Global forest observation using the L-band SARs on ALOS and ALOS-2. Masanobu Shimada, Rajesh Thapa, Manabu Watanabe, and Takeshi Motooka JAXA, EORC

Transcription

1 Global forest observation using the L-band SARs on ALOS and ALOS-2 Masanobu Shimada, Rajesh Thapa, Manabu Watanabe, and Takeshi Motooka JAXA, EORC

2 Contents Summary from the PALSAR Land Use Land Cover FNF Biomass Estimation(gamma, LUC, texture) Global PALSAR datasets BOS ALOS-2 and current status Conclusion

3 Deforestation process from L-band SAR 2009 年 (ALOS/PALSAR) 1996 年 (JERS-1/SAR) 13 年

4 Land Use Classification in Riau, Sumatra( 土 地 利 用 分 類 ) 200km WWF 10 classes PALSAR 10 classes Natural forest Natural mangrove forest Natural re-growth Acacia Oil Palm Rubber Coconut Open area Other Water Forest(exclude Mangrove)/Non-forest Accuracy: 90.22% PALSAR 10 classes: % Indonesia, Riau, Sumatra

5 Biomass estimation from g 0 HV (latest) Riau Province of Indonesia, 2012 Method Natural forest only Biomass data Obtaion from (LiDAR)-(field plot) PALSAR data 2007, 2008, 2009, 2010 年 AG-biomass (tons/ha) Std. Dev. 1 / RMS error 2 (tons/ha) Simple Average Use AG-biomass - g 0 total < 100 tons/ha >100 tons/ha Std. Dev. (%) Good accuracy, if AG-biomass - g 0 is available

6 Use classification Biomass map Use g 0 HV (AG-biomass) relation Total : 3.06 G tons Error: 99.1 tons/ha Mask Total : 3.23 Gt Error: 13.6 tons/ha (< 100 t/ha) 63.1 tons/ha (>100 t/ha)

7 Orthophoto visualizing the forest landscape corresponding to the AFCS map using the general LiDAR to AFCS Model for each land use type. Source: Thapa, R. B., Watanabe, M., Motohka, T., Shiraishi, T., Shimada, M. (2014), Calibration of aboveground forest carbon stock models for major tropical forests in central Sumatra using airborne LiDAR and field measurement data. Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

8 PALSAR mosaic data in the left, Land use map in the center, and AFCS pattern using texture Model in the right. 10m PALSAR Mosaic data 2009 and RMSE: Mg C ha 1 Thapa, R. B., Watanabe, M., Motohka, T., and Shimada, M. (2015, in press), Potential of high-resolution PALSAR mosaic texture for aboveground forest carbon tracking in tropical region, Remote Sensing of Environment.

9 AFCS map of Riau Province RMSE: Mg C ha 1 25m PALSAR Mosaic data 2009 and 2010 Thapa, R. B., Motohka, T., Watanabe, M., and Shimada, M. (in review). High-resolution forest carbon baseline map and future perspective of stocks in Central Sumatra, Indonesia, Remote Sensing.

10 Environment Global Forest Monitoring Global 25 m mosaic (Ortho+slope correction) Global 25m Forest/non-forest map

11 PALSAR data: global 25m resolution mosaic ( )-ortho and slope corrected - were completed. Can be used as GIS data: geometric accuracy is better than 10m

12 1. FNF map generation FNF classification results( )

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14 Global Mangrove distribution from PALSAR2010

15 3.3 Accuracy Assessment (1/3) PALSAR vs. FRA vs. Landsat x1000ha Region Landsat(2000) PALSAR(2007 ) FRA(2005) Africa Asia Eurasia N/C America Oceania S America Total Diff Hansen et al (2013), Science FAO This results Masanobu Shimada, Takuya Itoh, Takeshi Motooka, Manabu Watanabe, Shiraishi Tomohiro, Rajesh Thapa, and Richard Lucas, New Global Forest/Non-forest Maps from ALOS PALSAR Data ( ), Remote Sensing of Environment, accepted April 4, 2014, DOI= /j.rse

16 JAXA s Forest Observation Plan Using ALOS/ALOS-2(JERS-1) Rely on the L-band sensitivity to the forest at amplitude, high resolution texture, and InSAR on detecting the Forest cover, change, and biomass. Conduct the Forest observation using 10m Dual + ScanSAR Dual, mainly, and polarimetry and higher resolution. Operate the Basic Observation Scenario effectively. Create some global datasets and open to the public.

17 25 m Data set Size(/year):~3T(compressed), ~11T(uncompressed) HH, HV, HH/HV: amplitude, ortho and terrain corrected Mask(normal, ocean, shadowing, layover) Local Incidence angle Date from the launch SRTM 90m DEM (PALSAR) and 30m for PALSAR-2

18 ALOS PALSAR 25 m global mosaic data Open release Product specifications and ancillary data

19 ALOS PALSAR 100 m global mosaic data Open release Product specifications and ancillary data

20 ALOS PALSAR 25 m global mosaic data Open release In addition, JAXA are making available also their global forest/non-forest (FNF) classification "version 1" from JAXA has evaluated the classification maps using three different data sets (GE, DCP and FRA), and obtained 90%, 87% and 95% correspondence.

