Development Direction of the Soil-Formation Processes for Reclaimed Soda Solonetz-Solonchak Soils of the Ararat Valley During Their Cultivation
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World Reference Base for Soil Resources 2014 International Soil Classification System for Naming Soils and Creating Legends for Soil Maps
ISSN 0532-0488 WORLD SOIL RESOURCES REPORTS 106 World reference base for soil resources 2014 International soil classification system for naming soils and creating legends for soil maps Update 2015 Cover photographs (left to right): Ekranic Technosol – Austria (©Erika Michéli) Reductaquic Cryosol – Russia (©Maria Gerasimova) Ferralic Nitisol – Australia (©Ben Harms) Pellic Vertisol – Bulgaria (©Erika Michéli) Albic Podzol – Czech Republic (©Erika Michéli) Hypercalcic Kastanozem – Mexico (©Carlos Cruz Gaistardo) Stagnic Luvisol – South Africa (©Márta Fuchs) Copies of FAO publications can be requested from: SALES AND MARKETING GROUP Information Division Food and Agriculture Organization of the United Nations Viale delle Terme di Caracalla 00100 Rome, Italy E-mail: [email protected] Fax: (+39) 06 57053360 Web site: http://www.fao.org WORLD SOIL World reference base RESOURCES REPORTS for soil resources 2014 106 International soil classification system for naming soils and creating legends for soil maps Update 2015 FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS Rome, 2015 The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations (FAO) concerning the legal or development status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. The mention of specific companies or products of manufacturers, whether or not these have been patented, does not imply that these have been endorsed or recommended by FAO in preference to others of a similar nature that are not mentioned. The views expressed in this information product are those of the author(s) and do not necessarily reflect the views or policies of FAO. -
The Digital Soil Map of the World
THE DIGITAL SOIL MAP OF THE WORLD FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS Version 3.6, completed January 2003 (C) FAO/UNESCO, 1995 All rights reserved worldwide. Background The present version (3.6) of the digitized Soil Map of the World has been cleaned of errors both in the database and in the lines constituting the digitized map itself. The original map sheets covering the Americas are in bipolar oblique conformal projection. The other sheets, covering Europe, Africa, Asia and Australasia, are based on the Miller oblated stereographic projection; a system consisting of three conformal projections centred on each continent, joined together in a continuous fashion by so-called "fill-in" projections. This allows a complete angular continuity between all sheets. The soil map was prepared using the topographic map series of the American Geographical Society of New York as a base at a nominal scale of 1:5 000 000. The base map comprises sixteen sheets; for the purpose of the Soil Map of the World the information has been redistributed over eighteen sheets in order to obtain sheets of equal size. A nineteenth sheet contains the legend. The digital database is in the Geographic projection. All maps were intersected with a template containing water related features (coastlines, lakes, islands, glaciers and double-lined rivers). This layer was superimposed on the soil map (the information is represented in the FAOSOIL item as: inland WATer, and GLaciers). The Soil Map of the World except for Africa was intersected with the Country Boundaries map from the World Data Bank II (with country boundaries updated to January 1994 at 1:3 000 000 scale), obtained from the US Government. -
The Use of Proximal Soil Sensor Data Fusion and Digital Soil Mapping For
