From d4e7925292da01c30b2f6171529e26db5693b785 Mon Sep 17 00:00:00 2001
From: "hermes.herrera" <hermes.herrera@orionhealth.com>
Date: Mon, 22 Jun 2026 16:17:34 +1200
Subject: [PATCH] Add kriging interpolation page (CONNECTIONTYPE kriging)

Document the kriging CONNECTIONTYPE: the localized NNGP method and its two
output bands (predictive mean and standard deviation), the PROCESSING reference,
and a self-contained, reproducible worked example. The example ships
downloadable files (the complete mapfile, two sampling networks, city points and
a simplified coastline) that render standalone with no external dependencies,
comparing IDW, the kriging mean and the kriging standard deviation for a dense
and a clustered sampling network.
---
 en/images/kriging-clustered.png               | Bin 0 -> 63989 bytes
 en/images/kriging-dense.png                   | Bin 0 -> 78071 bytes
 en/output/index.txt                           |   1 +
 en/output/kriging-example/cities_major.csv    |   7 +
 .../kriging-example/grid_nz_clustered.csv     |  64 +++
 en/output/kriging-example/grid_nz_regular.csv | 239 ++++++++++
 en/output/kriging-example/nz_coast.geojson    |  14 +
 en/output/kriging-example/nz_scenarios.map    | 408 ++++++++++++++++++
 en/output/kriging.txt                         | 242 +++++++++++
 9 files changed, 975 insertions(+)
 create mode 100644 en/images/kriging-clustered.png
 create mode 100644 en/images/kriging-dense.png
 create mode 100644 en/output/kriging-example/cities_major.csv
 create mode 100644 en/output/kriging-example/grid_nz_clustered.csv
 create mode 100644 en/output/kriging-example/grid_nz_regular.csv
 create mode 100644 en/output/kriging-example/nz_coast.geojson
 create mode 100644 en/output/kriging-example/nz_scenarios.map
 create mode 100644 en/output/kriging.txt

diff --git a/en/images/kriging-clustered.png b/en/images/kriging-clustered.png
new file mode 100644
index 0000000000000000000000000000000000000000..7b232fd48baf9bbe5afc42a4210753e06bb735b4
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diff --git a/en/output/index.txt b/en/output/index.txt
index 30860f0eb72..337b7295b89 100644
--- a/en/output/index.txt
+++ b/en/output/index.txt
@@ -16,6 +16,7 @@
    idw
    imagemaps
    kerneldensity
+   kriging
    ogr_output
    pdf
    svg
diff --git a/en/output/kriging-example/cities_major.csv b/en/output/kriging-example/cities_major.csv
new file mode 100644
index 00000000000..05167fdf513
--- /dev/null
+++ b/en/output/kriging-example/cities_major.csv
@@ -0,0 +1,7 @@
+wkt,city,annual_mm,elevation_m,weight,label
+POINT(174.76 -36.85),Auckland,1169,35,39,Auckland 1169 mm
+POINT(174.78 -41.29),Wellington,763,3,25,Wellington 763 mm
+POINT(173.28 -41.27),Nelson,1181,4,39,Nelson 1181 mm
+POINT(171.21 -42.45),Greymouth,2833,6,94,Greymouth 2833 mm
+POINT(172.64 -43.53),Christchurch,531,11,18,Christchurch 531 mm
+POINT(168.66 -45.03),Queenstown,1496,318,50,Queenstown 1496 mm
diff --git a/en/output/kriging-example/grid_nz_clustered.csv b/en/output/kriging-example/grid_nz_clustered.csv
new file mode 100644
index 00000000000..487a21d2faf
--- /dev/null
+++ b/en/output/kriging-example/grid_nz_clustered.csv
@@ -0,0 +1,64 @@
+wkt,annual_mm,elevation_m,weight
+POINT(169.737 -46.353),860,23,29
+POINT(169.792 -46.063),956,237,32
+POINT(170.137 -45.916),939,29,31
+POINT(169.536 -45.712),1435,390,48
+POINT(169.858 -45.614),982,948,33
+POINT(170.185 -45.644),713,289,24
+POINT(170.433 -45.609),781,545,26
+POINT(169.711 -45.302),776,840,26
+POINT(170.107 -45.302),750,1080,25
+POINT(170.465 -45.346),723,393,24
+POINT(170.763 -45.356),950,329,32
+POINT(170.432 -44.945),965,738,32
+POINT(171.978 -43.889),606,63,20
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+POINT(172.288 -43.567),704,97,23
+POINT(172.521 -43.606),558,18,19
+POINT(171.883 -43.172),1344,567,45
