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Development of Soil Information System and Its Application in Korea
S. Young Hong, Yong Seon Zhang, Yi Hyun Kim, Kang Ho Jung,
Ye Jin Lee, Eunyoung Choe, Sang Keun Ha, Yeon Kyu Sonn,
Byung Keun Hyun, Myung Suk Kim, Seung Oh Hur, Kwan Cheol Song,
Goo Bok Jung, Gun Yeob Kim, and Ki Yeol Jung
National Academy of Agricultural Science (NAAS),
Rural Development Administration (RDA)
150 Suinro, Gweonsun-gu, Suwon 441-707, Korea, 2010-04-19

Abstract

An internet-based Soil Information System (SIS) was developed based on the results of all the soil survey projects and related activities carried out by the Rural Development Administration (RDA) in about 40 years of managing soil resources in Korea. Korea's soil information system provides web-based fertilizer prescription program that recommends the amount and type of fertilizer, and the timing of fertilizer application for optimum plant growth based on soil nutrition diagnosis in the soil. It also contains soil theme maps and crop suitability maps; soil statistics for selected soil themes; a textual information about Korean soils; and soil information for kids. The Agro-environmental Resources Information System has also been developed at the NAAS-RDA. It contains spatial database on natural resources, 3-D soil maps, an image database, statistics, and cyber forum. Among the applications of the soil information are: digital soil mapping of soil carbon storage and water capacity; mapping of hydrologic soil groups; mapping of soil erosion in Gyeongbuk Province; and soil fertility mapping of Korea. Future research direction is towards pedometrics or the application of mathematical and statistical method for the study of soil genesis and distribution. This will be useful for soil mapping and prediction of soil and environment properties. Remote Sensing and Geographic Information System will continue to play important roles in spatial and temporal assessment of agricultural environment. Key words: soil information system, soils, agro-environmental resources, remote sensing, digital soil mapping, Korea

Key words: soil information system, soils, agro-environmental resources, remote sensing, digital soil mapping, Korea

Introduction

Soil map delineates the boundaries of different kinds of soils whose characteristics are markedly different due to the various factors affecting soil formation. These factors include climate, parent material, topography, vegetation, and length of time for the soil formation. Detailed knowledge of soil characteristics is important in soil resources use and conservation.

The importance of soils as the basis of Korean farming was recognized long ago. A book titled "Nong-Sa-Jik-Seol"(Instruction for Agriculture) was published in 1429 during the reign of Great King Sejong. The quality of soils was mentioned in detail, touching upon how and when to plow the lands, how to improve the fertility of barren soils, and even how to test the quality of soil by tasting it. Many books about agriculture were published during the Choson Dynasty, following the example of "Nong-Sa-Jik-Seol."

The first modern soil survey was initiated in 1964, when the Korean Government and UNDP/FAO of the United Nations jointly established the Korea Soil Survey Organization Plant Environment Research Institute (now National Academy of Agricultural Science, NAAS) under the Office of Rural Development (now Rural Development Administration, RDA) in Suwon. Since then, soil survey has made substantial progress that leads to understanding spatial soil distribution, recommending fertilizer prescription, land suitability for crop cultivation, and rationally managing soils in agricultural lands.

All the soil maps surveyed and made in RDA were computerized to make digital soil maps. An Internet-based soil information system was developed based on the results of all the Soil Survey Projects carried out by RDA in about 40 years of managing soil resources rationally and providing soil information to the public promptly.

This paper introduces and explains agro-environmental inventory in Korea focusing on soils database, soil information system, and its application and future direction for natural resources management.

Agro-Environmental Inventory in Korea

Agro-environmental inventory can be defined as `an integration of data and value-added information on natural resources to assess agricultural and environmental sustainability. Agro-environmental resources include soils, land surface, water, crops, microbes, vegetation, management practice, and climate. Agro-environmental resources and soil properties are important for land management, plant production, and environment and ecosystem management. Land quality, soil quality, water quality, land use intensity, agro-diversity, and greenhouse gas emission are important factors indicating the static and dynamic condition of the agro-environment.

