The creation of a digital soil map for Cyprus using decision-tree classification techniques Zomeni Z., Camera C., Noller J., Zissimos A., Bruggeman A. Cyprus Geological Survey 65 years of public service Scope of study •This study will develop a digital soil properties map of Cyprus, at 1:50,000 scale. •The soil physical properties which the map will provide are texture, depth, water holding capacity •Use Correlation and Regression Training for predictive mapping •Use existing topographical and soils data and integrate new geological, geochemical, geomorphological, geochronological, ecological and remote sensed data Random Forest Workflow 1. Initial Analysis of Existing Mapped Areas Random Forest Runs GIS Analyses 2. Extrapolation of Rule Sets to Unmapped Areas Random Forest Runs Ground Truthing 3. Reiterations of #2 until desired accuracy reached Soil Map of Cyprus methodology • Use known environmental variables, i.e. geology, geomorphology, topography, climatic parameters • Use existing 1:25.000 soil maps to “train” the software • The software will create decision trees based on rules, i.e. • Rule : • IF elevation <= 1742, and • precipitation <=2465, and • slope is < 6, and • geology = 15, THEN • Soil= 1 (ie Letymbou soil series) • The software will predict soil units in unmapped areas • The output will be field checked Soil forming factors, from Jenny (1941) to McBratney (2003) clorpt ... scorpan •Soil properties •Climate (precipitation, soil moisture, temperature) •Organisms (vegetation, fauna, humans) •Relief (topography, slope, aspect, landscape) •Parent material (e.g, surficial geology, bedrock lithology) •Age (time factor) •N space, spatial position 5 scorpan, soil properties Soil map of Cyprus, 1961, 1:125.000 Legend 1.1 Kafkalla - Fairly level 2.3 Terra Rossa on kafkalla - Deep 6.2 Calcareous raw soils - Shallow 1.2 Kafkalla - Moderately sloping 3.1 Terra Rossa on hard limestone - Shallow w. outcrops 6.3 Calcareous raw soils - Deep 10.1.1 Silicate raw soils on igneous rocks - Shallow 3.2 Terra Rossa on hard limestone - Shallow 7.1.1 Xerorendzinas on Kythrea beds - Sandstone 10.1.2 Silicate raw soils on igneous rocks - Deep 3.3 Terra Rossa on hard limestone - Deep 7.1.2 Xerorendzinas on Kythrea beds - Shallow 10.1.3 Silicate raw soils on igneous rocks - Under pines 4.1 Red earths - Shallow 7.1.3 Xerorendzinas on Kythrea beds - Deep 10.2.1 Silicate raw soils on Mamonia rocks - Shallow 4.2 Red earths - Deep 7.2.1 Xerorendzinas on limestones, etc - Shallow 10.2.2 Silicate raw soils on Mamonia rocks - Deep 4.3 Red earths - Immature 7.2.2 Xerorendzinas on limestones, etc - Deep 11 Blown sand 4.4 Red earths - Degraded 7.3 Xerorendzinas on pliocene marls 12 Urban 5.1 Brown earths - Shallow 8 Shallow rendzinas with hard limestone outcrops 2.1 Terra Rossa on kafkalla - Shallow 5.2 Brown earths - Deep 9.1 Alluvial soils - Saline and marshy 2.2 Terra Rossa on kafkalla - Immature 6.1 Calcareous raw soils - Rocky 9.2 Alluvial soils - Non saline scorpan, Soil properties Legend Bc, Calcaric Cambisols Ie, Eutric Lithosols Vr, Rhodic Vertisols Bc, Calcaric Cambisols