Johan Fransson - Academia.edu (original) (raw)

Papers by Johan Fransson

Canadian Journal of Remote Sensing, 2020

Above-ground biomass change accumulated during four growth seasons in a hemi-boreal forest was pr... more Above-ground biomass change accumulated during four growth seasons in a hemi-boreal forest was predicted using airborne Land P-band synthetic aperture radar (SAR) backscatter. The radar data were collected in the BioSAR 2007 and BioSAR 2010 campaigns over the Remningstorp test site in southern Sweden. Regression models for biomass change were developed from biomass maps created using airborne LiDAR data and field measurements. To facilitate training and prediction on image pairs acquired at different dates, a backscatter offset correction method for L-band data was developed and evaluated. The correction, based on the HV/VV backscatter ratio, facilitated predictions across image pairs almost identical to those obtained using data from the same image pair for both training and prediction. For P-band, previous positive results using an offset correction based on the HH/VV ratio were validated. The best L-band model achieved a root mean square error (RMSE) of 21 t/ha, and the best P-band model achieved an RMSE of 19 t/ha. Those accuracies are similar to that of the LiDAR-based biomass change of 18 t/ha. The limitation of using LiDARbased data for training was considered. The findings demonstrate potential for improved biomass change predictions from L-band backscatter despite varying environmental conditions and calibration uncertainties. RÉSUMÉ

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 17, 2022

This paper describes the tower-based radar BorealScat, which is being developed for polarimetric,... more This paper describes the tower-based radar BorealScat, which is being developed for polarimetric, tomographic and Doppler measurements at the hemi-boreal forest test site in Remningstorp, Sweden. The facility consists of a 50-m high tower equipped with an antenna array at the top of the tower, a 20-port vector network analyser (VNA), 20 low-loss cables for interconnection, and a calibration loop with a switching network. The first version of BorealScat will perform the full set of measurements in the frequency range 0.4-1.4 GHz, i.e. P-band and L-band. The tower is currently under construction at a forest stand dominated by Norway spruce (Picea abies (L.) Karst.). The mature stand has an above-ground dry biomass of 300 tons/ha. Data collections are planned to commence in autumn 2016.

IEEE Transactions on Geoscience and Remote Sensing, Jun 1, 2005

Multitemporal European Remote Sensing satellites 1 and 2 (ERS-1/2) and the Japanese Earth Resourc... more Multitemporal European Remote Sensing satellites 1 and 2 (ERS-1/2) and the Japanese Earth Resources Satellite 1 (JERS-1) interferometric synthetic aperture radar (InSAR) data from a boreal forest test site in Sweden (stem volumes up to 335 m 3 /ha, equivalent to above-ground dry biomass of 200 tons/ha) are studied in order to estimate stem volume using coherence and backscatter. The changes of JERS-1 backscatter and ERS-1/2 tandem coherence between images are consistent over the area studied, in contrast to ERS-1/2 backscatter. A model-based regression analysis has been performed, and the use of the model for inversion is discussed and compared with other approaches found in the literature. The model parameters are discussed in terms of their relation to wind speed and temperature. Results from the different acquisitions are combined to improve the stem volume estimation. The accuracy in terms of rms error (RMSE) for standwise estimated stem volume is 10 m 3 /ha using ERS-1/2 coherence. Using backscatter and coherence from JERS-1 we obtain an RMSE of 30-35 m 3 /ha. Finally, conditions for accurate retrieval of stem volume using multitemporal InSAR observations are discussed. We conclude that C-and L-band repeat-pass InSAR can provide stem volume estimates in boreal forests with accuracies similar to those of standard in situ measurements. Index Terms-Borel forest, European Remote Sensing satellite (ERS), Japanese Earth Resources Satellite (JERS), interferometric sythetic aperture radar (InSAR), multitemporal. I. INTRODUCTION T HERE IS AN increasing need for forest information related to its importance for the environment and global climate (e.g., monitoring for the Kyoto protocol) as well as forest management aspects. In particular, satellite observations can be useful for environmental studies, since an internationally accepted, consistent, and robust method is required for monitoring on a large scale. The synthetic aperture radars (SARs) on the European Remote Sensing 1 and 2 satellites (ERS-1/2) and the Japanese Earth Resources Satellite 1 (JERS-1) missions have provided not only the possibility for multitemporal acquisitions independent of clouds but also interferometric SAR (InSAR) observations. This study reports an investigation of the use of multitem

