scholarly journals Adopting “Difference-in-Differences” Method to Monitor Crop Response to Agrometeorological Hazards with Satellite Data: A Case Study of Dry-Hot Wind

2021 ◽  
Vol 13 (3) ◽  
pp. 482
Author(s):  
Shuai Wang ◽  
Yuhan Rao ◽  
Jin Chen ◽  
Licong Liu ◽  
Wenqing Wang
Keyword(s):  
Food Security ◽  
Winter Wheat ◽  
Real Time ◽  
Natural Hazards ◽  
Large Scale ◽  
Confounding Factors ◽  
Crop Response ◽  
Difference In Differences ◽  
The Impact

Rapid changing climate has increased the risk of natural hazards and threatened global and regional food security. Near real-time monitoring of crop response to agrometeorological hazards is fundamental to ensuring national and global food security. However, quantifying crop responses to a specific hazard in the natural environment is still quite challenging, especially over large areas, due to the lack of tools to separate the independent impact of the hazard on crops from other confounding factors. In this study, we present a general difference-in-differences (DID) framework to monitor crop response to agrometeorological hazards at near real-time using widely accessible remotely sensed vegetation indices (VIs). To demonstrate the effectiveness of the DID framework, we applied it in quantifying the dry-hot wind impact on winter wheat in northern China as a case study using the VIs calculated from the MODIS data. The monitoring results for three years with varying severity levels of dry-hot events (i.e., 2007, 2013, and 2014) demonstrated that the framework can effectively detect winter wheat growing areas affected by dry-hot wind hazards. The estimated damage shows a notable relationship (R2 = 0.903, p < 0.001) with the dry-hot wind intensity calculated from meteorological data, suggesting the effectiveness of the method when field data on a large scale is not available for direct validation. The main advantage of this method is that it can effectively isolate the impact of a specific hazard (i.e., dry-hot wind in the case study) from the mixed signals caused by other confounding factors. This general DID framework is very flexible and can be easily extended to other natural hazards and crop types with proper adjustment. Not only can this framework improve the crop yield forecast but also it can provide near real-time assessment for farmers to adapt their farming practice to mitigate impacts of agricultural hazards.

scholarly journals Multitemporal Mapping of Post-Fire Land Cover Using Multiplatform PRISMA Hyperspectral and Sentinel-UAV Multispectral Data: Insights from Case Studies in Portugal and Italy

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3982
Author(s):  
Giacomo Lazzeri ◽  
William Frodella ◽  
Guglielmo Rossi ◽  
Sandro Moretti
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Fire Severity ◽  
Experimental Methodology ◽  
Vegetation Recovery ◽  
Burned Area ◽  
Remotely Sensed Data ◽  
The Impact ◽  
Sentinel 2

Wildfires have affected global forests and the Mediterranean area with increasing recurrency and intensity in the last years, with climate change resulting in reduced precipitations and higher temperatures. To assess the impact of wildfires on the environment, burned area mapping has become progressively more relevant. Initially carried out via field sketches, the advent of satellite remote sensing opened new possibilities, reducing the cost uncertainty and safety of the previous techniques. In the present study an experimental methodology was adopted to test the potential of advanced remote sensing techniques such as multispectral Sentinel-2, PRISMA hyperspectral satellite, and UAV (unmanned aerial vehicle) remotely-sensed data for the multitemporal mapping of burned areas by soil–vegetation recovery analysis in two test sites in Portugal and Italy. In case study one, innovative multiplatform data classification was performed with the correlation between Sentinel-2 RBR (relativized burn ratio) fire severity classes and the scene hyperspectral signature, performed with a pixel-by-pixel comparison leading to a converging classification. In the adopted methodology, RBR burned area analysis and vegetation recovery was tested for accordance with biophysical vegetation parameters (LAI, fCover, and fAPAR). In case study two, a UAV-sensed NDVI index was adopted for high-resolution mapping data collection. At a large scale, the Sentinel-2 RBR index proved to be efficient for burned area analysis, from both fire severity and vegetation recovery phenomena perspectives. Despite the elapsed time between the event and the acquisition, PRISMA hyperspectral converging classification based on Sentinel-2 was able to detect and discriminate different spectral signatures corresponding to different fire severity classes. At a slope scale, the UAV platform proved to be an effective tool for mapping and characterizing the burned area, giving clear advantage with respect to filed GPS mapping. Results highlighted that UAV platforms, if equipped with a hyperspectral sensor and used in a synergistic approach with PRISMA, would create a useful tool for satellite acquired data scene classification, allowing for the acquisition of a ground truth.

