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EcoSIS NGEE Tropics GLiHT Puerto Rico Campaign Leaf Spectral Reflectance and Transmittance March 2017 (transmittance)

ecosis · NIR

EcoSIS NGEE Tropics GLiHT Puerto Rico Campaign Leaf Spectral Reflectance and Transmittance March 2017 (transmittance). v2.0 standardized NIRS package: 1 spectral source(s), 8 declared target(s). Auto-generated from dataset_card.json (verify before publication).

nirv2ecosis
222
samples
2,151
wavelengths
1
sources
8
targets
27
metadata
NIR
family

Dataset property explorer

Mean profile risk0.60
Highest axisArtefacts locaux · 1.00
Diagnostics8
Sources profiled1
EcoSIS NGEE Tropics GLiHT Puerto Rico Campaign Leaf Spectral Reflectance and Transmittance March 2017 (transmittance) property profile0.250.50.751integritynoiseartefactsbaselinePCA outliersreferencerepeatabilitystructureEcoSIS NGEE Tropics GLiHT Puerto Rico Campaign Leaf Spectral Reflectance and Transmittance March 2017 (transmittance) profileintegrity: 0.00noise: 0.01artefacts: 1.00baseline: 0.43PCA outliers: 0.55reference: 1.00repeatability: 1.00structure: 0.78EcoSIS NGEE Tro…0 center · 1 outer ring · outward = stronger anomaly / heterogeneity signal

Profile axes

Intégrité0.00
Artefacts locaux1.00
Bruit0.01
Outliers PCA0.55
Distance à la référence1.00
Répétabilité1.00
Baseline / forme0.43
Structure multi-régimes0.78
Diagnostic hypotheses00.250.50.751hypothesis scoreMauvaise répétabilité d'acqui…Mauvaise répétabilité d'acquisition: 0.830.83Splice / raccord détecteursSplice / raccord détecteurs: 0.810.81Signature VERA25-likeSignature VERA25-like: 0.680.68Différence de sonde / géométr…Différence de sonde / géométrie: 0.630.63Dataset multi-régimesDataset multi-régimes: 0.620.62Erreur interpolation / réécha…Erreur interpolation / rééchantillonnage: 0.550.55Spectre hors domaine valideSpectre hors domaine valide: 0.530.53Erreur calibration / référenc…Erreur calibration / référence blanche: 0.530.53
DiagnosticScoreForceSignauxInterprétation probable
Mauvaise répétabilité d'acquisitionX0.83forteRMS/SAM intra-ID 1.00, Bruit/artefacts variables 1.00Positionnement, opérateur ou protocole instable; investiguer les répétitions intra-ID.
Splice / raccord détecteursX0.81forteSpike rate 1.00, Jump rate 1.00, RMS/SAM référence 1.00Rupture aux jonctions de détecteurs, calibration locale ou sonde différente.
Signature VERA25-likeX0.68moyenneSpike rate 1.00, Jump rate 1.00, RMS/SAM référence 1.00Combinaison possible changement de sonde + splice, amplifiée par géométrie, fond ou calibration.
Différence de sonde / géométrieX0.63moyenneRMS/SAM référence 1.00, Répétabilité 1.00, Mahalanobis / T2 0.55Modification de l'illumination, collecte, angle ou distance sonde-échantillon.
Dataset multi-régimesX0.62moyenneRMS/SAM référence 1.00, Répétabilité 1.00, Structure PCA 0.78Mélange de campagnes, opérateurs, lots, setups ou sous-populations spectrales.
Erreur interpolation / rééchantillonnageX0.55moyenneSpike rate 1.00, Jump rate 1.00, SNR normal/élevé 1.00Artefacts numériques ou traitement spectral incorrect.
Spectre hors domaine valideX0.53moyenneRMS/SAM référence 1.00, Structure PCA 0.78, Mahalanobis / T2 0.55Variété, espèce, lot ou condition différente mais physiquement plausible.
Erreur calibration / référence blancheX0.53moyenneRMS/SAM référence 1.00, artefacts locaux 1.00, Mahalanobis / T2 0.55Décalage systématique entre campagnes, instruments ou référence blanche.

