Evaluating Potential of MODIS-based Indices in Determining “Snow Gone” Stage over Forest-dominant Regions
Abstract
:1. Introduction
2. Methods
2.1. General Description of the Study Area and Data Requirement
Natural subregion | Area (Sq. Km.) | Mean annual Temp. (°C) | Mean annual precip. (mm) | Dominant vegetation | No. of lookout towers* |
---|---|---|---|---|---|
Dry Mixedwood | 85,321 | 1.1 | 461 | Deciduous-dominant mixedwood | 2 |
Central Mixedwood | 167,856 | 0.2 | 478 | Deciduous-dominant mixedwood | 24 |
Lower Boreal Highlands | 55,615 | −1.0 | 495 | Early to mid-seral pure or mixed forests hybrids | 21 |
Upper Boreal Highlands | 11,858 | −1.5 | 535 | Conifer dominated | 11 |
Northern Mixedwood | 29,513 | −2.5 | 387 | Conifer dominated | 2 |
Boreal Subarctic | 11,823 | −3.6 | 512 | Conifer dominated (Picea mariana ) | 3 |
Upper Foothills | 21,537 | 1.3 | 632 | Conifer dominated | 15 |
Lower Foothills | 44,899 | 1.8 | 588 | Conifer-dominant mixedwood | 15 |
Alpine | 15,084 | −2.4 | 989 | Largely non-vegetated, shrublands | 5 |
Sub-Alpine | 25,218 | −0.1 | 755 | Mixed Conifer | 12 |
Montane | 8,768 | 2.3 | 589 | Populus, Pinus, Pseudotsuga, grasslands | 2 |
Athabasca Plain | 13,525 | −1.2 | 428 | Pinus, dunes largely unvegetated | 2 |
Kazan Uplands | 9,719 | −2.6 | 380 | Mainly rock barrens, pockets of Pinus, Betula, Populus | 1 |
2.2. Data Processing
- extracted the temporal dynamics of each of the indices at all of the lookout tower sites; and then generated subregion-specific average temporal dynamics for each of the indices;
- calculated the natural subregion-specific average SGN day using the ground-based observations; and
- compared the values obtained from steps (i) and (iii).
3. Results and Discussion
3.1. Qualitative Evaluation of the Remote Sensing-Based Indices in Predicting SGN Stage
3.2. Determining the Best Index in Predicting SGN Periods
- The ground-based observations were entirely on the basis of visual inspection, thus it highly depended on the experience of an operator to interpret the situation; and
- Spatial resolution of the NDWI’s and ground-based observations might not be in agreement in some instances.
3.3. Spatial Dynamics of the SGN Map
- In general, temperature decreases northwards in the northern hemisphere [13], so that the northward increment of SGN stages in our study would be expected.
- The natural subregions in the high elevation areas (i.e., alpine and sub-alpine as shown in polygon I; montane in the middle of polygon II; upper boreal highlands in the middle of polygon III; and sub-alpine in polygon IV) experienced relatively high SGN stages (i.e., in the range of 137–200 DOY). This is reasonable as the high elevation areas experience relatively cooler temperature regime, which influences the snow to stay relatively longer period of time.
4. Concluding Remarks
Acknowledgements
References and Notes
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Sekhon, N.S.; Hassan, Q.K.; Sleep, R.W. Evaluating Potential of MODIS-based Indices in Determining “Snow Gone” Stage over Forest-dominant Regions. Remote Sens. 2010, 2, 1348-1363. https://doi.org/10.3390/rs2051348
Sekhon NS, Hassan QK, Sleep RW. Evaluating Potential of MODIS-based Indices in Determining “Snow Gone” Stage over Forest-dominant Regions. Remote Sensing. 2010; 2(5):1348-1363. https://doi.org/10.3390/rs2051348
Chicago/Turabian StyleSekhon, Navdeep S., Quazi K. Hassan, and Robert W. Sleep. 2010. "Evaluating Potential of MODIS-based Indices in Determining “Snow Gone” Stage over Forest-dominant Regions" Remote Sensing 2, no. 5: 1348-1363. https://doi.org/10.3390/rs2051348