Remote Sensing in Ecology
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Which of the following best describes the primary advantage of using remote sensing in ecological studies?

  • It provides a broad spatial perspective, enabling monitoring of large or inaccessible areas. (correct)
  • It guarantees higher data accuracy compared to traditional field surveys.
  • It allows for detailed microscopic analysis of soil samples.
  • It eliminates the need for any ground-based data collection, reducing field work.

What is the key difference between a Digital Elevation Model (DEM) and a Digital Surface Model (DSM) derived from LiDAR data?

  • A DEM includes vegetation and buildings, while a DSM only shows the terrain.
  • A DEM is created using hyperspectral data, while a DSM is created using LiDAR data.
  • A DEM represents the top of all objects, while a DSM represents the bare Earth surface.
  • A DEM represents the bare Earth surface, while a DSM represents the top of all objects. (correct)

How does LiDAR technology enable ecologists to study forest structure?

  • By directly measuring the age of trees through laser penetration of the bark.
  • By using sound waves to create acoustic maps of the forest understory.
  • By emitting laser pulses and measuring the time it takes for the light to return, creating detailed 3D maps of the forest. (correct)
  • By capturing high-resolution imagery of individual leaves, which permits species identification .

A researcher aims to assess the health of a forest by detecting early signs of plant stress and nutrient deficiencies. Which remote sensing technology would be most suitable for this?

<p>Hyperspectral imagery (D)</p> Signup and view all the answers

Which of the following is NOT a typical application of hyperspectral imagery in ecological research?

<p>Estimating forest biomass using canopy height models. (D)</p> Signup and view all the answers

How does the Airborne Observation Platform (AOP) of the National Ecological Observatory Network (NEON) contribute to ecological research?

<p>By collecting systematic data using LiDAR, hyperspectral, and high-resolution camera systems across NEON's field sites. (D)</p> Signup and view all the answers

A research team is studying the impact of deforestation on local biodiversity. They need to quickly assess changes in habitat structure and composition over a large, previously inaccessible area. Which combination of remote sensing technologies would be most effective?

<p>LiDAR for structural changes and hyperspectral imagery for species identification. (B)</p> Signup and view all the answers

A scientist wants to monitor the effects of a prolonged drought on plant health in a grassland ecosystem. Which capability of hyperspectral imagery makes it particularly useful for this task?

<p>Its ability to detect subtle changes in spectral reflectance related to plant stress and nutrient content. (B)</p> Signup and view all the answers

Which of the following is a primary advantage of combining LiDAR and hyperspectral data in ecological studies?

<p>It allows for a more comprehensive understanding of ecosystems by providing both structural and compositional information. (C)</p> Signup and view all the answers

How does remote sensing contribute to understanding the effects of climate change on ecosystems?

<p>By tracking changes in vegetation phenology and species distributions. (D)</p> Signup and view all the answers

Which of the following steps is essential during hyperspectral data processing?

<p>Atmospheric correction to account for the effects of the atmosphere on the data. (D)</p> Signup and view all the answers

Why is ground truthing important in remote sensing projects?

<p>To validate remote sensing data with field measurements, ensuring accuracy. (D)</p> Signup and view all the answers

What is a key challenge associated with using remote sensing data in ecological research?

<p>The potential for errors and uncertainties in the data. (B)</p> Signup and view all the answers

How can remote sensing data be used in monitoring forest carbon stocks effectively?

<p>By estimating biomass using LiDAR-derived canopy height and hyperspectral-derived species information. (A)</p> Signup and view all the answers

What role does Google Earth Engine play in ecological remote sensing?

<p>It offers a cloud-based platform for processing and analyzing geospatial data at scale. (C)</p> Signup and view all the answers

In the context of remote sensing, what does temporal resolution refer to?

<p>The frequency at which data is collected over a specific area. (C)</p> Signup and view all the answers

What advancement in remote sensing technology allows for flexible and high-resolution data collection?

<p>The use of drones equipped with specialized sensors. (D)</p> Signup and view all the answers

Which aspect of an ecosystem can be directly informed by hyperspectral data?

<p>Ecosystem composition (C)</p> Signup and view all the answers

Flashcards

Remote Sensing

Gathering information about an object without direct physical contact.

Common Remote Sensing Platforms

Satellites, airplanes, and drones.

Remote Sensing Sensors

Cameras, LiDAR, and spectrometers.

LiDAR

Active remote sensing using laser light to measure distances.

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LiDAR: Time-of-Flight

Time it takes for laser light to return to the sensor.

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Digital Elevation Model (DEM)

Represents the bare Earth surface.

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Hyperspectral Imagery

Captures data across many narrow, contiguous spectral bands.

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Spectral Fingerprinting

Spectral reflectance properties unique to different materials.

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NEON AOP Data

Active Optical Platform (AOP) data collected by NEON, freely available to the public.

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LiDAR in Ecology

Data that measures vegetation structure using laser pulses.

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Hyperspectral Data

Data that measures the light reflected off the earth's surface across many narrow bands.

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LiDAR & Hyperspectral Synergy

LiDAR provides structural info; hyperspectral provides compositional info.

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Vegetation Phenology

In ecology, this refers to tracking changes in the timing of life cycle events in plants.

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LiDAR Data Products

Digital Elevation Models (DEMs) and Digital Surface Models (DSMs).

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Hyperspectral Data Processing

Correcting for atmospheric effects and geometric distortions in hyperspectral data.

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Ground Truthing

Validating remotely sensed data with on-the-ground measurements.

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Drones in Remote Sensing

Collection of flexible, high-resolution ecological data.

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Google Earth Engine

Using a cloud-based platform to process ecological geospatial data at scale.

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Description

Explore remote sensing in ecological research. Learn how LiDAR and hyperspectral imagery enable monitoring of vegetation structure, composition, and function over large, inaccessible areas. Gain insights into mapping using laser light and time-of-flight measurements.

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