Mapping Regional Inundation with Spaceborne L-Band SAR
"> Figure 1
<p>Mean offsets of 388 UTM grid-zone-projected path images from SRTM DEM.</p> "> Figure 2
<p>Average mean-difference between average image brightness and each of 70 ScanSAR image strips in UTM grid-zone tile 19M.</p> "> Figure 3
<p>Orthorectified ScanSAR mosaic of most of South America, late-2006 to mid-2010. Colored letters correspond to details shown in subsequent figures. © JAXA,METI.</p> "> Figure 4
<p>Yellow scale bar corresponds to 50 km, and the location of each sub-figure is shown in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>. Generally, we may associate the brighter areas as caused by double-bounce reflections in inundated vegetation areas or urban regions. Water and bare soil appear dark and forest areas are medium-grey shades. Locations are indicated in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>. (<b>a</b>) Noel Kempff National Park, Bolivia; (<b>b</b>) Deforestation near the city of Rio Branco, Brazil (bright area at center) and inundated Iquiri River floodplain; (<b>c</b>) Pacaya-Samiria Reserve, Peru; (<b>d</b>) middle Rio Negro; and (<b>e</b>) Orinoco Delta. © JAXA, METI.</p> "> Figure 4 Cont.
<p>Yellow scale bar corresponds to 50 km, and the location of each sub-figure is shown in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>. Generally, we may associate the brighter areas as caused by double-bounce reflections in inundated vegetation areas or urban regions. Water and bare soil appear dark and forest areas are medium-grey shades. Locations are indicated in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>. (<b>a</b>) Noel Kempff National Park, Bolivia; (<b>b</b>) Deforestation near the city of Rio Branco, Brazil (bright area at center) and inundated Iquiri River floodplain; (<b>c</b>) Pacaya-Samiria Reserve, Peru; (<b>d</b>) middle Rio Negro; and (<b>e</b>) Orinoco Delta. © JAXA, METI.</p> "> Figure 5
<p>HH backscatter threshold <span class="html-italic">versus</span> incidence angle for the detection of inundation, derived empirically such that similar classifications were obtained in the near and far range of overlapping images acquired five days apart.</p> "> Figure 6
<p>Black bar indicates 10 km scale. (<b>a</b>) Mid-swath classification from 27 June 2007 (coordinate: −5.98°, −64.83° shown by “x” in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>); (<b>b</b>) near-swath classification from 22 June 2007; (<b>c</b>) mid-swath classification from June 27, 2007 (coordinate −4.13°, −63.42° shown by “y” in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>); (<b>d</b>) far-swath classification from 22 June 2007. Yellow indicates inundated vegetation and dark blue indicates open water. All other areas are unclassified.</p> "> Figure 7
<p>Inundation classification late-2006 to mid-2010; same location as shown in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>. (<b>a</b>) maximum inundation, (<b>b</b>) minimum inundation. Black-topographically excluded; <b>dark blue</b>: open water; <b>light blue</b>: open water maximum; <b>green</b>: not inundated; <b>yellow</b>: inundated vegetation; <b>light yellow</b>: inundated vegetation maximum; <b>brown</b>: croplands from GlobCover 2009; <b>grey</b>: unclassified.</p> "> Figure 8
<p>Location shown in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a> by yellow box where horizontal extent is 3500 km. (<b>a</b>) JERS-1 SAR-based wetland mask (white is inundatable; black is not) [<a href="#B4-remotesensing-07-05440" class="html-bibr">4</a>]; (<b>b</b>) JERS-1 SAR image mosaic—Amazon River low flood (late–1995); (<b>c</b>) JERS-1 SAR image mosaic—Amazon River high flood (mid-1996). ©NASDA.</p> "> Figure 9
