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FRINGE '96 Workshop: ERS SAR Interferometry, 30 September - 2 October 1996
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Fringe 96

Interferometry for Forest Studies

Nicolas FLOURY
Thuy LE TOAN
Jean-Claude SOUYRIS
Centre d'Etudes Spatiales de la Biosphère
18 avenue Edouard Belin, bpi 2801
31401 Toulouse Cedex 4, France
floury@cesbio.cnes.fr
Kuldip SINGH
Nicolas STUSSI
Centre for Remote Imaging, Sensing and Processing
National University of Singapore
Lower Kent Ridge Road, Singapore 119260

Chih Chien HSU
Jin Au KONG
Department of Electrical Engineering and Computer Science
Research Laboratory of Electronics
Massachusets Institute of Technology
Cambridge, MA02139, USA


Abstract

This paper presents the use of ERS-1 repeat-pass interferometric data for forest environment studies. The overall objective is to assess the use of interferometric information - degree of coherence and phase difference - for forest / non-forest mapping and for retrieving forest parameters. Interferometric data acquired over a reference test site of temperate forest (Landes, France) and over a tropical forest site (South Sumatra) have been analysed. Coherence is shown to be a good discriminator between forest stands and bare soil surfaces. However, the conditions for optimal use of coherence depend on the forest and environment characteristics. In the specific case of the Landes forest (flat and homogeneous forest stands), phase difference statistics are shown to be linked to forest stands heights. The knowledge of the penetration depth of the wave into the forest canopy, obtained from theoretical modeling, is shown to be necessary to get a good estimate of stands height from interferometric phase difference.

Keywords: Interferometry, Forest, Mapping, Forest Biomass, Forest Height

Introduction

Several studies have shown the potentialities of repeat-pass interferometry for the extraction of DEMs over temporally stable terrains or for the detection of small terrain movements. The interest in interferometry as a tool to study forests is more recent [1]-[2]. The objective of this paper is 1) to analyse the relations between interferometric data and forest parameters over a well known site, 2) to interpret the underlined physical phenomena using a theoretical model, and 3) to discuss on the influence of environmental and temporal conditions on the results.

Test-sites and Datasets

The reference test site is the Landes forest, located in South-Western France. It is the largest plantation forest in France, constituting nearly one million hectares on flat topography. This artificial forest is almost totally formed of maritime pine (pinus pinaster) and is managed in a consistent fashion, which ensures the canopy to be homogeneous.

The ground data consist in a biomass map which provides information about location and age of more than 50 stands of maritime pine, covering about 20 ha each. The age of these stands ranges between 2 and 50 years, while the corresponding biomass is between 5 and 150 tons / ha. Clear cuts and agricultural fields are also present in the area. Other parameters such as tree densities and dendrometric information are also available. Interferometric data consists of 3 interferometric couples based on ERS-1 SLC images acquired in 1991 and processed by the CNES. The characteristics of the interferometric data are summarized in Table1.

An alternative test-site is chosen in a tropical environment, at Selatan, South Sumatra, Indonesia. This site comprises a mix of primary forest, plantations and deforested areas. Concurrent data consists of a SPOT XS image of the area acquired within one month of the ERS images.

Two tandem (ERS-1/ERS-2) and two 35 days (ERS-1 and ERS-2) interferograms are available over the area. Interferometric data has been processed by CRISP.

Interferometric Set Date of acquisition Time interval
(days)
Baseline
given by ESA (m)
Landes A 15 oct 91/ 20 nov 91 35 10
Landes B 20 nov 91 / 02 dec 91 12 142
Landes C 15 oct 91 / 02 dec 91 47 130
Sumatra D 12 apr 96 / 13 apr 96 1 -
Sumatra E 17 may 96 / 18 may 96 1 135
Sumatra F 12 apr 96 / 17 may 96 35 -
Sumatra G 13 apr 96 / 18 may 96 35 -

Table 1 : Characteristics of available interferometric data.

Theoretical modeling

An accurate interpretation of the phase information contained in the interferometric data would need coherent electromagnetic modeling. Until now, the development of coherent models for such natural medium is very limited. Most of the existing models for radar backscatter of forests are based on the Radiative Transfer Theory which cannot be used to interpret the phase information. However, some insights on the dependency of interferometric data to forest parameters can be derived from the these theoretical models. This section summarizes the four-layer Radiative Transfer (RT) model developed at MIT for the modeling of pine forest [7] which is used in this study.