The impact of large-scale reclamation on hydro-dynamic environment–A case study of Xinghua Bay

2015 ◽  
Vol 15 (4) ◽  
pp. 583-592 ◽  
Author(s):  
Jing Yu ◽  
Xianwen Bao ◽  
Yang Ding ◽  
Wei Zhang ◽  
Lingling Zhou
Keyword(s):  
Large Scale ◽  
Dynamic Environment ◽  
The Impact

Overcoming the Challenges of Experimental Research: Lessons From a Criminal Justice Case Study Involving TASER Exposure

2018 ◽  
Vol 42 (3) ◽  
pp. 358-385 ◽  
Author(s):  
Natalie Todak ◽  
Michael D. White ◽  
Lisa M. Dario ◽  
Andrea R. Borrego
Keyword(s):  
Criminal Justice ◽  
Large Scale ◽  
Human Subjects ◽  
Controlled Trial ◽  
Human Subjects Research ◽  
Case Study Approach ◽  
Study Approach ◽  
Randomized Controlled ◽  
The Impact

Objective: To provide guidance to criminologists for conducting experiments in light of two common discouraging factors: the belief that they are overly time-consuming and the belief that they can compromise the ethical principles of human subjects’ research. Method: A case study approach is used, based on a large-scale randomized controlled trial experiment in which we exposed participants to a 5-s TASER shock, to describe how the authors overcame ethical, methodological, and logistical difficulties. Results: We derive four pieces of advice from our experiences carrying out this experimental trial: (1) know your limitations, (2) employ pilot testing, (3) remain flexible and patient, and (4) “hold the line” to maintain the integrity of the research and the safety of human subjects. Conclusions: Criminologists have an obligation to provide the best possible evidence regarding the impact and consequences of criminal justice practices and programs. Experiments, considered by many to be the gold standard of empirical research methodologies, should be used whenever possible in order to fulfill this obligation.

Toward a Model of Brand Creation for International Large-Scale Sporting Events: The Impact of Leadership, Context, and Nature of the Event

2008 ◽  
Vol 22 (5) ◽  
pp. 526-549 ◽  
Author(s):  
Milena M. Parent ◽  
Benoit Séguin
Keyword(s):  
Large Scale ◽  
Sporting Events ◽  
Related Factors ◽  
Initial Event ◽  
Leadership Group ◽  
Leadership Context ◽  
The Impact ◽  
Communication Paths ◽  
Brand Creation

The purpose of this study was to develop a model of brand creation for one-off large-scale sporting events. A case study of the 2005 Montreal FINA (Fédération Internationale de Natation) World Championships highlighted the importance of the leadership group (which must include individuals with political/networking, business/management, and sport/event skills), the context, and the nature of the event for creating the event’s brand. The importance of each aspect is suggested to vary depending on the situation. For example, the lack of an initial event brand will result in the leadership group having the greatest impact on the event’s brand creation process. Findings also highlighted differing communication paths for internal and external stakeholders. Thus, this study contributes to the literature by focusing on brand creation and its related factors instead of the management and outcomes of a brand.

scholarly journals Automatic delineation of debris-covered glaciers using InSAR coherence derived from X-, C- and L-band radar data: a case study of Yazgyl Glacier

