Monitoring Bark Beetle Forest Damage in Central Europe. A Remote Sensing Approach Validated with Field Data
Over the last decades, climate change has triggered an increase in the frequency of spruce bark beetle (<i>Ips typographus</i> L.) in Central Europe. More than 50% of forests in the Czech Republic are seriously threatened by this pest, leading to high ecological and economic losses. The...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/21/3634 |
| _version_ | 1827702761580396544 |
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| author | Angel Fernandez-Carrillo Zdeněk Patočka Lumír Dobrovolný Antonio Franco-Nieto Beatriz Revilla-Romero |
| author_facet | Angel Fernandez-Carrillo Zdeněk Patočka Lumír Dobrovolný Antonio Franco-Nieto Beatriz Revilla-Romero |
| author_sort | Angel Fernandez-Carrillo |
| collection | DOAJ |
| description | Over the last decades, climate change has triggered an increase in the frequency of spruce bark beetle (<i>Ips typographus</i> L.) in Central Europe. More than 50% of forests in the Czech Republic are seriously threatened by this pest, leading to high ecological and economic losses. The exponential increase of bark beetle infestation hinders the implementation of costly field campaigns to prevent and mitigate its effects. Remote sensing may help to overcome such limitations as it provides frequent and spatially continuous data on vegetation condition. Using Sentinel-2 images as main input, two models have been developed to test the ability of this data source to map bark beetle damage and severity. All models were based on a change detection approach, and required the generation of previous forest mask and dominant species maps. The first damage mapping model was developed for 2019 and 2020, and it was based on bi-temporal regressions in spruce areas to estimate forest vitality and bark beetle damage. A second model was developed for 2020 considering all forest area, but excluding clear-cuts and completely dead areas, in order to map only changes in stands dominated by alive trees. The three products were validated with in situ data. All the maps showed high accuracies (acc > 0.80). Accuracy was higher than 0.95 and F1-score was higher than 0.88 for areas with high severity, with omission errors under 0.09 in all cases. This confirmed the ability of all the models to detect bark beetle attack at the last phases. Areas with no damage or low severity showed more complex results. The no damage category yielded greater commission errors and relative bias (CEs = 0.30–0.42, relB = 0.42–0.51). The similar results obtained for 2020 leaving out clear-cuts and dead trees proved that the proposed methods could be used to help forest managers fight bark beetle pests. These biotic damage products based on Sentinel-2 can be set up for any location to derive regular forest vitality maps and inform of early damage. |
| first_indexed | 2024-03-10T15:04:04Z |
| format | Article |
| id | doaj.art-6bd8e4128d8945498b491feca6d664be |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T15:04:04Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-6bd8e4128d8945498b491feca6d664be2023-11-20T19:56:12ZengMDPI AGRemote Sensing2072-42922020-11-011221363410.3390/rs12213634Monitoring Bark Beetle Forest Damage in Central Europe. A Remote Sensing Approach Validated with Field DataAngel Fernandez-Carrillo0Zdeněk Patočka1Lumír Dobrovolný2Antonio Franco-Nieto3Beatriz Revilla-Romero4Remote Sensing and Geospatial Analytics Division, GMV, Isaac Newton 11, P.T.M. Tres Cantos, E-28760 Madrid, SpainDepartment of Forest Management and Applied Geoinformatics, Faculty of Forestry and Wood Technology, Mendel University in Brno, 613 00 Brno, Czech RepublicUniversity Forest Enterprise Masaryk Forest Křtiny, Mendel University in Brno, 613 00 Brno, Czech RepublicRemote Sensing and Geospatial Analytics Division, GMV, Isaac Newton 11, P.T.M. Tres Cantos, E-28760 Madrid, SpainRemote Sensing and Geospatial Analytics Division, GMV, Isaac Newton 11, P.T.M. Tres Cantos, E-28760 Madrid, SpainOver the last decades, climate change has triggered an increase in the frequency of spruce bark beetle (<i>Ips typographus</i> L.) in Central Europe. More than 50% of forests in the Czech Republic are seriously threatened by this pest, leading to high ecological and economic losses. The exponential increase of bark beetle infestation hinders the implementation of costly field campaigns to prevent and mitigate its effects. Remote sensing may help to overcome such limitations as it provides frequent and spatially continuous data on vegetation condition. Using Sentinel-2 images as main input, two models have been developed to test the ability of this data source to map bark beetle damage and severity. All models were based on a change detection approach, and required the generation of previous forest mask and dominant species maps. The first damage mapping model was developed for 2019 and 2020, and it was based on bi-temporal regressions in spruce areas to estimate forest vitality and bark beetle damage. A second model was developed for 2020 considering all forest area, but excluding clear-cuts and completely dead areas, in order to map only changes in stands dominated by alive trees. The three products were validated with in situ data. All the maps showed high accuracies (acc > 0.80). Accuracy was higher than 0.95 and F1-score was higher than 0.88 for areas with high severity, with omission errors under 0.09 in all cases. This confirmed the ability of all the models to detect bark beetle attack at the last phases. Areas with no damage or low severity showed more complex results. The no damage category yielded greater commission errors and relative bias (CEs = 0.30–0.42, relB = 0.42–0.51). The similar results obtained for 2020 leaving out clear-cuts and dead trees proved that the proposed methods could be used to help forest managers fight bark beetle pests. These biotic damage products based on Sentinel-2 can be set up for any location to derive regular forest vitality maps and inform of early damage.https://www.mdpi.com/2072-4292/12/21/3634bark beetle<i>Ips typographus</i> L.pestremote sensingchange detectionforest damage |
| spellingShingle | Angel Fernandez-Carrillo Zdeněk Patočka Lumír Dobrovolný Antonio Franco-Nieto Beatriz Revilla-Romero Monitoring Bark Beetle Forest Damage in Central Europe. A Remote Sensing Approach Validated with Field Data Remote Sensing bark beetle <i>Ips typographus</i> L. pest remote sensing change detection forest damage |
| title | Monitoring Bark Beetle Forest Damage in Central Europe. A Remote Sensing Approach Validated with Field Data |
| title_full | Monitoring Bark Beetle Forest Damage in Central Europe. A Remote Sensing Approach Validated with Field Data |
| title_fullStr | Monitoring Bark Beetle Forest Damage in Central Europe. A Remote Sensing Approach Validated with Field Data |
| title_full_unstemmed | Monitoring Bark Beetle Forest Damage in Central Europe. A Remote Sensing Approach Validated with Field Data |
| title_short | Monitoring Bark Beetle Forest Damage in Central Europe. A Remote Sensing Approach Validated with Field Data |
| title_sort | monitoring bark beetle forest damage in central europe a remote sensing approach validated with field data |
| topic | bark beetle <i>Ips typographus</i> L. pest remote sensing change detection forest damage |
| url | https://www.mdpi.com/2072-4292/12/21/3634 |
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