The use of proximal soil sensor data fusion and digital soil mapping for precision agriculture Wenjun Ji, Viacheslav Adamchuk, Songchao Chen, Asim Biswas, Maxime Leclerc, Raphael Viscarra Rossel To cite this version: Wenjun Ji, Viacheslav Adamchuk, Songchao Chen, Asim Biswas, Maxime Leclerc, et al.. The use of proximal soil sensor data fusion and digital soil mapping for precision agriculture. Pedometrics 2017, Jun 2017, Wageningen, Netherlands. 298 p. hal-01601278 HAL Id: hal-01601278 https://hal.archives-ouvertes.fr/hal-01601278 Submitted on 2 Jun 2020 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution - ShareAlike| 4.0 International License Abstract Book Pedometrics 2017 Wageningen, 26 June – 1 July 2017 2 Contents Evaluating Use of Ground Penetrating Radar and Geostatistic Methods for Mapping Soil Cemented Horizon .................................... 13 Digital soil mapping in areas of mussunungas: algoritmos comparission .......... 14 Sensing of farm and district-scale soil moisture content using a mobile cosmic ray probe (COSMOS Rover) .................................... 15 Proximal sensing of soil crack networks using three-dimensional electrical resistivity to- mography ......................................... 16 Using digital microscopy for rapid determination of soil texture and prediction of soil organic matter ..................................... -
Understanding the Environmental Background of an Invasive Plant
plants Article Understanding the Environmental Background of an Invasive Plant Species (Asclepias syriaca) for the Future: An Application of LUCAS Field Photographs and Machine Learning Algorithm Methods Péter Szilassi 1,* ,Gábor Szatmári 2 ,László Pásztor 2 ,Mátyás Árvai 2,József Szatmári 1, Katalin Szitár 3 and Levente Papp 4 1 Department of Physical Geography and Geoinformatics, University of Szeged, Egyetem utca 2, 6722 Szeged, Hungary; [email protected] 2 Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, Herman Ottó út 15, 1022 Budapest, Hungary; [email protected] (G.S.); [email protected] (L.P.); [email protected] (M.Á.) 3 Institute of Ecology and Botany, Centre for Ecological Research, Alkotmány u. 2-4, 2163 Vácrátót, Hungary; [email protected] 4 Department of Geoinformatics, University of Salzburg, Schillerstraße 30, 5020 Salzburg, Austria; [email protected] * Correspondence: [email protected] Received: 4 November 2019; Accepted: 10 December 2019; Published: 12 December 2019 Abstract: For developing global strategies against the dramatic spread of invasive species, we need to identify the geographical, environmental, and socioeconomic factors determining the spatial distribution of invasive species. In our study, we investigated these factors influencing the occurrences of common milkweed (Asclepias syriaca L.), an invasive plant species that is of great concern to the European Union (EU). In a Hungarian study area, we used country-scale soil and climate databases, as well as an EU-scale land cover databases (CORINE) for the analyses. For the abundance data of A. syriaca, we applied the field survey photos from the Land Use and Coverage Area Frame Survey (LUCAS) Land Cover database for the European Union. -
List M - Soils - German and French Equivalents of English Terms
LIST M - SOILS - GERMAN AND FRENCH EQUIVALENTS OF ENGLISH TERMS AMERICAN GERMAN FRENCH AMERICAN GERMAN FRENCH Acrisols Acrisol Sol-mediterraneen Gray podzolic soils Podsolierter grauer Podzol Albolls Boden Alfisols Gray warp soils Paternia Sol-peu-evolue or Alluvial soils Auen-Boden Sol-d’alluvions Sol-d’alluvions Alpine meadow soils Alpiner Wiesen- Sol-hydromorphe Gray wooded soils boden Ground-water podzols Gley-Podsol Podzol Andepts Ground-water Grundwasser- Laterite Andosols Andosol Sol-peu-evolue laterite soils Laterite roche- Grumosols Grumosol Vertisol volcanique Half bog soils Anmoor Tourbe Aqualfs Halomorphic soils Salz-Boden Sol-halomorphe Aquents Halosols Halosols Sal-halomorphe Aquepts Hemists Aquods High moor Hochmoor Tourbe Aquolls Histosols Aquox Humic gley soils Humus Gley Boden Aquults Sol-humique-a-gley Arctic tundra soils Arktische Tundra Sol-de-toundra Humic soils Humus-reiche- Sol-riche-en- Boden Boden humus Arenosols Arenosol Sol-brut sable Humods Arents Hydromorphic soils Hydromorpher- Sol-hydro- Argids Boden morphique Aridisols Inceptisols Azonal soils Roh-Boden Sol-brut Intrazonal soils Intrazonaler Boden Sol Black earth use Schwarzerde Chernozem Kastanozems Chernozems Krasnozems Krasnozem Krasnozem Bog soils Moorboden Tourbe laterites Laterit-Boden Sol-lateritique Boreal frozen taiga Sol-gele Latosols Latosol Sol-ferralitique soils Lithosols Gesteins-roh-Boden Sol-squelettique Boreal taiga and Sol Low-humic gley soils forest soils Luvisols Luvisols Sol lessivage Brown desert steppe Burozem Sierozem Mediterranean -