Spectral sources

ngee-tropics_puerto_rico_march2017_leaf_spectral_transmittance.csv

X · NIR · Spectra Vista Corporation, Spectral Evolution HR-1024i, PSR Plus
ngee-tropics_puerto_rico_march2017_leaf_spectral_transmittance.csv spectra-20020406001,0002,0003,000q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / nm350nm — median 8.33 (q25–q75 -1.315–17.86)365nm — median 2.21 (q25–q75 0.315–4.345)381nm — median 0.9 (q25–q75 0.27–1.805)396nm — median 0.55 (q25–q75 0.16–1.04)412nm — median 0.37 (q25–q75 0.105–0.63)427nm — median 0.37 (q25–q75 0.19–0.745)443nm — median 0.51 (q25–q75 0.24–0.915)458nm — median 0.68 (q25–q75 0.345–1.305)474nm — median 0.87 (q25–q75 0.385–1.505)489nm — median 0.97 (q25–q75 0.495–1.74)505nm — median 1.67 (q25–q75 0.97–3.135)520nm — median 4.2 (q25–q75 2.78–6.75)536nm — median 6.89 (q25–q75 4.78–10.55)551nm — median 7.83 (q25–q75 5.575–11.74)567nm — median 7.1 (q25–q75 4.815–11.32)582nm — median 5.32 (q25–q75 3.43–9.225)597nm — median 4.73 (q25–q75 2.86–8.435)613nm — median 4.07 (q25–q75 2.425–7.365)628nm — median 3.54 (q25–q75 2.075–6.59)644nm — median 2.69 (q25–q75 1.475–5.265)659nm — median 2.01 (q25–q75 0.98–3.875)675nm — median 1.33 (q25–q75 0.675–2.475)690nm — median 3.1 (q25–q75 1.795–5.64)706nm — median 14.95 (q25–q75 11.5–20.74)721nm — median 27.41 (q25–q75 22.68–32.64)737nm — median 35.99 (q25–q75 31.97–40.57)752nm — median 39.55 (q25–q75 35.67–43.77)768nm — median 40.81 (q25–q75 36.98–45.07)783nm — median 41.46 (q25–q75 37.53–45.66)799nm — median 41.99 (q25–q75 37.99–46.02)814nm — median 42.35 (q25–q75 38.3–46.24)829nm — median 42.67 (q25–q75 38.65–46.45)845nm — median 42.98 (q25–q75 39.01–46.8)860nm — median 43.38 (q25–q75 39.3–46.95)876nm — median 43.62 (q25–q75 39.6–47.2)891nm — median 43.91 (q25–q75 39.89–47.43)907nm — median 44.05 (q25–q75 40.09–47.57)922nm — median 44.17 (q25–q75 40.46–47.78)938nm — median 44.32 (q25–q75 40.4–47.84)953nm — median 44.11 (q25–q75 40.26–47.47)969nm — median 43.78 (q25–q75 39.89–47.18)984nm — median 43.86 (q25–q75 39.74–47.08)1,000nm — median 44.2 (q25–q75 40.1–47.56)1,015nm — median 44.77 (q25–q75 40.73–48.09)1,031nm — median 45.26 (q25–q75 41.34–48.56)1,046nm — median 45.58 (q25–q75 41.68–48.9)1,062nm — median 45.79 (q25–q75 42.03–49.2)1,077nm — median 45.99 (q25–q75 42.2–49.38)1,092nm — median 46.09 (q25–q75 42.39–49.35)1,108nm — median 46.05 (q25–q75 42.37–49.4)1,123nm — median 45.96 (q25–q75 42.11–49.35)1,139nm — median 45.26 (q25–q75 41.04–48.64)1,154nm — median 44.02 (q25–q75 39.92–47.44)1,170nm — median 43.68 (q25–q75 39.44–47.03)1,185nm — median 43.66 (q25–q75 39.33–47.01)1,201nm — median 43.58 (q25–q75 39.32–47.06)1,216nm — median 43.94 (q25–q75 39.66–47.26)1,232nm — median 44.31 (q25–q75 40.12–47.65)1,247nm — median 44.57 (q25–q75 40.46–47.88)1,263nm — median 44.82 (q25–q75 40.67–48.08)1,278nm — median 44.85 (q25–q75 40.64–48.11)1,294nm — median 44.61 (q25–q75 40.34–47.9)1,309nm — median 44 (q25–q75 39.81–47.4)1,324nm — median 42.7 (q25–q75 38.42–46.28)1,340nm — median 41.03 (q25–q75 36.42–44.46)1,355nm — median 39.61 (q25–q75 34.78–43.42)1,371nm — median 37.31 (q25–q75 32.38–41.51)1,386nm — median 