Johan E. S. Fransson

Multitemporal repeat-pass SAR interferometry of boreal forests

Multitemporal interferometric European Remote Sensing 1 and 2 satellite tandem pairs from a forest test site in Finland are examined in order to determine the stem volume retrieval accuracy. A form of multitemporal filtering is introduced to investigate what forest stands show a multitemporal consistency in coherence. It is found that a large stand size is a major factor to obtain accurate retrievals. The effect of heterogeneity of forest stands is also discussed. Based on the stands showing highest multitemporal consistency different models for scattering and coherence are compared. The interferometric water cloud model is chosen for stem volume retrieval. The variation of the model parameters with meteorological parameters is investigated and the results illustrate that the best imaging conditions are obtained for subzero temperatures and windy conditions. It is shown that for the 20 stands showing highest multitemporal consistency the stem volume can be retrieved with a relative error of 21%, deteriorating when the number of testing stands is increased, e.g., for 80 stands the error is 48%. For 37 large forest stands representing 48% of the investigated area the relative stem volume error is 26%. With experience from another site in Sweden we may conclude that the error level for a multitemporal interferometric synthetic aperture radar evaluation of stem volume for large forest stands (>2 ha) in a well managed and homogeneous boreal forest may be expected to be in the 15% to 25% range, deteriorating for small and heterogeneous stands and for images acquired under nonwinter conditions.

Forest variable estimation using photogrammetric matching of digital aerial images in combination with a high-resolution DEM

Abstract The rapid development in aerial digital cameras in combination with the increased availability of high-resolution Digital Elevation Models (DEMs) provides a renaissance for photogrammetry in forest management planning. Tree height, stem volume, and basal area were estimated for forest stands using canopy height, density, and texture metrics derived from photogrammetric matching of digital aerial images and a high-resolution DEM. The study was conducted at a coniferous hemi-boreal site in southern Sweden. Three different data-sets of digital aerial images were used to test the effects of flight altitude and stereo overlap on an area-based estimation of forest variables. Metrics were calculated for 344 field plots (10 m radius) from point cloud data and used in regression analysis. Stand level accuracy was evaluated using leave-one-out cross validation of 24 stands. For these stands the tree height ranged from 4.8 to 26.9 m (17.8 m mean), stem volume 13.3 to 455 m3 ha−1 (250 m3 ha−1 mean), and basal area from 4.1 to 42.9 m2 ha−1 (27.1 m2 ha−1 mean) with mean stand size of 2.8 ha. The results showed small differences in estimation accuracy of forest variables between the data-sets. The data-set of digital aerial images corresponding to the standard acquisition of the Swedish National Land Survey (Lantmäteriet), showed Root Mean Square Errors (in percent of the surveyed stand mean) of 8.8% for tree height, 13.1% for stem volume and 14.9% for basal area. The results imply that photogrammetric matching of digital aerial images has significant potential for operational use in forestry.

Stem volume retrieval in boreal forests from ERS-1/2 interferometry

C-band repeat-pass interferometry, in particular, the coherence, has been shown to be of great potential for stem volume retrieval. For boreal forests, we have investigated a stem volume retrieval method based on inversion of ERS-1/2 coherence measurements by means of a semiempirical model. A multitemporal combination of several stem volume estimates has been used in order to reduce errors in the estimation. The retrieval procedure was first applied in a forest estate located in Kattbole, Sweden, where accurate in situ measurements were taken. Stem volume was determined both at the stand level (between 2 and 14 ha) and at the pixel level (25 � 25 m). A multitemporal combination of coherence data acquired in stable winter-type conditions gave the most accurate results. Based on the results obtained in Kattbole, the retrieval procedure was extended to a large area of 4235 km 2 around Kattbole. Retrieval was performed in all forested areas on a pixel basis (25 � 25 m), generating stem volume maps. In Kattbole, at the stand level, stem volume up to 350 m 3 /ha was estimated with an error comparable to the ground truth, i.e. 10 m 3 /ha. At the pixel level, the error reached the value of 55 and 71 m 3 /ha in the forest estate and in the large area, respectively. Compared to the results from the stand analysis, the higher error is believed to be mainly due to the higher uncertainty of coherence estimation at high stem volume and to geometric mismatch between field data and coherence data. Moreover, over large areas, spatial variation of the parameters in the model should be considered. D 2002 Elsevier Science Inc. All rights reserved.

