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

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

950
Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
The ATR process begins by directing a beam...
950
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

1.6K
IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
1.6K
Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

8.4K
Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
8.4K

You might also read

Related Articles

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

Sort by
Same author

Hyperspectral reflectance spectroscopy for rapid nondestructive microstructural evaluation of high strength internally cured concrete.

Scientific reports·2025
Same author

Water quality mapping using airborne and satellite hyperspectral imagery across the selected coastal waters of India.

Marine pollution bulletin·2025
Same author

Hyperspectral discrimination of vegetable crops grown under organic and conventional cultivation practices: a machine learning approach.

Scientific reports·2025
Same author

Precision crop mapping: within plant canopy discrimination of crop and soil using multi-sensor hyperspectral imagery.

Scientific reports·2024
Same author

Ultra-high-resolution hyperspectral imagery datasets for precision agriculture applications.

Data in brief·2024
Same author

Deep learning-based prediction of plant height and crown area of vegetable crops using LiDAR point cloud.

Scientific reports·2024

Related Experiment Video

Updated: Dec 4, 2025

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

4.2K

Multi-platform optical remote sensing dataset for target detection.

Sudhanshu Shekhar Jha1, Manohar Kumar1, Rama Rao Nidamanuri1

  • 1Department of Earth and Space Sciences, Indian Institute of Space Science and Technology, Valiamala, Thiruvananthapuram, Kerala, India.

Data in Brief
|October 22, 2020
PubMed
Summary

A new remote sensing dataset offers high-resolution, multi-platform data for target detection. This benchmark dataset aids in developing and validating algorithms for diverse applications like agriculture and surveillance.

Keywords:
AVIRIS-NGEngineered material detectionField reflectance spectroscopyMulti-platform remote sensingSub-pixel material detectionTarget detectionTerrestrial hyperspectral imaging

More Related Videos

Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor IRIS
11:04

Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor IRIS

Published on: May 3, 2011

15.0K
Multimodal Optical Imaging Platform for Studying Cellular Metabolism
04:47

Multimodal Optical Imaging Platform for Studying Cellular Metabolism

Published on: June 6, 2025

879

Related Experiment Videos

Last Updated: Dec 4, 2025

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

4.2K
Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor IRIS
11:04

Biomolecular Detection employing the Interferometric Reflectance Imaging Sensor IRIS

Published on: May 3, 2011

15.0K
Multimodal Optical Imaging Platform for Studying Cellular Metabolism
04:47

Multimodal Optical Imaging Platform for Studying Cellular Metabolism

Published on: June 6, 2025

879

Area of Science:

  • Remote Sensing
  • Geospatial Analysis
  • Data Science

Background:

  • Target detection in remote sensing is crucial for applications like mineral mapping, agriculture, and surveillance.
  • Existing datasets often lack multi-platform integration and high-resolution data for comprehensive target detection studies.

Purpose of the Study:

  • To present a novel, high-resolution, multi-platform remote sensing benchmark dataset for target detection.
  • To provide a comprehensive resource for algorithm development and validation across various scales.

Main Methods:

  • Acquired data using terrestrial hyperspectral imager (THI), airborne AVIRIS-NG, and space-borne Sentinel-2 sensors.
  • Processed imagery with atmospheric correction (FLAASH) and resampled in-situ spectral data.
  • Established target regions of interest (ROIs) using GPS coordinates for airborne and space-borne imagery.

Main Results:

  • Developed a unique dataset integrating ground, airborne, and space-borne remote sensing data.
  • Included processed imagery, in-situ spectral references, and designated ROIs for five engineered targets.
  • The dataset facilitates multi-scale, multi-platform target detection assessments.

Conclusions:

  • The presented dataset is a valuable resource for advancing target detection algorithms in remote sensing.
  • It supports research and development for both strategic and civilian applications.
  • Enables the assessment of engineered material detection capabilities across different platforms.