31.39 (q25–q75 26.66–35.88)1,402nm — median 22.24 (q25–q75 18.03–26.9)1,417nm — median 16.82 (q25–q75 13.22–21.45)1,433nm — median 14.91 (q25–q75 11.54–19.32)1,448nm — median 14.38 (q25–q75 11.23–18.97)1,464nm — median 14.75 (q25–q75 11.6–19.45)1,479nm — median 16.24 (q25–q75 12.86–21.07)1,495nm — median 18.41 (q25–q75 14.72–23.55)1,510nm — median 20.65 (q25–q75 16.74–25.89)1,526nm — median 23.13 (q25–q75 18.72–28.26)1,541nm — median 25.19 (q25–q75 20.53–30.24)1,556nm — median 26.98 (q25–q75 22.16–32.05)1,572nm — median 28.66 (q25–q75 23.64–33.68)1,587nm — median 29.87 (q25–q75 24.91–34.88)1,603nm — median 31.07 (q25–q75 26.05–36.09)1,618nm — median 32.03 (q25–q75 26.9–36.62)1,634nm — median 32.72 (q25–q75 27.52–37.65)1,649nm — median 33.14 (q25–q75 27.84–38.09)1,665nm — median 33.26 (q25–q75 28.06–38.07)1,680nm — median 33.2 (q25–q75 27.97–37.91)1,696nm — median 32.94 (q25–q75 27.44–37.73)1,711nm — median 32.52 (q25–q75 26.82–37.23)1,727nm — median 31.77 (q25–q75 26.12–36.39)1,742nm — median 31.23 (q25–q75 25.67–35.92)1,758nm — median 30.16 (q25–q75 24.75–35.14)1,773nm — median 29.36 (q25–q75 24.15–34.62)1,788nm — median 29.05 (q25–q75 23.93–34.32)1,804nm — median 29.26 (q25–q75 24.09–34.33)1,819nm — median 29.37 (q25–q75 24.3–34.45)1,835nm — median 29.09 (q25–q75 24.02–34.23)1,850nm — median 27.86 (q25–q75 22.68–32.95)1,866nm — median 23.27 (q25–q75 18.63–28.33)1,881nm — median 14.22 (q25–q75 10.91–18.92)1,897nm — median 6.54 (q25–q75 4.945–9.83)1,912nm — median 2.03 (q25–q75 1.01–3.735)1,928nm — median 1.42 (q25–q75 0.62–2.915)1,943nm — median 1.67 (q25–q75 0.77–3.33)1,959nm — median 2.36 (q25–q75 1.25–4.51)1,974nm — median 3.2 (q25–q75 1.85–5.81)1,990nm — median 4.47 (q25–q75 2.88–7.72)2,005nm — median 5.78 (q25–q75 3.98–9.535)2,021nm — median 7.18 (q25–q75 5.01–11.45)2,036nm — median 8.73 (q25–q75 6.18–13.01)2,051nm — median 9.88 (q25–q75 7.33–14.44)2,067nm — median 11.06 (q25–q75 8.005–15.66)2,082nm — median 11.98 (q25–q75 8.92–17.18)2,098nm — median 13.34 (q25–q75 9.85–18.59)2,113nm — median 14.84 (q25–q75 10.94–19.91)2,129nm — median 16.02 (q25–q75 11.77–21.05)2,144nm — median 16.3 (q25–q75 12.31–21.91)2,160nm — median 17.52 (q25–q75 13.18–22.69)2,175nm — median 17.91 (q25–q75 13.41–22.88)2,191nm — median 18.32 (q25–q75 13.88–23.31)2,206nm — median 18.34 (q25–q75 13.91–23.94)2,222nm — median 18.32 (q25–q75 14.15–23.61)2,237nm — median 18.69 (q25–q75 13.96–23.41)2,253nm — median 17.55 (q25–q75 12.71–22.33)2,268nm — median 16.5 (q25–q75 11.71–20.82)2,283nm — median 15.36 (q25–q75 10.99–20.19)2,299nm — median 14.39 (q25–q75 10.16–18.77)2,314nm — median 13.44 (q25–q75 9.34–18.56)2,330nm — median 12.7 (q25–q75 9.01–17.09)2,345nm — median 11.79 (q25–q75 7.315–16.24)2,361nm — median 11.51 (q25–q75 8.25–15.65)2,376nm — median 11.22 (q25–q75 7.785–15.37)2,392nm — median 8.92 (q25–q75 5.995–13.97)2,407nm — median 8.13 (q25–q75 4.77–11.38)2,423nm — median 7.04 (q25–q75 3.785–10.46)2,438nm — median 6.17 (q25–q75 3.54–8.525)2,454nm — median 5.24 (q25–q75 2.715–8.245)2,469nm — median 4.54 (q25–q75 2.08–6.7)2,485nm — median 3.87 (q25–q75 1.685–6.17)2,500nm — median 3.34 (q25–q75 1.625–5.57)

