A Landsat Surface Reflectance Dataset for North America, 1990–2000

Masek, Jeffrey G.; Vermote, Éric; Saleous, Nazmi; Wolfe, Robert E.; Hall, Forrest G.; Huemmrich, K. F.; Gao, Feng; Kutler, J.; Lim, T.K.

doi:10.1109/lgrs.2005.857030

Cited by 1,425 publications

(844 citation statements)

References 21 publications

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“…Through visual examination of Landsat imagery and digital orthophotos, calibrated surface reflectance from the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) (Masek et a!., 2006). We used this surface reflectance image as reference for the Multivariate Alteration and Detection (MAD) relative radiometric normalization procedure (Canty et al, 2004).…”

Section: Preliminary Classificationmentioning

confidence: 99%

Quantification of impervious surface in the Snohomish Water Resources Inventory Area of Western Washington from 1972-2006

Powell

Cohen

Yang

et al. 2007

Remote Sensing of Environment

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A 34 year time series of Landsat imagery for a portion of Snohomish and King Counties, Washington (the Snohomish Water Resource Inventory Area (WRIA)) was analyzed to estimate the amount ofland that was converted into impervious surface as a result of urban and residential development. Spectral unmixing was used to determine the fractional composition of vegetation, open, and shadow for each pixel. Unsupervised and supervised classification techniques were then used to derive preliminary land cover maps for each time period. Digital orthophotos were used to create agricultural, forest management, high elevation, and riparian masks. In conjunction with established Urban Growth Areas (UGAs), these masks were utilized for the application of spatial rules that identified impervious surface as a surrogate for urban and residential development. Temporal rules, that minimized classification error, were developed based on each pixel's classified trajectory over the time series of imagery. Overall cross-date classification accuracy for impervious v. non-impervious surface was .95%. The results of the analysis indicate that the area of impervious surface in the Snohomish WRlA increased by 255% over 34 years, from 3285 ha in 1972 to 11,652 ha in 2006. This approach demonstrates the unique value of the 35 year Landsat archive for monitoring impervious surface trends in rapidly urbanizing areas.

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Section: Preliminary Classificationmentioning

confidence: 99%

Quantification of impervious surface in the Snohomish Water Resources Inventory Area of Western Washington from 1972-2006

Powell

Cohen

Yang

et al. 2007

Remote Sensing of Environment

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“…The respective MODIS bands have similar spectral response functions and are highly correlated with the six Landsat multispectral measurements [22] (Table 1). Terra and Landsat-7 are in the same orbit, with nadir observations by Terra MODIS occurring approximately 15 min after Landsat-7 ETM+ observations.…”

Section: Landsat Datamentioning

confidence: 92%

Assessment of MODIS BRDF/Albedo Model Parameters (MCD43A1 Collection 6) for Directional Reflectance Retrieval

et al. 2017

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Measurements of solar radiation reflected from Earth's surface are the basis for calculating albedo, vegetation indices, and other terrestrial attributes. However, the "bi-directional" geometry of illumination and viewing (i.e., the Bi-directional Reflectance Distribution Function (BRDF)) impacts reflectance and all variables derived or estimated based on these data. The recently released MODIS BRDF/Albedo Model Parameters (MCD43A1 Collection 6) dataset enables retrieval of directional reflectance at arbitrary solar and viewing angles, potentially increasing precision and comparability of data collected under different illumination and observation geometries. We quantified the ability of MCD43A1 Collection 6 for retrieving directional reflectance and compared the daily Collection 6 retrievals to those of MCD43A1 Collection 5, which are retrieved on an eight-day basis. Correcting MODIS-based estimates of surface reflectance from the illumination and viewing geometry of the Terra satellite (MOD09GA) to that of the MODIS Aqua (MYD09GA) overpass, as well as MCD43A4 Collection 6 and Landsat-5 TM images show that the BRDF correction of MCD43A1 Collection 6 results in greater consistency among datasets, with higher R 2 (0.63-0.955), regression slopes closer to unity (0.718-0.955), lower root mean squared difference (RMSD) (0.422-3.142), and lower mean absolute error (MAE) (0.282-1.735) compared to the Collection 5 data. Smaller levels of noise (observed as high-frequency variability within the time series) in MCD43A1 Collection 6 in comparison to Collection 5 corroborates the improvement of BRDF parameters time series. These results corroborates that the daily MCD43A1 Collection 6 product represents the anisotropy of surface features and results in more precise directional reflectance derivation at any solar and viewing geometry than did the previous Collection 5.

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“…The SR data are produced by the specialized software Landsat Ecosystem Disturbance Adaptive Processing System for Landsat 5-TM and L8SR for Landsat 8-OLI, developed by the Making Earth System Data Records for Use in Research Environments of the Goddard Space Flight Center of NASA and the University of Maryland [27].…”

Section: Datasetmentioning

confidence: 99%

Thresholding Algorithm Optimization for Change Detection to Satellite Imagery

Vázquez-Jiménez¹,

Ramos-Bernal²,

Calcerrada³

et al. 2018

Colorimetry and Image Processing

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To detect changes in satellite imagery, a supervised change detection technique was applied to Landsat images from an area in the south of México. At first, the linear regression (LR) method using the first principal component (1-PC) data, the Chi-square transformation (CST) method using first three principal component (PC-3), and tasseled cap (TC) images were applied to obtain the continuous images of change. Then, the threshold was defined by statistical parameters, and histogram secant techniques to categorize as change or unchanged the pixels. A threshold optimization iterative algorithm is proposed, based on the ground truth data and assessing the accuracy of a range of threshold values through the corresponding Kappa coefficient of concordance.Finally, to evaluate the change detection accuracy of conventional methods and the threshold optimization algorithm, 90 polygons (15,543 pixels) were sampled, categorized as real change/unchanged zones, and defined as ground truth, from the interpretation of color aerial photo slides aided by the land cover maps to obtain the omission/ commission errors and the Kappa coefficient of agreement. The results show that the threshold optimization is a suitable approach that can be applied for change detection analysis.

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A Landsat Surface Reflectance Dataset for North America, 1990–2000

Cited by 1,425 publications

References 21 publications

Quantification of impervious surface in the Snohomish Water Resources Inventory Area of Western Washington from 1972-2006

Quantification of impervious surface in the Snohomish Water Resources Inventory Area of Western Washington from 1972-2006

Assessment of MODIS BRDF/Albedo Model Parameters (MCD43A1 Collection 6) for Directional Reflectance Retrieval

Thresholding Algorithm Optimization for Change Detection to Satellite Imagery

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