Outdoor infrared imaging for spatial and temporal thermography: A case study of necrotic versus healthy leaf areas on woody plants

The aim of the article is to describe the issue of determining the characteristics and parameters of raw timber natural losses due to shrinkage at long-term storage, defining the theoretical basis for creating standards, and verify its finding by means of a case study in raw timber storing. This issue is very topical in forestry practice in the Czech Republic as well as in other countries. The lower and upper limits of the standards were calculated, and the proposed mean value was grouped according to woody plants that reflected the most frequent commercial usage with respect to subsequent processing. Subsequently, experimental verification was carried out on a representative sample of 2 209.99 m3 of raw timber of Norway spruce (Picea abies /L./ H. Karst.) at selected forest administrations. Furthermore, the article addresses the related accounting and tax issues of the standards of natural losses of raw timber. Currently, no legislation mandates an entity to establish standards.

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Use of multi-spectral visible and near-infrared satellite data for timely estimates of the Earth's surface reflectance in cloudy conditions: Part 2 - image restoration with HICO satellite data in overcast conditions

10.31223/x5ww4z ◽

2021 ◽

Author(s):

Joanna Joiner ◽

Zachary Fasnacht ◽

Bo-Cai Gao ◽

Wenhan Qin

Keyword(s):

Spatial Resolution ◽

Satellite Data ◽

Precision Agriculture ◽

Land Surface ◽

Near Infrared ◽

Infrared Imaging ◽

Space Station ◽

Water Quality Assessment ◽

Low Contrast

Satellite-based visible and near-infrared imaging of the Earth's surface is generally not performed in moderate to highly cloudy conditions; images that look visibly cloud covered to the human eye are typically discarded. Here, we expand upon previous work that employed machine learning (ML) to estimate underlying land surface reflectances at red, green, and blue (RGB) wavelengths in cloud contaminated spectra using a low spatial resolution satellite spectrometer. Specifically, we apply the ML methodology to a case study at much higher spatial resolution with the Hyperspectral Imager for the Coastal Ocean (HICO) that flew on the International Space Station (ISS). HICO spatial sampling is of the order of 90 m. The purpose of our case study is to test whether high spatial resolution features can be captured using multi-spectral imaging in lightly cloudy and overcast conditions. We selected one clear and one cloudy image over a portion ofthe panhandle coastline of Florida to demonstrate that land features are partially recoverable in overcast conditions. Many high contrast features are well recovered in the presence of optically thin clouds. However, some of the low contrast features, such as narrow roads, are smeared out in the heavily clouded part of the reconstructed image. This case study demonstrates that our approach may be useful for many science and applications that are being developed for current and upcoming satellite missions including precision agriculture and natural vegetation analysis, water quality assessment as well as disturbance, change, hazard, and disaster detection.

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Woody plants structure and composition in Burkina Faso Sahel: Case study in Kékénéné village

International Journal of Biological and Chemical Sciences ◽

10.4314/ijbcs.v13i3.38 ◽

2019 ◽

Vol 13 (3) ◽

pp. 1682

Author(s):

Pounyala Awa Ouoba ◽

Dapola Evariste Constant Da

Keyword(s):

Burkina Faso ◽

Woody Plants

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Identification of Shrinkage and Growth Patterns of a Shrinking City in China Based on Nighttime Light Data: A Case Study of Yichun

Sustainability ◽

10.3390/su11246906 ◽

2019 ◽

Vol 11 (24) ◽

pp. 6906 ◽

Cited By ~ 3

Author(s):

Ying Zhou ◽

Chenggu Li ◽

Zuopeng Ma ◽

Shuju Hu ◽

Jing Zhang ◽

...

Keyword(s):

Satellite Images ◽

Infrared Imaging ◽

Demographic Data ◽

Growth Patterns ◽

Nighttime Light Data ◽

Nighttime Light ◽

Urban Science ◽

New Perspective ◽

Shrinking City

Urban shrinkage has become a topic of major concern to scholars of geography and urban science. However, the methods of identifying urban shrinkage and growth have mostly focused on traditional statistical methods, and studies based on nighttime light (NTL) data are rare. Here, we use the NTL data for 56 months from 2012 to 2019 obtained by the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar Orbiting Partnership (NPP) to identify the shrinkage and growth patterns of Yichun in China, by calculating the slope of the NTL radiance value after denoising. At the same time, by combining high-resolution Google satellite images and traditional demographic data, we analyzed the shrinkage characteristics of Yichun. The results of the study confirmed the characteristics of partial shrinkage in China’s shrinking cities. In addition, the use of NPP-VIIRS NTL data was able to more accurately identify the urban shrinkage and growth patterns, and may also be seen to present a more objective picture of reality, thus providing a new perspective for studies of urban shrinkage.