Lithic phase Rc, Calcaric Regosols Vr, Rhodic Vertisols Lithic phase Be, Eutric Cambisols Rc, Calcaric Regosols Lithic phase Vx, Xeric Vertisols Soil map of Cyprus, Be, Eutric Cambisols Lithic phase Rc, Calcaric Regosols Shifting sands Vx, Xeric Vertisols Lithic phase Bv, Vertic Cambisols Re, Eutric Regosols Xc, Calcaric Xerosols 1970, 1:200.000 Bv, Vertic Cambisols Lithic phase Re, Eutric Regosols Lithic phase Xg, Gypsic Xerosols Em, Mollic Rendzinas Lithic phase So, Orthic Solonetz Xg, Gypsic Xerosols Lithic phase Eo, Ochric Rendzinas Urban, Urban Xv, Vertic Xerosols Eo, Ochric Rendzinas Lithic phase Vc, Chromic Vertisols Zg, Gleyic Solonchaks Ic, Calcaric Lithosols Vp, Pellic Vertisols Ic, Calcaric Lithosols Petrocalcic phase Vp, Pellic Vertisols Lithic phase scorpan, Soil properties Soil map of Cyprus, 1999, 1:250.000 Legend Salt Lake Deposits vertic-CAMBISOLS and calcaric-REGOSOLS eutric-lithic-LEPTOSOLS and eutric-skeletic-REGOSOLS calcaric-fluvic-CAMBISOLS and vertic-CAMBISOLS eutric-GAMBISOLS and eutric-anthropic-REGOSOLS calcaric-CAMBISOLS and calcaric-REGOSOLS lithic-LEPTOSOLS and epipetric-CALCISOLS eutric-chromic-VERTISOLS calcaric-lithic-LEPTOSOLS and calcaric-leptic-REGOSOLS calcaric-lithic LEPTOSOLS epipetric-CALCISOLS and leptic-chromic-LUVISOLS gleyic-SOLONCHALKS calcic-LUVISOLS and chromic-vertic-LUVISOLS skeletic-leptic-REGOSOLS skeletic-calcaric-REGOSOLS and calcaric-lithic-LEPTOSOLS vertic-leptic-CAMBISOLS and chromic-VERTISOLS calcaric-rendzic-LEPTOSOLS and calcaric-leptic-CAMBISOLS gypsiric-REGOSOLS and leptic-GYPSISOLS calcaric-leptic-REGOSOLS and lithic-LEPTOSOLS scorpan, climate Wetness Index water loss (red) and water accumulation (blue) • rainfall, 50 cm/year, xeric • January temperatures, 0oC to 25oC •July temperatures, 25oC to 40oC scsocorpan,rpan, organisms organisms Legend CorganicCStop_per100 Value High : 11 % Low : 0 Geochemical Atlas of Cyprus Cyprus Geological Survey 2011 •5500 sites •2 samples per site scorpan, organisms, long presence of man •Agriculture and salinization •landscaping •overgrazing •unsupervised industrialisation •abandoned agricultural land •deforestation Berm 30,000 polygons scorpan, relief Closed depression Cuesta Drainages Landscape Fan position Flat Fluvial Hillslope Horst Mesa Plains Ridges Terrace Nea Dimmata Nea Dimmata Nea Dimmata Elevation ! Aspect! Slope ! Kato Gialia Kato Gialia Kato Gialia Agia! Marina Chrysochous Agia! Marina Chrysochous Agia! Marina Chrysochous ! ! ! Gialia Gialia Gialia ! ! ! Argaka Argaka Argaka ! ! ! Makounta Makounta Makounta ! ! ! Lakki Lakki Lakki ! Polis Kynousa ! Polis Kynousa ! Polis Kynousa Prodromi! Pelathousa! Prodromi! Pelathousa! Prodromi! Pelathousa! ! ! ! ! ! ! 