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EcoSIS NGEE Arctic Leaf Spectral Reflectance and Transmittance Data 2014 to 2016 Utqiagvik (Barrow) Alaska (reflectance)

ecosis · NIR

EcoSIS NGEE Arctic Leaf Spectral Reflectance and Transmittance Data 2014 to 2016 Utqiagvik (Barrow) Alaska (reflectance). v2.0 standardized NIRS package: 1 spectral source(s), 10 declared target(s). Auto-generated from dataset_card.json (verify before publication).

nirv2ecosis
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Private dataset. Full metadata and metrics are shown, but the bytes are not redistributed here — exporting the data requires a Dataverse token. The identity card carries no spectra, only descriptive statistics.
199
samples
2,151
wavelengths
1
sources
10
targets
27
metadata
NIR
family

Dataset property explorer

Mean profile risk0.40
Highest axisArtefacts locaux · 1.00
Diagnostics8
Sources profiled1
EcoSIS NGEE Arctic Leaf Spectral Reflectance and Transmittance Data 2014 to 2016 Utqiagvik (Barrow) Alaska (reflectance) property profile0.250.50.751integritynoiseartefactsbaselinePCA outliersreferencerepeatabilitystructureEcoSIS NGEE Arctic Leaf Spectral Reflectance and Transmittance Data 2014 to 2016 Utqiagvik (Barrow) Alaska (reflectance) profileintegrity: 0.00noise: 0.00artefacts: 1.00baseline: 0.70PCA outliers: 0.37reference: 0.59repeatability: 0.00structure: 0.57EcoSIS NGEE Arc…0 center · 1 outer ring · outward = stronger anomaly / heterogeneity signal

Profile axes

Intégrité0.00
Artefacts locaux1.00
Bruit0.00
Outliers PCA0.37
Distance à la référence0.59
Répétabilité0.00
Baseline / forme0.70
Structure multi-régimes0.57
Diagnostic hypotheses00.250.50.751hypothesis scoreSplice / raccord détecteursSplice / raccord détecteurs: 0.720.72Erreur interpolation / réécha…Erreur interpolation / rééchantillonnage: 0.590.59Signature VERA25-likeSignature VERA25-like: 0.530.53Erreur calibration / référenc…Erreur calibration / référence blanche: 0.520.52Fond différentFond différent: 0.450.45Différence de sonde / géométr…Différence de sonde / géométrie: 0.440.44Spectre hors domaine valideSpectre hors domaine valide: 0.350.35Dataset multi-régimesDataset multi-régimes: 0.350.35
DiagnosticScoreForceSignauxInterprétation probable
Splice / raccord détecteursX0.72forteSpike rate 1.00, Jump rate 1.00, SNR non dégradé 1.00Rupture aux jonctions de détecteurs, calibration locale ou sonde différente.
Erreur interpolation / rééchantillonnageX0.59moyenneSpike rate 1.00, Jump rate 1.00, SNR normal/élevé 1.00Artefacts numériques ou traitement spectral incorrect.
Signature VERA25-likeX0.53moyenneSpike rate 1.00, Jump rate 1.00, RMS/SAM référence 0.59Combinaison possible changement de sonde + splice, amplifiée par géométrie, fond ou calibration.
Erreur calibration / référence blancheX0.52moyenneartefacts locaux 1.00, Baseline/mean/area 0.70, RMS/SAM référence 0.59Décalage systématique entre campagnes, instruments ou référence blanche.
Fond différentX0.45moyenneBaseline/mean/area 0.70, RMS/SAM référence 0.59, Mahalanobis / T2 0.37Effet systématique du support, blanc/noir, transflectance ou environnement de mesure.
Différence de sonde / géométrieX0.44moyenneBaseline/mean/area 0.70, RMS/SAM référence 0.59, Mahalanobis / T2 0.37Modification de l'illumination, collecte, angle ou distance sonde-échantillon.
Spectre hors domaine valideX0.35faibleRMS/SAM référence 0.59, Structure PCA 0.57, Mahalanobis / T2 0.37Variété, espèce, lot ou condition différente mais physiquement plausible.
Dataset multi-régimesX0.35faibleRMS/SAM référence 0.59, Structure PCA 0.57, Mahalanobis / T2 0.37Mélange de campagnes, opérateurs, lots, setups ou sous-populations spectrales.