+POINT(172.295 -43.122),1312,876,44
+POINT(172.646 -43.123),786,123,26
+POINT(172.195 -42.932),1212,1051,40
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+POINT(172.983 -42.769),562,218,19
+POINT(173.251 -42.904),698,32,23
+POINT(172.557 -42.537),1033,499,34
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+POINT(174.97 -41.361),1002,398,33
+POINT(175.367 -41.392),840,300,28
+POINT(174.302 -41.132),1006,118,34
+POINT(174.992 -41.09),1308,321,44
+POINT(175.408 -41.079),1337,79,45
+POINT(175.766 -41.18),892,476,30
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+POINT(174.773 -38.603),1729,38,58
+POINT(175.041 -38.732),1495,261,50
+POINT(175.439 -38.696),1855,629,62
+POINT(175.797 -38.575),1231,474,41
+POINT(176.017 -38.661),1064,530,35
+POINT(175.092 -38.377),1315,177,44
+POINT(175.461 -38.3),1915,471,64
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+POINT(176.051 -38.212),1615,621,54
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+POINT(176.776 -38.257),1489,242,50
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+POINT(175.383 -37.866),1332,58,44
+POINT(175.818 -37.976),1349,107,45
+POINT(176.175 -37.983),1791,486,60
+POINT(176.525 -37.953),1687,227,56
+POINT(176.819 -38.013),1490,8,50
+POINT(175.13 -37.597),1215,133,40
+POINT(175.394 -37.545),1291,21,43
+POINT(175.726 -37.644),1301,30,43
+POINT(174.721 -37.205),1354,19,45
+POINT(174.963 -37.294),1234,4,41
+POINT(175.312 -37.208),1204,58,40
+POINT(175.836 -37.272),1489,65,50
+POINT(174.621 -36.813),1206,58,40
+POINT(175.065 -36.917),1289,30,43
+POINT(175.739 -36.876),1339,165,45
+POINT(174.274 -36.593),1104,48,37
+POINT(174.69 -36.637),1123,17,37
+POINT(174.42 -36.121),1323,134,44
+POINT(174.662 -36.282),1383,88,46
diff --git a/en/output/kriging-example/grid_nz_regular.csv b/en/output/kriging-example/grid_nz_regular.csv
new file mode 100644
index 00000000000..60d6abf3121
--- /dev/null
+++ b/en/output/kriging-example/grid_nz_regular.csv
@@ -0,0 +1,239 @@
+wkt,annual_mm,elevation_m,weight
+POINT(167.657 -47.058),2438,253,81
+POINT(168.127 -47.024),1249,151,42
+POINT(167.716 -46.766),2400,194,80
+POINT(169.083 -46.62),1300,224,43
+POINT(168.33 -46.269),1434,28,48
+POINT(168.676 -46.42),1296,49,43
+POINT(169.012 -46.278),1507,185,50
+POINT(169.434 -46.314),1063,507,35
+POINT(169.737 -46.353),860,23,29
+POINT(166.609 -46.043),5024,24,167
+POINT(167.057 -45.988),3846,661,128
+POINT(167.313 -46.037),2123,157,71
+POINT(167.734 -46.075),1745,40,58
+POINT(167.993 -45.997),1380,179,46
+POINT(168.407 -46.015),1542,206,51
+POINT(168.787 -45.975),1150,133,38
+POINT(169.05 -46.052),1087,152,36
+POINT(169.424 -45.951),1104,472,37
+POINT(169.792 -46.063),956,237,32
+POINT(170.137 -45.916),939,29,31
+POINT(166.616 -45.728),5242,319,175
+POINT(167.006 -45.721),4172,913,139
+POINT(167.336 -45.566),3693,801,123
+POINT(167.729 -45.634),1988,299,66
+POINT(168.071 -45.617),1539,454,51
+POINT(168.319 -45.654),1498,257,50
+POINT(168.775 -45.623),1436,501,48
+POINT(169.08 -45.726),1401,604,47
+POINT(169.536 -45.712),1435,390,48
+POINT(169.858 -45.614),982,948,33
+POINT(170.185 -45.644),713,289,24
+POINT(170.433 -45.609),781,545,26
+POINT(167.047 -45.382),5228,1116,174
+POINT(167.434 -45.318),3170,483,106
+POINT(167.746 -45.331),2087,203,70
+POINT(168.005 -45.239),2072,1348,69
+POINT(168.489 -45.348),1645,829,55
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+POINT(170.107 -45.302),750,1080,25
+POINT(170.465 -45.346),723,393,24
+POINT(170.763 -45.356),950,329,32
+POINT(167.623 -45.004),5585,1010,186
+POINT(168.094 -44.946),2703,1095,90
+POINT(168.322 -45.005),2144,1833,71
+POINT(168.8 -44.98),1307,449,44
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+POINT(169.41 -44.911),1049,383,35
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+POINT(170.162 -44.864),935,1201,31
