Agricultural Land Use Patterns Research Articles

Evaluating Land Suitability for Wheat Cultivation Criteria Analysis Fuzzy-AHP and Geospatial Techniques in Northern Basrah Governorate.

Land suitability assessment is essential for planned land management strategies aimed at preserving soil and increasing productivity while ensuring sustainable agricultural production. Land degradation resulting from poor land management and fallowing practices typically leads to low land productivity in Iraq. To maintain agricultural productivity in the targeted area, agricultural requirements must align with available resources through land suitability analysis. In the northern region of Basrah Governorate in Iraq, the study focused on integrating GIS-based land suitability analysis with the fuzzy-analytical hierarchy process (F-AHP) approach. The analysis revealed varying suitability categories throughout the study area, with the largest proportion of unsuitable areas found in category N2, covering 31,202.36 hectares (37.76%), and category N1, currently unsuitable, covering an area of 19,956.24 hectares (24.15%). On the other hand, the moderately suitable category (S3) covered 8,297.26 hectares (10.04%), while the moderately suitable category (S2) covered 23,177.79 hectares (28.05%) of the total study area. No highly suitable lands were identified. The key determining factors for the suitability of lands for wheat cultivation were high values of electrical conductivity, carbonate minerals, bulk density, and low organic carbon content. Most agricultural lands are being used in a manner that contradicts their suitable potentials in the study area. Therefore, the pattern of agricultural land use needs to be adjusted based on their current potentials to reduce soil degradation.

Using Geographic Information System Technology for Land-Use Modelling on Developing area of Tanah Datar Sumatera Barat

GIS technology has advanced rapidly in recent decades to become a standard tool for managing and analyzing spatial data to solve spatial problems. Spatial modelling is one of the GIS products that can be used as a reference for future policy development for effective spatial management. This research aims to create land use models for the Tanah Datar area of West Sumatra in 2025 and 2035. The model is created using the Cellular Automata method and remote sensing data. The land use data from 1989 and 2002 became the model's base year, and 2019 served as the basis for testing the model's accuracy. According to the modelling results, there are several trends in land use change. Dryland agriculture expanded significantly, indicating an improvement in the pattern of agricultural land use. This condition suggests that regional development should focus more on potential and good spatial management.

Agricultural Land Use Influences Bacteriophage Community Diversity, Richness, and Heterogeneity.

The last two decades have witnessed a large-scale conversion of crop cultivation areas into small and mid-sized tea plantations in Assam, India. Agricultural land-use pattern positively or negatively influences native hydrology and above- and belowground biodiversity. Very little is known about the effect of agricultural land-use patterns on the soil virus (especially, bacteriophage) community structure and function. This metagenomic-based study evaluated the rhizosphere viral community structure of three interlinked cultivation areas, viz., mixed cropping area (coded as CP1), tea-seed orchard (CP2), and monocropping tea cultivation (CP3). The bacteriophages belonged to four major classes with the dominance of Malgrandaviricetes (CP1: 79.37%; CP2: 64.62%; CP3: 4.85%) followed by Caudoviricetes (CP1: 20.49%; CP2: 35.22%; CP3: 90.29%), Faserviricetes (CP1: 0.03%; CP2: 0.08%; CP3: 3.88%), and Tectiliviricetes (CP1: 0.12%; CP2: 0.07%; CP3: 0.97%). Microviruses dominated the phage population in both CP1 and CP2, representing 79.35% and 64.59% of total bacteriophage abundance. Both CP1 and CP2 had higher bacteriophage richness (species richness, R in CP1: 65; R in CP2: 66) and lower evenness (Pielou's evenness index, J in CP1: 0.531; J in CP2: 0.579) compared to the CP3 (R: 30; J: 0.902). Principal component analysis of edaphic soil factors and bacteriophage community structure showed a reverse-proportional correlation between the levels of Al saturation, and exchangeable Al3+ ions with that of soil pH, and bacteriophage abundance. Our study indicates that monocropping tea cultivation soil bears less viral richness, abundance, and heterogeneity.