Spectral sources

NGEE-Arctic_Barrow_2016_SVCHR1024i_Leaf_Spectral_Reflectance.csv

X · NIR · Spectra Vista Corporation HR-1024i
NGEE-Arctic_Barrow_2016_SVCHR1024i_Leaf_Spectral_Reflectance.csv spectra020406001,0002,0003,000q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / nm350nm — median 5.213 (q25–q75 3.533–6.619)365nm — median 3.592 (q25–q75 2.35–4.771)381nm — median 3.091 (q25–q75 2.11–4.07)396nm — median 2.616 (q25–q75 1.711–3.601)412nm — median 2.471 (q25–q75 1.531–3.732)427nm — median 3.285 (q25–q75 1.706–4.664)443nm — median 4.544 (q25–q75 1.868–5.754)458nm — median 5.174 (q25–q75 2.092–6.252)474nm — median 5.347 (q25–q75 2.23–6.473)489nm — median 5.317 (q25–q75 2.291–6.606)505nm — median 5.879 (q25–q75 2.727–7.843)520nm — median 7.89 (q25–q75 4.94–11.43)536nm — median 10.86 (q25–q75 8.557–15.15)551nm — median 12.29 (q25–q75 10.19–16.43)567nm — median 11.32 (q25–q75 9.265–15.21)582nm — median 9.206 (q25–q75 7.108–12.84)597nm — median 8.433 (q25–q75 6.156–11.89)613nm — median 7.497 (q25–q75 5.147–10.5)628nm — median 6.81 (q25–q75 4.422–9.615)644nm — median 5.976 (q25–q75 3.714–8.598)659nm — median 5.139 (q25–q75 2.89–7.061)675nm — median 4.517 (q25–q75 2.292–5.702)690nm — median 6.366 (q25–q75 3.845–8.567)706nm — median 19.37 (q25–q75 17.13–22.77)721nm — median 33.7 (q25–q75 31.04–36)737nm — median 42.9 (q25–q75 40.78–45.18)752nm — median 46.21 (q25–q75 43.76–48.8)768nm — median 47.03 (q25–q75 44.59–49.45)783nm — median 47.21 (q25–q75 44.73–49.48)799nm — median 47.21 (q25–q75 44.76–49.53)814nm — median 47.13 (q25–q75 44.69–49.49)829nm — median 47.11 (q25–q75 44.7–49.48)845nm — median 47.09 (q25–q75 44.71–49.5)860nm — median 47.15 (q25–q75 44.72–49.55)876nm — median 47.08 (q25–q75 44.59–49.44)891nm — median 46.9 (q25–q75 44.49–49.36)907nm — median 46.86 (q25–q75 44.4–49.29)922nm — median 46.66 (q25–q75 44.41–49.22)938nm — median 46.41 (q25–q75 44.05–48.92)953nm — median 45.81 (q25–q75 43.62–48.38)969nm — median 45.23 (q25–q75 43.28–47.85)984nm — median 44.99 (q25–q75 43.07–47.45)1,000nm — median 45.34 (q25–q75 43.3–47.93)1,015nm — median 46.05 (q25–q75 43.96–48.57)1,031nm — median 46.43 (q25–q75 44.29–49)1,046nm — median 46.55 (q25–q75 44.4–49.29)1,062nm — median 46.65 (q25–q75 44.47–49.49)1,077nm — median 46.66 (q25–q75 44.47–49.51)1,092nm — median 46.6 (q25–q75 44.45–49.44)1,108nm — median 46.44 (q25–q75 44.33–49.22)1,123nm — median 46.14 (q25–q75 44.08–48.83)1,139nm — median 45.15 (q25–q75 43.01–47.68)1,154nm — median 43.53 (q25–q75 41.48–46.25)1,170nm — median 42.97 (q25–q75 41.14–45.82)1,185nm — median 42.69 (q25–q75 40.9–45.41)1,201nm — median 42.63 (q25–q75 40.95–45.38)1,216nm — median 42.88 (q25–q75 41.09–45.47)1,232nm — median 43.15 (q25–q75 41.41–45.81)1,247nm — median 43.48 (q25–q75 41.57–45.92)1,263nm — median 43.56 (q25–q75 41.62–45.95)1,278nm — median 43.39 (q25–q75 41.43–45.83)1,294nm — median 42.75 (q25–q75 40.95–45.4)1,309nm — median 41.81 (q25–q75 40.26–44.73)1,324nm — median 40.51 (q25–q75 38.75–43.71)1,340nm — median 38.56 (q25–q75 36.48–42.31)1,355nm — median 36.93 (q25–q75 34.62–40.82)1,371nm — median 34.69 (q25–q75 32.12–38.63)1,386nm — median 28.96 (q25–q75 26.37–32.76)1,402nm — median 20.87 (q25–q75 18.2–24.22)1,417nm — median 16.3 (q25–q75 14.14–19.39)1,433nm — median 14.65 (q25–q75 12.91–17.19)1,448nm — median 14.41 (q25–q75 12.68–16.73)1,464nm — median 14.84 (q25–q75 13.07–17.34)1,479nm — median 16.21 (q25–q75 14.39–19.02)1,495nm — median 18.21 (q25–q75 16.22–21.36)1,510nm — median 20.12 (q25–q75 18.08–23.56)1,526nm — median 22.11 (q25–q75 19.98–25.58)1,541nm — median 24.17 (q25–q75 21.72–27.24)1,556nm — median 25.63 (q25–q75 23.15–28.8)1,572nm — median 26.85 (q25–q75 24.55–30.2)1,587nm — median 27.93 (q25–q75 25.59–31.31)1,603nm — median 28.85 (q25–q75 26.5–32.38)1,618nm — median 29.56 (q25–q75 27.22–33.25)1,634nm — median 30.19 (q25–q75 27.85–33.81)1,649nm — median 30.59 (q25–q75 28.31–34.23)1,665nm — median 30.75 (q25–q75 28.57–34.46)1,680nm — median 30.58 (q25–q75 28.42–34.28)1,696nm — median 30.08 (q25–q75 28.1–33.77)1,711nm — median 29.67 (q25–q75 27.64–33.2)1,727nm — median 29.05 (q25–q75 26.95–32.55)1,742nm — median 28.26 (q25–q75 26.23–31.84)1,758nm — median 27.23 (q25–q75 25.18–30.85)1,773nm — median 26.35 (q25–q75 24.35–30.11)1,788nm — median 26 (q25–q75 24.04–29.76)1,804nm — median 26 (q25–q75 24.07–29.77)1,819nm — median 26 (q25–q75 24–29.69)1,835nm — median 25.66 (q25–q75 23.58–29.26)1,850nm — median 24.37 (q25–q75 22.29–27.9)1,866nm — median 20.03 (q25–q75 17.97–23.45)1,881nm — median 12.83 (q25–q75 10.84–15.26)1,897nm — median 6.288 (q25–q75 4.958–7.815)1,912nm — median 3.693 (q25–q75 2.749–4.724)1,928nm — median 3.189 (q25–q75 2.392–4.162)1,943nm — median 3.342 (q25–q75 2.518–4.481)1,959nm — median 3.882 (q25–q75 2.937–5.163)1,974nm — median 4.638 (q25–q75 3.603–6.016)1,990nm — median 5.647 (q25–q75 4.509–7.109)2,005nm — median 6.677 (q25–q75 5.46–8.243)2,021nm — median 7.789 (q25–q75 6.434–9.443)2,036nm — median 8.723 (q25–q75 7.289–10.38)2,051nm — median 9.593 (q25–q75 8.036–11.23)2,067nm — median 10.47 (q25–q75 8.885–12.26)2,082nm — median 11.36 (q25–q75 9.679–13.26)2,098nm — median 12.34 (q25–q75 10.57–14.2)2,113nm — median 13.3 (q25–q75 11.51–15.3)2,129nm — median 14.08 (q25–q75 12.28–16.23)2,144nm — median 14.55 (q25–q75 12.78–16.8)2,160nm — median 15.18 (q25–q75 13.35–17.41)2,175nm — median 15.54 (q25–q75 13.69–17.79)2,191nm — median 15.65 (q25–q75 13.94–18.15)2,206nm — median 16.01 (q25–q75 14.19–18.5)2,222nm — median 16.13 (q25–q75 14.25–18.63)2,237nm — median 15.83 (q25–q75 13.94–18.34)2,253nm — median 14.93 (q25–q75 13.18–17.35)2,268nm — median 14.04 (q25–q75 12.28–16.28)2,283nm — median 13.38 (q25–q75 11.71–15.55)2,299nm — median 12.72 (q25–q75 11.1–14.82)2,314nm — median 12.06 (q25–q75 10.56–14.12)2,330nm — median 11.28 (q25–q75 9.757–13.21)2,345nm — median 10.55 (q25–q75 9.179–12.45)2,361nm — median 10.35 (q25–q75 8.883–11.98)2,376nm — median 10.01 (q25–q75 8.632–11.6)2,392nm — median 8.735 (q25–q75 7.503–10.25)2,407nm — median 7.856 (q25–q75 6.682–9.364)2,423nm — median 7.347 (q25–q75 6.208–8.792)2,438nm — median 6.823 (q25–q75 5.708–8.231)2,454nm — median 6.063 (q25–q75 5.02–7.391)2,469nm — median 5.35 (q25–q75 4.415–6.603)2,485nm — median 4.837 (q25–q75 3.91–5.992)2,500nm — median 4.733 (q25–q75 3.775–5.867)