2018 ◽  
Vol 64 (247) ◽  
pp. 811-821 ◽  
Author(s):  
STEFAN LIPPL ◽  
SAURABH VIJAY ◽  
MATTHIAS BRAUN
Keyword(s):  
Large Scale ◽  
Window Size ◽  
Radar Data ◽  
Morphological Operations ◽  
L Band ◽  
Surrounding Areas ◽  
Coherence Estimation ◽  
The Impact

ABSTRACTDespite their importance for mass-balance estimates and the progress in techniques based on optical and thermal satellite imagery, the mapping of debris-covered glacier boundaries remains a challenging task. Manual corrections hamper regular updates. In this study, we present an automatic approach to delineate glacier outlines using interferometrically derived synthetic aperture radar (InSAR) coherence, slope and morphological operations. InSAR coherence detects the temporally decorrelated surface (e.g. glacial extent) irrespective of its surface type and separates it from the highly coherent surrounding areas. We tested the impact of different processing settings, for example resolution, coherence window size and topographic phase removal, on the quality of the generated outlines. We found minor influence of the topographic phase, but a combination of strong multi-looking during interferogram generation and additional averaging during coherence estimation strongly deteriorated the coherence at the glacier edges. We analysed the performance of X-, C- and L- band radar data. The C-band Sentinel-1 data outlined the glacier boundary with the least misclassifications and a type II error of 0.47% compared with Global Land Ice Measurements from Space inventory data. Our study shows the potential of the Sentinel-1 mission together with our automatic processing chain to provide regular updates for land-terminating glaciers on a large scale.

Numerical Modelling of a District Scale Groundwater Heat Pump Operation: Case Study from Colchester, UK

2021 ◽  
Author(s):  
Taha Sezer ◽  
Abubakar Kawuwa Sani ◽  
Rao Martand Singh ◽  
David P. Boon
Keyword(s):  
Large Scale ◽  
District Level ◽  
Thermal Plume ◽  
Injection Wells ◽  
Term Operation ◽  
Heating And Cooling ◽  
Groundwater Heat Pump ◽  
The Impact

&lt;p&gt;Groundwater heat pumps (GWHP) are an environmentally friendly and highly efficient low carbon heating technology that can benefit from low-temperature groundwater sources lying in the shallow depths to provide heating and cooling to buildings. However, the utilisation of groundwater for heating and cooling, especially in large scale (district level), can create a thermal plume around injection wells. If a plume reaches the production well this may result in a decrease in the system performance or even failure in the long-term operation. This research aims to investigate the impact of GWHP usage in district-level heating by using a numerical approach and considering a GWHP system being constructed in Colchester, UK as a case study, which will be the largest GWHP system in the UK. Transient 3D simulations have been performed pre-construction to investigate the long-term effect of injecting water at 5&amp;#176;C, into a chalk bedrock aquifer. Modelling suggests a thermal plume develops but does not reach the production wells after 10 years of operation. The model result can be attributed to the low hydraulic gradient, assumed lack of interconnecting fractures, and large (&gt;500m) spacing between the production and injection wells. Model validation may be possible after a period operational monitoring.&lt;/p&gt;

Measuring the Impact of the Semantic-Based Process Mining Approach

2020 ◽  
pp. 217-237
Keyword(s):  
Knowledge Base ◽  
Real Time ◽  
Learning Process ◽  
Conceptual Analysis ◽  
Process Mining ◽  
Levels Of Analysis ◽  
Use Case ◽  
Abstraction Levels ◽  
The Impact

This chapter looks at the extent to which the semantic-based process mining approach of this book supports the conceptual analysis of the events logs and resultant models. Qualitatively, the chapter leverages the use case study of the research learning process domain to determine how the proposed method support the discovery, monitoring, and enhancement of the real-time processes through the abstraction levels of analysis. Also, the chapter quantitatively assesses the level of accuracy of the classification process to predict behaviours of unobserved instances within the underlying knowledge base. Overall, the work looks at the implications of the semantic-based approach, validation of the classification results, and their influence compared to other existing benchmark techniques/algorithms used for process mining.

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