Capability Classification Research Articles

Rice Soil Fertility Classification in the Mekong Delta, Vietnam

The rice crop intensification led to soil degradation and yield decline in the Mekong Delta, Vietnam. Therefore, it is necessary to classify soil fertility and identify the constraints for proper soil use. The soil legend classified by World Reference Based was converted to the Fertility Capability Classification system. The soil constraints and recommendations for appropriate services are suggested. The findings indicate seven primary soil categories, ten diagnostic layers, three diagnostic features, and three diagnostic materials in the rice soils of the Mekong Delta. Eleven soil constraints were found, most of which were associated with acid sulfate and saline soils. These constraints included low acidity, strong acidity, low available P, high P fixation, high potential Fe toxicity, slightly actual acid sulfate and shallow potential acid sulfate, deep potential acid sulfate, slight salinity, and strong salinity, low mineral supply capacity, limited organic carbon content, and low nutrient retention capacity. Reclamation of acid sulfate and saline soils by leaching soil toxicity and boosting soil nutritional status with organic matter and P, K treatment were recommended for degraded, acid sulfate, and saline soils.

Land capability and carrying capacity analysis against land use change in the Motaain Border Region (Indonesia-Timor Leste)

Changes in land use in the border regions of the Motaain state (Indonesia-Timor Leste) are caused by population growth and a variety of activities of the population. Thus, changes in land use that are not controlled affect the ability and carrying capacity of the land. Moreover, the research objective is to assess the characteristics of the region from the physical aspects of the environment to spatial changes, as a reference for controlling spatial use. The analytical methods are used population density and activity density (Kernel density); analysis of activity patterns (cluster and outlier analysis and spatial auto-correlation Moran’s I); class analysis of land capability and carrying capacity (overlay); and quantitative statistical quantitative analysis. The results of the analysis explain that from the year 2013 until 2017 the border area of the Motaain state experienced population growth and activities, these affected spatial patterns that change in land use from non-developed land to build-up land. It is also explained that overlay analysis results are more dominant land capability classes are very low as well as the carrying capacity to land that is predominantly a potential and protected development area. The difference in capability and carrying capacity to land is a product of social activities that cannot be controlled.

Delineation and Prioritisation of Groundwater Recharge Areas in the State of Tamil Nadu using Geographical Information System

Delineation and prioritisation of suitable areas for artificial groundwater recharging (AGR) in the state of Tamil Nadu was carried out in the present study. Soil properties namely, soil drainage and land capability class, and geology of the aquifer were identified as spatial parameters that influence the AGR. Weights of 25, 25, and 50% were given to the soil drainage, land capability class, and geology of the aquifer, respectively. Variability within a specific theme was considered by assigning appropriate score to the subtheme. The depth of water table, in addition to soil drainage and land capability class, and geology of the aquifer, was used to decide the priority area of the AGR. Prioritised areas were divided into different rainfall zones as priority first (PR1) and priority second (PR2), which was found to be 14.29% and 38.18% of total area of the state, respectively. Considering bi-modal nature of rainfall in Tamil Nadu, the estimated numbers of percolation pond and check dam were worked out as 6,118 and 15,730 for PR1 areas; while numbers of percolation pond and check dam were worked out as 16,468 and 42,350 for PR2 areas, respectively. The results of this study can help state departments to implement the AGR scheme.

Unlocking the Land Capability and Soil Suitability of Makuleke Farm for Sustainable Banana Production

Sub-Saharan Africa (SSA) is experiencing an increase in food insecurity, which is fueled by both high population growth and low agricultural productivity. Smallholder farmers are seriously affected by low soil fertility, land degradation, and poor agronomic management practices that reduce crop productivity. Therefore, there is a huge need for reliable soil information to support agricultural decision-making in smallholder farms to ensure sustainable agricultural production. However, most studies focused on land capability and soil suitability do not consider the spatial variability of soils and their inherent properties. The main objectives of this study were (1) to survey, classify and characterise soils at Makuleke farm in order to derive and map the land capability classes and (2) to quantify the physical and chemical properties of the soils in order to derive and map the suitability classes. A field survey and classification of soils led by transect walks complemented by auger holes revealed existential spatial variation of soils across the 12 ha banana plantation. The dominating soil forms in the plantation were Hutton, Westleigh, Glenrosa and Valsrivier. Land capability analysis revealed that 17% of the 12 ha portion of the farm had very high arable potential, while 60% had medium arable potential, 6% of the farm had low arable potential and 17% was considered non-arable. Subsequent soil suitability analysis revealed that 12% of the farm is highly suitable, 34% is moderately suitable, 38% is marginally suitable and 16% is permanently not suitable for banana production. The variable capability of the land and suitability of soils for banana production led to notable yield gaps. The in-depth description and quantification of the productive capacity of the land is pivotal to the farmers at Makuleke farm as it unlocks their true potential and such information is crucial to effectively manage the soil and utilize the land for sustainable banana production.