Sampling

Wavelengths2,151
Axis range350–2,500 nm
Mean spacing1 nm
Griduniform
Observations199

Signal & quality

Value range-3.03 – 57.7
Mean range2.66 – 47.6
Mean level23.74
Area5.105e+04
PTP44.95
Noise RMS0.0024971
SNR9.5e+03
SNR dB8e+01 dB
Dynamic range45
Smoothness0.103
Saturated0.0%
X-outliers83

Integrity & artefacts

NaN ratio0.00%
Inf count0
Zero ratio0.00%
Spike count34,195
Spike rate8.00%
Jump count12,427
Jump rate2.90%
Clip fraction0.00%

Shape & reference

Baseline slope-15.722
Curvature RMS0.099862
D1 RMS0.18816
RMS to mean3.2824
RMS p955.7902
SAM to mean0.061135
SAM p950.19291
Affine offset p957.4552
Affine gain p95 Δ0.19695
Affine residual p953.1645
Xcorr lag p950

Outliers & repeatability

PCA Q p95/median2.7
Hotelling T2 p95/median2.2
Mahalanobis H p95/median1.5
Repeat groups0

Dimensionality (PCA)

Effective rank2.4
PCs → 95% var3
PCs → 99% var5
Top-10 cum. var99.8%
Computed metric scores 29worst 1.00
FamilleMétrique calculéeValeurScoreNiveauInterprétation datasetCauses typiquesCalcul / scoring
Intégrité des donnéesNaN ratiointegrity.nan_ratio0%0.00faibleSpectre completErreur acquisition/exportcount(isnan(X)) / X.sizealert = min(1, nan_ratio / 0.05)
Intégrité des donnéesInf countintegrity.inf_count00.00faibleNormalCalculs invalidescount(isinf(X))alert = min(1, inf_count / 1)
Intégrité des donnéesZero ratiointegrity.zero_ratio0.000467%0.00faibleNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Amplitude globaleMean reflectanceamplitude.mean_reflectance23.7360.70moyenValeur atypique: Trop clair / fond visible ou Trop sombreFond, géométriemean(X finite)alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent
Amplitude globaleArea under curveamplitude.area_under_curve510510.70moyenValeur atypique: Différence d'éclairement ou NormalDistance sondetrapezoid(mean_spectrum, spectral_axis)alert reuses baseline/shape drift because area scale depends on axis and units
Amplitude globalePeak-to-peak (PTP)amplitude.peak_to_peak44.9550.00faibleVariabilité forteSaturationmax(mean_spectrum) - min(mean_spectrum)alert increases when dynamic range is abnormally flat
Amplitude globaleVarianceamplitude.variance269.560.00faibleNormal ou hétérogèneMauvais contactvar(X finite)alert increases when variance/dynamic range is abnormally flat
BruitNoise RMSnoise.noise_rms0.00249710.00faibleStableLampe, détecteurmedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
BruitSNRnoise.snr9505.40.00faibleBon signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
BruitBandwise SNRnoise.bandwise_snr_min8.17960.48moyenZone problématiqueDétecteurmin(abs(mean_spectrum) / local second-derivative noise)alert decreases with worst-band SNR dB; >=35 dB is treated as low alert
Artefacts locauxSpike countartefacts.spike_count34,1951.00fortArtefactsCosmic rays, splicecount robust outliers in second derivativealert follows spike_rate, saturated at 1%
Artefacts locauxSpike rateartefacts.spike_rate8%1.00fortSpectre suspectInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Artefacts locauxJump countartefacts.jump_count12,4271.00fortRaccord détecteurSplicecount robust outliers in first derivativealert follows jump_rate, saturated at 1%
Artefacts locauxJump rateartefacts.jump_rate2.9%1.00fortProblème spectralCalibrationjump_count / (n_samples * (n_features - 1))alert = min(1, jump_rate / 0.01)
Artefacts locauxClip fractionartefacts.clip_fraction0.000467%0.00faibleNormalDétecteur saturéfraction of finite cells equal to repeated min/max extremaalert = min(1, clip_fraction / 0.01)
Forme spectraleBaseline slopeshape.baseline_slope-15.7220.70moyenDériveÉclairementlinear slope of mean_spectrum over normalized axisalert = abs(slope / signal_scale), saturated at 0.5
Forme spectraleCurvature RMSshape.curvature_rms0.0998620.22faibleLisseFond, splicemedian RMS(second derivative per spectrum)alert = curvature_rms / signal_scale, saturated at 1%
Forme spectraleD1 RMSshape.d1_rms0.188160.08faiblePlatBiologie ou artefactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Outliers multivariésPCA Q (SPE)outliers.pca_q_ratio2.70390.34faibleConformeArtefact, mélangep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Outliers multivariésHotelling T²outliers.hotelling_t2_ratio2.22680.28faibleCentralVariabilité naturellep95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Outliers multivariésMahalanobis Houtliers.mahalanobis_h_ratio1.49220.37faiblePopulation normaleDomaine différentp95(sqrt(T2)) / median(sqrt(T2))alert = min(1, mahalanobis_h_ratio / 4)
Comparaison à référenceRMS to mean spectrumreference.rms_to_mean_spectrum_p955.79020.52moyenSpectre différentDomain shiftp95 RMS distance to dataset mean spectrumalert = RMS_p95 / signal_scale, saturated at 25%
Comparaison à référenceSpectral Angle Mapper (SAM)reference.sam_to_mean_spectrum_p950.192910.55moyenForme différenteFond, géométriep95 spectral angle to dataset mean spectrumalert = min(1, SAM_p95 / 0.35 rad)
RépétabilitéRMS intra-IDrepeatability.rms_intra_id—0.00faibleStablePositionnementmedian RMS distance to repeated-sample centroidalert = RMS_intra_ID / signal_scale, saturated at 10%
RépétabilitéSAM intra-IDrepeatability.sam_intra_id—0.00faibleStableAcquisitionmedian SAM to repeated-sample centroidalert = min(1, SAM_intra_ID / 0.15 rad)
RépétabilitéCV intra-IDrepeatability.cv_intra_id—0.00faibleStableOpérateurmedian within-ID band CValert = min(1, CV_intra_ID / 0.25)
Structure du datasetPCA score densitystructure.pca_score_density0.0285360.57moyenSous-populationsLots différents1 / median kNN distance in PCA score spacealert follows density_cv/profile structure complexity, not raw density alone
