Global land cover mapping from MODIS: algorithms and early results

Friedl, M. A.; McIver, D.K.; Hodges, J.C.F.; Zhang, X.Y; Muchoney, D.; Strahler, Alan H.; Woodcock, Curtis E.; Gopal, Sucharita; Schneider, Annemarie; Cooper, Alan; Baccini, Alessandro; Gao, Feng; Schaaf, Crystal B.

doi:10.1016/s0034-4257(02)00078-0

Cited by 2,327 publications

(1,467 citation statements)

References 32 publications

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“…Atmospheric pressure was obtained using mean elevations from the ETOPO1 global digital elevation model 41 in each 1° cell and correcting using the ideal gas law 34 . Land cover classes were obtained from the NASA MODIS satellite product MOD12 42 and monthly means of leaf area index for the period 2001-2012 were obtained from the MODIS-derived Global Land Surface Satellite leaf area index data set 43,44 , averaged over the period [2001][2002][2003][2004][2005][2006][2007][2008][2009][2010][2011][2012]. All data at a higher resolution than 1° were aggregated to mean values at 1° resolution before calculation of PET.…”

Section: Methodsmentioning

confidence: 99%

Water balance creates a threshold in soil pH at the global scale

Slessarev

Lin

Bingham

et al. 2016

Nature

420

255

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Soil pH regulates the capacity of soils to store and supply nutrients, and thus contributes substantially to controlling productivity in terrestrial ecosystems 1 . However, soil pH is not an independent regulator of soil fertility-rather, it is ultimately controlled by environmental forcing. In particular, small changes in water balance cause a steep transition from alkaline to acid soils across natural climate gradients 2,3 . Although the processes governing this threshold in soil pH are well understood, the threshold has not been quantified at the global scale, where the influence of climate may be confounded by the effects of topography and mineralogy. Here we evaluate the global relationship between water balance and soil pH by extracting a spatially random sample (n = 20,000) from an extensive compilation of 60,291 soil pH measurements. We show that there is an abrupt transition from alkaline to acid soil pH that occurs at the point where mean annual precipitation begins to exceed mean annual potential evapotranspiration. We evaluate deviations from this global pattern, showing that they may result from seasonality, climate history, erosion and mineralogy. These results demonstrate that climate creates a nonlinear pattern in soil solution chemistry at the global scale; they also reveal conditions under which soils maintain pH out of equilibrium with modern climate.Climate controls many aspects of soil chemistry, affecting soil pH (ref. 4). Alkaline soils are known to be common in arid climates, while acid soils are known to be common in humid climates 1 . Surprisingly, however, the global-scale mechanisms governing this pattern remain broadly defined, and untested by direct observation. What are the dominant chemical equilibria that constrain soil pH? What aspect of climate defines the transition between alkaline and acid soils, and is the transition linear? The answers to these questions are fundamental to understanding soil development and surface geochemistry at the global scale. Furthermore, achieving this understanding may prove essential for representing soils in models of the terrestrial biosphere, given that soil pH controls many aspects of soil fertility 5,6 . Here we illustrate that simple geochemical and hydrological concepts can be used to build a mechanistic understanding of soil pH at the global scale.Interpretations of acid-titration experiments indicate that the soil pH is typically most strongly buffered by equilibrium with two secondary minerals: calcite (CaCO 3 ), or gibbsite (Al(OH) 3 ) 7,8 Fig. 1).Local studies of climate gradients have shown that the relative importance of these two buffers is determined by leaching, which removes Ca 2+ from the soil 2,3,8,9 . In climates where evaporative demand exceeds precipitation, leaching rates are low, and dissolved Ca 2+ accumulates as CaCO 3 -buffering soil pH near 8.2 (ref. 4). Conversely, in climates where precipitation exceeds evaporative demand, water leaches through the soil, removing Ca 2+ and allowing accumulation of relatively immobile...

