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classification result from esri's lulcm  (Esri inc)

 
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    Esri inc classification result from esri's lulcm
    Classification results in a typical urban area (104.09014 °E, 30.61249 °N), ( a ) is the composite Landsat image <t>from</t> <t>2020</t> for classification; ( b ) is the historical image from World Imagery Wayback, 12/16/2020; ( c ) is the classification result from <t>ESA’s</t> WC; ( d ) is the result from Google’s DW; ( e ), ESRI’s LULCM; ( f ), CAS’s GLC-FCS30; ( g ), WHU’s CLCD; ( h ) is the classification result of gradient tree boosting (GTB) from GEE, the best one of the six classifiers’ results.
    Classification Result From Esri's Lulcm, supplied by Esri inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/classification/classification+result+from+esri+s+lulcm/pmc11928614-125-45-59
    Average 90 stars, based on 1 article reviews
    classification result from esri's lulcm - by Bioz Stars, 2026-10
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    Images

    1) Product Images from "An inclusive classification optimization model for land use and land cover classification"

    Article Title: An inclusive classification optimization model for land use and land cover classification

    Journal: Scientific Reports

    doi: 10.1038/s41598-025-91260-0

    Classification results in a typical urban area (104.09014 °E, 30.61249 °N), ( a ) is the composite Landsat image from 2020 for classification; ( b ) is the historical image from World Imagery Wayback, 12/16/2020; ( c ) is the classification result from ESA’s WC; ( d ) is the result from Google’s DW; ( e ), ESRI’s LULCM; ( f ), CAS’s GLC-FCS30; ( g ), WHU’s CLCD; ( h ) is the classification result of gradient tree boosting (GTB) from GEE, the best one of the six classifiers’ results.
    Figure Legend Snippet: Classification results in a typical urban area (104.09014 °E, 30.61249 °N), ( a ) is the composite Landsat image from 2020 for classification; ( b ) is the historical image from World Imagery Wayback, 12/16/2020; ( c ) is the classification result from ESA’s WC; ( d ) is the result from Google’s DW; ( e ), ESRI’s LULCM; ( f ), CAS’s GLC-FCS30; ( g ), WHU’s CLCD; ( h ) is the classification result of gradient tree boosting (GTB) from GEE, the best one of the six classifiers’ results.

    Techniques Used:

    Classification results in a typical suburban area (103.871413 °E, 30.504502 °N), ( a ) is the composite Landsat image of 2020 for classification; ( b ) is the historical image from World Imagery Wayback, 12/16/2020; ( c ) is the classification result from ESA’s WC; ( d ) is the result from Google’s DW; ( e ), ESRI’s LULCM; ( f ), CAS’s GLC-FCS30; ( g ), WHU’s CLCD; ( h ) is the classification result of the minimum distance (MD) from GEE, the best one of the six classifiers’ results.
    Figure Legend Snippet: Classification results in a typical suburban area (103.871413 °E, 30.504502 °N), ( a ) is the composite Landsat image of 2020 for classification; ( b ) is the historical image from World Imagery Wayback, 12/16/2020; ( c ) is the classification result from ESA’s WC; ( d ) is the result from Google’s DW; ( e ), ESRI’s LULCM; ( f ), CAS’s GLC-FCS30; ( g ), WHU’s CLCD; ( h ) is the classification result of the minimum distance (MD) from GEE, the best one of the six classifiers’ results.

    Techniques Used:

    Related Articles

    other:

    Article Title: An inclusive classification optimization model for land use and land cover classification
    Article Snippet: Fig. 7 Classification results in a typical urban area (104.09014 °E, 30.61249 °N), ( a ) is the composite Landsat image from 2020 for classification; ( b ) is the historical image from World Imagery Wayback, 12/16/2020; ( c ) is the classification result from ESA’s WC; ( d ) is the result from Google’s DW; ( e ), ESRI’s LULCM; ( f ), CAS’s GLC-FCS30; ( g ), WHU’s CLCD; ( h ) is the classification result of gradient tree boosting (GTB) from GEE, the best one of the six classifiers’ results.