Global Change Biology, Jun 1, 2023

When modeling forest variables from InSAR phase height data, phase noise is a nuisance that can b... more When modeling forest variables from InSAR phase height data, phase noise is a nuisance that can be mitigated by spatial averaging. In this empirical study, based on data from a hemi-boreal forest, the relation between field measured forest variables and TanDEM-X phase height and its dependence on the size of the field plots was investigated. Also, the impact of extending the region of phase height extraction beyond the actual plot size was investigated in order to determine the usefulness of this approach when small plot sizes cause significant noise in the estimation of phase height. For fixed field plot sizes (7 m and 10 m radii), the maximum correlation between Lorey's height and phase height occurred for phase height extraction regions multiple times larger in area than the field plots, which were located in homogenous stands.

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 17, 2022

A first evaluation of ALOS-2 PALSAR-2 data for forest stem volume estimation has been performed a... more A first evaluation of ALOS-2 PALSAR-2 data for forest stem volume estimation has been performed at a coniferous dominated test site in southern Sweden. Both the Fine Beam Dual (FBD) polarization and the Quad-polarimetric mode were investigated. Forest plots with stem volume reaching up to a maximum of about 620 m 3 ha-1 (corresponding to 370 tons ha-1) were analyzed by relating backscatter intensity to field data using an exponential model derived from the Water Cloud Model. The estimation accuracy of stem volume at plot level (0.5 ha) was calculated in terms of Root Mean Square Error (RMSE). For the best case investigated an RMSE of 43.1% was obtained using one of the FBD HV-polarized images. The corresponding RMSE for the FBD HH-polarized images was 43.9%. In the Quadpolarimetric mode the lowest RMSE at HV-and HHpolarization was found to be 39.8% and 47.4%, respectively.

Interferometric TanDEM-X data from 2011 and 2014 were used to create biomass maps over the Swedis... more Interferometric TanDEM-X data from 2011 and 2014 were used to create biomass maps over the Swedish test site Remningstorp. These maps were used to compute the biomass change for four classes; pre-commercial thinning, thinning, clear-cutting, and untouched forest. Field inventory and ALS data from the corresponding years were used as reference data. The biomass change was compared on 12 subjectively chosen plots with 40 m radius for each class. It was found, that pre-commercial thinning was difficult to detect, as the biomass loss was less than the biomass growth during the four vegetation seasons investigated. Thinning could be detected from the biomass change being about zero or slightly negative, while clear-cut plots were obvious to notice, with the biomass withdrawal being several hundreds of tons ha-1. The untouched plots had a biomass growth of about 4 to 6 tons ha-1 year-1. It was concluded, that annual TanDEM-X images can be used to detect also smaller silviculture activities such as thinning, but further research with shorter time periods would be desired.

