Ways to Create Classifications of Soils and Land Resources

This paper reviews the use of Water Resources carrying capacity concept to control environmental sustainability with the particular note for the case in Indonesia. Carrying capacity is a capability measure of an environment or an area to support human and the other lives as well as their activities in a sustainable manner. Recurrently water-related hazards and environmental problems indicate that the environments are exploited over its carrying capacity. Environmental carrying capacity (ECC) assessment includes Land and Water Carrying Capacity analysis of an area, suggested to always refer to the dimension of the related watershed as an incorporated hydrologic unit on the basis of resources availability estimation. Many countries use this measure to forecast the future sustainability of regional development based on water availability. Direct water Resource Carrying Capacity (WRCC) assessment involves population number determination together with their activities could be supported by available water, whereas indirect WRCC assessment comprises the analysis of supply-demand balance status of water. Water resource limits primarily environmental carrying capacity rather than the land resource since land capability constraints are easier. WRCC is a crucial factor known to control land and water resource utilization, particularly in a growing densely populated area. Even though capability of water resources is relatively perpetual, the utilization pattern of these resources may change by socio-economic and cultural technology level of the users, because of which WRCC should be evaluated periodically to maintain usage sustainability of water resource and environment.

A study was conducted to determine land capability and to develop suitability map based on soil characteristics and climatic factors of watershed area. Detailed soil survey was carried out for Donur-2 micro watershed which comes under Basavana Bagewadi taluka of Vijayapura district, Karnataka to acquire the comprehensive data related land resources. From the study area, it was observed that based on soil-site characteristics four soil series were identified such as Dadamatti, Karjol, Nidoni and Rampur series and mapped into eight mapping units using GIS techniques. Donur-2 watershed area has been grouped into three land capability classes (LCC) viz., II, III and IV with four subclasses IIes, IIIs, IIIse and IVe. Subclass ‘e’ is due to major limitation of soil property group ‘e’ i.e erosion and slope, subclass ‘s’ is due to major limitations group ‘s’ having parameters like texture, depth and gravelliness. Subclass ‘se’ and ‘es’ are due to limitations of both soil parameters group above mentioned, however se and es are different classes which are based major limitation one of the group and followed by other group. Land capability map was developed using GIS techniques which indicates that out of 324.3 ha study area, LCC class IIIs covering major area i.e. 179 ha (55.12%), followed by class IIs i.e. 109 ha (33.51%), class IVe i.e. 23 ha (7.15%) and minor area of 7 ha (2.15%) area is covered by class IIIse. Soil suitability assessment indicates that majority of land is moderately suitable for agriculture. Class III soils are designated as moderately fertile agricultural land with significant constraints. However, with special conservation practices soils under class III can be used for cultivation of different crops. Class IV soils are categorized as reasonably fertile for intermittent cultivation, characterized by significant restrictions that limit crop options but with careful management practices these can be used for cultivation of arable crops. Therefore, the utilization of a land use planning approach (LUP) is instrumental in formulating tailored land resource management strategies to enhance land productivity, mitigate land degradation and attain sustainability goals.