Land capability analysis using LCLP software in cangkringan micro watershed model

Each land in a watershed area has different capabilities depending on the characteristics of the land in the area. Land capability analysis is needed in land management and land use, the aim is that land use can be carried out optimally and reduce the impact of land damage. Determination of land capability class using the matching method, by matching and comparing land characteristics or land limiting factors with land capability class criteria according to the USDA classification system. This study was started by conducting field observations and taking soil samples, then analyzed using Land Capability and Landuse Planing (LCLP) software and GIS to get a map of the land capability class. The results showed that the land capability in site are consists of class II-IV and VI-VII. The limiting factors for land management are erosion (e), permeability (P), texture (t) and slope (L)

Comparative Study of Three Land Evaluation Systems by using a Geographic Information System (GIS) under Mediterranean Condition

Background: The purpose of this work consists of doing a comparative study of three Land Capability Classification (LCC), Storie, National Institute of Irrigation and Drainage Institute (INSID) by applying them to the region of the Oriental Mitidja (Rouiba-Algeria). Methods: A geographic information system for the region in question was carried out, with a view to developing different thematic maps and allowing the comparison of these three evaluation systems, thanks to a database that has been created for this purpose. Result: The system adapted by INSID has given rise to lower evaluation results compared to the two other systems, because 99.99% of the total agricultural ability by the LCC, 97% Apt for agriculture. By Storie while only 48% of the total area is fit for agriculture according to INSID. Statistical results have shown the existence of a significant difference between the three land evaluation systems. However, the correlation is significant between the INSID and STORIE system.

Comparison of three land evaluation systems in capability assessment of soils of coastal plains sand in Southeastern Nigeria

Land evaluation systems vary in approach and have not always produced good results outside regions where they were originally conceived. To test the extent of their agreement, Land Capability Classification (LCC), Fertility Capability Classification (FCC), and Suitability Rating were combined in physically evaluating soils of Coastal plains sand, Imo State, Nigeria, using data from 20 pedons. With respect to LCC, soils of inland valleys were limited mainly by wetness, which had 2 out of 6 profiles of the unit classified beyond the arable. The well-drained upland soils, all of which fell within the arable classes, were subject to sheet and rill erosion. By standards of FCC, soils were limited by ‘g’ - water logging; e - low ability to retain nutrients; i - potential fe - toxicity; k - low nutrient capital reserves. Based on suitability rating, soils potentials for agriculture varied from poor to good. Results of LCC and FCC correlated significantly (r = 0.771), but none of these correlated with suitability ratings of the soils. Use of the international systems should be augmented with further soil tests some of which may be got from other comparable systems so as to capture other locally important environmental details. Subjecting factors identified by FCC to suitability rating improved evaluation procedure. Land use in the location did not strictly consider the capability of the land. Cultivating rice to the wet soils or draining them, contour cultivation on slopes, adequate fertilization of soils are recommendations to improve land management.

Spatio Prediction of Soil Capability Modeled with Modified RVFL Using Aptenodytes Forsteri Optimization and Digital Soil Assessment Technique

To meet the needs of Egypt’s rising population, more land must be cultivated. Land evaluation is vital to achieving sustainable agricultural production. To determine the soil capability in the northeast Nile Delta region of Egypt, the present study introduces a new form of integration between the Agriculture Land Evaluation System (ALES Arid) model and the machine learning (ML) approach. The soil capability indicators required for the ALES Arid model were determined for the 47 collected soil profiles covering the study area. These indicators include soil pH, soil salinity, the sodium adsorption ratio (SAR), the exchangeable sodium percentage (ESP), the organic matter (OM) content, the calcium carbonate (CaCO3) content, the gypsum content, the clay percentage, and the slope. The ALES Arid model was run using these indicators, and soil capability indexes were obtained. Using GIS, these indexes helped to classify the study area into four capability classes, ranging from good to very poor soils. To predict the soil capability, three machine learning algorithms named traditional RVFL, sine cosine algorithm (SCA), and AFO were also applied to the same soil criteria. The developed ML method aims to enhance the prediction of soil capability. This method depends on improving the performance of Random Vector Functional Link (RVFL) using an optimization technique named Aptenodytes Forsteri Optimization (AFO). The operators of AFO were used to determine the best parameters of RVFL since traditional RVFL is sensitive to parameters. To assess the performance of the developed AFO-RVFL method, a set of real collected data was used. The experimental results illustrate the high efficacy of AFO-RVFL in the spatial prediction of soil capability. The correlations found in this study are critical for understanding the overall techniques for predicting soil capability.

