Relevant bibliographies by topics / Land capability classification

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Land capability classification'

Author: Grafiati
Published: 4 June 2025
Last updated: 14 July 2025

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Journal articles on the topic "Land capability classification"

1

Neitsch, Conrad, Micheal Golden, and L. R. Hossner. "LAND CAPABILITY CLASSIFICATION." Journal American Society of Mining and Reclamation 1997, no. 1 (1997): 141–51. http://dx.doi.org/10.21000/jasmr97010141.

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Ternan, J. L., A. G. Williams, and C. Francis. "Land Capability Classification in Grenada, West Indies." Mountain Research and Development 9, no. 1 (1989): 71. http://dx.doi.org/10.2307/3673466.

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Ahukaemere, C.M., and N.S. Obasi. "Potentials of Soils derived from Asu River Group and Asata Nkporo Shale for Arable Crop Production in Ebonyi State, Nigeria." Bulgarian Journal of Soil Science 3, no. 1 (2018): 48–62. https://doi.org/10.5281/zenodo.2586704.

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Land capability classification (LCC), fertility capability classification (FCC) and land suitability evaluation of some soils of Ebonyi State were carried out for cassava, yam and maize cultivation. Land capability and fertility capability classes were obtained using the method of United State Development of Agriculture (USDA) while suitability evaluation was done using the Food and Agricultural Organization of the United Nations’ (FAO) conventional method. Four (4) pedons were investigated, two from Akaeze (Asu river group) and two from Abakaliki (Asata nkporo shale) . Results of LCC showed that sites 1 and 2 (Asu river group) were classified as class II soils while sites 3 and 4 (Asata nkporo shale) were classified as class IV soils. According to FCC results, the major classes obtained were SM,g,k for site 1, A,g,k for site 2 and SA,e,k,r for sites 3 and 4 respectively. The results of land suitability evaluation showed that despite climatic factors and topography, there was no highly suitable (S1) land for maize, yam and cassava cultivation. Total nitrogen and organic carbon contents of pedons 1, 2 and 4 were marginally (S3) suitable for the production of yam and cassava while the nitrogen and organic carbon contents of pedon 3 were currently not suitable (N1) for yam and cassava cultivation. Soil texture, pH, ECEC and available phosphorus made the 4 sites moderately suitable (S2) for cassava and yam cultivation. Also, the acidic condition of the soils made all the sites moderately suitable for maize production. From the results of the aggregate suitability ratings, the major constraint for yam, cassava and maize cultivation in the sites was soil fertility (f) resulting from low organic carbon and total nitrogen contents of the soils. Though not optimum for the cultivation of the crops evaluated, the soils can still produce increased and sustainable crop yield if the appropriate husbandry practices are adopted, with particular reference to organic and nitrogen fertilizer application.
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IA, Nweke, and Ejikeme CS. "Land capability evaluation and classification of Obosi Land in Anambra State Nigeria." World Journal of Advanced Research and Reviews 10, no. 2 (2021): 098–107. https://doi.org/10.5281/zenodo.5030716.

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Land capability evaluation and classification of Obosi land was carried out on an approximately total area of 25.58km2 using the map of the area. The aims of the study were to map out the soils of Obosi, classify them for suitability and sustainability for agricultural production and other land use development projects. Auger sample and profile pit samples were collected and examined. Using morphology and topography of the surveyed area, three mapping units; MUI-lowland areas, MUII- upland areas and MUIII-gullied areas were established. The result of the study indicated the textural class of the soils to be sandy loam, except for upland areas in Auger 1 were the textural class were loamy sand. The particle sizes range from 50gkg-1-90gkg-1 clay, 50-90gkg-1 silt, 130-590gkg-1 fine sand and 310-650gkg-1 sand. The pH of the soils varies from slightly acidity to slightly alkaline and was fairly uniform throughout the depths. The exchangeable bases, CEC, TEA, SAR and ESP of the soils were found to be low and below their critical level for crop production the base saturation value of the soils range from 22.28-99.21%. The low land areas and the upland areas were found to be suitable for arable crops. They fall under the suitability class S2 (suitable) and the capability class 11. Their major constraint on agricultural production is low fertility status. The gullied areas MUIII were found within the uplands and low-land areas. They fall under the non-suitability class NS (not suitable) and the capability class vi. The prominent limitation of this unit is erosion hazard. The area cannot be used in their present state without serious reclamation activities. The soils were classified as mixed isothermic kandic argiudult using the USDA soil Taxonomy and correlated as eutric ferralsols by FAO-WAB classification. Generally the soils need to be upgraded in soil nutrients through soil organic matter application and reclamation processes to produce maximally.
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A. C. Pandey, N.N. Sirothia, and R.S. Singh. "A Proposed Land Use Capability Classification System for Indian Sub-Continent." Journal of Agricultural Engineering (India) 43, no. 4 (2006): 1–8. http://dx.doi.org/10.52151/jae2006434.1209.

