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mapping soil nutrients via different covariates combinations:theory and an example from Morocco

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Ecological Processes 2022年第1期11卷 302-318页

作者： Kingsley John Yassine Bouslihim Isong Abraham Isong Lahcen Hssaini Rachid Razouk Ndiye M.Kebonye Prince C.Agyeman Vit Penížek Tereza Zádorová Department of soil Science and soil Protection Faculty of AgrobiologyFoodand Natural ResourcesCzech University of Life SciencesKamýcká12916500 PragueCzech Republic National Institute of Agricultural Research RabatMorocco Department of soil Science University of CalabarCalabarNigeria

Background:mapping of soil nutrients using different covariates was carried out in northern *** study was undertaken in response to the region’s urgent requirement for an updated soil *** aimed to test various covariates combinations for predicting the variability in soil properties using ordinary kriging and kriging with external ***:A total of 1819 soil samples were collected at a depth of 0–40 cm using the 1-km grid sampling *** were screened for their pH,soil organic matter(SOM),potassium(K_(2)O),and phosphorus(P_(2)O_(5))using standard laboratory *** attributes(T)computed using a 30-m resolution digital elevation model,bioclimatic data(C),and vegetation indices(V)were used as covariates in the *** targeted soil property was modeled using covariates separately and then combined(e.g.,pH~T,pH~C,pH~V,and pH~T+C+V).k=tenfold cross-validation was applied to examine the performance of each employed *** statistical parameter RMSE was used to determine the accuracy of different ***:The pH of the area is slightly above the neutral level with a corresponding 7.82%of SOM,290.34 ppm of K_(2)O,and 100.86 ppm of P_(2)O_(5).This was used for all the selected targeted soil *** a result,the studied soil properties showed a linear relationship with the selected ***,SOM,and K 2O presented a moderate spatial autocorrelation,while P2O5 revealed a strong *** cross-validation result revealed that soil pH(RMSE=0.281)and SOM(RMSE=9.505%)were best predicted by climatic variables.P_(2)O_(5)(RMSE=106.511 ppm)produced the best maps with climate,while K_(2)O(RMSE=209.764 ppm)yielded the best map with terrain ***:The findings suggest that a combination of too many environmental covariates might not provide the actual variability of a targeted soil *** demonstrates that specific covariates with close relationships with certain soil properties might perform bet

关键词： soil mapping Environmental variables Agriculture soil properties soil management

mapping of Regional soil Salinities in Xinjiang and Strategies for Amelioration and Management

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Chinese Geographical Science 2015年第3期25卷 321-336页

作者： WANG Fei CHEN Xi LUO Geping HAN Qifei State Key Laboratory of Desert and Oasis Ecology Xinjiang Institute of Ecology and GeographyChinese Academy of Sciences University of Chinese Academy of Sciences

Information on the spatial distribution of soil salinity can be used as guidance in avoiding the continued degradation of land and water resources by better informing policy makers. However, most regional soil-salinity maps are produced through a conventional direct-linking method derived from historic observations. Such maps lack spatial details and are limited in describing the evolution of soil salinization in particular instances. To overcome these limitations, we employed a method that included an integrative hierarchical-sampling strategy(IHSS) and the soil Land Inference Model(So LIM) to map soil salinity over a regional area. A fuzzy c-means(FCM) classifier is performed to generate three measures, comprising representative grade, representative area, and representative level(membership). IHSS employs these three measures to ascertain how many representative samples are appropriate. Through this synergetic assessment, representative samples are obtained and their soil-salinity values are measured. These samples are input to So LIM, which is constructed based on fuzzy logic, to calculate the soil-forming environmental similarities between representative samples and other locations. Finally, a detailed soil-salinity map is produced through an averaging function that is linearly weighted, which is used to integrate the soil salinity value and soil similarity. This case study, in the Uyghur Autonomous Region of Xinjiang of China, demonstrates that the employed method can produce soil salinity map at a higher level of spatial detail and accuracy. Twenty-three representative points are determined. The results show that 1) the prediction is appropriate in Kuqa Oasis(R2 = 0.70, RPD = 1.55, RMSE = 12.86) and Keriya Oasis(R2 = 0.75, RPD = 1.66, RMSE = 10.92), that in Fubei Oasis(R2 = 0.77, RPD = 2.01, RMSE = 6.32) perform little better than in those two oases, according to the evaluation criterion. 2) Based on all validation samples from three oases, accuracy estimatio