Agro-environmental indicator (AEI) is defined as a measure of a key environmental condition, risk, or change resulting from agriculture, or of management practices used by producers (McRae et al. 2000). AEIs are becoming more important and are gaining international interest because of issues on environmental sustainability. Farmers, govern-ments, researchers, environmentalists, and consumers as decision makers link with each other and influence each other in ensuring a sustainable agriculture industry. For instance, farmers' management practices directly influence environmental sustainability, but agriculture policy influences decision-making activities. Information is one of the common needs of all decision makers concerned with agricultural sustainability.

Soils Database

The soil survey started with a reconnaissance survey, making use of aerial photographs purchased from USA using the Korea Soil Survey Organization fund between 1964 and 1967 (when the reconnaissance soil survey was carried out). As a result, 1:250,000 and 1:50,000 scales of soil maps of Korea were published. The detailed soil survey was followed thereafter adopting the Soil Taxonomy of the United States Department of Agriculture (USDA) between 1968 and 1990. Now, detailed Soil Maps (1:25,000) for the entire country are available both in hard copies and digital (digitized) soil map files. Super-Detailed Digital Soil Maps (1:5,000) for the entire country will be provided to the public on-line and will be published soon ( Fig. 1(1088)).

During a field study, morphological and physical characteristics of soil such as parent material, soil texture, topography, soil drainage classes, gravel content, slope, effective soil depth, and erosion rates are often used to determine the series, order, and age of soil. Topography, soil drainage classes, soil texture, effective soil depth, and gravel content not only play important roles in determining soil series, but along with vegetation and climate are significant and fundamental factors for both understanding the formation of soils and analyzing the characteristics of farmland.

Based on National Soil Survey Projects, two big soil databases were established. One is the spatial database of soil map in a variety of scales (1:250,000, 1:50,000, 1:25,000, and 1:5,000) established between 1998 and 2005. Table 1(1246) summarizes soil survey methods at each scale and its application. All the soil maps were digitized and made into a GIS file format.

The other is parcel-based soil fertility (chemical properties) database by soil testing established using an oracle relational database management system. Soil testing determines both the amount of soil nutrients essential for plant growth and the existence of any harmful ingredients in the soil. It can be used to make recommendation on the amount and type of fertilizer, the timing and the exact location of fertilizer application for optimum plant growth. Furthermore, it can help achieve proper and effective nutrient management of crops. Improper application of fertilizer would be problematic because of the uniqueness of soils and crops. Understanding soil chemistry by measuring the exact content of chemicals in soil is the first step towards maintaining and managing environmentally sound soil.

Two big important soil databases are the solid basis of the soil information system of Korea. The purpose of the data collection and utilization, the check items, and the form of data sampled and built of the two databases are significantly different ( Table 2(1174)).

RDA is in charge of National Soil Survey Project and updating of soils information. For a soil testing project, RDA makes a plan which the Agricultural Technical Center (ATC) of each city or county carries out. RDA provides the standard of fertilization for 99 crops, checks samples for laboratory analysis, and handles the web-based operating program to print out fertilizer recommendation. Each local Agricultural Technical Center collects and analyzes soil samples for the areas. They also need to upload the analyzed soil fertility data to RDA database. Web-based fertilizer recommendation program developed in 2007 uploads soil testing data from local ATCs automatically to the RDA soil fertility database while they input the soil test data for printing out a fertilizer prescription.

Agro-Environmental Change Monitoring Database and Others

The agro-environmental change monitoring project started in 1999 under the `environment-friendly agriculture fostering law' of the Ministry of Agriculture and Forestry (now the Ministry for Food, Agriculture, Forestry and Fisheries). Data for soil physical and chemical properties, water quality, and soil microorganisms at fixed sampling points evenly distributed in the country were collected and analyzed regularly. The number of samples collected and the sampling frequency differ between sampling items. Sampling was designed to represent regions and topography in relation to soil characteristics.