+POINT(170.432 -44.945),965,738,32
+POINT(170.85 -44.915),713,93,24
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new file mode 100644
index 00000000000..8cf9bdd528a
--- /dev/null
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+{"type":"Feature","properties":{"scalerank":0,"featurecla":"Land","min_zoom":3.0},"geometry":{"type":"Polygon","coordinates":[[[173.914648437500034,-40.863671875],[173.780859375000034,-40.921777343749994],[173.812402343750023,-40.793652343750011],[173.873339843750045,-40.749316406250017],[173.964453125000034,-40.712988281250006],[173.9580078125,-40.786816406250011],[173.914648437500034,-40.863671875]]]}},
+{"type":"Feature","properties":{"scalerank":0,"featurecla":"Land","min_zoom":3.0},"geometry":{"type":"Polygon","coordinates":[[[166.746289062500011,-45.655859375],[166.729199218750011,-45.729687500000011],[166.532031250000045,-45.699804687500006],[166.567089843750011,-45.644433593749994],[166.685644531250034,-45.615039062500017],[166.746289062500011,-45.655859375]]]}},
+{"type":"Feature","properties":{"scalerank":0,"featurecla":"Land","min_zoom":2.0},"geometry":{"type":"Polygon","coordinates":[[[168.144921875000023,-46.862207031249994],[168.145312500000045,-46.902148437500017],[168.041015625,-46.887792968750006],[168.043164062500011,-46.9326171875],[168.12548828125,-46.956152343750006],[168.155957031250011,-46.98828125],[168.241406250000011,-46.97900390625],[168.260644531250023,-47.027050781250011],[168.240917968750011,-47.070019531250011],[168.183886718750045,-47.1015625],[168.015039062500023,-47.117480468750017],[167.905566406250045,-47.179882812500011],[167.784960937500045,-47.176074218750017],[167.676367187500034,-47.242968750000017],[167.52197265625,-47.258691406249994],[167.538769531250011,-47.199023437500017],[167.629003906250034,-47.142285156250011],[167.630957031250034,-47.087792968749994],[167.654101562500045,-47.044238281250017],[167.740917968750011,-47.013574218749994],[167.741992187500045,-46.956835937500017],[167.80078125,-46.906542968750017],[167.765234375000034,-46.797656250000017],[167.783984375000045,-46.699804687500006],[167.955761718750011,-46.694433593750006],[168.144921875000023,-46.862207031249994]]]}},
+{"type":"Feature","properties":{"scalerank":0,"featurecla":"Land","min_zoom":4.0},"geometry":{"type":"Polygon","coordinates":[[[166.9794921875,-45.1796875],[167.022656250000011,-45.2998046875],[166.93115234375,-45.27685546875],[166.892675781250034,-45.240527343750017],[166.9794921875,-45.1796875]]]}}
+]
+}
diff --git a/en/output/kriging-example/nz_scenarios.map b/en/output/kriging-example/nz_scenarios.map
new file mode 100644
index 00000000000..96a66dfcfd5
--- /dev/null
+++ b/en/output/kriging-example/nz_scenarios.map
@@ -0,0 +1,408 @@
+MAP
+  NAME       "nz_kriging_scenarios"
+  SIZE       340 440
+  EXTENT     990000 4730000 2120000 6190000
+  UNITS      meters
+  IMAGETYPE  "png"
+  IMAGECOLOR 222 234 244
+  CONFIG "MS_ERRORFILE" "stderr"
+  PROJECTION
+    "init=epsg:2193"
+  END
+
+  #=== scenario 1: dense, even network =================================#
+  LAYER
+    NAME "idw_regular"
+    TYPE raster
+    STATUS off
+    CONNECTIONTYPE idw
+    CONNECTION "grid_regular"
+    MASK "landmask"
+    PROCESSING "RANGE_COLORSPACE=RGB"
+    PROCESSING "IDW_RADIUS=250"
+    PROCESSING "IDW_POWER=2"
+    PROCESSING "IDW_COMPUTE_BORDERS=OFF"
+    OFFSITE 0 0 0
+    CLASS
+      STYLE                                    # < 250 mm
+        COLORRANGE "#8b0000" "#8b0000"
+        DATARANGE  0 8.33
+      END
+      STYLE                                    # 250 - 500
+        COLORRANGE "#e41a1c" "#e41a1c"
+        DATARANGE  8.33 16.67
+      END
+      STYLE                                    # 500 - 750
+        COLORRANGE "#ff7f00" "#ff7f00"
+        DATARANGE  16.67 25
