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            <gco:CharacterString>Cette publication de données contient une mosaïque d’un composite d’été optimisé pour l’année 2020 de la rétrodiffusion radar PALSAR-2 en bande L bipolarisée qui couvre tout le Canada (à l'exception de l'Archipel Arctique). Son objectif principal est d'offrir une mosaïque du meilleur composite estival radar en bande L bipolarisée possible et principalement adaptée pour i) classifier les couvertures de végétation naturelle arborée ou arbustive, et ii) estimer leurs attributs de structure (par exemple, hauteur et biomasse). 

## Méthodologie:

Ce produit est issu du post-traitement des mosaïques annuelles « JAXA Global PALSAR-2/PALSAR Mosaics ver. 1 » (ci-après JAXA GPM v1) accessibles gratuitement en tant que données ouvertes. Elles ont été générées par l’Agence spatiale japonaise (JAXA) à l’aide de capteurs radar à synthèse d’ouverture en bande L PALSAR et montés à bord du Advanced Land Observing Satellite (ALOS): ALOS-2 PALSAR-2 (2015 à 2020) et ALOS PALSAR (2007 à 2010). JAXA GPM v1 fournit des mosaïques annuelles d’amplitude de rétrodiffusion gamma zéro (γ°) en bande L bipolarisée HH et HV, orthorectifiées et radiométriquement corrigées pour la pente, avec une résolution de 25 m et échelonnées sur 16 bits (Shimada et al. 2014). Elles sont disponibles comme collection d’images Google Earth Engine à https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_SAR. 

Les données JAXA GPM v1 couvrant le Canada de 2007 à 2020 a fait l’objet d’une méthodologie de post-traitement et de composition infonuagique mise en œuvre dans Google Earth Engine, détaillée dans Pontone et al. 2024 et résumée dans le fichier pdf ‘’Lisezmoi’’ accompagnant le jeu de données. Cette méthode se résume succinctement dans les trois étapes suivantes:

1. Post-traitement des données annuelles γ° HH et HV: gestion des manques de données, filtrage du bruit de speckle, et création de deux indices radar de végétation, soient le ratio HV/HH (HVHH) et le Radar Forest Degradation Index (RFDI).

2. Composition temporelle des données PALSAR-2 γ° post-traitées HH, HV, HVHH et RFDI de 2015 à 2020 visant à i) traiter les manques annuels de données et ii) atténuer les fluctuations nuisibles de la rétrodiffusion à travers les orbites d'ALOS-2, dues aux nombreuses acquisitions effectuées en dehors de l'été.

3. Génération des fichiers matriciels finaux des composites d’été 2020 PALSAR-2 bande L. 

## Performance et limitations: 

Le composite d’été du Canada de rétrodiffusion radar PALSAR-2 en bande L bipolarisée du Canada 2020, sans données manquantes, et optimisé radiométriquement pour 2020, s'est avéré nettement amélioré par rapport à la mosaïque JAXA GPM v1 de l'année 2020 seule, en particulier dans le nord du Canada (Pontone et al. 2024). Cependant, ce produit doit être considéré comme un composite pseudo-estival et les utilisateurs doivent être conscients des limitations connues suivantes :

• Dans le nord-ouest du Canada, il y avait souvent un nombre minimal, voire nul, d'acquisitions estivales de PALSAR-2, entraînant des fluctuations résiduelles de la rétrodiffusion.

• Le composite peut présenter du bruit radiométrique dans les zones ayant connu des perturbations majeures (feux, coupes) entre 2015 et 2020 malgré qu'elles ont été prises en compte dans la méthodologie de composition.

• Ce produit est considéré comme moins performant, voire possiblement inadapté, pour i) caractériser des couvertures terrestres dynamiques telles que les prairies, les terres cultivées et les plans d'eau, ou ii) estimer le contenu en humidité du sol et/ou de la végétation. 

