{"id":4806,"date":"2022-09-23T07:41:13","date_gmt":"2022-09-23T07:41:13","guid":{"rendered":"https:\/\/www.icterra.pt\/?p=4806"},"modified":"2022-09-23T07:42:03","modified_gmt":"2022-09-23T07:42:03","slug":"aboveground-biomass-mapping-by-integrating-icesat-2-sentinel-1-sentinel-2-alos2-palsar2-and-topographic-information-in-mediterranean-forests","status":"publish","type":"post","link":"https:\/\/www.icterra.pt\/legacy\/index.php\/2022\/09\/23\/aboveground-biomass-mapping-by-integrating-icesat-2-sentinel-1-sentinel-2-alos2-palsar2-and-topographic-information-in-mediterranean-forests\/","title":{"rendered":"Aboveground biomass mapping by integrating ICESat-2, SENTINEL-1, SENTINEL-2, ALOS2\/PALSAR2, and topographic information in Mediterranean forests"},"content":{"rendered":"<p style=\"font-weight: 400; text-align: justify;\"><span style=\"font-size: 12pt; font-family: arial, helvetica, sans-serif;\">Juan Guerra-Hern\u00e1ndez, Lana L. Narine, Adri\u00e1n Pascual, Eduardo Gonzalez-Ferreiro, Brigite Botequim, Lonesome Malambo, Amy Neuenschwander, Sorin C. Popescu &amp;\u00a0<strong>Sergio Godinho<\/strong>\u00a0(2022).\u00a0Aboveground biomass mapping by integrating ICESat-2, SENTINEL-1, SENTINEL-2, ALOS2\/PALSAR2, and topographic<\/span><\/p>\n<p>&nbsp;<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-size: 12pt; font-family: arial, helvetica, sans-serif;\">The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) provides an extraordinary opportunity to support global large-scale forest carbon mapping, but further research is needed in order to obtain wall-to-wall forest aboveground biomass (AGB) maps with this technology. The effects of vegetation structure on the performance of canopy height and AGB modeling using ICESat-2 photon-counting light detection and ranging (LiDAR) data in Mediterranean forest areas have not been previously studied in the literature. In this study, we combined recent ICESat-2 vegetation (ATL08) data, Airborne Laser Scanning (ALS)- and field-based estimates, and a multi-sensor earth observation composite for extrapolation of AGB estimates and AGB mapping. A diverse gradient of forest Mediterranean ecosystems, distributed over 19,744.15 km<sup>2<\/sup>\u00a0of forest area in the region of Extremadura (Spain), with different species and structural complexity forming 5 different forest types (3\u00a0<i>Quercus<\/i>\u00a0spp. dominated and 2\u00a0<i>Pinus<\/i>\u00a0spp. dominated forests), was used to (i) evaluate the precision of ICESat-2 canopy height estimations, (ii) develop ICESat-2-based AGB models, and (iii) generate a spatially continuous prediction of AGB by using data from the satellite missions Sentinel-1 (S1), Sentinel-2 (S2), Phased Array L-band Synthetic Aperture Radar (ALOS2\/PALSAR2), and Shuttle Radar Topography Mission (SRTM). First, ALS- and ICESat-2-derived metrics that best described canopy height (p98 and rh98, respectively) were compared at the ATL08 segment level. Second, ALS-based AGB values were derived at the ATL08 segment scale. Third, ALS-based AGB estimates at the ICESat-2 segment level were used as dependent variables to fit ICESat-2-based AGB models. Fourth, a multi-sensor approach was then implemented to predict ICESat-2-derived AGB, by means of a Random Forest (RF) modeling technique, with predictors retrieved from S1, S2, ALOS2\/PALSAR2, and SRTM. Finally, RF was used to generate wall-to-wall AGB maps that were compared with field-, ALS- and ICESat-2-based observations. The agreement between the ALS- and ICESat-2-derived metrics related to the canopy height distribution was higher for\u00a0<i>Pinus<\/i>\u00a0spp. forest than for the\u00a0<i>Quercus<\/i>\u00a0spp-dominated forests. The ICESat-2-based AGB models yielded model efficiency (Mef) values between 0.56 and 0.80, with a RMSE ranging from 7.76 to 17.71\u00a0Mg ha<sup>\u22121<\/sup>\u00a0and rRMSE from 19.04 to 55.21%. The