21 ALOS PALSAR 25 m global mosaic data Open release

22 PALSAR 50 m global mosaic data

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24 Bulk download of data over 5 x 5 region (25 tiles 1 x1 each) OR click on a tile on the grid to download the individual 1 tile

25 ALOS PALSAR 25m global mosaic data Open release Backscatter (HH) Radar backscatter, normalised for incidence angle ( g o = s o /cosq i ) Radiometric and geometric corr for topography GEOTIF header information 16 bits (UINT)

26 ALOS PALSAR 25m global mosaic data Open release Backscatter (HV) Radar backscatter normalised for incidence angle ( g o = s o /cosq i ) Radiometric and geometric corr for topography 16 bits (UINT)

27 ALOS PALSAR 25m global mosaic data Open release Backscatter false-colour composite R: HH G: HV B: HH/HV

28 ALOS PALSAR 25m global mosaic data Open release DN=917 29/07/2008 DN=854 27/05/2008 DN=975 25/09/2008 Observation date Data layer showing the acquisition date for each pixel in the image: Date = 24/1/ DN 16 bits (UINT)

29 ALOS PALSAR 25m global mosaic data Open release Incidence angle Layer with local incidence angle for each pixel 16 bits (UINT)

30 ALOS PALSAR 25m global mosaic data Open release Mask data Layer showing ocean and nodata areas: layover, shadow. 8 bits

31 ALOS PALSAR 25m global mosaic data Open release Forest/Non-Forest JAXA global classification (version 0) 8 bits

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35 ALOS-2 Schedule ALOS-2 is in good condition and the everything is on-going. May launched and PALSAR-2 antenna deployed. June PALSAR-2 first images were acquired. June 27 PALSAR-2 first images were released. Aug. 4 Initial Calibration started Aug. 20 Move to the operational observation phase Nov. 25 starts the product distribution

36 ALOS-2 satellite ALOS-2 in-orbit configuration Specification Y Z X Data relay antenna L-band SAR (PALSAR-2) Stripmap: 3 to 10m res., 50 to 70 km swath ScanSAR: 100m res., 350km/490km swath Spotlight: 1 3m res., 25km swath Solar Arrays Orbit Sun-synchronous orbit Altitude: 628km Local sun time : 12:00 +/- 15min Revisit: 14days Orbit control: +/-500m Life time 5 years (target: 7 years) L-band SAR antenna X-band downlink antenna Launch Downlink May 24, 2014, H-IIA launch vehicle X-band: 800Mbps(16QAM) 400/200Mbps(QPSK) Ka-band: 278Mbps (Data Relay) Experimental Compact InfraRed Camera (CIRC) SPace based Automatic Identification System Experiment(SPAISE2) 38

37 25m PALSAR-2 mosaic and the forest/non-forest data(fnf map generation) HH HV 25m PALSAR-2 Forest/Non-forest map(fnf) 25m PALSAR-2モザイクから 森 林 非 森 林 の 分 類 により, 森 林 伐 採 の 状 況 把 握 が 可 能 (9 path images including the south America s forest/non-forest regions 39

38 25m PALSAR-2 モザイクによる 森 林 非 森 林 (FNF: change detection of the forest area) 森 林 非 森 林 増 加 減 少 2014 (PALSAR-2 FNF) Change detection of the FNF2010 and FNF (PALSAR FNF) 2010 年 から2014 年 の 森 林 面 積 変 化 が 把 握 可 能 PALSARに 比 べて 分 解 能 の 向 上,NESZが 小 さい 為 に 良 好 な 分 類 が 可 能 になる 40

39 BOS observation results( 2014/8/4~2014/12/21 ) 別 紙 4 世 界 域 観 測 実 績 ( 高 分 解 能 10m/28Mhz) F2-5~F2-7/ 右 観 測 / 昇 交 軌 道 /HH+HV Global: Forest/Defomation F2-6/ 左 観 測 / 降 交 軌 道 /HH スーパサイト/ 氷 河 流 動 モニタリング 41

40 BOS observation results( 2014/8/4~2014/12/21 ) 世 界 域 観 測 実 績 ( 広 域 観 測 350km/14Mhz/HH+HV) W2/ 右 ( 北 極 ) 左 ( 南 極 )/ 昇 交 軌 道 Polar region observation W2/ 右 観 測 / 降 交 軌 道 Deformation, wetland, deforestation 42 monitoring