Structure du datasetLocal Outlier Factor (LOF)structure.local_outlier_factor_p951.72450.36faiblePopulation normaleCas raresp95 approximate LOF from PCA-score kNN distancesalert = min(1, max(0, LOF_p95 - 1) / 2)
Structure du datasetIsolation Forest scorestructure.isolation_forest_score_p950.565460.57moyenSpectre atypiqueDiverses causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent
X PCA score plot-400-2000200400-300-200-1000100200PC1 -65.23 · PC2 -186.2PC1 -37.64 · PC2 -163.5PC1 -63.5 · PC2 -222.1PC1 -44.75 · PC2 -158.5PC1 -25.88 · PC2 -175PC1 -63.03 · PC2 -162.9PC1 -92.6 · PC2 -176.9PC1 -109.1 · PC2 -145PC1 -69.8 · PC2 -159.6PC1 -46.27 · PC2 -109.4PC1 -107.1 · PC2 -149.8PC1 5.716 · PC2 15.05PC1 -20.58 · PC2 -131.3PC1 -32.9 · PC2 -127PC1 -74.28 · PC2 -176.4PC1 -66.59 · PC2 -100.9PC1 -51.46 · PC2 1.008PC1 91.72 · PC2 86.75PC1 46.75 · PC2 90.5PC1 53.48 · PC2 87.59PC1 39.09 · PC2 108.8PC1 -107.7 · PC2 -29.11PC1 -17.94 · PC2 38.71PC1 -26.78 · PC2 21.72PC1 0.5063 · PC2 43.68PC1 70.58 · PC2 100.8PC1 -222.6 · PC2 22.76PC1 -148.9 · PC2 72.94PC1 -122.7 · PC2 32.97PC1 -45.02 · PC2 -24.11PC1 12.06 · PC2 38.38PC1 -4.909 · PC2 73.43PC1 -113.3 · PC2 7.966PC1 32.72 · PC2 98.77PC1 165.7 · PC2 100.6PC1 174.9 · PC2 89.34PC1 176.6 · PC2 58.55PC1 193.9 · PC2 55.63PC1 188.8 · PC2 90.84PC1 177.1 · PC2 43.65PC1 102.1 · PC2 143.2PC1 41.74 · PC2 105.1PC1 73.91 · PC2 138PC1 12.65 · PC2 75.05PC1 -48.47 · PC2 66.46PC1 57.26 · PC2 127.6PC1 22.38 · PC2 45.25PC1 -106.2 · PC2 -144.7PC1 -178.8 · PC2 -15.8PC1 -155 · PC2 30.84PC1 35.83 · PC2 28.83PC1 100.5 · PC2 28.19PC1 -49.01 · PC2 -124.6PC1 -99.83 · PC2 -132.5PC1 238 · PC2 -82.28PC1 188.5 · PC2 -25.37PC1 125.3 · PC2 -62.22PC1 195.8 · PC2 -59.36PC1 321.4 · PC2 -39.97PC1 -169.6 · PC2 18.53PC1 -174.2 · PC2 27.78PC1 -163.1 · PC2 168.2PC1 -142.5 · PC2 70.45PC1 49.45 · PC2 112.8PC1 36.24 · PC2 48.04PC1 42.93 · PC2 75.45PC1 128.4 · PC2 -3.674PC1 88.65 · PC2 -8.51PC1 102.1 · PC2 137.4PC1 110.5 · PC2 106.7PC1 -95.01 · PC2 -136.1PC1 62.46 · PC2 2.482PC1 -198.5 · PC2 67.53PC1 -191.7 · PC2 1.644PC1 -139.7 · PC2 102.5PC1 104.3 · PC2 -1.76PC1 73.05 · PC2 -29.45PC1 117.2 · PC2 53.12PC1 33.99 · PC2 59.43PC1 -9.119 · PC2 82.96PC1 16.25 · PC2 107.1PC1 -60.71 · PC2 36.44PC1 193.7 · PC2 39.33PC1 -267.8 · PC2 1.389PC1 -187.6 · PC2 69.49PC1 -198.8 · PC2 75.51PC1 -209.4 · PC2 17.79PC1 34.34 · PC2 121.5PC1 11.84 · PC2 66.19PC1 -29.15 · PC2 -15.78PC1 -68.97 · PC2 11.42PC1 9.725 · PC2 84.43PC1 -251.3 · PC2 -6.419PC1 -186.9 · PC2 25.67PC1 11.88 · PC2 22.1PC1 -182.3 · PC2 50.25PC1 247.9 · PC2 -73.23PC1 222.9 · PC2 -68.9PC1 265 · PC2 -91.95PC1 -208 · PC2 34.74PC1 -239.2 · PC2 -0.818PC1 -256.3 · PC2 13.01PC1 -207.7 · PC2 17.64PC1 37.24 · PC2 -0.3769PC1 46.11 · PC2 45.74PC1 53.4 · PC2 91.17PC1 38.56 · PC2 80.31PC1 66.82 · PC2 40.51PC1 32.94 · PC2 44.76PC1 218.5 · PC2 -63.92PC1 265.9 · PC2 -61.27PC1 281.5 · PC2 -38.16PC1 187.2 · PC2 -96.7PC1 -203.1 · PC2 -61.5PC1 -197.2 · PC2 2.939PC1 268.9 · PC2 -63.93PC1 188.1 · PC2 -57.12PC1 248.7 · PC2 -100.7PC1 -138.7 · PC2 -152.5PC1 -78.01 · PC2 -127.2PC1 -61.27 · PC2 -120.1PC1 -83.33 · PC2 -101.1PC1 -53.21 · PC2 -110PC1 -79.69 · PC2 -159.6PC1 90.62 · PC2 -50.59PC1 75.94 · PC2 -28.25PC1 115.7 · PC2 2.167PC1 87.6 · PC2 -45.92PC1 -53.8 · PC2 -107.1PC1 -131.6 · PC2 -175.2PC1 -97.31 · PC2 -136.1PC1 -96.2 · PC2 -118.8PC1 -95.41 · PC2 -142.4PC1 -119.2 · PC2 -132.7PC1 184 · PC2 81.11PC1 175.4 · PC2 48.44PC1 142.5 · PC2 -4.456PC1 200.5 · PC2 69.25PC1 -91.65 · PC2 -84.86PC1 -99.39 · PC2 -113.8PC1 -30.69 · PC2 -152.3PC1 -65.68 · PC2 -132.1PC1 -55.36 · PC2 -105.6PC1 -127.8 · PC2 -3.917PC1 -38.72 · PC2 -25.46PC1 -35.72 · PC2 -36.9PC1 -191.9 · PC2 50.29PC1 -157.6 · PC2 69.73PC1 229.4 · PC2 32.7PC1 201.4 · PC2 4.976PC1 182.8 · PC2 46.37PC1 202.9 · PC2 20.86PC1 21.83 · PC2 10.49PC1 102.4 · PC2 150.9PC1 37.04 · PC2 43.89PC1 42.28 · PC2 90.65PC1 13.97 · PC2 61.3PC1 24.21 · PC2 49.3PC1 39.63 · PC2 30.1PC1 59.43 · PC2 78.89PC1 33.42 · PC2 63.69PC1 46.77 · PC2 41.48PC1 21.34 · PC2 28.47PC1 43.83 · PC2 31.55PC1 50.45 · PC2 95.55PC1 85.24 · PC2 92.2PC1 84.58 · PC2 63.45PC1 81.63 · PC2 131.6PC1 -108.1 · PC2 79.55PC1 -123.9 · PC2 31.35PC1 -157.4 · PC2 44.7PC1 -243.1 · PC2 49.82PC1 -123.1 · PC2 167.6PC1 -206.7 · PC2 44.19PC1 -277.1 · PC2 18.21PC1 -220.8 · PC2 19.35PC1 -158.8 · PC2 102.5PC1 248.8 · PC2 -117.5PC1 -152.6 · PC2 129.9PC1 -92.98 · PC2 82.71PC1 -189.4 · PC2 -6.087PC1 221.8 · PC2 -108.3PC1 -111.5 · PC2 79.51PC1 -121.2 · PC2 89.43PC1 -125.3 · PC2 55.13PC1 168.9 · PC2 -168.1PC1 122.6 · PC2 -118.4PC1 221.5 · PC2 -119.2PC1 -97.66 · PC2 94.5PC1 61.13 · PC2 118PC1 38.3 · PC2 76.01PC1 -37.26 · PC2 63.57PC1 29.1 · PC2 5.849PC1 10.61 · PC2 5.546PC1 31.69 · PC2 17.02PC1 20.78 · PC2 35.7PC1 243 · PC2 -128.1PC1 30.69 · PC2 35.54PC1 216.8 · PC2 -141.3PC1 (66.5%)PC2 (28.5%)199 scores
PCA explained variance0%25%50%75%100%PC1: 66.5% (cumulative 66.5%)1PC2: 28.5% (cumulative 95.0%)2PC3: 3.1% (cumulative 98.0%)3PC4: 0.6% (cumulative 98.6%)4PC5: 0.5% (cumulative 99.1%)5PC6: 0.4% (cumulative 99.4%)6PC7: 0.1% (cumulative 99.6%)7PC8: 0.1% (cumulative 99.6%)8PC9: 0.1% (cumulative 99.7%)9PC10: 0.1% (cumulative 99.8%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)
X-Y spectral correlation 8
X · C_mass_mg_g spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale
X · C_mass_g_g spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale
X · N_mass_mg_g spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale
Targetmax |r|axis @ maxmean |r||r| ≥ .5
C_mass_mg_g0.5591,9350.35418.3%
C_mass_g_g0.4481,9430.2540.0%
N_mass_mg_g0.5581,9350.35318.0%
N_mass_g_g0.5581,9350.35318.0%
LMA_g_m20.2857730.1150.0%
C_area_g_m20.5141,9260.3616.3%
N_area_g_m20.5131,9260.366.1%
CN_ratio0.5581,9350.35317.9%