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The existing Land Use Capability Classification for India is almost the true copy of United States Department of Agriculture Land Use Capability Classification system with very few minor changes; and thus it is mainly based on the Agro-economic structure of USA. As a result. many fertile and productive lands of India, which are highly economic to cultivate, comes under the class "Not Suitable for Agriculture", e.g. Tea Gardens of India and fertile cultivable lands on hill slopes. Further the factors considered in determination of Land Capability Class, have not been assigned specific weightage and contribution, and this might lead to subjectivity in determination of land class. Moreover the Indian Land Use Capability Classification divides the cultivable lands into two groups, suitable for cultivation and not suitable for cultivation, which is not justified under the existing cultivation conditions in India. The proposed Land Use Capability Classification system eliminates the dividing line between the land suitable and not suitable for cultivation; and recommends all lands which are economical to cultivate as Suitable for cultivation. In the proposed pattern of land classification, many factors have been considered and all these factors have been given a weighatge on marks basis and this helps in clear and distinct contribution of these factors in land class determination. In the proposed Land Use Capability Classification system, the class of land only denotes the relative productivity of land and not its suitability and unsuitability for cultivation.
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Ičanović, Mirsad, Husnija Kudić, and Irma Ičanović. "Capability Classification of the Land Belonging to the Bužim Municipality." АГРОЗНАЊЕ 18, no. 1 (2017): 37. http://dx.doi.org/10.7251/agren1701037i.

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One of the primary soil functions is the production of food and raw materials, but the soil is used for ther purposes as well, outside the sphere of agricultural production, e.g.road construction and housing, exploitation of mineral resources. The research in this paper, appropriate agricultural land capability classification, was carried out in the Bužim Municipality using the guideline of unique methodology regarding the classification of agricultural land in the rating categories and criteria for individual soil properties, based on which land capability classes are determined. As a result of the research, six agricultural land capability classes (LCC) and land capability subclasses (LCS), ranging from III to VII, were determined, and areas were also marked as forest and built land. The most common land areas were marked under the VI LCC with the total area of 18.99% of the territory of the municipality. The V LCC was represented with a percentage of 11.65, while the IVa LCS was only represented with 1.02%.
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Zarlin, Een, Ardi Arfani, and Heru Wahyono. "Development of Land Capability-Based Settlement Areas in Banyuasin District." Jurnal Lahan Suboptimal : Journal of Suboptimal Lands 11, no. 2 (2022): 120–39. http://dx.doi.org/10.36706/jlso.11.2.2022.564.

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Lack study of land capability aspects in development of residential area affect the carrying capacity of environment. Therefore, this study aimed to analyze the land capability in Banyuasin District and formulate the land use directions according to its capability class. The research method used descriptive quantitative method using a spatial analysis approach with Geographic Information System and scoring analysis. The study results found out that the LCU of morphology was classified into low morphological LCU of 96.77% and less morphological LCU of 3.23%, the LCU of ease of work was high 48.11% and low 24.83%, the LCU of slope stability with the classification of high slope stability of 48.11% nd low slope stability of 24.83%, the LCU of foundation stability with high classification of 48.11% and low classification of 24.83%, the LCU of water availability with high classification of 48.11 and very low classification of 24.83%, the LCU of drainage with high classification of 56.62% and less classification of 46.11%, the LCU of erosion with high classification of 31.80% and very low classification of 1.85%, the LCU of waste disposal with sufficient classification of 46.11% and less classification of 56.62%, the LCU of disaster prone with high classification of 48.11% and low classification of 24.83%. In conclusion, the research area was divided into 3 classes of very high, moderately high, and low land development capability.
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Eacrett, Adrienne M., and Peter Wilson. "Development and Application of a Land Use Capability Classification for a Selected Area of Co. Laois." Irish Geography 23, no. 1 (2016): 31–37. http://dx.doi.org/10.55650/igj.1990.606.

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A land use capability classification, based on soil, slope and altitudinal attributes, has been developed and applied to a selected area of Co. Laois. The actual land use of the area was also recorded, from a false-colour satellite image, in order to determine whether land was being used to its maximum capability. Actual land use is appropriate to the established capability classes over half of the area; 40% of land is being used below its potential and 9.5% above its potential. Underutilisation is attributed to land that is capable of arable production being used for grassland and is probably a function of traditional agricultural practices and farm structure. The classification does not imply that land should be always used at its maximum capability but seeks to determine the capability of land as an aid to land use planning decisions.
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Utama, Putu Wira, and I. Wayan Sandi Adnyana. "EVALUATION OF LAND USE WITH LAND CAPABILITY CLASSIFICATION USING SATELLITE DATA AND GIS IN BATUR UNESCO GLOBAL GEOPARK." ECOTROPHIC : Jurnal Ilmu Lingkungan (Journal of Environmental Science) 13, no. 1 (2019): 61. http://dx.doi.org/10.24843/ejes.2019.v13.i01.p07.