41 BOS observation results( 2014/8/4~2014/12/21 ) 世 界 域 観 測 実 績 ( 高 分 解 能 3m/6m) U2-6~9/ 右 観 測 / 降 交 軌 道 /HH/84MHz Global observation FP6-3~7/ 右 観 測 / 昇 交 軌 道 /HH+HV+VH+VV/42MHz Global observation 43

42 Acquisition Status for the forest observations FBD (10m Dual) has almost covered the globe and Forest areas: 90% of forest area Number of observations: 55,530 scenes(62.7% of request) Strip data (2~4 times per year) ScanSAR 9 time per year Amazon area has been used for the calibration of the different beams

43 Conclusions ALOS-2/PALSAR-2 shows the excellent performance (high resolution, low noise level, polarimetry) as a high resolution L-band SAR to monitor the earth environment. ALOS-2/PALSAR-2 has started the forest observation already since Aug. 2014, and observed almost 90% of the forest region at least once. JAXA will start to produce the 25m PALSAR-2 forest mosaic (HH-HV-HH/HV),TBD m resolution browse mosaic, and will open them to the public through JAXA/EORC Web. JAXA will continue to produce the high level products.

44 The ALOS-2 Basic Observation Scenario (BOS) (as of February 2014) 基 本 観 測 計 画

45 BOS-2 Forest monitoring Temporal repeat: 6 cov/year GSD: 10 m (off-nadir ) Mode: Stripmap Dual-pol (HH+HV/28MHz) 47

46 BOS-2 Wetlands & Rapid deforestation monitoring Temporal repeat: 9 cov/year GSD: 100 m (off-nadir ) Mode: ScanSAR 350km Dual-pol (HH+HV/14MHz) 48

47 BOS-2 Global land areas VHR baseline mapping Temporal repeat: 1 cov/ 3 years GSD: 3 m (off-nadir ) Mode: Stripmap Single-pol (HH/84MHz) 1 st year 2 nd year 3 rd year * 3 years required for global coverage in 3m mode Prio 1 Prio 2 49

48 BOS-2 Global land areas Quad-polarimetric baseline Temporal repeat: 1 cov/ 5 years GSD: 6 m (off-nadir ) Mode: Stripmap Quad-pol (HH+HV+VV+VH) 1 st year 2 nd year 3 rd year 4 th year 5 th year * 5 years required for global coverage in 6m QP mode Areas observed every year 50

49 Basic Observation Scenario (Global) Polar Ice Temporal repeat: 3 cov/year GSD: 100 m (off-nadir ) Mode: ScanSAR 350km (HH+HV/14MHz) Right looking Left looking 51

50 BOS-2 Observation pattern for annual acquisitions* Super sites (TBD) 52 * 3m SP and 6m QP modes require 3 and 5 years for global

51 New Global Forest/Non-Forest Maps from ALOS PALSAR data ( ) Masanobu Shimada, Takuya Itoh, Manabu Watanabe, Takeshi Motooka, Rajesh Thapa, Richard Lucas

52 H Sumatra Forest - HH Non-Forest - HH Red: 2007 Blue: 2008 Green: 2009 Yellow: 2010 New Guinea Forest - HV Non-Forest - HV HH Forest is stable, and Non-forest is unstable HV has larger difference of gamma-zero at forest and non-forest Borneo Malaysia Philippines East Asia Japan India Europe /Russia Australia Amazon Chile Africa North America Central America Red: 2007 Blue: 2008 Green: 2009 Yellow: Sumatra New Guinea HV Borneo Malaysia Philippines East Asia Japan India Europe /Russia Australia Amazon Chile Africa North America Central America

53 Histogram property H-3 森 林 分 類 毎 に 反 射 係 数 に 差 がある Natural forest Natural mangrove forest Natural re-growth Acacia Oil Palm Rubber Coconut Open area Other Water c) a) b) Teacher HH HV

54 Annual Change of the gamma-naught (Global Forest and Amazon Forest) H-1

55 H-1 Annual change of gamma-zero(db/yr) G0の 年 毎 の 変 化 率 g 0 decreased by 0.040dB yr -1 in HH and 0.028dB yr -1 in HV globally and regionally, with this potentially related to decreases in forest area and AGB and a smoothing of the non-forest area (e.g., as a consequence of agricultural management leading to improvement of cleared areas).

56 1. FNF map generation PALSAR 25m Mosaic 2007 Forest/Non-Forest Map New Version of the FNF FNF map was generated using the this method shows the improvement of the results in several areas, i.e., south east Asia.

57 Validation GEI DCP

58 Accuracy measure of the FNF using the database Year GE DCP FRA % Mean % Note: GE>4000 points, DCP>2000 points

59 3.1 Forest definition PALSAR, FRA:Forest coverage larger than 1 0%, area larger than 0.5ha, natural forest, forest height(not from satellite) Landsat(Hansen et al.):tree coverage : %

60 3.2 comparison Landsat, FRA, PALSAR Forest areas estimated from three method show almost the same values. Hansen et al (2013), Science showed the trend of the forest change(gain and loss) between 2000 and Both (Landsat and PALSAR) methods have similar evaluation method for their forest and non-forest areas. PALSAR s forest area is 5% less than Landsat value.:>1)l-band signal is slightly less sensitive fro vegetation.