关键词： salinity soil mapping purposive sampling soil Land Inference Model(So LIM) fuzzy c-means(FCM) multiple linear regression(MLR) model

Modelling soil erodibility in mountain rangelands of southern Kyrgyzstan

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Pedosphere 2020年第4期30卷 443-456页

作者： Maksim KULIKOV Udo SCHICKHOFF Alexander GRONGROFT Peter BORCHARDT Centrum für Erdsystemforschung und Nachhaltigkeit(CEN) Center for Earth System Research and SustainabilityInstitute of GeographyUniversity of HamburgHamburg D-20146(Germany) Centrum für Erdsystemforschung und Nachhaltigkeit(CEN) Center for Earth System Research and SustainabilityInstitute of Soil ScienceUniversity of HamburgHamburg D-20146(Germany)

soil erosion in mountain rangelands in Kyrgyzstan is an emerging problem due to vegetation loss caused by overgrazing. It is further exacerbated by mountain terrain and high precipitation values in Fergana range in the south of Kyrgyzstan. The main objective of this study was to map soil erodibility in the mountainous rangelands of Kyrgyzstan. The results of this effort are expected to contribute to the development of soil erodibility modelling approaches for mountainous areas. In this study, we mapped soil erodibility at two sites, both representing grazing rangelands in the mountains of Kyrgyzstan and having potentially different levels of grazing pressure. We collected a total of 232 soil samples evenly distributed in geographical space and feature space. Then we analyzed the samples in laboratory for grain size distribution and calculated soil erodibility values from these data using the Revised Universal soil Loss Equation (RUSLE) K-factor formula. After that, we derived different terrain indices and ratios of frequency bands from ASTER GDEM and LANDSAT images to use as auxiliary data because they are among the main soil forming factors and widely used for prediction of various soil properties. soil erodibility was significantly correlated with channel network base level (geographically extrapolated altitude of water channels), remotely sensed indices of short-wave infrared spectral bands, exposition, and slope degree. We applied multiple regression analysis to predict soil erodibility from spatially explicit terrain and remotely sensed indices. The final soil erodibility model was developed using the spatially explicit predictors and the regression equation and then improved by adding the residuals. The spatial resolution of the model was 30 m, and the estimated mean adjusted coefficient of determination was 0.47. The two sites indicated different estimated and predicted means of soil erodibility values (0.035 and 0.039) with a 0.05 significance level, which i

关键词： channel network base level K-factor LANDSAT RUSLE soil enhancement ratio soil mapping slope terrain

Limited Spatial Transferability of the Relationships Between Kriging Variance and soil Sampling Spacing in Some Grasslands of Ireland:Implications for Sampling Design

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Pedosphere 2019年第5期29卷 577-589页

作者： SUN Xiaolin WANG Huili Dermot FORRISTAL FU Weijun Hubert TUNNEY Chaosheng ZHANG Guangdong Provincial Key Laboratory for Urbanization and Geo-simulation School of Geography and PlanningSun Yat-sen UniversityGuangzhou 510275 (China) State Key Laboratory of soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008 (China) International Network for Environment and Health School of Geography and ArchaeologyNational University of IrelandGalway H91 TK33 (Ireland) Guangxi Forestry Research Institute Nanning 530002 (China) Crop Science Department TeagascOak ParkCarlow (Ireland) School of Environmental and Resource Sciences Zhejiang 4&F UniversityLirVan 311300 (China) Teagasc Johnstown Castle Research CentreWexford (Ireland)