The four layers (Fig. 1) include a crown layer, a trunk layer, an understory layer, and a ground interface. Forest canopy and ground surface characteristics are provided by experimental measurements. The Kirchhoff approximation is used to compute the scattering from the ground modeled as a random rough surface. The trunk is modeled as a tilted circular cylinder, branches and needles are modeled as circular cylinders where finite cylinder approximation is applied. The scattering properties of structured pine trees are taken into account in the model by incorporating the branching model [8] into the phase matrix of the RT equation: the crown is modelled as a 4-scale cluster constituted of trunk, primary branches, secondary branches and needles. The vector radiative transfer equation for the specific intensity in each scattering region is of the form :

where the Stokes vector contains information regarding field intensity and phase relation of the two orthogonal polarisations and is defined as :

In (2), the subscripts h and v represent the horizontal and vertical polarisations, respectively. The bracket < > denotes ensemble averaging over the size and orientation distributions of scatterers and is the free space impedance. The extinction matrix represents the attenuation due to both scattering and absorption, and can be obtained through the optical theorem in terms of forward scattering functions. The phase matrix characterizes the scattering of the Stokes vector from direction into direction. The phase matrix can be formulated in terms of the scattering functions of the randomly distributed discrete scatterers.

Figure 1: Radiative Transfer Approach

Complex Coherence

The complex degree of coherence of the two co-registered complex image values s1 and s2, is given by:

where is the degree of coherence and the phase difference between the two signals.

Degree of Coherence

Landes Test-Site

Fig. 2 presents the variations of the coherence versus stand age for the 3 interferometric sets. High temporal coherence is obtained for clear cuts and open fields whereas it decreases with stand age.

Figure 2: Variations of the degree of coherence with stand age

Fig. 3 shows the result of theoretical modeling, where different scattering mechanisms at C-band, VV and 23° of incidence are presented.

Figure. 3: Decomposition of scattering mechanisms derived from theory described in [7]

For clear-cuts and very young stands, the backscattered signal results mainly from the soil contribution. As vegetation grows, this high contribution from the soil is attenuated by the crown layer, and the backscattering from the crown increases. Consequently, three distinct regions can be defined. For very young stands, the soil contribution is dominant in the total signal (region 1), for older stands (3-12 years in the case of the Landes forest), backscattered signal is a sum of ground and crown contributions (region 2), for larger biomasses (> 12 years), most of the backscattered signal comes from the crown layer contribution (region 3).

In terms of degree of coherence, bare surfaces present a high degree of coherence, if they do not undergo any modification in their characteristics (geometry, dielectric, vegetation regrowth) between the two acquisitions. Volume scatterers such as needles or branches are more sensitive to structure variations due to vegetation growth or wind effect. In the case of repeat-pass interferometry, these scatterers have a high probability to move between acquisitions. Thus the volume scattering from vegetation corresponds to a low degree of coherence. The degree of coherence, as a function of forest age or biomass, can be interpreted using the knowledge of the scattering mechanisms as follows. In the region where the soil contribution is dominant (region 1), the degree of coherence is high. On the other hand, the region where most of the backscatter comes from the volume contribution (region 3) shows a low degree of coherence. In the intermediary region (region 2), the degree of coherence decreases with stands age/biomass, with a slope depending on soil/vegetation parameters.

The overall coherence of sets A and C is shown to be lower than coherence of set B. This could be the result of two effects: (a) a decrease of the degree of coherence as a function of time interval between acquisitions as shown in [4] and (b) a drop of coherence due to the strong precipitation (34 mm) which occured on October 15. Lower coherence of A and C compared to B observed over clear cuts can in addition be explained by changes in the remaining vegetation cover (growth of herbaceous, cleaning of a stand after a cut) or by strong modifications of the roughness state (by harrowing or plough). For long intervals between acquisitions, the degree of coherence obtained over an area can reach the lowest stable values when the time period is sufficient to statistically integrate all possible (non anthropic) temporal changes.

As a consequence, the degree of coherence between two separate acquisitions can be a good discriminator between forests and bare surfaces (or surfaces with low vegetation cover). A comparison with the intensity of the backscattered signal of ERS-1 as forest / non-forest discriminator can be made. At C-band, the intensity of backscattered signal from bare soil surfaces depends on the soil parameters (moisture, roughness). Consequently, bare soil surfaces can present a large range of responses (Fig 4). These possible variations of the soil responses may impede the forest / non-forest discrimination because of the possible confusion between some vegetated and non-vegetated areas. On the contrary, the degree of coherence of a bare surface is in most cases higher than the degree of coherence characterizing forested areas, and this independently of the soil moisture and roughness parameters.

