Waterlogging susceptibility describes the degree and duration of impact to soils, and hence plants, arising from poor drainage. Mapping indicates the most severely waterlogged areas (provided they occupy at least 30% of a map unit), while detailed proportion data are supplied for calculating respective areas of each waterlogging susceptibility class (spatial data statistics).

Susceptibility to flooding imposes a serious limitation on land especially where infrastructure is required. Mapping shows the proportion of land susceptible to flooding, while detailed proportion data are supplied for calculating total areas of susceptible land (spatial data statistics).

우리나라의 토양을 405개(토양통)로 구분하고 각 토양의 특성정보를 제공합니다.* 토양특성 : 토색, 토성, 경사, 침식 정도, 토심, 자갈함량, 반층의 유무, 토양배수등급, 모암, 토양반응 등

토양특성 통계정보란 지역별로 토양의 형태적, 물리적, 화학적 특성을 수치와 면적 단위로 정리한 데이터로, 작물 재배나 토지 이용에 적합한 토양 관리 및 의사결정에 활용됩니다. *토양 형태적 특성: 토양의 색(토색), 구성 입자(토성), 토층의 깊이(토심), 자갈 포함 정도(자갈함량), 경사, 침식 정도, 반층의 유무, 토양 구조 및 생성 모암 등 물리적‧외관적 특성을 포함합니다. *배수, 이용 등급: 토양의 배수 등급(배수양호, 불량 등), 유효 토심, 작물별 적합성 등급, 토지 이용 추천 정보가 포함되어 있습니다. *통계자료 형식: 통계는 시도/시군구/읍면동별로 제공돼 지역 단위별 토양면적, 색깔 분포, 물리‧화학성 항목별 수치 및 분포 면적(ha 단위)로 정리됩니다. 예를 들어, ‘진갈색토 507ha, 황갈색토 200ha, 회갈색토 341ha’처럼 구분됩니다. *활용 분야: 농업에서는 작물별 토양 적성도 평가, 비료 사용 처방, 토지 평가에 이용되며, 환경 분야에서는 침식 등 토양환경 관리에 사용됩니다. 이 통계정보는 각 지역의 토양 특성을 종합적으로 파악할 수 있도록 설계되어, 농업 생산성 확보와 토양 환경 보전에 중요한 자료로 활용됩니다.

Non-watertable salinity (or dry saline land) is where soil contains elevated levels of soluble salts that are not associated with a watertable. Mapping shows the degree of non-watertable salinity, based on the most saline part of the map unit (provided it occupies at least 30%), while detailed proportion data are supplied for calculating respective areas of each non-watertable salinity class (spatial data statistics).

The data set consists of a subset of the ISRIC-WISE global data set of derived soil properties for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 to 30 degrees W, latitude 25 degrees S to 10 degrees N).The World Inventory of Soil Emission Potentials (WISE) database currently contains data for over 4300 soil profiles collected mostly between 1950 and 1995. This database has been used to generate a series of uniform data sets of derived soil properties for each of the 106 soil units considered in the Soil Map of the World (FAO-UNESCO, 1974). These data sets were then linked to a 1/2 degree longitude by 1/2 degree latitude version of the edited and digital Soil Map of the World (FAO, 1995) to generate GIS raster image files for the following variables:Total available water capacity (mm water per 1 m soil depth)Soil organic carbon density (kg C/m**2 for 0-30 cm depth range)Soil organic carbon density (kg C/m**2 for 0-100 cm depth range)Soil carbonate carbon density (kg C/m**2 for 0-100 cm depth range)Soil pH (0-30 cm depth range)Soil pH (30-100 cm depth range)LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. LBA was a cooperative international research initiative led by Brazil and NASA was a lead sponsor for several experiments. More information about LBA and links to other LBA project sites can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.

This data set is a subset of a global vegetation and soils data set by Wilson and Henderson-Sellers (1985a). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10° N to 25° S, 30° to 85° W). The data are in ASCII GRID format.The original global data set (Wilson and Henderson-Sellers 1985a) is an archive of soil type and land cover data derived for use in general circulation models (GCMs). The data were collated from maps depicting natural vegetation, forestry, agriculture, land use, and soil, and they were archived at a resolution of 1° latitude by 1° longitude. The data set indicates soil type, soil data reliability, primary vegetation, secondary vegetation, and land cover data reliability. Approximately 50 land cover classifications are used, including categories for agricultural and urban uses. The inclusion of secondary vegetation type is particularly useful in areas with cover types that may have a fragmented distribution, such as in areas of urban development. The soil type data are classified according to climatically important properties for GCMs, and they indicate color (light, medium, or dark), texture, and drainage quality of the soil. The land cover data are compatible with the soils data, forming a coherent and consistent data set. The reliability of the land cover data is ranked on a scale of 1 to 5 (high to low). The reliability of the soil data is ranked as high, good, moderate, fair, or poor.Recommendations for the use of these data, as well as more detailed information can be found in Wilson and Henderson-Sellers (1985b).Further data set information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/wilhend/comp/wilhend_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.

전국의 토양시료를 채취 하고 분석 결과를 바탕으로 각 필지별로 작물재배에 필요한 적정 비료량 데이터 제공* 토양분석 (화학적 특성파악) : pH, 유기물, 질소, 인산, 칼륨, 마그네슘, 전기전도도, 규산 등