Effect of Agricultural Land-Use Patterns on Soil Organic Carbon Stock in the Upper Vietnamese Mekong Delta

Effect of Agricultural Land-Use Patterns on Soil Organic Carbon Stock in the Upper Vietnamese Mekong Delta

The impact of agricultural waste on river water quality of kreo watershed in Semarang city

Agricultural waste, especially from the use of fertilizers and pesticides, has become a serious problem in several countries because it has caused a decrease in river water quality. The land use and livelihoods of the people in the Kreo watershed are oriented towards agricultural activities. This study aims to (1) analyze the pattern of agricultural land use in the Kreo watershed and (2) analyze the impact of agricultural waste on river water quality in the Kreo watershed. The method used is descriptive quantitative. Analysis of the impact of agricultural waste on river water quality was carried out by laboratory testing of river water samples that referred to the criteria for water quality standards based on class according to Government Regulation of the Republic of Indonesia Number 82 of 2001 for class I river designation. Laboratory tests of water samples used parameters TSS, TDS, Nitrate, BOD, and COD. While the analysis of the status of water quality using the STORET method. The results showed that the pattern of use of rice fields was clustered upstream and in the middle, farmland was clustered in the downstream and mixed gardens were spread out in the upstream, middle, and downstream areas. The status of river water quality in the upstream and middle parts of the Kreo watershed has been lightly polluted, while the downstream still meets the quality standards. The river water will be harmful to human health if it is intended as a raw source of drinking water.

Estimating global land system impacts of timber plantations using MAgPIE 4.3.5

Abstract. Out of 1150 Mha (million hectares) of forest designated primarily for production purposes in 2020, plantations accounted for 11 % (131 Mha) of this area and fulfilled more than 33 % of the global industrial roundwood demand. However, adding additional timber plantations to meet increasing timber demand intensifies competition for scarce land resources between different land uses such as food, feed, livestock and timber production. Despite the significance of plantations with respect to roundwood production, their importance in meeting the long-term timber demand and the implications of plantation expansion for overall land-use dynamics have not been studied in detail, in particular regarding the competition for land between agriculture and forestry in existing land-use models. This paper describes the extension of the modular, open-source land system Model of Agricultural Production and its Impact on the Environment (MAgPIE) using a detailed representation of forest land, timber production and timber demand dynamics. These extensions allow for a better understanding of the land-use dynamics (including competition for land) and the associated land-use change emissions of timber production. We show that the spatial cropland patterns differ when timber production is accounted for, indicating that timber plantations compete with cropland for the same scarce land resources. When plantations are established on cropland, it causes cropland expansion and deforestation elsewhere. Using the exogenous extrapolation of historical roundwood production from plantations, future timber demand and plantation rotation lengths, we model the future spatial expansion of forest plantations. As a result of increasing timber demand, we show a 177 % increase in plantation area by the end of the century (+171 Mha in 1995–2100). We also observe (in our model results) that the increasing demand for timber amplifies the scarcity of land, which is indicated by shifting agricultural land-use patterns and increasing yields from cropland compared with a case without forestry. Through the inclusion of new forest plantation and natural forest dynamics, our estimates of land-related CO2 emissions better match with observed data, in particular the gross land-use change emissions and carbon uptake (via regrowth), reflecting higher deforestation with the expansion of managed land and timber production as well as higher regrowth in natural forests and plantations.