Estimation of forest parameters using CARABAS-II VHF SAR data

The use of airborne CARABASII VHF (20-90 MHz) SAR data for retrieval of forest parameters has been investigated. The investigation was performed at a test site located in the southwest of Sweden consisting mainly of Norway spruce forests. Regression models predicting forest parameters from radar backscattering amplitude were developed and evaluated. The results showed a linear relationship between backscattering amplitude and forest stem volume, stem diameter, and tree height. The analysis also showed that the radar signal is strongly affected by ground slope conditions. The root mean square errors from the regression analysis, restricted to forest stands on near-horizontal ground, were found to be 66 m/sup 3/ ha/sup -1/, 3.2 cm, and 2.3 m for stem volume, stem diameter, and tree height respectively. No saturation of the backscattered signal was observed up to the maximum stem volume of 625 m/sup 3/ ha/sup -1/, corresponding to a biomass of 375 tons ha/sup -1/. The results imply that VHF SAR data have significant potential for operational use in forestry.

Assessing Performance of L- and P-Band Polarimetric Interferometric SAR Data in Estimating Boreal Forest Above-Ground Biomass

Biomass estimation performance using polarimetric interferometric synthetic aperture radar (PolInSAR) data is evaluated at L- and P-band frequencies over boreal forest. PolInSAR data are decomposed into ground and volume contributions, retrieving vertical forest structure and polarimetric layer characteristics. The sensitivity of biomass to the obtained parameters is analyzed, and a set of these parameters is used for biomass estimation, evaluating one parametric and two non-parametric methodologies: multiple linear regression, support vector machine, and random forest. The methodology is applied to airborne SAR data over the Krycklan Catchment, a boreal forest test site in northern Sweden. The average forest biomass is 94 tons/ha and goes up to 183 tons/ha at forest stand level (317 tons/ha at plot level). The results indicate that the intensity at HH-VV is more sensitive to biomass than any other polarization at L-band. At P-band, polarimetric scattering mechanism type indicators are the most correlated with biomass. The combination of polarimetric indicators and estimated structure information, which consists of forest height and ground-volume ratio, improved the root mean square error (rmse) of biomass estimation by 17%-25% at L-band and 5%-27% at P-band, depending on the used parameter set. Together with additional ground and volume polarimetric characteristics, the rmse was improved up to 27% at L-band and 43% at P-band. The cross-validated biomass rmse was reduced to 20 tons/ha in the best case. Non-parametric estimation methods did not improve the cross-validated rmse of biomass estimation, but could provide a more realistic distribution of biomass values.

Retrieval of forest stem volume using VHF SAR

The ability to retrieve forest stem volume using CARABAS (coherent all radio band sensing) SAR images (28-60 MHz) has been investigated. The test site is a deciduous mixed forest on the island of Oland in southern Sweden. The images have been radiometrically calibrated using an array of horizontal dipoles. The images exhibit a clear discrimination between the forest and open fields. The results show that the dynamic range of the backscattering coefficient among the forest stands is higher than what has been found with conventional SAR using microwave frequencies. The backscatter increases with increasing radar frequency. This work shows an advantage compared to higher frequencies for stem volume estimation in dense forests.

Detection of storm-damaged forested areas using airborne CARABAS-II VHF SAR image data

Strong winds cause severe damage worldwide to forested land every year. The devastating storms that struck large parts of Europe in late 1999 destroyed the equivalent of several years of normal forest harvesting, amounting to very large economical sums. Therefore, rapid mapping of damaged areas is of major importance for assessment of short-term actions as well as for long-term reforestation purposes. In this paper, the use of airborne CARABAS-II very high frequency (VHF) (20-90 MHz) synthetic aperture radar (SAR) imagery for high spatial resolution mapping of wind-thrown forests has been investigated and evaluated. The investigation was performed at a test site located in southern Sweden and dominated by Norway spruce forests. A regression model estimating radar backscattering amplitude prior to the storm was developed. The estimated amplitudes were compared to measured amplitudes after the storm. The results clearly show that the backscattering amplitude, at a given stem volume, is considerably higher for wind-thrown forests than for unaffected forests. Furthermore, the backscattering from fully harvested storm-damaged areas was, as expected, significantly lower than from unaffected stands. These findings imply that VHF SAR imagery has potential for mapping wind-thrown forests. However, to prevent ambiguities in increased backscattering caused by normal stem volume growth or wind-fellings, multitemporal change detection techniques using VHF SAR images acquired prior to and after wind-fellings would be preferable.