Sampling

Wavelengths2,151
Axis range350–2,500 nm
Mean spacing1 nm
Griduniform
Observations223

Signal & quality

Value range-65.3 – 325
Mean range0.563 – 45.6
Mean level23.29
Area5.008e+04
PTP45.09
Noise RMS0.012105
SNR1.9e+03
SNR dB7e+01 dB
Dynamic range45.1
Smoothness0.882
Saturated0.0%
X-outliers97

Integrity & artefacts

NaN ratio0.00%
Inf count0
Zero ratio0.07%
Spike count55,308
Spike rate11.54%
Jump count13,850
Jump rate2.89%
Clip fraction0.00%

Shape & reference

Baseline slope-9.7427
Curvature RMS0.7374
D1 RMS0.70559
RMS to mean4.5217
RMS p9513.654
SAM to mean0.097155
SAM p950.22798
Affine offset p957.3788
Affine gain p95 Δ0.24993
Affine residual p955.2765
Xcorr lag p953

Outliers & repeatability

PCA Q p95/median2.9
Hotelling T2 p95/median4.4
Mahalanobis H p95/median2.1
Repeat groups1
RMS intra-ID6.7259
SAM intra-ID0.16064
CV intra-ID0.50387

Dimensionality (PCA)

Effective rank2
PCs → 95% var4
PCs → 99% var15
Top-10 cum. var98.5%
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_ratio0.0705%0.01faibleNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Amplitude globaleMean reflectanceamplitude.mean_reflectance23.2870.43moyenValeur 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_curve500850.43moyenValeur 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_peak45.0860.00faibleVariabilité forteSaturationmax(mean_spectrum) - min(mean_spectrum)alert increases when dynamic range is abnormally flat
Amplitude globaleVarianceamplitude.variance283.720.00faibleNormal ou hétérogèneMauvais contactvar(X finite)alert increases when variance/dynamic range is abnormally flat
BruitNoise RMSnoise.noise_rms0.0121050.01faibleStableLampe, détecteurmedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
BruitSNRnoise.snr1927.30.00faibleBon signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
BruitBandwise SNRnoise.bandwise_snr_min1.22270.95fortZone 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_count55,3081.00fortArtefactsCosmic rays, splicecount robust outliers in second derivativealert follows spike_rate, saturated at 1%
Artefacts locauxSpike rateartefacts.spike_rate11.5%1.00fortSpectre suspectInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Artefacts locauxJump countartefacts.jump_count13,8501.00fortRaccord détecteurSplicecount robust outliers in first derivativealert follows jump_rate, saturated at 1%
Artefacts locauxJump rateartefacts.jump_rate2.89%1.00fortProblème spectralCalibrationjump_count / (n_samples * (n_features - 1))alert = min(1, jump_rate / 0.01)
Artefacts locauxClip fractionartefacts.clip_fraction0.000417%0.00faibleNormalDétecteur saturéfraction of finite cells equal to repeated min/max extremaalert = min(1, clip_fraction / 0.01)
Forme spectraleBaseline slopeshape.baseline_slope-9.74270.43moyenDériveÉclairementlinear slope of mean_spectrum over normalized axisalert = abs(slope / signal_scale), saturated at 0.5
Forme spectraleCurvature RMSshape.curvature_rms0.73741.00fortForme inhabituelleFond, splicemedian RMS(second derivative per spectrum)alert = curvature_rms / signal_scale, saturated at 1%
Forme spectraleD1 RMSshape.d1_rms0.705590.31faiblePlatBiologie ou artefactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Outliers multivariésPCA Q (SPE)outliers.pca_q_ratio2.92860.37faibleConformeArtefact, mélangep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Outliers multivariésHotelling T²outliers.hotelling_t2_ratio4.37820.55moyenExtrême mais cohérentVariabilité naturellep95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Outliers multivariésMahalanobis Houtliers.mahalanobis_h_ratio2.09230.52moyenOutlier globalDomaine différentp95(sqrt(T2)) / median(sqrt(T2))alert = min(1, mahalanobis_h_ratio / 4)