Metric interpretation reference

Metric catalog 29
FamilleMétriqueCe qu’elle détecteForte valeur =Faible valeur =Causes typiquesCalcul / score
Intégrité des donnéesNaN ratioDonnées manquantesSpectre corrompuSpectre completErreur acquisition/exportcount(isnan(X)) / X.sizealert = min(1, nan_ratio / 0.05)
Intégrité des donnéesInf countValeurs infiniesCorruptionNormalCalculs invalidescount(isinf(X))alert = min(1, inf_count / 1)
Intégrité des donnéesZero ratioColonnes ou cellules nullesSpectre tronquéNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Amplitude globaleMean reflectanceNiveau moyenTrop clair / fond visibleTrop sombreFond, géométriemean(X finite)alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent
Amplitude globaleArea under curveIntensité globaleDifférence d'éclairementNormalDistance sondetrapezoid(mean_spectrum, spectral_axis)alert reuses baseline/shape drift because area scale depends on axis and units
Amplitude globalePeak-to-peak (PTP)DynamiqueVariabilité forteSpectre platSaturationmax(mean_spectrum) - min(mean_spectrum)alert increases when dynamic range is abnormally flat
Amplitude globaleVarianceVariabilité spectraleNormal ou hétérogèneSpectre platMauvais contactvar(X finite)alert increases when variance/dynamic range is abnormally flat
BruitNoise RMSBruit haute fréquenceBruitéStableLampe, détecteurmedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
BruitSNRQualité signalBon signalMauvais signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
BruitBandwise SNRBruit localiséZone fiableZone problématiqueDétecteurmin(abs(mean_spectrum) / local second-derivative noise)alert decreases with worst-band SNR dB; >=35 dB is treated as low alert
Artefacts locauxSpike countPics étroitsArtefactsSpectre propreCosmic rays, splicecount robust outliers in second derivativealert follows spike_rate, saturated at 1%
Artefacts locauxSpike rateDensité de picsSpectre suspectNormalInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Artefacts locauxJump countDiscontinuitésRaccord détecteurContinuSplicecount robust outliers in first derivativealert follows jump_rate, saturated at 1%
Artefacts locauxJump rateFréquence de sautsProblème spectralNormalCalibrationjump_count / (n_samples * (n_features - 1))alert = min(1, jump_rate / 0.01)
Artefacts locauxClip fractionSaturationClippingNormalDétecteur saturéfraction of finite cells equal to repeated min/max extremaalert = min(1, clip_fraction / 0.01)
Forme spectraleBaseline slopePente globaleDériveStableÉclairementlinear slope of mean_spectrum over normalized axisalert = abs(slope / signal_scale), saturated at 0.5
Forme spectraleCurvature RMSCourbureForme inhabituelleLisseFond, splicemedian RMS(second derivative per spectrum)alert = curvature_rms / signal_scale, saturated at 1%
Forme spectraleD1 RMSVariabilité localeSpectre structuréPlatBiologie ou artefactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Outliers multivariésPCA Q (SPE)Non expliqué par PCASpectre atypiqueConformeArtefact, mélangep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Outliers multivariésHotelling T²Extrême dans PCAExtrême mais cohérentCentralVariabilité naturellep95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Outliers multivariésMahalanobis HDistance au nuageOutlier globalPopulation normaleDomaine différentp95(sqrt(T2)) / median(sqrt(T2))alert = min(1, mahalanobis_h_ratio / 4)
Comparaison à référenceRMS to mean spectrumDistance moyenneSpectre différentTypiqueDomain shiftp95 RMS distance to dataset mean spectrumalert = RMS_p95 / signal_scale, saturated at 25%
Comparaison à référenceSpectral Angle Mapper (SAM)Différence de formeForme différenteSimilaireFond, géométriep95 spectral angle to dataset mean spectrumalert = min(1, SAM_p95 / 0.35 rad)
RépétabilitéRMS intra-IDReproductibilitéMauvaise répétabilitéStablePositionnementmedian RMS distance to repeated-sample centroidalert = RMS_intra_ID / signal_scale, saturated at 10%
RépétabilitéSAM intra-IDVariation de formeInstableStableAcquisitionmedian SAM to repeated-sample centroidalert = min(1, SAM_intra_ID / 0.15 rad)
RépétabilitéCV intra-IDVariabilité interneMauvais contrôleStableOpérateurmedian within-ID band CValert = min(1, CV_intra_ID / 0.25)
Structure du datasetPCA score densityClustersSous-populationsHomogèneLots différents1 / median kNN distance in PCA score spacealert follows density_cv/profile structure complexity, not raw density alone
Structure du datasetLocal Outlier Factor (LOF)Anomalie localeSpectre isoléPopulation normaleCas raresp95 approximate LOF from PCA-score kNN distancesalert = min(1, max(0, LOF_p95 - 1) / 2)
Structure du datasetIsolation Forest scoreAnomalie globaleSpectre atypiqueNormalDiverses causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent
Technology-specific extensions
TechnologieAdaptations / métriquesAnomalies cibléesCommentaire pratique