Land-use harmonization datasets for annual global carbon budgets

Abstract. Land-use change has been the dominant source of anthropogenic carbon emissions for most of the historical period and is currently one of the largest and most uncertain components of the global carbon cycle. Advancing the scientific understanding on this topic requires that the best data be used as input to state-of-the-art models in well-organized scientific assessments. The Land-Use Harmonization 2 dataset (LUH2), previously developed and used as input for simulations of the 6th Coupled Model Intercomparison Project (CMIP6), has been updated annually to provide required input to land models in the annual Global Carbon Budget (GCB) assessments. Here we discuss the methodology for producing these annual LUH2-GCB updates and extensions which incorporate annual wood harvest data updates from the Food and Agriculture Organization (FAO) of the United Nations for dataset years after 2015 and the History Database of the Global Environment (HYDE) gridded cropland and grazing area data updates (based on annual FAO cropland and grazing area data updates) for dataset years after 2012, along with extrapolations to the current year due to a lag of 1 or more years in the FAO data releases. The resulting updated LUH2-GCB datasets have provided global, annual gridded land-use and land-use-change data relating to agricultural expansion, deforestation, wood harvesting, shifting cultivation, regrowth and afforestation, crop rotations, and pasture management and are used by both bookkeeping models and dynamic global vegetation models (DGVMs) for the GCB. For GCB 2019, a more significant update to LUH2 was produced, LUH2-GCB2019 (https://doi.org/10.3334/ORNLDAAC/1851, Chini et al., 2020b), to take advantage of new data inputs that corrected cropland and grazing areas in the globally important region of Brazil as far back as 1950. From 1951 to 2012 the LUH2-GCB2019 dataset begins to diverge from the version of LUH2 used for the World Climate Research Programme's CMIP6, with peak differences in Brazil in the year 2000 for grazing land (difference of 100 000 km2) and in the year 2009 for cropland (difference of 77 000 km2), along with significant sub-national reorganization of agricultural land-use patterns within Brazil. The LUH2-GCB2019 dataset provides the base for future LUH2-GCB updates, including the recent LUH2-GCB2020 dataset, and presents a starting point for operationalizing the creation of these datasets to reduce time lags due to the multiple input dataset and model latencies.

The spatial pattern of agricultural land use in China during the Holocene Megathermal

During the Holocene Megathermal, China entered a stage of extensive agricultural farming, although there are few reports on the possible distribution pattern of agricultural land use. The main objective of this paper is to discuss issues related to the spatial pattern of agricultural land use in China during the Holocene Megathermal. According to historic and archaeological information, three widely planted crops (foxtail millet, broom millet and rice) were selected to represent the main crops, and their distribution was assumed to reflect the agricultural land-use pattern at that time. From the perspective of these crops and their required climate conditions and based on proxy-based ancient temperature and precipitation data combined with modern climate data, an average annual accumulated temperature of ≥10°C in the Holocene Megathermal was retrieved and spatially interpolated to capture a picture of land use. Validation was conducted using archaeological data from 141 agricultural heritage sites. The results indicated that in the Holocene Megathermal, agricultural farming activities were widespread in China The northern-most boundary of agricultural land use was north of Daxinganling, and the southern-most boundary extended to Hainan Island. In the region of the Qinghai–Tibet Plateau where climate is currently much colder than during the Holocene Megathermal, the environment for foxtail millet and broom millet was suitable from the eastern segment of the Qilian Mountains to Lhasa. This study provides a reference for exploring the distribution pattern of agricultural land use in the early period of agricultural production in China and provides useful information for agricultural archaeology.

Spatial patterns of vineyard landscape evolution and their impacts on erosion susceptibility: RUSLE simulation applied in Mercurey (Burgundy, France) since the mid-20th century

Erosion susceptibility in vineyards is approximately one order of magnitude above the reference level calculated for all agricultural activities, and preventing soil erosion is thus one of the most important environmental issues in vineyards. Spatially explicit models are necessary to address the coevolution of erosion susceptibility and anthropogenic practices because of the heterogeneous spatial patterns of erosion within vineyards. In this paper, we apply the RUSLE model to assess erosion susceptibility through time in a Burgundy vineyard (Mercurey) at a catchment scale (15 km²). The model is first calibrated with data acquired in 2015-2018. Second, erosion susceptibility during former stages (1953 and 1984) is compared to current reference frame. Such theoretical comparison considers that both C (land cover) and LS (Length-Slope) factors evolved through time. We hypothesize that such factors reveal both the land use evolution (especially agricultural land uses) and the development of a soil erosion management strategy based on the collection of sediments using roads, hedges and ditches. The current reference frame of erosion susceptibility calculated at catchment scale is about 9,152 t.yr-1. In the early 1980s a peak in erosion susceptibility is concomitant with vineyard expansion during the second half of the 20th century. Erosion susceptibility in vine parcels in 1984 is estimated to be 32% higher than current period. In the mid-20th century the spatial patterns of agricultural land use (patchwork of grasslands and vines, vines on moderately-rugged hillslopes) led to moderate rates of erosion susceptibility. At this stage, past level of erosion susceptibility is estimated to be 40% lower than current reference frame.

