Determination of the relationship among compound Topographic Index (CTI), soil properties and land-use in karst ecosystems

References

• Anonymous, (2020). Dataset: © JAXA/METI ALOS PALSAR L1.0 2007. Accessed through ASF DAAC, Date: 02 May 2020.
   Google Scholar
• Armesto, J. J., & Gutierrez, J. R. (1978). El efecto del fuego en Iaestructura de Iavegetacion de Chilecentral. AnalesMuseoHistoria Natural Valparaiso, 11(1), 43-48. http://bibliotecadigital.ciren.cl/bitstream/handle/123456789/20429/00009166.nul?sequence=1
   Google Scholar
• Babur, E. (2019). Effects of parent material on soil microbial biomass carbon and basal respiration with in young afforested areas. Scandinavian Journal of Forest Research 43, (2), 94–101. https://doi.org/10.1080/02827581.2018.1561936
   Web of Science ®Google Scholar
• Baggaley, N., Mayr, T., & Bellamy, P. (2009). Identification of key soil and terrain properties that influence the spatial variability of soil moisture throughout the growing season. Soil Use and Management, 25(3), 262–273. https://doi.org/10.1111/j.1475-2743.2009.00222.x
   Web of Science ®Google Scholar
• Bangroo, S. A., Najar, G. R., Achin, E., & Truong, P. N. (2020). Application of predictor variables in spatial quantification of soil organic carbon and total nitrogen using regression kriging in the North Kashmir forest Himalayas. Catena, 193(104632), 1-9. https://doi.org/10.1016/j.catena.2020.104632
   Web of Science ®Google Scholar
• Battaglia, M. L. (2018). Crop residue management effects on crop production, greenhouse gases emissions, and soil quality in the Mid-Atlantic USA. Virginia Tech. Blacksburg, VA. https://vtechworks.lib.vt.edu/handle/10919/86483 ( accessed: Oct/ 19/2020).
   Google Scholar
• Baver, L. D. (1956). Soil Physics. John Wiley and Sons Inc.
   Google Scholar
• Beaudette, D. E., Dahlgren, R. A., & O’Green, A. T. (2013). Terrain-shape indices for modeling soil moisture dynamics. Soil Science Society of America Journal, 77(5), 1696–1710. https://doi.org/10.2136/sssaj2013.02.0048
   Web of Science ®Google Scholar
• Beven, K. J., & Kirkby, M. J. (1979). A physically based, variable contributing area model of basin hydrology. Hydrological Sciences Bulletin, 24(1), 43–69. https://doi.org/10.1080/02626667909491834
   Google Scholar
• Blumenthal, M. (1947). Geology of Taurus Mountains at the hinterland of Seydişehir-Beyşehir. MTA Publications, D, 2.
   Google Scholar
• Bremmer, J. M., & Mulvaney, C. S. (1982). Nitrogen Total. In Methods of Soil Analysis. Part II, Chemical and Microbiological Methods (2nd ed., pp. 595–624). Agronomy Monograph No. 9, American Society of Agronomy and Soil Science Society of America.
   Google Scholar
• Brocca, L., Morbidelli, R., & Melone, F. (2007). Soil moisture spatial variability in experimental areas of central Italy. Journal of Hydrology, 333(2–4), 356–373. https://doi.org/10.1016/j.jhydrol.2006.09.004
   Web of Science ®Google Scholar
• Brocca, L., Tullo, T., & Melone, F. (2012). Catchment scale soil moisture spatial–temporal variability. Journal of Hydrology, 422(423), 63–75. https://doi.org/10.1016/j.jhydrol.2011.12.039
   Web of Science ®Google Scholar
• Brubaker, S. C., Jones, A. J., Lewis, D. T., & Frank, K. (1993). Soil properties associated with landscape position. Soil Science Society of America Journal, 57(1), 235–239. https://doi.org/10.2136/sssaj1993.03615995005700010041x
   Web of Science ®Google Scholar
• Buchanan, B. P., Fleming, M., Schneider, R. L., Richards, B. K., Archibald, J., Qiu, Z., & Walter, M. T. (2014). Evaluating topographic wetness indices across central New York agricultural landscapes. Hydrology and Earth System Sciences, 18(8), 3279–3299. https://doi.org/10.5194/hess-18-3279-2014
   Web of Science ®Google Scholar
• Burt, T., & Butcher, D. (1985). Topographic controls of soil moisture distributions. Journal of Soil Science, 36(3), 469–486. https://doi.org/10.1111/j.1365-2389.1985.tb00351.x
   Google Scholar
• Cepel, N. (1988). Soil Science Text Book. I.U. Publication No: 3416 (pp. No: 389). Faculty of Forestry Publication.