NAAS is in charge of `the agro-environmental change monitoring project' and controls the quality of the data analyzed for soils and water by providing analysis methods and checks samples of each Provincial Agricultural Research and Extension Services who are implementing the sampling and laboratory analysis. Soils data from topsoil and/or subsoil were collected in paddy fields, dry fields, plastic film houses, and orchards to analyze their chemical properties including pH, organic matter, available phosphate, and exchangeable cations. Soil samples for each cropland type are collected every four years in turn in paddy fields, dry fields, plastic film houses, and orchards from 1999. The number of samples for paddy fields is about 2,000 points, dry fields about 1,600 points, plastic film houses about 1,200 points, and orchards about 1,300 points. Four hundred fifty samples of soil microbes and their biomass C were examined yearly in turn from paddy fields, dry fields, plastic film houses, and orchards using the same soil samples for soil properties ( Fig. 2(1141)).

Surface and groundwater quality of farming areas were examined and elements like T-N, T-P, NH4-N, NO3-N, CODMn/Cr and exchangeable cations were analyzed thrice and twice a year depending on the farming period and using the standard methods for water quality analysis ( Fig. 2(1141)).

Biological diversity is important in assessing agro-ecosystem and its sustainability. Vegetation and weeds in the agricultural fields were surveyed to understand the spatial distribution, appearance frequency, and dominance of plant species. Spatial database for synoptic meteorological data observed from 57 weather stations of the Korea Meteorological Administration (KMA) were established as well ( Fig. 3(1121)).

NAAS started to make these data spatially referenced using the parcel information on the sampling sites for soil physical and chemical properties, water quality, and soil microbes to monitor spatial distribution and temporal changes for the resources of the country in 2007 as shown in Fig. 2(1141) and Fig. 3(1121).

Information System Development

Information systems are the software and hardware systems that support data-intensive applications. A geographic information system (GIS) is used to integrate, store, edit, analyze, share, and display georeferenced information. GIS plays essential roles in integrating a variety of data layers to express a real world. The usefulness of an information system will depend on its ability to provide decision makers with the right data at the right time in the proper manner.

Internet-based soil information system of Korea was developed to provide soils information for the public in 2006 _ anybody, anywhere, and anytime _ since the super detailed soil map (1:5,000) and soil testing data started to be computerized from 1998. The development of the National Agro-environmental Resources Information System (NARIS) has just started.

Soil Information System

A digital soil database based on paper soil maps made in Korea over a period of more than 40-years and at different scales _ 1:250,000, 1:50,000, 1:25,000, and 1:5,000 _ was established to provide valuable soil information over the whole country. RDA made a soil information system (http://asis.rda.go.kr) of Korea based on super detailed soil map (1:5,000) and opened `all about soils' information to the public through the web as shown in Fig. 4(1288). It is an Internet system to show soil theme maps for suitable crops and recommend the amount of fertilizer.

Korean soils web site consists of five main parts, which are digital soil map services such as: 1) soil theme maps and crop suitability maps; 2) fertilizer recommendation; 3) soil statistics for selected soil themes; 4) Korean soils; and 5) `soil love' for kids. Soil attributes shown graphically in the digital maps are 79 items which are soil texture, gravel content, drainage, available soil depth, slope, topography, parent material, land use at the time of soil survey, soil suitability group for paddy, upland, and orchard, soil classification regimes, and the like ( Table 3(1233)). Each soil property can be provided in a form of map, showing its spatial distribution with statistics such as sum and average of the attributes.

Soil map-based attributes provided at the web site are morphological, physical, land use, soil classification, crop and soil suitability ( Fig. 5(1315)). Parcel information which is aspatial database provided by Ministry of Land, Transport, and Marine Affairs was used to link the soil testing database to express the parcel-based soil fertility map using the parcel information as a relational key in the web site ( Fig. 6(1135)).