<p>Location shown in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a> by yellow box where horizontal extent is 3500 km. (<b>a</b>) Melack and Hess inundation classification (mid-90s); (<b>b</b>) ALOS inundation classification (2007–2009). Yellow—always inundated vegetation; off-yellow—occasionally inundated vegetation; dark blue—always open water; medium blue—occasionally open water; brown (ALOS only)—high topographic slopes.</p> "> Figure 10
<p>(<b>a</b>) Melack and Hess classification, where yellow and off-yellow indicate maximum extent of flooded herbaceous vegetation; (<b>b</b>) ALOS classification, where dark blue and medium blue indicate maximum extent of open water and yellow and off-yellow indicate always or occasionally flooded vegetation, respectively. The flooded herbaceous classes tend to be classified as open water (and sometimes as not inundated) in the ALOS classification. (center coordinates: −1.978°, −53.708°, shown by letter “w” in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>. The black bar indicates 50 km scale).</p> "> Figure 11
<p>(<b>a</b>) Melack and Hess classification, where off-yellow indicate maximum extent of flooded shrubs; (<b>b</b>) ALOS classification, where dark blue and medium blue indicate maximum extent of open water and brown represents areas of steep slope not likely to be inundated. The flooded shrub classes tend to be classified as not inundated in the ALOS classification. (center coordinates: −8.487°, −61.788° shown by letter “z” in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>, black bar indicates 50 km scale).</p> "> Figure 12
<p>(<b>a</b>) Inundation classification for Pacaya_Samiria, Peru, and surrounding locations, overlaid on JERS-1 based wetland mask, centered on letter “c” in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>. The black box is 45 km by 45 km. The colors of the inundation classification are overlaid on the JERS-1 based wetland mask, (light grey indicates inundatable and dark grey indicates outside the inundatable area; (<b>b</b>) ALOS ScanSAR estimated inundation dynamics for box shown in (a) depicting fractional total inundation <span class="html-italic">versus</span> time. <b>yellow</b>: always inundated vegetation; <b>off-yellow</b>: occasionally inundated vegetation; <b>dark blue</b>: always open water; <b>medium blue</b>: occasionally open water; <b>brown (ALOS only)</b>: high topographic slopes.</p> "> Figure 13
<p>Classification overlaid on low contrast multi-temporal image mosaic of the area within the box from <a href="#remotesensing-07-05440-f012" class="html-fig">Figure 12</a> for specific ScanSAR observations acquired from the same path orbit, at letter “c” in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>. Area shown is 45 km by 45 km. (<b>a</b>) 29 January 2007; (<b>b</b>) 16 March 2007; (<b>c</b>) 1 May 2007; (<b>d</b>) 16 June 2007; (<b>e</b>) 1 August 2007; (<b>f</b>) 16 September 2007. Yellow is inundated vegetation on the date of observation; black is open water. Area shown is 2000 km<sup>2</sup>.</p> "> Figure 13 Cont.
<p>Classification overlaid on low contrast multi-temporal image mosaic of the area within the box from <a href="#remotesensing-07-05440-f012" class="html-fig">Figure 12</a> for specific ScanSAR observations acquired from the same path orbit, at letter “c” in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>. Area shown is 45 km by 45 km. (<b>a</b>) 29 January 2007; (<b>b</b>) 16 March 2007; (<b>c</b>) 1 May 2007; (<b>d</b>) 16 June 2007; (<b>e</b>) 1 August 2007; (<b>f</b>) 16 September 2007. Yellow is inundated vegetation on the date of observation; black is open water. Area shown is 2000 km<sup>2</sup>.</p> "> Figure 14