   Google Scholar
• Cepel, N. (1995). Forest Ecology Text Book. I.U (pp. 423). Publications. Faculty of ForestryPublication.
   Google Scholar
• Chen, Z. S., Hsieh, C. F., Jiang, F. Y., Hsieh, T. H., & Sun, I. F. (1997). Relations of soil properties to topography and vegetation in a subtropical rain forest in southern Taiwan. Plant Ecology, 132(2), 229–241. https://doi.org/10.1023/A:1009762704553
   Web of Science ®Google Scholar
• Collick, A. S., Veith, T. L., Fuka, D. R., Kleinman, P. J. A., Buda, A. R., Weld, J., Bryant, Vadas, P. A., White, M. J., Harmel, R. D., Easton, Z. M., & Bryant, R. B. (2016). Improved simulation of edaphic and manure phosphorus loss in SWAT. Journal of Environmental Quality, 45(4), 1215–1225. https://doi.org/10.2134/jeq2015.03.0135
   PubMed Web of Science ®Google Scholar
• CORINE. (1992). Soil Erosion Risk and Important Land Resources in the Southeastern Regions of the European Community. EUR 13233, Luxembourg, BELGIUM. pp.32–48.
   Google Scholar
• Da Silva, A. P., Nadler, A., & Kay, B. D. (2001). Factors contributing to temporal stability in spatial patterns of water content in the tillage zone. Soil and Tillage Research, 58(3–4), 207–218. https://doi.org/10.1016/S0167-1987(00)00169-0
   Web of Science ®Google Scholar
• Dar, S. A., Singh, S. K., Wan, H. Y., Kumar, V., Cushman, S. A., & Sathyakumar, S. (2021). Projected climate change threatens Himalayan brown bear habitat more than human land use. Animal Conservation. 24(3), 1-17.https://doi.org/10.1111/acv.12671
   Web of Science ®Google Scholar
• Devkota, S., Shakya, N. M., Sudmeier, K., McAdoo, B. G., & Jaboyedoff, M. (2018). Predicting soil depth to bedrock in an anthropogenic landscape: a case study of phewa watershed in panchase region of central-western hills, nepal. Journal of Nepal Geological Society, 55(1), 173–182. https://doi.org/10.3126/jngs.v55i1.22809
   Google Scholar
• Dindaroglu, T. (2021). Determination of ecological networks for vegetation connectivity using GIS & AHP technique in the Mediterranean degraded karst ecosystems. Journal of Arid Environments, 188(104385), 1-11. https://doi.org/10.1016/j.jaridenv.2020.104385
   Web of Science ®Google Scholar
• Dindaroglu, T., Babur, E., Yakupoglu, T., Rodrigo-Comino, J., & Cerdà, A. (2021). Evaluation of geomorphometric characteristics and soil properties after a wildfire using Sentinel-2 MSI imagery for future fire-safe forest. Fire Safety Journal, 122(103318), 1-19. https://doi.org/10.1016/j.firesaf.2021.103318
   Web of Science ®Google Scholar
• Dindaroglu, T., & Canbolat, M. Y. (2017). Investigation of change in soil properties due to physiographic characteristics and land use. Turkish Journal of Forest Science, 1(1), 10–24. https://doi.org/10.32328/turkjforsci.294930
   Google Scholar
• Dindaroğlu, T., & Vermez, Y. (2019). Classification and mapping of some site features of karst ecosystems (Sarımsak Mountain Andırın-Kahramanmaraş). Turkish Journal of Forest Science, 3(1), 60–83. https://doi.org/10.32328/turkjforsci.468388
   Google Scholar
• Droesen, J. M. (2016). Downscaling soil moisture using topography. In The evaluation and optimisation of a downscaling approach. MS Thesis GIRS-2016-17. Wageningen University and Research Centre Laboratory of Geo-Information Science and Remote Sensing Wageningen. Editor: Arend Ligtenberg. 4-6.