Remote Sensing of Environment, Feb 1, 2021

Agricultural and Forest Meteorology, Aug 1, 2019

Boreal forests exchange large amounts of carbon dioxide (CO 2) with the atmosphere. A managed bor... more Boreal forests exchange large amounts of carbon dioxide (CO 2) with the atmosphere. A managed boreal landscape usually comprises various potential CO 2 sinks and sources across forest stands of varying age classes, clearcut areas, mires, and lakes. Due to this heterogeneity and complexity, large uncertainties exist regarding the net CO 2 balance at the landscape scale. In this study, we present the first estimate of the net CO 2 exchange over a managed boreal landscape (∼68 km 2) in northern Sweden, based on tall tower eddy covariance measurements. Our results suggest that from March 1, 2016 to February 28, 2018, the heterogeneous landscape was a net CO 2 sink with a 2-year mean uptake of −87 ± 6 g C m −2 yr −1. Due to an earlier and warmer spring and sunnier autumn, the landscape was a stronger CO 2 sink during the first year (−122 ± 8 g C m −2) compared to the second year (−52 ± 9 g C m −2). Footprint analysis shows that 87% of the CO 2 flux measurements originated from forests, whereas mires, clear-cuts, lakes, and grassland contributed 11%, 1%, 0.7%, and 0.2%, respectively. Altogether, the CO 2 sink strength of the heterogeneous landscape was up to 38% lower compared to the sink strength of a mature stand surrounding the tower. Overall, this study suggests that the managed boreal landscape acted as a CO 2 sink and advocates tall tower eddy covariance measurements to improve regional carbon budget estimates.

Global Change Biology, Feb 12, 2020

Article type : Primary Research Articles The Net Landscape Carbon Balance-integrating terrestrial... more Article type : Primary Research Articles The Net Landscape Carbon Balance-integrating terrestrial and aquatic carbon fluxes in a managed boreal forest landscape in Sweden

Remote Sensing of Environment, Oct 1, 2015

ABSTRACT This paper presents and assesses spatially explicit estimates of forest growing stock vo... more ABSTRACT This paper presents and assesses spatially explicit estimates of forest growing stock volume (GSV) of the northern hemisphere (north of 10°N) from hyper-temporal observations of Envisat Advanced Synthetic Aperture Radar (ASAR) backscattered intensity using the BIOMASAR algorithm. Approximately 70,000 ASAR images at a pixel size of 0.01° were used to estimate GSV representative for the year 2010. The spatial distribution of the GSV across four ecological zones (polar, boreal, temperate, subtropical) was well captured by the ASAR-based estimates. The uncertainty of the retrieved GSV was smallest in boreal and temperate forest (< 30% for approximately 80% of the forest area) and largest in subtropical forest. ASAR-derived GSV averages at the level of administrative units were mostly in agreement with inventory-derived estimates. Underestimation occurred in regions of very high GSV (> 300 m3/ha) and fragmented forest landscapes. For the major forested countries within the study region, the relative RMSE between ASAR-derived GSV averages at provincial level and corresponding values from National Forest Inventory was between 12% and 45% (average: 29%)

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 17, 2022

Agricultural and Forest Meteorology, May 1, 2022

In this paper, the potential of mono-and bistatic HHpolarized UHF-band SAR imagery for mapping of... more In this paper, the potential of mono-and bistatic HHpolarized UHF-band SAR imagery for mapping of a hemiboreal forest is studied. SAR data have been acquired with the two airborne SAR sensors LORA and SETHI during a joint FOI-ONERA campaign conducted in 2010. Three acquisition modes are compared: monostatic, quasimonostatic (difference in elevation angle around 0°) and bistatic (difference in elevation angle around 6°). Images acquired at two perpendicular flight headings are used, i.e. 178° and 268°, to evaluate the influence of topography, which often has an aggravating effect on forest variable estimation. It is observed that for the quasi-monostatic and bistatic acquisitions, the influence of ground topography is lower compared to the monostatic acquisition. A linear regression model is used to explain the dependence of the backscattering coefficient on the logarithm of biomass, and it is observed that the estimated intercept and slope are similar for the two headings only in the case of quasi-monostatic and bistatic acquisitions, of which the latter features the lowest error and the highest coefficient of determination (0.73 and 0.70, respectively, for headings 178° and 268°).

