Results of the classification are shown for two control ponds: Ducky. Strike Club North field (DSN - Figs. 6b,c,d) and Mud Slough Unit field 3b. (MS3b - Figs.
Multitemporal Wetland Delineation in the SeasonallyManaged San Joaquin River Basin Wetland Complex Olga Epshtein 1 and Nigel W.T. Quinn 2 1 Arizona
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State University, 2 Lawrence Berkeley National Laborator y 19 Sep 2011
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Fig 1: Chronosequence of seasonally-managed San Joaquin River Basin wetland flood up and drawdown, beginning in April 12th, 2011 (left-most panel) and ending June 17th 2012 (right-most panel). Seasonal management in the SJR Basin seeks to provide flooded overwintering ponds for migrating wildfowl on the Pacific Flyway.
III. Thematic Conversion and Initial Classification
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51 Landsat 7,5,3 RGB
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[1,51] [52,126] [127, 254] [0,255]
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Landsat 7,5,3 RGB
Band 5: Band 2 Ratio
Bands 5:2 Classification
Fig 3: ReSET surface temperature workflow diagram: point-scale surface temperature is calculated at each satellite image pixel as a function of incoming radiation, thermal satellite signal, and ground emissivity.
The means of Class 1 and Class 2 Wetlands (Figs. 9, 10) were significantly different at the 95% confidence level (P-value < α = 0.05) across all images: the two classes of surface temperature can be assumed to have come from distinct populations.
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Unsupervised classification assigns pixels to the two classes. As new pixels change the statistical makeup of a class, other pixels become reassigned, resulting in groups of self-similar pixels.
In this study we proposed a method to delineate the seasonally-managed wetland tract in the San Joaquin River Basin using Landsat ETM+ satellite imagery and a thermal hypothesis that assumed discernible surface temperature differences between flooded and terrestrial vegetation could be used to map the entire wetland footprint. Comparisons with field-derived surface area estimates show significant improvement over previous delineations which mapped open surface area only and did not account for flooded emergent vegetation.
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The ReSET surface temperature Image (discussed in Fig. 3) is masked to the Wetland pixels; iterative unsupervised classification is carried out for 2 classes with a 0.999 convergence threshold, initialized from statistics.
VI. Summary
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Inundated Terrestrial
Figs. 6 c,f: Open Water Wetland Upland Figs. 6 d,g: Wetland Class 1 Wetland Class 2 Fig 6 (a-g): 5:2 band ratio classification (Figs. 6c,f); multispectral band combination of original Landsat image (Fig 6a). Clipped to South Grasslands; showing Ducky Strike Club north field (Figs. 6b,c,d) and Mud Slough Unit field 3b (Figs. 6e,f,g) control ponds.
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Fig. 9: 24 Dec 11 DSN surface temperature means and Fig. 10: 02 Aug 11 DSN surface temperature means and variance across 4 classified categories. variance across 4 classified categories.
While further refinement of the classification methods is required to narrow the remaining error margins, the utility and efficiency of the methods make them a good preliminary step for wetland pond delineation in the study area. Acknowledgments
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Surface Temperature (°K)
Effects of vegetation (though unobserved for MS3b in Fig. 7) may limit the application of this methodology to periods of seasonal flood-up.
Monitored (total flooded) Thermal Classified
= =
Results of the classification are shown for two control ponds: Ducky Strike Club North field (DSN - Figs. 6b,c,d) and Mud Slough Unit field 3b (MS3b - Figs. 6e,f,g).
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Thermal classification combining both open water and classified flooded wetland area (Open Water + Wetland Class 1 – Figs. 7,8: dashed) helped to reduce the error in estimates of total flooded area from 38% to 8% at DSN, and from 63% to 13% at MS3b.
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Fig. 2: Conceptual diagram of the energy balance equation (Eq. 1), where 𝑅𝑛 is the incoming solar radiation, 𝐻 is the heat emitted into the atmosphere, 𝐺 is the heat flux into the surface, and 𝜆𝐸 is latent heat flux, composed of surface evaporation and plant transpiration. The energy balance equation partitions incoming radiation into emitted and absorbed components.
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Photo credit: Tres Rios Constructed Wetlands - Jorge Ramos: Wetland Ecosystem Ecology Lab, Arizona State University (2011).
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Fig. 8: Ducky Strike Club north pond (DSN) - open water delineation compared with monitored flooded area and classification results. One Landsat image pixel = 900 m2.
Open Water
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Ground Heat Flux
Fig. 7: Mud Slough Unit pond 3b (MS3b) - open water delineation compared with monitored flooded area and classification results (Thermal Classified = Open Water + Wetland Class 1).
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𝐺
A comparison of open water surface area (Figs. 7, 8: dotted line) to the total flooded area (Figs. 7, 8: solid line) calculated at two monitored control ponds (DSN and MS3b) shows the contribution of flooded wetland vegetation to the total flooded area. This area is underestimated by delineation limited to open water classification.
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𝐸𝑣𝑎𝑝𝑜𝑟𝑎𝑡𝑖𝑜𝑛
𝐻
6d
V. Result Validation and Thermal Hypothesis Performance
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𝑇𝑟𝑎𝑛𝑠𝑝𝑖𝑟𝑎𝑡𝑖𝑜𝑛
Sensible Heat Flux
𝑅𝑛
Following thematic conversion of the Landsat image (Figs. 6c,6f), the Wetland class is further classified into two categories: Wetland Class 1 Wetland Class 2
A comparison of scenes during floodup (Fig. 4) and drawdown (Fig. 5) show the effect of managed drainage not only on open water surface, but wetland area as well. As ponds drain and dry out, the 5:2 band ratio tracks an initially flooded pixel’s transition from open water, to inundated and dry wetland, to upland.
Fig 5: Multiband transformation for South Grasslands, June 17th, 2011. The This Landsat satellite image captures complete pond drainage during the summer drawdown period. Open water is both minimal and fragmented.
Pixels (count)
Incoming Solar Radiation
Latent Heat Flux
𝜆𝐸
(Eq. 1)
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= Open Water = Wetland = Upland = No Data
The initial 3-category classification (Figs. 4, 5: left panel) simplifies the process of tracking the seasonal changes in open water and moist-soil wetland area during flood-up and drawdown.
Fig 4: Multiband transformation for South Grasslands, October 21st, 2011. From left to right: Landsat image spectral band combination 7, 5, 3; Band 5: Band 2 output; classification into open water (blue), wetland (dark green), and upland (light green). Image captures start of fall flood-up.
Surface Temperature (°K)
𝑅𝑛 = 𝐻 + 𝜆𝐸 + 𝐺
6a
Results are compared with a 7, 5, 3 “natural color” multiband transformation of the original Landsat image (Figs. 4, 5: left panel).
II. Thermal Processing Spatially-distributed grids of surface temperature are calculated in ReSET (Remote Sensing of Evapotranspiration – surface temperature workflow shown in Fig. 3) using the surface energy balance equation (Eq. 1, Fig. 2):
IV. Thermal Analysis and Sub-Classification
The thematic raster (Figs. 4, 5: center) is classified into three categories (Figs. 4, 5: right panel):
A band ratio of Landsat satellite band 5 (midlength infrared) and band 2 (visible green) converts the Landsat image into a thematic integer raster (Figs. 4, 5: center), with pixel values (ratio values) in the range of [0,255]:
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Seasonally-managed wetlands within the San Joaquin River Basin were delineated over the course of pond flood-up and drawdown. The wetland footprint was derived from analysis of high-resolution (30 m) Landsat Enhanced Thematic Mapper Plus (ETM+) satellite imagery. Surface temperature was expected to provide a metric for classifying wetland vegetation as inundated or terrestrial – thereby capturing the extent of total flooded area. The project and its hypothesis were motivated by two coupled objectives: delineating each wetland pond in the study area in its entirety by capturing the surface area of open water and extent of inundation of emergent and terrestrial vegetation, and closing the water balance by calculating corresponding seepage, transpiration, and evaporative losses from each pond. An operational methodology for determining a dynamic wetland footprint will contribute to more accurate simulations of real-time evapotranspiration (ET), improving evapoconcentration estimates and leading to more precise accounting of wetland salt load discharge.
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I. Abstract
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Wetland Class 1
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This work was funded by the U.S. Department of Energy through the Workforce Development of Teachers and Scientists program, and supported by Lawrence Berkeley National Laboratory and the Center for Science and Engineering Education. ReSET was developed by Aymn Elhaddad and Luis Garcia together with the Integrated Decision Support Group at Colorado State University; we thank them for generously providing model resources and support. We acknowledge the contributions of Aymn Elhaddad (Integrated Decision Support Group, Colorado State University), Richard Snyder (UC Davis Cooperative Extension), Susan Ustin (UC Davis), and Janice Gillespie (CSU Bakersfield) and thank each one for providing valuable technical guidance. Finally we thank HEADS interns Virginia Lehr, Taiki Murakami, and Monique de Brito Guedes for their support throughout the summer.