   Google Scholar
• Easton, Z. M., Fuka, D. R., Walter, M. T., Cowan, D. M., Schneiderman, E. M., & Steenhuis, T. S. (2008). Re-conceptualizing the soil and water assessment tool (SWAT) model to predict runoff from variable source areas. Journal of Hydrology, 348(3–4), 279–291. https://doi.org/10.1016/j.jhydrol.2007.10.008
   Web of Science ®Google Scholar
• EC. (2009). European Commission, Eurostat, 2009. LUCAS 2009 Technical reference document C1. Instruction for surveyors. http://ec.europa.eu/eurostat/documents/205002/6786255/LUCAS2015-C1-Instructions-20150227.pdf [accessed on 07 February 2018]
   Google Scholar
• Entin, J. K., Robock, A., & Vinnikov, K. Y. (2000). Temporal and spatial scales of observed soil moisture variations in the extratropics. Journal of Geophysical Research: Atmospheres, 105(D9), 11865–11877. https://doi.org/10.1029/2000JD900051
   Web of Science ®Google Scholar
• ERDAS, 2009. Leica Geosystems, LLC, Atlanta, U.S.A
   Google Scholar
• Fisher, R. F., & Binkley, D. (2000). Ecology and management of forest soils (pp. 512). John Wiley and Sons.
   Google Scholar
• Florinsky, I. V., Eilers, R. G., & Manning, G. R. (2002). Prediction of soil properties by digital terrain modeling. Environmental Modelling and Software, 17(3), 295–311. https://doi.org/10.1016/S1364-8152(01)00067-6
   Web of Science ®Google Scholar
• Gee, G. W., & Hortage, K. H. (1986). Particle- Size Analysis. In Methods of Soil Analysis. Part 1. Physical and Mineralogical Methods (Second ed., pp. 383–441). Agronomy. No: 9. 2. Edition.
   Google Scholar
• Grafius, D. R., Malanson, G. P., & Weiss, D. (2012). Secondary controls of alpine treeline elevations in the western USA. Physical Geography, 33(2), 146–164. https://doi.org/10.2747/0272-3646.33.2.146
   Web of Science ®Google Scholar
• Gulcur, F. (1974). Soil Physical and Chemical Analysis Methods.İ.Ü. Faculty of Forestry (pp. 201). Yay.
   Google Scholar
• Higginbottom, T. P., Field, C. D., Rosenburgh, A. E., Wright, A., Symeonakis, E., & Caporn, S. J. (2018). High-resolution wetness index mapping: A useful tool for regional scale wetland management. Ecological Informatics, 48(2018), 89–96. https://doi.org/10.1016/j.ecoinf.2018.08.003
   Web of Science ®Google Scholar
• Hu, C., Wright, A. L., & Lian, G. (2019a). Estimating the spatial distribution of soil properties using environmental variables at a catchment scale in the loess hilly area, China. International Journal of Environmental Research and Public Health, 16(3), 491. https://doi.org/10.3390/ijerph16030491
   PubMed Web of Science ®Google Scholar
• Hu, C., Wright, A. L., & Lian, G. (2019b). Estimating the spatial distribution of soil properties using environmental variables at a catchment scale in the loess hilly area, China. International Journal of Environmental Research and Public Health, 16(3), 491. https://doi.org/10.3390/ijerph16030491
   PubMed Web of Science ®Google Scholar
• IPCC. (2000). Land Use, Land Use Change and Forestry. In IPCC, Special Report. Cambridge University Press. 1-388
   Google Scholar
• Irmak, A. (1966).Forest Ecology. Publisher:I.U. Faculty of Forestry Publication No (pp. 1187/104).