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Post-Earthquake Night-Time Light Piecewise (PNLP) Pattern Based on NPP/VIIRS Night-Time Light Data: A Case Study of the 2015 Nepal Earthquake

Remote Sensing ◽

10.3390/rs12122009 ◽

2020 ◽

Vol 12 (12) ◽

pp. 2009 ◽

Cited By ~ 1

Author(s):

Shengjun Gao ◽

Yunhao Chen ◽

Long Liang ◽

Adu Gong

Keyword(s):

Infrared Imaging ◽

Random Noise ◽

Development Rate ◽

Night Time ◽

Nepal Earthquake ◽

Decomposition Procedure ◽

Spatiotemporal Changes ◽

Reconstruction Rate ◽

2015 Nepal Earthquake

Earthquakes are unpredictable and potentially destructive natural disasters that take a long time to recover from. Monitoring post-earthquake human activity (HA) is of great significance to recovery and reconstruction work. There is a strong correlation between night-time light (NTL) and HA, which aid in the study of spatiotemporal changes in post-earthquake human activities. However, seasonal and noise impact from National Polar-Orbiting Partnership Satellite Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) data greatly limits their application. To tackle these issues, random noise and seasonal fluctuation of NPP/VIIRS from January 2014 to December 2018 is removed by adopting the seasonal-trend decomposition procedure based on loess (STL). Based on the theory of post-earthquake recovery model, a post-earthquake night-time light piecewise (PNLP) pattern is explored by employing the National Polar-Orbiting Partnership Satellite Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) monthly data. PNLP indicators, including pre-earthquake development rate (kp), recovery rate (kr1), reconstruction rate (kr2), development rate (kd), relative reconstruction rate (krp) and loss (S), are defined to describe the PNLP pattern. Furthermore, the 2015 Nepal earthquake is chosen as a case study and the spatiotemporal changes in different areas are analyzed. The results reveal that: (1) STL is an effective algorithm for obtaining HA trend from the time series of denoising NTL; (2) the PNLP pattern, divided into four phases, namely the emergency phase (EP), recovery phase (RP-1), reconstruction phase (RP-2), and development phase (DP), aptly describes the variation in post-earthquake HA; (3) PNLP indicators are capable of evaluating the recovery differences across regions. The main socio-economic factors affecting the PNLP pattern and PNLP indicators are energy source for lighting, type of building, agricultural economy, and human poverty index. Based on the NPP/VIIRS data, the PNLP pattern can reflect the periodical changes of HA after earthquakes and provide an effective means for the analysis and evaluation of post-earthquake recovery and reconstruction.

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Thermal Infrared Imaging to Evaluate Emotional Competences in Nursing Students: A First Approach through a Case Study

Sensors ◽

10.3390/s20092502 ◽

2020 ◽

Vol 20 (9) ◽

pp. 2502

Author(s):

Pilar Marqués-Sánchez ◽

Cristina Liébana-Presa ◽

José Alberto Benítez-Andrades ◽

Raquel Gundín-Gallego ◽

Lorena Álvarez-Barrio ◽

...

Keyword(s):

Nursing Students ◽

Infrared Imaging ◽

Student Nurses ◽

Environmental Data ◽

Thermal Infrared Imaging ◽

Emotional Skills ◽

Non Invasive ◽

Video Stimulus ◽

Music Stimulus

During university studies of nursing, it is important to develop emotional skills for their impact on academic performance and the quality of patient care. Thermography is a technology that could be applied during nursing training to evaluate emotional skills. The objective is to evaluate the effect of thermography as the tool for monitoring and improving emotional skills in student nurses through a case study. The student was subjected to different emotions. The stimuli applied were video and music. The process consisted of measuring the facial temperatures during each emotion and stimulus in three phases: acclimatization, stimulus, and response. Thermographic data acquisition was performed with an FLIR E6 camera. The analysis was complemented with the environmental data (temperature and humidity). With the video stimulus, the start and final forehead temperature from testing phases, showed a different behavior between the positive (joy: 34.5 °C–34.5 °C) and negative (anger: 36.1 °C–35.1 °C) emotions during the acclimatization phase, different from the increase experienced in the stimulus (joy: 34.7 °C–35.0 °C and anger: 35.0 °C–35.0 °C) and response phases (joy: 35.0 °C–35.0 °C and anger: 34.8 °C–35.0 °C). With the music stimulus, the emotions showed different patterns in each phase (joy: 34.2 °C–33.9 °C–33.4 °C and anger: 33.8 °C–33.4 °C–33.8 °C). Whenever the subject is exposed to a stimulus, there is a thermal bodily response. All of the facial areas follow a common thermal pattern in response to the stimulus, with the exception of the nose. Thermography is a technique suitable for the stimulation practices in emotional skills, given that it is non-invasive, it is quantifiable, and easy to access.

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