Assessing the Accuracy of Satellite-Derived Land-Cover Classification Using Historical Aerial Photography, Digital Orthophoto Quadrangles, and Airborne Video Data

Skirvin, S. M.; Kepner, William G.; Marsh, Stuart E.; Drake, S.; Maingi, John K.; Edmonds, Curtis M.; Watts, Christopher J.; Williams, David R.

doi:10.1201/9780203497586.ch9

Cited by 17 publications

(10 citation statements)

References 11 publications

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“…Care must also be taken in interpretation of these land cover changes. In the accuracy assessment of the classified cover maps by Skirvin et al [2004] they noted that both the producer and user accuracies for the mesquite woodland class were low for all four dates (80% and 30%, respectively, for 1973, and 65% and 40% for the other dates). In addition, they noted particular problems with the mesquite woodland class by noting, “it was likely that neither the spectral nor the spatial resolution of MSS imagery was adequate to distinguish the mesquite woodland class in a heterogeneous semiarid environment, where most pixels are mixtures of green and woody vegetation, standing litter, and soils of varying brightness” [ Skirvin et al , 2004, p. 127].…”

Section: Resultsmentioning

confidence: 99%

Event to multidecadal persistence in rainfall and runoff in southeast Arizona

Goodrich

Unkrich

Keefer

et al. 2008

Water Resources Research

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[1] Spatial and temporal rainfall variability over watersheds directly impacts the hydrologic response over virtually all watershed scales. Changes in the precipitation regime over decades due to some combination of inherent local variability and climate change may contribute to changes in vegetation, water supply, and, over longer timescales, landscape evolution. Daily, seasonal, and annual precipitation volumes and intensities from the dense network of rain gauges on the Agricultural Research Service, U. S. Department of Agriculture Walnut Gulch Experimental Watershed (WGEW) in southeast Arizona are evaluated for multidecadal trends in amount and intensity over a range of watershed scales (1.5 ha to 149 km 2 ) using observations from 1956 to 2006. Rainfall and runoff volume and rate variability are compared over the same spatial scales over a 40 year period . The major findings of this study are that spatial variability of cumulative precipitation decreases exponentially with time, and, on average, became spatially uniform after 20 years of precipitation accumulation. The spatial variability of high-intensity, runoff-producing precipitation also decreased exponentially, but the variability was still well above the measurement error after 51 years. There were no significant temporal trends in basin scale precipitation. A long-term decrease in runoff from 1966 to 1998 from ephemeral tributaries like the WGEW may be a critical factor in decreasing summer flows in the larger San Pedro due to changes in higher-intensity, runoff-producing rainfall.

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Section: Resultsmentioning

confidence: 99%

Event to multidecadal persistence in rainfall and runoff in southeast Arizona

Goodrich

Unkrich

Keefer

et al. 2008

Water Resources Research

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“…However, as no ground data exist for the earlier dates in the series, we assessed the classification accuracies for the 1987, 1996, and 2004 data using coincident high-resolution aerial imagery (table 1). This method provides an acceptable alternative to the field-based accuracy assessments, but successful assessment depends upon the image quality and expert interpretation of the high-resolution imagery (Skirvin et al 2004 were of higher quality than the 1996 and 1980 imagery, but all were generally of com parable quality and pixel resolution between years (table 1). Land-cover classes were interpreted from these high-resolution images by M. L. Villarreal, who is a trained photogrammetrist with more than 10 years experience interpreting aerial photographs from the region.…”

Section: Land-cover Map Accuracymentioning

confidence: 98%

Mapping and monitoring riparian vegetation distribution, structure and composition with regression tree models and post-classification change metrics

Villarreal

Leeuwen

Romo-León

2011

International Journal of Remote Sensing

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2012) Mapping and monitoring riparian vegetation distribution, structure and composition with regression tree models and post-classification change metrics, International Journal of Remote Sensing, 33:13, 4266-4290, Riparian systems have become increasingly susceptible to both natural and human disturbances as cumulative pressures from changing land use and climate alter the hydrological regimes. This article introduces a landscape dynamics monitoring pro tocol that incorporates riparian structural classes into the land-cover classification scheme and examines riparian change within the context of surrounding land-cover change. We tested whether Landsat Thematic Mapper (TM) imagery could be used to document a riparian tree die-off through the classification of multi-date Landsat images using classification and regression tree (CART) models trained with phys iognomic vegetation data. We developed a post-classification change map and used patch metrics to examine the magnitude and trajectories of riparian class change relative to mapped disturbance parameters. Results show that catchments where riparian change occurred can be identified from land-cover change maps; however, the main change resulting from the die-off disturbance was compositional rather than structural, making accurate post-classification change detection difficult.

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“…The Iterative Self-Organizing Data Analysis (ISODATA) classification in ESRI ArcGIS is a robust clustering algorithm for areas with sparse ground-truth data and is used initially to understand the distribution of pixels DNs within a mosaic (Ball and Hall, 1967;Liu and Mason, 2016). An exaggerated number of clusters (≥15) is established across the range of spectral values, and neighboring clusters are merged until the overlap between cluster quartiles is ≤1% ( Figure 4E) (Anderson and Cobb, 2004;Skirvin et al, 2004;Okeke and Karnieli, 2006;Bolles et al, 2017). A majority filter is applied to reclassify pixels where it can be reasonably assumed the pixel belongs to the surrounding cluster, producing a smoothing effect (Mather and Koch, 2011;Liu and Mason, 2016).…”

Section: Processing and Analysis Of Digitized Historical Imagerymentioning

confidence: 99%

Evaluating Landscape Degradation Along Climatic Gradients During the 1930s Dust Bowl Drought From Panchromatic Historical Aerial Photographs, United States Great Plains

Bolles

Forman

2018

Front. Earth Sci.

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The United States Great Plains (USGP) are some of the most productive rangelands globally and a significant carbon sink for the atmosphere, but grassland response to precipitation is highly variable and poorly constrained over time and space. There is a rich historical aerial photographic record of the USGP which provides an unparalleled view of past landscapes and allows for evaluation of surficial response to drought beyond the satellite record, such as during the 1930s Dust Bowl Drought (DBD). This study classified the extent and loci of surficial denudation from seamless mosaics of radiometrically corrected and georectified digitized aerial negatives acquired in the late 1930s from six counties distributed across USGP ecoregions. The dominant sources of degradation found for sites east of the 100th meridian are cultivated fields and fluvial deposits, associated with woody vegetation response to water availability in uncultivated areas. For sites to the west, denuded surfaces are predominantly eolian sandsheets and dunes, correlated with intensity of drought conditions and reduced plant diversity. Discrete spatial signatures of the drought are observed not only within the classically recognized southern Dust Bowl area, but also in the northern and central plains. Statistical analyses of site variability suggest landscape response to the DBD is most strongly influenced by the arid-humid divide and severity of precipitation and temperature anomalies. With a projected increase 21st century aridity, eolian processes cascading across western grasslands, like during the Dust Bowl, may significantly impact future dust particle emission and land and carbon storage management.

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Assessing the Accuracy of Satellite-Derived Land-Cover Classification Using Historical Aerial Photography, Digital Orthophoto Quadrangles, and Airborne Video Data

Cited by 17 publications

References 11 publications

Event to multidecadal persistence in rainfall and runoff in southeast Arizona

Event to multidecadal persistence in rainfall and runoff in southeast Arizona

Mapping and monitoring riparian vegetation distribution, structure and composition with regression tree models and post-classification change metrics

Evaluating Landscape Degradation Along Climatic Gradients During the 1930s Dust Bowl Drought From Panchromatic Historical Aerial Photographs, United States Great Plains

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