A noter que JAXA a publié une version 2 améliorée de leurs mosaïques GPM, qui n'était pas disponible au moment où notre jeu de données a été développé et créé. Une analyse préliminaire montre que notre composite d’été PALSAR-2 de 2020 semble être meilleure que la mosaïque JAXA GPM v2 de 2020 dans le nord du Canada. 

## Informations supplémentaires sur l’ensemble de données : 

Cet ensemble de données comprend quatre fichiers matriciels au format geotiff des quatre mosaïques des composites d’été 2020 PALSAR-2 en bande L de l’amplitude de rétrodiffusion gamma zéro (γ°) bipolarisée (HH, HV) incluant deux indices radar de végétation (HVHH, RFDI). Ces données sont orthorectifiées et radiométriquement corrigées pour la pente, et échelonnées en valeurs numériques (DN) sur 16 bits avec une taille de pixel de 30 m dans la projection conforme conique de Lambert. Un cinquième fichier d'aperçu rapide RVB de 8 bits accompagne ces données ainsi qu’un fichier pdf ‘’Lisezmoi’’ décrivant plus en détails les caractéristiques des fichiers ainsi que des équations permettant de convertir les valeurs numériques en valeurs absolues de rétrodiffusion γ°. 

## Citation pour cet ensemble de données: 

Beaudoin, A., Villemaire, P., Gignac, C., Tolszczuk, S., Guindon, L., Pontone, N., Millard, C. (2024). Canada’s PALSAR-2 dual-polarized L-band radar summer backscatter composite, circa 2020. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/8ec4ee78-9240-4bd0-9c97-d3a27829e209

De plus, s’il vous plaît donner le crédit à l’Agence spatiale japonaise JAXA avec la mention “L’ensemble de données Global PALSAR-2/PALSAR Mosaics v1 a été fourni par JAXA (©JAXA)” 

## Référence pour le développement de cet ensemble de données et son utilisation pour la cartographie des milieux humides du Canada: 

Pontone, N., Millard, K., Thompson, D., Guindon, L., Beaudoin, A. (2024). A hierarchical, Multi-Sensor Framework for Peatland Sub-Class and Vegetation Mapping Throughout the Canadian Boreal Forest. Remote Sensing for Ecology and Conservation (accepté pour publication)

## Référence citée: 

Shimada, M., Itoh, T., Motooka, T., Watanabe, M., Tomohiro, S., Thapa, T., Lucas, R. (2014). New Global Forest/Non-Forest Maps from ALOS PALSAR Data (2007-2010). Remote Sensing of Environment, 155, pp. 13-31. https://doi.org/ 10.1016/j.rse.2014.04.014</gco:CharacterString>
            <gmd:PT_FreeText>
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                  <gmd:LocalisedCharacterString locale="#eng">This data publication contains an optimized mosaic of PALSAR-2 L-band dual-polarized radar backscatter summer composite for the year 2020 across Canada (excluding the Arctic Archipelago). Its primary purpose is to offer the best possible L-band radar summer-like composite mosaic mostly tailored for i) classifying natural treed or shrubby vegetation covers, and ii) estimating their structural attributes, such as height and biomass. 

## Methodology:

This product is based on the freely available and open dataset of yearly JAXA Global PALSAR-2/PALSAR Mosaics ver. 1 (hereafter JAXA GPM v1). They were generated by the Japanese space agency (JAXA) using PALSAR L-band synthetic aperture radar sensors aboard the Advanced Land Observing Satellites (ALOS): ALOS-2 PALSAR-2 (2015 to 2020) and ALOS PALSAR (2007 to 2010). JAXA GPM v1 provide yearly mosaics orthorectified and slope-corrected L-band HH- and HV-polarized gamma naught (γ°) backscatter amplitude with 25-m pixel size and scaled as 16-bit data (Shimada et al. 2014). JAXA GPM v1 are accessible as a Google Earth Engine image collection at https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_SAR.

