Large Area Mapping of Forest and Land Cover from ALOS/PALSAR data. Wayne Walker, Josef Kellndorfer, Alessandro Baccini, Scott Goetz, & Nadine Laporte

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1 Large Area Mapping of Forest and Land Cover from ALOS/PALSAR data Wayne Walker, Josef Kellndorfer, Alessandro Baccini, Scott Goetz, & Nadine Laporte Ruhengeri Rwanda June 21-24, 2011

2 The Woods Hole Research Center Science, Education, and Public Policy for a Habitable Earth The Woods Hole Research Center seeks to conserve and sustain the planet s forests, soils, water, and climate by demonstrating their value to human health and economic prosperity. Approximately 60 staff members, including scientists, policy experts, research and administrative staff. Funding is provided through government grants, foundation and corporate support, and individual donors.

3 The Woods Hole Research Center Science, Education, and Public Policy for a Habitable Earth The Center has initiatives in the Amazon, the Arctic, Africa, Russia, Asia, Boreal North America, and throughout the United States. Center programs focus on the global carbon cycle, forest function, land cover/land use, and water and chemical cycles in the environment. We work in collaboration with partners ranging from local NGOs and research centers to national governments and the United Nations.

4 Woods Hole Pan-tropical Mapping Project I. Pan-tropical Mapping 2007 Forest cover (15 m) 2007 Above-ground biomass (500 m) ll. Capacity Building/Training Pan-tropical forest scholars program Technical workshops on forest measurement/monitoring

5 Woods Hole Pan-tropical Mapping Project I. Pan-tropical Mapping 2007 Forest cover (15 m)

6 Pan-tropical forest cover mapping Product highlights: Based on cloud-free RADAR data Consistent across space and time Unprecedented spatial resolution (15 m) National maps to be available online for all countries

7 RADAR: Contributions to tropical forest monitoring Cloud, dust, haze, and smoke penetration All-weather and day/night image acquisition Sensitivity to 3-D forest structure RADAR has the potential to provide for wall-to-wall tropical forest monitoring over very narrow (sub-annual) time frames.

8 RADAR: Contributions to tropical forest monitoring Advanced Land Observing Satellite/Phased-Array L-band SAR Launched on January 24, 2006 by JAXA First polarimetric L-band sensor on a free-flying satellite High spatial resolution (10-20 meters) High geolocation accuracy (9.3 meters) First-of-its-kind systematic global land observation strategy Ceased operation on April 22, 2011 after 5+ years of service Annual coverage of all major forest biomes

9 ALOS/PALSAR: Global observation strategy HH/HV HH Polarimetric

10 ALOS/PALSAR: Assembling a pan-tropical mosaic

11 ALOS/PALSAR: Assembling a pan-tropical mosaic Locations of 17,000 dual-polarimetric ALOS/PALSAR scenes to be used for forest cover mapping

12 ALOS/PALSAR: State-of-the-art processing stream

13 ALOS/PALSAR: 2007 pan-tropical mosaic Image Data By JAXA/METI

14 ALOS/PALSAR: Africa example 5754 Dual-Polarimetric Scenes 76% from Jun-Aug % from Jun-Oct 2007

15 Forest cover mapping: Pan-tropical results

16 Mexico: ALOS/PALSAR coverage with 950 scenes 16

17 Mexico: ALOS/PALSAR mosaic

18 Mexico: National forest inventory data Linking imagery with field observations

19 Mexico: Forest/Non-Forest map Cloud-free forest/non-forest map 19

20 Objectives: Forest and land cover pilot research Evaluate the suitability of ALOS/PALSAR data for the production of high-resolution ( 30 m) wall-to-wall maps of tropical land cover with an emphasis on forest-cover (i.e., forest/non-forest) mapping at regional to continental scales. The specific objectives were to classify land cover: 1.At five different levels of class aggregation (15, 10, 7, 6, and 2 classes) 2.Using two different predictor-variable subsets (spectral and spectral/ancillary) 3.For both PALSAR- and Landsat-based data sets resulting in 20 different classifications

21 Study area: Xingu River Headwaters region 387,000-km 2 (~15 times larger than Rwanda) More dense humid forest (ca. 221,000 km 2 ) than 90% of tropical nations An exceptional landscape for exploring policy scenarios/technological options to inform the design of REDD+ mechanisms.

22 Image data 2007 ALOS/PALSAR mosaic consisting of 116 Level 1.1 (single-look complex) fine beam, dual-polarimetric scenes acquired 8-June to 22-July (RGB = HH,HV,HH-HV) 2007 Landsat 5 mosaic consisting of 12 Level 1G scenes acquired 16-June to 17- August (RGB = Bands 5,4,3)

23 Image segmentation PALSAR segmentation image-object attributes (predictor variables) computed. Landsat segmentation image-object attributes computed.

24 Predictor variable subsets Spectral and ancillary spatial/topographic predictor variables used in the PALSARand Landsat-derived classifications.

25 Land cover reference data set Locations of 535 ground (26-June to 23-August 2006) and 361 supplemental reference (2007) points used in the calibration and cross-validation of both the PALSAR- and Landsat-based classifications. Point locations are superimposed on a PALSAR-based map forest cover.

26 Land cover classification scheme Hierarchical, multi-level land cover classification scheme developed for the Xingu River headwaters region.

27 Results: Classification accuracy comparison A comparison of ALOS/PALSAR- and Landsat-derived overall classification accuracies for the five levels of class aggregation (15, 10, 7, 6, and 2 classes).

28 Results: Mapping of forest cover Walker et al Large-area classification and mapping of forest and land cover in the Brazilian Amazon: A comparative analysis of ALOS/PALSAR and Landsat data sources. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing.

29 Results: Spatial map comparison Spatial similarity (%) based on a two-way fuzzy comparison procedure between PALSAR, Landsat, and PRODES map products. Analysis conducted within the region of PALSAR/Landsat acquisition overlap. Analysis conducted within the region of PALSAR/Landsat acquisition overlap following PRODES-based masking. Walker et al Large-area classification and mapping of forest and land cover in the Brazilian Amazon: A comparative analysis of ALOS/PALSAR and Landsat data sources. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing.

30 Conclusions ALOS/PALSAR represents a consistent and accurate source for estimates of forest cover across large areas with accuracies nearly equaling those produced by Landsat, the most widely used monitoring sensor, and PRODES, the most highly regarded national monitoring system. The potential exists for PALSAR imagery to be used either by itself as the primary data source or to potentially fill voids in optical acquisitions associated with the presence of haze, smoke or clouds.

31 Future work Conduct case studies in regions like Central and East Africa where forest disturbance occurs at a much finer scale ( 1 hectare). Complete 2007 baseline map of pan-tropical forest cover. Following recent JAXA release of the 2010 m PALSAR mosaic, begin work on a threeyear ( ) pan-tropical map of forest change. Investigate possible fusion of PALSAR data with MODIS, GLAS LiDAR, and field observations as part of our ongoing pan-tropical forest cover and carbon stock mapping effort. Partner with countries to build capacity and assist in developing MRV strategies.

32 Future work Deforestation Monitoring Fire Degradation Monitoring

33 Future work m PALSAR Mosaic JAXA, METI Analyzed by WHRC m PALSAR Mosaic

34 Thank you!

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