Determining the Effect of Urbanization on Agricultural Lands Using Remote Sensing and Geographic Information System Techniques

Bu çalışmanın amacı, yıldan yıla tarımsal arazi varlığında önemli derecede daralma meydana gelen Türkiye’de; Konya ili Selçuklu ilçesinde, Uzaktan Algılama (UA) yöntemleri ve Coğrafi Bilgi Sistemleri (CBS) kullanılarak, kentleşmenin farklı yıllardaki alansal değişimi ve bu değişimin tarım arazileri üzerindeki etkisini belirlemeye yöneliktir. Çalışmada, Landsat 5-8 uydu görüntülerinde, CBS tabanlı olarak, NDVI ve NDBI indeksleri hesaplanmış; 2001, 2014 ve 2021 yıllarına ait, kentsel ve tarımsal alanlardaki değişimin görselleştirilmesi amacıyla dağılım haritaları hazırlanmıştır. Buna göre, 2001 yılında 79300.63 hektar olan tarımsal alanlarının, 2021 yılında 50167.97 hektara gerilediği, 2001 yılında 9265.19 hektar olan kentsel alanların 2021 yılında 15690.5 hektarlık alana yayıldığı tespit edilmiştir. Ayrıca çalışma alanına ait arazi yetenek sınıfları ve toprak dağılım haritaları oluşturularak, yerleşime uygun olmayan alanlar tespit edilmiştir. Sonuç olarak; sektörel anlamda bir tarafta kazanımlar var iken, diğer tarafta kayıplar söz konusudur. Bu nedenle kentsel alanlardaki genişlemenin, özellikle tarım alanlarının daralması anlamına geldiği, son 20 yıl içinde kentsel alanların % 3.35 oranında büyüdüğü, tarım alanlarında da % 15.18 oranında bir kayıp yaşandığı belirlenmiştir. Ayrıca alüvyal arazilerin ve tarımsal üretim yapılan arazilerin üzerinde yerleşim yerlerinin ve diğer yapay alanların yayıldığı tespit edilmiştir.

Arahan Perubahan Penggunaan Lahan Berbasis Rendah Emisi Karbon Di Hulu Das Jeneberang

Jeneberang watershed is one of the watersheds in the MAMMINASATA area (Maros, Makassar, Sungguminasa and Takalar). The watershed, upstream, is now in a critical condition. This study aims to identify and map land use patterns, carbon stock emissions, both in the present condition and after rehabilitation condition. The data and information used in this research are Landsat 7 ETM+ in 2006 and 2010, the Jeneberang watershed boundary map, critical land map, forest area map, rainfall data, population data, and land capability class map. The method used is the interpretation of land use or land cover, biomass calculation, and analysis with REDD ABACUS. The results showed that land use was dominated by plantations and then followed by low density forest, agricultural dry land, rice fields, water bodies, plantation forests, vacant land, shrubs, settlements, high density forests, and savannas. The direction of land cover/land use that can increase carbon sequestration is the conversion of barren land, shrubs and savannas into plantation forests and agroforestry. Potential carbon stocks for plantations, dry land agriculture and rice fields will increase to 2.295.626,32 tons in 2026.

Evaluasi Kesesuaian Penggunaan Lahan Berdasarkan Kemampuan Lahan dengan Metode Skoring di Kabupaten Aceh Besar

Aceh Besar District is designated as an Integrated Economic Development Zone (KAPET) with the potential for rapid economic and regional development. This has an effect on the demand for land and housing for development which at any time can increase sharply, if not accompanied by certain policies and considerations it can cause a decrease in land capacity and affect the sustainable development of the area. The demand for more rapid development can lead to uncontrolled land-use change, changes in spatial use, and trigger disasters that affect community economic development. This study aims to evaluate the suitability of land use based on the ability of the land to use spatial data in Aceh Besar District. This study uses the scoring method for spatial analysis that refers to the Permen PU No. 20 / PRT / M / 2007. The results showed that the land capability unit of Aceh Besar District had an average weight of 3, except for the land capability of the carrying capacity and foundation stability was less with a weight of 2-3. The land capability value of the Aceh Besar Regency is 71-121, with the highest land capability class being class c (value 83-109) covering an area of 215,861.16 Ha or 74.96% and is included in the medium development classification. The suitability of land use in Aceh Besar District has a high level of land-use suitability with an area corresponding to 277.887,38 Ha or 96,56% and an area according to conditionally covering 9.895,94 Ha or 3.44%, while the level of land use mismatch in Aceh Besar District is classified as low with an area of 2,15 Ha or 0,0007%.