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    Image Search Results


    Coronal Plane Alignment of the Knee (CPAK) classification with nine theoretical knee types. Source : Adapted from MacDessi et al. . aHKA, arithmetic hip–knee–ankle angle; HKA, hip–knee–ankle angle; JLO, joint line obliquity; LDFA, lateral distal femoral angle; MPTA, medial proximal tibial angle.

    Journal: Journal of Experimental Orthopaedics

    Article Title: Speaking the same language? A direct cartography between functional knee phenotypes and CPAK

    doi: 10.1002/jeo2.70801

    Figure Lengend Snippet: Coronal Plane Alignment of the Knee (CPAK) classification with nine theoretical knee types. Source : Adapted from MacDessi et al. . aHKA, arithmetic hip–knee–ankle angle; HKA, hip–knee–ankle angle; JLO, joint line obliquity; LDFA, lateral distal femoral angle; MPTA, medial proximal tibial angle.

    Article Snippet: The present study aimed to establish a theoretical mapping between the FKP described by Hirschmann and the CPAK classification by analytically deriving the arithmetic HKA angle and JLO from FMA and TMA.

    Techniques:

    Deterministic mapping between functional knee phenotypes (FMA mean = x ‐coordinate − TMA mean = y ‐coordinate) and CPAK classification femoral. The x ‐axis represents the femoral mechanical angle (FMA): values to the left (FMA < 93°) correspond to varus femoral orientation, values to the right (FMA > 93°) to valgus femoral orientation. The y ‐axis represents the tibial mechanical angle (TMA): values below (TMA < 87°) correspond to varus tibial orientation, values above (TMA > 87°) to valgus tibial orientation. Population means (FMA = 93°, TMA = 87°) serve as phenotypic neutrality references per the Hirschmann classification. CPAK, Coronal Plane Alignment of the Knee.

    Journal: Journal of Experimental Orthopaedics

    Article Title: Speaking the same language? A direct cartography between functional knee phenotypes and CPAK

    doi: 10.1002/jeo2.70801

    Figure Lengend Snippet: Deterministic mapping between functional knee phenotypes (FMA mean = x ‐coordinate − TMA mean = y ‐coordinate) and CPAK classification femoral. The x ‐axis represents the femoral mechanical angle (FMA): values to the left (FMA < 93°) correspond to varus femoral orientation, values to the right (FMA > 93°) to valgus femoral orientation. The y ‐axis represents the tibial mechanical angle (TMA): values below (TMA < 87°) correspond to varus tibial orientation, values above (TMA > 87°) to valgus tibial orientation. Population means (FMA = 93°, TMA = 87°) serve as phenotypic neutrality references per the Hirschmann classification. CPAK, Coronal Plane Alignment of the Knee.

    Article Snippet: The present study aimed to establish a theoretical mapping between the FKP described by Hirschmann and the CPAK classification by analytically deriving the arithmetic HKA angle and JLO from FMA and TMA.

    Techniques: Functional Assay

    Correspondence between functional knee phenotypes and CPAK types across femoral (FMA = x ‐coordinate) and tibial (TMA = y ‐coordinate) mechanical angle intervals. Each functional phenotype corresponds to a 3° angular interval, defined as ± 1.5° around the central femoral (FMA) and tibial (TMA) mechanical angle values. The table illustrates the theoretical mapping between these FMA–TMA intervals and the CPAK classification. When the angular interval of a phenotype intersects several CPAK regions, multiple CPAK types are listed within the same cell. CPAK, Coronal Plane Alignment of the Knee.