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Development in ??Batur UNESCO Global Geopark has increased significantly in recent years. The land use changes in Bangli regency that the plantation, built-up/residential and tourism support facilities development increased quickly, especially in Kintamani district. To know the suitability of land use in Batur UNESCO Global Geopark area, it is necessary to evaluate land use with land capability classification. Landsat 8 remote sensing data on 27 September 2017 was used to create land use maps. Land use maps obtained through the process of image classification using supervised classification method and verified by ground check, this technique result 10 classes of land use. Land capability class map generated from improvisation overlay methods, reclassification of differentiator classes into the differentiator value of a raster data pixel (differentiator pixel value method). Furthermore, to evaluate of land use suitability was conducted by comparing land use with land capability class. In this process, there is an overlay between the land use maps with land capability class map using geographic information system (GIS). The results of evaluation land use in Batur UNESCO Global Geopark with land capability class overall has suitable area 15,764.78 ha (88.49%), not suitable area 1,767.48 ha (9.92%) and not detected/cloud interference 283.67 ha (1.59%).
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Fonataba, Brenda, Prima Jiwa Osly, and Irfan Ihsani. "CLASSIFICATION OF LAND CAPABILITY IN MANOKWARI AREA USING GEOGRAPHIC INFORMATION SYSTEM (GIS)." Jurnal Infrastruktur 6, no. 2 (2020): 129–39. http://dx.doi.org/10.35814/infrastruktur.v6i2.1721.

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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).
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Dissertations / Theses on the topic "Land capability classification"

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Cruz, Rex Victor O., and Peter F. Ffolliott. "A Geographically-Based Land Use Suitability Assessment and Land Capability Classification." Arizona-Nevada Academy of Science, 1990. http://hdl.handle.net/10150/296434.

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From the Proceedings of the 1990 Meetings of the Arizona Section - American Water Resources Association and the Hydrology Section - Arizona-Nevada Academy of Science - April 21, 1990, Arizona State University, Tempe, Arizona
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Cruz, Rex Victor Oafallas. "Land-use suitability assessment and land capability classification in Ibulao watershed, Philippines." Diss., The University of Arizona, 1990. http://hdl.handle.net/10150/184989.

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A geographically-based framework for landuse suitability assessment and land capability classification in Ibulao watershed, Philippines was developed and used in this study. Landuse suitability assessment was based primarily on soil erosion, the results of which were compared with the outcome of suitability assessments based on two land classification systems in the Philippines. The Ibulao watershed was subdivided into 10-ha cells, and each cell was independently evaluated with the aid of a geographic information system called MAP. The soil erosion rates for each cell were estimated using the MUSLE. The surface runoff and peak runoff rates were simulated using an infiltration-kinematic routing model, an event-based stochastic rainfall duration model, and the CREAMS model. The land capability classification was based on erosion index representing the inherent soil erodibility of a cell computed on the basis of runoff erosivity factor, soil erodibility factor, and the slope length-gradient factor. The results of capability classification were used to identify the different alternative uses of any cell in the watershed. The framework described in this study for landuse suitability assessment and land capability classification illustrated potentials for applications to the management and allocation of land resources in the Philippines. An erosion-based landuse assessment and land capability classification appears to be a better alternative to a slope-based system as far as the following are concerned: (1) identification of landuses which would not jeopardize the long term productivity and stability of an area; (2) a more accurate and meaningful land capability description and classification; and (3) making more lands available for various alternative uses by using criteria such as soil erosion which can easily be manipulated.
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Panda, Girish Chandra. "Geomorphology and agricultural land use capability classification in Mawsynram region of Meghalaya." Thesis, 1987. http://hdl.handle.net/2009/4383.

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Tesfagiorgis, Girmai Berhe. "An investigation into land capability classification in Eritrea : the case study of Asmara city environs." 2004. http://hdl.handle.net/10413/3603.