Comparaison à référenceRMS to mean spectrumreference.rms_to_mean_spectrum_p9513.6541.00fortSpectre 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_p950.227980.65moyenForme différenteFond, géométriep95 spectral angle to dataset mean spectrumalert = min(1, SAM_p95 / 0.35 rad)
RépétabilitéRMS intra-IDrepeatability.rms_intra_id6.72591.00fortMauvaise répétabilitéPositionnementmedian RMS distance to repeated-sample centroidalert = RMS_intra_ID / signal_scale, saturated at 10%
RépétabilitéSAM intra-IDrepeatability.sam_intra_id0.160641.00fortInstableAcquisitionmedian SAM to repeated-sample centroidalert = min(1, SAM_intra_ID / 0.15 rad)
RépétabilitéCV intra-IDrepeatability.cv_intra_id0.503871.00fortMauvais contrôleOpérateurmedian within-ID band CValert = min(1, CV_intra_ID / 0.25)
Structure du datasetPCA score densitystructure.pca_score_density0.0166690.78fortSous-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_p952.33670.67moyenSpectre isoléCas raresp95 approximate LOF from PCA-score kNN distancesalert = min(1, max(0, LOF_p95 - 1) / 2)
Structure du datasetIsolation Forest scorestructure.isolation_forest_score_p950.543120.78fortSpectre atypiqueDiverses causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent
X PCA score plot-1,000-50005001,000-400-2000200400PC1 -220.2 · PC2 17.58PC1 413 · PC2 78.2PC1 -124.7 · PC2 63.44PC1 -217.8 · PC2 83.89PC1 42.79 · PC2 -39.09PC1 119.5 · PC2 56.92PC1 17.77 · PC2 -38.86PC1 148.4 · PC2 -35.63PC1 168.7 · PC2 -14.17PC1 -228.2 · PC2 -8.352PC1 -18.27 · PC2 106.7PC1 -39.91 · PC2 56.12PC1 -78.05 · PC2 -7.206PC1 -78.98 · PC2 -26.48PC1 134.3 · PC2 -0.9525PC1 188.5 · PC2 34.76PC1 624.5 · PC2 -68.21PC1 732.2 · PC2 5.116PC1 267.3 · PC2 -61.3PC1 308.8 · PC2 -35.33PC1 662.1 · PC2 -67.25PC1 550.5 · PC2 -142.8PC1 712.8 · PC2 -31.88PC1 238.3 · PC2 -24.77PC1 317.9 · PC2 37.98PC1 167.7 · PC2 -119.9PC1 194.4 · PC2 -65.7PC1 -19.52 · PC2 -149.3PC1 58.84 · PC2 -95.86PC1 -28.19 · PC2 -15.77PC1 290.5 · PC2 -76.93PC1 436.9 · PC2 35.38PC1 158.3 · PC2 -57.41PC1 86.91 · PC2 -42.25PC1 220 · PC2 -121.8PC1 261.9 · PC2 -78.06PC1 262.7 · PC2 22.4PC1 20.5 · PC2 7.796PC1 80.57 · PC2 -9.84PC1 346.5 · PC2 -114PC1 434.5 · PC2 -0.3469PC1 522.7 · PC2 39.36PC1 -104.4 · PC2 -24.75PC1 7.697 · PC2 -15.66PC1 -121.7 · PC2 79.87PC1 -136.5 · PC2 1.702PC1 -36.92 · PC2 -25.49PC1 -142 · PC2 -23.56PC1 44.52 · PC2 -7.141PC1 -137.4 · PC2 -9.488PC1 -186.3 · PC2 -16.89PC1 -399.4 · PC2 51.19PC1 -291.2 · PC2 77.91PC1 -349.2 · PC2 73.97PC1 -125.1 · PC2 73.43PC1 -163.6 · PC2 101.5PC1 -120.4 · PC2 61.68PC1 675.9 · PC2 -75.42PC1 139.9 · PC2 -173.9PC1 249.8 · PC2 -57.69PC1 -4.353 · PC2 -12.82PC1 -59.57 · PC2 -2.983PC1 -69.06 · PC2 39.49PC1 681.3 · PC2 -73.9PC1 685.4 · PC2 -76.96PC1 -192.2 · PC2 55.05PC1 -113.1 · PC2 24.44PC1 -157 · PC2 27.98PC1 -203.4 · PC2 48.73PC1 181.7 · PC2 -54.67PC1 373.9 · PC2 55.36PC1 339.6 · PC2 80.86PC1 404.3 · PC2 77.52PC1 70.84 · PC2 -98.71PC1 84.29 · PC2 -46.07PC1 94.05 · PC2 -1.52PC1 -81.98 · PC2 39.33PC1 26.78 · PC2 103.9PC1 631.7 · PC2 -55.09PC1 66.08 · PC2 78.22PC1 212.2 · PC2 43.89PC1 -56.24 · PC2 -81.96PC1 -24.87 · PC2 -65.27PC1 174.1 · PC2 11.05PC1 176.5 · PC2 38.86PC1 -440 · PC2 -25.77PC1 -492.4 · PC2 58.98PC1 -110.4 · PC2 80.95PC1 106.9 · PC2 41.45PC1 178.4 · PC2 13.98PC1 -180.3 · PC2 42.18PC1 -201.5 · PC2 -86.1PC1 6.6 · PC2 -52.18PC1 -166.2 · PC2 114.8PC1 89.93 · PC2 77.05PC1 -262.1 · PC2 48.05PC1 -18.37 · PC2 110.9PC1 -79.45 · PC2 