M. Santoro

Assessment of stand-wise stem volume retrieval in boreal forest from JERS-1 L-band SAR backscatter

JERS‐1 L‐band SAR backscatter from test sites in Sweden, Finland and Siberia has been investigated to determine the accuracy level achievable in the boreal zone for stand‐wise forest stem volume retrieval using a model‐based approach. The extensive ground‐data and SAR imagery datasets available allowed analysis of the backscatter temporal dynamics. In dense forests the backscatter primarily depended on the frozen/unfrozen state of the canopy, showing a ∼4 dB difference. In sparse forests, the backscatter depended primarily on the dielectric properties of the forest floor, showing smaller differences throughout the year. Backscatter modelling as a function of stem volume was carried out by means of a simple L‐band Water Cloud related scattering model. At each test site, the model fitted the measurements used for training irrespective of the weather conditions. Of the three a priori unknown model parameters, the forest transmissivity coefficient was most affected by seasonal conditions and test site specific features (stand structure, forest management, etc.). Several factors determined the coefficients estimate, namely weather conditions at acquisition, structural heterogeneities of the forest stands within a test site, forest management practice and ground data accuracy. Stem volume retrieval was strongly influenced by these factors. It performed best under unfrozen conditions and results were temporally consistent. Multi‐temporal combination of single‐image estimates eliminated outliers and slightly decreased the estimation error. Retrieved and measured stem volumes were in good agreement up to maximum levels in Sweden and Finland. For the intensively managed test site in Sweden a 25% relative rms error was obtained. Higher errors were achieved in the larger and more heterogeneous forest test sites in Siberia. Hence, L‐band backscatter can be considered a good candidate for stand‐wise stem volume retrieval in boreal forest, although the forest site conditions play a fundamental role for the final accuracy. When the article was submitted L. Eriksson was at the Department of Geoinformatics and Remote Sensing, Friedrich‐Schiller University, D‐07743 Jena, Germany.

Model-based biomass estimation of a hemi-boreal forest from multitemporal TanDEM-X acquisitions

Above-ground forest biomass is a significant variable in the terrestrial carbon budget, but is still estimated with relatively large uncertainty. Remote sensing methods can improve the characterization of the spatial distribution and estimation accuracy of biomass; in this respect, it is important to examine the potential offered by new sensors. To assess the contribution of the TanDEM-X mission, eighteen interferometric Synthetic Aperture Radar (SAR) image pairs acquired over the hemi-boreal test site of Remningstorp in Sweden were investigated. Three models were used for interpretation of TanDEM-X signatures and above-ground biomass retrieval: Interferometric Water Cloud Model (IWCM), Random Volume over Ground (RVoG) model, and a simple model based on penetration depth (PD). All use an allometric expression to relate above-ground biomass to forest height measured by TanDEM-X. The retrieval was assessed on 201 forest stands with a minimum size of 1 ha, and ranging from 6 to 267 Mg/ha (mean biomass of 105 Mg/ha) equally divided into a model training dataset and a validation test dataset. Biomass retrieved using the IWCM resulted in a Root Mean Square Error (RMSE) between 17% and 33%, depending on acquisition date and image acquisition geometry (angle of incidence, interferometric baseline, and orbit type). The RMSE in the case of the RVoG and the PD models were slightly higher. A multitemporal estimate of the above-ground biomass using all eighteen acquisitions resulted in an RMSE of 16% with R 2 = 0.93. These results prove the capability of TanDEM-X interferometric data to estimate forest aboveground biomass in the boreal zone.

Multitemporal JERS repeat-pass coherence for growing-stock volume estimation of Siberian forest

Multitemporal radar data from the Japanese Earth Resources Satellite (JERS) satellite from the period 1993 to 1998 have been used to investigate if L-band interferometric coherence with a 44-day temporal baseline is suitable for estimations of growing-stock volume in boreal forest. Two forest regions north of Krasnoyarsk in Siberia have been used as test areas. Seasonal variations in the repeat-pass coherence have been studied, and a comparison with C-band coherence from the European Remote sensing Satellite 1 and 2 (ERS-1/2) tandem missions in 1997 and 1998 has been done. JERS coherence from the winter shows a clear correlation with the forest growing-stock volume. For the summer scenes, the spread in the values is too large to give reliable results. Acquisitions from the spring and fall show large problems with decorrelation caused by temporal changes. The results indicate potential of repeat-pass interferometric L-band coherence in winter, as will be provided by the forthcoming Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR) to map growing-stock volume in Siberia and boreal forests.