Three-year forest above-ground biomass change were measured using L- and P-band Synthetic Apertur... more Three-year forest above-ground biomass change were measured using L- and P-band Synthetic Aperture Radar (SAR) backscatter. The SAR data were collected in the airborne BioSAR 2007 and BioSAR 2010 campaigns over the hemiboreal Remningstorp test site in southern Sweden. Regression models for biomass were developed using reference biomass maps created using airborne laser scanning data and field measurements. The results from regression analysis show that using HV backscatter (or VH) in a model with above-ground biomass and backscatter change on either natural logarithmic or square root, and decibel scale, respectively, explained most of the variation in the biomass change, both for L- and P-band. In the case of L-band, the two best cases showed R2 values of 66%, when comparing two SAR images acquired 2007 and 2010. For P-band using the same models, the best cases showed R2 values of 62%. In summary, the results look promising using L- and P-band backscattering for mapping biomass change.

Remote Sensing of Environment, Mar 1, 2022

Scandinavian Journal of Forest Research, Feb 8, 2016

ABSTRACT Discrimination of deciduous trees using spectral information from aerial images has only... more ABSTRACT Discrimination of deciduous trees using spectral information from aerial images has only been partly successfully due to the complexity of the reflectance at different view angles, times of acquisition, phenology of the trees and inter-tree radiance. Therefore, the objective was to evaluate the accuracy of estimating the proportion of deciduous stem volume (P) utilizing change detection between canopy height models (CHMs) generated by digital photogrammetry from leaf-on and leaf-off aerial images instead of using spectral information. The study was conducted at a hemi-boreal study area in Sweden. Using aerial images from three seasons, CHMs with a resolution of approximately 0.5 m were generated using semi-global matching. For training plots, metrics describing the change between leaf-on and leaf-off conditions were calculated and used to model the continuous variable P, using the Random Forest approach. Validated at sub-stands, the estimation accuracy of P in terms of root mean square error and bias was found to be 18% and −6%, respectively. The overall classification accuracy, using four equally wide classes, was 83% with a kappa value of 0.68. The validation plots in classes of high proportion of coniferous or deciduous stem volume were well classified, whereas the mixed forest classes showed lower classification accuracies.

Canadian Journal of Remote Sensing, 2020

Above-ground biomass change accumulated during four growth seasons in a hemi-boreal forest was pr... more Above-ground biomass change accumulated during four growth seasons in a hemi-boreal forest was predicted using airborne Land P-band synthetic aperture radar (SAR) backscatter. The radar data were collected in the BioSAR 2007 and BioSAR 2010 campaigns over the Remningstorp test site in southern Sweden. Regression models for biomass change were developed from biomass maps created using airborne LiDAR data and field measurements. To facilitate training and prediction on image pairs acquired at different dates, a backscatter offset correction method for L-band data was developed and evaluated. The correction, based on the HV/VV backscatter ratio, facilitated predictions across image pairs almost identical to those obtained using data from the same image pair for both training and prediction. For P-band, previous positive results using an offset correction based on the HH/VV ratio were validated. The best L-band model achieved a root mean square error (RMSE) of 21 t/ha, and the best P-band model achieved an RMSE of 19 t/ha. Those accuracies are similar to that of the LiDAR-based biomass change of 18 t/ha. The limitation of using LiDARbased data for training was considered. The findings demonstrate potential for improved biomass change predictions from L-band backscatter despite varying environmental conditions and calibration uncertainties. RÉSUMÉ

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 17, 2022

This paper describes the tower-based radar BorealScat, which is being developed for polarimetric,... more This paper describes the tower-based radar BorealScat, which is being developed for polarimetric, tomographic and Doppler measurements at the hemi-boreal forest test site in Remningstorp, Sweden. The facility consists of a 50-m high tower equipped with an antenna array at the top of the tower, a 20-port vector network analyser (VNA), 20 low-loss cables for interconnection, and a calibration loop with a switching network. The first version of BorealScat will perform the full set of measurements in the frequency range 0.4-1.4 GHz, i.e. P-band and L-band. The tower is currently under construction at a forest stand dominated by Norway spruce (Picea abies (L.) Karst.). The mature stand has an above-ground dry biomass of 300 tons/ha. Data collections are planned to commence in autumn 2016.