Could PES Change the Agrarian Structure? a Lesson Learned of Citaman Village, Banten

This study aimed to analyze changes in the agrarian structure in Citaman Village, whether or not capitalists enters the formation of community land, after payment for Environmental Services (PES) mechanism is effective. This research relies on the constructivism paradigm, using qualitative method. The primary data was collected through in-depth interviews and focus groups discussion, with farmer groups, community leaders and related parties. Relevant secondary data was also collected. The results show that: First the PES program which has been running for more than 15 years, has not changed the agrarian structure significantly in Citaman Village. The agricultural land is still dominantly controlled and owned by Citaman Village residents. Second the changes that occurred as a PES program were found in the patterns of agricultural land use. Agricultural land that was originally used for upland rice cultivation or huma is now turned into an agroforestry area.

The framework of an agricultural land-use decision support system based on ecological environmental constraints

Agricultural land use is a complicated systems engineering. Modern agriculture faces increasingly more risks. Managers should obtain reliable information to assist in decision-making through certain methods that allow them to achieve an economic, social, and ecological environment that is crucial in coordinating the development of agricultural land-use patterns. This study proposes a framework of an agricultural land-use decision support system (LDSS) based on ecological environmental constraints according to the DSS design philosophy, which provides a scientific basis for managers to allocate land resources. This framework of LDSS consists of a land quality assessment module, an eco-economic coupling module, and a land-use optimisation module. Firstly, it establishes a natural-society-economic land quality evaluation system to simulate the comprehensive benefit relationship of land use. Secondly, it analyses the risks of soil, water, and ecological security in the process of land use; simulates and reveals the mechanism of occurrence; and completes the correlation equation expression between natural-economic-social indictor and land use risk. Based on different scenarios design, the ecological environmental risk factors are used as constraints. Finally, the multi-objective linear programming method is employed to calculate the optimal comprehensive benefits of land use and optimal land-use structure based on the constraints of the ecological environment. Then the study takes Changsha County, a high-intensification, main grain-producing area in Central and South China, as a case area to demonstrate the feasibility of the framework of LDSS, and draws the highest comprehensive benefits and optimal structure of land use under the premise that the rural ecological environment conforms to national standards. Case study shows that the LDSS framework is feasible, easy to operate, and easy to promote. The research results can provide efficient and practical support for managers to allocate land resources and formulate sustainable land-use policies rationally.

Mapping Agricultural Landuse Patterns from Time Series of Landsat 8 Using Random Forest Based Hierarchial Approach

Increase in irrigated area, driven by demand for more food production, in the semi-arid regions of Asia and Africa is putting pressure on the already strained available water resources. To cope and manage this situation, monitoring spatial and temporal dynamics of the irrigated area land use at basin level is needed to ensure proper allocation of water. Publicly available satellite data at high spatial resolution and advances in remote sensing techniques offer a viable opportunity. In this study, we developed a new approach using time series of Landsat 8 (L8) data and Random Forest (RF) machine learning algorithm by introducing a hierarchical post-processing scheme to extract key Land Use Land Cover (LULC) types. We implemented this approach for Mashhad basin in Iran to develop a LULC map at 15 m spatial resolution with nine classes for the crop year 2015/2016. In addition, five irrigated land use types were extracted for three crop years—2013/2014, 2014/2015, and 2015/2016—using the RF models. The total irrigated area was estimated at 1796.16 km2, 1581.7 km2 and 1578.26 km2 for the cropping years 2013/2014, 2014/2015 and 2015/2016, respectively. The overall accuracy of the final LULC map was 87.2% with a kappa coefficient of 0.85. The methodology was implemented using open data and open source libraries. The ability of the RF models to extract key LULC types at basin level shows the usability of such approaches for operational near real time monitoring.

