Comcast Cable Communications, LLC

China Institute of Water Resources and Hydropower Research

Wenjing Lu

Wenlong Song

Yizhu Lu

Xiuhua Chen

Fan Yang

Qiang Wang

Jian Li

Yu Cao

Lin Lin

Long Chen

Hongjie Liu

Yun Liu

Lang Yu

Changjun Liu

Mengyi Li

Hanyu Liu

Xuecheng Xing

Yangjun Shi

Rongjie Gui

Ruofei Ma

Pu Zhou

A rapid monitoring and identification method for winter wheat drought levels includes: 1) obtaining multispectral images and ground-measured LAI through UAV-based multi-payload low-altitude remote sensing technology, and calculating vegetation indices such as Normalized Difference Vegetation Index (NDVI), Difference Vegetation Index (DVI), Ratio Vegetation Index (RVI), Enhanced Vegetation Index (EVI), Optimized soil adjusted vegetation index (OSAVI) and Transformed Chlorophyll Absorption Reflectance Index; 2) establishing regression equations between the calculated vegetation indices and measured LAI for different growth stages, and selecting the optimal model equation for each growth stage; 3) using the optimal model equation to invert the LAI of winter wheat at various growth stages, and calibrating the LAI thresholds for different drought stress levels; 4) acquiring the multispectral images of target plot through real-time monitoring, calculating the required vegetation indices, inverting to obtain the LAI value, and comparing it with the threshold to determine the current drought stress level.

Rapid drought monitoring and identification method for winter wheat based on UAV measurements of leaf area index

A rapid monitoring and discrimination method for drought conditions in summer maize based on chlorophyll content includes: 1) Obtaining multi-spectral imagery through UAV multi-payload low-altitude remote sensing technology and measuring chlorophyll content on the ground. Additionally, calculating vegetation indices including Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and Renormalized Difference Vegetation Index (RENDVI). 2) Selecting vegetation indices and constructing regression equations with measured chlorophyll content during different growth stages. The regression equation with the highest correlation for each growth stage is chosen as the optimal model equation for that particular stage. 3) Using the optimal model equations to retrieve chlorophyll content for each period and determining thresholds for chlorophyll content across different drought levels through calibration. 4) Calculating the required vegetation indices from real-time multi-spectral imagery of the field under test, retrieving chlorophyll content, and comparing it with the established thresholds to assess the real-time drought level.

Rapid UAV-based monitoring and discrimination method for drought in summer maize based on chlorophyll content

Systems, apparatuses, and methods are described for generating unique identifiers. Identifiers may be organized or grouped by different topics. Identifiers may be requested, generated, stored as groups, and may be allocated from those groups based on requests for identifiers to improve the efficiency of one or more computing devices or systems. The size of each group of identifiers may be adjusted.

Generating unique identifiers

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Beijing, China

Wenjing Lu