IEEE Transactions on Geoscience and Remote Sensing, Jun 1, 2005

Multitemporal European Remote Sensing satellites 1 and 2 (ERS-1/2) and the Japanese Earth Resourc... more Multitemporal European Remote Sensing satellites 1 and 2 (ERS-1/2) and the Japanese Earth Resources Satellite 1 (JERS-1) interferometric synthetic aperture radar (InSAR) data from a boreal forest test site in Sweden (stem volumes up to 335 m 3 /ha, equivalent to above-ground dry biomass of 200 tons/ha) are studied in order to estimate stem volume using coherence and backscatter. The changes of JERS-1 backscatter and ERS-1/2 tandem coherence between images are consistent over the area studied, in contrast to ERS-1/2 backscatter. A model-based regression analysis has been performed, and the use of the model for inversion is discussed and compared with other approaches found in the literature. The model parameters are discussed in terms of their relation to wind speed and temperature. Results from the different acquisitions are combined to improve the stem volume estimation. The accuracy in terms of rms error (RMSE) for standwise estimated stem volume is 10 m 3 /ha using ERS-1/2 coherence. Using backscatter and coherence from JERS-1 we obtain an RMSE of 30-35 m 3 /ha. Finally, conditions for accurate retrieval of stem volume using multitemporal InSAR observations are discussed. We conclude that C-and L-band repeat-pass InSAR can provide stem volume estimates in boreal forests with accuracies similar to those of standard in situ measurements. Index Terms-Borel forest, European Remote Sensing satellite (ERS), Japanese Earth Resources Satellite (JERS), interferometric sythetic aperture radar (InSAR), multitemporal. I. INTRODUCTION T HERE IS AN increasing need for forest information related to its importance for the environment and global climate (e.g., monitoring for the Kyoto protocol) as well as forest management aspects. In particular, satellite observations can be useful for environmental studies, since an internationally accepted, consistent, and robust method is required for monitoring on a large scale. The synthetic aperture radars (SARs) on the European Remote Sensing 1 and 2 satellites (ERS-1/2) and the Japanese Earth Resources Satellite 1 (JERS-1) missions have provided not only the possibility for multitemporal acquisitions independent of clouds but also interferometric SAR (InSAR) observations. This study reports an investigation of the use of multitem

Global Change Biology, Jun 1, 2023

When modeling forest variables from InSAR phase height data, phase noise is a nuisance that can b... more When modeling forest variables from InSAR phase height data, phase noise is a nuisance that can be mitigated by spatial averaging. In this empirical study, based on data from a hemi-boreal forest, the relation between field measured forest variables and TanDEM-X phase height and its dependence on the size of the field plots was investigated. Also, the impact of extending the region of phase height extraction beyond the actual plot size was investigated in order to determine the usefulness of this approach when small plot sizes cause significant noise in the estimation of phase height. For fixed field plot sizes (7 m and 10 m radii), the maximum correlation between Lorey's height and phase height occurred for phase height extraction regions multiple times larger in area than the field plots, which were located in homogenous stands.

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 17, 2022

A first evaluation of ALOS-2 PALSAR-2 data for forest stem volume estimation has been performed a... more A first evaluation of ALOS-2 PALSAR-2 data for forest stem volume estimation has been performed at a coniferous dominated test site in southern Sweden. Both the Fine Beam Dual (FBD) polarization and the Quad-polarimetric mode were investigated. Forest plots with stem volume reaching up to a maximum of about 620 m 3 ha-1 (corresponding to 370 tons ha-1) were analyzed by relating backscatter intensity to field data using an exponential model derived from the Water Cloud Model. The estimation accuracy of stem volume at plot level (0.5 ha) was calculated in terms of Root Mean Square Error (RMSE). For the best case investigated an RMSE of 43.1% was obtained using one of the FBD HV-polarized images. The corresponding RMSE for the FBD HH-polarized images was 43.9%. In the Quadpolarimetric mode the lowest RMSE at HV-and HHpolarization was found to be 39.8% and 47.4%, respectively.

