Capability of C-Band SAR for Operational Wetland Monitoring at High Latitudes
Abstract
:1. Introduction
2. Material and Methods
2.1. ENVISAT ASAR Wide Swath Data
2.2. Study Area
2.3. Saturated Areas Mapping
2.4. Validation
3. Results
4. Assessment and Discussion
- Compared with the Wetland type map [17], mainly oligotrophic and mixed peatlands were mapped. However, only 23% of the oligotrophic peatlands coincided with hSW areas. Seventy percent of the peatland classes in [17] is classified as “other” with the approach of this study. Since in the approach of this study only hSW areas are mapped (and not peatland), local and regional variations in the surface and soil moisture are expected between years. The difference in spatial resolution more reasonably explains the low overlap of identified peatlands. The high resolution mapping with SAR distinguishes smaller wetland patches from each other and from surrounding land cover. These small variations or land cover changes are not captured in the generalized maps, which are the source of the WSL database. This is supported by the fact that a large number of small ponds do not occur in the classification in [17] (Figure 11). Thus, the map in [17] might be overestimating oligotrophic peatland.
- Areas classified as hSW show a mean soil carbon content of 46 kg·C·m−2 when compared with the Soil Organic Carbon Map [32], while regions with abundant open water bodies and seasonally inundated areas show a mean of 30 kg·C·m−2 and other land cover 33 kg·C·m−2. Recognized wetland locations point to significant accumulation of organic carbon, which is a potential source of methane (see Figure 8).
- A direct comparison of hSW areas with the GBFM map shows significant differences in some areas. The major class of the GBFM map contained by the classified hSW area of the decision tree approach of this study is class 4 (‘forest med’). Kropacek et al. [33] define the class of bogs as follows: “The surface of bogs is usually formed by open water, grass, shrubs and even patches of woods. The association of a single backscatter class to bogs is therefore not possible. The class wetlands in the classification of this study represents areas of wet soil covered with low biomass vegetation.” This land cover map focuses on forest classification not primarily on wetlands. Although L-band backscatter is able to penetrate the forest vegetation and is therefore able to map temporarily inundated forests, the class definition constrains mapping of hSW area. In a ten years period, land cover changes are likely to occur (GBFM: 1996/97, saturated area: 2007). The maps were thus compared with the ESA DUE Permafrost burnt area map [38] to investigate differences between the maps. In the test region of the Lena basin, fire events caused a new forming of hSW area in former forest areas (Figure 12). This region is underlain by continuous permafrost (see Figure 2). Two Landsat images (RGB 3-2-1, path 127, row 14, before (2005-06-27) and after (2007-07-03) forest fire) show a similar structure.
- The Great Vasyugan Mire of alternating mire phytocoenoses, located between the Iksa and Bakchar Rivers [39], is well covered by the classification of the hSW area (Figure 13). Differences in classifications can be explained by 8 years of time difference or different weather conditions in these years (e.g., wetter in 2007), or confusion with forests or herbaceous land cover.
- The hSW area distribution was compared against the Regional Wetland Product in the transects (Figure 3) of the Ob and the Lena test regions. The regional wetland product provides the areal extent of wetland for the boreal zone for one year (from July 2007 to June 2008), on an equal area grid of 25 km (equal area grid of 0.25° at the equator), with a 10-day temporal sampling [7]. The comparison which included the dynamics of open water of [11] confirms that open water surfaces are underestimated in areas with tundra ponds in the regional product. The differences over the Lena Delta are however strongly impacted by masking of the Lena river channels. In boreal areas, the ASAR WS information on saturated and open inundated areas enables the discrimination between the different components that contribute to the regional wetland fraction (compare Figure 9).
- The Inventory of Wetland Area [35] distinguishes classes with respect to land cover compositions, e.g., tree cover and pools, which result in wetland complexes. Wetland complexes agree in most parts with the classification of this study (compare Figure 14: “forested shrubs- and moss-dominated mires” agree with ”areas with high degree of saturation”, “sphagnum dominated bogs with pools and open stand trees” agree with regions with a mixture of “water bodies” and “areas with high degree of saturation”.) Bartsch et al. [10] suggested the use of metrics such as water bodies density for tundra wetland complex retrieval. A combined use of those two classes may lead to the delineation of classes as used in [35]. Validation problems with the data set occur due to different acquisition date of underlying imagery, spatial detail and the thematic resolution.