61 3.3 Accuracy Assessment (1/3) PALSAR vs. FRA vs. Landsat x1000ha Region Landsat(2000) PALSAR(2007 ) FRA(2005) Africa Asia Eurasia N/C America Oceania S America Total Diff Hansen et al (2013), Science This results FAO

62 3.4 temporal variation PALSAR s forest decrease(annual)shows 16Kkm 2 ( ),320Kkm 2 ( ), in average with several Kkm 2 /yr. FRA shows the decrease of 200Kkm 2 ( ), 40Kkm 2 /yr. In general, PALSAR and FRA meets. Landsat(Hansen et al., 2013)is 2300Kkm 2 /yr and quite large.

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64 25m data will be freely open Sept/E.

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68 New Global Forest/Non-Forest Maps from ALOS PALSAR data ( ) Masanobu Shimada 1), Takuya Itoh 2), Manabu Watanabe 1), Takeshi Motooka 1), Rajesh Thapa 1) Earth Observation Research Center Japan Aerospace Exploration Agency IGARSS2014 Quebec July 14-April 29, 2014

69 Contents 1. Spatio-temporal dependency of the PALSAR gamma-zero on forest/non-forest (FNF) classification 2. Generation of the forest/non-forest map 3. Comparison with the Landsat Forest/non-forest map Masanobu Shimada, Takuya Itoh, Takeshi Motooka, Manabu Watanabe, Rajesh Thapa, and Richard Lucas, New Global Forest/Non-forest Maps from ALOS PALSAR Data ( ), Remote Sensing Environment, DOI= /j.rse

70 PALSAR 10m Mosaic 2007 Forest/Non-Forest Map First Version of the FNF(2010): Threshold : -14dB (constant) World first SAR based FNF data, but, classification accuracy shows the regionality Needs the investigation on spatio temporal dependency

71 PALSAR data: global 25m resolution mosaic ( )-ortho and slope corrected - were completed. Can be used as GIS data: geometric accuracy is better than 10m

72 Histogram of the gamma-zero from the global mosaic data Cross over point is -14 db 1 st Version of FNF was produced in 2010 as the world first SAR based Forest product. This is generally good accuracy. However, more accuracy is necessary.

73 Investigation of the SAR data stability in three scales H-1)global scale H-2)15 continental or sub continental scale H-3)regional scale investigation with 10 smaller sub regions

74 H Sumatra Forest - HH Non-Forest - HH Red: 2007 Blue: 2008 Green: 2009 Yellow: 2010 New Guinea Forest - HV Non-Forest - HV HH Forest is stable, and Non-forest is unstable HV has larger difference of gamma-zero at forest and non-forest Borneo Malaysia Philippines East Asia Japan India Europe /Russia Australia Amazon Chile Africa North America Central America Red: 2007 Blue: 2008 Green: 2009 Yellow: Sumatra New Guinea HV Borneo Malaysia Philippines East Asia Japan India Europe /Russia Australia Amazon Chile Africa North America Central America

75 Histogram property H-3 森 林 分 類 毎 に 反 射 係 数 に 差 がある Natural forest Natural mangrove forest Natural re-growth Acacia Oil Palm Rubber Coconut Open area Other Water c) a) b) Teacher HH HV

76 Annual Change of the gamma-naught (Global Forest and Amazon Forest) H-1

77 H-1 Difference of two averages There are two distribution functions, each of which has averages of m 1 and m 2 and standard deviation of s 1 and s 2. Averages m 1 and m 2 are different or same? If m1-m2 >d95% or d99%, they can be different with 95% or 99% confidence. m 1 (s 1 ) m 2 (s 2 ) D 95% = s n D 99% = s n Distribution of SAR data

78 H-1 Annual change of gamma-zero(db/yr) G0の 年 毎 の 変 化 率 g 0 decreased by 0.040dB yr -1 in HH and 0.028dB yr -1 in HV globally and regionally, with this potentially related to decreases in forest area and AGB and a smoothing of the non-forest area (e.g., as a consequence of agricultural management leading to improvement of cleared areas).

79 Spatio-temporal property of the forest back scatter(summary) Gamma-zero in forest (HH and HV )is stable. That in non-forest is less stable. Gamma-zero(average) shows the region dependence. In Amazon, HH and HV g 0 was, on average, and db, Indonesia, and db. Difference of forest and non-forest is 3.97 db in HH, 6.42 db in HV. In general,g 0 はrelatively stable for all forest areas with HH and HV values averaging ±0.95 db and ±1.52 db respectively over the four years. A normal distribution was also followed, with the standard deviation being 2.13 and 2.04 db respectively;) within all years but annual averages being as small as 0.21±0.18dB and 0.21±0.19dB when all four years were considered. Values of g 0 were lower and more variable for non-forest areas, averaging ±4.78 db and ±3.84 db at HH and HV polarization respectively. HV has higher sensitivity than HH for forest/non-forest classification. FNF classification is preferable using the threshold method.