<p>Inundation duration (for vegetated areas) estimated from seven images acquired between 2007 and 2008 from a single orbit path for the Pacaya-Samiria Reserve (area “c” in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>) and surrounding areas in Peruvian Amazon. The area shown spans 300 km from east to west and 350 km from north to south. The yellow bar shows 50 km scale. Background is low contrast multi-temporal image mosaic.</p> "> Figure 15
<p>Comparison of inundation and coarse-resolution surface water fraction products for the same area shown in <a href="#remotesensing-07-05440-f003" class="html-fig">Figure 3</a>. (<b>a</b>) Minimum fraction of open water from ALOS ScanSAR classification; (<b>b</b>) minimum fractional surface water area from coarse resolution sensors; (<b>c</b>) minimum fraction of inundated vegetation from ALOS ScanSAR classification; (<b>d</b>) maximum fraction of open water from ALOS ScanSAR classification; (<b>e</b>) maximum fractional surface water area from coarse resolution sensors; (<b>f</b>) maximum fraction of inundated vegetation from ALOS ScanSAR classification. Blue indicates masked pixels; grey scale indicates relative fractional inundation with white indicating maximum surface water fraction and black indicating no inundation.</p> "> Figure 16
<p>Comparison of ALOS and JERS-1 products with coarse-resolution surface water fraction. (<b>a</b>) ALOS open water fraction; (<b>b</b>) ALOS inundated vegetation fraction; (<b>c</b>) JERS-1-based mask (where there is overlap) <span class="html-italic">versus</span> the coarse resolution surface water fraction. Note that the scale of (c) is much larger. Only the ALOS open water fraction has a significant relation to the coarse resolution surface water fraction estimates.</p> ">
Abstract
:1. Introduction
2. Methodology
2.1. Description of Satellite Data
2.2. Orthorectification and Radiometric Terrain Calibration
2.3. Relative and Absolute Calibration
2.4. Mosaicking
2.5. Image Classification
Initial Class | Radar Backscatter (dB) | GlobCover Class |
---|---|---|
Urban | Ia > −5.9 | 190 1 |
Flooded vegetation | Ia > −5.9 | Any |
Forest | −5.9 > Ia > −9 | Any |
Low vegetation | −9.0 > Ia > −13.7 | Any |
Open water/low veg or bare | −13.7 > Ia > −19.0 | Any |
Open water 1 | Ia < −19 | 210 2 |
Open water 2 | Ia < −19 | Any |
Topographic slope mask (if SRTM height difference to adjacent pixels exceeds 18 m) | Any | Any |
Initial Class | Condition | Final Class |
---|---|---|
Forest | Δb > 3 dB | Occasionally inundated vegetation |
Inundated vegetation | Δb < −3 dB | Occasionally inundated vegetation |
Inundated vegetation | Variable with incidence angle | Occasionally inundated vegetation |
Low vegetation | Δb < −3 dB | Occasionally open water |
Open water | Δb > 6 dB | Occasionally open water |
Inundated vegetation | Δb < −12 dB | Variable inundation state |
Low vegetation | Δb > 10 dB | Occasionally inundated vegetation |
Forest | Δb < −10 dB | Variable inundation state |
Any except topographic slope | Ia +Δb > −5.9 dB | Occasionally inundated vegetation |
Any open water or inundated | Maximum SRTM slope = 0 | SRTM open water vegetation class |
Any except topographic slope | 11 ≤ GlobCover2009 class ≤ 2011 | Crops |
3. Results and Discussion
3.1. Comparison with JERS Results
Inundation Category |
---|
Open water (one date) |
Open water (both dates) |
Flooded herbaceous vegetation (one date) |
Flooded herbaceous vegetation (both dates) |
