Remote Sensing and GIS Accuracy Assessment - Chapter 6 potx

... spectral bands and tasseled-cap bands were created in ERDAS Imagine 8.4. This resulted in one 6- band image for 19 86 (MSS spectral bands 1, 2, 3, 4, and tasseled-cap bands 1 and 2), a 10-band image ... Collection 79 6. 2.3 Data Processing 80 6. 2.4 Image Classification 81 6. 2.5 Accuracy Assessment 81 6. 3 Results and Discussion 82 6. 3.1 Classified Imagery and Land-Cover...

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... 42.3 56. 4 42.3 53.8 51.3 66 .7 4.1 100.0 46. 5 55 .6 60 .6 68.7 79.8 83.8 4.2 100.0 55.7 63 .9 72.1 78.7 85.2 88.5 4.3 100.0 27.2 43.0 29.8 48.2 64 .9 82.0 8.1 100.0 27.2 37.9 26. 2 36. 9 44.7 62 .1 8.2 ... 44.5 64 .1 43.8 64 .8 64 .8 79.7 8.5 100.0 31.3 46. 6 25.2 40.5 42.7 69 .5 9.1 100.0 44.8 55.2 49.0 61 .5 70.8 87.5 9.2 100.0 66 .3 73.9 63 .0 72.8 72.8 80.4 Total Percentage...

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... LLC 1 56 REMOTE SENSING AND GIS ACCURACY ASSESSMENT Figure 11.2 Conditional probabilities for forest (a), shrub (b), and rangeland (c), based on Gaussian maximum likelihood (GML), and corresponding ... Francis Group, LLC 1 46 REMOTE SENSING AND GIS ACCURACY ASSESSMENT remotely sensed imagery can evaluate the appropriateness of different maps on their part...

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... 6 0.00 0. 06 0.13 0.19 0.25 0.31 0.38 0.44 0.50 0. 56 0 .63 0 .69 0.75 0.81 0.88 0.94 1.00 0.00 0. 06 0.13 0.19 0.25 0.31 0.38 0.44 0.50 0. 56 0 .63 0 .69 0.75 0.81 0.88 0.94 1.00 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.74 0.32 0.35 0.37 0.40 0.43 0.45 0.48 0.51 0.54 0.57 0.59 0 .62 0 .65 0 .68 0.70 0.73 0. 76 L1443_C17.fm Page 244 Satur...

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... bias in classification accuracy assessment, Int. J. Remote Sens. , 17, 1 261 –1 266 , 19 96. Janssen, L.L.F. and F.J.M. van der Wel, Accuracy assessment of satellite derived land-cover data: a review, ... LLC 22 REMOTE SENSING AND GIS ACCURACY ASSESSMENT for accuracy assessment supposedly represent higher-quality data (i.e., less measurement error), so thes...

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... 46 REMOTE SENSING AND GIS ACCURACY ASSESSMENT crown), whorls, branches, and shoots. The TRAC instrument was developed at the Canada Centre for Remote Sensing (CCRS) to address canopy nonrandomness ... Group, LLC 56 REMOTE SENSING AND GIS ACCURACY ASSESSMENT Eidenshink, J.C. and R.H. Haas, Analyzing vegetation dynamics of land systems with satellite dat...

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... labeling accuracy assessment reference sites. L1443_C12.fm Page 167 Saturday, June 5, 2004 10:33 AM © 2004 by Taylor & Francis Group, LLC 168 REMOTE SENSING AND GIS ACCURACY ASSESSMENT ... 166 REMOTE SENSING AND GIS ACCURACY ASSESSMENT • How should the samples be chosen? The choice and distribution of samples, or sampling scheme, is ... Congalton and...

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... of global rule-to-rule comparison. For instance, the wetlands-to-forested upland possibility of a wet- lands-labeled pixel in a low -accuracy, wetlands-dominant area (rule 6- a) was double (0 .69 vs. 0.33) the ... ACCURACY AND ESTIMATING LANDSCAPE INDICATORS 183 Figure 13.3 presents six fuzzy cover-type-conversion maps of water-to-forested upland, devel- oped-to-forested upland, barren-t...

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... Ponderosa Pine-Mixed Conifer 23 3 13.0 16 69 .6 13 56. 5 17 Ponderosa Pine-Gambel Oak- Juniper/Pinyon-Juniper Complex 36 6 16. 7 20 55 .6 14 38.9 18 Ponderosa Pine-Pinyon-Juniper 39 2 5.1 29 74.4 27 69 .2 20 ... Pinyon-Juniper-Shrub Live Oak-Mixed Shrub Woodland Pinyon-Juniper (Mixed)/Mixed Chaparral-Scrub Woodland Pinyon-Juniper-Mixed Shrub Woodland Pinyon-Juniper-Mixed Grass-Scrub Woo...

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... 86 88 90 92 94 96 AWMPFD 0 5 10 15 20 82 84 86 88 90 92 94 96 MPFD −8 6 −4 −2 0 82 84 86 88 90 92 94 96 MSI −45 −40 −35 −30 −25 −20 −15 82 84 86 88 90 92 94 96 ED 0 30 60 90 120 150 82 84 86 ... 96 MNN −50 −40 −30 −20 −10 0 82 84 86 88 90 92 94 96 AWMPFD 2 4 6 8 10 82 84 86 88 90 92 94 96 MPFD −7 6 −5 −4 −3 −2 82 84 86 88 90 92 94 96 MSI −45 −40 −35 −30 −25 −20 −15 82...

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