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111 to 120 of 7,787 Results
Plain Text - 26.9 KB - MD5: ebc86a5a2e3a47c0c44f38afd2ccd731
Données
Debit journalier : THYSSE KAYMOR MICROBV1 a S4 codification 1381299004Q
Plain Text - 22.1 KB - MD5: b2626679bf62894c460e7139ddc193af
Données
Debit journalier : THYSSE KAYMOR MICROBV2 a S5 codification 1381299005Q
Plain Text - 8.3 KB - MD5: d016dcc72a197735885714c7c2f4a06c
Données
Debit journalier : THYSSE KAYMOR SONKORONG a SAM codification 1381299006Q
JPEG Image - 225.1 KB - MD5: 54fd9a37cd1d7428b87200ddd58e2c35
Documentation
Image/carte de situation des stations hydrométriques - GoogleEarth
Adobe PDF - 7.5 KB - MD5: 2bcb0558dbf39e8cc45a708f8faa37a4
Documentation
Fichier Lisez moi, Readme
Keyhole Markup Language - 320.4 KB - MD5: c08775bfe02453c034a14985aac453a2
Données
Fichier GoogleEarth : positionnement géographique des stations hydrométriques
Python Source Code - 7.7 KB - MD5: 79fdb788c37dbc1c2aa1769f4b89e763
Code
Script to estimate oxygen production from peat thickness using statistical regressions.
Python Source Code - 5.1 KB - MD5: 5519f5d34ae05f3410c1f6b1cbf04bed
Code
Script to displays two regressions (a polynomial fit between square root of peat thickness and TOC %), and then a linear fit between TOC % and the oxygen demand (dO₂)), displaying and saving the fitted curves with their uncertainties.
Python Source Code - 2.7 KB - MD5: 3c516a94589b526f979cc3f2fd1cd913
Code
Script to read two raster files representing median peat thickness and its relative uncertainty, then to compute and save two maps showing the estimated upper (here deeper peat depths) and lower bounds (here shallower peat depths) of thickness.
Python Source Code - 4.8 KB - MD5: b2e174f368715a11429e32421a0f8f15
Code
Script to perform a lower-bound (here derived from shallower peat depths) estimation of dO2 from peat thickness using polynomial and linear regressions, then to apply the model to raster data and to export TOC and dO2 maps with visualizations.
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