Development of Land Capability-Based Settlement Areas in Banyuasin District

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.

Fertility capability classification (FCC) of soils of a lower Brahmaputra valley area of Assam, India

Fertility capability classification (FCC) is a system of classification which uses pedological data of soils and coverts it into capability classes based on major fertility constraints portrayed by the soils. The present study was aimed to classify the soils major landforms of a lower Brahmaputra valley region of Assam, India in to FCC classes, to suggest specific management practices in order to overcome the fertility constraints and improve the crop productivity.The major strata types used were found to be loamy top soil, 'L' and clayey top soil 'C'. The sub-strata type found were loamy sub soil, 'L' and clayey sub soils, 'C'. The major condition modifiers or the major fertility constraints were found to be Al toxicity 'a’ and 'a-', high leaching potential, 'e', low nutrient reserves 'k' and 'g' waterlogging. The paddy soils of alluvial plains were classified into La-eg and Lg+a-e. The tea growing soils of younger alluvial plains were classified into Car+e. The non-paddy soils of alluvial plains were categorized as Ca-gke. The soils of uplands and inselberg were categorized into LCae class. The study revealed that FCC classification can successfully bring out the soil fertility constraints and can be very much helpful in soil fertility management for sustainable crop productions.

Quantifying agricultural property value diminution due to upstream oil and gas activities using Alberta's abandoned well sites as an example

There is public perception that agricultural property value in Alberta is negatively affected by abandoned but unreclaimed oil and gas well sites. This exploratory research examines whether a difference in property values exists between those with reclaimed well sites and properties with abandoned but unreclaimed well sites (i.e., reclamation status). A total of 485 property transfer records from the provincial registry and oil and gas well information from an industry database were used in the research. Stepwise, sequential-search regression was applied to derive an optimized set of potential factors and covariates to predict per-acre agricultural property value. Property sale date, residential density, and agricultural land capability class were the covariates. Property location, well type, and reclamation status were the factors. The data analysis did not support the public perception about reclamation status but did confirm property location and the listed covariates as significant predictors of agricultural property value in Alberta.

Evaluation of carrying capacity based on land capability of Kulon Progo Regency as an input for spatial planning in the new aerotropolis era

The new aerotropolis era due to airport construction in Kulon Progo has stimulated regional development and changed the image of the area from rural to urban-oriented. The negative impact of rapid growth, such as the urban sprawl, can be mitigated through sustainable spatial planning. Therefore, this study aims to evaluate the carrying capacity based on the land capability of both existing and official land use planning. The matching criteria method was used to conduct the capability evaluation. According to the analysis results, 56.13% of the Kulon Progo area was dominated by moderate to low land capability classes (V-VIII) with the main inhibiting factor as slopes. Furthermore, the evaluation of conformity with land use/land cover (LULC) in 2020 showed most land uses were in not conform (NC) and conditionally conform (CC) status. The area of land use that did not conform with its carrying capacity was 8,286.44 ha which was distributed in the southern part. Meanwhile, an evaluation of the official land use planning of the area showed 57% of the plan was conform (C) with land capability. Therefore, the carrying capacity of the land in Kulon Progo is in reasonably good condition. However, planning interventions should be carried out for areas with not conform status.

Production Potential Appraisal of Soils of for Part of Palamaner Division in Chittoor District, Andhra Pradesh, India

The soil profile samples that are present in upper slopes of the Palamaner agricultural division are evaluated to know the production potential of the study area. The soils have moderate slope and are affected by erosion. Besides, soils have excessive drainage limitation. Geologically, soils are developed on the quartz-migmatite gneiss complex. All the soils are studied for morphological, physico-chemical and chemical properties. The results shown that, soils are slightly acidic to neutral in soil reaction (pH), non saline (EC), moderately deep to deep (90-135 cm) in depth. The texture of soils varied from moderately well drained with no erosion to severe erosion. The soils are placed under IVes land capability class. The actual productivity and the potential productivity are calculated; the maximum potential productivity was 81.23 and the crop improvement factor was 1.59.

