Exploring the short-scale spatial variability of calcic red latosol soil using DUALEM-1S proximal soil sensor

Short-scale spatial variability of soil properties need to be identified for the proper management of soil resources for crop production. Proximally sensing of soil apparent electrical conductivity (ECa) and the application of inversion technique are highly potential approaches to predict the spatial variability of soil properties. This study was carried out to investigate the applicability of ECa data together with inversion technique to predict the spatial variability of soil variability in Calcic Red Latosols. DUALEM-1S sensor was used to perform the ECa survey in an agricultural land (3.2 ha) situated in Allaveddy in the Jaffna district. The acquired ECa data were used to predict ECa at 20 cm depth increments down to 80 cm soil depth. Exploratory data analyses and then local kriging procedure were applied separately for original and inverted ECa data to construct continuous maps. Soil samples were taken from six sample points (at 20 cm depth intervals upto 80 cm from each sample point) using the purposive sampling scheme. Soil samples were analyzed for soil texture, organic matter, electrical conductivity (EC) and pH. Proximally sensed ECaPRP (CV = 45.4%) and ECaHCP (CV = 73.5%) and the depth profiles of different soil properties showed a high vertical and horizontal spatial variability of soil in the site. High correlations were shown between EC (measured at different depths) and both ECaPRP (r >0.60) and ECaHCP (r >0.60) at different depths. However, ECa did not show strong correlations with other soil properties. The high correlations (r > 0.76) between depth specific inverted ECaPRP and ECaHCP measurements and measured EC of respective depths indicated that these ECa data layers can be used to map the soil salinity development in different soil layers. This study revealed a strong short-scale spatial variability of soil properties in the selected Calcic Red Latosol and proximal soil sensing using the DUALEM-1S sensor is a highly potential tool for producing three dimensional maps of the soil EC. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	R. A. A. S. Rathnayaka [verfasserIn] W. A. U. Vitharana [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Schlagwörter:	apparent electrical conductivity, proximal soil sensing, short-scale spatial variability

Übergeordnetes Werk:	In: Tropical Agricultural Research - Postgraduate Institute of Agriculture, University of Peradeniya, 2019, 27(2016), 3
Übergeordnetes Werk:	volume:27 ; year:2016 ; number:3