Soil testing determines both the amount of soil nutrients essential for plant growth and the existence of any harmful ingredients in the soil. It can be used to make a recommendation for the amount and type of fertilizer and the timing and exact location of fertilizer application for optimum plant growth. Furthermore, it can help achieve proper and effective nutrient management of crops. Improper application of fertilizer becomes a problem because of the uniqueness of soils and crops. Understanding soil chemistry by measuring the exact content of chemicals in soil is the first step towards maintaining and managing environmentally sound soil. Soil testing reveals the chemical properties of soil such as pH, soil organic matter, available phosphoric acid, available silicic acid, and exchangeable cations.

The soil information system of Korea (http://asis.rda.go.kr) provides web-based fertilizer prescription program that recommens the amount and type of fertilizer, and the timing of fertilizer application for optimum plant growth based on soil nutrition diagnosis in the crop land ( Fig. 7(1109)). A person in charge of soil testing and diagnosis at ATC has his or her own ID and password to access the system to use the data and functions of program provided by the system. The Program provides fertilization standards for 99 crops and issues fertilizer and management prescription. Soil test data are automatically uploaded to the oracle database located at NAAS when one inputs the soils data and saves them for the program operation.

For the web-based fertilizer prescription program, parcel (Korean Land Information System, KLIS) provided by Ministry of Land, Transportation, and Marine Affairs and farming land information provided by Ministry for Food, Agriculture, Forestry and Fisheries to offer parcel-based soil fertility map and fertilizer prescription for farming.

The statistics of soil attributes queried on the web can be calculated for representative areas in the form of pie charts, bar charts, and tables ( Fig. 8(1262)). Soil information that can be queried for statistics are all 62 attributes including soil morphological, physical, and chemical properties.

Also, the system provides text information on Korean soils. Soil is a mixture of mineral particles and organic matter of varying size and composition. The particles make up about 50% of the soil's volume. The proportions of sand, silt, and clay in a soil determine its texture. Soil is not a constant entity by itself but in dynamic equilibrium with its environment. The zone at the soil surface, called the pedosphere, is the envelope of the Earth where soils occur and where soil-forming processes are active. Most soils take a long time to form. Soils are formed from various parent materials under different environmental conditions. Their characteristics are very different, depending on the combination of soil forming factors. Factors of soil formation include: climate, biota, source materials, slope, and time. The influence of these factors is interdependent and, in fact, they exert a combined but by no means equal control on soil formation. Three hundred ninety soil series were recognizable in Korea as of 2007. Fig. 8(1262) also shows soil types of paddy fields and dry fields in Korea.

Development of Agro-Environmental Resources Information System

Based on agro-environmental resources inventory, development of agro-environmental resources system just started in NAAS. The purpose of system development is the establishment of national agro-environmental resources inventory and its rational use. Web-GIS system for agro-environmental resources information will provide a spatial database on natural resources, 3-D soil maps, an image database, statistics, and cyber forum as shown in Fig. 9(1196) from early 2009.

Applications of Soil Information

Digital Soil Mapping of Soil Carbon Storage and Water Capacity

Soil carbon storage and available water capacity are important properties for land management, plant production and environment, and ecosystem management. This project tried to apply the digital soil mapping concept for mapping these two properties in South Korea. A Korean soil database was compiled, which includes chemical and physical properties such as particle size, moisture retention, organic matter, cation exchange capacity, and a limited number of bulk density data based on 380 soil series. The first step is to estimate bulk density for estimation of both C storage and available water capacity. Bulk density at different depths of soils was predicted by deriving a pedo transfer function model with sand, depth, and organic matter, based on Adams' model (1973). Organic C distribution with depth was first derived by converting from mass basis C(kg/kg) to volume basis C(kg/m3). C storage (kg/m2) was first calculated by multiplying C on the volume basis to the thickness of each soil layer (m), and finally integrated to a depth of 1 m for each soil series.