A simulation–optimization modeling approach for watershed-scale agricultural N2O emission mitigation under multi-level uncertainties

In this research, an integrated simulation–optimization modeling approach (ISOMA) was developed for supporting agricultural N2O emission mitigation at the watershed scale. This approach can successfully combine soil N2O emission simulation and the consequential mitigation management within a general modeling framework. Also, uncertainties associated with the key soil parameter can be effectively reflected and addressed through adoption of Monte Carlo analysis for the simulation results. The Monte Carlo simulated results were then used to generate fuzzy membership functions that can be consequentially used for emission mitigation management, reflecting the combined uncertainties for N2O emission simulation and mitigation management. The developed ISOMA was then applied to a reservoir watershed in Miyun county of Beijing municipality. In the studying watershed, the simulation model was calibrated and verified. Then, N2O emission from multiple agricultural land-use patterns were predicted. The amounts of N2O emission of four land use patterns (i.e., cash tree, orchard, cropland, and natural forest) were (536.9, 590.8, 653.1), (237.7, 254.4, 275.9), (79.5, 100.7, 105.1), (33.0, 47.3, 61.1) kg CO2 eq ha−1 year−1, respectively. Two scenarios (i.e., G1 and G2) were set up according to development priorities of local economy and society. Meanwhile, multiple credibility levels were considered according to the risk of N2O emission. The land use patterns could be adjusted according to solutions of ISOMA. The developed methods could help regional manager choose various production patterns with cost-effective agriculture N2O emission management schemes in the Miyun reservoir watershed. The manager also can obtain deeply insights into the tradeoffs between agricultural benefits and system reliabilities.

Agricultural land-use change in Kerala, India: Perspectives from above and below the canopy

Abstract Despite the availability of a wide range of tools, measuring and explaining changes in land cover and land use in tropical regions can be extremely challenging. Kerala, India, is a biodiversity hotspot with a high population density and a long history of complex agricultural land-use patterns. Some reports suggest that agriculture in Kerala, which historically is rice paddy-wetland and agroforestry-based, is on the decline. However, the evidence is often anecdotal, especially with regards to smallholding homegarden agriculture. In this study we employ mixed methods, including remote sensing, quantitative household surveys, and semi-structured interviews, to unravel the complex land-cover and land-use changes occurring in Kerala. Results indicate that, from a land-cover change perspective, agroforests are in dynamic equilibrium with other land covers, being cleared for roads and new buildings, but offset by the expansion of younger, less diverse agroforests into paddy wetlands. Yet beneath the canopy, agroforests are undergoing rapid land-use change not discernible using remote sensing. These changes include a reported decrease in the cultivation of 80% of Kerala’s primary crop species during 2003–2013, alongside a dramatic decline in chickens (from 12.5 to 2.6 per homestead on average) and cows (from 1.7 to 0.8). Over this period, no crop increased in cultivation. According to farmers, the primary drivers of this shift were declining profitability of agriculture in Kerala, labour shortages, unreliable weather, unfamiliar pests and diseases, and government policy. Despite the undeniable move away from agricultural activity in homegardens, we conclude that these ecologically and culturally important systems are not disappearing, but rather evolving to meet the needs of a less agricultural Kerala. Our research highlights the value of using mixed methods for characterizing land-use and land-cover histories in tropical regions.

Patterns of land use, extensification, and intensification of Brazilian agriculture

Sustainable intensification of agriculture is one of the main strategies to provide global food security. However, its implementation raises enormous political, technological, and social challenges. Meeting these challenges will require, among other things, accurate information on the spatial and temporal patterns of agricultural land use and yield. Here, we investigate historical patterns of agricultural land use (1940-2012) and productivity (1990-2012) in Brazil using a new high-resolution (approximately 1km(2) ) spatially explicit reconstruction. Although Brazilian agriculture has been historically known for its extensification over natural vegetation (Amazon and Cerrado), data from recent years indicate that extensification has slowed down and was replaced by a strong trend of intensification. Our results provide the first comprehensive historical overview of agricultural land use and productivity in Brazil, providing clear insights to guide future territorial planning, sustainable agriculture, policy, and decision-making.