   Google Scholar
• Jensen, J. R. (2005). Digital image processing: A remote sensing perspective. In Upper Saddle River, NJ: SPrentice Hall. Part of the Pearson Series Geographic Information Science, 505-512.
   Google Scholar
• Johnson, C. E., Méndez, J. J. R., & Lawrence, G. B. (2000). Forest soil chemistry and terrain attributes in a catskills watershed. Soil Science Society of America Journal, 64(5), 1808–1814. https://doi.org/10.2136/sssaj2000.6451804x
   Web of Science ®Google Scholar
• Johnston, K., Ver Hoef, J. M., Krivoruchko, K., & Lucas, N. (2001). Using ArcGIS geostatistical analyst (Vol. 380). Esri.
   Google Scholar
• Jones, S. L., Slattery, M. C., & Ritter, E. C. (2020). Near-surface soil moisture dynamics in a prairie hillslope seep/headwater stream system in Texas, USA. Physical Geography, Latest online article,1–21. https://doi.org/10.1080/02723646.2020.1838120
   Web of Science ®Google Scholar
• Klute, A., & Dirksen, C. (1986). Hydrolic conductivity and diffusivity: Laboratory methods. Metod of soil analysis.Part 1. Physical and minerological methods 2. Agronomy. No: 9. 2, Edition 687–734.
   Google Scholar
• Kozhuhovsky, A., Komatsu, G., & Yamskikh, G. (2015). The evolution of gullies in steppe and forest-steppe landscapes of the Minusinskaya intermountain depression, Siberia: A case study in the central part of the Krasnoyarsk water reservoir. Physical Geography, 36(4), 305–321. https://doi.org/10.1080/02723646.2015.1041199
   Web of Science ®Google Scholar
• Kozlu, H. (1987). Stratigraphy and Structural Evolution of Misis-Andirin (Vol. 7, pp. 104–116). Ankara.
   Google Scholar
• Kumar, P., Lai, L., Battaglia, M. L., Kumar, S., Owens, V., Fike, J., Galbraith, J., Hong, C. O., Faris, R., Crawford, R., Crawford, J., Hansen, J., Mayton, H., & Viands, D. (2019). Impacts of nitrogen fertilization rate and landscape position on select soil properties in switch grass field at four sites in the USA. CATENA, 180(1), 183–193. https://doi.org/10.1016/j.catena.2019.04.028
   Web of Science ®Google Scholar
• Kumar, S., Lai, L., Kumar, P., Feliciano, Y. M. V., Battaglia, M. L., Hong, C. O., Owens, V. N., Fike, J., Farris, R., & Galbraith, J. (2019). Impacts of nitrogen rate and landscape position on soils and switchgrass root growth parameters. Agronomy Journal, 111(3), 1046–1059. https://doi.org/10.2134/agronj2018.08.0483
   Web of Science ®Google Scholar
• Lafon, C. W., Hanson, A. A., & Dwight, R. A. (2019). Geographic variations in fine-scale vegetation patterns: Aspect preferences of montane pine stands over Southern Appalachian landscapes. Physical Geography, 40(5), 433–460. https://doi.org/10.1080/02723646.2019.1576013
   Web of Science ®Google Scholar
• Leonelli, G., Masseroli, A., & Pelfini, M. (2016). The influence of topographic variables on treeline trees under different environmental conditions. Physical Geography, 37(1), 56–72. https://doi.org/10.1080/02723646.2016.1153377
   Web of Science ®Google Scholar
• Li, X., McCarty, G. W., Lang, M., Ducey, T., Hunt, P., & Miller, J. (2018). Topographic and physicochemical controls on soil denitrification in prior converted croplands located on the Delmarva Peninsula, USA. Geoderma, 309(2018), 41–49. https://doi.org/10.1016/j.geoderma.2017.09.003
   Web of Science ®Google Scholar
• Liao, C., Li, H., Lv, G., Tian, J., Liu, B., Tian, M., & Xu, Y. (2021). Can ecological restoration improve soil properties and plant growth in valley-slope sand dunes on southern Tibetan Plateau? Physical Geography, 42(2), 143–159. https://doi.org/10.1080/02723646.2020.1735859
   Web of Science ®Google Scholar
• Lillesand, T. M., & Kiefer, R. W. (2000). Remote Sensing and Image Interpretation (Fourth ed.). The Lehigh Press.