+      END
+      STYLE                                    # 750 - 1000
+        COLORRANGE "#ffe93a" "#ffe93a"
+        DATARANGE  25 33.33
+      END
+      STYLE                                    # 1000 - 1250
+        COLORRANGE "#a6d96a" "#a6d96a"
+        DATARANGE  33.33 41.67
+      END
+      STYLE                                    # 1250 - 1500
+        COLORRANGE "#41ab5d" "#41ab5d"
+        DATARANGE  41.67 50
+      END
+      STYLE                                    # 1500 - 2000
+        COLORRANGE "#1d9182" "#1d9182"
+        DATARANGE  50 66.67
+      END
+      STYLE                                    # 2000 - 3000
+        COLORRANGE "#6baed6" "#6baed6"
+        DATARANGE  66.67 100
+      END
+      STYLE                                    # 3000 - 4000
+        COLORRANGE "#2166ac" "#2166ac"
+        DATARANGE  100 133.33
+      END
+      STYLE                                    # > 4000 mm
+        COLORRANGE "#6a3d9a" "#6a3d9a"
+        DATARANGE  133.33 260
+      END
+    END
+  END
+  LAYER
+    NAME "km_regular"
+    TYPE raster
+    STATUS off
+    CONNECTIONTYPE kriging
+    CONNECTION "grid_regular"
+    MASK "landmask"
+    PROCESSING "RANGE_COLORSPACE=RGB"
+    PROCESSING "KRIGING_MODEL=EXPONENTIAL"
+    PROCESSING "KRIGING_TYPE=ORDINARY"
+    PROCESSING "KRIGING_NEIGHBORS=16"
+    PROCESSING "KRIGING_RANGE=40"
+    PROCESSING "KRIGING_SILL=2000"
+    PROCESSING "KRIGING_NUGGET=0"
+    PROCESSING "BANDS=1"
+    OFFSITE 0 0 0
+    CLASS
+      STYLE                                    # < 250 mm
+        COLORRANGE "#8b0000" "#8b0000"
+        DATARANGE  0 8.33
+      END
+      STYLE                                    # 250 - 500
+        COLORRANGE "#e41a1c" "#e41a1c"
+        DATARANGE  8.33 16.67
+      END
+      STYLE                                    # 500 - 750
+        COLORRANGE "#ff7f00" "#ff7f00"
+        DATARANGE  16.67 25
+      END
+      STYLE                                    # 750 - 1000
+        COLORRANGE "#ffe93a" "#ffe93a"
+        DATARANGE  25 33.33
+      END
+      STYLE                                    # 1000 - 1250
+        COLORRANGE "#a6d96a" "#a6d96a"
+        DATARANGE  33.33 41.67
+      END
+      STYLE                                    # 1250 - 1500
+        COLORRANGE "#41ab5d" "#41ab5d"
+        DATARANGE  41.67 50
+      END
+      STYLE                                    # 1500 - 2000
+        COLORRANGE "#1d9182" "#1d9182"
+        DATARANGE  50 66.67
+      END
+      STYLE                                    # 2000 - 3000
+        COLORRANGE "#6baed6" "#6baed6"
+        DATARANGE  66.67 100
+      END
+      STYLE                                    # 3000 - 4000
+        COLORRANGE "#2166ac" "#2166ac"
+        DATARANGE  100 133.33
+      END
+      STYLE                                    # > 4000 mm
+        COLORRANGE "#6a3d9a" "#6a3d9a"
+        DATARANGE  133.33 260
+      END
+    END
+  END
+  LAYER
+    NAME "sd_regular"
+    TYPE raster
+    STATUS off
+    CONNECTIONTYPE kriging
+    CONNECTION "grid_regular"
+    MASK "landmask"
+    PROCESSING "RANGE_COLORSPACE=RGB"
+    PROCESSING "KRIGING_MODEL=EXPONENTIAL"
+    PROCESSING "KRIGING_TYPE=ORDINARY"
+    PROCESSING "KRIGING_NEIGHBORS=16"
+    PROCESSING "KRIGING_RANGE=40"
+    PROCESSING "KRIGING_SILL=2000"
+    PROCESSING "KRIGING_NUGGET=0"
+    PROCESSING "BANDS=2"
+    OFFSITE 0 0 0
+    CLASS
+      STYLE
+        COLORRANGE "#440154" "#3b528b"
+        DATARANGE 0 11.25
+      END
+      STYLE
+        COLORRANGE "#3b528b" "#21908c"
+        DATARANGE 11.25 22.5
+      END
+      STYLE
+        COLORRANGE "#21908c" "#5dc863"
+        DATARANGE 22.5 33.75
+      END
+      STYLE
+        COLORRANGE "#5dc863" "#fde725"
+        DATARANGE 33.75 45
+      END
+    END
+  END
+