39.93PC1 48.16 · PC2 46.74PC1 -425.5 · PC2 -246.6PC1 84.19 · PC2 -5.709PC1 -398.6 · PC2 247.7PC1 -276 · PC2 268.4PC1 108.7 · PC2 92.5PC1 179.1 · PC2 -30.38PC1 -81.95 · PC2 -30.82PC1 -346 · PC2 190.1PC1 9.463 · PC2 -80.93PC1 -728.4 · PC2 -235.6PC1 68.3 · PC2 12.36PC1 -706.3 · PC2 -1.896PC1 -108.4 · PC2 -3.456PC1 -72.93 · PC2 1.417PC1 -218.7 · PC2 5.902PC1 -127.3 · PC2 1.556PC1 -212.2 · PC2 -16.39PC1 -379 · PC2 -152.8PC1 -515.4 · PC2 -165.4PC1 3.211 · PC2 35.52PC1 -205.4 · PC2 48.66PC1 -57.33 · PC2 57.14PC1 -405.9 · PC2 -81.26PC1 394 · PC2 19.35PC1 409.9 · PC2 21.99PC1 385.6 · PC2 21.74PC1 -46.18 · PC2 -136.4PC1 -130.7 · PC2 -131.1PC1 14.05 · PC2 -124.2PC1 -115.2 · PC2 109.4PC1 -178.4 · PC2 95.55PC1 -196.1 · PC2 36.11PC1 -119.6 · PC2 26.09PC1 -210.6 · PC2 92.17PC1 4.096 · PC2 12.43PC1 -84.27 · PC2 -88.95PC1 -331.2 · PC2 141PC1 -336.4 · PC2 103PC1 81.25 · PC2 32.87PC1 207.6 · PC2 -8.377PC1 -616.1 · PC2 -62.62PC1 -38.29 · PC2 -41.92PC1 -1.203 · PC2 -11.81PC1 31.71 · PC2 14.72PC1 -4.678 · PC2 149.2PC1 -225.4 · PC2 126.4PC1 1.142 · PC2 85.82PC1 -118.8 · PC2 107.7PC1 -286.2 · PC2 -32.9PC1 -169.1 · PC2 77.12PC1 -33.64 · PC2 121.5PC1 230.9 · PC2 80.5PC1 118.5 · PC2 103.9PC1 -236 · PC2 133PC1 -189.4 · PC2 104.3PC1 -39.89 · PC2 48.27PC1 298.5 · PC2 -62.73PC1 -137.5 · PC2 10.45PC1 -146.3 · PC2 90.55PC1 -206.6 · PC2 41.82PC1 -146.3 · PC2 -136.9PC1 378.8 · PC2 28.89PC1 -409.2 · PC2 -103.5PC1 -314.6 · PC2 -57.38PC1 -55.79 · PC2 44.06PC1 -195.5 · PC2 27.21PC1 -246.8 · PC2 39.99PC1 192.1 · PC2 -5.303PC1 -61.74 · PC2 -147.8PC1 232.4 · PC2 -3.464PC1 412.8 · PC2 -50.79PC1 459.8 · PC2 -15.14PC1 401.1 · PC2 -21.05PC1 154.4 · PC2 38.39PC1 151 · PC2 11.11PC1 53.29 · PC2 21.14PC1 83.5 · PC2 15.16PC1 10.86 · PC2 -11.8PC1 330.3 · PC2 126PC1 358.6 · PC2 92.6PC1 335.1 · PC2 110.9PC1 340.5 · PC2 110.6PC1 66.12 · PC2 -8.592PC1 39.94 · PC2 -21.05PC1 -58.85 · PC2 -45.32PC1 2.34 · PC2 -12.85PC1 192.8 · PC2 -15.32PC1 251.5 · PC2 5.852PC1 184.4 · PC2 8.559PC1 -163.9 · PC2 -201.8PC1 -121.1 · PC2 -225.6PC1 -78.76 · PC2 -189.5PC1 186.6 · PC2 -33.86PC1 163.4 · PC2 -30.96PC1 209.3 · PC2 -28.84PC1 26.4 · PC2 51.94PC1 -258.1 · PC2 -133.5PC1 -206.5 · PC2 -125.6PC1 156.3 · PC2 83.04PC1 -391.8 · PC2 -169.6PC1 224.1 · PC2 67.56PC1 -92.74 · PC2 112.7PC1 -309.2 · PC2 -205PC1 -115.3 · PC2 -158.9PC1 82.81 · PC2 16.33PC1 204.5 · PC2 22.4PC1 -538.9 · PC2 -167.6PC1 -508.3 · PC2 -40.51PC1 -371.3 · PC2 52.3PC1 -331.7 · PC2 92.85PC1 -141.2 · PC2 -25.3PC1 -20.91 · PC2 22.1PC1 -701.6 · PC2 -10.61PC1 -438.5 · PC2 163.9PC1 -188.3 · PC2 -142.2PC1 -7.636 · PC2 -56.97PC1 185.5 · PC2 102.1PC1 -363.2 · PC2 -175.9PC1 57.58 · PC2 16.4PC1 18.2 · PC2 74.13PC1 -266.1 · PC2 -105.9PC1 209.2 · PC2 93.89PC1 -639 · PC2 60.37PC1 -440.2 · PC2 103PC1 (84.4%)PC2 (8.1%)223 scores
PCA explained variance0%25%50%75%100%PC1: 84.4% (cumulative 84.4%)1PC2: 8.1% (cumulative 92.5%)2PC3: 2.5% (cumulative 95.0%)3PC4: 1.2% (cumulative 96.1%)4PC5: 0.8% (cumulative 96.9%)5PC6: 0.6% (cumulative 97.5%)6PC7: 0.4% (cumulative 97.9%)7PC8: 0.2% (cumulative 98.2%)8PC9: 0.2% (cumulative 98.4%)9PC10: 0.2% (cumulative 98.5%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)
X-Y spectral correlation 8
X · Leaf_H2O_pc spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale
X · SLA spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale
X · LMA 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
Leaf_H2O_pc0.6165920.2515.4%
SLA0.1223980.01140.0%
LMA0.1782,4900.09250.0%
Cmass0.3534430.130.0%
Nmass0.4652,2800.3750.0%
CNratio0.4491,6580.3390.0%
Carea0.1812,4900.07630.0%
Narea0.1672,4900.05620.0%