New demands on our land resources require more stringent controls and management practices. The administration of these controls requires better and more frequent information concerning land use. Although new tools became available to aid in acquiring and processing the data, a major lack in uniform techniques for isJ-entifying the land use was a major problem. Creation of a more standard form of classification of land use, based on the capabilities inherent in the various forms of remote sensors and other data sources was a necessary step. classification has been created, and published in preliminary form, by the Geological Survey of the United States Department of Interior. It is presented as Geological Survey 671, entitled A Land Use Classification System for Use With RemoteSensor Data. This paper discusses the origin, development, and controlling influences of that classification system. The desire for information about land use is not a new phenanenon. In fact, the concept of the Cadastral Survey dates back to early mideastern settlement and includes information about land use as a major part of the Cadastral Survey. Land use and land capability were associated, even then, in developing a sound basis on which to establish taxation policies. What is new is the fact that we, in this country, and several others have used land lavishly, and are now faced with difficult decisions that require more information than we now have readily available. The pressure on our land resources stems from a number of sources, but includes at the top of the list increased population and an economic syst.en that provides the highest profit to those who exploit our best resources first. Other new things relevant to the probIen include an awareness at many levels of goverrment of a need for a new approach to management of the land resource. Attempts at the local level to control land use through zoning have been less than effective in most areas. But there is a genuine reluctance in all parts of the country to undertake regulated zoning at the higher levels of government. This is due to the historical precedent of giving zoning powers to the local government units. Some notable exceptions are just now starting their long struggle for validation through the court systxms . Examples include the new concept of state agencies with New York State's Adirondack Agency and the Coastal Zone legislation now operative in New Jersey, some of the New England states, and along parts of the eastern seaboard. Others are the Agricultural Districts legislation of New York State, permitting land owners to create their own areas of land use control, and in some states such as Vermont statewide legislation is being used as a source of land use control. All of these examples have at least two things in crnmon. First, they seek to control and guide the development and use of the land resource. Second, they need, in fact require, a great volume of information about land use to meet their objectives. Two new fields of scieqce, apparently completely unrelated to the above situations, now provide opportunities to gain the information needed in solving our land use problems. They are

Remote sensing and geographic information system (GIS) have emerged as the most effective tools in generating up-to-date, reliable information on soil and land resources of large regions in a cost-effective and time-efficient manner. Advances in spatial, spectral, and radiometric resolutions of the remote sensing sensors are providing a wide opportunity to the user to characterize soil and land resources. Multispectral broadband remote sensing data have been used for mapping soil types/classes, whereas hyperspectral remote sensing data have been used in quantifying surface soil properties showing their potential application in soil health monitoring. Soil and terrain parameters derived from remote sensing or soil proxies can be used as secondary variables to improve the interpolation of existing soil data and in deriving digital soil map. Availability of temporal remote sensing data in various spatial and spectral resolutions has provided edge in characterizing, mapping, and monitoring of degraded lands. Several web resources have provided various thematic information of soil, land use/land cover, vegetation/forest cover, geomorphology, hydro-geomorphology, geology, terrain, groundwater level, drainage network, watershed boundary, climate, etc. at various scales. Land evaluation methods like land capability classification, parametric methods of land evaluation, FAO framework of land evaluation, agroclimatic suitability, soil quality index, etc. are commonly used to assess the potential of land employing biophysical information. Recent advances in remote sensing technology provide enormous opportunity to resource managers to monitor the state of land degradation as well as to assess the potential of land resources to ascertain their optimal use in insuring food security.

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.

The land resources of Bareli watershed in Seoni district of Madhya Pradesh were characterized, classified and evaluated using IRS-LISS-IV and LISS-III data and GIS. Five major landforms viz. plateau, escarpement, isolated mound, hills and ridges and pediment were identified and delineated. Based on image characteristics, five major land use/land cover viz. forest, cultivated land, wasteland, habitation and water bodies were identified. Five slope classes viz., very gently sloping (1–3%), gently sloping (35%), moderately sloping (5–10%), strongly sloping (10–15%) and moderately step to steep sloping (1515%) lands have been identified using Cartosat-1 DEM (30 m resolution) and topographic information. Five soil series (Diwartola, Diwara, Bareli-1, Bareli-2 and Bareli-3) were tentatively identified and mapped as mono series on 1: 10000 scale based on landform-soil relationship. Soils are shallow, clayey, well drained and severely eroded at upper elevations, whereas, they are moderately deep, clayey, moderately well drained with moderate erosion at lower elevations. The soils are, in general, clayey, neutral in reaction, non-saline and non-calcareous and qualify for Lithic Haplustepts/Lithic Ustorthents/Vertic Haplustepts/Typic Ustorthents at subgroup level. The soils were grouped under land capability sub classes IVs and IVst and 2st, 3s, 3st and 4st land irrigability sub-classes. The soils of Diwartola are moderately suitable for growing sorghum and marginally suitable for growing cotton, pigeonpea, maize and rice and not suitable for growing soybean. The soils of Diwara and Bareli-2 are marginally suitable for sorghum and not suitable for growing cotton, pigeonpea, soybean, maize and rice. The soils of Bareli-1 and Bareli-3 are moderately suitable for growing sorghum and marginally suitable for growing cotton, pigeonpea, soybean, maize and rice. Suitable land use interventions and soil and water conservation measures have been suggested for better management of land resources in the watershed.