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The problems of land resources degradation as a result of misuse of arable land for non agricultural development and lack of appropriate methods and guidelines for land resources assessment are currently evident in Eritrea. These problems, have called for an urgent need for an appropriate land resources assessment in Eritrea. In response to this, a land capability classification in the areas around Asmara city that covers about 11742.7 ha was conducted. The intended aim was to properly assess the potential of the land resources in the study area and classify the capability of the land so as to designate the land according to its capability and foster appropriate land use. All the available natural resources in the study area were carefully assessed. A detailed soil survey was conducted and soil units were examined, described, classified and mapped out. Several criteria for the limitations were selected from the reviewed literature mainly USDA and RSA Land Capability Classification systems and in consultation with the soil survey and natural resources experts of the Ministry of Agriculture in Eritrea. In formation on land and soil characteristics, and the specified limitations and criteria were captured in a spatial digital format and then analysed within a GIS. Based on the specified parameters, different land capability units, subclasses, classes and orders were identified and mapped out. Finally, the sub classes were grouped to create,land capability classes ranging from Class I to Class VII and consequently the capability classes were grouped and mapped out at the level of land capability orders. The results revealed seven land capability classes (Class I to VII). Class III land in the study area covers 4149.43 ha (36.9 percent of the total area). The largest portion of this class is found in the central, southern and south eastern parts of the study area. However, classes I and II are very limited and cover 1562.95 ha (13.9 percent) of the study area. These classes are found mainly in the southern and central parts of the study area. Most of the gentle and steep sloping lands in the north and north eastern parts of the study area are classified as classes IV and VI. These classes have an area of 2652.08 ha (23.6 percent) and 2594.87 ha (23.1 percent) of the study area, respectively. Classes V and VII are very limited. These classes cover 221.53 ha (2 percent) and 57.55 ha (0.5 percent), respectively. The largest portion of class V land is found in the central part of the study area. Class VII land is mainly confined to the north eastern, western and southern corners of the study area. Four land capability orders were arrived at ranging from (high to moderate potential to non-arable land). The high to moderate potential arable lands are largely found in the southern and central parts of the study area. These lands cover 5715.39 ha (50.8 percent) of the study area. However, low potential arable (marginal productive) and non-arable lands have a considerable area of 2652.08 ha (23.6 percent) and 2652.42 ha (23.1 percent) of the study area, respectively. The largest portion of these lands is found in the north, north eastern and eastern parts of the study area. A small portion of the lands in the study area is classified as seasonally wetland. This land has an are~\ of 221.53 h~{2 percent) of the study area and is mainly found in the central part of the study area. It was concluded that nearly 50 percent of the land in the study area is classified as of moderately to high agricultural potential whereas the rest of the land is classified as marginal to non-arable land. However, the steady growth of demand for land for nonagricultural development due to the increasing population that depend on farm production in the study area, renders the prime arable lands as too limited to support the current population in the study area. Hence, protecting the prime arable lands and properly using such lands based on their sustained capacity can only secure the livelihood of the community.<br>Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2004.
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Horng, Chorng-Jen, and 洪崇仁. "Study of practical review for the classification standard of “Land Use Capability for Slopelands” in Taiwan." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/34176114442434904347.

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碩士<br>國立中興大學<br>水土保持學系所<br>96<br>Abstract The “Land Use Capability for Slopelands” has been according to classifying the land use capability of slopelands in Taiwan and has been executed up to now. That was set out early by referencing the action of USA. Because there are many disadvantages such as objective interpretation, bad precision and accuracy, low efficiency and constant arguing, during classifying the land use capacity, so we processed the study. Three watersheds were chosen to study the affecting extent of standard factors which may affect the classification results of land use capability for slopelands in Taiwan. By using ArcGIS v.9.2, the mean slope of each land sit within research area was calculated from 5 × 5m DEM (Digital Elevation Model) data. Outputs were compared with the measured slope data stored in database of “Land Use Capability Management system for Slopeland”. If calculated data were not consistent with slope data recorded in database, field survey was conducted to find out the reasons which may result in such differences. The study shows the mean slope is the key standard factor for classification. According to the classification standards, slopeland with mean slope ≥ 55% was classified to be forestry land, while the classification of land with mean slope < 55% is depending on many other factors. Nevertheless, most of slopelands with mean slope < 55% do not classified to be forestry lands. At Nuan-Pyi-Keng only 1.75% while at the other two watersheds none were classified to be forestry land. The mean slope data calculated from 5×5m DEM data are well consistent with the measured mean slope data. So, we can depend only on mean slope for agricultural slopeland planning and apply GIS technology to analyze mean slope of slopelands to simplify the procedure and reduce the cost of classification. The result should be sustained for “Land use Capability for Slopelands”. And on planning the agricultural land, it would be simplyzed, objective, reasonable and actual. Key Words：Land use Capability Classification for Slopelands , Watershed, DEM(Digital Elevation Model)
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Huang, Sheng-Tang, and 黃勝堂. "A study for the suitability of single cadastral unit as the identification and classification of “land use capability for slopelands”." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/25293730295713027445.

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碩士<br>國立中興大學<br>土木工程學系所<br>99<br>Slopeland management first heavy land reasonable using, and relief soil and sand disaster, in pursuit economic development of while, often led part industry and population to slopeland to development, plus global environment climate of exception extreme changes, makes land resources conservation adverse.Government through slopeland land use cassification and identification work,in order to achieve slopeland to utilization and the conservation both of principles,ensure limited of slopeland resources wing continued using. Existing identification work, according to the slopeland land use classification and identification standards , average slope calculation is the most importantetermining factor for identification agricultural or afforestation. Study on the application of geographic information systems (GIS) analysis technology combined with DEM data, against the actual identification for classification of agricultural and afforestation single cadastral unit land,using ArcGIS slope analysis module features. The results compared with actual identification agricultural or afforestation results. Results obtained in this study: (1) TIN average slope analysis accuracy more DEM high, and on actual identification will suitable agricultural land results consistency more better; (2) 25mx25m square cadastral unit analysis, slope obvious slowed, actual identification afforestation becomes agricultural land increased, on land using limit has relax of trend; (3) non- single cadastral unit land of TIN slope analysis results can be referenced to find a more rational approach for slopeland land use identification and classification.
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Camp, Kelson Gerald Temple. "A bioresource classification for KwaZulu-Natal, South Africa." 1999. http://hdl.handle.net/10413/5406.