multi-sensor RF models provided the following results when compared with the ICESat-2- and ALS-based AGB observations:\u00a0<i>R<\/i><sup>2<\/sup>\u00a0values of 0.63 and 0.64, and RMSE values of 11.10\u00a0Mg ha<sup>\u22121<\/sup>(rRMSE\u00a0=\u00a028.15%) and 12.28\u00a0Mg ha<sup>\u22121<\/sup>\u00a0(rRMSE\u00a0=\u00a031.45%), respectively, and an approximately unbiased result (0.03\u00a0Mg ha<sup>\u22121<\/sup>\u00a0and 0.09\u00a0Mg ha<sup>\u22121<\/sup>). When applied to the field-based validation data set (4th Spanish National Forest Inventory (SNFI-4) plots\u00a0=\u00a0508), the RF-derived AGB model showed a relatively lower predictive capacity (<i>R<\/i><sup>2<\/sup>\u00a0=\u00a00.45), a higher RMSE value (25.88\u00a0Mg ha<sup>\u22121<\/sup>) and slightly biased results (\u22121.47\u00a0Mg ha<sup>\u22121<\/sup>), especially for larger field-derived AGB intervals. The results of this study serve to provide an initial quantitative assessment of the ICESat-2 ATL08 data for large-scale AGB estimation. The findings suggest that a multi-sensor approach may be feasible for extrapolating ICESat-2-derived AGB estimates over areas where field or ALS reference data are not available.<\/span><\/p>\n<p style=\"font-weight: 400;\"><span style=\"font-size: 12pt; font-family: arial, helvetica, sans-serif;\"><span style=\"font-size: 12pt; text-align: justify;\">Read the<\/span><span style=\"font-size: 12pt; text-align: justify;\">\u00a0<\/span><a style=\"font-size: 12pt; text-align: justify;\" href=\"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/15481603.2022.2115599\">full article<\/a><span style=\"font-size: 12pt; text-align: justify;\">.<\/span>\u00a0information in Mediterranean forests. GIScience &amp; Remote Sensing, 59:1, 1509-1533, DOI: 10.1080\/15481603.2022.2115599 <a href=\"https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/15481603.2022.2115599\" data-saferedirecturl=\"https:\/\/www.google.com\/url?q=https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/15481603.2022.2115599&amp;source=gmail&amp;ust=1663923888713000&amp;usg=AOvVaw3Rad8Mcoe4DwgNTKkkVXDG\">https:\/\/www.tandfonline.com\/doi\/full\/10.1080\/15481603.2022.2115599<\/a><\/span><\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Juan Guerra-Hern\u00e1ndez, Lana L. Narine, Adri\u00e1n Pascual, Eduardo Gonzalez-Ferreiro, Brigite Botequim, Lonesome Malambo, Amy Neuenschwander, Sorin C. Popescu &amp;\u00a0Sergio Godinho\u00a0(2022).\u00a0Aboveground biomass mapping by integrating ICESat-2, SENTINEL-1, SENTINEL-2, ALOS2\/PALSAR2, and topographic &nbsp; The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) provides an extraordinary opportunity to support global large-scale forest carbon mapping, but further research is needed [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"_links":{"self":[{"href":"https:\/\/www.icterra.pt\/legacy\/index.php\/wp-json\/wp\/v2\/posts\/4806"}],"collection":[{"href":"https:\/\/www.icterra.pt\/legacy\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.icterra.pt\/legacy\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.icterra.pt\/legacy\/index.php\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.icterra.pt\/legacy\/index.php\/wp-json\/wp\/v2\/comments?post=4806"}],"version-history":[{"count":2,"href":"https:\/\/www.icterra.pt\/legacy\/index.php\/wp-json\/wp\/v2\/posts\/4806\/revisions"}],"predecessor-version":[{"id":4808,"href":"https:\/\/www.icterra.pt\/legacy\/index.php\/wp-json\/wp\/v2\/posts\/4806\/revisions\/4808"}],"wp:attachment":[{"href":"https:\/\/www.icterra.pt\/legacy\/index.php\/wp-json\/wp\/v2\/media?parent=4806"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.icterra.pt\/legacy\/index.php\/wp-json\/wp\/v2\/categories?post=4806"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.icterra.pt\/legacy\/index.php\/wp-json\/wp\/v2\/tags?post=4806"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}