Poor knowledge on location specific data, mostly on soils, and of situation-specific recommendations has been the causes of failure for most of the agricultural related development schemes that operated in the country in the past. The land resource inventory (LRI) may be filled these gaps by generating data on location specific soil and other land resources. LRI involves systematic surveys of soils on 1:10,000 scale for land use planning scientifically in the GIS platform. The present work was undertaken in Kadwa block, Katihar district in northeastern Bihar, India. Four major landforms like old alluvial plains (9.12%), young alluvial plains (24.46%), meander plains (39.48%) and flood plains (4.61%) were identified after visual interpretation of Indian Remote Sensing Satellite (IRS) R2-LISS-IV data in conjunction with cadastral map. The detailed soil survey was carried out and eight soil series viz. Chauni, Sitalpur, Kumaripur, Asiani, Kaliganj, Sikarpur, Dangi and Mahinagar were identified in different landforms and mapped into 14 soil mapping units (phases of series). Soils developed on meander plains are very deep, moderately well drained, brown to gray, loam to silt loam texture with reddish brown mottles and classified as Coarse-loamy, mixed hyperthermic Fluventic Endoaquepts (Kumaripur series), Coarse-loamy, mixed, hyperthermic Aquic Haplustepts (Asiani series) and Fine-loamy, mixed, hyperthermic Aeric Endoaquepts (Kaliganj series). Young alluvial plains soils are very deep, well to somewhat poorly drained, yellowish brown to dark gray, silt loam in texture with brown mottles and classified as Coarse-loamy, mixed, hyperthermic Typic Ustifluvents (Sikarpur series) and Fine-loamy, mixed, hyperthermic Typic Haplustepts (Dangi series). Soils developed on old alluvial plains are very deep, moderately well drained, light brownish gray to dark gray, silt loam to clay loam in texture dark brown mottles and classified as Coarse-loamy, mixed, hyperthermic Typic Haplustepts (Chauni series) and Fine-loamy, mixed, hyperthermic Typic Endoaquepts (Sitalpur series). Flood plains soil are very deep, well drained, light yellowish brown to brown, silt loam surface texture, severe erosion and very frequent flooding and classified as mixed, hyperthermic Typic Ustipsamments (Mahinagar series). Surface soils of the block were grouped into eight soil reaction classes. It was observed that very strongly acid to moderately acidic soils are occupying 50.84% and neutral soils 7.53% of total geographical area (TGA). Organic carbon status (medium to high) occupied 64.10% and available phosphorus is low in 45.82% of TGA. Based on interpretation of soil survey data, the study area is divided into three land capability classes viz. II, III and IV. The results on suitability indicates that crops grown in the study area are moderate to marginally suitable due to coarse texture, fertility and ponding of water for long period limitations. Considering the major problems and potentials four land management units (LMUs) were identified and suggested alternate land use for each LMU of the study area. KeywordsLand resource inventoryRemote sensingGISMappingLand evaluationCrop suitabilitySustainable land use options