UV-Vis 300-1000 nmBaseline, pente globale, dérive aux bords 300-350 et 900-1000; métriques par zonesLumière parasite, mauvais blanc, saturation, faible signal aux extrémitésLes bords sont souvent instables; calculer aussi des scores edge/middle.
UV-Vis 300-1000 nmSaturation / clipping proche absorbance max ou réflectance maxSignal écrêtéTrès important si absorption forte.
UV-Vis 300-1000 nmRed-edge, position de maximum, ratios de bandes si végétalDécalage biologique ou artefact optiqueAide à distinguer changement réel et problème d'acquisition.
UV-Vis 300-1000 nmSmoothness / roughness indexBruit haute fréquenceSouvent plus informatif que le SNR seul.
MIR / ATR-FTIRATR contact quality index: intensité globale, aire totale, profondeur des bandes clésMauvais contact cristal-échantillonCrucial: beaucoup d'anomalies viennent du contact ATR.
MIR / ATR-FTIRCO2 / H2O atmospheric bandsMauvaise correction atmosphériquePics parasites fréquents.
MIR / ATR-FTIRBaseline curvature / rubber-band residualDiffusion, contact, dérive baselineTrès utile avant PCA.
MIR / ATR-FTIRPeak position shiftMauvais alignement spectral / calibrationImportant en FTIR car de petits shifts comptent.
MIR / ATR-FTIRBand area ratios sur bandes connuesSpectre chimiquement incohérentÀ adapter par matrice: polysaccharides, protéines, lipides, etc.
HS-MSTotal Ion Current (TIC), Base Peak Intensity (BPI)Injection faible, ionisation instableÉquivalent MS du niveau global spectral.
HS-MSNombre de pics détectésSpectre pauvre ou trop bruitéTrop peu = mauvais signal; trop = bruit/contamination.
HS-MSMass accuracy / m/z driftProblème calibration masseFondamental en HRMS.
HS-MSRetention time drift si LC/GC-MSDérive chromatographiqueÀ suivre sur standards/QC pools.
HS-MSBlank contamination scoreContaminants / carry-overComparer échantillons vs blancs.
HS-MSInternal standard CVVariabilité instrumentaleTrès robuste si standards disponibles.
HS-MSMissingness par featureInstabilité de détectionCrucial pour filtrer les variables.
Avec répétitionsRMS intra-échantillonRépétabilité globaleApplicable à toutes les technologies.
Avec répétitionsSAM / corrélation intra-échantillonRépétabilité de formeTrès utile pour spectres.
Avec répétitionsCV intra-échantillon par bande / featureRépétabilité localeDétecte les zones instables.
Avec répétitionsICC ou variance componentsPart variance échantillon vs techniqueTrès utile si plusieurs répétitions par sample.
Avec répétitionsDistance au centroïde intra-IDRépétition aberrantePermet de flagger la mauvaise répétition plutôt que le sample entier.
Bug-hunting / supervised audits
Famille de bug potentielMéthodes à ajouterCe que ça détecteÉtat dans l’explorateur
Shift spectral globalCorrélation spectre moyen inter-dataset, DTW, cross-correlation, comparaison positions de picsDécalage en longueur d'onde, mauvais alignement, interpolation différentePartiellement calculé: cross-correlation lag et dispersion des positions de pics vs spectre moyen.
Baseline / offset / gainRégression chaque spectre vs spectre moyen: x = a + b ref + residual; suivi de a, b, RMS résiduelOffset additif, effet multiplicatif, dérive de baselineCalculé dans reference.affine_*.
Mélange de lignes / mauvais appariement X-M-YVérification index, hash des lignes, duplication ID, distance spectrale intra-ID, labels incohérentsLignes mélangées, metadata mal alignées, Y attribué au mauvais spectrePartiellement couvert par répétabilité intra-ID; checks index/hash à ajouter au pipeline canonical.
Fuite d'information / répétitions mal splitéesGroupKFold par sample_id vs StratifiedKFold random; audit des partitions par sample_idPerformance artificiellement bonne due aux répétitionsNécessite splits et benchmark modèle; non calculé par la carte descriptive.
Label bugsÉchantillons proches en X mais Y différents, confident learning, erreurs systématiques FP/FNY inversés, erreurs de saisie, classes ambiguësNécessite Y et/ou modèle; recommandé pour l'explorateur supervisé.
Sous-domaines cachésPCA/UMAP/t-SNE + clustering non supervisé + association avec dataset/Y/date/operatorLots, campagnes, sondes, backgrounds non renseignésPartiellement calculé par structure PCA/LOF; UMAP/t-SNE hors carte statique.
Artefacts localisés inconnusCarte wavelength x dataset: différence moyenne, différence variance, KS par longueur d'ondeRégions spectrales anormales non anticipéesÀ calculer au niveau banque quand plusieurs datasets partagent un axe spectral.
Ruptures instrumentalesDiscontinuités dans dérivées, changepoint detectionSplice, raccord détecteur, saut local non prévuCalculé par jump/spike rates; changepoint plus avancé à ajouter.
Mélange / contamination spectraleNMF / unmixing / reconstruction par convex hullComposante externe: fond, plastique, solNon calculé automatiquement; nécessite hypothèses de composants ou grande bibliothèque.
Features instables mais prédictivesImportance modèle vs instabilité QC par variableModèle qui apprend un artefact plutôt qu'un signal biologiqueNécessite modèle supervisé; recommandé pour rapports de benchmark.