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 8

Leaf_H2O_pc

target · numeric
Leaf_H2O_pc distribution0102044.19 – 45.88: 345.88 – 47.56: 647.56 – 49.24: 649.24 – 50.93: 1750.93 – 52.61: 1652.61 – 54.3: 1854.3 – 55.98: 855.98 – 57.67: 2057.67 – 59.35: 1759.35 – 61.04: 1661.04 – 62.72: 1662.72 – 64.41: 1064.41 – 66.09: 466.09 – 67.78: 1067.78 – 69.47: 869.47 – 71.15: 571.15 – 72.83: 572.83 – 74.52: 774.52 – 76.2: 676.2 – 77.89: 177.89 – 79.57: 1079.57 – 81.26: 281.26 – 82.94: 282.94 – 84.63: 2102050100
n / missing222 / 7
Mean ± SD60.61 ± 9.28
Median59.11
Range44.19 – 84.63
CV0.153
Skew / kurtosis0.6 / -0.42
Normal?no

SLA

target · numeric
SLA distribution0100200300-9,999 – -9570: 1-9570 – -9141: 0-9141 – -8712: 0-8712 – -8283: 0-8283 – -7854: 0-7854 – -7425: 0-7425 – -6996: 0-6996 – -6567: 0-6567 – -6138: 0-6138 – -5709: 0-5709 – -5280: 0-5280 – -4851: 0-4851 – -4422: 0-4422 – -3993: 0-3993 – -3564: 0-3564 – -3135: 0-3135 – -2706: 0-2706 – -2277: 0-2277 – -1848: 0-1848 – -1419: 0-1419 – -990: 0-990 – -561: 0-561 – -132: 0-132 – 297: 214-10,000-5,00005,000
n / missing222 / 7
Mean ± SD69.49 ± 692
Median109.9
Range-9,999 – 297
CV9.95
Skew / kurtosis-15 / 2.1e+02
Normal?no

LMA

target · numeric
LMA distribution0100200300-9,999 – -9568: 1-9568 – -9137: 0-9137 – -8706: 0-8706 – -8275: 0-8275 – -7844: 0-7844 – -7413: 0-7413 – -6982: 0-6982 – -6551: 0-6551 – -6120: 0-6120 – -5690: 0-5690 – -5259: 0-5259 – -4828: 0-4828 – -4397: 0-4397 – -3966: 0-3966 – -3535: 0-3535 – -3104: 0-3104 – -2673: 0-2673 – -2242: 0-2242 – -1811: 0-1811 – -1380: 0-1380 – -949.1: 0-949.1 – -518.1: 0-518.1 – -87.16: 0-87.16 – 343.8: 214-10,000-5,00005,000
n / missing222 / 7
Mean ± SD56.04 ± 691
Median90.94
Range-9,999 – 343.8
CV12.3
Skew / kurtosis-15 / 2.1e+02
Normal?no

Cmass

target · numeric
Cmass distribution01020358.2 – 366.3: 2366.3 – 374.4: 0374.4 – 382.6: 0382.6 – 390.7: 0390.7 – 398.8: 1398.8 – 406.9: 0406.9 – 415: 0415 – 423.2: 2423.2 – 431.3: 0431.3 – 439.4: 2439.4 – 447.5: 9447.5 – 455.6: 5455.6 – 463.8: 7463.8 – 471.9: 18471.9 – 480: 20480 – 488.1: 20488.1 – 496.3: 12496.3 – 504.4: 19504.4 – 512.5: 14512.5 – 520.6: 11520.6 – 528.7: 8528.7 – 536.9: 5536.9 – 545: 1545 – 553.1: 41002005001,000
n / missing222 / 62
Mean ± SD486 ± 31.1
Median485.2
Range358.2 – 553.1
CV0.064
Skew / kurtosis-0.85 / 2.6
Normal?no

Nmass

target · numeric
Nmass distribution010209.6 – 11.38: 1011.38 – 13.15: 913.15 – 14.93: 1514.93 – 16.7: 1416.7 – 18.48: 1918.48 – 20.25: 1820.25 – 22.02: 1222.02 – 23.8: 1723.8 – 25.58: 1325.58 – 27.35: 1527.35 – 29.12: 229.12 – 30.9: 430.9 – 32.68: 232.68 – 34.45: 334.45 – 36.23: 136.23 – 38: 138 – 39.77: 339.77 – 41.55: 141.55 – 43.33: 043.33 – 45.1: 045.1 – 46.88: 046.88 – 48.65: 048.65 – 50.43: 050.43 – 52.2: 10204060
n / missing222 / 62
Mean ± SD20.67 ± 6.97
Median19.55
Range9.6 – 52.2
CV0.337
Skew / kurtosis1.1 / 2.3
Normal?no

