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Frontiers | Mapping of Pollution Distribution for Electric Power System Based on Satellite Remote Sensing

In recent years, the frequent fouling accidents has posed a serious threat to people's life and property safety. Due to the wide distribution of pollution sources and variable meteorological factors, it is a very time-consuming and labour-intensive task to map the pollution distribution by traditional methods. In this work, a study on the mapping of pollution distribution based on satellite remote sensing is carried out in Yunnan Province, China, as an example. Several machine learning methods (e.g. KNN, SVM, etc.) are used to analyze the effects of conditions such as multiple air pollution data and meteorological data on pollution distribution map levels. The results indicate that the ensemble learning model has the highest accuracy of 71.2\% in this application. The new pollution distribution map using this classifier has 5,506 more pixels in the most severe pollution level than the traditional. Lastly, The remote sensing-based map and the manual measurement-based map were combin

Kunming
Yunnan
China
Beijing
Syria
South-korea
Jordan
Gong-da
Jiangxi
Sichuan
Gansu
Syrian

Hyperspectral Sensor for High-Resolution Chlorophyll Fluorescence Measurements

Hyperspectral Sensor for High-Resolution Chlorophyll Fluorescence Measurements The award-winning Hyperspec® Solar Induced Fluorescence (SIF) imaging sensor from Analytik is ideal for remote sensing, particularly plant and crop photosynthesis and climatology applications where high-resolution chlorophyll fluorescence measurements are vital. Hyperspec® solar induced fluorescence imaging sensor (courtesy Headwall Photonics) The push-broom sensor collects hyperspectral image data with 1,600 spatial pixels per line at extremely high spectral resolution (0.1-0.2nm full width at half maximum) across the chlorophyll fluorescence emission spectrum from 671nm to 780nm. This allows both the important ‘Oxygen-A’ and ‘Oxygen-B’ bands (O2-A and O2-B) to be exploited for more accurate insight into photosynthetic processes. With this data, environmental scientists can gain a better understanding of plant physiology and stress.

Hiran-vegad
Analytik-ltdmar
From-analytik-ltdmar
Solar-induced-fluorescence
Headwall-photonics
Spectral-imaging-specialist
ஹிரான்-வேகாட்
ஹெட்வால்-ஃபோட்டானிக்ஸ்
நிறமாலை-இமேஜிங்-நிபுணர்

Light signal emitted during photosynthesis used to quickly screen crops

Loading video. VIDEO: University of Illinois researchers have revealed a new approach to estimate the photosynthetic capacity of crops to pinpoint their top-performing traits and speed up the plant screening process, according to. view more  Credit: Amanda Nguyen/RIPE project An international effort called Realizing Increased Photosynthetic Efficiency (RIPE) aims to transform crops ability to turn sunlight and carbon dioxide into higher yields. To achieve this, scientists are analyzing thousands of plants to find out what tweaks to the plant s structure or its cellular machinery could increase production. University of Illinois researchers have revealed a new approach to estimate the photosynthetic capacity of crops to pinpoint these top-performing traits and speed up the screening process, according to a new study in the

Illinois
United-states
University-of-illinois
Matthew-siebers
Katherine-meacham-hensold
Peng-fu
Carl-bernacchi
Us-department-of-agriculture
Us-foundation-for-food
Research-plant-physiologist
Melinda-gates-foundation
Agricultural-research-service

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