Combining airborne CARABAS-II VHF SAR data and optical SPOT-4 satellite data for estimation of forest stem volume

The accuracy of forest stem volume estimation at stand level is investigated using a combination of airborne radar and optical satellite data. The hypothesis is that the accuracy will be improved for the combined stem volume estimates compared with that using single sensor data. The test site is located in the south of Sweden and consists mainly of coniferous forest. The stem volume for the selected stands was in the range of 15–585 m3·ha–1, with an average stem volume of 266 m3·ha–1 and an average size of 3.5 ha. Remotely sensed data have been collected with the airborne CARABAS-II very high frequency (VHF) synthetic aperture radar (SAR) sensor and the multispectral optical SPOT-4 satellite sensor. Regression analysis has been used to develop stem volume functions for each sensor and for the combination. The accuracy in terms of root mean square error (RMSE) was 49 m3·ha–1 (corresponding to a relative error of 18.5% of the average stem volume) for CARABAS-II, 63 m3·ha–1 (23.5%) for SPOT-4, and 42 m3·ha–1 (15.8%) for the combination. Thus, the improvement was 15% using only CARABAS-II data and 33% using only SPOT-4 data over the full range of stem volumes investigated. CARABAS-II gave the best results for high stem volumes, and SPOT-4 was more accurate for lower stem volumes, hence the combination of the two techniques provided significantly better results over the whole range of stem volumes. The results imply that the combination of low-frequency radar data and multispectral optical satellite data can be used for standwise stem volume estimation in forestry applications.

Estimates of Forest Growing Stock Volume for Sweden, Central Siberia, and Québec Using Envisat Advanced Synthetic Aperture Radar Backscatter Data

A study was undertaken to assess Envisat Advanced Synthetic Aperture Radar (ASAR) ScanSAR data for quantifying forest growing stock volume (GSV) across three boreal regions with varying forest types, composition, and structure (Sweden, Central Siberia, and Quebec). Estimates of GSV were obtained using hyper-temporal observations of the radar backscatter acquired by Envisat ASAR with the BIOMASAR algorithm. In total, 5.3×106 km2 were mapped with a 0.01 degrees pixel size to obtain estimates representative for the year of 2005. Comparing the SAR-based estimates to spatially explicit datasets of GSV, generated from forest field inventory and/or Earth Observation data, revealed similar spatial distributions of GSV. Nonetheless, the weak sensitivity of C-band backscatter to forest structural parameters introduced significant uncertainty to the estimated GSV at full resolution. Further discrepancies were observed in the case of different scales of the ASAR and the reference GSV and in areas of fragmented landscapes. Aggregation to 0.1 degrees and 0.5 degrees was then undertaken to generate coarse scale estimates of GSV. The agreement between ASAR and the reference GSV datasets improved; the relative difference at 0.5 degrees was consistently within a magnitude of 20-30%. The results indicate an improvement of the characterization of forest GSV in the boreal zone with respect to currently available information.

Detection of forest changes using ALOS PALSAR satellite images

A controlled experiment has been performed to quantify the ability to detect clear-cuts using ALOS PALSAR data. The experiment consisted of 8 old spruce dominated stands, each with a size of about 1.5 ha, located at a test site in southern Sweden. Four of the stands were clear-felled and the remaining stands were left untreated for reference. A time series of PALSAR images was acquired prior to, during, and after treatment, including 7 fine beam single polarization (FBS, look angle 34.3deg, HH-polarization) SAR images. The results clearly show that the clear-felled stands could be separated from the reference stands. The drop in backscattering coefficient between the reference and the clear-felled stands was on average 2.1 dB. This implies that ALOS PALSAR data potentially can be used for large-scale mapping of changes in forest cover.