Flooded shrub vegetation (one date) |
Flooded shrub vegetation (both dates) |
Flooded woodlands (less than 60% canopy cover) (both dates) |
Flooded forest (one date) |
Flooded forest (both dates) |
Within JERS Mask | % of All Pixel Locations Where ALOS and MH Classifications Both Show Inundation (Refer to Table 3) | % of All Pixel Locations Where MH Classification Shows Inundation (Refer to Table 3) |
---|---|---|
Maximum Inundation | ||
Flooded forest extent | 86% | 58% |
Flooded woodland extent | 7% | 8% |
Flooded herbaceous extent | 2% | 22% |
Flooded shrubs extent | 3% | 13% |
Minimum Inundation | ||
Flooded forest extent | 99% | 73% |
Flooded woodlands extent | 0% | 13% |
Flooded herbaceous extent | 1% | 15% |
Within JERS Mask | ALOS Inundated Vegetation (Mha) | MH Flooded Forest (Mha) | MH, Flooded Woodland (Mha) | ALOS Open Water (Mha) | MH, Open Water (Mha) | MH, Flooded Herbaceous (Mha) |
---|---|---|---|---|---|---|
Maximum inundation | 20.7 | 23.8 | 5.2 | 8.8 | 8.4 | 9.3 |
Minimum inundation | 4.8 | 9.3 | 5.2 | 4.7 | 5.9 | 3.7 |
3.2. Monitoring Inundation Dynamics
ALOS Maximum Inundation Class | Criteria | Temporal Class |
---|---|---|
Occasionally inundated vegetation or forest | Δb >3 dB | Inundated vegetation |
Occasionally inundated vegetation or forest | Δb < −10 dB and θx,y > 29° | Open water |
Low vegetation, forest, or occasionally open water | Δb < −3 dB and θx,y > 29° | Open water |
Low vegetation or occasionally open water | Δb < 10 dB | Inundated vegetation |
Low vegetation or occasionally open water | Δb > 10dB | Inundated vegetation |
Always inundated vegetation | Open water | |
Always inundated vegetation | Inundated vegetation |
Area from ALOS ScanSAR Classification (km2) | |
---|---|
Maximum | |
Open water | 1504 |
Flooded vegetation | 26,074 |
Combined | 27,578 |
Minimum | |
Open water | 1085 |
Flooded vegetation | 6939 |
Combined | 8024 |
Melack and Hess [4] mask inundatable area: 103,673 km2 |
Relative Inundation Duration | Area |
---|---|
7 (Yellow) | 6939 km2 |
6 (Light Green) | 540 km2 |
5 (Dark Green) | 911 km2 |
4 (Turquoise) | 1715 km2 |
3 (Red) | 2952 km2 |
2 (Pink) | 4778 km2 |
1 (Dark Blue) | 8237 km2 |
3.3. Comparison with Coarse Resolution Surface Water Fraction Estimates
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Hess, L.L.; Melack, J.M.; Novo, E.M.L.M.; Barbosa, C.C.F.; Gastil, M. Dual-season mapping of wetland inundation and vegetation for the central Amazon region. Remote Sens. Environ. 2003, 87, 404–428. [Google Scholar] [CrossRef]
- Hess, L.L.; Melack, J.M.; Filoso, S.; Wang, Y. Delineation of inundated area and vegetation along the Amazon floodplain with the SIR-C synthetic aperture radar. IEEE Trans. Geosci. Remote Sens. 1995, 33, 896–904. [Google Scholar] [CrossRef]
- Richey, J.E.; Melack, J.M.; Aufdenkampe, A.K.; Ballester, V.M.; Hess, L.L. Outgassing from Amazonian rivers and wetlands as a large tropical source of atmospheric CO2. Nature 2002, 416, 617–620. [Google Scholar] [CrossRef] [PubMed]
- Melack, J.M.; Hess, L.L. Remote sensing of the distribution and extent of wetlands in the Amazon basin. In Amazonian Floodplain Forests: Ecophysiology, Ecology, Biodiversity and Sustainable Management; Junk, W.J., Piedade, M., Wittmann, F., Schöngart, J., Parolin, P., Eds.; Springer: New York, NY, USA, 2011; pp. 43–59. [Google Scholar]
- Melton, J.R.; Wania, R.; Hodson, E.L.; Poulter, B.; Ringeval, B.; Spahni, R.; Bohn, T.; Avis, C.A.; Beerling, D.J.; Chen, G.; et al. Present state of global wetland extent and wetland methane modeling: conclusions from a model inter-comparison project. Biogeosciences 2013, 10, 753–788. [Google Scholar] [CrossRef]