Figure 4: Impact of soil parameters on backscattered intensity

Fig. 5b shows a map of forest / non-forest obtained by thresholding the degree of coherence of A and B interferometric sets (5a for set A). The resulting map is in good agreement with the forest map established from ground data. White areas are ground surfaces which did not change between the two extreme acquisition dates (15 oct / 2 dec). Black areas are forest stands characterized by a low correlation. Areas in grey are fields or stands which correlation state has changed. This could have been caused by plough, harvest (on agricultural fields), growth of herbaceous or cleaning of stands.

Figure 5: Map of (a) coherence of set B
and (b) forest / non-forest areas based on the degree of coherence. Nezer test-site.

Concerning the study of young forest biomass, in the case of the Landes forest, the characteristics of the underlying ground and vegetation do not differ much from one stand to another, thus reducing the dispersion of the degree of coherence. Inversion of the degree of coherence into young forest biomass for monitoring is then possible.

Selatan Test-Site

In the case of the tropical test site, the forest environment is drastically different. The comparison of a tandem and 35 days interval interferogram shows that the latter is useless to discriminate vegetated from non vegetated areas (Fig. 6b-c). In particular, the quick growth of vegetation over former deforested surfaces brings a fast temporal change of target areas. A much shorter time interval is necessary between acquisitions to minimize this effect.

The analysis of the tandem interferogram concurrently to the SPOT image of May 1996 (Fig. 6a) shows that under these environmental conditions, the degree of coherence can be helpful in discriminating heavy vegetated areas (plantations and forests) from sparsely covered surfaces. A more thorough study on the possibilities of discriminating other classes of vegetation (primary forest, different kinds of plantations, deforested areas) using a combination of intensity and interferometric data has been undertaken by CRISP [10].

Figure 6: (a) SPOT image of the test-site.
Comparison of the degree of coherence over the same area for (b) tandem and (c) 35 days interval interferograms.

Previous studies [11] have shown the possibility to discriminate forested from non-forested areas in tropical environment using multi-temporal intensity ratio information. A first qualitative comparison between this technique and the use of the degree of coherence of a tandem interferogram shows similar results (Fig. 7). A quantitative analysis of the two algorithms in terms of classification accuracy and effective final resolution is to be undertaken.

Figure 7 (a) Degree of Coherence ERS-1 / ERS-2 96/04/12 - 96/04/13
(b) Intensity Ratio Image ERS-1 93/12/01 - 94/08/05

Phase Difference

The interferometric phase shift between forest and ground responses is related to the integrated height of the vegetation scatterers. Thus, penetration of the wave into the medium must be taken into account. Consequently, the interferometric estimated height is an " effective height " function of the real height of the trees and of the penetration depth (Fig. 8).

The Landes forest test-site is well suited to the study aimed at retrieving the forest height for the following reasons:
-the stands are large: large number of samples for statistical estimation
-the terrain is flat: no topographic effect
-a validated theoretical model is available and provides theoretical extinction coefficient and penetration depth

Since the phase difference rms decreases with an increase of the degree of coherence, the measurements were extracted from the interferometric set B, which presents the highest overall coherence. The larger baseline of B is also well suited to reducing the rms-height errors [5].

Figure 8: Determination of canopy height from interferometry

The general topography of the test-site is flat (as a rule, the slope is less than 0.5%). In addition, we chose to restrict the study to a small area around a clear cut which was considered as the ground reference level. The mean value of the phase difference is extracted from each stand and the corresponding height difference is computed. This leads to the interferometric measured heights displayed in Fig. 9.

We can observe on Fig. 9 that the variation of the mean value of the phase difference estimated from interferometry is an increasing function of the stand age. However, discrepancies are observed between the estimated and the actual tree heights.

Figure 9: Estimation of tree height from interferometry

Discrepancies exist between estimated and actual heights, as the measured height is not the height of the top of the trees, but the height of scatterers distributed over a thickness equal to the penetration depth, and is smaller than the actual height. One way to correct these estimated stand heights is to use theoretical modeling to compute the penetration depth of the wave into the medium.

For each stand under study, the penetration depth d defined by:

(where P(z) is the transmitted power at a depth z below the top of the crown layer, and where the conventions are those of Fig. 8 ) is estimated using the modified radiative transfer model described above. In the case of the Landes forest, young stands are characterized by a high density of trees and a thin crown layer. As the trees grow older, the crown becomes thicker, but the tree density decreases as a consequence of thinning practice. As a first approach, the tree crown is modeled as homogeneous layers; a young stand will be represented by a thin slab of homogeneous medium, an older stand will be represented by a thicker slab of homogeneous medium with a lower extinction coefficient, as depicted in Fig. 10.

Figure 10: Variations of penetration depth with tree stand age

In the case of the Landes forest, and for ERS configuration, the resulting penetration depth increases with the age of the trees. A corrected estimated height, sum of the interferometric derived height and of the simulated penetration depth is shown to be a good estimate of the actual height of the trees (Fig. 9).

