Forest height estimation using Space-borne PolInSAR dataset over Tropical forests of India

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1 Forest height estimation using Space-borne PolInSAR dataset over Tropical forests of India Unmesh Khati Shashi Kumar Shefali Agrawal Jenia Singh Indian Institute of Remote Sensing, ISRO, Dehradun, India

2 Introduction PolInSAR is a powerful technique for quantitative estimation of forest structure parameters Many studies have been carried out using airborne SAR data This study utilizes C-band Space-borne SAR data for forest height estimation Moist Deciduous forests of India are the target test sites

3 Study Area Thano and Barkot Forest Range, Uttarakhand, India

4 Barkot and Thano Forest Tropical Moist Deciduous Forest Dominant Species: Sal (Shorea robusta) (57%) Teak (Tectona grandis) (31%) Moderately Dense Canopy 40% to 70% canopy cover

5 Data Sets SAR Data Radarsat-2 PolInSAR pair Temporal Baseline: 24 days Normal Baseline: 78.7 m Kz: rad/m Acquisition Pass I Pass II Satellite-Sensor RADARSAT-2 RADARSAT-2 Frequency Band C Band C Band Date of Acquisition 04-Mar Mar

6 Field Data 100 Field Plots of 12.5m x 12.5m Field data collected Average tree height (Havg) Highest tree height (H100) Understory height (Hund) Species Geo-location

7 Complex Coherence As a function of Ground-to-volume scattering ratio in Forested region: HH+VV coherence increases with increased ground contribution HV+VH showed increased coherence with increased volume coherence HH+VV HV+VH HH-VV

8 Forest Height: Coherence Amplitude Inversion HH+VV - Ground scattering HV+VH Volume Scattering

9 Forest Height: Coherence Amplitude Inversion CAI height Mean height RMSE Correlation m 2.77 m 0.34 Field Measured Avera ge Tree Height (H_avg) (m) Coherence Amplitude Inversion Height (m) Best Fit Line 45 Degree Line

10 Coherence Amplitude Inversion Estimated height is insensitive to tree density and type variation. Over-estimates height in non-forest areas such as dry-river bed and urban areas. Lease robust as it ignores phase and considers only amplitude.

11 Forest Height: Three Stage Inversion Height A two layer model for vegetation considered. For the model, the polarization dependent complex coherence is given by:

12 Forest Height: Three Stage Inversion Technique Utilizes the Three Stage Inversion technique developed by Cloude and Papathanassiou. Coherences in different polarizations are plotted on the complex plane. Using Least Squares line fit, the ground topography and vegetation height are estimated. Minimum Height: 18 m Maximum Height: 27 m

13 Forest Height: Three Stage Inversion Technique Field Measured Average Tree Height (H_avg) (m) y = x R² = Three Stage Inversion Height (m) Best Fit Line 45 degree line Forest Height Derived Mean height RMSE Correlation Three Stage Inversion technique m 2.16 m 0.712

14 Under-estimation of Tree Height Multiple stages of growth (6 plots) Leads to independent volume scattering centers Vegetation bias increases Leads to underestimation of forest height Mixed plantations (6 plots) Leads to underestimation of height Dense Understory (4 plots) Dense understory acts as pseudo-ground layer Leads to underestimation of height

15 Three Stage Inversion Technique: Limitations Assumes presence of polarization independent volume coherence Overestimation of height in non-forested areas. Shift in polarization orientation angle due to dense urban clusters. This may lead to increased volume scattering as compared to double-bounce scattering. Algorithm considers RVoG model. Agricultural fields require modeling with OVoG models.

16 Conclusions PolInSAR based forest height is estimated for tropical forests of India Space-borne C-band SAR data can be utilized for PolInSAR studies. Three Stage Inversion technique is more robust and accurate than other techniques for height estimation. Field validation with 100 sample plots carried out for forest height determination

17 Future Work C-band Radarsat-2 data has limited penetration capability, further work using L-band ALOS-2 data is proposed. Bi-static SAR data utilization for forest height and biomass estimation using TanDEM-X data.

18 Thank You

19 Forest height estimation using Space-borne PolInSAR dataset over Tropical forests of India Unmesh Khati Shashi Kumar Shefali Agrawal Jenia Singh Indian Institute of Remote Sensing, ISRO, Dehradun, India

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POLINSAR COHERENCE-BASED REGRESSION ANALYSIS OF FOREST BIOMASS USING RADARSAT-2 DATASETS Jenia Singh, Shashi Kumar, S.P.S Kushwaha Indian Institute of Remote Sensing, ISRO Dehradun, 248001, India (jeniasinghvce@gmail.com,