Variables

Targets 10

USDA_Species_Code

target · categorical
USDA_Species_Code classesCAAQCAAQ: 4646ARLA2ARLA2: 3838ERAN6ERAN6: 3333ARFU2ARFU2: 3131SAPU15SAPU15: 2626PEFR5PEFR5: 2525
n / missing199 / 0
Classes6
Balance (entropy)0.99
Imbalance ratio2
Top classCAAQ (46)

C_mass_mg_g

target · numeric
C_mass_mg_g distribution0100200-9,999 – -9556: 27-9556 – -9114: 0-9114 – -8671: 0-8671 – -8228: 0-8228 – -7785: 0-7785 – -7343: 0-7343 – -6900: 0-6900 – -6457: 0-6457 – -6014: 0-6014 – -5572: 0-5572 – -5129: 0-5129 – -4686: 0-4686 – -4243: 0-4243 – -3801: 0-3801 – -3358: 0-3358 – -2915: 0-2915 – -2472: 0-2472 – -2030: 0-2030 – -1587: 0-1587 – -1144: 0-1144 – -701.4: 0-701.4 – -258.7: 0-258.7 – 184.1: 0184.1 – 626.8: 172-10,000-5,00005,000
n / missing199 / 0
Mean ± SD-968.1 ± 3.59e+03
Median439.2
Range-9,999 – 626.8
CV3.71
Skew / kurtosis-2.1 / 2.6
Normal?no

C_mass_g_g

target · numeric
C_mass_g_g distribution0100200-9,999 – -9580: 15-9580 – -9161: 0-9161 – -8741: 0-8741 – -8322: 0-8322 – -7903: 0-7903 – -7484: 0-7484 – -7064: 0-7064 – -6645: 0-6645 – -6226: 0-6226 – -5807: 0-5807 – -5387: 0-5387 – -4968: 0-4968 – -4549: 0-4549 – -4130: 0-4130 – -3710: 0-3710 – -3291: 0-3291 – -2872: 0-2872 – -2453: 0-2453 – -2033: 0-2033 – -1614: 0-1614 – -1195: 0-1195 – -775.8: 12-775.8 – -356.5: 0-356.5 – 62.7: 172-10,000-5,00005,000
n / missing199 / 0
Mean ± SD-775.1 ± 2.65e+03
Median43.9
Range-9,999 – 62.7
CV3.42
Skew / kurtosis-3.2 / 8.4
Normal?no

N_mass_mg_g

target · numeric
N_mass_mg_g distribution0100200-9,999 – -9581: 27-9581 – -9162: 0-9162 – -8744: 0-8744 – -8325: 0-8325 – -7907: 0-7907 – -7488: 0-7488 – -7070: 0-7070 – -6651: 0-6651 – -6233: 0-6233 – -5814: 0-5814 – -5396: 0-5396 – -4977: 0-4977 – -4559: 0-4559 – -4140: 0-4140 – -3722: 0-3722 – -3303: 0-3303 – -2885: 0-2885 – -2466: 0-2466 – -2048: 0-2048 – -1629: 0-1629 – -1211: 0-1211 – -792.4: 0-792.4 – -373.9: 0-373.9 – 44.6: 172-10,000-5,00005,000
n / missing199 / 0
Mean ± SD-1335 ± 3.44e+03
Median24.9
Range-9,999 – 44.6
CV2.58
Skew / kurtosis-2.1 / 2.6
Normal?no

N_mass_g_g

target · numeric
N_mass_g_g distribution0100200-9,999 – -9582: 27-9582 – -9165: 0-9165 – -8749: 0-8749 – -8332: 0-8332 – -7915: 0-7915 – -7498: 0-7498 – -7081: 0-7081 – -6664: 0-6664 – -6248: 0-6248 – -5831: 0-5831 – -5414: 0-5414 – -4997: 0-4997 – -4580: 0-4580 – -4164: 0-4164 – -3747: 0-3747 – -3,330: 0-3,330 – -2913: 0-2913 – -2496: 0-2496 – -2080: 0-2080 – -1663: 0-1663 – -1246: 0-1246 – -829.1: 0-829.1 – -412.3: 0-412.3 – 4.5: 172-10,000-5,00005,000
n / missing199 / 0
Mean ± SD-1354 ± 3.43e+03
Median2.5
Range-9,999 – 4.5
CV2.54
Skew / kurtosis-2.1 / 2.6
Normal?no

LMA_g_m2

target · numeric
LMA_g_m2 distribution0100200-9,999 – -9578: 3-9578 – -9156: 0-9156 – -8735: 0-8735 – -8314: 0-8314 – -7892: 0-7892 – -7471: 0-7471 – -7050: 0-7050 – -6628: 0-6628 – -6207: 0-6207 – -5786: 0-5786 – -5364: 0-5364 – -4943: 0-4943 – -4522: 0-4522 – -4100: 0-4100 – -3679: 0-3679 – -3258: 0-3258 – -2836: 0-2836 – -2415: 0-2415 – -1994: 0-1994 – -1572: 0-1572 – -1151: 0-1151 – -729.9: 0-729.9 – -308.5: 0-308.5 – 112.8: 196-10,000-5,00005,000
n / missing199 / 0
Mean ± SD-82.91 ± 1.23e+03
Median65.67
Range-9,999 – 112.8
CV14.8
Skew / kurtosis-8 / 63
Normal?no

C_area_g_m2

target · numeric
C_area_g_m2 distribution0100200-9,999 – -9580: 30-9580 – -9162: 0-9162 – -8743: 0-8743 – -8324: 0-8324 – -7905: 0-7905 – -7487: 0-7487 – -7068: 0-7068 – -6649: 0-6649 – -6230: 0-6230 – -5812: 0-5812 – -5393: 0-5393 – -4974: 0-4974 – -4555: 0-4555 – -4137: 0-4137 – -3718: 0-3718 – -3299: 0-3299 – -2880: 0-2880 – -2462: 0-2462 – -2043: 0-2043 – -1624: 0-1624 – -1205: 0-1205 – -786.6: 0-786.6 – -367.9: 0-367.9 – 50.88: 169-10,000-5,00005,000
n / missing199 / 0
Mean ± SD-1480 ± 3.6e+03
Median29.66
Range-9,999 – 50.88
CV2.43
Skew / kurtosis-2 / 1.9
Normal?no