80 1. FNF map generation Determination of the threshold 1) Measure the DF of Forest & Non-F 2) Calculate the Cumulative DFs and measure the threshold that maximizes the both. 3) Threshold is region dependent. F F F F F NF ( x) = 1- F NF ( x) ò x ( x) º f F x' x ò - ( ) dx' ( x) º f NF x' ( ) dx' Histograms for Forest & Non-forest (Acacia) Cumulative Distribution Fn. Sumatra Case Threshold

81 FNF 分 類 アルゴリズム 1. FNF map generation Figure. 11. Rules used for the classification of forest and non-forest areas from the ALOS PALSAR mosaic data.

82 1. FNF map generation PALSAR 25m Mosaic 2007 Forest/Non-Forest Map New Version of the FNF FNF map was generated using the this method shows the improvement of the results in several areas, i.e., south east Asia.

83 1. FNF map generation PALSAR 10m Mosaic 2007 Forest/Non-Forest Map First(older) Version of the FNF 東 南 アジアが 改 善

84 1. FNF map generation FNF classification results( )

85 Validation GEI DCP

86 Accuracy measure of the FNF using the database Year GE DCP FRA % Mean % Note: GE>4000 points, DCP>2000 points

87 3. Discussion Forest definition Comparison with Landsat data (Hansen, et al., FRA) Temporal variation of the gamma-zero

88 3.1 Forest definition PALSAR, FRA:Forest coverage larger than 1 0%, area larger than 0.5ha, natural forest, forest height(not from satellite) Landsat(Hansen et al.):tree coverage : %

89 3.2 comparison Landsat, FRA, PALSAR Forest areas estimated from three method show almost the same values. Hansen et al (2013), Science showed the trend of the forest change(gain and loss) between 2000 and Both (Landsat and PALSAR) methods have similar evaluation method for their forest and non-forest areas. PALSAR s forest area is 5% less than Landsat value.:>1)l-band signal is slightly less sensitibe fro vegetation.

90 3.4 temporal variation PALSAR s forest decrease(annual)shows 16Kkm 2 ( ),320Kkm 2 ( ), in average with several Kkm 2 /yr. FRA shows the decrease of 200Kkm 2 ( ), 40Kkm 2 /yr. In general, PALSAR and FRA meets. Landsat(Hansen et al., 2013)is 2300Kkm 2 /yr and quite large.

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94 4. Conclusions The PALSAR remained stable (within 0.065dB) over its lifetime (from 2006 to 2010) so changes in HV g 0 over time could be attributed to changes in the land cover. For forest areas, g 0 remained stable at both HH and HV, with annual averages of the standard deviation being 0.21 ±0.18dB and 0.21±0.19dB respectively. The thresholds for HH and HV g 0 for separating forest and non-forest were regionally variable, being 6.89±0.95dB in HH and ±1.52dB in HV. In comparison to the DCP, GEI and FRA 2005/2010, accuracies of 84.86%, 91.25%, and 94.81% were obtained in the mapping of forest and non-forest at a global level with regional variations. Based on these estimates, the decrease in forest cover between 2007 and 2010 was million ha (-0.042%), with the FRA estimating a decrease of million ha (-0.687%; based on FRA2010 and FRA2005). g 0 decreased by 0.040dB yr -1 in HH and 0.028dB yr -1 in HV globally and regionally, with this potentially related to decreases in forest area and AGB and a smoothing of the non-forest area (e.g., as a consequence of agricultural management leading to improvement of cleared areas). 97

95 ALOS PALSAR 50 m global mosaic data Open release The data can be downloaded from dex.htm As of January 16, 2014, JAXA have made PALSAR 50 m global mosaic data openly available free of charge. (soon after, 25m will be avilable) Annual mosaics from 2007, 2008, 2009 and 2010, covering all land areas except Greenland and Antarctica. Generation will continue from 2014 with ALOS-2 The 50m mosaic data were generated by averaging from JAXAs 25m resolution mosaic products. Available in 1 x1 tiles.

96 ALOS-2 satellite Launch : May 24, 2014 ALOS-2 Orbit type : Sun-synchronous Altitude : 628 km +/- 500 m (for reference orbit) Revisit time : 14 days LSDN : 12:00 +/- 15 min PALSAR-2 L-band Synthetic Aperture Radar X Active Phased Array Antenna Solar paddles type Y two dimensions scan (range and Z azimuth) Antenna size : 3m(El) x 10m(Az) Bandwidth : 14 84MHz Peak transmit Power : 5100W Observation swath : km Resolution : Range: 3 m to 100 m Azimuth: 1 m to 100 m SAR antenna ALOS-2 Specifications.