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The classification of Bioresource Units (BRUs) was developed to provide a reconnaissance appraisal of the natural resources for both environmental impact assessments and the agricultural potential of KwaZulu- Natal. Storage of the Bioresource Programme in a geographical information system (GIS) facilitates usage. Of the criteria used for the classification of BRUs, climate (rainfall and temperature in particular), was considered to be the most important factor. Other factors used were the soil association codes of the Land Types, plant indicator species and communities, and terrain type. The base map used for the study was the 1 : 50 000 topo-cadastral map on which the Land Types (LTs) were demarcated. The result of the study was the mapping of 590 BRUs, each of which is sufficiently homogeneous in environmental factors (climate, soil association, vegetation type and terrain form), such that uniform land use practices, production techniques and levels, can be defined with a reasonable degree of accuracy. Ecotopes, based on LT information, were defined for each BRU. An ecotope is a class of land, defined according to soil characteristics, within which agricultural production will be uniform and will differ significantly between one ecotope and another. The ecotopes, both for cropping and veld, are not spatially defined, but expressed as percentages of the total area of the BRU. In the BRU inventory, crops suitable for the BRU and each ecotope, and the level of production (tons/ha/annum) in the case of crop ecotopes, are supplied at a stated level of management. In addition, it is possible to investigate the potential for 29 crops for which crop production models exist, and for any other crop providing its growth and site requirements, particularly climate and soil, are known. Additional crop production models will be developed, as the demand for this type of information is high. Veld management norms, such as grazing capacity, are supplied for the veld ecotopes. On the completion of the classification of BRUs the decision was made to develop a third level of classification and the Bioresource Groups (BRGs) were mapped. In the classification of the BRUs 23 vegetation types had been identified and used as one of the criteria for BRU demarcation. By grouping all the BRUs with the same vegetation type, BRGs were defined. Each BRG, therefore, consists of a specific vegetation type containing one or more BRUs of the same vegetation type. The 23 BRGs are used mainly for regional and veld management planning. The programme was designed for use by a wide range of people with individual skills and knowledge, and contains most of the information needed for land use planning. It is essential however, to be able to identify ecotopes in the field to effectively use the information at a detailed level for farm planning.<br>Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 1999.
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Books on the topic "Land capability classification"

1

Bibby, J. S. Land capability classification for forestry in Britain. Macaulay Land Use Research Institute, 1988.

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Leskiw, L. A. Land reclamation: Agricultural capability classification field manual. Alberta Land Conservation and Reclamation Council, Reclamation Research Technical Advisory Committee, 1993.

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Leskiw, L. A. Agricultural capability classification for reclamation: Working document. Alberta Conservation and Reclamation Council (Reclamation Research Technical Advisory Committee), 1993.

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Pettapiece, W. W. Land capability classification for arable agriculture in Alberta (1987): Technical report. Alberta Soils Advisory Committee, 1987.

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Association, Cumulative Environmental Management. Land capability classification system for forest ecosystems in the oil sands, 3rd edition: Field manual for land capability determination. 3rd ed. Alberta Environment, 2006.

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Page, M. J. Correlation of North Island regional land use capability units from the New Zealand land resource inventory. National Water and Soil Conservation Authority, 1985.

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Macyk, T. M. An agricultural capability rating system for reconstructed soils. Heritage Fund, 1987.

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Reunião de Classificação, Correlação de Solos e Interpretação de Aptidão Agrícola (3rd 1988 Rio de Janeiro, Brazil). Anais da III Reunião de Classificação, Correlação de Solos e Interpretação de Aptidão Agrícola. Empresa Brasileira de Pesquisa Agropecuária, Serviço Nacional de Levantamento e Conservação de Solos, 1988.

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Lazio (Italy). Assessorato agricoltura, foreste, caccia e pesca., ed. Produttività potenziale e classificazione dei terreni. Regione Lazio, Assessorato agricoltura, foreste, caccia e pesca, 1985.

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Noble, K. E. Land use capability classification of the southern Hawke's Bay-Wairarapa region: A bulletin to accompany New Zealand land resource inventory worksheets. National Water and Soil Conservation Authority, 1985.

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Book chapters on the topic "Land capability classification"

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Fenton, Thomas E. "Land Capability Classification." In Landscape and Land Capacity. CRC Press, 2020. http://dx.doi.org/10.1201/9780429445552-25.