Sampling plays an important role in acquiring precise soil information required in modern agricultural production worldwide, which determines both the cost and quality of final soil mapping products. For sampling design, it has been proposed possibile to transfer the relationships between kriging variance and sampling grid spacing from an area with existing information to other areas with similar soil-forming environments. However, this approach is challenged in practice because of two problems: i) different population vaxiograms among similar areas and ii) sampling errors in estimated variograms. This study evaluated the effects of these two problems on the transferability of the relationships between kriging variance and sampling grid spacing, by using spatial data simulated with three variograms and soil samples collected from four grasslands in Ireland with similar soil-forming environments. Results showed that the variograms suggested by different samples collected with the same grid spacing in the same or similar areas were different, leading to a range of mean kriging variance (MKV) for each grid spacing. With increasing grid spacing, the variation of MKV for a specific grid spacing increased and deviated more from the MKV generated using the population variograms. As a result, the spatial transferability of the relationships between kriging variance and grid spacing for sampling design was limited.

关键词： Key Words. geostatistics, population variogram, sampling error, sampling grid spacing soil-forming environment soil information soil mapping spatial variability

Superficial Color Patches as a Visual Diagnostic Criterion for Agricultural Management

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Pedosphere 2013年第6期23卷 740-751页

作者： C.CASTANEDA D.MORET-FERNNDEZ Estacio'n Experimental de Aula Dei CSIC

soil management matters in semiarid lands are key to have acceptable yields and to preserve diversity. After the major agricultural intensification underwent in the semiarid lands of Monegros, NE Spain, custom tailored tools are needed to reconcile agriculture with habitats conservation. The objectives of this study were to quantify the effect of soil properties of two distinctly colored soils, white patches （WP） and dark patches （DP）, dominant in the arid landscape of the central Ebro Basin, Spain on winter cereal grain yield and to prove that superficial soil color could be used as a visual diagnostic criterion for evaluation of agricultural practices in arid lands. Significant differences between WP and DP soils were found in gypsum, carbonate contents, available water holding capacity and infiltration rate. The grain yield ranged from 51 to 5 713 kg ha-1. Significantly lower yields （P 〈 0.01） and precipitation-use efficiency （P 〈 0.05） were attained in the WP soils for the three seasons studied. This difference increased with the average rainfall due to the significantly lower soil water infiltration （P 〈 0.01） and water holding capacity （P 〈 0.05） found in the gypseous soils. Our results show that mapping the soil surface color at farm scale can be a low=cost tool for optimizing agricultural practices and recovering the natural vegetation. This approach can be advantageous in similar arid or semiarid environments around the world.

关键词： arid zones dryland cropping gypsum hydraulic conductivity soil mapping

Preliminary mapping and Characterisation of soils in the Pirin Mountains (Bulgaria)

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Journal of Mountain Science 2008年第2期5卷 122-129页

作者： Maika Lβiger Jrg Scheithauer Karsten Grunewald University of Technology Dresden D-01062 Dresden Germany Landscape Research Centre Dresden Am Ende 14 D-01277 Dresden Germany

soil types, humus types and vegetation as well as their hypsometric variation were analysed in terms of sequences in the northern part of the high mountains of the Pirin National Park at altitudes between looo and 2400 m a.s.1. The study area is characterised by a large variety of natural parameters like petrology （mainly marble and granite）, morphology （different slope deposits, exposition） and the orographic climate gradient. Statistical analyses using these parameters provided a basis for the soil group classification of the sites. Based on a Digital Terrain Model （DTM） and a geological map of the Pirin National Park, the results of these statistical analyses were used to generate a ＂map of potential soil groups＂（regionalisation using GIS）. Six potential soil groups could be determined. The resulting map exhibits a confidence level of 68 % on 74.4 % of the covered area. Rendzic Leptosols, in combination with Folic Histosols and Histi-lithic Leptosols occur in the alpine and subalpine regions on calcareous substrates. With decreasing altitude they are replaced by a mosaic of Rendzic Leptosols, Phaeozems and an increasing occurrence of Cambic Umbrisols. Umbrisols found on silicatic substrates in the alpine region are replaced by Cambic Umbrisols with decreasing altitude as well. Hence, pedogenesis is characterised by increasing browning and depth of the soil profiles with decreasing altitude. The pH-level is slightly acidic to neutral in lower zones and on calcareous rocky bases. Acidification increases in the subalpine zone. soil pH decreases down to 4 on silicate subtrates. Typical humic values in mineral topsoils are 10 to 12 %, and in organic layers of the soils above 2000 m a.s.1, they are even more. The C：N ratio closely ranges around 20 （median）.