+  #=== scenario 2: clustered network (gaps over the back-country) ======#
+  LAYER
+    NAME "idw_clustered"
+    TYPE raster
+    STATUS off
+    CONNECTIONTYPE idw
+    CONNECTION "grid_clustered"
+    MASK "landmask"
+    PROCESSING "RANGE_COLORSPACE=RGB"
+    PROCESSING "IDW_RADIUS=250"
+    PROCESSING "IDW_POWER=2"
+    PROCESSING "IDW_COMPUTE_BORDERS=OFF"
+    OFFSITE 0 0 0
+    CLASS
+      STYLE                                    # < 250 mm
+        COLORRANGE "#8b0000" "#8b0000"
+        DATARANGE  0 8.33
+      END
+      STYLE                                    # 250 - 500
+        COLORRANGE "#e41a1c" "#e41a1c"
+        DATARANGE  8.33 16.67
+      END
+      STYLE                                    # 500 - 750
+        COLORRANGE "#ff7f00" "#ff7f00"
+        DATARANGE  16.67 25
+      END
+      STYLE                                    # 750 - 1000
+        COLORRANGE "#ffe93a" "#ffe93a"
+        DATARANGE  25 33.33
+      END
+      STYLE                                    # 1000 - 1250
+        COLORRANGE "#a6d96a" "#a6d96a"
+        DATARANGE  33.33 41.67
+      END
+      STYLE                                    # 1250 - 1500
+        COLORRANGE "#41ab5d" "#41ab5d"
+        DATARANGE  41.67 50
+      END
+      STYLE                                    # 1500 - 2000
+        COLORRANGE "#1d9182" "#1d9182"
+        DATARANGE  50 66.67
+      END
+      STYLE                                    # 2000 - 3000
+        COLORRANGE "#6baed6" "#6baed6"
+        DATARANGE  66.67 100
+      END
+      STYLE                                    # 3000 - 4000
+        COLORRANGE "#2166ac" "#2166ac"
+        DATARANGE  100 133.33
+      END
+      STYLE                                    # > 4000 mm
+        COLORRANGE "#6a3d9a" "#6a3d9a"
+        DATARANGE  133.33 260
+      END
+    END
+  END
+  LAYER
+    NAME "km_clustered"
+    TYPE raster
+    STATUS off
+    CONNECTIONTYPE kriging
+    CONNECTION "grid_clustered"
+    MASK "landmask"
+    PROCESSING "RANGE_COLORSPACE=RGB"
+    PROCESSING "KRIGING_MODEL=EXPONENTIAL"
+    PROCESSING "KRIGING_TYPE=ORDINARY"
+    PROCESSING "KRIGING_NEIGHBORS=16"
+    PROCESSING "KRIGING_RANGE=40"
+    PROCESSING "KRIGING_SILL=2000"
+    PROCESSING "KRIGING_NUGGET=0"
+    PROCESSING "BANDS=1"
+    OFFSITE 0 0 0
+    CLASS
+      STYLE                                    # < 250 mm
+        COLORRANGE "#8b0000" "#8b0000"
+        DATARANGE  0 8.33
+      END
+      STYLE                                    # 250 - 500
+        COLORRANGE "#e41a1c" "#e41a1c"
+        DATARANGE  8.33 16.67
+      END
+      STYLE                                    # 500 - 750
+        COLORRANGE "#ff7f00" "#ff7f00"
+        DATARANGE  16.67 25
+      END
+      STYLE                                    # 750 - 1000
+        COLORRANGE "#ffe93a" "#ffe93a"
+        DATARANGE  25 33.33
+      END
+      STYLE                                    # 1000 - 1250
+        COLORRANGE "#a6d96a" "#a6d96a"
+        DATARANGE  33.33 41.67
+      END
+      STYLE                                    # 1250 - 1500
+        COLORRANGE "#41ab5d" "#41ab5d"
+        DATARANGE  41.67 50
+      END
+      STYLE                                    # 1500 - 2000
+        COLORRANGE "#1d9182" "#1d9182"
+        DATARANGE  50 66.67
+      END
+      STYLE                                    # 2000 - 3000
+        COLORRANGE "#6baed6" "#6baed6"
+        DATARANGE  66.67 100
+      END
+      STYLE                                    # 3000 - 4000
+        COLORRANGE "#2166ac" "#2166ac"
+        DATARANGE  100 133.33
+      END
+      STYLE                                    # > 4000 mm
+        COLORRANGE "#6a3d9a" "#6a3d9a"
+        DATARANGE  133.33 260
+      END
+    END
+  END
+  LAYER
+    NAME "sd_clustered"
+    TYPE raster
+    STATUS off
+    CONNECTIONTYPE kriging