Interferometric TanDEM-X data from 2011 and 2014 were used to create biomass maps over the Swedis... more Interferometric TanDEM-X data from 2011 and 2014 were used to create biomass maps over the Swedish test site Remningstorp. These maps were used to compute the biomass change for four classes; pre-commercial thinning, thinning, clear-cutting, and untouched forest. Field inventory and ALS data from the corresponding years were used as reference data. The biomass change was compared on 12 subjectively chosen plots with 40 m radius for each class. It was found, that pre-commercial thinning was difficult to detect, as the biomass loss was less than the biomass growth during the four vegetation seasons investigated. Thinning could be detected from the biomass change being about zero or slightly negative, while clear-cut plots were obvious to notice, with the biomass withdrawal being several hundreds of tons ha-1. The untouched plots had a biomass growth of about 4 to 6 tons ha-1 year-1. It was concluded, that annual TanDEM-X images can be used to detect also smaller silviculture activities such as thinning, but further research with shorter time periods would be desired.

Remote Sensing of Environment, Feb 1, 2021

Agricultural and Forest Meteorology, Aug 1, 2019

Boreal forests exchange large amounts of carbon dioxide (CO 2) with the atmosphere. A managed bor... more Boreal forests exchange large amounts of carbon dioxide (CO 2) with the atmosphere. A managed boreal landscape usually comprises various potential CO 2 sinks and sources across forest stands of varying age classes, clearcut areas, mires, and lakes. Due to this heterogeneity and complexity, large uncertainties exist regarding the net CO 2 balance at the landscape scale. In this study, we present the first estimate of the net CO 2 exchange over a managed boreal landscape (∼68 km 2) in northern Sweden, based on tall tower eddy covariance measurements. Our results suggest that from March 1, 2016 to February 28, 2018, the heterogeneous landscape was a net CO 2 sink with a 2-year mean uptake of −87 ± 6 g C m −2 yr −1. Due to an earlier and warmer spring and sunnier autumn, the landscape was a stronger CO 2 sink during the first year (−122 ± 8 g C m −2) compared to the second year (−52 ± 9 g C m −2). Footprint analysis shows that 87% of the CO 2 flux measurements originated from forests, whereas mires, clear-cuts, lakes, and grassland contributed 11%, 1%, 0.7%, and 0.2%, respectively. Altogether, the CO 2 sink strength of the heterogeneous landscape was up to 38% lower compared to the sink strength of a mature stand surrounding the tower. Overall, this study suggests that the managed boreal landscape acted as a CO 2 sink and advocates tall tower eddy covariance measurements to improve regional carbon budget estimates.

Global Change Biology, Feb 12, 2020

Article type : Primary Research Articles The Net Landscape Carbon Balance-integrating terrestrial... more Article type : Primary Research Articles The Net Landscape Carbon Balance-integrating terrestrial and aquatic carbon fluxes in a managed boreal forest landscape in Sweden

Remote Sensing of Environment, Oct 1, 2015

ABSTRACT This paper presents and assesses spatially explicit estimates of forest growing stock vo... more ABSTRACT This paper presents and assesses spatially explicit estimates of forest growing stock volume (GSV) of the northern hemisphere (north of 10°N) from hyper-temporal observations of Envisat Advanced Synthetic Aperture Radar (ASAR) backscattered intensity using the BIOMASAR algorithm. Approximately 70,000 ASAR images at a pixel size of 0.01° were used to estimate GSV representative for the year 2010. The spatial distribution of the GSV across four ecological zones (polar, boreal, temperate, subtropical) was well captured by the ASAR-based estimates. The uncertainty of the retrieved GSV was smallest in boreal and temperate forest (< 30% for approximately 80% of the forest area) and largest in subtropical forest. ASAR-derived GSV averages at the level of administrative units were mostly in agreement with inventory-derived estimates. Underestimation occurred in regions of very high GSV (> 300 m3/ha) and fragmented forest landscapes. For the major forested countries within the study region, the relative RMSE between ASAR-derived GSV averages at provincial level and corresponding values from National Forest Inventory was between 12% and 45% (average: 29%)