The Soil Vulnerability Index (SVI) was developed by the USDA Natural Resources Conservation Service (NRCS) to classify inherent vulnerability of cropland soils based on field sediment and nutrient transport resulting from surface runoff and leaching. The primary purpose of the SVI is to aid conservation planners in more rapidly assessing managed lands and inherent resource concerns. The index is based on hydrologic soil group, slope, and soil erodibility for cultivated cropland soils, with the addition of percentage rock fragments and organic matter when considering leaching. Although the SVI is intended for use throughout the United States, its development was based on the physiographic and rainfall characteristics of the Upper Mississippi and Ohio-Tennessee River basins. The purpose of this study was to evaluate the SVI in areas both in and outside of the area for which it was developed. Thirteen different watersheds were selected to conduct this evaluation. Vulnerability classifications using the SVI were compared with those from on-site experts9 knowledge and with model simulations using local data. Four companion papers in this special collection discuss SVI classification based on the effects of land slope, artificial drainage, sediment and nutrient loads, and vulnerability assessment using hydrologic simulation models. Using results from the various sites, the objective of this paper was to synthesize the interpretation of the value and applicability of SVI vulnerability classification to sediment and nutrient loss across various physiographic regions and suggest where improvement in the SVI could be made.

The Land is a natural resource that has limitations to accommodate human activities in land use. Utilization of land for residential land, regional development or, other land uses sometimes creates many environmental problems such as degradation of land quality and disturbance of natural balance. The increasing need for and competition in land use for regional development in Manokwari Regency requires careful thought in making decisions about the most beneficial use of limited land resources. Land Capability Classification is directed to determine the potential of land for broad land use based on suitable methods of use. The research variables used are nine Land Capability Units (LCU), namely LCU Morphology, LCU Slope Stability, LCU for Foundation Stability, LCU Water Availability, LCU Ease of Doing, LCU Against Erosion, LCU for Waste Disposal, LCU for Drainage and LCU for Natural Disasters. All LCU are analyzed using input in the form of factors limiting land capability consisting of maps of elevation, slope, soil type, rainfall, watershed, geology, natural disasters, and land use. The analysis produces an output in the form of a land capability classification map from the results of the digital spatial analysis process using a Geographical Information System (GIS).

Soil is an important basic natural resource in human production and life. Studying the micro-structure of soil, understanding various types of soil and grasping its specific data are of great guiding significance and reference value for the growth and development of plants and crops. Therefore, the systematic classification of soil is particularly important. There is no study on Soil Taxonomy in Renhe District of Panzhihua City, so this study will make up for this gap.The soil samples of 8 towns and townships in Renhe District of Panzhihua City were collected and analyzed. The main nutrient components were soil water content, soil ammonium nitrogen, soil available phosphorus, soil effective potassium, soil organic matter and soil pH value. The characteristics of soil were obtained through data analysis, and the soil types in the study area were also analyzed. Types were named and classified. Complete the task of land resources survey in Renhe District, clarify the types and distribution of soil in Renhe District, and enrich the content of soil science. The nutrient contents of various soils were analyzed by laboratory tests, which provided scientific basis for soil classification.Through the analysis of experimental data, it is found that the soil water content in Renhe District is low, the soil is weak alkaline, the content of organic matter is generally high, the content of ammonium nitrogen is low, the content of available phosphorus is generally high, and the content of effective potassium is relatively low

The Godawari-Purna sub basin is located between 76°36' to 77059' E and 19°07' to 19°17' N with an area of 34413.87 ha falls in assured rainfall region. Majority of the area under basin is used for agricultural purpose. The basin boundary is updated using the updated drainage and terrain information from high resolution satellite data of LISS-IV using GIS tool. Based on the derived thematic maps of land use and land capability class, the GP sub basin is divided into 11 sub catchments. Thematic maps viz., land use cover, has been interpreted using the visual interpretation techniques by heads-on digitization in the GIS environment using the enhanced high-resolution satellite imagery. Slope map has been generated from CartoDEM using the surface tools of the spatial analyst toolbox in ArcGIS. Land use mapping indicated that 85.68 per cent land is under cultivation with cropped area indicating a good vegetative cover in basin area. Digital Elevation Model (DEM) indicated that majority of the area of basin is having a slope in the range of 0 to 3 per cent. Majority of the area was found to be under class III and class IV category. All the generated thematic maps of Godawari-Purna sub basin will be useful for land resources planning.