- Cox, P.M.; Betts1, R.A.; Collins, M.; Harris, P.P.; Huntingford, C.; Jon, C.D. Amazonian forest dieback under climate-carbon cycle projections for the 21st century. Theor. Appl. Climatol. 2004, 78, 137–156. [Google Scholar] [CrossRef]
- Huntingford, C.; Fisher, R.A.; Mercado, L.; Booth, B.; Sitch, S.; Harris, P.P.; Cox, P.M.; Jones, C.D.; Betts, R.A.; Malhi, Y.; et al. Towards quantifying uncertainty in predictions of Amazon “dieback”. Phil. Trans. R. Soc. B 2008. [Google Scholar] [CrossRef] [Green Version]
- Lenton, T.M.; Held, H.; Kriegler, E.; Hall, J.W.; Lucht, W.; Rahmstorf, S.; Schellnhuber, H.J. Tipping elements in the Earth’s climate system. Proc. Natl. Acad. Sci. USA 2008, 105, 1786–1793. [Google Scholar] [CrossRef] [PubMed]
- Smith, L.C. Satellite remote sensing of river inundation area, stage, and discharge: A review. Hydrol. Process. 1997, 11, 1427–1439. [Google Scholar] [CrossRef]
- Vanderbilt, V.C.; Perry, G.L.; Livingston, G.P.; Ustin, S.L.; Barrios, M.C.D.; Bréon, F.-M.; Leroy, M.M.; Balois, J.-Y.; Morrissey, L.A.; Shewchuk, S.R.; et al. Inundation discriminated using sun glint. IEEE Trans. Geosci. Remote Sens. 2002, 40, 1279–1287. [Google Scholar] [CrossRef]
- Prigent, C.; Papa, F.; Aires, F.; Rossow, W.B.; Matthews, E. Global inundation dynamics inferred from multiple satellite observations, 1993–2000. J. Geophys. Res. 2007, 112, D12107. [Google Scholar] [CrossRef]
- Alsdorf, D.; Han, S.-C.; Bates, P.; Melack, J. Seasonal water storage on the Amazon floodplain measured from satellites. Remote Sens. Environ. 2010, 114, 2448–2456. [Google Scholar] [CrossRef]
- Lee, H.R.; Beighley, E.; Alsdorf, D.; Jung, H.C.; Shum, C.K.; Duan, J.; Guo, J.; Yamazak, D.; Andreadis, K. Characterization of terrestrial water dynamics in the Congo Basin using GRACE and satellite radar altimetry. Remote Sens. Environ. 2011, 115, 3530–3538. [Google Scholar] [CrossRef]
- Hess, L.L.; Melack, J.M.; Simonett, D.S. Radar detection of flooding beneath the forest canopy: A review. Int. J. Remote Sens. 1990, 11, 1313–1325. [Google Scholar] [CrossRef]
- Kasischke, E.S.; Bourgeau-Chavez, L.L. Monitoring South Florida wetlands using ERS-1 SAR imagery. Photogramm. Eng. Remote Sens. 1997, 33, 281–291. [Google Scholar]
- Kasischke, E.S.; Smith, K.B.; Bourgeau-Chavez, L.L.; Romanowicz, E.A.; Brunzell, S.; Richardson, C.J. Effects of seasonal hydrologic patterns in South Florida wetlands on radar backscatter measured from ERS-2 SAR imagery. Remote Sens. Environ. 2003, 88, 423–441. [Google Scholar] [CrossRef]
- Frappart, F.; Seyler, F.; Martinez, J.-M.; Leon, J.G.; Cazenave, A. Floodplain water storage in the Negro River basin estimated from microwave remote sensing of inundation area and water levels. Remote Sens. Environ. 2005, 99, 387–399. [Google Scholar] [CrossRef] [Green Version]
- Arnesen, A.S.; Silva, T.S.F.; Hess, L.L.; Novo, E.M.L.M.; Rudorff, C.M.; Chapman, B.D.; McDonald, K.C. Monitoring flood extent in the lower Amazon River floodplain using ALOS/PALSAR ScanSAR images. Remote Sens. Environ. 2013, 130, 51–61. [Google Scholar] [CrossRef]
- Rosenqvist, A.; Shimada, M.; Chapman, B.; Freeman, A.; De Grandi, G.; Saatchi, S.; Rauste, Y. The Global Rain Forest Mapping project—A review. Int. J. Remote Sens. 2000, 21, 1375–1387. [Google Scholar] [CrossRef]
- Farr, T.G.; Rosen, P.A.; Caro, E.; Crippen, R.; Duren, R.; Hensley, S.; Kobrick, M.; Paller, M.; Rodriguez, E.; Roth, L.; et al. The Shuttle Radar Topography Mission. Rev. Geophys. 2007, 45. [Google Scholar] [CrossRef]
- NASA Ames Advanced Supercomputing Division. Available online: http://www.nas.nasa.gov (accessed on 15 April 2014).