Observations, Modeling, and Applications of ERS-ENVISAT Coherence Over Land Surfaces

European Remote Sensing satellite (ERS) ENVISAT coherence is a new repeat-pass interferometric synthetic aperture radar product characterized by a very short repeat-pass interval between acquisitions (28min). In this paper, we investigate the properties of two 28-mins coherence images acquired over the regions of Paris, France, and Prague, Czech Republic, as well as a 35-day coherence image from Prague. Bare soils showed higher coherence compared to forests and urban areas. The range of coherence was larger for 28-min pairs, perpendicular baseline closer to 2km, and stable weather conditions between acquisitions. Coherence modeling shows that because of the long baseline: 1) significant surface decorrelation occurs when slopes are not accounted for in the common-band filtering and for variation of topography in the resolution cell and 2) volume decorrelation is significant. Temporal decorrelation seems to be relevant for vegetation even at the 28-min interval time scale. Observations and modeled coherence were found to be in good agreement. Land cover classification using coherence and backscatter has been tested for the Paris scene for mapping the four major classes. The classification accuracy was 86% when an edge-eroded version of the reference land cover map was used. It decreases to 68% when the full land cover map was used as reference because of local mismatches between the coherence image and the land cover map, and the reduced common band in range. The high coherence difference between forests and bare fields suggests the possibility to use the ERS-ENVISAT coherence for forest/nonforest mapping and estimation of biophysical properties of short vegetation. Coherence, decorrelation, ENVISAT Advanced Synthetic Aperture Radar (ASAR), European Remote Sensing satellite (ERS), land cover, synthetic aperture radar interferometry (InSAR).

Tree height influence on ERS interferometric phase in boreal forest

The European Remote Sensing 1/2 (ERS-1/2) tandem coherence has been shown to provide estimates of stem volume in boreal forest in agreement with in situ data. Tree height estimation from ERS interferometric phase represents a further step in the investigations concerning the retrieval of biophysical parameters using repeat-pass synthetic aperture radar (SAR) interferometry. At two test sites located in Sweden and Finland, sets of respectively nine and eight ERS tandem interferograms were available. Images acquired under stable winter weather conditions and during nighttime were found to be less affected by atmospheric artifacts. Reduction of atmospheric artifacts in interferograms was performed with a phase screen estimated over a dense grid of open areas. Nonetheless, at each test site, only a limited set of pairs was useful for tree height investigations. Under stable winter conditions, the interferometric tree height obtained from an inversion of the differential interferometric phase at stand level was found to be much lower than the true tree height. Spread and uncertainty in the interferometric tree height measurements were caused by phase noise and residual atmospheric artifacts. Using the semiempirical interferometric water cloud model (IWCM), the modeled interferometric tree height was generally in reasonable agreement with the measurements, showing the need of a phase term in interferometric modeling of forests. The inversion of the IWCM for tree height retrieval showed the strong effect of phase noise and atmospheric artifacts on the estimates. Hence, tree height retrieval from ERS repeat-pass SAR interferometry seems to have limited forestry applications. The results also indicate under what conditions the forest influence is small on digital elevation models derived from repeat-pass interferometry.

Nation-Wide Clear-Cut Mapping in Sweden Using ALOS PALSAR Strip Images

Advanced Land Observing Satellite (ALOS) Phased Array L-band type Synthetic Aperture Radar (PALSAR) backscatter images with 50 m pixel size (strip images) at HV-polarization were used to map clear-cuts at a regional and national level in Sweden. For a set of 31 clear-cuts, on average 59.9% of the pixels within each clear-cut were correctly detected. When compared with a one-pixel edge-eroded version of the reference dataset, the accuracy increased to 88.9%. With respect to statistics from the Swedish Forest Agency, county-wise clear-felled areas were underestimated by the ALOS PALSAR dataset (between 25% and 60%) due to the coarse resolution. When compared with statistics from the Swedish National Forest Inventory, the discrepancies were larger, partly due to the estimation errors from the plot-wise forest inventory data. In Sweden, for the time frame of 2008–2010, the total area felled was estimated to be 140,618 ha, 172,532 ha and 194,586 ha using data from ALOS PALSAR, the Swedish Forest Agency and the Swedish National Forest Inventory, respectively. ALOS PALSAR strip images at HV-polarization appear suitable for detection of clear-felled areas at a national level; nonetheless, the pixel size of 50 m is a limiting factor for accurate delineation of clear-felled areas.