Mapping Soils under Water

In Egypt, the excessive population growth and the lack of food security were the guide to increase production in unit area, expand the cultivated land horizontally, and to utilize the land with respect to its potentiality in an appropriate way. Therefore, this study aims to integrate soil qualities (or characteristics) with remote sensing data and Digital Elevation Model (DEM) into a Geographic Information System (GIS) to produce a database for the land resources and the soil map, and assess the current and potential suitability of some specific crops in El-Qaa plain, South Sinai, Egypt. Two SPOT5 images were classified using unsupervised classification technique. The base map of the study area was used in the field to check, confirm, correct and modify the physiographic mapping unit boundaries. Four sample areas were selected. 26 soil profiles were taken to represent the different mapping units in the study area. Morphological description and soil sampling were collected for laboratory analyses. The physiographic units were classified into subgroup level on the basis of the key to soil taxonomy. the results show that soils in the study area include: sand sheet (Low, moderate, and high) classified as Typic Torripsamments and Typic Haplosalids, Bajada classified as Typic Torripsamments and Sodic Haplocalcids, Basin classified as Typic Torriorthents, Wadi classified as Typic Torripsamments and Sodic Haplocalcids, Dry sabkhas classified as Typic Aquisalids, and Wet sabkhas classified as Sodic Psammaquents. The main land qualities of the different mapping units were selected and crop requirements of 21 crops were rated and matched to obtain the current and potential land suitability. The suitability of the selected crops currently not suitable in the different mapping units. The main limiting factors are texture, salinity and alkalinity, nutrient availability and calcium carbonate content, only in sabkhas added flooding, drainage, and soil depth. The potential suitability in the different mapping units refers that soils can be highly (S1), moderately (S2), and marginally (S3) suitable with a proper management practices and fertilization, and can not be suitable due to soil texture in all mapping units except in sabkhas where the limiting factors are texture, salinity and alkalinity, flooding, drainage, and soil depth which can not be enhanced in the near future. The results obtained can be employed by landuse planners (decision makers) to select areas suitable for the selected crops production.

Successful crop production requires the knowledge of soil variation and the evaluation of the agricultural potentials of the land. Detailed land resource survey of approximately 100 ha land in Abeokuta North Local Government Area of Ogun State was carried out. Identified soil mapping units were examined in modal profiles. The soils were classified using the USDA Soil Taxonomy, FAO/IUSS World Reference Base (WRB) system and local soil series methods. Five soil mapping units were identified and were classified as Ilaro Series (Kanhaplic Haplustalf), Ibeshe (Typic Kandiustalf), Kulfo (Udic Kandiustalf), Molo (Rhodic Kandiustalf) and Otteyi Series (Lithic Haplustept). The soils were classified as Alfisols (71.56%) and Inceptisols (28.44%). Land Capability Classification (LCC) revealed that Ilaro, Ibeshe and Molo series belong to Capability Class II while Kulfo series was Class III but Otteyi series is of non-arable Class VI. Otteyyi Series had severe limitations of very shallow soil depth, high slope gradient and high gravel content. The area has good potential for crop production if soil fertility can be managed with appropriate fertilizer application and seasonal water deficit ameliorated by supplemental irrigation. Otteyi Series that is non-arable could be used for farm buildings and other physical infrastructures or animal grazing. Key words: Land evaluation, fertility capability class, soil series, limitations, arable cropping. &nbsp

The Australian Soil Classification provides a framework for organising knowledge about Australian soils by allocating soils to classes via a key. Since its publication in 1996, this book has been widely adopted and formally endorsed as the official national system. It has provided a means of communication among scientists and land managers and has proven to be of particular value in land resource survey and research programs, environmental studies and education. Classification is a basic requirement of all science and needs to be periodically revised as knowledge increases. This third edition of The Australian Soil Classification includes updates from a working group of the National Committee on Soil and Terrain (NCST). The main change in this edition accommodates new knowledge and understanding of the significance, nature, distribution and refined testing for soils comprising deep sands, leading to the inclusion of a new Order, the Arenosols. The introduction of the Arenosols Order led to a review and changes to Calcarosols, Tenosols and Rudosols. The Australian Soil Classification is Volume 4 in the Australian Soil and Land Survey Handbook Series.