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.4038/tar.v27i3.8203

Katalog-ID:	DOAJ067927092

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spelling	10.4038/tar.v27i3.8203 doi (DE-627)DOAJ067927092 (DE-599)DOAJf08352c188e5406fa4c9825a2bc4df34 DE-627 ger DE-627 rakwb eng R. A. A. S. Rathnayaka verfasserin aut Exploring the short-scale spatial variability of calcic red latosol soil using DUALEM-1S proximal soil sensor 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Short-scale spatial variability of soil properties need to be identified for the proper management of soil resources for crop production. Proximally sensing of soil apparent electrical conductivity (ECa) and the application of inversion technique are highly potential approaches to predict the spatial variability of soil properties. This study was carried out to investigate the applicability of ECa data together with inversion technique to predict the spatial variability of soil variability in Calcic Red Latosols. DUALEM-1S sensor was used to perform the ECa survey in an agricultural land (3.2 ha) situated in Allaveddy in the Jaffna district. The acquired ECa data were used to predict ECa at 20 cm depth increments down to 80 cm soil depth. Exploratory data analyses and then local kriging procedure were applied separately for original and inverted ECa data to construct continuous maps. Soil samples were taken from six sample points (at 20 cm depth intervals upto 80 cm from each sample point) using the purposive sampling scheme. Soil samples were analyzed for soil texture, organic matter, electrical conductivity (EC) and pH. Proximally sensed ECaPRP (CV = 45.4%) and ECaHCP (CV = 73.5%) and the depth profiles of different soil properties showed a high vertical and horizontal spatial variability of soil in the site. High correlations were shown between EC (measured at different depths) and both ECaPRP (r >0.60) and ECaHCP (r >0.60) at different depths. However, ECa did not show strong correlations with other soil properties. The high correlations (r > 0.76) between depth specific inverted ECaPRP and ECaHCP measurements and measured EC of respective depths indicated that these ECa data layers can be used to map the soil salinity development in different soil layers. This study revealed a strong short-scale spatial variability of soil properties in the selected Calcic Red Latosol and proximal soil sensing using the DUALEM-1S sensor is a highly potential tool for producing three dimensional maps of the soil EC. apparent electrical conductivity, proximal soil sensing, short-scale spatial variability Agriculture S W. A. U. Vitharana verfasserin aut In Tropical Agricultural Research Postgraduate Institute of Agriculture, University of Peradeniya, 2019 27(2016), 3 (DE-627)684963523 (DE-600)2648923-5 27060233 nnns volume:27 year:2016 number:3 https://doi.org/10.4038/tar.v27i3.8203 kostenfrei https://doaj.org/article/f08352c188e5406fa4c9825a2bc4df34 kostenfrei https://tar.sljol.info/articles/8203 kostenfrei https://doaj.org/toc/1016-1422 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 27 2016 3
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author	R. A. A. S. Rathnayaka
spellingShingle	R. A. A. S. Rathnayaka misc apparent electrical conductivity, proximal soil sensing, short-scale spatial variability misc Agriculture misc S Exploring the short-scale spatial variability of calcic red latosol soil using DUALEM-1S proximal soil sensor
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topic_title	Exploring the short-scale spatial variability of calcic red latosol soil using DUALEM-1S proximal soil sensor apparent electrical conductivity, proximal soil sensing, short-scale spatial variability
topic	misc apparent electrical conductivity, proximal soil sensing, short-scale spatial variability misc Agriculture misc S
topic_unstemmed	misc apparent electrical conductivity, proximal soil sensing, short-scale spatial variability misc Agriculture misc S
topic_browse	misc apparent electrical conductivity, proximal soil sensing, short-scale spatial variability misc Agriculture misc S
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title	Exploring the short-scale spatial variability of calcic red latosol soil using DUALEM-1S proximal soil sensor
ctrlnum	(DE-627)DOAJ067927092 (DE-599)DOAJf08352c188e5406fa4c9825a2bc4df34
title_full	Exploring the short-scale spatial variability of calcic red latosol soil using DUALEM-1S proximal soil sensor
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title_sort	exploring the short-scale spatial variability of calcic red latosol soil using dualem-1s proximal soil sensor
title_auth	Exploring the short-scale spatial variability of calcic red latosol soil using DUALEM-1S proximal soil sensor
abstract	Short-scale spatial variability of soil properties need to be identified for the proper management of soil resources for crop production. Proximally sensing of soil apparent electrical conductivity (ECa) and the application of inversion technique are highly potential approaches to predict the spatial variability of soil properties. This study was carried out to investigate the applicability of ECa data together with inversion technique to predict the spatial variability of soil variability in Calcic Red Latosols. DUALEM-1S sensor was used to perform the ECa survey in an agricultural land (3.2 ha) situated in Allaveddy in the Jaffna district. The acquired ECa data were used to predict ECa at 20 cm depth increments down to 80 cm soil depth. Exploratory data analyses and then local kriging procedure were applied separately for original and inverted ECa data to construct continuous maps. Soil samples were taken from six sample points (at 20 cm depth