N_area_g_m2

target · numeric
N_area_g_m2 distribution0100200-9,999 – -9582: 30-9582 – -9165: 0-9165 – -8749: 0-8749 – -8332: 0-8332 – -7915: 0-7915 – -7498: 0-7498 – -7082: 0-7082 – -6665: 0-6665 – -6248: 0-6248 – -5831: 0-5831 – -5414: 0-5414 – -4998: 0-4998 – -4581: 0-4581 – -4164: 0-4164 – -3747: 0-3747 – -3331: 0-3331 – -2914: 0-2914 – -2497: 0-2497 – -2080: 0-2080 – -1664: 0-1664 – -1247: 0-1247 – -830: 0-830 – -413.2: 0-413.2 – 3.56: 169-10,000-5,00005,000
n / missing199 / 0
Mean ± SD-1506 ± 3.59e+03
Median1.5
Range-9,999 – 3.56
CV2.38
Skew / kurtosis-2 / 1.9
Normal?no

CN_ratio

target · numeric
CN_ratio distribution0100200-9,999 – -9580: 27-9580 – -9160: 0-9160 – -8741: 0-8741 – -8322: 0-8322 – -7903: 0-7903 – -7483: 0-7483 – -7064: 0-7064 – -6645: 0-6645 – -6226: 0-6226 – -5806: 0-5806 – -5387: 0-5387 – -4968: 0-4968 – -4549: 0-4549 – -4129: 0-4129 – -3710: 0-3710 – -3291: 0-3291 – -2872: 0-2872 – -2452: 0-2452 – -2033: 0-2033 – -1614: 0-1614 – -1195: 0-1195 – -775.3: 0-775.3 – -356.1: 0-356.1 – 63.19: 172-10,000-5,00005,000
n / missing199 / 0
Mean ± SD-1338 ± 3.44e+03
Median15.64
Range-9,999 – 63.19
CV2.57
Skew / kurtosis-2.1 / 2.6
Normal?no

USDA_Species_Code_aux

target · categorical
USDA_Species_Code_aux classesCAAQCAAQ: 4646ARLA2ARLA2: 3838ERAN6ERAN6: 3636ARFU2ARFU2: 3131SAPU15SAPU15: 2626PEFR5PEFR5: 2222
n / missing199 / 0
Classes6
Balance (entropy)0.98
Imbalance ratio2
Top classCAAQ (46)

Metadata 1

date

metadata · categorical
date classes2016071820160718: 27272016071720160717: 25252016071420160714: 23232016071620160716: 23232016071320160713: 19192016071920160719: 19192016071120160711: 18182016071020160710: 15152016071220160712: 14142016072020160720: 1010+2 more+2 more: 66
n / missing199 / 0
Classes12
Balance (entropy)0.95
Imbalance ratio9
Top class20160718 (27)
Constant metadata 19
  • ecosis_resource_id0abf3f1f-eb51-4ae6-add8-e8f37f2a664b
  • siteBarrow (Utqiagvik) Environmental Observatory
  • coordinate_precision_notessource-provided coordinates when available
  • year2,019
  • plant_partLeaf
  • canopy_or_leafleaf
  • instrumentSpectra Vista Corporation HR-1024i
  • acquisition_modeContact
  • signal_typereflectance
  • axis_unitnm
  • axis_min350
  • axis_max2,500
  • n_points_original2,151
  • publication_doi10.5440/1336809 | 10.5440/1336812 | 10.5440/1437044 | 10.5440/1482338
  • citationShawn Serbin Wil Lieberman-Cribbin Kim Ely Alistair Rogers. 2019. NGEE Arctic Leaf Spectral Reflectance and Transmittance Data 2014 to 2016 Utqiagvik (Barrow) Alaska. Data set. Available on-line [http://ecosis.org] from the Ecological Spectral Information System (EcoSIS). https://doi.org/10.5440/1437044
  • licensenot specified
  • rights_statusmanual_review_needed
  • usage_scopeprivate_use_only
  • notesEcoSIS package ngee-arctic-leaf-spectral-reflectance-and-transmittance-data-2014-to-2016-utqiagvik--barrow--alaska, no interpolation applied by project.

7 variable(s) omitted (no recorded values).

Alignment

Alignment levelobservation
Sample id availableyes
Samples199
Observations (total)199
Reps per samplemin 1 · mean 1 · max 1

Provenance & citation

ContributorNGEE Arctic Leaf Spectral Reflectance and Transmittance Data 2014 to 2016 Utqiagvik (Barrow) Alaska
Origin · url [open]https://data.ecosis.org/dataset/ngee-arctic-leaf-spectral-reflectance-and-transmittance-data-2014-to-2016-utqiagvik--barrow--alaska
Origin · script [manual]source_to_standard.py — standardization script (maintainer-only)
Publication10.5440/1437044 — NGEE Arctic Leaf Spectral Reflectance and Transmittance, Barrow, Alaska, 2014-2016
Publication10.5440/1336812 — Leaf Mass Area, Leaf Carbon and Nitrogen Content, Barrow, Alaska, 2012-2016
Publication10.5440/1336809 — Leaf Photosynthetic Parameters Vcmax and Jmax and Supporting Gas Exchange Data, Barrow, Alaska, 2012-2016
Publication10.5440/1482338 — Leaf Photosynthetic Parameters: Quantum Yield, Convexity, Respiration, Gross CO2 Assimilation Rate and Raw Gas Exchange Data, Barrow, Alaska, 2016

Governance & integrity

Tierprivate
LicenseLicenseRef-not-cleared
Permitted useResearch and benchmarking; private use only.
Access policyManual download / private-use-only per source.
RedistributionEcoSIS license is missing or unclear; private/internal conversion only by v0.5 policy.
Content version1.0.0
Schema / protocol2.0
Content hashb640bc2c2b71c228…
Processing hash8e296bfe6a68b589…
Metadata hashb8983db4093d726b…

Load this dataset

# pip install nirs4all-datasets
from nirs4all_datasets import get

# private dataset — export requires a Dataverse token
ds = get("ecosis_ngee_arctic_leaf_spectral_reflectance_and_transmittance_reflectance_nirs", token="…")
X, y = ds.x(), ds.y()
print(X.shape, y.shape)

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