+    CONNECTION "grid_clustered"
+    MASK "landmask"
+    PROCESSING "RANGE_COLORSPACE=RGB"
+    PROCESSING "KRIGING_MODEL=EXPONENTIAL"
+    PROCESSING "KRIGING_TYPE=ORDINARY"
+    PROCESSING "KRIGING_NEIGHBORS=16"
+    PROCESSING "KRIGING_RANGE=40"
+    PROCESSING "KRIGING_SILL=2000"
+    PROCESSING "KRIGING_NUGGET=0"
+    PROCESSING "BANDS=2"
+    OFFSITE 0 0 0
+    CLASS
+      STYLE
+        COLORRANGE "#440154" "#3b528b"
+        DATARANGE 0 11.25
+      END
+      STYLE
+        COLORRANGE "#3b528b" "#21908c"
+        DATARANGE 11.25 22.5
+      END
+      STYLE
+        COLORRANGE "#21908c" "#5dc863"
+        DATARANGE 22.5 33.75
+      END
+      STYLE
+        COLORRANGE "#5dc863" "#fde725"
+        DATARANGE 33.75 45
+      END
+    END
+  END
+
+  #=== sample sources, basemap, labelled cities ========================#
+  LAYER
+    NAME "grid_regular"
+    TYPE point
+    STATUS off
+    CONNECTIONTYPE OGR
+    CONNECTION "grid_nz_regular.csv"
+    DATA "grid_nz_regular"
+    PROJECTION
+      "init=epsg:4326"
+    END
+    CLASS
+      STYLE
+        SIZE [weight]
+      END
+    END
+  END
+  LAYER
+    NAME "grid_clustered"
+    TYPE point
+    STATUS off
+    CONNECTIONTYPE OGR
+    CONNECTION "grid_nz_clustered.csv"
+    DATA "grid_nz_clustered"
+    PROJECTION
+      "init=epsg:4326"
+    END
+    CLASS
+      STYLE
+        SIZE [weight]
+      END
+    END
+  END
+  LAYER
+    NAME "landmask"
+    TYPE polygon
+    STATUS off
+    CONNECTIONTYPE OGR
+    CONNECTION "nz_coast.geojson"
+    DATA "nz_coast"
+    PROJECTION
+      "init=epsg:4326"
+    END
+    CLASS
+      STYLE
+        COLOR 0 0 0
+      END
+    END
+  END
+  LAYER
+    NAME "coastline"
+    TYPE line
+    STATUS on
+    CONNECTIONTYPE OGR
+    CONNECTION "nz_coast.geojson"
+    DATA "nz_coast"
+    PROJECTION
+      "init=epsg:4326"
+    END
+    CLASS
+      STYLE
+        COLOR 90 110 130
+        WIDTH 0.6
+      END
+    END
+  END
+  LAYER
+    NAME "cities"
+    TYPE point
+    STATUS on
+    CONNECTIONTYPE OGR
+    CONNECTION "cities_major.csv"
+    DATA "cities_major"
+    PROJECTION
+      "init=epsg:4326"
+    END
+    CLASS
+      STYLE
+        SYMBOL "circle"
+        SIZE 5
+        COLOR 20 20 20
+        OUTLINECOLOR 255 255 255
+        WIDTH 1
+      END
+    END
+  END
+
+  SYMBOL
+    NAME  "circle"
+    TYPE  ellipse
+    FILLED true
+    POINTS 1 1 END
+  END
+END
diff --git a/en/output/kriging.txt b/en/output/kriging.txt
new file mode 100644
index 00000000000..64c32a7c7fc
--- /dev/null
+++ b/en/output/kriging.txt
@@ -0,0 +1,242 @@
+.. _kriging:
+
+*****************************************************************************
+ Kriging interpolation
+*****************************************************************************
+
+.. contents:: Table of Contents
+    :depth: 2
+    :backlinks: top
+
+Introduction
+============
+
+.. versionadded:: 8.8
+
+Kriging turns scattered vector features into a continuous raster surface, like
+:ref:`idw`, but it is a *geostatistical* interpolator: it fits a model of the
+data's spatial correlation and returns, together with the interpolated value,
+an estimate of how uncertain that value is.
+
+It is implemented as a localized **Nearest-Neighbor Gaussian Process (NNGP)**:
+each output pixel is predicted by ordinary (or simple) kriging using only its
+``m`` nearest input samples, so cost scales with the neighbour count rather
+than with a dense solve over the whole dataset.
+
+It produces **two raster bands**, selected with ``PROCESSING "BANDS=n"``:
+
+- band **1**: the predictive **mean**, the interpolated surface;
+- band **2**: the predictive **standard deviation** (the kriging standard
+  error), close to zero at the sample locations and rising across the gaps
+  between them.