97 ALOS-2 Specifications. Spotlight Ultra Fine High ScanSAR ScanSAR Fine sensitive nominal wide Bandwidth 84MHz 84MHz 42MHz 28MHz 14MHz 28MHz 14MHz Resolution Rg Az: 3 1m 3m 6m 10m 100m 60m Swath Rg Az: 350km 490km 50km 50km 70km 25 25km (5-scan) (7-scan) Polarization SP SP/DP SP/DP/FP/CP SP/DP NESZ -24dB -24dB -28dB -26dB -26dB -23dB -23dB S/A Rg 25dB 25dB 23dB 25dB 25dB 20dB Az 20dB 25dB 20dB 23dB 20dB 20dB SP : HH or VV or HV, DP : HH+HV or VV+VH, FP : HH+HV+VH+VV, CP : Compact pol (Experimental mode) Main applications: Fine beam (DP): Forest and land cover monitoring ScanSAR (DP): Rapid deforestation / wetlands / InSAR (ScanSAR-ScanSAR) Spotlight (SP): Emergency observations Ultra Fine (SP) : Global map, InSAR base mapping High sensitive (QP): Global map ScanSAR wide (SP) : Polar ice

98 Conclusions Hoping the successful launch of ALOS-2 in May Polar/Okhotsk sea ice distribution was observed by the ALOS/PALSAR Radar backscatter can be used for sea ice discrimination from the ocean. ALOS-2 will be used for the polar monitoring in summer (winter) for ship.

99 ALOS PALSAR 50 m global mosaic data Open release As of January 16, 2014, JAXA have made PALSAR 50 m global mosaic data openly available free of charge. Annual mosaics from 2007, 2008, 2009 and 2010, covering all land areas except Greenland and Antarctica. Generation will continue from 2014 with ALOS-2 The 50m mosaic data were generated by averaging from JAXAs 25m resolution mosaic products. Available in 1 x1 tiles. The data can be downloaded from

100 ALOS PALSAR global mosaic data Open release Open release of 25 m versions foreseen for mid 2014 Same production chain availabe for ALOS- 2

101 ALOS-2 Data Policy (Part) JAXA data policy defines tentatively 15m as the critical sensor data resolution. Lower resolution data can be distributed for free and higher data will be distributed commercially by a private operator. While the ScanSAR data has lower resolution, the data will be handled on commercial basis, as the data is considered to have a commercial value. Data distribution to the governmental users, that includes the international collaboration activities, i.e., CEOS, GEO, etc., can be conducted with the reasonable price. (General user needs to bear the commercial price which will be determined by the private operator). The reasonable price is approx yen/ scene considering the costs converting from the level 0 to the 1.5. For GFOI, since its observation requirements are already included in the ALOS-2 Baseline Observation Strategy (BOS), observation request charge does not occur.

102 Conclusion( 結 論 ) ALOS/PALSARを 基 本 とした 森 林 非 森 林 情 報 が95%の 精 度 で 抽 出 されている ALOS-2に 繋 げたい L-band time series SAR data showed the decrease of backscatter and forest areas. This means that the earth surface becomes smoother than before. JERS-1 SAR will be included in near future for longer time variation and ALOS-2/PALSAR-2 will be used for forest variation after Masanobu Shimada, Takuya Itoh, Takeshi Motooka, Manabu Watanabe, Rajesh Thapa, and Richard Lucas, New Global Forest/Non-forest Maps from ALOS PALSAR Data ( ), Remote Sensing Environment, accepted March 25, 2014, in press. 105