    Journal: Journal of Experimental Orthopaedics

    Article Title: Speaking the same language? A direct cartography between functional knee phenotypes and CPAK

    doi: 10.1002/jeo2.70801

    Figure Lengend Snippet: Correspondence between functional knee phenotypes and CPAK types across femoral (FMA = x ‐coordinate) and tibial (TMA = y ‐coordinate) mechanical angle intervals. Each functional phenotype corresponds to a 3° angular interval, defined as ± 1.5° around the central femoral (FMA) and tibial (TMA) mechanical angle values. The table illustrates the theoretical mapping between these FMA–TMA intervals and the CPAK classification. When the angular interval of a phenotype intersects several CPAK regions, multiple CPAK types are listed within the same cell. CPAK, Coronal Plane Alignment of the Knee.

    Article Snippet: The present study aimed to establish a theoretical mapping between the FKP described by Hirschmann and the CPAK classification by analytically deriving the arithmetic HKA angle and JLO from FMA and TMA.

    Techniques: Functional Assay

    Distribution of functional knee phenotypes according to the Hirschmann and MacDessi (CPAK) classifications in osteoarthritic (OA) and non‐osteoarthritic (NO) populations. CPAK distributions obtained from the Hirschmann functional phenotype cohort are compared with those reported in the original CPAK cohort (MacDessi) in NO and OA populations. Four attribution strategies were applied: mean, using the central FMA and TMA values; interval, considering the full angular ranges (±1.5°) of each phenotype; stochastic, using Monte Carlo sampling within these intervals; and rare, selecting CPAK types located at the margins of the compatible aHKA–JLO space. aHKA, arithmetic hip–knee–ankle angle; CPAK, Coronal Plane Alignment of the Knee; FMA, femoral mechanical angle; JLO, joint line obliquity; TMA, total knee arthroplasty.

    Journal: Journal of Experimental Orthopaedics

    Article Title: Speaking the same language? A direct cartography between functional knee phenotypes and CPAK

    doi: 10.1002/jeo2.70801

    Figure Lengend Snippet: Distribution of functional knee phenotypes according to the Hirschmann and MacDessi (CPAK) classifications in osteoarthritic (OA) and non‐osteoarthritic (NO) populations. CPAK distributions obtained from the Hirschmann functional phenotype cohort are compared with those reported in the original CPAK cohort (MacDessi) in NO and OA populations. Four attribution strategies were applied: mean, using the central FMA and TMA values; interval, considering the full angular ranges (±1.5°) of each phenotype; stochastic, using Monte Carlo sampling within these intervals; and rare, selecting CPAK types located at the margins of the compatible aHKA–JLO space. aHKA, arithmetic hip–knee–ankle angle; CPAK, Coronal Plane Alignment of the Knee; FMA, femoral mechanical angle; JLO, joint line obliquity; TMA, total knee arthroplasty.

    Article Snippet: The present study aimed to establish a theoretical mapping between the FKP described by Hirschmann and the CPAK classification by analytically deriving the arithmetic HKA angle and JLO from FMA and TMA.

    Techniques: Functional Assay, Sampling

    Hirschmann‐CPAK (HCT‐9) reading grid. CPAK, Coronal Plane Alignment of the Knee; FMA, femoral mechanical angle; HCT‐9, Hirschmann–CPAK Translational grid; TMA, tibial mechanical angle.

    Journal: Journal of Experimental Orthopaedics

    Article Title: Speaking the same language? A direct cartography between functional knee phenotypes and CPAK

    doi: 10.1002/jeo2.70801

    Figure Lengend Snippet: Hirschmann‐CPAK (HCT‐9) reading grid. CPAK, Coronal Plane Alignment of the Knee; FMA, femoral mechanical angle; HCT‐9, Hirschmann–CPAK Translational grid; TMA, tibial mechanical angle.

    Article Snippet: The present study aimed to establish a theoretical mapping between the FKP described by Hirschmann and the CPAK classification by analytically deriving the arithmetic HKA angle and JLO from FMA and TMA.

    Techniques: