|Titre||Temporal filters for mapping phragmites with C-HH SAR data / Filtres temporels pour cartographier les phragmites à partir de données RSO en bande C-HH|
|Auteur||White, L; Brisco, B; Murnaghan, K; Pasher, J; Duffe, J|
|Source||Canadian Journal of Remote Sensing 2020 p. 1-10, https://doi.org/10.1080/07038992.2020.1799770 Accès ouvert|
|Séries alt.||Ressources naturelles Canada, Contribution externe 20200393|
|Éditeur||Taylor & Francis Inc.|
|Document||publication en série|
|Media||papier; en ligne; numérique|
|SNRC||31D/13; 31E/04; 41A/16; 41H/01|
|Région||Parc national du Canada des îles-de-la-Baie-Georgienne|
|Lat/Long OENS|| -80.1992 -79.7775 45.1547 44.7731|
|Sujets||télédétection; imagerie par satellite; méthodes radar; logiciel; végétation; terres humides; eaux de surface; Traitement des données; géophysique; Sciences et technologie; Nature et
|Illustrations||cartes de localisation; tableaux; images satellitaires; organigrammes; séries chronologiques|
|Diffusé||2020 08 18|
|Résumé||(disponible en anglais seulement)|
We compared traditional spatial filters and multi-temporal filters to remove speckle from synthetic aperture radar (SAR) data for mapping Phragmites australis.
SAR constellations, with more rapid revisit capability, allow one to generate stacks of SAR data and to use multi-temporal filters for speckle reduction. GAMMA software offers multi-temporal filters for SAR processing, two of which we compared to the
traditional Enhanced Lee and the Lee filters. We evaluated the filters using three criteria: (1) visual inspection, (2) signal level ratio, and (3) the equivalent number of looks (ENL). The results of this study show that multi-temporal filters were
able to reduce speckle from areas of surface water and land, as well as to improve the detection of Phragmites patches due to preserving the resolution and texture which helped in the detection of the patch boundaries. The signal level ratio was
approximately 1.0 with the GAMMA Multi-temporal filter and approximately 0.9 with the other filters. The enhanced Lee and the two multi-temporal filters produced an equal ENL of about 6. However, due to small patch sizes and backscatter similarity
with cattails and other cover types Phragmites patches were difficult to separate from other types of flooded vegetation with C-HH intensity only.
|Sommaire||(Résumé en langage clair et simple, non publié et disponible en anglais seulement)|
This study focused on improving the accuracy of mapping Phragmites australis, a type of wetland plant, using
synthetic aperture radar (SAR) data. SAR data can be noisy due to speckles, which are unwanted artifacts. To reduce this noise, the researchers compared traditional spatial filters with multi-temporal filters. Multi-temporal filters take advantage of
SAR data collected at different times to improve speckle reduction.
They used software called GAMMA that offers these multi-temporal filters and compared them to traditional filters like Enhanced Lee and Lee. They evaluated the filters based on
visual inspection, signal level ratio, and equivalent number of looks (ENL).
The study found that multi-temporal filters effectively reduced speckle in areas with water and land while preserving important details, which helped detect Phragmites
patches more accurately. The signal level ratio was about 1.0 for the GAMMA Multi-temporal filter and around 0.9 for the other filters. The filters all achieved a similar ENL of about 6.
Overall, this research contributes to improving the mapping
of wetland vegetation, which is crucial for environmental monitoring and conservation efforts.