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Rustu, Tewoldemedhin D. "Agricultural Land Conversion: Application of Land Capability Classification in Land-Use Planning of Embaderho Village in Eritrea." In Developments in Soil Classification, Land Use Planning and Policy Implications. Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-5332-7_29.

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Harahsheh, Hussein, Mohamed Mashroom, Yousef Marzouqi, Eman Al Khatib, B. R. M. Rao, and M. A. Fyzee. "Soil Thematic Map and Land Capability Classification of Dubai Emirate." In Developments in Soil Classification, Land Use Planning and Policy Implications. Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-5332-7_5.

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Pawar-Patil, V. S., Sainath Aher, Vidya Chougule, Sandipan Das, and Rushikesh Patil. "Field Survey and Geoinformatic Approaches for Micro-Level Land Capability Classification." In Geospatial Practices in Natural Resources Management. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-38004-4_3.

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Gurung, Shirshak. "Land Capability Classification for Agriculture: GIS and Remote Sensing Approach—A Survey." In Advances in Communication, Cloud, and Big Data. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8911-4_4.

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Nanwal, R. K., and G. A. Rajanna. "Land Use Capability Classification, Scope of Agro-Horticultural, Agro-Forestry and Silvi-Pasture in Dryland Agriculture." In Rainfed Agriculture. CRC Press, 2022. http://dx.doi.org/10.1201/9781003364917-8.

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Fenton, Thomas E. "Land Capability Classification." In Encyclopedia of Natural Resources: Land. CRC Press, 2014. http://dx.doi.org/10.1081/e-enrl-120049143.

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Fenton, Thomas. "Land Capability Classification." In Encyclopedia of Soil Science, Second Edition. CRC Press, 2005. http://dx.doi.org/10.1201/noe0849338304.ch197.

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"Land Capability Classification." In Encyclopedia of Soil Science, Third Edition. CRC Press, 2017. http://dx.doi.org/10.1081/e-ess3-120049143.

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Costantini, Edoardo. "The Land Capability Classification." In Manual of Methods for Soil and Land Evaluation. Science Publishers, 2009. http://dx.doi.org/10.1201/b10197-3.

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Conference papers on the topic "Land capability classification"

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Dewallef, P., C. Romessis, O. Le´onard, and K. Mathioudakis. "Combining Classification Techniques With Kalman Filters for Aircraft Engine Diagnostics." In ASME Turbo Expo 2004: Power for Land, Sea, and Air. ASMEDC, 2004. http://dx.doi.org/10.1115/gt2004-53541.

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A diagnostic method consisting of a combination of Kalman filters and Bayesian Belief Networks (BBN) is presented. A soft-constrained Kalman filter uses a priori information derived by a BBN at each time step, to derive estimations of the unknown health parameters. The resulting algorithm has improved identification capability in comparison to the stand alone Kalman filter. The paper focuses on the way of combining the information produced by the BBN with the Kalman filter. An extensive set of fault cases is used to test the method on a typical civil turbofan layout. The effectiveness of the method is thus demonstrated and its advantages over individual constituent methods are shown.
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Papaiordanidis, S., C. Minakou, and I. Z. Gitas. "ON-THE-FLY LAND COVER MAPPING USING MACHINE LEARNING WITH MULTISPECTRAL SATELLITE IMAGERY ON GOOGLE EARTH ENGINE." In Лесные экосистемы в условиях изменения климата: биологическая продуктивность и дистанционный мониторинг. Crossref, 2020. http://dx.doi.org/10.25686/7229.2020.6.58827.

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Land cover is one of the most important environmental variables used to describe natural ecosystems. Constant changes on the Earth’s surface create the need for new, up-to-date, and accurate land cover maps. During the last decades, remote sensing products have been used in conjunction with field measurements for the production of land cover maps in a cost-efficient manner. The aim of the present study was the development of a method for reliable on-the-fly land cover mapping using the Random Forest classifier and Sentinel-2 multispectral imagery on the Google Earth Engine cloud platform. The Random Forests algorithm was employed, and two classification schemes were adopted, one using the original 44 land cover classes used by the CORINE land cover product, and one using five general land cover classes (Artificial surfaces, Agricultural areas, Forest and semi-natural areas, Wetlands, and Water bodies), resulting in the generation of two land cover maps. The 2018 CORINE land cover product was used to identify training samples and validate the resulting land cover maps. The results showcased that the 44-class land cover map had an overall accuracy of 72.85% and the 5-class land cover map 88.32%. Overall, the results of this research indicate the capability of Random Forest algorithm in the reliable land cover classification.
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Byington, Carl S., Michael J. Roemer, Matthew J. Watson, Thomas R. Galie, and Christopher Savage. "Prognostic Enhancements to Diagnostic Systems (PEDS) Applied to Shipboard Power Generation Systems." In ASME Turbo Expo 2004: Power for Land, Sea, and Air. ASMEDC, 2004. http://dx.doi.org/10.1115/gt2004-54135.

