrawal ◽  
Shahnawaz Muhammed
Keyword(s):  
Information Sharing ◽  
Structural Equation ◽  
Large Scale ◽  
Positive Impact ◽  
First Century ◽  
Equation Modeling ◽  
Future Research ◽  
Web Based ◽  
Delivery Performance ◽  
Research Findings

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">The twenty first century organization is required to provide accurate on time deliveries in addition to providing high quality products at low costs. This can be achieved if various processes within and between the organizations are streamlined and well defined. Several studies have indicated the significance of various manufacturing (or internal) practices that are instrumental in creating time-based competitive capability. Collaborative relations and information sharing practices with suppliers have long been believed to positively impact the responsiveness and delivery performance of organizations and supply chains. Responsive suppliers can play a key role in affecting a firm&rsquo;s own delivery performance. <span style="mso-spacerun: yes;">&nbsp;</span>This research investigates and tests the relationships between information sharing practices of a firm, supplier network responsiveness, and delivery dependability of a firm. The large scale web-based survey yielded 294 responses from industry professionals in the manufacturing and supply chain area. The proposed relationships were tested using structural equation modeling. The research findings point out that higher level of information sharing practices can lead to improved supplier network responsiveness, and higher levels of supplier network responsiveness can have a direct positive impact on delivery dependability of a firm. The implications of our findings are discussed and directions for future research are provided.</span></span></p>

A Theory of Global Biodiversity (MPB-60)

2018 ◽  
Author(s):  
Boris Worm ◽  
Derek P. Tittensor
Keyword(s):  
Large Scale ◽  
Deep Ocean ◽  
Global Scale ◽  
Community Size ◽  
Biogeographic Patterns ◽  
Environmental Correlates ◽  
Species Groups ◽  
Global Patterns ◽  
Underlying Processes ◽  
Evolutionary Perspectives

The number of species found at a given point on the planet varies by orders of magnitude, yet large-scale gradients in biodiversity appear to follow some very general patterns. Little mechanistic theory has been formulated to explain the emergence of observed gradients of biodiversity both on land and in the oceans. Based on a comprehensive empirical synthesis of global patterns of species diversity and their drivers, this book develops and applies a new theory that can predict such patterns from few underlying processes. The book shows that global patterns of biodiversity fall into four consistent categories, according to where species live: on land or in coastal, pelagic, and deep ocean habitats. The fact that most species groups, from bacteria to whales, appear to follow similar biogeographic patterns of richness within these habitats points toward some underlying structuring principles. Based on empirical analyses of environmental correlates across these habitats, the book combines aspects of neutral, metabolic, and niche theory into one unifying framework. Applying it to model terrestrial and marine realms, the book demonstrates that a relatively simple theory that incorporates temperature and community size as driving variables is able to explain divergent patterns of species richness at a global scale. Integrating ecological and evolutionary perspectives, the book yields surprising insights into the fundamental mechanisms that shape the distribution of life on our planet.

scholarly journals A Review on Early Forest Fire Detection Systems Using Optical Remote Sensing

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6442 ◽  
Author(s):  
Panagiotis Barmpoutis ◽  
Periklis Papaioannou ◽  
Kosmas Dimitropoulos ◽  
Nikos Grammalidis
Keyword(s):  
Remote Sensing ◽  
Early Warning ◽  
Forest Fires ◽  
Large Scale ◽  
Fire Detection ◽  
Future Research ◽  
Optical Remote Sensing ◽  
Effective Prevention ◽  
Detection Systems ◽  
The World

The environmental challenges the world faces nowadays have never been greater or more complex. Global areas covered by forests and urban woodlands are threatened by natural disasters that have increased dramatically during the last decades, in terms of both frequency and magnitude. Large-scale forest fires are one of the most harmful natural hazards affecting climate change and life around the world. Thus, to minimize their impacts on people and nature, the adoption of well-planned and closely coordinated effective prevention, early warning, and response approaches are necessary. This paper presents an overview of the optical remote sensing technologies used in early fire warning systems and provides an extensive survey on both flame and smoke detection algorithms employed by each technology. Three types of systems are identified, namely terrestrial, airborne, and spaceborne-based systems, while various models aiming to detect fire occurrences with high accuracy in challenging environments are studied. Finally, the strengths and weaknesses of fire detection systems based on optical remote sensing are discussed aiming to contribute to future research projects for the development of early warning fire systems.

scholarly journals Designing a Validation Protocol for Remote Sensing Based Operational Forest Masks Applications. Comparison of Products Across Europe

2020 ◽  
Vol 12 (19) ◽  
pp. 3159
Author(s):  
Angel Fernandez-Carrillo ◽  
Antonio Franco-Nieto ◽  
Erika Pinto-Bañuls ◽  
Miguel Basarte-Mena ◽  
Beatriz Revilla-Romero
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Forest Cover ◽  
Performance Metrics ◽  
Temporal Dynamics ◽  
Forest Products ◽  
Future Research ◽  
Forest Types ◽  
Visual Interpretation ◽  
Sampling System