103 Discussion

104 概 要 宇 宙 航 空 研 究 開 発 機 構 (Japan Aerospace Exploration Agency, JAXA)は, 陸 域 観 測 衛 星 (Advanced Land Observing Satellite, ALOS)が2007 年 から2010 年 にかけて 取 得 した 全 球 PALSARデータを 高 精 度 処 理 して25m 分 解 能 の 全 球 PALSARモザイク 画 像 を 作 成 し た 1,2,3) それらを 用 いて 全 球 の 森 林 非 森 林 マップを 試 験 的 に 作 成 した 4) が, 今 回,PALSARモ ザイク 画 像 を 地 域 毎 年 代 毎 に 詳 細 に 評 価 し, 光 学 衛 星 (Google Earth 画 像 )や 現 地 データを 参 考 とした 分 類 を 行 い, 新 森 林 非 森 林 マップ( 検 証 済 み 版 )を 作 成 した 5) 図 1が 2010の 年 の 森 林 非 森 林 マップである 森 林 非 森 林 マップは, 森 林 土 地 利 用 の 時 間 的 な 変 化 を 把 握 し, 陸 域 起 源 の 地 球 温 暖 化 の 要 因 の 特 定 や,Reducing the Emission from Deforestation and forest Degradation plus (REDD+) 活 動 を 推 進 する 上 で, 非 常 に 重 要 な 基 礎 情 報 である このマップは,3 種 類 の 検 証 データと 比 較 した 結 果, 約 90%の 精 度 を 持 つことが 確 認 されている JAXAではL-band SARデータが 森 林 解 析 に 使 用 されることを 期 待 し, 50m 分 解 能 のデー タ(PALSARモザイクデータ 及 び 森 林 非 森 林 データ) 公 開 することとした 上 記 精 度 は, 無 作 為 抽 出 での 評 価 であり, 森 林 の 定 義 が 国 によって 異 なることを 考 慮 すると 更 に 改 善 の 余 地 があり 今 後 時 間 をかけて 精 度 向 上 を 目 指 す Masanobu Shimada, Takuya Itoh, Takeshi Motooka, Manabu Watanabe, Rajesh Thapa, and Richard Lucas, New Global Forest/Non-forest Maps from ALOS PALSAR Data ( ), Remote Sensing Environment, accepted March 25, 2014, in press.

105 Sound and Radar Technology Fidelity High Quality Wide Band Low noise High speed signal processor Innovated so much > What we could do in next?

106 Japanese Earth Resources Satellite -1 (JERS-1) 1992~1998 Instruments 1)OPS(8 bands) 2)SAR(L HH): 3)MDR(Mission Data recorder) 4)MDT(Mission Data transmitter) Total data (at EOC) SAR:707,393 scenes(97%) OPS:335,619 scenes(63%) 109

107 L-band SAR and Penetration/Interferometry/Polarimetry X: a little C: a little L: Some

108 JAXA s SAR history JERS-1/SAR:1992/2/ /10/12 Pi-SAR-L:1997/11/M-2011/11/E ALOS/PALSAR:2006/1/ /4/22 Pi-SAR-L2:2012/4/17- ALOS-2/PALSAR-2:2013/11/7- ALOS-followon:201? or 2020 All L-band, of large Duty SAR for global Observation, heritages from 1990 for solid Earth and Biospheric observation. Application (including disaster) and the science are the main objectives. 111

109 JERS-1/SAR ( ) ALOS/PALSAR( ) Pi-SAR-L(1998~2011) Pi-SAR-L2(2012~) ALOS-2(2014~)

110 Sat. JERS-1 Pi-SAR-L ALOS/PAL SAR Resol.(m: Az-Rg) Pi-SAR-L2 ALOS- 2/PALSAR NESZ(dB) (-23) -54(-35)?(-30) Polarizati on Revisit/Of f-nadir Mode(sw ath)(km) HH Quad HH+HV Quad(E) ScanSAR( HH) 44D 35.1 NA D Strip(75) Strip(15) Strip(70) Scan(350) Quad NA 7-60 Strip(20) HH+HV Quad ScanSAR( HH+HV) 14D 7-70 Spot(25) Strip(50) Scan(350/ 490)

111 Comparison among L-C-X L(23cm) C(5.6cm) X(3.0cm) Resolution <85MHz <TBD <500MHz Penetration Much less less Observables Forest covered surface Surface scattering Surface scattering Forest sensitive Less sensitive less-sensitive Agriculture Less sensitive Medium sensitive sensitive Ocean Sensitive Sensitive Sensitive Coastal erosion DinSAR Disaster Sensitive (sometimes coast invisible) Very sensitive with longer time Effective use of Pol + InSAR Sensitive Sensitive only in urban Effective Sensitive Sensitive only in urban Effective

112 L-band Radar Remote Sensing Imaging under All weather Observation Accurate Geometry > GIS Accurate Radiometry Interferometry > CCD, Deformation Polarimetry > Classification/Disaster PolInSAR > 3D structure

113 3. Interferometry and Deformation Deformation monitoring (Seismic) ScanSAR interferometry Subsidence monitoring

114 Speed cm/year Subsidence of the peatland

115 3. Forest Monitoring Deforestation monitoring Illegal Logging monitoring LULUCF classification REDD+ Mangrove Watch

116 Land Use Classification in Riau, Sumatra( 土 地 利 用 分 類 ) 200km WWF 10 classes PALSAR 10 classes Natural forest Natural mangrove forest Natural re-growth Acacia Oil Palm Rubber Coconut Open area Other Water Forest(exclude Mangrove)/Non-forest Accuracy: 87.9% iインドネシア リアウ 州 スマトラ 島