12 ! ! ! ! ! ! scorpan, parent material Holocene Alluvium Pleistocene Terraces Calcareous sediments Ophiolite Limestone scorpan, parent material and age " Morfou Fyllia Masari " " Argaki Nikitas " Katokopia Prastio "Morfou " " Kato Zodeia Deneia Mammari " " Pano Zodeia Avlona " " " Kokkinotrimithia " Astromeritis " Akaki Peristerona Lefkosias " Surficial Deposits, 5.800 polygons " Palaiometocho " Angolemi " Agioi Trimithias " Morfou " Meniko Fyllia Potami " Masari " Kato Koutrafas " " " Argaki Pano Koutrafas Orounta Nikitas " " " Katokopia Prastio "Morfou " " Kato Zodeia Deneia Mammari " " Pano Zodeia Avlona " " " Mandres Vyzakia " Nikitari " " Kokkinotrimithia Agios Ioannis Lefkosias " Kato Moni " " Astromeritis Agioi Iliofotoi " " Akaki Agia Marina Xyliatou Arediou Peristerona Lefkosias " " Agrokipia " " Palaiometocho Agios Theodoros Soleas Mitsero " " Agios Georgios Kafkallou " Angolemi " " Malounta Agioi Trimithias " Xyliatos Meniko " " Potami " Kato Koutrafas Klirou " " " Pano Koutrafas Orounta " " Mandres Vyzakia " Nikitari " " OneGeology, 13.600 polygons Agios Ioannis Lefkosias Kato Moni " " Agioi Iliofotoi " Agia Marina Xyliatou Arediou " Agrokipia " Agios Theodoros Soleas Mitsero " Agios Georgios Kafkallou " " Malounta Xyliatos " " Klirou " Extrapolation beyond the training areas Training data Pakhna PA PA1 PA2 PA3 PA2-3 PAr1 PAr2 PAr3 PA1t PA2t C3(PAr) C3(PA) Pendayia P P1 P2 P3 Pc Pl Peristerona PE1 Polemi PE2 PE3 I II PE4 III IV PEi1 V VI VII VIII IX PEi2 X XI XII XIII XIV XV XVI PEi3 XVII XVIII XIX XX XXI XXII XXIII XXIV PEi4 XXV XXVI XXVII XXVIII XXIX XXX XXXI XXXII XXXIII C2(PEi) XXXIV XXXV XXXVI XXXVII XXXVIII XXXIX XL XLI XLII XLIII C3(PEi) XLIV XLV XLVI XLVII XLVIII XLIX L LI LII LIII LIV LV LVI LVII LVIII LIX The method involves compiling a dataset of values for all these variables at random points and then ground truthing Elevation Precipitation Slope Easting Northing Geology Soil (m) (mm) (%) x1 y1 637 246 4 15 1 x2 y2 621 246 10 15 2 x3 y3 716 257 4 15 1 x4 y4 704 247 27 15 4 x5 y5 715 248 5 15 1 x6 y6 728 246 3 15 1 geology 15 = Troodos pillow lavas Regosol on umber deposit in Asgata Ap Btk CRtk umber Soil formation behind terrace wall in Asgata on basalt Terrace wall Soil toposequence in Vasa on diabase Coastal soils in Tochni Orchard and destroyed check dam in Agios Theodoros Small test area west of Lefkosia Error associated with increasing number of decision trees different type of soils (dashed lines) mean error (black line) Predicted and observed soil series in a mapped area for testing method observed LP.li.ca LP.li.eu CL.ptp- CM.eu- LV.cc- RG.ca.s CM.fv.c CM.vr- - - LV.cr.c RG.ah.e LV.vr.c k- a-CM.vr RG.ca RG.le.c RG.le.e a u r LP.li.ca a u CL.ptp- 0.950 0.000 0.004 0.021 0.021 0.000 0.004 0.000 LV.cr.ca CM.eu- 0.000 0.942 0.000 0.000 0.000 0.053 0.000 0.005 RG.ah.eu CM.fv.ca- 0.009 0.000 0.882 0.091 0.018 0.000 0.000 0.000 CM.vr CM.vr- 0.017 0.000 0.009 0.916 0.049 0.000 0.007 0.002 RG.ca LP.li.ca- 0.014 0.000 0.002 0.029 0.946 0.001 0.000 0.006 predicted RG.le.ca LP.li.eu- 0.000 0.026 0.000 0.001 0.004 0.958 0.000 0.011 RG.le.eu LV.cc- 0.032 0.000 0.000 0.043 0.004 0.000 0.921 0.000 LV.vr.cr RG.ca.sk- 0.000 0.002 0.000 0.005 0.016 0.011 0.000 0.966 LP.li.ca conclusions • decision‐tree classification techniques can be used successfully to predict soil properties in unmapped areas • Detailed physiographic and geological data is needed for maximizing accuracy • Final project results will be presented in September of 2014.