A Study of Soil and Land Features with Geographic Information Systems (GIS) Analysis: Iğdır, Türkiye

The aim of this study was to determine the soil and land characteristics of the province of Iğdır in Türkiye and to create a database by using geographical data system analysis, which is widely used today. The study area was 3674.42 km2 and the digital elevation model of the area was created using a 1/25000 scale topographic map from the General Command of Mapping in Iğdır province, and elevation, slope, aspect, and drainage maps were produced. Additionally, by using data and maps from the previous General Directorate of Rural Services and General Directorate of Soil Reform, large soil groups, depth, land use capability classification, problematic soils, water erosion, and wind erosion maps were created, and area calculations were made with ArcGIS Pro 2.5 software. As a result, flat and near flatlands were located in the center, east, and north and mountainous lands with high altitudes were located in the west and south of Iğdır province. Therefore, slopes were steep in the south and west, and low in the central, east, and north parts. The land use capability map consisted of 122040 ha suitable for cultivated agriculture (I-IV class); 211220 ha unsuitable for cultivated agriculture (V-VII class) as grassland; and 29260 ha of non-agricultural land. Land with moderate, severe, and very severe erosion comprised 16.3%, 27.3%, and 25.8%, respectively, of water erosion. Wind erosion affected 36670 ha of land. Iğdır has large diversity and variety in terms of soil and land features, despite its small area.

Mapping of Agricultural Land Use Change and Effect on Land Capability as a Basis for Land Use Direction in Nguntoronadi-Indonesia

The occurrence of conversion of agricultural land can cause erosion proneness, low fertility soils, and decreased land productivity. Land conversion requires an evaluation of land capability, as a basis for direction to maintain land productivity. This study aims to determine the rate of conversion of agricultural land, land capability class, the determinants of land capability, and direction of land management on initial land and converted land in agricultural land, Nguntoronadi District, Karanganyar Regency. The method used is a survey, with the research area divided into 6 LMU (Land Map Units) represented by 6 sample points in each LMU including 3 points on fixed land and 3 points on converted land, resulting in 36 samples determined by purposive sampling. The research stages include; 1) Pre survey, 2) Survey, 3) Post survey. The results of the study show that the land-use change from 2011 to 2020 covers an area of 258.56 ha and a rate of 28.73 ha per year. The land capability of the research area on fixed land and converted land is classified into land capability III and class IV. Factors that determine land capability include soil erodibility and drainage. The recommended direction for land use and management for Nguntoronadi District is the provision of green manure, making terracing, and making drainage irrigation

PEMETAAN KELAS KAPABILITAS KESUBURAN TANAH SEBAGAI DASAR IDENTIFIKASI PERMASALAHAN DAN STRATEGI PENGELOLAAN LAHAN SAWAH

Farmers' lack of understanding of agricultural land characteristics leads to inaccuracy in farm management. As a result, this research aimed to classify soil fertility capability and design soil management strategies based on the limiting factor. This study took place in Malang Regency's Turen District. Soil samples were taken from 45 observation locations throughout 15 LMUs (Land Map Unit). The Fertility Capability Classification (FCC) technique was used to evaluate soil fertility classification utilizing soil texture, pH, organic C, CEC, cation base (K, Na, Ca, Mg), and base saturation. Turen District was found to have eight fertility capability classifications, including Chm (3-8 %), Chm (8-15 %), CLhm (0-3 %), CLhm (3-8 %), LChm (3-8 %), Lhm (0-3 %), Lhm (3-8 %), and Lhm (8-15 %). Single symbol C is interpreted as clay texture for both top and subsoil, as well as a single symbol for L as loamy texture. Symbol CL is interpreted as clay texture on topsoil and loamy texture on subsoil. Symbol LC is interpreted as loamy texture on topsoil and clay texture on subsoil. Symbol h in FCC class is interpreted as low pH (acid), and symbol m as low organic C. Soil pH and organic C content are the two most important limiting parameters for soil fertility.

Evaluation Of Land Capabilities For Coffee And Durian Crops To Sustainable Agriculture

The utilization of land that is not corresponding to its capabilities will accelerate land degradation. Therefore, in this study, the land capability was assessed to determine land capability classes and land use directions for applying sustainable agricultural systems in coffee and durian cultivation areas in the Wonosalam region, Jombang, East Java. The procedures included field observations, soil sampling, and laboratory analysis. Soil samples were taken at two depths, 0-30 cm and 30-60 cm, carried out by taking samples at two different points, then analyzed in a composite manner. The results showed that the class of land capability for planting coffee and durian was in class VII, which had a limiting factor in the form of slopes. Limited grazing and nature reserves are the focus of class VII land-use guidelines so that the land use direction follows the characteristics of the nature reserve and the principles of sustainable agriculture. Concerning long-term agriculture, we need to use conservation strategies both vegetatively and mechanically. Thus, the land that is the research site will be able to maintain its carrying capacity and minimize the decline in land quality and quantity on land use in the Wonosalam, Jombang area.