Soilgrids 2.0: Producing Soil Information for the Globe with Quantified Spatial Uncertainty
SOIL, 7, 217–240, 2021 https://doi.org/10.5194/soil-7-217-2021 © Author(s) 2021. This work is distributed under SOIL the Creative Commons Attribution 4.0 License. SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty Laura Poggio, Luis M. de Sousa, Niels H. Batjes, Gerard B. M. Heuvelink, Bas Kempen, Eloi Ribeiro, and David Rossiter ISRIC – World Soil Information, Wageningen, the Netherlands Correspondence: Laura Poggio ([email protected]) Received: 14 October 2020 – Discussion started: 9 November 2020 Revised: 9 April 2021 – Accepted: 18 April 2021 – Published: 14 June 2021 Abstract. SoilGrids produces maps of soil properties for the entire globe at medium spatial resolution (250 m cell size) using state-of-the-art machine learning methods to generate the necessary models. It takes as inputs soil observations from about 240 000 locations worldwide and over 400 global environmental covariates describing vegetation, terrain morphology, climate, geology and hydrology. The aim of this work was the production of global maps of soil properties, with cross-validation, hyper-parameter selection and quantification of spatially explicit uncertainty, as implemented in the SoilGrids version 2.0 product incorporating state-of-the-art practices and adapting them for global digital soil mapping with legacy data. The paper presents the evaluation of the global predictions produced for soil organic carbon content, total nitrogen, coarse fragments, pH (water), cation exchange capacity, bulk density and texture fractions at six standard depths (up to 200 cm). The quantitative evaluation showed metrics in line with previous global, continental and large-region studies. -
Digital Soil Mapping As a Tool for Improved Road and Game Drive Management Within Phinda Private Game Reserve, Kwa-Zulu Natal
University of South Africa ― Fourie, P.J. (2020) DIGITAL SOIL MAPPING AS A TOOL FOR IMPROVED ROAD AND GAME DRIVE MANAGEMENT WITHIN PHINDA PRIVATE GAME RESERVE, KWA-ZULU NATAL by Petrus Johannes Fourie Submitted in accordance with the requirements For the application in the degree of Masters of Environmental Science in the DEPARTMENT OF AGRICULTURAL AND ENVIRONMENTAL SCIENCES at the UNIVERSITY OF SOUTH AFRICA Supervisor Dr G.P. Nortjé Co-supervisor Dr George van Zijl June 2020 i University of South Africa ― Fourie, P.J. (2020) Declaration I, Petrus Johannes Fourie, hereby declare that the dissertation/ thesis, which I hereby submit for the degree of Master of Environmental Science at the University of South Africa, is my own work and has not previously been submitted by me for a degree at this or any other institution. I declare that the dissertation/ thesis does not contain any written work presented by other persons whether written, pictures, graphs or data or any other information without acknowledging the source. I declare that where words from a written source have been used, the words have been paraphrased and referenced. Where exact words from a source have been used, the words have been placed inside quotation marks and referenced. I declare that I have not copied and pasted any information from the Internet, without specifi- cally acknowledging the source and have inserted appropriate references to these sources in the reference section of the dissertation or thesis. I declare that during my study I adhered to the Research Ethics Policy of the University of South Africa, received ethics approval for the duration of my study prior to the commencement of data gathering, and have not acted outside the approval conditions. -
Organic Matter Dynamics Along a Salinity Gradient in Siberian Steppe Soils