+
+Configuration
+=============
+
+Set the `LAYER` `CONNECTIONTYPE` parameter to `KRIGING`.  As with :ref:`idw`,
+the samples come from another vector `LAYER` referenced by `CONNECTION`, and
+each sample's value is read from that layer's ``STYLE SIZE [attribute]``
+binding (see the corresponding section of :ref:`kerneldensity`).
+
+The interpolation takes the following parameters:
+
+- **CONNECTION "layername"** : reference to the `NAME` or `GROUP` of a `LAYER`
+  to use as an input vector datasource.  The referenced layer should be a
+  `TYPE` `POINT` layer.
+
+- **PROCESSING "KRIGING_MODEL=EXPONENTIAL"** : the covariance model, one of
+  ``EXPONENTIAL`` (Matern nu=1/2, the default), ``GAUSSIAN`` or ``SPHERICAL``.
+
+- **PROCESSING "KRIGING_TYPE=ORDINARY"** : ``ORDINARY`` (the default) assumes an
+  unknown, locally constant mean; ``SIMPLE`` assumes a known (zero or
+  pre-detrended) mean.
+
+- **PROCESSING "KRIGING_NEIGHBORS=16"** : the number of nearest samples ``m``
+  used to predict each pixel.  Larger values approach a full kriging solve at
+  higher cost (roughly ``O(m^3)`` per pixel).  The default is 16.
+
+- **PROCESSING "KRIGING_RANGE=numeric"** : the practical range of the
+  covariance model, in pixels: the lag beyond which samples are effectively
+  uncorrelated.  The default auto-fits to about a third of the image diagonal.
+
+- **PROCESSING "KRIGING_SILL=numeric"** : the partial sill, the variance the
+  covariance model reaches at large lags.  The default auto-fits from the
+  sample variance.
+
+- **PROCESSING "KRIGING_NUGGET=numeric"** : the nugget.  ``0`` (the default)
+  makes the surface interpolate the samples exactly; a positive value smooths
+  through them and stabilises the solve where samples are dense or coincident.
+
+- **PROCESSING "BANDS=1|2"** : which output band to render: ``1`` for the mean
+  (the default), ``2`` for the standard deviation.
+
+Worked example: two sampling networks
+======================================
+
+The example interpolates annual rainfall over New Zealand from the same field
+two ways, to show both what kriging adds over IDW and how the uncertainty band
+responds to the sampling layout.  Each scenario is rendered as three panels:
+IDW, the kriging mean (band 1) and the kriging standard deviation (band 2).
+
+Example files
+-------------
+
+Download the files into one directory and render the example as is; no
+preprocessing step and no external data are required.
+
+- :download:`nz_scenarios.map <kriging-example/nz_scenarios.map>`: the complete
+  mapfile (the IDW, kriging-mean and kriging-SD layers for both scenarios, plus
+  the point sources, land mask, coastline and city points).
+- :download:`grid_nz_regular.csv <kriging-example/grid_nz_regular.csv>`: the
+  dense, evenly spaced network (238 samples).
+- :download:`grid_nz_clustered.csv <kriging-example/grid_nz_clustered.csv>`:
+  samples kept only near six cities (63 samples), leaving the West Coast,
+  Fiordland and inland Southland unsampled.
+- :download:`cities_major.csv <kriging-example/cities_major.csv>`: six cities,
+  drawn as points for orientation.
+- :download:`nz_coast.geojson <kriging-example/nz_coast.geojson>`: a simplified
+  coastline, used for both the land mask and the outline.
+
+Each sample's value is the annual rainfall scaled to the 0-255 byte range
+(rainfall in mm divided by 30); the kriging layer reads it through
+``STYLE SIZE [weight]``.
+
+Mapfile
+-------
+
+The complete mapfile is the download above.  Its essential elements are the
+point layer that holds the samples and the two kriging layers that read it.