The remaining errors could be reduced (a) by using interferometric pairs with a larger baseline to reduce rms height dependence on rms phase difference, and (b) by enhancing the overal degree of coherence using interferometric pairs with a smaller time interval.

If the different penetration depths are not available, is should be noted that a classification of relative forest heights is still possible using phase difference information alone. For a given forest, the relation between interferometric height from ERS and real height can be derived once and used (as a look up table) to monitor the forest height variations.

Conclusions

This study has underlined the relations between the interferometric degree of coherence and the forest age (or biomass). Coherence has been shown to be efficient to discriminate forest areas from clear-cuts in a temperate forest environment. For a tropical forest environment, good results are also obtained if the time interval between acquisitions is short enough. In a specific case, the use of phase difference has been undertaken to retrieve forest stands heights. Optimal interferometric pairs with a smaller time interval (tandem acquisitions) and a larger baseline should (a) enhance the use of the degree of coherence to discriminate young forest stands and (b) permit a more quantitative use of the phase difference to extract forest height.

However, some important improvements are to be made:
- the behaviour of the degree of coherence in the region where backscattered signal comes from both ground and crown contributions is quantitatively unknown. This may impede the retrieval of young forest biomass when the underlayer varies from stand to stand.
-the computation of the penetration depth requires knowledge of the crown parameters, and is only an estimate of the real integrated penetration of the electromagnetic wave into the crown.

To process further into the study of the relations between interferometric data and forest parameters, theoretical modeling must be improved to account for coherent interactions.

Acknowledgments

The work is carried out under CNES/CESBIO Contract n°833/2/95/CNES/171. The interferometric data have been provided by CNES/QTIS. Nicolas Floury receives a grant from CNES and Alcatel Espace.

References

[1] J.O. Hagberg, L.M.H. Ulander and J. Askne: " Repeat-Pass SAR Interferometry over Forested Terrain ", IEEE TGRS, Vol. 33, No. 2, March 1995, pp 331-340.

[2] U. Wegmüller and C.L. Werner: " SAR Interferometric Signatures of Forest ", IEEE TGRS, Vol. 33, No. 5, September 1995, pp 1153-1161.

[3] J.C. Souyris, T. Le Toan, C.C. Hsu and J.A. Kong: " Inversion of Landes Forest Biomass using SIR-C/XSAR Data: Experiment and Theory ", Proceedings of IGARSS'95, July 95, Vol. 2, pp 1201-1203.

[4] H.A. Zebker and J. Villasenor: " Decorrelation in Interferometric Radar Echoes ", IEEE TGRS, Vol. 30, No. 5, September 1992, pp 950-959.

[5] F.K. Li and R.M. Goldstein: " Studies of Multibaseline Spaceborne Interferometric Synthetic Aperture Radars ", IEEE TGRS, Vol. 28, No. 1, January 1990, pp 88-97.

[6] J.S. Lee, K.W. Hoppel, A. Mango, A.R. Miller: " Intensity and Phase Statistics of Multilook Polarimetric and Interferometric SAR Imagery ", IEEE TGRS, Vol. 32, No. 5, September 1994, pp 1017-1028.

[7] C.C.Hsu, H.C.Han, R.T.Shin, J.A.Kong, A. Beaudoin and T. Le Toan: " Radiative transfer theory for polarimetric remote sensing of pine forest at P band ", IJRS, Vol. 15, No. 14, September 1994, pp 2943-2954.

[8] Yueh, S.H., J.A. Kong, J.K. Jao, R.T. Shin and T. Le Toan, "Branching model for vegetation", IEEE Trans. on Geoscience and Remote Sensing, vol.30, no.2, pp. 390-402, March 1992.

[9] Tsang, L., J.A.Kong, and R. T. Shin, Theory of Microwave Remote Sensing, Wiley-Interscience, New York, 1985.

[10] N.Stussi, L.K.Kwoh, S.C.Liew, K.Singh, H.Lim: " ERS-1/2 Interferometry: Some Results on Tropical Forests ", FRINGE 96, September-October 1996.

[11] T.Le Toan, F.Ribbes, T.Hahn, N.Floury, U.R.Wasrin: " Use of ERS-1 SAR Data for Forest Monitoring in South Sumatra ", Proceedings of IGARSS'96, May 96, Vol.2, pp 842-844.

Keywords: ESA European Space Agency - Agence spatiale europeenne, observation de la terre, earth observation, satellite remote sensing, teledetection, geophysique, altimetrie, radar, chimique atmospherique, geophysics, altimetry, radar, atmospheric chemistry