   Google Scholar
• Liu, C. Q. (2009). Biogeochemical Processes and Cycling of Nutrients in the Earth’s Surface: Cycling of Nutrients in Soil–plant Systems of Karstic Environments, South-west China. Science Press.
   Google Scholar
• Liu, S., An, N., Yang, J., Dong, S., Wang, C., & Yin, Y. (2015). Prediction of soil organic matter variability associated with different land use types in mountainous landscape in southwestern Yunnan province, China. Catena, 133 (2015), 137–144. https://doi.org/10.1016/j.catena.2015.05.010
   Web of Science ®Google Scholar
• Loeppert, R. H., & Suarez, D. L. (1996). Carbonate and gypsum. In D. L. Sparks (Ed.), Methods of soil analysis. Part 3 (3rd ed., pp. 437–474). SSSA, ASA.
   Google Scholar
• Loew, A., & Schlenz, F. (2011). A dynamic approach for evaluating coarse scale satellite soil moisture products. Hydrology and Earth System Sciences, 15(1), 75–90. https://doi.org/10.5194/hess-15-75-2011
   Web of Science ®Google Scholar
• Mallick, J., Ahmed, M., Alqadhi, S. D., Falqi, I. I., Parayangat, M., Singh, C. K., & Ijyas, T. (2020). Spatial stochastic model for predicting soil organic matter using remote sensing data. Geocarto International, 1–32. https://doi.org/10.1080/10106049.2020.1720314
   Web of Science ®Google Scholar
• McKenzie, N. J., & Ryan, P. J. (1999). Spatial prediction of soil properties using environmental correlation. Geoderma, 89(1–2), 67–94. https://doi.org/10.1016/S0016-7061(98)00137-2
   Web of Science ®Google Scholar
• Meles, M. B., Younger, S. E., Jackson, C. R., Du, E., & Drover, D. (2020). Wetness index based on landscape position and topography (WILT): Modifying TWI to reflect landscape position. Journal of environmental management, 255(109863), 1–9. https://doi.org/10.1016/j.jenvman.2019.109863
   Web of Science ®Google Scholar
• Meles, M. B., Younger, S. E., Jackson, C. R., Du, E., & Drover, D. (2020). Wetness index based on landscape position and topography (WILT): Modifying TWI to reflect landscape position. Journal of environmental management, 255, 109863.
   PubMed Web of Science ®Google Scholar
• MGM. (1995). General Directorate of Meteorology Weather archive of Kahramanaraş Province. https://www.mgm.gov.tr/veridegerlendirme/il-ve-ilceler-istatistik.aspx?k=A&m=KAHRAMANMARAS AccessedDate: 01.Jun.2020
   Google Scholar
• Mirchooli, F., Kiani-Harchegani, M., Darvishan, A. K., Falahatkar, S., & Sadeghi, S. H. (2020). Spatial distribution dependency of soil organic carbon content to important environmental variables. Ecological Indicators, 116(106473), 1-12. https://doi.org/10.1016/j.ecolind.2020.106473
   Web of Science ®Google Scholar
• Mitasova, H., & Hofierka, J. (1993). Interpolation by regularized spline with tension. II: Application to terrain modeling and surface geometry analysis. Mathematical Geology, 25(6), 657–669. https://doi.org/10.1007/BF00893172
   Google Scholar
• Mitasova, H., & Mitas, L. (1993). Interpolation by regularized spline with tension: i. theory and implementation. Mathematical Geology, 25(6), 641–655. https://doi.org/10.1007/BF00893171
   Google Scholar
• Moeslund, J. E., Arge, L., Bøcher, P. K., Dalgaard, T., Odgaard, M. V., Nygaard, B., & Svenning, J. C. (2013). Topographically controlled soil moisture is the primary driver of local vegetation patterns across a lowland region. Ecosphere, 4(7), 1–26. https://doi.org/10.1890/ES13-00134.1
   Web of Science ®Google Scholar
• Moore, I. D., Burch, G. J., & Mackenzie, D. H. (1988). Topographic effects on the distribution of surface soil water and the location of ephemeral gullies. Transactions of the ASAE,31(4), 1098–1107.
