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Extracting features of lake ice phenology over Canada from daily Extracting features of lake ice phenology over Canada from daily AVHRR observations AVHRR observations A. Davidson, S. Wang and R. A. Davidson, S. Wang and R. Latifovic Latifovic Canada Centre for Remote Sensing, Natural Resources Canada, Otta Canada Centre for Remote Sensing, Natural Resources Canada, Otta wa, ON, Canada. wa, ON, Canada. Email: Email: [email protected] [email protected] Changes in climate are expected to have profound affects on Canadian freshwater fisheries. However, studies of climate change impact on fisheries are hindered by the lack of data for analyzing the large spatial scale dynamics of lake water and ice regimes and their relationship with climate. Here, we demonstrate the utility of daily AVHRR 1km satellite data for extracting important features of lake ice phenology. These features correspond to (a) the earliest and latest dates of complete ice cover for lakes that freeze completely in the winter, (b) the earliest and latest dates of complete water cover for lakes that thaw completely in the summer, and (c) the dates of maximum (minimum) ice cover for lakes that do not freeze (thaw) completely in the winter (summer). We spectrally unmixed daily AVHRR observations to estimate the daily ice fractions of 30 large (> 100 Km2) Canadian lakes during the period 1988-1990, then used an automated approach to extract each lake ice phenology feature. We validated this approach using in situ lake ice observations taken from the Canadian Ice Database. Our validation shows a good agreement between ice phenology features extracted from the AVHRR data with ground observations. We then used the automatic extraction procedure to extract the important feature of lake ice phenology for 558 large Canadian lakes for the freeze/thaw periods of 2001/02 and 2002/03. A preliminary analysis of these data show that the features of lake ice phenology during these periods correlate with lake morphological characteristics to various degrees. Abstract Abstract Canadian freshwater fisheries are mainly concentrated in large lakes and are highly vulnerable to adverse climate change impacts. However, we know little of how climate change will impact these fisheries. Thus, the long-term monitoring of these resources is necessary if freshwater fisheries are to be managed sustainably. Remote sensing data collected at fine temporal resolutions can potentially provide an efficient and reliable way for the effects of climate change on Canadian lakes to be monitored at a national scale. The AVHRR sensors, flown onboard the NOAA series of satellites, have been collecting daily observations over Canada at a spatial resolution of 1km since the early 1980s. The Canada Centre for Remote Sensing (CCRS) has created an AVHRR data archive for Canada for 1981–2004 at 1km spatial resolution that is suitable for climate change studies [Latifovic, et al., 2005]. This data set is ideal for testing the utility of AVHRR data for monitoring the characteristics of lake ice phenology over long time periods. 1. Introduction 1. Introduction 2. Aims 2. Aims AVHRR satellite data: Obtained from the CCRS data archive. The archive contains 1-day clear-sky composites for a 5700 km × 4800 km area centred over Canada (1km resolution; LCC-projected). National lake cover map: Created from a vector spatial dataset that contained all of Canada’s mapped lakes and reservoirs (Source: Department of Fisheries and Oceans). Water bodies with surface areas > 100km 2 were extracted from this dataset to create a second dataset of 563 lakes and reservoirs. This map was then reprojected to an LCC-projected raster grid of 1km resolution. Non- water pixels not identified in the original map were further identified and eliminated if their annual maximum and minimum VIS and NIR albedo values fell outside the ranges expected for freshwater. In situ validation data: Obtained from the Canadian Ice Database [Lenormand et al., 2002]. Lake location and morphological data: Obtained from the Department of Fisheries and Oceans. Lake morphological characteristics (lake surface area, maximum lake depth, mean lake depth, lake elevation, lake drainage area, lake orientation, lake fetch) were available for 164 of the lakes contained in the national lake cover map. 3. Data Sources 3. Data Sources 4. Methods 4. Methods Good agreements were found between AVHRR-derived ice phenology features for 1988/89 and 1989/90 ice seasons and in situ measurements for the 30-lake test data set. Best results were achieved using a filter (window) size of approximately 20 days. This filter size best minimized the effects of within-season variations in ice fraction, and periods of missing data, while simultaneously accentuated between season changes in ice fraction. Best ice fraction threshold for determining the start of full water cover was IF = 0.10 and determining the start of full ice cover was IF = 0.55. 