The yearly 2007 to 2020 JAXA GPM v1 dataset across Canada underwent a post-processing and compositing methodology implemented in Google Earth Engine, as detailed in Pontone et al. 2024 and summarized in a pdf “Readme” file provided with the dataset. In summary, the method involves these three steps: 

1. Post-processing of yearly γ° HH and HV datasets: handling data gaps, filtering speckle noise, and generating two radar vegetation indices, the HV/HH ratio (HVHH) and the radar forest degradation index (RFDI).

2. Temporal compositing from 2015 to 2020 of post-processed yearly γ° PALSAR-2 HH, HV, HVHH, and RFDI backscatter data aimed to i) address data gaps and ii) mitigate detrimental backscatter fluctuations across ALOS-2 orbits resulting from numerous out-of-summer acquisitions.

3. Generating the final PALSAR-2 L-band γ° radar backscatter summer composite circa 2020 raster files. 

## Performance et limitations:

The resulting Canada-wide, excluding the Arctic Archipelago, gap-free and radiometrically optimized mosaic of circa 2020 PALSAR-2 L-band backscatter summer composite was found significantly improved compared to the single-year 2020 JAXA GPM v1 mosaic, particularly in northern boreal Canada (Pontone et al. 2024). However, this product should be considered as a summer-like composite and users should be mindful of the following known limitations:	

• In northwestern Canada, there were often minimal to no summer PALSAR-2 acquisitions, resulting in residual backscatter fluctuations across ALOS-2 orbits.

• The composite may exhibit patchy radiometric noise in areas that experienced major disturbances (fires, harvesting) between 2015 and 2020 despite they were accounted for in our compositing methodology.

• This product is deemed less performant, or possibly not suitable, for i) characterizing highly dynamic land cover types such as grasslands, croplands, and water bodies, or for ii) estimating soil and/or vegetation moisture content for the year 2020.

As a final note, JAXA released an improved GPM ver. 2 that was not available at the time of this study. A preliminary analysis shows that the circa 2020 PALSAR-2 composite product still seems to outperform the 2020 JAXA GPM v2 in northern Canada.  

## Additional Information on Dataset: 

This dataset comprises four raster geotiff files of circa 2020 L-band PALSAR-2 summer temporal composites as mosaics of orthorectified and radiometrically slope corrected dual-polarized HH and HV gamma naught (γ°) backscatter amplitude, along with two radar vegetation indices (HVHH, RFDI), all scaled as 16-bit Digital Number (DN) values with 30-m pixel size in Lambert conformal conic projection. An additional 8-bit RGB quick-view file is also provided. A companion pdf ”Readme” file provides further details about these geotiff files and equations to convert DN values to γ° absolute intensity values. 

## Dataset Citation: 

Beaudoin, A., Villemaire, P., Gignac, C., Tolszczuk, S., Guindon, L., Pontone, N., Millard, C. (2024). Canada’s PALSAR-2 dual-polarized L-band radar summer backscatter composite, circa 2020. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/8ec4ee78-9240-4bd0-9c97-d3a27829e209

In addition, please provide credits to the Japanese space agency JAXA with the mention “Original Global PALSAR-2/PALSAR Mosaics v1 provided by JAXA (©JAXA)” 

## Publication Reference for Product Development and Use in Wetland Mapping: 

Pontone, N., Millard, K., Thompson, D., Guindon, L., Beaudoin, A. (2024). A hierarchical, Multi-Sensor Framework for Peatland Sub-Class and Vegetation Mapping Throughout the Canadian Boreal Forest. Remote Sensing for Ecology and Conservation (accepted for publication).

## Cited reference: 

Shimada, M., Itoh, T., Motooka, T., Watanabe, M., Tomohiro, S., Thapa, T., Lucas, R. (2014). New Global Forest/Non-Forest Maps from ALOS PALSAR Data (2007-2010). Remote Sensing of Environment, 155, pp. 13-31. https://doi.org/ 10.1016/j.rse.2014.04.014</gmd:LocalisedCharacterString>
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