intervals upto 80 cm from each sample point) using the purposive sampling scheme. Soil samples were analyzed for soil texture, organic matter, electrical conductivity (EC) and pH. Proximally sensed ECaPRP (CV = 45.4%) and ECaHCP (CV = 73.5%) and the depth profiles of different soil properties showed a high vertical and horizontal spatial variability of soil in the site. High correlations were shown between EC (measured at different depths) and both ECaPRP (r >0.60) and ECaHCP (r >0.60) at different depths. However, ECa did not show strong correlations with other soil properties. The high correlations (r > 0.76) between depth specific inverted ECaPRP and ECaHCP measurements and measured EC of respective depths indicated that these ECa data layers can be used to map the soil salinity development in different soil layers. This study revealed a strong short-scale spatial variability of soil properties in the selected Calcic Red Latosol and proximal soil sensing using the DUALEM-1S sensor is a highly potential tool for producing three dimensional maps of the soil EC.
abstractGer	Short-scale spatial variability of soil properties need to be identified for the proper management of soil resources for crop production. Proximally sensing of soil apparent electrical conductivity (ECa) and the application of inversion technique are highly potential approaches to predict the spatial variability of soil properties. This study was carried out to investigate the applicability of ECa data together with inversion technique to predict the spatial variability of soil variability in Calcic Red Latosols. DUALEM-1S sensor was used to perform the ECa survey in an agricultural land (3.2 ha) situated in Allaveddy in the Jaffna district. The acquired ECa data were used to predict ECa at 20 cm depth increments down to 80 cm soil depth. Exploratory data analyses and then local kriging procedure were applied separately for original and inverted ECa data to construct continuous maps. Soil samples were taken from six sample points (at 20 cm depth intervals upto 80 cm from each sample point) using the purposive sampling scheme. Soil samples were analyzed for soil texture, organic matter, electrical conductivity (EC) and pH. Proximally sensed ECaPRP (CV = 45.4%) and ECaHCP (CV = 73.5%) and the depth profiles of different soil properties showed a high vertical and horizontal spatial variability of soil in the site. High correlations were shown between EC (measured at different depths) and both ECaPRP (r >0.60) and ECaHCP (r >0.60) at different depths. However, ECa did not show strong correlations with other soil properties. The high correlations (r > 0.76) between depth specific inverted ECaPRP and ECaHCP measurements and measured EC of respective depths indicated that these ECa data layers can be used to map the soil salinity development in different soil layers. This study revealed a strong short-scale spatial variability of soil properties in the selected Calcic Red Latosol and proximal soil sensing using the DUALEM-1S sensor is a highly potential tool for producing three dimensional maps of the soil EC.
abstract_unstemmed	Short-scale spatial variability of soil properties need to be identified for the proper management of soil resources for crop production. Proximally sensing of soil apparent electrical conductivity (ECa) and the application of inversion technique are highly potential approaches to predict the spatial variability of soil properties. This study was carried out to investigate the applicability of ECa data together with inversion technique to predict the spatial variability of soil variability in Calcic Red Latosols. DUALEM-1S sensor was used to perform the ECa survey in an agricultural land (3.2 ha) situated in Allaveddy in the Jaffna district. The acquired ECa data were used to predict ECa at 20 cm depth increments down to 80 cm soil depth. Exploratory data analyses and then local kriging procedure were applied separately for original and inverted ECa data to construct continuous maps. Soil samples were taken from six sample points (at 20 cm depth intervals upto 80 cm from each sample point) using the purposive sampling scheme. Soil samples were analyzed for soil texture, organic matter, electrical conductivity (EC) and pH. Proximally sensed ECaPRP (CV = 45.4%) and ECaHCP (CV = 73.5%) and the depth profiles of different soil properties showed a high vertical and horizontal spatial variability of soil in the site. High correlations were shown between EC (measured at different depths) and both ECaPRP (r >0.60) and ECaHCP (r >0.60) at different depths. However, ECa did not show strong correlations with other soil properties. The high correlations (r > 0.76) between depth specific inverted ECaPRP and ECaHCP measurements and measured EC of respective depths indicated that these ECa data layers can be used to map the soil salinity development in different soil layers. This study revealed a strong short-scale spatial variability of soil properties in the selected Calcic Red Latosol and proximal soil sensing using the DUALEM-1S sensor is a highly potential tool for producing three dimensional maps of the soil EC.
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title_short	Exploring the short-scale spatial variability of calcic red latosol soil using DUALEM-1S proximal soil sensor
url	https://doi.org/10.4038/tar.v27i3.8203 https://doaj.org/article/f08352c188e5406fa4c9825a2bc4df34 https://tar.sljol.info/articles/8203 https://doaj.org/toc/1016-1422
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Exploring the short-scale spatial variability of calcic red latosol soil using DUALEM-1S proximal soil sensor

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