Mapping available water capacity was more challenging as only half of the database contains measurement of water retention at -33 and -1,500 kPa. Furthermore, measurement of water retention is in mass basis and based on disturbed soil samples. Pedotransfer functions were derived for volumetric water content at field capacity (-33 kPa) and wilting point (-1,500 kPa). Further adjustments based on total soil porosity are required as the field capacity values were derived from disturbed soil samples. Field capacity was calculated from clay content and predicted bulk density and adjusted by considering porosity. Wilting point was calculated from clay content and adjusted for any discrepancy with predicted field capacity and porosity. Available water capacity (mm) to a depth of 1 m was estimated by multiplying the amount of water stored between field capacity and wilting point and the thickness of the layer.

The carbon storage and available water capacity from surface to a depth of 1 m for the south part of whole Korean peninsula were mapped using the estimated parameters in a soil series map unit (1:25 000). Mean value of carbon storage of Korea is approximately 7 kg/m2 and available water capacity is approximately 138 mm as shown in Fig. 10(1178).

Mapping Hydrologic Soil Group

The soils were classified into four hydrologic soil groups (HSG) on the basis of measured infiltration and percolation rates, and pedotransfer functions for Ks (saturated hydraulic conductivity) of the representative soils (Jung et al. 2006). They are A(7.62-11.43 mm/hr), B(3.81-7.62 mm/hr), C(1.27-3.81 mm/hr), and D(0-1.27 mm/hr) groups (Mishira and Singh 2003). HSG A is faster in the infiltration and percolation rates than B, C, and D group.

HSGs by Jung et al. (1995) and Jung et al. (NIAST 2006) were mapped using the estimated infiltration rate in a soil type map (1:25,000) in Fig. 11(1120) and compared the areas by each group in Table 4(1170). The area of HSG D increased more than four times and that of the other HSG decreased by Jung et al. (NIAST 2006) in comparison with the classification of Jung et al. (1995).

Soil Erosion

Soil loss is one of the important properties for understanding environmental loads and practicing best management of land and agricultural fields. Soil erosion can be classified as natural soil erosion or accelerated erosion. Under normal climate conditions, and with natural ground cover, soil erosion can often balance out with the rate of soil production. This is called 'natural erosion', or 'geological erosion'. Natural soil erosion includes water erosion caused by rainfall and runoff of water, wind erosion, glacial erosion caused by flowing ice, stream erosion occurring during channelized water flow, coastal erosion caused by waves and tides, and erosion due to transportation. Erosion occurring at a rate that exceeds the rate of natural erosion is called accelerated erosion. Accelerated erosion can result from certain human land use practices such as surface mining, forestry, agriculture, and construction. Additional natural erosion processes, such as water erosion, are responsible for accelerated soil erosion. Soil erosion in Korea is primarily caused by rainfall. This rain-splash erosion detaches earth materials from the surface by the impact of water striking the surface and by the force of surface runoff. Wind erosion is found in coastal regions and highlands. The intensity and amount of rainfall, soil type, the length and steepness of slope determine the degree of soil erosion by rainfall.

Soil erosion of Gyeongbuk Province in Korea was mapped, basically using the Universal Soil Loss Equation (USLE), multiplying rainfall-runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management factors (C), and support practice factors (P) ( Fig. 12(1192)). Revised USLE (RUSLE) was used to calculate for K and LS factors. Rainfall and runoff erosivity factors (R) of 158 locations of cities and counties were spatially interpolated by the inverse distance weight (IDW) method. K factors and C and P factors were applied to soil map and land use/cover map, respectively, at 1:25,000 scale. Digital elevation model (30 m) was used to derive LS factors using RUSLE. A grid-based soil loss concept and model was made to map soil erosion using GIS ( Fig. 12(1192)). Soil loss is classified into seven grades in Korea and five grades in OECD. It needs to do conservation practice for the classes, which are greater than moderate grade.