The SIBERIA and SIBERIA-II projects: an overview

The international EU-funded SIBERIA project (1998-2000) aimed at the production of an extensive forest map using spaceborne SAR data acquired by the ERS and JERS satellites. For a large geographical region (900.000 km2) located in the Central Siberian Plateau, one-day ERS coherence and JERS backscatter were used to retrieve growing stock volume. A classification algorithm based on peaks in the coherence and backscatter histograms was used. Four volume classes, water and open land were considered. An independent test in 10 areas showed an accuracy above 80%. The produced forest map serves as a tool for the sustainable management of Siberian natural resources and for a better understanding of the role of boreal forests in climate change. The objective of the international EU-funded SIBERIA-II project (2002-2005) is to demonstrate the viability of full carbon accounting, including all greenhouse gasses, with a multi-sensor approach over a 2 million-km2 area in Siberia. Having recently started, a general overview of the aims and the objectives of the project is given. Using several satellite observations available and the SIBERIA database, the first step consists in the generation of several Earth Observation (EO) products (such as biomass, phenological parameters, soil moisture, snow cover etc). Together with land-cover information from local institutions, these products will be input to two dynamic vegetation models for full regional carbon accounting. To increase knowledge, additional products such as Afforestation-Reforestation-Deforestation and fire scars maps are planned.

Seasonal dynamics and stem volume retrieval in boreal forests using JERS-1 backscatter

The paper analyses seasonal effects on L-band backscatter in boreal forests and the implications for stem volume retrieval (JERS-1 mission). As test sites, the estate of Kattbole, Sweden, and two compartments in Bolshe-Murtinsky, Siberia, were considered. The in-situ measured stem volumes ranged from 5 to 350 m3/ha in Kattbole and to 400 m3/ha in Bolshe-Murtinsky, at stand level. For each site nine SAR images were available. Forest backscatter strongly depended on seasonal conditions. With respect to other seasons, in frozen conditions the dynamic range was smaller and the forest backscatter at least 3 dB lower. When precipitation occurred, the backscatter showed saturation. In Kattbole, no saturation was found in images acquired at dry/unfrozen conditions. By means of a semi-empirical model, a regression between stem volume and backscatter was performed. Stem volume was then retrieved for an independent set of backscatter measurements. Images acquired at dry/unfrozen conditions showed a relative RMS error of around 30 % for the images acquired over Kattbole. At both sites the retrieval error was higher for other weather conditions, around 50%. When dry/unfrozen conditions occurred, multi-temporal combination of stem volume estimates showed the smallest error (22%). Hence, for boreal forest monitoring L-band images acquired at dry/unfrozen conditions should be used.

ScanSAR Interferometry for Land Use Applications and Terrain Deformation

ScanSAR interferometry is an attractive technology thanks to its wide swath imaging capabilities. It allows efficient interferometric mapping for various applications such as deformation or landuse monitoring. The motivation for this work is the availability of the new Envisat ASAR Wide Swath Mode Single Look Complex Product (WSS) produced by ESA. Furthermore, other sensors as Radarsat, Radarsat 2, and ALOS PALSAR can be operated in ScanSAR mode resulting in an increased relevance of repeat-pass ScanSAR interferometry and related applications. With the launch of the new Envisat product, a large archive of historical wide swath Envisat ASAR data is now available for ScanSAR interferometry. First applications include deformation mapping, topographic mapping, large-scale athmosphere monitoring, and landuse mapping. Keywords-Scansar interferometry, SAR, Interferometry, land use

Use of ENVISAT ASAR wide-swath mode data over Siberia for large area land cover mapping, parameter retrieval, and change detection

Multi-temporal, multi-incidence ASAR WSM data over Siberia were used to derive land cover information. In an initial step several hundred ASAR WSM scenes were integrated into a database. Then the backscattering characteristics (signatures) of different land cover types were investigated. Based on the results, methodologies to retrieve land cover classes, including different forest biomass classes, were developed and applied. Parameters considered include a temporal backscattering variability parameter and an incidence angle dependence parameter.