+``KRIGING_RANGE`` and ``KRIGING_SILL`` are pinned so the two scenarios share one
+covariance model and their SD bands stay comparable:
+
+.. code-block:: mapfile
+
+  # the sample layer; each point's value is taken from SIZE [weight]
+  LAYER
+    NAME "grid_regular"
+    TYPE point
+    CONNECTIONTYPE OGR
+    CONNECTION "grid_nz_regular.csv"
+    CLASS
+      STYLE
+        SIZE [weight]
+      END
+    END
+  END
+
+  # band 1: the interpolated mean, drawn with the rainfall isohyet palette
+  LAYER
+    NAME "km_regular"
+    TYPE raster
+    CONNECTIONTYPE kriging
+    CONNECTION "grid_regular"
+    MASK "landmask"
+    PROCESSING "KRIGING_MODEL=EXPONENTIAL"
+    PROCESSING "KRIGING_TYPE=ORDINARY"
+    PROCESSING "KRIGING_NEIGHBORS=16"
+    PROCESSING "KRIGING_RANGE=40"
+    PROCESSING "KRIGING_SILL=2000"
+    PROCESSING "BANDS=1"
+    # CLASS with the rainfall isohyet ramp (see the full mapfile)
+  END
+
+  # band 2: the standard deviation, drawn with a viridis ramp
+  LAYER
+    NAME "sd_regular"
+    TYPE raster
+    CONNECTIONTYPE kriging
+    CONNECTION "grid_regular"
+    MASK "landmask"
+    PROCESSING "KRIGING_RANGE=40"
+    PROCESSING "KRIGING_SILL=2000"
+    PROCESSING "BANDS=2"
+    CLASS
+      STYLE
+        COLORRANGE "#440154" "#fde725"
+        DATARANGE 0 45
+      END
+    END
+  END
+
+The clustered scenario uses the same layers reading ``grid_nz_clustered.csv``.
+
+Rendering
+---------
+
+Render the six panels (each is a surface plus the coastline and city points),
+then combine them into the two triptychs with ImageMagick:
+
+.. code-block:: bash
+
+  # six panels: IDW, kriging mean and kriging SD, for each scenario
+  for s in idw_regular km_regular sd_regular \
+           idw_clustered km_clustered sd_clustered; do
+    map2img -m nz_scenarios.map -l "$s coastline cities" -o "$s.png" -i png
+  done
+
+  # one triptych per scenario
+  montage -label 'IDW' idw_regular.png \
+          -label 'Kriging mean' km_regular.png \
+          -label 'Kriging std dev' sd_regular.png \
+          -tile 3x1 -geometry +8+8 idw_vs_kriging.png
+  montage -label 'IDW' idw_clustered.png \
+          -label 'Kriging mean' km_clustered.png \
+          -label 'Kriging std dev' sd_clustered.png \
+          -tile 3x1 -geometry +8+8 idw_vs_kriging_clustered.png
+
+Scenario 1: a dense, even network
+---------------------------------
+
+.. figure:: ../images/kriging-dense.png
+   :width: 100%
+
+   IDW, kriging mean and kriging standard deviation from 238 evenly spaced
+   samples.
+
+With samples everywhere, IDW and the kriging mean agree closely (kriging is a
+little smoother), and both resolve the dominant west-east pattern: the Southern
+Alps wring out the prevailing westerlies, so the West Coast is very wet (the
+purple spine) while Canterbury sits in the rain shadow.  The standard-deviation
+band is low and uniform across the country (every pixel is close to a
+measurement), so the surface is well supported everywhere.
+
+Scenario 2: a clustered network
+-------------------------------
+
+.. figure:: ../images/kriging-clustered.png
+   :width: 100%
+
+   The same three panels from 63 samples clustered near the cities (the dots).
+
+Now the network covers only the populated areas.  IDW and the kriging mean still
+look plausible, but both have lost the West Coast high: with no samples there,
+the South Island reads uniformly dry, and the mean alone gives no hint that
+anything is wrong.  The standard-deviation band does: it stays dark over the
+city clusters (the dots) and turns bright over the unsampled West Coast,
+Fiordland and Southland.  This is the practical value of kriging over IDW: it
+reports not only an estimate but also where that estimate is unsupported by
+data.
+
+Technical notes
+---------------
+
+- IDW's per-sample bullseyes stand out against the kriging mean's smoother
+  bands because both are drawn with the same isohyet palette.
+- ``KRIGING_RANGE`` is pinned smaller than the gaps in the clustered network,
+  which is why the clustered SD rises over those gaps.  Left unset it auto-fits
+  to about a third of the image diagonal.
+- ``KRIGING_SILL`` is pinned to the sample variance so the SD scale is the same
+  in both scenarios and the two SD panels stay comparable.
+- Output bands are 8-bit (0 to 255).  The mean is the value within the layer's
+  ``DATARANGE``; the standard deviation is in the same units, so the SD layer's
+  ``DATARANGE`` is the expected range of the standard error.
+
+References
+==========
+
+- Datta, A., Banerjee, S., Finley, A. O., Gelfand, A. E. (2016). Hierarchical
+  Nearest-Neighbor Gaussian Process Models for Large Geostatistical Datasets.
+  *Journal of the American Statistical Association* 111(514), 800 to 812.
+- Vecchia, A. V. (1988). Estimation and Model Identification for Continuous
+  Spatial Processes. *Journal of the Royal Statistical Society: Series B*
+  50(2), 297 to 312.