5. Validation 5. Validation Features of lake ice phenology were then extracted for 558 lakes for the 2001/02 and 2002/03 ice seasons using the validated algorithm. Morphological data exists for 81 of these lakes. Significant relationships were found between lake morphological characteristics and the earliest and latest dates of full water cover (ME and FS): a) ME was highly correlated with lake latitude, lake longitude, lake altitude, lake drainage area, lake surface area and lake fetch (Multiple R 2 = 0.79; RMSE = 9.51). b) FS was less-well correlated with lake latitude, lake longitude, lake surface area, lake fetch, lake maximum depth and lake volume (Multiple R 2 = 0.42; RMSE = 14.92). Significant relationships were found between lake morphological characteristics and the earliest and latest dates of full ice cover (FE and MS). a) FE was highly correlated with lake altitude, lake drainage area, lake surface area, lake orientation and average lake evaporation (Multiple R 2 = 0.62; RMSE = 12.57). b) MS was less-well correlated with lake latitude, lake longitude and lake orientation (Multiple R 2 = 0.53; RMSE = 10.4). Results suggest that important dates of lake ice phenology are dependent to varying degrees on lake morphological and hydrological characteristics. ME and FE were the dates of ice phenology that were best predicted by these variables. However, the FS and MS, and consequently, the length of the full ice and water seasons, could not be as easily correlated with lake morphological characteristics. Latifovic, R., A. P. Trishchenko, J. Chen, W. B. Park, K. V. Khlopenkov, R. Fernandes, D. Pouliot, C. Ungureanu, Y. Luo, S. Wang, A. Davidson, and J. Cihlar (2005), Generating historical AVHRR 1 km baseline satellite data records over Canada suitable for climate change studies, Canadian Journal of Remote Sensing, 31, 324-346. Lenormand, F., C. R. Duguay, and R. Gauthier (2002), Development of a historical ice database for the study of climate change in Canada, Hydrological Processes, 16, 3707-3722. 7. References 7. References 6. Relationships to Lake Morphology 6. Relationships to Lake Morphology The aims of this study were to: a) Develop and test an algorithm that estimates daily lake ice fraction from AVHRR reflectance data then extracts features of lake ice phenology from these data; and: b) Provide a preliminary assessment of the relationship of these features to lake morphological and locational characteristics. The features of ice phenology extracted from these data were: a) Earliest and latest dates of complete ice cover for lakes that freeze fully in winter; b) Earliest and latest dates of complete water cover for lakes that thaw fully in summer; c) Dates of max (min) ice cover for lakes that do not freeze (thaw) fully in winter (summer). (b) Estimate daily ice fraction for each lake by linear spectral unmixing of daily mean lake TSW reflectances. f i = (ρ - ρ w ) / (ρ i - ρ w ) where f w is the fraction of ice in the lake, ρ is the reflectance of a given lake at a given time, ρ w is the reflectance of pure water, and ρ i is the reflectance of pure ice. (c) Filter lake time series and extract dates of lake ice phenology using automated procedure. FS = freeze start (), FE = freeze end (), MS = melt start (), ME = melt end ().Red line corresponds to 80 th percentile filter used to identify times of FE and MS. Blue line corresponds to 20 th percentile filter used to identify times of ME and FS. (a) Extract daily mean TSW reflectances for each lake using lake cover mask and daily cloud-free AVHRR observations. + (d) Validate automated feature extraction algorithm for 30 lakes where in situ data is available and further modify algorithm where necessary. 0 50 100 150 200 250 300 0 50 100 150 200 250 300 Feature date (AVHRR) Feature date (in situ data) ? ID Lake ID Lake ID Lake ID Lake 111 Lac St Jean 214 Island Lake 285 Lac La Ronge 350 Teslin Lake 128 Attawapiskat Lake 230 Playgreen Lake 301 Primrose Lake 392 Great Slave Lake 130 Big Trout Lake 255 Lake Winnipeg 318 Cold Lake 463 Baker Lake 145 Lake of the Woods 259 Lake Athabasca 320 Lesser Slave Lake 576 Clearwater Lake 152 Lake Muskoka 261 Bid Quill Lake 325 Atlin Lake 591 Allumette Lake 155 Lake Nipissing 267 Churchill Lake 334 Okanagan Lake 623 Little Playgreen Lake 161 Red Lake - Bruce Channel 269 Cree Lake - Cable Bay 339 Stuart Lake 174 Lake Simcoe 274 Diefenbaker Lake 349 Lake Laberge (e) Use algorithm to extract lake ice phenology features from AVHRR time series for 558 lakes for the 2001/02 and 2002/03 ice seasons and correlate these features with lake morphological characteristics (where data available). Date of Freeze Start y = 0.6247x + 126.63 R 2 = 0.7414 270 290 310 330 350 370 390 270 290 310 330 350 370 390 Date of Freeze Start (In Situ) Date of Freeze Start (AVHRR) Date of Freeze End y = 0.6042x + 122.3 R 2 = 0.6177 200 250 300 350 400 450 500 200 250 300 350 400 450 500 Date of Freeze End (In Situ) Date of Freeze End (AVHRR) Date of Melt Start y = 0.9174x + 5.5029 R 2 = 0.5567 0 50 100 150 200 250 300 0 50 100 150 200 250 300 Date of Melt Start (In Situ) Date of Melt Start (AVHRR) Date of Melt End y = 0.9393x + 5.4944 R 2 = 0.8404 0 50 100 150 200 250 300 0 50 100 150 200 250 300 Date of Melt End (In Situ) Date of Melt End (AVHRR)
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