   Google Scholar
• Moore, I. D., Gessler, P. E., & Nielsen, G. A. (1993). Soil attribute prediction using terrain analysis. Soil Science Society of American Journal, 57(2), 443–452. https://doi.org/10.2136/sssaj1993.03615995005700020026x
   Web of Science ®Google Scholar
• Moore, I. D., Grayson, R. B., & Ladson, A. R. (1991). Digital terrain modelling: A review of hydrological, geomorphological, and biological applications. Hydrological Processes, 5(1), 3–30. https://doi.org/10.1002/hyp.3360050103
   Web of Science ®Google Scholar
• Nazik, L. (2004). The Karst Regions of Turkey (According to the Morpho genesis and Morphometric Properties). Proceeding of Int. Symposium on Earth SystemSciences 2004, Istanbul-Turkey, 77-82.
   Google Scholar
• Negasi, S., Shiferaw, H., Gebremedhin, A., Taye, G., & Zenebe, A. (2019). Comparative study on spatial variability of topsoil moisture content and carbon stocks as influenced by land use and soil and water conservation structures in the semi-arid Ethiopian highlands. http://ugspace.ug.edu.gh/handle/123456789/34093
   Google Scholar
• Nelson, D. W., & Sommers, L. E. (1982). Organic Matter. In Methods of Soil Analysis Part2.Chemical and Microbiological Properties (Second ed., pp. 574–579). Agronamy. No: 9 Part 2. Edition.
   Google Scholar
• Özyuvacı, N. (1971). Topraklarda Erozyon Eğiliminin Tespitinde Kullanılan Bazı Önemli İndeksler. Istanbul Üniversitesi Orman Fakültesi Dergisi Istanbul, 21(1), 190–207.
   Google Scholar
• Nyberg, L. (1996). Spatial variability of soil water content in the covered catchment of Gardsjon, Sweden. Hydrological Processes, 10(1), 89–103. https://doi.org/10.1002/(SICI)1099-1085(199601)10:1<89::AID-HYP303>3.0.CO;2-W
   Web of Science ®Google Scholar
• Pei, T., Qin, C. Z., Zhu, A. X., Yang, L., Luo, M., Li, B., & Zhou, C. (2010). Mapping soil organic matter using the topographic wetness index: A comparative study based on different flow-direction algorithms and kriging methods. Ecological Indicators, 10(3), 610–619. https://doi.org/10.1016/j.ecolind.2009.10.005
   Web of Science ®Google Scholar
• Peppa, M. V., Mills, J. P., Moore, P., Miller, P. E., & Chambers, J. E. (2019). Automated co‐registration and calibration in SfM photogrammetry for landslide change detection. Earth Surface Processes and Landforms, 44(1), 287–303. https://doi.org/10.1002/esp.4502
   Web of Science ®Google Scholar
• Quesada-Román, A., & Mata-Cambronero, E. (2021). The geomorphic landscape of the Barva volcano, Costa Rica. Physical Geography, 42(3), 265-282. URL: https://doi.org/10.1080/02723646.2020.1759762
   Web of Science ®Google Scholar
• Raduła, M. W., Szymura, T. H., & Szymura, M. (2018). Topographic wetness index explains soil moisture better than bioindication with Ellenberg’s indicator values. Ecological Indicators, 85(1), 172–179. https://doi.org/10.1016/j.ecolind.2017.10.011
   Web of Science ®Google Scholar
• Raduła, M. W., Szymura, T. H., & Szymura, M. (2018). Topographic wetness index explains soil moisture better than bioindication with Ellenberg’s indicator values. Ecological Indicators, 85(2018), 172–179. https://doi.org/10.1016/j.ecolind.2017.10.011
   Web of Science ®Google Scholar
• Rawls, W. J., & Pachepsky, Y. A. (2002). Using field topographic descriptors to estimate soil water retention. Soil Science, 167(7), 423–435. https://doi.org/10.1097/00010694-200207000-00001
   Web of Science ®Google Scholar
• Rhoades, J. D. (1986). Cation Exchange Capasity. In Methods of Soil Analysis (pp. II).(pp. 149-157 Agronomy 9.1179-1237) Am. Soc. of Agron. Inc. Madison, Wiscosin USA.