Runoff Potential

"Curve number" (CN) indicates the runoff potential of an area. The US Soil Conservation Service's CN method is a simple, widely used, and efficient method for estimating the runoff from a rainfall event in a particular area, and is also used in Korea in disaster assessment. CN is based on an area's hydrologic soil group, land use, management practices, and hydrologic condition. The two former characters are of greatest importance. Spatial variability in land use, cover, and soil hydrological properties reflecting infiltration rate, at the field level during the crop growing season must be considered when runoff is being estimated. HSG information NIAST(2006) of the soil map (1:25,000) of Korea and land use/cover map(1:25,000) provided by Ministry of Environment were used to calculate CN values, with antecedent soil moisture condition II, of 30 m grid format. CN values, which are ranged from 0 (no runoff) to 100 (all precipitation runs off), of Korea were mapped (Hong et al. 2007) as shown in Fig. 13(1262).

Soil Fertility Map

Soil fertility map for the country was expressed in terms of soil pH and organic matter (OM) content for paddy and dry fields using a weighted average value of soil chemical property based on soil testing database ( Fig. 14(1200) and Fig. 15(1086)). Mean OM content of paddy field soils had a tendency to be greater than that of dry field soils. pH of paddy field soils in the mountainous areas was lower than in the rest of the soils. Dry field soils showed higher pH, in general, than paddy field soils.

The pH of soil can be an important parameter for crop growth. When a soil's pH is about neutral (6.5-7.0), availability of soil nutrients is at maximum. As soil becomes more acidic (pH<5.5), significant dissolution of manganese and iron from the soil not only impede the crop growth, but also hinder the propagation and function of useful soil microbes. The solubility of cations such as iron and zinc becomes low in the alkaline soils with a pH of greater than 8.0. As a result, crops may suffer a deficiency of these cations. The map indicates that the range of a pH of rice paddy and farmland ranges from less than a pH of 4.5 to above a pH of 6.5. According to RDA-NAAS, optimal ranges of pH for rice paddy and farmland are 5.5-6.5 and 6.0-6.5, respectively.

Soil organic matter is an important element in soil fertility. Soil organic matter contains a variety of nutrients and provides these nutrients to microbes and vegetation. Organic matter in soil enhances soil quality by increasing porosity and permeability. As a result, a soil with abundant organic matter provides the favorable environment for soil microbes to thrive. Soil organic matter content in rice paddy and farmland ranges from below 10g/kg to above 50g/kg. According to RDA-NAAS, the optimal ranges of soil organic matter for rice paddy and farmland are 25-30g/kg and 20-30g/kg, respectively.

Other Uses

Soil information requested from other agencies, universities, and private corporations varies according to the purpose of use. The information includes soil classification, soil texture, soil depth, drainage class, gravel content, parent materials, and other properties as shown in Fig. 16(1262). The purpose of soil data use also varies from environment assessment to water modeling as input parameters or initial condition.

Understanding and assessing ecosystem and environment using a GIS-based information system is in high demand because it is very helpful in decision making activities of farmers, government, researchers, and consumers.

Future Direction

Pedometrics and Digital Soil Mapping

"Pedometrics (PM)," a term coined by A.B. McBratney, is a neologism, which stems from two Greek words pedos (meaning soil) and metron (meaning measurement). It is formed and used analogously to other applied statistical fields such as biometrics, psychometrics, econometrics etc. (www.pedometrics.org). In that sense, pedometrics is "the application of mathematical and statistical methods for the study of the distribution and genesis of soils." Pedometrics can be considered as an interdisciplinary science in between soil science, geoinformation science, and statistics ( Fig. 17(1016)).

The development of PM can also be considered as a result of new technological discoveries and improvements, specifically in remote and close-range sensing techniques and computers in general. PM is a growing field of Science compared to other Soil Science sub-disciplines and subjects. Because of this, PM has been promoted from a working group to a Commission under the IUSS. The most recent topics covered by PM include analysis and modeling of spatial and temporal variation of soil properties, error propagation, multiscale data integration, use of wavelets transforms to analyze complex variation, soil-landscape modeling using digital terrain analysis, quantitative soil classification algorithms, quantification of uncertainty and fuzziness of information and evaluation criteria, soil genesis simulation, soil pattern analysis, design and evaluation of sampling schemes, incorporation of exhaustively sampled information (remote sensing) in spatial interpolation, precision agriculture applications.