The spatial and temporal dynamics of the forest cover can be captured using remote sensing data. Forest masks are a valuable tool to monitor forest characteristics, such as biomass, deforestation, health condition and disturbances. This study was carried out under the umbrella of the EC H2020 MySustainableForest (MSF) project. A key achievement has been the development of supervised classification methods for delineating forest cover. The forest masks presented here are binary forest/non-forest classification maps obtained using Sentinel-2 data for 16 study areas across Europe with different forest types. Performance metrics can be selected to measure accuracy of forest mask. However, large-scale reference datasets are scarce and typically cannot be considered as ground truth. In this study, we implemented a stratified random sampling system and the generation of a reference dataset based on visual interpretation of satellite images. This dataset was used for validation of the forest masks, MSF and two other similar products: HRL by Copernicus and FNF by the DLR. MSF forest masks showed a good performance (OAMSF = 96.3%; DCMSF = 96.5), with high overall accuracy (88.7–99.5%) across all the areas, and omission and commission errors were low and balanced (OEMSF = 2.4%; CEMSF = 4.5%; relBMSF = 2%), while the other products showed on average lower accuracies (OAHRL = 89.2%; OAFNF = 76%). However, for all three products, the Mediterranean areas were challenging to model, where the complexity of forest structure led to relatively high omission errors (OEMSF = 9.5%; OEHRL = 59.5%; OEFNF = 71.4%). Comparing these results with the vision from external local stakeholders highlighted the need of establishing clear large-scale validation datasets and protocols for remote sensing-based forest products. Future research will be done to test the MSF mask in forest types not present in Europe and compare new outputs to available reference datasets.

scholarly journals Spatial Assessment of Community Resilience from 2012 Hurricane Sandy Using Nighttime Light

2021 ◽  
Vol 13 (20) ◽  
pp. 4128
Author(s):  
Jinwen Xu ◽  
Yi Qiang
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Low Cost ◽  
Community Resilience ◽  
Hurricane Sandy ◽  
Future Research ◽  
Remote Sensing Images ◽  
Community Recovery ◽  
Human Dynamics ◽  
Explanatory Variables

Quantitative assessment of community resilience is a challenge due to the lack of empirical data about human dynamics in disasters. To fill the data gap, this study explores the utility of nighttime lights (NTL) remote sensing images in assessing community recovery and resilience in natural disasters. Specifically, this study utilized the newly-released NASA moonlight-adjusted SNPP-VIIRS daily images to analyze spatiotemporal changes of NTL radiance in Hurricane Sandy (2012). Based on the conceptual framework of recovery trajectory, NTL disturbance and recovery during the hurricane were calculated at different spatial units and analyzed using spatial analysis tools. Regression analysis was applied to explore relations between the observed NTL changes and explanatory variables, such as wind speed, housing damage, land cover, and Twitter keywords. The result indicates potential factors of NTL changes and urban-rural disparities of disaster impacts and recovery. This study shows that NTL remote sensing images are a low-cost instrument to collect near-real-time, large-scale, and high-resolution human dynamics data in disasters, which provide a novel insight into community recovery and resilience. The uncovered spatial disparities of community recovery help improve disaster awareness and preparation of local communities and promote resilience against future disasters. The systematical documentation of the analysis workflow provides a reference for future research in the application of SNPP-VIIRS daily images.

Change of Attitude, Technology and Practice: Identifying the Change for Increased Value Creation with Customer Co-creation

2017 ◽  
Vol 5 (1) ◽  
pp. 70-82
Author(s):  
Soumi Paul ◽  
Paola Peretti ◽  
Saroj Kumar Datta
Keyword(s):  
Social Media ◽  
New Product Development ◽  
Value Creation ◽  
Large Scale ◽  
Customer Orientation ◽  
Customer Relationships ◽  
Future Research ◽  
Management Competencies ◽  
Business Decisions ◽  
Prime Concern

Building customer relationships and customer equity is the prime concern in today’s business decisions. The emergence of internet, especially social media like Facebook and Twitter, changed traditional marketing thought to a great extent. The importance of customer orientation is reflected in the axiom, “The customer is the king”. A good number of organizations are engaging customers in their new product development activities via social media platforms. Co-creation, a new perspective in which customers are active co-creators of the products they buy and use, is currently challenging the traditional paradigm. The concept of co-creation involving the customer’s knowledge, creativity and judgment to generate value is considered not only an upcoming trend that introduces new products or services but also fitting their need and increasing value for money. Knowledge and innovation are inseparable. Knowledge management competencies and capacities are essential to any organization that aspires to be distinguished and innovative. The present work is an attempt to identify the change in value creation procedure along with one area of business, where co-creation can return significant dividends. It is on extending the brand or brand category through brand extension or line extension. This article, through an in depth literature review analysis, identifies the changes in every perspective of this paradigm shift and it presents a conceptual model of company-customer-brand-based co-creation activity via social media. The main objective is offering an agenda for future research of this emerging trend and ensuring the way to move from theory to practice. The paper acts as a proposal; it allows the organization to go for this change in a large scale and obtain early feedback on the idea presented. 