- Geo-Wiki ([36,37], http://www.geo-wiki.org/) is an on-line tool to visualize and validate spatial datasets based on the Google Earth imagery ( http://www.google.com/earth/). Besides imagery, Geo-Wiki provides some additional information that help to validate a dataset: land cover class by GLC2000, MODIS land cover and GlobCover as well as NDVI seasonal profile. In the particular case study, we have checked 465 points randomly distributed over a subset of the hSW area classification (Extent: SV in Figure 3) whether wetlands are observed there or not. Eighty percent of validation points confirm our area of hSW area. Taking into account a subset of validation points with a high reliability on distinguished land cover, we got an accuracy of 86%. The underlying Google Earth imagery was taken in 2005/2006.
5. Conclusions
Acknowledgments
References
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Product | Data-Type | Resolution | Comments |
---|---|---|---|
(1) Wetland type map [17], Coverage: Western Siberia | polygons | Digitized from 1: 1 Mio and 1: 2.5 Mio maps | Generalized Shape boundaries lead to overestimation of wetlands, the file is compiled of different data sets, with the latest set of the year 1999. |
(2) Soil Organic Carbon Map [32], Coverage: Russia | raster | 1 km | Dataset was used to compare distribution of mapped areas against soil carbon accumulation. |
(3) Global Boreal Forest Mapping project [33], Coverage: Boreal Zone of North America, Siberia, Europe | raster | 100 m | Focus of forest mapping, 1996/1997, L-band SAR based |
(4) Vasyugan Mire classification [34], Coverage: Centre of West Siberian Plain | raster | 30 m | Small, but detailed part of test region, Landsat 1999 |
(5) ALANIS Methane Regional Wetland Product ([7], http://www.alanis-methane.info), Coverage: Northern Eurasia | centre points | 25 km | Wetland fraction dynamics in 10-day intervals for 2007/2008, multi-sensor approach |
(6) Inventory of Wetland Area ([35]), Coverage: Western Siberia | polygons | Digitized from 1:2.5 Mio map, refined with 1:200,000 imagery | Spatial structure of wetland complexes, satellite data from 1995, 1999 and 2000 |
(7) GeoWiki ([36,37], http://www.geo-wiki.org), Coverage: global | raster | high to coarse | Google Earth imagery (mostly 2003–2010) |
Ramsar Convention on Wetlands: Inland wetlands (Ramsar Convention Secretariat, 2006 [45]) | Russian Classification System: Three main types of peatland regarding their development [22] |
---|---|
Non-forested peatlands (U): includes shrub or open bogs, swamps, fens | Eutrophic (Phragmites) |
Forested peatlands (Xp): peatswamp forests | Mesotrophic (Carex-hypnum and forest) |
Oligotrophic (Sphagnum) | |
Tundra wetlands (Vt): includes tundra pools, temporary waters from snowmelt |
Share and Cite
Reschke, J.; Bartsch, A.; Schlaffer, S.; Schepaschenko, D. Capability of C-Band SAR for Operational Wetland Monitoring at High Latitudes. Remote Sens. 2012, 4, 2923-2943. https://0-doi-org.brum.beds.ac.uk/10.3390/rs4102923
Reschke J, Bartsch A, Schlaffer S, Schepaschenko D. Capability of C-Band SAR for Operational Wetland Monitoring at High Latitudes. Remote Sensing. 2012; 4(10):2923-2943. https://0-doi-org.brum.beds.ac.uk/10.3390/rs4102923
Chicago/Turabian StyleReschke, Julia, Annett Bartsch, Stefan Schlaffer, and Dmitry Schepaschenko. 2012. "Capability of C-Band SAR for Operational Wetland Monitoring at High Latitudes" Remote Sensing 4, no. 10: 2923-2943. https://0-doi-org.brum.beds.ac.uk/10.3390/rs4102923