CNratio

target · numeric
CNratio distribution010209.03 – 10.78: 110.78 – 12.53: 112.53 – 14.27: 514.27 – 16.02: 816.02 – 17.77: 717.77 – 19.52: 1419.52 – 21.27: 1721.27 – 23.01: 1823.01 – 24.76: 1224.76 – 26.51: 1226.51 – 28.26: 1128.26 – 30: 1030 – 31.75: 731.75 – 33.5: 833.5 – 35.25: 735.25 – 37: 437 – 38.74: 138.74 – 40.49: 340.49 – 42.24: 442.24 – 43.99: 143.99 – 45.74: 245.74 – 47.48: 147.48 – 49.23: 349.23 – 50.98: 30204060
n / missing222 / 62
Mean ± SD26.11 ± 8.78
Median24.13
Range9.03 – 50.98
CV0.336
Skew / kurtosis0.87 / 0.41
Normal?no

Carea

target · numeric
Carea distribution0100200-9,999 – -9575: 1-9575 – -9152: 0-9152 – -8728: 0-8728 – -8304: 0-8304 – -7881: 0-7881 – -7457: 0-7457 – -7033: 0-7033 – -6610: 0-6610 – -6186: 0-6186 – -5762: 0-5762 – -5339: 0-5339 – -4915: 0-4915 – -4491: 0-4491 – -4068: 0-4068 – -3644: 0-3644 – -3220: 0-3220 – -2797: 0-2797 – -2373: 0-2373 – -1949: 0-1949 – -1526: 0-1526 – -1102: 0-1102 – -678.4: 0-678.4 – -254.8: 0-254.8 – 168.9: 159-10,000-5,00005,000
n / missing222 / 62
Mean ± SD-11.84 ± 795
Median44.39
Range-9,999 – 168.9
CV67.1
Skew / kurtosis-13 / 1.6e+02
Normal?no

Narea

target · numeric
Narea distribution0100200-9,999 – -9582: 1-9582 – -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 – -3330: 0-3330 – -2913: 0-2913 – -2496: 0-2496 – -2080: 0-2080 – -1663: 0-1663 – -1246: 0-1246 – -829.1: 0-829.1 – -412.2: 0-412.2 – 4.57: 159-10,000-5,00005,000
n / missing222 / 62
Mean ± SD-60.51 ± 791
Median1.98
Range-9,999 – 4.57
CV13.1
Skew / kurtosis-13 / 1.6e+02
Normal?no
Constant metadata 18
  • ecosis_resource_id4d62bf32-4045-4fdf-87cc-8320076a453a
  • coordinate_precision_notessource-provided coordinates when available
  • year2,019
  • plant_partLeaf
  • canopy_or_leafleaf
  • instrumentSpectra Vista Corporation, Spectral Evolution HR-1024i, PSR Plus
  • acquisition_modeContact
  • signal_typetransmittance
  • axis_unitnm
  • axis_min350
  • axis_max2,500
  • n_points_original2,151
  • publication_doi10.15486/ngt/1495202 | 10.15486/ngt/1495204
  • citationShawn Serbin Ran Meng Jin Wu Kim Ely. 2019. NGEE Tropics GLiHT Puerto Rico Campaign Leaf Spectral Reflectance and Transmittance March 2017. Data set. Available on-line [http://ecosis.org] from the Ecological Spectral Information System (EcoSIS). http://dx.doi.org/10.15486/ngt/1495204
  • licenseOpen Data Commons Attribution License
  • rights_statusexplicit_open
  • usage_scopepublic_reuse_possible
  • notesEcoSIS package ngee-tropics-gliht-puerto-rico-campaign-leaf-spectral-reflectance-and-transmittance-march-2017, no interpolation applied by project.

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

Alignment

Alignment levelobservation
Sample id availableyes
Samples222
Observations (total)223
Reps per samplemin 1 · mean 1.005 · max 2

Provenance & citation

ContributorNGEE Tropics GLiHT Puerto Rico Campaign Leaf Spectral Reflectance and Transmittance March 2017
Origin · url [open]https://data.ecosis.org/dataset/ngee-tropics-gliht-puerto-rico-campaign-leaf-spectral-reflectance-and-transmittance-march-2017
Origin · script [manual]source_to_standard.py — standardization script (maintainer-only)
Publication10.15486/ngt/1495204 — G-LiHT Campaign Leaf Spectral Reflectance and Transmittance, Mar2017: Puerto Rico
Publication10.15486/ngt/1495202 — G-LiHT Campaign Leaf Mass Area and Water Content, Mar2017: Puerto Rico

Governance & integrity

Tierpublic
LicenseODC-By-1.0
Permitted useResearch and benchmarking.
Access policyOpen per source license.
RedistributionEcoSIS CKAN metadata exposes an open license.
Content version1.0.0
Schema / protocol2.0
Content hashd4f18182a778ca10…
Processing hashd883331b2331eca5…
Metadata hash23648fb8f3a0b6ce…

Load this dataset

# pip install nirs4all-datasets
from nirs4all_datasets import get

ds = get("ecosis_ngee_tropics_gliht_puerto_rico_campaign_leaf_spectral_r_transmittance_nirs")            # DOI-pinned, checksum-verified, cached
X, y = ds.x(), ds.y()
print(X.shape, y.shape)
card.jsoncroissant.jsonIdentity metadata only — the dataset bytes live at the origin / DOI.