Overview of Subsynchronous Oscillation in Grid-connected Wind Farm

2020 ◽  
Vol 13 (7) ◽  
pp. 969-979
Author(s):  
Xu Pei-Zhen ◽  
Lu Yong-Geng ◽  
Cao Xi-Min
Keyword(s):  
Power Systems ◽  
Wind Turbine ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Induction Generator ◽  
Future Research ◽  
Stable Operation ◽  
Subsynchronous Oscillation ◽  
Different Types

Background: Over the past few years, the subsynchronous oscillation (SSO) caused by the grid-connected wind farm had a bad influence on the stable operation of the system and has now become a bottleneck factor restricting the efficient utilization of wind power. How to mitigate and suppress the phenomenon of SSO of wind farms has become the focus of power system research. Methods: This paper first analyzes the SSO of different types of wind turbines, including squirrelcage induction generator based wind turbine (SCIG-WT), permanent magnet synchronous generator- based wind turbine (PMSG-WT), and doubly-fed induction generator based wind turbine (DFIG-WT). Then, the mechanisms of different types of SSO are proposed with the aim to better understand SSO in large-scale wind integrated power systems, and the main analytical methods suitable for studying the SSO of wind farms are summarized. Results: On the basis of results, using additional damping control suppression methods to solve SSO caused by the flexible power transmission devices and the wind turbine converter is recommended. Conclusion: The current development direction of the SSO of large-scale wind farm grid-connected systems is summarized and the current challenges and recommendations for future research and development are discussed.

MILL: Channel Attention–based Deep Multiple Instance Learning for Landslide Recognition

2021 ◽  
Vol 17 (2s) ◽  
pp. 1-11
Author(s):  
Xiaochuan Tang ◽  
Mingzhe Liu ◽  
Hao Zhong ◽  
Yuanzhen Ju ◽  
Weile Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Large Scale ◽  
Remote Sensing Image ◽  
Disaster Risk ◽  
Multiple Instance Learning ◽  
Remote Sensing Images ◽  
Loess Area ◽  
Remote Sensing Image Classification ◽  
Natural Disaster Risk

Landslide recognition is widely used in natural disaster risk management. Traditional landslide recognition is mainly conducted by geologists, which is accurate but inefficient. This article introduces multiple instance learning (MIL) to perform automatic landslide recognition. An end-to-end deep convolutional neural network is proposed, referred to as Multiple Instance Learning–based Landslide classification (MILL). First, MILL uses a large-scale remote sensing image classification dataset to build pre-train networks for landslide feature extraction. Second, MILL extracts instances and assign instance labels without pixel-level annotations. Third, MILL uses a new channel attention–based MIL pooling function to map instance-level labels to bag-level label. We apply MIL to detect landslides in a loess area. Experimental results demonstrate that MILL is effective in identifying landslides in remote sensing images.

scholarly journals ‘CTRL’: an online, Dynamic Consent and participant engagement platform working towards solving the complexities of consent in genomic research

2021 ◽  
Author(s):  
Matilda A. Haas ◽  
Harriet Teare ◽  
Megan Prictor ◽  
Gabi Ceregra ◽  
Miranda E. Vidgen ◽  
...  
Keyword(s):  
Large Scale ◽  
Genomic Medicine ◽  
International Standards ◽  
Security And Privacy ◽  
Genomic Research ◽  
Return Of Results ◽  
Future Research ◽  
Design And Development ◽  
Participant Engagement ◽  
Dynamic Consent

AbstractThe complexities of the informed consent process for participating in research in genomic medicine are well-documented. Inspired by the potential for Dynamic Consent to increase participant choice and autonomy in decision-making, as well as the opportunities for ongoing participant engagement it affords, we wanted to trial Dynamic Consent and to do so developed our own web-based application (web app) called CTRL (control). This paper documents the design and development of CTRL, for use in the Australian Genomics study: a health services research project building evidence to inform the integration of genomic medicine into mainstream healthcare. Australian Genomics brought together a multi-disciplinary team to develop CTRL. The design and development process considered user experience; security and privacy; the application of international standards in data sharing; IT, operational and ethical issues. The CTRL tool is now being offered to participants in the study, who can use CTRL to keep personal and contact details up to date; make consent choices (including indicate preferences for return of results and future research use of biological samples, genomic and health data); follow their progress through the study; complete surveys, contact the researchers and access study news and information. While there are remaining challenges to implementing Dynamic Consent in genomic research, this study demonstrates the feasibility of building such a tool, and its ongoing use will provide evidence about the value of Dynamic Consent in large-scale genomic research programs.

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