关键词： Cluster analysis soil mapping hypsometric soil differentiation Southeast Europe

Studies on Land Resource Inventory for Agricultural Land Use Planning in Northern Transition Zone of India through Remote Sensing and GIS Techniques

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Journal of Geographic Information System 2021年第6期13卷 710-728页

作者： Denis Magnus Ken Amara Sayyadsaheb A. Nadaf Daniel Hindogbe Saidu Osman S. Vonu Raymond Morie Musa Philip Jimia Kamanda Patrick A. Sawyerr John Christian Mboma Saidu Deggy Mansaray Mohammed Azim Sannoh Department of soil Science & Agricultural Chemistry University of Agricultural Sciences Dharwad Dharwad India Department of soil Science School of Agriculture & Food Sciences Njala University Njala Campus Freetown Sierra Leone Department of Agriculture Food Security & Livelihood Sustainable Cassava Commercialization through Entrepreneurs Strengthening & Support (SUCCESS) Project BRAC Bo Sierra Leone Department of soil Science Eastern Technical University of Sierra Leone Private Mail Bag Kenema Sierra Leone Department of Agricultural Education Eastern Technical University of Sierra Leone Private Mail Bag Kenema Sierra Leone Department of Extension & Rural Sociology School of Agriculture & Food Sciences Njala University Freetown Sierra Leone Department of Social Studies Eastern Technical University of Sierra Leone Private Mail Bag Kenema Sierra Leone

Land suitability analysis is a prerequisite to achieving optimum utilization of available land resources. Hence, a study on land resource inventory for agricultural land use planning was conducted in the Northern Transition Zone of India to determine land capability and develop a suitability map for wheat and sorghum-based on physical and climatic factors of production using remote sensing and GIS techniques. Detailed soil survey information was used for this exercise. Four series (Singhanhalli, Mugli, Bogur and Venkatapur series) were identified and mapped into seventeen mapping units. Land capability classification showed that a greater portion of the study area belonged to class III followed by class IV with limitations of erosion, wetness and varying soil properties. Four land capability classes viz., II, III, IV, and VI, and seven subclasses viz., IIsf, IIItsf, IVs, IVt, IVts, IVtsf and VIt were identified. Major limitations of these subclasses were slope, erosion, depth, texture, coarse fragments, pH, organic carbon and base saturation. soil suitability assessment revealed that the soils are moderately suitable to permanently not suitable. About 234 ha (31.6%) is moderately suitable, 494 ha (65.0%) marginally suitable and 10.2 ha (1.3%) permanently not suitable for wheat;while 78.5 ha (10.3%) is moderately suitable, 633.4 ha (82.3%) marginally suitable and 32.6 ha (4.3%) permanently not suitable for sorghum respectively. The moderate, marginal and permanent non-suitability was due to moderate, severe and very severe limitations respectively. However, it is possible to achieve potential yield of the crops in the study area if these limitations are addressed.

关键词： Land Resource Inventory soil Suitability Land Use Planning Land Evaluation soil Survey Remote Sensing soil mapping

DEVELOPMENT OF KNOWLEDGE FOR PREDICTIVE mapping USING A FUZZY C-MEANS CLASSIFICATION

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DEVELOPMENT OF KNOWLEDGE FOR PREDICTIVE MAPPING USING A FUZZ...