Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time Series
Introduced insects and pathogens impact millions of acres of forested land in the United States each year, and large-scale monitoring efforts are essential for tracking the spread of outbreaks and quantifying the extent of damage. However, monitoring the impacts of defoliating insects presents a sig...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-07-01
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| Series: | Forests |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4907/8/8/275 |
| _version_ | 1811315465557901312 |
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| author | Valerie J. Pasquarella Bethany A. Bradley Curtis E. Woodcock |
| author_facet | Valerie J. Pasquarella Bethany A. Bradley Curtis E. Woodcock |
| author_sort | Valerie J. Pasquarella |
| collection | DOAJ |
| description | Introduced insects and pathogens impact millions of acres of forested land in the United States each year, and large-scale monitoring efforts are essential for tracking the spread of outbreaks and quantifying the extent of damage. However, monitoring the impacts of defoliating insects presents a significant challenge due to the ephemeral nature of defoliation events. Using the 2016 gypsy moth (Lymantria dispar) outbreak in Southern New England as a case study, we present a new approach for near-real-time defoliation monitoring using synthetic images produced from Landsat time series. By comparing predicted and observed images, we assessed changes in vegetation condition multiple times over the course of an outbreak. Initial measures can be made as imagery becomes available, and season-integrated products provide a wall-to-wall assessment of potential defoliation at 30 m resolution. Qualitative and quantitative comparisons suggest our Landsat Time Series (LTS) products improve identification of defoliation events relative to existing products and provide a repeatable metric of change in condition. Our synthetic-image approach is an important step toward using the full temporal potential of the Landsat archive for operational monitoring of forest health over large extents, and provides an important new tool for understanding spatial and temporal dynamics of insect defoliators. |
| first_indexed | 2024-04-13T11:31:54Z |
| format | Article |
| id | doaj.art-7f401d1184c94361b8a6b45c7a98b074 |
| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
| last_indexed | 2024-04-13T11:31:54Z |
| publishDate | 2017-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Forests |
| spelling | doaj.art-7f401d1184c94361b8a6b45c7a98b0742022-12-22T02:48:33ZengMDPI AGForests1999-49072017-07-018827510.3390/f8080275f8080275Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time SeriesValerie J. Pasquarella0Bethany A. Bradley1Curtis E. Woodcock2Department of Environmental Conservation, University of Massachusetts Amherst, 160 Holdsworth Way, Amherst, MA 01003, USADepartment of Environmental Conservation, University of Massachusetts Amherst, 160 Holdsworth Way, Amherst, MA 01003, USADepartment of Earth and Environment, Boston University, 675 Commonwealth Ave., Boston, MA 02215, USAIntroduced insects and pathogens impact millions of acres of forested land in the United States each year, and large-scale monitoring efforts are essential for tracking the spread of outbreaks and quantifying the extent of damage. However, monitoring the impacts of defoliating insects presents a significant challenge due to the ephemeral nature of defoliation events. Using the 2016 gypsy moth (Lymantria dispar) outbreak in Southern New England as a case study, we present a new approach for near-real-time defoliation monitoring using synthetic images produced from Landsat time series. By comparing predicted and observed images, we assessed changes in vegetation condition multiple times over the course of an outbreak. Initial measures can be made as imagery becomes available, and season-integrated products provide a wall-to-wall assessment of potential defoliation at 30 m resolution. Qualitative and quantitative comparisons suggest our Landsat Time Series (LTS) products improve identification of defoliation events relative to existing products and provide a repeatable metric of change in condition. Our synthetic-image approach is an important step toward using the full temporal potential of the Landsat archive for operational monitoring of forest health over large extents, and provides an important new tool for understanding spatial and temporal dynamics of insect defoliators.https://www.mdpi.com/1999-4907/8/8/275Landsattime seriessynthetic imagesContinuous Change Detection and Classification (CCDC)defoliationgypsy mothLymantria dispar |
| spellingShingle | Valerie J. Pasquarella Bethany A. Bradley Curtis E. Woodcock Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time Series Forests Landsat time series synthetic images Continuous Change Detection and Classification (CCDC) defoliation gypsy moth Lymantria dispar |
| title | Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time Series |
| title_full | Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time Series |
| title_fullStr | Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time Series |
| title_full_unstemmed | Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time Series |
| title_short | Near-Real-Time Monitoring of Insect Defoliation Using Landsat Time Series |
| title_sort | near real time monitoring of insect defoliation using landsat time series |
| topic | Landsat time series synthetic images Continuous Change Detection and Classification (CCDC) defoliation gypsy moth Lymantria dispar |
| url | https://www.mdpi.com/1999-4907/8/8/275 |
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