117 JERS-1 SAR Mosaic data (HH)

118 PALSAR 25m Mosaic RGB Composite Image :HH :HV :HH/HV

119 Land Use sensitivity of polarizations HV much more sensitive than HH

120 PALSAR 25m Mosaic 2007 Forest/Non-Forest Map, (produced in 2013, Feb.) :Forest :Non-Forest :Water

121 PALSAR 25m Mosaic 2008 Forest/Non-Forest Map, (produced in 2013, Feb.) :Forest :Non-Forest :Water

122 PALSAR 25m Mosaic 2009 Forest/Non-Forest Map, (produced in 2013, Feb.) :Forest :Non-Forest :Water

123 PALSAR 25m Mosaic 2010 Forest/Non-Forest Map, (produced in 2013, Feb.) :Forest :Non-Forest :Water

124 Validation Using the GE images

125 Accuracy measure of the FNF using the database Year GE DCP Mean Note: GE>4000 points, DCP>2000 points

126 Accuracy Assessment (1/3) PALSAR vs. FRA Product PALSAR(2008) [1000ha] 2008 FRA(2005) [1000ha] Relative Error (±) [%] (PALSAR vs FRA) Africa 630, , % Asia 583, , % Europe 1,007,734 1,009, % North and Central America 660, , % Oceania 177, , % South America 825, , % Total 4,535,687 4,759, %

127 Accuracy Assessment (2/3) Time Series PALSAR(20 07) [1000ha] PALSAR(20 08) [1000ha] PALSAR(20 09) [1000ha] PALSAR(20 10) [1000ha] FRA(2005) [1000ha] FRA(2010) [1000ha] Africa Asia Europe North and Central America Oceania South America Total

128 Accuracy Assessment (3/3) Time Series Temporal Change of the Forest Areas Forest area is decreasing.

129 JAXA-MRV Time series SAR Basic Information Ortho, Slope Mosaic, Multi season Processing Gamma0, GT Lulucf C(biomass, lidar) Ccalc FNF 1,2 FNFC 1,2 LULUCF LULUCFC GC C Simulator, Verification box 134 CC

130 Biomass estimation from g 0 HV (As of March 2013) Natural forest only Biomass data Obtaion from (LiDAR)-(field plot) PALSAR data 2007, 2008, 2009, 2010 年 Resolution 3.6 ha Simple mean Biomass < Biomass > All biomass 100 tons/ha 100 tons/ha Average(tons/ha) RMS Error (tons/ha) RMS Error (%) Good accuracy, if AG-biomass - g 0 is available

131 Conclusion L-band SAR has a big potential for capturing the land surface features. Time series amplitude, interferometric, polarimetric data can contribute to the science and applications. JERS-1, ALOS, ALOS-2, and its further continuity will provide the robust observation scheme. Germany-Japan-Twin 350km L-band SAR enhances the observation capability. 136

132 ALOS-2 satellite Launch : 2014 ALOS-2 Orbit type : Sun-synchronous Altitude : 628 km +/- 500 m (for reference orbit) Revisit time : 14 days LSDN : 12:00 +/- 15 min PALSAR-2 L-band Synthetic Aperture Radar X Active Phased Array Antenna Solar paddles type Y two dimensions scan (range and Z azimuth) Antenna size : 3m(El) x 10m(Az) Bandwidth : 14 84MHz Peak transmit Power : 5100W Observation swath : km Resolution : Range: 3 m to 100 m Azimuth: 1 m to 100 m SAR antenna ALOS-2 Specifications.

133 ALOS-2 Specifications. Spotlight Ultra Fine High ScanSAR ScanSAR Fine sensitive nominal wide Bandwidth 84MHz 84MHz 42MHz 28MHz 14MHz 28MHz 14MHz Resolution Rg Az: 3 1m 3m 6m 10m 100m 60m Swath Rg Az: 350km 490km 50km 50km 70km 25 25km (5-scan) (7-scan) Polarization SP SP/DP SP/DP/FP/CP SP/DP NESZ -24dB -24dB -28dB -26dB -26dB -23dB -23dB S/A Rg 25dB 25dB 23dB 25dB 25dB 20dB Az 20dB 25dB 20dB 23dB 20dB 20dB SP : HH or VV or HV, DP : HH+HV or VV+VH, FP : HH+HV+VH+VV, CP : Compact pol (Experimental mode) Main applications: Fine beam (DP): Forest and land cover monitoring ScanSAR (DP): Rapid deforestation / wetlands / InSAR (ScanSAR-ScanSAR) Spotlight (SP): Emergency observations Ultra Fine (SP) : Global map, InSAR base mapping High sensitive (QP): Global map ScanSAR wide (SP) : Polar ice

134 Comparison of the JERS-1 SARとALOS PALSAR on data amount/number of scenes(daily) JERS-1 SAR ALOS PALSAR ALOS-2 Daily Data Amount (GByte) Daily number of scenes (20.24) ( ) 1,176 (6.10) 1, ( ) CAL included All the OBS data included. Remarks Based on 1993~ 1997 Based on Simulation

135 ALOS PALSAR 25m global mosaic data Open release