   Google Scholar
• Schmidt, F., & Persson, A. (2003). Comparison of DEM Data Capture and Topographic Wetness Indices, Precision Agr. 4(2), 179–192. https://link.springer.com/article/10.1023/A:1024509322709
   Google Scholar
• Seibert, J., Stendahl, J., & Sorensen, R. (2007). Topographical influences on soil properties in boreal forests. Geoderma, 141(1–2), 139–148. https://doi.org/10.1016/j.geoderma.2007.05.013
   Web of Science ®Google Scholar
• SPSS. (2008). SPSS Statistics for Windows, Version 17.0.
   Google Scholar
• Stage, A. R., & Salas, C. (2007). Interactions of elevation, aspect, and slope in models of forest species composition and productivity. Forest Science, 53(4), 486–492. https://doi.org/10.1093/forestscience/53.4.486
   Web of Science ®Google Scholar
• Steiniger, S., & Bocher, E. (2009). An overview on current free and open source desktop Gis developments. International Journal of Geographical Information Science23, 23(10), 1345–1370. https://doi.org/10.1080/13658810802634956
   Web of Science ®Google Scholar
• Stolbovoy, V., Montanarella, L., Filippi, N., Jones, A., Gallego, J., & Grassi, G. (2007). Field soil sampling to detect the changes of organic carbon stock in mineral soil 2. EUR 23037 EN (pp. 49). Office for Official Publications of the European Communities. ISBN: 978-92-79-07691-6.
   Google Scholar
• Sulebak, J. R., Tallaksen, L. M., & Erichsen, B. (2000). Estimation of areal soil moisture by use of terrain data. Geografiska Annaler: Series A. Physical Geography, 82(1), 89–105. https://doi.org/10.1111/j.0435-3676.2000.00009.x
   Web of Science ®Google Scholar
• Tague, C., Band, L., Kenworthy, S., & Tenebaum, D. (2010). Plot‐and watershed‐scale soil moisture variability in a humid Piedmont watershed. Water Resources Research, 46(12), 12. https://doi.org/10.1029/2009WR008078
   Web of Science ®Google Scholar
• Teuling, A. J., & Troch, P. A. (2005). Improved understanding of soil moisture variability dynamics. Geophysical Research Letters, 32(5), 5. https://doi.org/10.1029/2004GL021935
   Web of Science ®Google Scholar
• Tromp-van Meerveld, H. J., & McDonnell, J. J. (2006). On the interrelations between topography, soil depth, soil moisture, transpiration rates and species distribution at the hillslope scale. Advances in Water Resources, 29(2), 293–310. https://doi.org/10.1016/j.advwatres.2005.02.016
   Web of Science ®Google Scholar
• UNECE. (2003). ICP Forests Manual Book on methods and criteria for harmonized sampling, assessment, monitoring and analysis of the effects of air pollution on forests, 2003. Part IIIa Sampling and Analysis of Soil and Part IIIb Soil Solution Collection and Analysis. United Nations Commission for Europe Convention on Long-Range Transboundary Air Pollution, International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests. http://icp-forests.net/page/icp-forests-manual [ acceded on 12 March 2020]
   Google Scholar
• Vermez, Y., Dindaroğlu, T., & Rızaoğlu, T. (2018). Karstik Orman ekosistemlerin bazi petrografik, toprak ve vejetasyon özellikleri; kahramanmaraş-andirin sarimsak daği örneği. KSÜ Doga Bilimleri Dergisi, 21(1), 32–43. https://doi.org/10.18016/ksudobil.291164