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Numerous advancements have been made in gas turbine health monitoring technologies focused on detection, classification, and prediction of developing machinery faults and performance degradation. Existing monitoring systems such as ICAS (Integrated Condition Assessment System), which is the Navy’s program of record and is deployed on many US Navy ships, employ alarm thresholds and event detection using rule-based algorithms. Adding the capability to predict the future condition (prognostics) of a machine would add significant benefit to the Navy practice. The current paper describes a framework and development process that allows more “plug ‘n play” integration of new diagnostic and prognostic technologies using evolving Open System Architecture (OSA) standards. Although many modules were developed in the PEDS framework, specific gas turbine modules that focus on compressor and nozzle degradation algorithms are discussed. The modules use statistical prediction algorithms and were developed using seeded fault data generated by the Navy engineering station. The modules are fully automated, interact with the existing monitoring system, process real-time data, and utilize advanced forecasting techniques. Such an advanced prognostic capability can enable a higher level of condition-based maintenance for optimally managing total Life Cycle Costs (LCC) and readiness of assets.
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Yu, LiJie, Dan Cleary, Mark Osborn, and Vrinda Rajiv. "Information Fusion Strategy for Aircraft Engine Health Management." In ASME Turbo Expo 2007: Power for Land, Sea, and Air. ASMEDC, 2007. http://dx.doi.org/10.1115/gt2007-27174.

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Modern aircraft engines are equipped with sophisticated sensing instruments to enable proactive condition monitoring and effective health management capability. Development of intelligent systems that efficiently process sensor and operational data both onboard and off-board, to provide maintenance personnel with timely decision support, is the key to minimize flight service disruption and reduce engine ownership cost. The goal of this research is to develop a practical approach and strategy to leverage various available information sources and modeling techniques to streamline the engine health management process and maximize system accuracy and efficiency. This paper demonstrates a flexible fusion architecture that encapsulates the key elements of the engine monitoring and diagnostic process, i.e., sensor trend analysis module for anomaly detection, feature selection and fault isolation module for root cause identification, a decision module for diagnostic model fusion and action determination, and finally, a feedback module for knowledge validation and continuous learning. At the core of this engine health management system is a diagnostic fusion model designed around a common fault hierarchy which captures both a priori probabilities and interactions among various engine faults isolated by different classification models. The fusion model will resolve conflicting assessments from individual diagnostic models and provide a more accurate and comprehensive engine state estimate.
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Ghosh, Amit. "Developing Performance-Based Classification Rules/Regulatory Guidelines to Improve Effectiveness of Incident Management and Outcome of Disasters." In ASME/USCG 2017 4th Workshop on Marine Technology and Standards. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/mts2017-0407.

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What was common between the capsizing of the cruise liner Costa Concordia, engine fire on the Carnival Triumph and the sinking of the Deepwater Horizon rig? In all cases, the people impacted did not believe or find that the authorities, whether public or private, were capable of meeting their immediate needs. Consequently, such biases led to collective behavior or ‘herding’ with devastating outcomes. Holding true to its mission of marine safety, the United States Coast Guard (USCG) finds itself in roles of maritime incident management and provider of training for examination of foreign ships carrying U.S. passengers. Also, following land-based costal events such as Hurricane Harvey, the USCG is called upon to perform rescue operations in which risk assessment through effective communication between stakeholders becomes extremely important. Accordingly, this paper proposes a performance-based approach to occupant safety, occupant circulation, and hazard communication so that both classification rules can be developed and guidelines can be proposed for inclusion in the USCG Incident Management Handbook. Advances in the analysis and modelling of the movement of people, especially in building fires, have established the decision-making processes that individuals or groups undergo before reacting to an imminent danger. When a large number of people have a high commitment either to activity or to inactivity, it becomes important that an equilibrium solution is adopted and the resources are allocated accordingly. The author proposes evaluating incident management as a dynamic system. Like any dynamic system, incident management for any disaster, evolves with time in terms of scale, needed inputs and desired outputs. Engineers today have the capability to influence the outputs by establishing protocols for sharing of information and resources among the stakeholders. The author presented a paper on a similar topic at ASME’s Dynamic Systems and Controls Conference (DSCC 2015)3. Paper published with permission.
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Ahmed, Rizwan, Gyunyoung Heo, Dong-Keun Cho, and Jongwon Choi. "Characterization of Radioactive Waste From Side Structural Components of a CANDU Reactor for Decommissioning Applications in Korea." In ASME 2010 13th International Conference on Environmental Remediation and Radioactive Waste Management. ASMEDC, 2010. http://dx.doi.org/10.1115/icem2010-40201.