Organic matter dynamics along a salinity gradient in Siberian steppe soils Norbert Bischoff1, Robert Mikutta2, Olga Shibistova1,3, Reiner Dohrmann4, Daniel Herdtle1, Lukas Gerhard1, Franziska Fritzsche1, Alexander Puzanov5, Marina Silanteva6, Anna 5 Grebennikova6, Georg Guggenberger1 1Institute of Soil Science, Leibniz University Hannover, Herrenhäuser Straße 2, 30419 Hannover, Germany 2Soil Science and Soil Protection, Martin Luther University Halle-Wittenberg, Von-Seckendorff-Platz 3, 06120 Halle (Saale), Germany 10 3VN Sukachev Institute of Forest, Siberian Branch of the Russian Academy of Sciences, Akademgorodok 50, 660036 Krasnoyarsk, Russian Federation 4Federal Institute for Geosciences and Natural Resources, Stilleweg 2, 30655 Hannover, Germany 5Institute for Water and Environmental Problems, Siberian Branch of the Russian Academy of Sciences, Molodezhnaya Street 1, 656038 Barnaul, Russian Federation 15 6Faculty of Biology, Altai State University, Prospekt Lenina 61a, 656049 Barnaul, Russian Federation Correspondence to: Norbert Bischoff ([email protected]) 1 Abstract Salt-affected soils will become more frequent in the next decades as arid and semi-arid ecosystems are predicted to expand as a result of climate change. Nevertheless, little is known about organic matter (OM) dynamics in these soils, though OM is crucial for soil fertility and represents an important carbon sink. We aimed at 5 investigating OM dynamics along a salinity and sodicity gradient in soils of the south-western Siberian Kulunda steppe (Kastanozem, Non-sodic Solonchak, Sodic Solonchak) by assessing the organic carbon (OC) stocks, the quantity and quality of particulate and mineral-associated OM in terms of non-cellulosic neutral sugar contents and carbon isotopes (δ13C, 14C activity), and the microbial community composition based on phospholipid fatty acid (PLFA) patterns. -
Fuzzy Logic Expert System for Classifying Solonchaks of Algeria
Hindawi Applied and Environmental Soil Science Volume 2018, Article ID 8741567, 11 pages https://doi.org/10.1155/2018/8741567 Research Article Fuzzy Logic Expert System for Classifying Solonchaks of Algeria Samir Hadj Miloud ,1,2 Kaddour Djili,1 and Mohamed Benidir3 1Soil Science Department, Higher National Agronomic School (ENSA-ES1603), BP 16200 El Harrach, Algeria 2Department of Agronomics, Faculty of Natural Science and Life, University Saad Dahlab, Soumaˆa, BP 270 Blida, Algeria 3Unit of Se´tif, Institut National de la Recherche Agronomique (INRAA), El Harrach, Algeria Correspondence should be addressed to Samir Hadj Miloud; [email protected] Received 29 November 2017; Accepted 13 June 2018; Published 8 July 2018 Academic Editor: Claudio Cocozza Copyright © 2018 Samir Hadj Miloud et al. +is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Under arid and semiarid regions of the North of Africa, the soils considered as Solonchaks contain both calcium carbonate and gypsum. When these elements are presented at high quantities, these Solonchaks are getting close to Calcisol or Gypsisol. +e World Reference Base (WRB) for soil classification does not take into account the soil as a continuum. Instead, this international soil system classification is based on threshold values that define hierarchical diagnostic criteria. Consequently, the distinction between Solonchaks, Calcisol, and Gypsisol is still not clear. To avoid this situation, fuzzy logic based on the Mamdani inference system (MFIS) was used to determine to what extent soil classified as Solonchak in WRB can interfere with Calcisols and Gypsisols. -
Fire Effects Guide This Page Was Last Modified 06/21/01 |Disclaimer| | Privacy| | Copyright| |Webmaster|
National Wildfire Coordinating Group Fire Effects Guide This page was last modified 06/21/01 |Disclaimer| | Privacy| | Copyright| |Webmaster| Home Preface FIRE EFFECTS GUIDE Objectives Fire Behavior Fuels Sponsored by: Air Quality Soils & Water Plants National Wildlife Coordinating Group Wildlife Cultural Res. Fire Use Working Team Grazing Mgmt. Evaluation Copies of the guide (NFES 2394) can be ordered form: Data Analysis Computer National Interagency Fire Center Soft. Great Basin Area Cache Glossary 3833 S. Development Ave. Bibliography Boise ID 83702 Contributions National Wildfire Coordinating Group Fire Effects Guide This page was last modified 06/20/01 |Disclaimer| | Privacy| | Copyright| |Webmaster| Home PREFACE Preface Objectives by Dr. Bob Clark and Melanie Miller Fire Behavior Fuels A. Purpose Air Quality Soils & Water Plants The Federal government manages a variety of ecosystems across the Wildlife United States, including deserts, grasslands, tundra, shrublands, Cultural Res. forestlands, estuaries, and riparian zones. These