Conventional soil survey methods are relatively slow and expensive. Furthermore, there is a worldwide crisis in collecting new field data in general. This leads some to bevery pessimistic about future developments in conventional soil surveying. To face this situation, people think that the current Spatial Soil Information Systems have to extend their functionalities from the storage and the use of digitized (existing) soil maps to the production of soil maps from the beginning. This is precisely the aim of digital soil mapping, which can be defined as the creation and the population of a geographically referenced soil databases generated at a given resolution by using field and laboratory observation methods coupled with environmental data through quantitative relationships (http://www. digitalsoilmapping.org) as shown in Fig. 18(1176).

Accurate, up-to-date and spatially referenced soil information is necessary. The modelling community, land users, and policy and decision makers have expressed this need. Also, this need coincides with an enormous leap in technologies that allow for accurately collecting and predicting soil properties (http://www.globalsoilmap.net). Accordingly, there is a global need for making a new digital soil map of the world using state-of-the-art and emerging technologies for soil mapping and predicting soil properties at fine resolution. This new global soil map will be supplemented by interpretation and functionality options that aim to assist better decisions in a range of global issues like food production and hunger eradication, climate change, and environmental degradation.

Remote Sensing and Gis

To provide AEIs (Agri-environmental indicators) as a form of map for different users, RS and GIS play essential roles in spatial and temporal assessment of agricultural environment with various spatial scales. RS technologies are used to detect and quantify various field conditions including crops, soils, water, and climate for immediate and future management decision. Functional relations have been developed between remote spectral and microwave observations and crop and soil properties in various spatial scales (Hong et al. 1997, Hong et al. 2001). Remote sensing which uses the electromagnetic spectrum is an efficient way to obtain soil information and to detect spatial variability of soils. The recent convergence of technological advances in GIS, global positioning systems (GPS), and automatic control of farm machinery have provided an ideal framework for utilizing RS for farm management.

Conclusions

Agro-environmental inventory based on soils database and agro-environmental change monitoring database was explained in terms of survey history, data types collected and established, and spatial and temporal scope for sampling. The Internet-based soil information system of Korea was developed in 2006. It consists of five digital soil map services on: 1) soil theme maps and crop suitability maps; 2) fertilizer recommendation; 3) soil statistics for selected soil themes; 4) Korean soils; and 5) `soil love' for kids. Based on agro-environmental resources inventory, development of agro- environmental resources system also just started in NAAS for the establishment of national agro- environmental resources inventory and its rational use. The Soil Information System of Korea will need an English version for global networking.

Future research directions include d use of pedometrics concept for soil mapping and predicting soil and environment properties and remote sensing for the estimation of soil properties. These are emerging technologies , which can be used, in digital mapping and in multi-scale analysis and modeling.

Acknowledgment

We thank RDA for the financial support and assistance to this project. We also thank all those who helped in various aspects of the project.

References

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  • Ha, S.K., K.H. Jung, and M.S. Kim. 2007. A study on mapping of soil fertility and soil erosion in Korea, RDA Project Report (2007), RDA
  • Hong, S.Y., J.T. Lee, S.K. Rim, and J.S. Shin. 1997. Radiometric estimates of grain yields related to crop aboveground net production (ANP) in paddy rice. p. 1793-1795. In: Proc. IGARSS, Singapore, August 3-7, 1997.
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  • Hong, S.Y., C.U. Choi, K.H. Jung, M.W. Jang, Y.H. Kim, S.K. Ha. 2007a. Using detailed soil maps (1:5,000) to estimate SCS runoff curve number in a small watershed. In, Proc. CD. Annual meeting of Korea Water Resources Association, May 17~18, 2007
  • Hong, S.Y., K.H. Jung, Y.H. Kim, S.O Hur, and S.K. Ha. 2007b. Development of runoff estimation in a watershed using remote sensing and GIS, NIAST Project Report (2007), RDA
  • Jung, K.H., S.J. Jung, Y.K. Sonn, and S.Y. Hong. 2006. Classification of hydrologic soil group for applying curve number estimation, NIAST Project Report (2006), RDA
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  • URL: Soil Information System of Korea, Available at: http://asis.rda.go.kr

Index of Images

Figure 1 History of Soil Survey and Database Established in Korea (Niast 1999).