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Reactor core components and structural materials of nuclear power plants to be decommissioned have been irradiated by neutrons of various intensities and spectrum. This long term irradiation results in the production of large number of radioactive isotopes that serve as a source of radioactivity for thousands of years for future. Decommissioning of a nuclear reactor is a costly program comprising of dismantling, demolishing of structures and waste classification for disposal applications. The estimate of radio-nuclides and radiation levels forms the essential part of the whole decommissioning program. It can help establishing guidelines for the waste classification, dismantling and demolishing activities. ORIGEN2 code has long been in use for computing radionuclide concentrations in reactor cores and near core materials for various burn-up-decay cycles, using one-group collapsed cross sections. Since ORIGEN2 assumes a constant flux and nuclide capture cross-sections in all regions of the core, uncertainty in its results could increase as region of interest goes away from the core. This uncertainty can be removed by using a Monte Carlo Code, like MCNP, for the correct calculations of flux and capture cross-sections inside the reactor core and in far core regions. MCNP has greater capability to model the reactor problems in much realistic way that is to incorporate geometrical, compositional and spectrum information. In this paper the classification of radioactive waste from the side structural components of a CANDU reactor is presented. MCNP model of full core was established because of asymmetric structure of the reactor. Side structural components of total length 240 cm and radius 16.122 cm were modeled as twelve (12) homogenized cells of 20 cm length each along the axial direction. The neutron flux and one-group collapsed cross-sections were calculated by MCNP simulation for each cell, and then those results were applied to ORIGEN2 simulation to estimate nuclide inventory in the wastes. After retrieving the radiation level of side structural components of in- and ex-core, the radioactive wastes were classified according to the international standards of waste classification. The wastes from first and second cell of the side structural components were found to exhibit characteristics of class C and Class B wastes respectively. However, the rest of the waste was found to have activity levels as that of Class A radio-active waste. The waste is therefore suitable for land disposal in accordance with the international standards of waste classification and disposal.
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Yin, Qi, Zhixiong Ma, Xichan Zhu, and Xiaowei Fang. "Test Concrete Scenarios Extraction of Lane-Changing Scenarios Based on China-FOT Naturalistic Driving Data." In SAE 2023 Intelligent and Connected Vehicles Symposium. SAE International, 2023. http://dx.doi.org/10.4271/2023-01-7055.

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&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;On account of the insufficient lane-changing scenario test cases and the inability to conduct graded evaluation testing in current autonomous driving system field testing, this paper proposed an approach that combined data-driven and knowledge-driven methods to extract lane-changing test concrete scenarios with graded risk levels for field testing. Firstly, an analysis of the potentially hazardous areas in lane-changing scenarios was conducted to derive key functional lane-changing scenarios. Three typical key functional lane-changing scenarios were selected, namely, lane-changing with a preceding vehicle braking, lane-changing with a preceding vehicle in the same direction, and lane-changing with a rear cruising vehicle in the adjacent lane, and their corresponding safety goals were respectively analyzed. Secondly, the GAMAB criterion was introduced as an evaluation standard for autonomous driving systems. By utilizing lane-changing scenario data selected from the China-FOT naturalistic driving data, a scenario risk classification model and a model for excellent driver response performance in lane-changing scenarios were established. Finally, concrete scenarios corresponding to different risk levels for each type of lane-changing scenario were extracted through simulation. Test concrete cases for field testing were selected at the risk boundaries based on the characteristics of China-FOT naturalistic driving data. The results demonstrated that the proposed approach was capable of effectively extracting 701 high-risk scenarios and 446 medium-risk scenarios from a pool of 9000 concrete scenarios based on key functional lane-changing scenarios. Furthermore, representative lane-changing test concrete cases can be selected from the risk boundaries. This approach enabled a graded evaluation of the lane-changing capability of the autonomous driving system.&lt;/div&gt;&lt;/div&gt;
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Singh, Manan, and Ryan Sharston. "Direct Air Capture Technology: An Investigation of Net Carbon Impacts." In 2020 ACSA Fall Conference. ACSA Press, 2020. http://dx.doi.org/10.35483/acsa.aia.fallintercarbon.20.17.

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In recent years, Direct Air Capture (DAC) has been emerging as a promising negative emission technology, primarily due to its flexibility of location and capability to absorb CO2, generated from non-localized sources. This study evaluates the two variants of DAC i.e. DAC-1 utilizing liquid solvents and DAC-2 using solid sorbents, in terms of overall emissions generated as a result of the process of CO2 removal from atmosphere. It was found that majority of overall emissions generated during the life cycle of DAC, may be attributed to the operational phase. The operational emissions were then classified into three major steps i.e. CO2 capture, CO2 separation and compression. The impact of the choice of energy source on generated emissions was then analyzed in the cases of both DAC-1 and DAC-2, separately for the three classifications. Both the variants were found to be reasonably efficient in terms of net CO2 removed from atmosphere, provided the energy requirements are sourced from renewable energy resources. Additionally, we analyzed the secondary impacts in terms of land use requirements and water loss during the process.
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