- Rosenqvist, A.; Shimada, M.; Ito, N.; Watanabe, M. ALOS PALSAR: A pathfinder mission for global-scale monitoring of the environment. IEEE Trans. Geosci. Remote Sens. 2007, 45, 3307–3316. [Google Scholar] [CrossRef]
- Rosenqvist, A.; Shimada, M.; Watanabe, M. ALOS PALSAR: Technical outline and mission concepts. In Proceedings of the 4th International Symposium on Retrieval of Bio- and Geophysical Parameters from SAR Data for Land Applications, Innsbruck, Austria, 16–19 November 2004.
- Shuttle Radar Topography Mission. Available online: http://www2.jpl.nasa.gov/srtm (accessed on 22 January 2015).
- Rodriguez, E.; Morris, C.S.; Belz, J.E.; Chapin, E.C.; Martin, J.M.; Daffer, W.; Hensley, S. An Assessment of the SRTM Topographic Products; Technical Report JPL D-31639; Jet Propulsion Laboratory: Pasadena, CA, USA, 2005; p. 143. [Google Scholar]
- Rosenqvist, A.; Shimada, M.; Chapman, B.; McDonald, K.; De Grandi, G.; Jonsson, H.; Williams, C.; Rauste, Y.; Nilsson, M.; Sango, D.; et al. An overview of the JERS-1 SAR Global Boreal Forest Mapping (GBFM) project. In Proceedings of the 2004 IEEE International Symposium on Geoscience and Remote Sensing (IGARSS’04), Anchorage, AK, USA, 20–24 September 2004.
- Kawanishi, T.; Sezai, T.; Ito, Y.; Imaoka, K.; Takeshima, T.; Ishido, Y.; Shibata, A.; Miura, M.; Inahata, H.; Spencer, R.W. The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), NASDA’s contribution to the EOS for global energy and water cycle studies. IEEE Trans. Geosci. Remote Sens. 2003, 41, 184–194. [Google Scholar] [CrossRef]
- NOAA Office of Satellite and Product Operations. Available online: http://www.ospo.noaa.gov/Products/land/smops/sensors_AMSRE.html (accessed on 22 January 2015).
- Ulander, L.M.H. Radiometric slope correction of synthetic-aperture radar images. IEEE Trans. Geosci. Remote Sens. 1996, 34, 1115–1122. [Google Scholar] [CrossRef]
- Shimada, M.; Isoguchi, O. JERS-1 SAR mosaics of Southeast Asia using calibrated path images. Int. J. Remote Sens. 2002, 23, 1507–1526. [Google Scholar] [CrossRef]
- Werner, C.; Wegmüller, U.; Strozzi, T.; Wiesmann, A. Gamma SAR and interferometric processing software. In Proceedings of the ERS-ENVISAT Symposium, Gothenburg, Sweden, 16–20 October 2000.
- Gabriel, A.K.; Goldstein, R.M. Crossed orbit interferometry: Theory and experimental results from SIR-B. Int. J. Remote Sens. 1988, 9, 857–872. [Google Scholar] [CrossRef]
- Shimada, M. Ortho-rectification and slope correction of SAR data using DEM and its accuracy evaluation. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2010, 3, 657–671. [Google Scholar] [CrossRef]
- Lucas, R.; Armston, J.; Fairfax, R.; Fensham, R.; Accad, A.; Carreiras, J.; Kelley, J.; Bunting, P.; Clewley, D.; Bray, S.; et al. An evaluation of the ALOS PALSAR L-band backscatter—Aboveground biomass relationship Queensland, Australia: Impacts of surface moisture condition and vegetation structure. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2010, 3, 576–593. [Google Scholar] [CrossRef]
- Martinez, J.-M.; Thuy Le, T. Mapping of flood dynamics and spatial distribution of vegetation in the Amazon floodplain using multitemporal SAR data. Remote Sens. Environ. 2007, 108, 209–223. [Google Scholar] [CrossRef]
- Telmer, K.H.; Costa, M.P.F. SAR-based estimates of the size distribution of lakes in Brazil and Canada: A tool for investigating carbon in lakes. Aquat. Conserv. Mar. Freshw. Ecosyst. 2007, 17, 289–304. [Google Scholar] [CrossRef]
- ESA GlobCover. Available online: http://due.esrin.esa.int/globcover (accessed on 15 April 2014).