Figure 1 History of Soil Survey and Database Established in Korea (Niast 1999).

Figure 2 Sampling Sites for Agro-Environmental Change Monitoring.

Figure 2 Sampling Sites for Agro-Environmental Change Monitoring.

Figure 3 Sampling Sites for Vegetation and Climate Resources.

Figure 3 Sampling Sites for Vegetation and Climate Resources.

Figure 4 An Overview of the Korean Soil Information System (HTTP://Asis.Rda.Go.KR).

Figure 4 An Overview of the Korean Soil Information System ( HTTP(794)).://Asis.Rda.Go.KR

Figure 5 Soil Map-Based Attributes Provided at the Website.

Figure 5 Soil Map-Based Attributes Provided at the Website.

Figure 6 Parcel-Based Soil Chemical Properties Provided at the Web-Site.

Figure 6 Parcel-Based Soil Chemical Properties Provided at the Web-Site.

Figure 7 Web-Based Ferilizer Prescription Program from Data Input to Fertilizer Recommendation.

Figure 7 Web-Based Ferilizer Prescription Program from Data Input to Fertilizer Recommendation.

Figure 8 Soil Statistics in the Form of Pie Charts, Bar Charts, and Tables (a) and Korean Soils (B).

Figure 8 Soil Statistics in the Form of Pie Charts, Bar Charts, and Tables (a) and Korean Soils (B).

Figure 9 Main Page of Agro-Environmental Resources Information System.

Figure 9 Main Page of Agro-Environmental Resources Information System.

Figure 10 Soil Carbon Storage and Available Water Capacity Map

Figure 10 Soil Carbon Storage and Available Water Capacity Map

Figure 11 Distribution of Hydrologic Soil Groups Based on Soil Map (1:25,000) of Korea.

Figure 11 Distribution of Hydrologic Soil Groups Based on Soil Map (1:25,000) of Korea.

Figure 12 A Gis Model for Soil Loss (a) and Soil Erosion Map of Gyeongbuk Province (B) (Ha Et Al. 2007).

Figure 12 A Gis Model for Soil Loss (a) and Soil Erosion Map of Gyeongbuk Province (B) (Ha Et Al. 2007).

Figure 13 Curve Number Distribution of Korea.

Figure 13 Curve Number Distribution of Korea.

Figure 14 The Acidity Map of Rice Paddies and DRY Farmland in Korea.

Figure 14 The Acidity Map of Rice Paddies and DRY Farmland in Korea.

Figure 15 The Organic Matter Map of Rice Paddies and DRY Farmland in Korea.

Figure 15 The Organic Matter Map of Rice Paddies and DRY Farmland in Korea.

Figure 16 Soil Properties of Korea Based on Detailed Soil Map (1:25,000).

Figure 16 Soil Properties of Korea Based on Detailed Soil Map (1:25,000).

Figure 17 Concept and Scope of Pedometrics.

Figure 17 Concept and Scope of Pedometrics.

Figure 18 Principles of Digital Soil Mapping (Minasny 2008).<BR>

Figure 18 Principles of Digital Soil Mapping (Minasny 2008).

Table 1 Soil Survey Methods at Each Scale and Its Application (Niast 1999)

Table 1 Soil Survey Methods at Each Scale and Its Application (Niast 1999)

Table 2 Characteristics of Databases for Soil Map and Soil Fertility Data

Table 2 Characteristics of Databases for Soil Map and Soil Fertility Data

Table 3 Soil Theme Map and Its Attributes Shown through the Information System

Table 3 Soil Theme Map and Its Attributes Shown through the Information System

Table 4 Areas of Hydrologic Soil Groups by Classification Method in Soil Map (1:25,000)

Table 4 Areas of Hydrologic Soil Groups by Classification Method in Soil Map (1:25,000)

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