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Section: Methodsmentioning

confidence: 99%

Water balance creates a threshold in soil pH at the global scale

Slessarev

Lin

Bingham

et al. 2016

Nature

420

255

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“…Decision trees are widely utilized in large area mapping of land cover (Friedl et al, 2002;Hansen et al, 2005) and urban areas where complex spectral datasets require robust algorithms.…”

Section: Classificat Io N O F 2010 Ur Ban Ext Entmentioning

confidence: 99%

“…The training data were built upon the System for Terrestrial Ecosystem Parameterization (STEP) database, a set of >2000 exemplars collected from Google Earth and Landsat data for 17 classes (Friedl et al, 2002;. The database was augmented with sites drawn from a stratified random sample of 250 locations within the East-Southeast Asia region (Figure 3a, b).…”

Section: Classificat Io N O F 2010 Ur Ban Ext Entmentioning

confidence: 99%

Detecting change in urban areas at continental scales with MODIS data

Mertes

Schneider

Sulla‐Menashe

et al. 2015

Remote Sensing of Environment

151

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Abstract. Urbanization is one of the most important components of global environmentalchange, yet most of what we know about urban areas is at the local scale. Remote sensing of urban expansion across large areas provides information on the spatial and temporal patterns of growth that are essential for understanding differences in socioeconomic and political factors that spur different forms of development, as well the social, environmental, and climatic impacts that result. However, mapping urban expansion globally is challenging: urban areas have a small footprint compared to other land cover types, their features are small, they are heterogeneous in both material composition and configuration, and the form and rates of new development are often highly variable across locations. Here we demonstrate a new methodology for monitoring urban land expansion at continental to global scales using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The new method focuses on resolving the spectral and temporal ambiguities between urban/non-urban land and stable/changed areas by: (1) spatially constraining the study extent to known locations of urban land; (2) integrating multi-temporal data from multiple satellite data sources to classify ca 2010 urban extent; and (3) mapping newly built areas (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010) within the 2010 urban land extent using a multi-temporal composite change detection approach based on MODIS 250 m annual maximum enhanced vegetation index (EVI). We test the method in 15 countries in East-Southeast Asia experiencing different rates and manifestations of urban expansion. A two-tiered accuracy assessment shows that the approach characterizes urban change across a variety of socicoeconomic/political and ecological/climatic conditions with good accuracy (70-91% overall accuracy by country, 69-89% by biome). The 250 m EVI data not only improve the classification results, but are capable of distinguishing between change and no-change areas in urban areas. Over 80% of ii the error in the change detection is related to human decision making or error propagation, rather than algorithm error. As such, these methods hold great potential for routine monitoring of urban change, as well as provide a consistent and up-to-date dataset on urban extent and expansion for a rapidly evolving region.

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“…Grassland shows a marginally higher percentage of the D1 and D2 variables, which is consistent with our physical understanding as they are fed by shallow soil moisture which varies at high temporal frequencies. While all are defined differently, the three land use types have overlapping characteristics, most commonly the widespread presence of short grasses (Friedl et al, 2002) and shallow root systems. These short grasses respond to changes in the shallow top layer of the soil, which is influenced at high temporal frequencies by rainfall events and evaporation.…”

Section: Resultsmentioning

confidence: 99%

Large-scale vegetation responses to terrestrial moisture storage changes

Andrew

Guan

Batelaan

2017

Hydrol. Earth Syst. Sci.

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Abstract. The normalised difference vegetation index (NDVI) is a useful tool for studying vegetation activity and ecosystem performance at a large spatial scale. In this study we use the Gravity Recovery and Climate Experiment (GRACE) total water storage (TWS) estimates to examine temporal variability of the NDVI across Australia. We aim to demonstrate a new method that reveals the moisture dependence of vegetation cover at different temporal resolutions. Time series of monthly GRACE TWS anomalies are decomposed into different temporal frequencies using a discrete wavelet transform and analysed against time series of the NDVI anomalies in a stepwise regression. The results show that combinations of different frequencies of decomposed GRACE TWS data explain NDVI temporal variations better than raw GRACE TWS alone. Generally, the NDVI appears to be more sensitive to interannual changes in water storage than shorter changes, though grassland-dominated areas are sensitive to higher-frequencies of water-storage changes. Different types of vegetation, defined by areas of land use type, show distinct differences in how they respond to the changes in water storage, which is generally consistent with our physical understanding. This unique method provides useful insight into how the NDVI is affected by changes in water storage at different temporal scales across land use types.

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Global land cover mapping from MODIS: algorithms and early results

Cited by 2,327 publications

References 32 publications

Water balance creates a threshold in soil pH at the global scale

Water balance creates a threshold in soil pH at the global scale

Detecting change in urban areas at continental scales with MODIS data

Large-scale vegetation responses to terrestrial moisture storage changes

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