Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory data
This paper introduces a method for rapid forest damage assessment using satellite images and stand-wise forest inventory data. Two Landsat 5 Thematic Mapper (TM) images from June and September 2010 and data from a forest stand register developed within the frameworks of conventional stand-wise fores...
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| Format: | Article |
| Language: | English |
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Italian Society of Silviculture and Forest Ecology (SISEF)
2013-06-01
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| Series: | iForest - Biogeosciences and Forestry |
| Subjects: | |
| Online Access: | https://iforest.sisef.org/contents/?id=ifor0715-006 |
| _version_ | 1818149991996194816 |
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| author | Jonikavičius D Mozgeris G |
| author_facet | Jonikavičius D Mozgeris G |
| author_sort | Jonikavičius D |
| collection | DOAJ |
| description | This paper introduces a method for rapid forest damage assessment using satellite images and stand-wise forest inventory data. Two Landsat 5 Thematic Mapper (TM) images from June and September 2010 and data from a forest stand register developed within the frameworks of conventional stand-wise forest inventories in Lithuania were used to assess the forest damage caused by wind storms that occurred on August 8, 2010. Satellite images were geometrically and radiometrically corrected. The percentage of damage in terms of wind-fallen or broken tree volume was then predicted for each forest compartment within the zone potentially affected by the wind storm, using the non-parametric k-nearest neighbor technique. Satellite imagery-based difference images and general forest stand characteristics from the stand register were used as the auxiliary data sets for prediction. All auxiliary data were available from existing databases, and therefore did not involve any added data acquisition costs. Simultaneously, aerial photography of the area damaged by the wind storm was carried-out and color infrared (CIR) orthophotos with a resolution of 0.5 x 0.5 m were produced. A precise manual interpretation of the effects of the wind storm was used to validate satellite image-based estimates. The total wind damaged volume in pine dominating forest (~1.180.000 m3) was underestimated by 2.2%, in predominantly spruce stands (~233.000 m3) by 2.6% and in predominantly deciduous stands (~195.000 m3) by 4.2%, compared to validation data. The overall accuracy of identification of wind-damaged areas was around 95-98%, based solely on difference data from satellite images gathered on two dates. |
| first_indexed | 2024-12-11T13:15:50Z |
| format | Article |
| id | doaj.art-ef1cc16170964d439166091c251f25c0 |
| institution | Directory Open Access Journal |
| issn | 1971-7458 1971-7458 |
| language | English |
| last_indexed | 2024-12-11T13:15:50Z |
| publishDate | 2013-06-01 |
| publisher | Italian Society of Silviculture and Forest Ecology (SISEF) |
| record_format | Article |
| series | iForest - Biogeosciences and Forestry |
| spelling | doaj.art-ef1cc16170964d439166091c251f25c02022-12-22T01:06:04ZengItalian Society of Silviculture and Forest Ecology (SISEF)iForest - Biogeosciences and Forestry1971-74581971-74582013-06-016115015510.3832/ifor0715-006715Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory dataJonikavičius D0Mozgeris G1Laboratory of Geomatics, Institute of Land Management and Geomatics, Aleksandras Stulginskis University, Studentu 11, LT-53361 Akademija, Kaunas distr. (Lithuania)Institute of Forest Management and Wood Science, Aleksandras Stulginskis University, Studentu 11, LT-53361 Akademija, Kaunas distr. (Lithuania)This paper introduces a method for rapid forest damage assessment using satellite images and stand-wise forest inventory data. Two Landsat 5 Thematic Mapper (TM) images from June and September 2010 and data from a forest stand register developed within the frameworks of conventional stand-wise forest inventories in Lithuania were used to assess the forest damage caused by wind storms that occurred on August 8, 2010. Satellite images were geometrically and radiometrically corrected. The percentage of damage in terms of wind-fallen or broken tree volume was then predicted for each forest compartment within the zone potentially affected by the wind storm, using the non-parametric k-nearest neighbor technique. Satellite imagery-based difference images and general forest stand characteristics from the stand register were used as the auxiliary data sets for prediction. All auxiliary data were available from existing databases, and therefore did not involve any added data acquisition costs. Simultaneously, aerial photography of the area damaged by the wind storm was carried-out and color infrared (CIR) orthophotos with a resolution of 0.5 x 0.5 m were produced. A precise manual interpretation of the effects of the wind storm was used to validate satellite image-based estimates. The total wind damaged volume in pine dominating forest (~1.180.000 m3) was underestimated by 2.2%, in predominantly spruce stands (~233.000 m3) by 2.6% and in predominantly deciduous stands (~195.000 m3) by 4.2%, compared to validation data. The overall accuracy of identification of wind-damaged areas was around 95-98%, based solely on difference data from satellite images gathered on two dates.https://iforest.sisef.org/contents/?id=ifor0715-006Forest DamageSatellite ImagesChange Detectionk-Nearest Neighbour |
| spellingShingle | Jonikavičius D Mozgeris G Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory data iForest - Biogeosciences and Forestry Forest Damage Satellite Images Change Detection k-Nearest Neighbour |
| title | Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory data |
| title_full | Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory data |
| title_fullStr | Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory data |
| title_full_unstemmed | Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory data |
| title_short | Rapid assessment of wind storm-caused forest damage using satellite images and stand-wise forest inventory data |
| title_sort | rapid assessment of wind storm caused forest damage using satellite images and stand wise forest inventory data |
| topic | Forest Damage Satellite Images Change Detection k-Nearest Neighbour |
| url | https://iforest.sisef.org/contents/?id=ifor0715-006 |
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