ecosystems range Grazing from arid to humid, warm to cold, and sea level to over 10,000 feet Mgmt. elevation. Fires naturally occur in almost all of these ecosystems, with Evaluation fire characteristics determined by climate, vegetation, and terrain. Data Analysis Computer The purposes of this Guide are to summarize available information on Soft. fire effects principles and processes, provide references for additional Glossary information, and provide guidelines for the collection, analysis, and Bibliography evaluation of wild and prescribed fire effects data. Basic mechanisms of Contributions fire effects are described so that the reader will be able to understand and interpret fire effects literature, and evaluate observed results that conflict with those presented in published reports. -
Lecture Notes on the Major Soils of the World
LECTURE NOTES ON THE GEOGRAPHY, FORMATION, PROPERTIES AND USE OF THE MAJOR SOILS OF THE WORLD P.M. Driessen & R. Dudal (Eds) in Q AGRICULTURAL KATHOLIEKE 1 UNIVERSITY UNIVERSITEIT ^.. WAGENINGEN LEUVEN \^ ivr^ - SI I 82 o ) LU- w*y*'tinge n ökSjuiOTHEEK ÎCANDBOUWUNWERSIIEI^ WAGENINGEN TABLE OF CONTENTS PREFACE INTRODUCTION The FAO-Unesco classificationo f soils 3 Diagnostichorizon s anddiagnosti cpropertie s 7 Key toMajo r SoilGrouping s 11 Correlation 14 SET 1. ORGANIC SOILS Major SoilGrouping :HISTOSOL S 19 SET 2. MINERAL SOILS CONDITIONED BYHUMA N INFLUENCES Major SoilGrouping :ANTHROSOL S 35 SET 3. MINERAL SOILS CONDITIONED BYTH E PARENT MATERIAL Major landforms involcani c regions 43 Major SoilGrouping :ANDOSOL S 47 Major landforms inregion swit h sands 55 Major SoilGrouping :ARENOSOL S 59 Major landforms insmectit eregion s 65 Major SoilGrouping :VERTISOL S 67 SET 4. MINERAL SOILS CONDITIONED BYTH E TOPOGRAPHY/PHYSIOGRAPHY Major landforms inalluvia l lowlands 83 Major SoilGroupings :FLUVISOL S 93 (with specialreferenc e toThioni c Soils) GLEYSOLS 105 Major landforms inerodin gupland s 111 Major SoilGroupings :LEPTOSOL S 115 REGOSOLS 119 SET 5. MINERAL SOILS CONDITIONED BYTHEI RLIMITE D AGE Major SoilGrouping : CAMBISOLS 125 SET 6. MINERAL SOILS CONDITIONED BYA WE T (SUB)TROPICAL CLIMATE Major landforrasi ntropica l regions 133 Major SoilGroupings :PLINTHOSOL S 139 FERRALSOLS 147 NITISOLS 157 ACRISOLS 161 ALISOLS 167 LIXISOLS 171 SET 7. MINERAL SOILS CONDITIONED BYA (SEMI-)AR-ID CLIMATE Major landforms inari d regions 177 Major SoilGroupings :SOLONCHAK S 181 SOLONETZ 191 GYPSISOLS 197 CALCISOLS 203 SET 8. MINERAL SOILS CONDITIONED BYA STEPPIC CLIMATE Major landforms instepp e regions 211 Major Soil Groupings:KASTANOZEM S 215 CHERNOZEMS 219 PHAEOZEMS 227 GREYZEMS 231 SET 9. -
Soils of Ceylon
SOILS OF CEYLON - ANEW APPROACH TO THE IDÊNTIfICATION AND aASSIFICATlON OF THf MOST IMPORTANT SOIL'GROUPS OF CEYLON By F. R. MOORMAKN and C R. PANÄBOKKt Land use Division Hfeiation of tt>6' Department of Agriculture NATIONS CEYLON •s 1961 PRINTED AT TH8 «OVRRNlf ENT PRESS, CBÏLON, ON PAPER MANUPACTÜBBD AT THB BA9TBRN PÄPRR MItXS CORPORATION, VALAICHOHBNAI. CBÏLON, - SOILS OF CEYLON A NEW APPROACH TO THE IDENTIFICATION AND CLASSIFICATION OF THE MOST IMPORTANT SOIL GROUPS OF CEYLON By Dr. F. R. MOORMANN F.A.O. Soil Classification Consultant and Dr. C. R. PANABOKKE Head, Land Use Division, Department of Agriculture, Ceylon Scanned from original by ISRIC - World Soil Information, as ICSI) j World Data Centre for Soils. The purpose is to make a safe depository for endangered documents and to make the accrued j information available for consultation, following Fair Use J Guidelines. Every effort is taken to respect Copyright of the ] materials within the archives where the identification of the i Copyright holder is clear and, where feasible, to contact the { originators. For questions please contact [email protected] indicating the item reference number concerned. j 2 It 2251—150 (4/82) SISH CONTENTS Pag& Foreword 4 CHAPTER I Introduction CHAPTER II Great Soil Groups of Ceylon 7 1. Reddish Brown Earths & 2. Noncalcic Brown Soils 11 3. Reddish Brown Lateritie 8oils ia 4. Red-Yellow Podzolic Soils . 16 5. Red-Yellow Latosols 21 6. Immature Brown Loams 24: 7. Rendzina Soils 2ft 8. Grumusols .. .27 9. Solodized Solonetz 29> '10. Low-Humic Gley Soils 31 11. Meadow Podzolic Soils 32" 12.