Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Responses to Drought and Flooding02:41

Responses to Drought and Flooding

12.0K
Water plays a significant role in the life cycle of plants. However, insufficient or excess of water can be detrimental and pose a serious threat to plants.
12.0K
Ranks01:02

Ranks

468
Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
468
Spearman's Rank Correlation Test01:20

Spearman's Rank Correlation Test

1.4K
Spearman's rank correlation test, also known as Spearman's rho, is a nonparametric method for assessing the strength and direction of association between two variables. This test is particularly valuable when the data distribution is unknown or when the assumption of normality does not hold. Named after the English psychologist and statistician Dr. Charles Edward Spearman, it serves as the nonparametric counterpart to Pearson's correlation coefficient.
Spearman's test calculates correlation by...
1.4K
Prediction Intervals01:03

Prediction Intervals

3.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
3.3K
Wilcoxon Rank-Sum Test01:21

Wilcoxon Rank-Sum Test

720
The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a nonparametric test used to determine if there is a significant difference between the distributions of two independent samples. This test is designed specifically for two independent populations and has the following key requirements:
720
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

485
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
485

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Dynamic change of vestibular function and the long-term prognosis of vestibular neuritis.

Journal of vestibular research : equilibrium & orientation·2023
Same author

Efficacy of add-on blonanserin in treatment-resistant schizophrenia therapy: A retrospective cohort study.

Asian journal of psychiatry·2023
Same author

Protein-centric omics integration analysis identifies candidate plasma proteins for multiple autoimmune diseases.

Human genetics·2023
Same author

Multiple therapies relieve long-term tardive dyskinesia in a patient with chronic schizophrenia: A case report.

World journal of clinical cases·2023
Same author

Internet appointment has more advantages than traditional appointment in the nursing service of dry eye patients.

Medicine·2023
Same author

Dynamic assessment of dust hazard risk in the reconstruction of old industrial buildings: coupling effects of dust distribution and personnel trajectories.

Environmental science and pollution research international·2023

Related Experiment Video

Updated: Jan 21, 2026

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
19:15

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale

Published on: August 25, 2014

87.6K

Drought risk evaluation model with interval number ranking and its application.

Xiao Liu1, Ping Guo2, Qian Tan2

  • 1Centre for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China; Heilongjiang Province Hydraulic Research Institute, Harbin 150080, China.

The Science of the Total Environment
|August 9, 2019
PubMed
Summary

This study developed a new regional drought risk assessment method using remote sensing and uncertainty analysis. The Temperature and Vegetation Polynomial Model (TVPM) proved most effective for monitoring drought conditions.

Keywords:
Advantage degree functionDrought risk evaluationRankingRemote sensing monitoring of droughtSoil moisture content

More Related Videos

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.5K
Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.8K

Related Experiment Videos

Last Updated: Jan 21, 2026

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
19:15

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale

Published on: August 25, 2014

87.6K
An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.5K
Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.8K

Area of Science:

  • Environmental Science
  • Agricultural Science
  • Remote Sensing

Background:

  • Increasing extreme weather events necessitate accurate drought monitoring for sustainable agriculture.
  • Regional drought risk evaluation is crucial for agricultural development and resilience.

Purpose of the Study:

  • To establish a regional drought risk evaluation method integrating remote sensing drought monitoring and uncertainty analysis.
  • To identify the most suitable drought monitoring model and develop a robust drought risk assessment framework.

Main Methods:

  • Utilized a multi-model optimization approach with five models to invert soil moisture content.
  • Selected the Temperature and Vegetation Polynomial Model (TVPM) as the optimal drought monitoring model.
  • Employed statistical-based interval weight determination and interval number sorting for uncertainty analysis in the drought risk model.

Main Results:

  • The TVPM was identified as the most suitable model for drought monitoring after comparative analysis.
  • A regional drought risk evaluation model was successfully established using uncertainty methods.
  • Applied the model to Heilongjiang province, China, ranking drought risk in eight regions for April 2018.

Conclusions:

  • The developed method effectively integrates remote sensing drought monitoring with uncertainty analysis for regional risk assessment.
  • The interval number-based evaluation method demonstrates superior capability in handling real-world uncertainties.
  • The findings provide a valuable tool for agricultural planning and disaster management in drought-prone areas.