- LPDAAC. NASA Shuttle Radar Topography Mission Water Body Data Shapefiles & Raster Files. Available online: https://lpdaac.usgs.gov/products/measures_products_table/srtmswbd (accessed on 22 January 2015).
- Chapman, B.; Siqueira, P.; Freeman, A. The JERS Amazon Multi-Season Mapping Study (JAMMS): Observation strategies and data characteristics. Int. J. Remote Sens. 2002, 23, 1427–1446. [Google Scholar] [CrossRef]
- Siqueira, P.; Chapman, B.; McGarragh, G. The creation and interpretation of the multiseason JERS-1 SAR mosaic over South America. Remote Sens. Environ. 2003, 87, 389–403. [Google Scholar] [CrossRef]
- Chapman, B.; Taylor, V.; Rosenqvist, A. Rain Forest Mapping Project to release CD-ROMs. EOS Trans. Am. Geophys. Union 1998, 79, 417. [Google Scholar] [CrossRef]
- Yongwei, S.; Alsdorf, D.E. Automated georeferencing and orthorectification of Amazon basin-wide SAR mosaics using SRTM DEM data. IEEE Trans. Geosci. Remote Sens. 2005, 43, 1929–1940. [Google Scholar] [CrossRef]
- Zhang, L.; Wu, W.; Zhou, Q.; Chen, Z.; Li, Z. Assess the accuracy of the Globcover cultivated land data in Northeast China. In Proceedings of the 2012 First International Conference on Agro-Geoinformatics (Agro-Geoinformatics), Shanghai, China, 2–4 August 2012.
- Kalliola, R.; Puhakka, M.; Salo, J.; Tuomisto, H.; Ruokolainen, K. The dynamics, distribution and classification of swamp vegetation in Peruvian Amazonia. Ann. Bot. Fenn. 1991, 28, 225–239. [Google Scholar]
- Schroeder, R.; Rawlins, M.; McDonald, K.C.; Podest, E.; Zimmermann, R.; Kueppers, M. Satellite microwave remote sensing of North Eurasian inundation dynamics: Development of coarse-resolution products and comparison with high-resolution synthetic aperture radar data. Environ. Res. Lett. 2010, 5, 015003. [Google Scholar] [CrossRef]
- JPL Wetlands Website. Available online: http://wetlands.jpl.nasa.gov (accessed on 8 May 2014).
- ASF Wetlands Portal. Available online: https://portal.asf.alaska.edu/wetlands (accessed on 8 May 2014).
© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Chapman, B.; McDonald, K.; Shimada, M.; Rosenqvist, A.; Schroeder, R.; Hess, L. Mapping Regional Inundation with Spaceborne L-Band SAR. Remote Sens. 2015, 7, 5440-5470. https://doi.org/10.3390/rs70505440
Chapman B, McDonald K, Shimada M, Rosenqvist A, Schroeder R, Hess L. Mapping Regional Inundation with Spaceborne L-Band SAR. Remote Sensing. 2015; 7(5):5440-5470. https://doi.org/10.3390/rs70505440
Chicago/Turabian StyleChapman, Bruce, Kyle McDonald, Masanobu Shimada, Ake Rosenqvist, Ronny Schroeder, and Laura Hess. 2015. "Mapping Regional Inundation with Spaceborne L-Band SAR" Remote Sensing 7, no. 5: 5440-5470. https://doi.org/10.3390/rs70505440