   Google Scholar
• Wang, G., Li, J., Sun, W., Xue, B., Yinglan, A., & Liu, T. (2019). Non-point source pollution risks in a drinking water protection zone based on remote sensing data embedded within a nutrient budget model. Water Research, 157(2019), 238–246. https://doi.org/10.1016/j.watres.2019.03.070
   Web of Science ®Google Scholar
• Welsch, D. L., Kroll, C. N., McDonnell, J. J., & Burns, D. A. (2001). Topographic controls on the chemistry of subsurface stormflow. Hydrological Processes, 15(10), 1925–1938. https://doi.org/10.1002/hyp.247
   Web of Science ®Google Scholar
• Whelan, M. J., & Gandolfi, C. (2002). Modelling of spatial controls on denitrification at the landscape scale. Hydrological Processes, 16(7), 1437–1450. https://doi.org/10.1002/hyp.354
   Web of Science ®Google Scholar
• Wilson, D. J., Western, A. W., & Grayson, R. B. (2004). Identifying and quantifying sources of variability in temporal and spatial soil moisture observations. Water Resources Research, 40(2), W02507. https://doi.org/10.1029/2003WR002306
   Web of Science ®Google Scholar
• Xiong, L., Wang, G., Bao, Y., Zhou, X., Sun, X., & Zhao, R. (2018). Detectability of repeated airborne laser scanning for mountain landslide monitoring. Geosciences, 8(12), 469. https://doi.org/10.3390/geosciences8120469
   Web of Science ®Google Scholar
• Xu, X. L., Ma, K. M., Fu, B. J., Song, C. J., & Liu, W. (2008). Relationships between vegetation and soil and topography in a dry warm river valley, SW China. Catena, 75(2), 138–145. https://doi.org/10.1016/j.catena.2008.04.016
   Web of Science ®Google Scholar
• Yilmaz, Y., & Gurer, Ö. F. (1996). Andırın, geology and evolution of Misis-Andırın belt around Kahramanmaraş. Turkish Journal of Earth Sciences, 5(3) 39–55. https://journals.tubitak.gov.tr/earth/abstract.htm?id=424
   Google Scholar
• Ying, L. X., Shen, Z. H., Piao, S. L., Liu, Y., & Malanson, G. P. (2014). Terrestrial surface-area increment: The effects of topography, DEM resolution, and algorithm. Physical Geography, 35(4), 297–312. https://doi.org/10.1080/02723646.2014.886923
   Web of Science ®Google Scholar
• Zak, D. R., Hairston, A., & Grigal, D. F. (1991). Topographic influences on nitrogen cycling within an upland pin oak ecosystem. Forest Science, 37(1), 45–53. https://doi.org/10.1093/forestscience/37.1.45
   Web of Science ®Google Scholar
• Zeverbergen, L. W., & Thorne, C. R. (1987). Quantitative analysis of land surface topography. Earth Surface Processes and Landforms, 12(1), 47–56. https://doi.org/10.1002/esp.3290120107
   Web of Science ®Google Scholar
• Zhu, H., Huang, W., & Liu, H. (2018). Loess terrain segmentation from digital elevation models based on the region growth method. Physical Geography, 39(1), 51–66. https://doi.org/10.1080/02723646.2017.1342215
   Web of Science ®Google Scholar
• Zinko, U., Seibert, J., & Dynesius, M. (2005). Plant species numbers predicted by a topography based groundwater-flow index. Ecosystems, 8(4), 430–441. https://doi.org/10.1007/s10021-003-0125-0
   Web of Science ®Google Scholar