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium, Jul 17, 2022

Agricultural and Forest Meteorology, May 1, 2022

In this paper, the potential of mono-and bistatic HHpolarized UHF-band SAR imagery for mapping of... more In this paper, the potential of mono-and bistatic HHpolarized UHF-band SAR imagery for mapping of a hemiboreal forest is studied. SAR data have been acquired with the two airborne SAR sensors LORA and SETHI during a joint FOI-ONERA campaign conducted in 2010. Three acquisition modes are compared: monostatic, quasimonostatic (difference in elevation angle around 0°) and bistatic (difference in elevation angle around 6°). Images acquired at two perpendicular flight headings are used, i.e. 178° and 268°, to evaluate the influence of topography, which often has an aggravating effect on forest variable estimation. It is observed that for the quasi-monostatic and bistatic acquisitions, the influence of ground topography is lower compared to the monostatic acquisition. A linear regression model is used to explain the dependence of the backscattering coefficient on the logarithm of biomass, and it is observed that the estimated intercept and slope are similar for the two headings only in the case of quasi-monostatic and bistatic acquisitions, of which the latter features the lowest error and the highest coefficient of determination (0.73 and 0.70, respectively, for headings 178° and 268°).

Three-year forest above-ground biomass change were measured using L- and P-band Synthetic Apertur... more Three-year forest above-ground biomass change were measured using L- and P-band Synthetic Aperture Radar (SAR) backscatter. The SAR data were collected in the airborne BioSAR 2007 and BioSAR 2010 campaigns over the hemiboreal Remningstorp test site in southern Sweden. Regression models for biomass were developed using reference biomass maps created using airborne laser scanning data and field measurements. The results from regression analysis show that using HV backscatter (or VH) in a model with above-ground biomass and backscatter change on either natural logarithmic or square root, and decibel scale, respectively, explained most of the variation in the biomass change, both for L- and P-band. In the case of L-band, the two best cases showed R2 values of 66%, when comparing two SAR images acquired 2007 and 2010. For P-band using the same models, the best cases showed R2 values of 62%. In summary, the results look promising using L- and P-band backscattering for mapping biomass change.

Remote Sensing of Environment, Mar 1, 2022

Scandinavian Journal of Forest Research, Feb 8, 2016

ABSTRACT Discrimination of deciduous trees using spectral information from aerial images has only... more ABSTRACT Discrimination of deciduous trees using spectral information from aerial images has only been partly successfully due to the complexity of the reflectance at different view angles, times of acquisition, phenology of the trees and inter-tree radiance. Therefore, the objective was to evaluate the accuracy of estimating the proportion of deciduous stem volume (P) utilizing change detection between canopy height models (CHMs) generated by digital photogrammetry from leaf-on and leaf-off aerial images instead of using spectral information. The study was conducted at a hemi-boreal study area in Sweden. Using aerial images from three seasons, CHMs with a resolution of approximately 0.5 m were generated using semi-global matching. For training plots, metrics describing the change between leaf-on and leaf-off conditions were calculated and used to model the continuous variable P, using the Random Forest approach. Validated at sub-stands, the estimation accuracy of P in terms of root mean square error and bias was found to be 18% and −6%, respectively. The overall classification accuracy, using four equally wide classes, was 83% with a kappa value of 0.68. The validation plots in classes of high proportion of coniferous or deciduous stem volume were well classified, whereas the mixed forest classes showed lower classification accuracies.