Linear downscaling from MODIS to landsat: connecting landscape composition with ecosystem functions

Journal Article · Wed Nov 06 00:00:00 EST 2019 · Landscape Ecology

DOI:https://doi.org/10.1007/s10980-019-00928-2· OSTI ID:1600743

Chen, Jiquan ^[1]; Sciusco, Pietro ^[1]; Ouyang, Zutao ^[1]; Zhang, Rong ^[1]; Henebry, Geoffrey M. ^[1]; John, Ranjeet ^[2]; Roy, David. P. ^[1]

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1. Michigan State Univ., East Lansing, MI (United States)
2. Univ. of South Dakota, Vermillion, SD (United States)

The open and free access to Landsat and MODIS products have greatly promoted scientific investigations on spatiotemporal change in land mosaics and ecosystem functions at landscape to regional scales. Unfortunately, there is a major mismatch in spatial resolution between MODIS products at coarser resolution (≥ 250 m) and landscape structure based on classified Landsat scenes at finer resolution (30 m). Based on practical needs for downscaling popular MODIS products at 500 m resolution to match classified land cover at Landsat 30 m resolution, we proposed an innovative modelling approach so that landscape structure and ecosystem functions can be directly studied for their interconnections. As a proof-of-concept of our downscaling approach, we selected the watershed of the Kalamazoo River in southwestern Michigan, USA as the testbed. MODIS products for three fundamental variables of ecosystem function are downscaled to ensure the approach can be extrapolated to multiple functional measurements. They are blue-sky albedo (0–1), evapotranspiration (ET, mm), and gross primary production (GPP, Mg C ha^-1 year^-1). An object-oriented classification of Landsat images in 2011 was processed to generate a land cover map for landscape structure. The downscaling model was tested for the five Level IV ecoregions within the watershed. We achieved satisfactory downscaling models for albedo, ET, and GPP for all five ecoregions. The adjusted R2 was > 0.995 for albedo, 0.915–0.997 for ET, and 0.902–0.962 for GPP. The estimated albedo, ET, and GPP values appear different in the region. The estimated albedo was the lowest for water (0.076–0.107) and the highest for cropland (0.166–0.172). Estimated ET was the highest for the built-up cover type (525.6–687.1 mm) and the lowest for forest (209.7–459.7 mm). The estimated GPP was the highest for the build-up cover type (8.65–9.85 Mg C ha^-1 year^-1) and the lowest for forest. Estimated values for albedo, ET, and GPP appear reasonable for their ranges in the Kalamazoo River region and are consistent with values reported in the literature. Despite these promising results, the downscaling approach relies on strong assumptions and can carry substantial uncertainty. Finally, it is only valid at a spatial scale where similar climate, soil, and landforms exist (i.e., values in isolated patches of the same cover type are similar). Plausibly, the uncertainties associated with each estimation, as well as the model residuals, can be explored for other pattern-process relationships within the landscape.

• Research Organization: Univ. of Wisconsin, Madison, WI (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Biological and Environmental Research (BER); National Aeronautics and Space Administration (NASA)
• Grant/Contract Number: SC0018409; FC02-07ER64494
• OSTI ID: 1600743
• Journal Information: Landscape Ecology, Vol. 34, Issue 12; ISSN 0921-2973
• Publisher: Springer
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
downscaling
MODIS
landsat
GPP
ET
albedo
Kalamazoo River watershed