Analysing Data of the Integrated Administration and Control System (IACS) to Detect Patterns of Agricultural Land-Use Change at Municipality Level

European landscapes have featured considerable changes towards intensification and marginalisation. These major trends are expected to continue in the future. Besides, the cultivation of bioenergy crops has become an important factor in agricultural land use. A thorough understanding of land-use processes for management purposes is needed. In this study, the spatial and temporal pattern of agricultural land use and land-use change was classified at the scale of municipalities from 2005 to 2010. The study region was the German federal state Hesse. By using data of the Integrated Administration and Control System (IACS) of the European Union and with the help of k-means cluster analysis, five types of agricultural land-use patterns and dynamics (TLPDs) were detected. These TLPDs represent different sub-regions. Sub-regions with favourable physical conditions for cultivation are dominated by arable land. A progressive land-use change occurred by conversion of grassland to arable land. In sub-regions, where physical conditions are rather unfavourable, especially in mountainous areas, grassland is the predominant land use. But on the remaining arable land, there is a slight change in favour of maize. The knowledge of sub-regions with spatially and temporally different agricultural land use could be utilised to develop land management instruments like site-specific agri-environmental schemes.

An economic theory-based explanatory model of agricultural land-use patterns: The Netherlands as a case study

An economic theory-based land-use modelling framework is presented aiming to explain the causal link between economic decisions and resulting spatial patterns of agricultural land use. The framework assumes that farmers pursue utility maximisation in agricultural production systems, while considering alternative production options and making land-use decisions. Local utility is assumed to depend on a complex combination of different types of factors that together set the opportunities and constraints for different production options. The framework's ability to reproduce the current patterns is demonstrated for a case study in the Netherlands. The framework was implemented in a land-use modelling simulation tool rooted in economic theory, that was first specified according to the current trends in the driving forces assumed to steer land-use change. Alternative model specifications accounting for different sets of cash flows were implemented in order to explore the importance of uncertainties on model conceptualisation and structure. The allocation of agricultural land use was then simulated according to these specifications and the results were validated by comparing the simulated land-use patterns with observed ones. When cash flows accounting for path-dependency and land-use inertia were considered, the framework performed well in reproducing current patterns in the Netherlands, with a degree of correspondence of 82.2% in the pixel-by-pixel validation, up to 87.4% in the multiple resolution validation. Production costs and gross revenues seem to only partly explain the observed patterns, as shown by the lower degrees of correspondence (57.5% up to 65.0%) for the model specification solely accounting for these cash flows. In our case study, transportation costs did not seem to play a significant role in the allocation of agricultural land use, although that might be attributed to the relatively small size of the study area and the existence of a high-quality transport network. The model did not perform equally well for different production systems: land-uses specified at the crop level appeared to be particularly well allocated; those defined at the aggregated production system level performed poorer. The ability to link economic decision-making processes with the resulting agricultural land-use patterns, while incorporating complex interactions with different type of factors, implies that a coherent modelling approach for the simulation of future patterns of agriculture land use was established. This approach can be used to help policy-makers explore possible future socio-economic and environmental impacts resulting e.g. from climate change and/or policy reform, allowing them to devise strategies to cope with future challenges in agricultural systems.

Associating conservation/production patterns in US farm policy with agricultural land-use in three Iowa, USA townships, 1933–2002

Agricultural policy objectives in developed nations include counteracting overproduction, increasing economic and social well-being, and environmental protection. Such policies, however, often work at cross-purposes. While vast financial resources have been invested in farm programs, little research connects historic trends in agricultural policy with land-use patterns in agricultural landscapes. We connect the legislative history of US farm bills with land-use decisions as observed on the historical agricultural landscape in three townships in Iowa, USA, 1933–2002. With a high proportion of agricultural land, increasing biofuels development, and high participation in federal conservation programs, Iowa presents an ideal case study to explore the relationship between policy and historical land use. Using data from the US Census of Agriculture and historical aerial photography, we conduct our analysis within a framework that identifies alternating eras of US farm policy in terms of legislative focus on conservation vs. production. We describe the impact of US farm policy on the following indicators: maize and soybean area, production, and productivity; hectares in idled land, pasture, and hay ground; and adoption of soil conservation practices. Patterns of agricultural and conservation land use support the idea of alternating conservation–production eras of US farm policy. Three important patterns emerge: (1) despite reductions in maize hectares that correspond with conservation-oriented policy eras, supply management policies have failed to control maize production due to increased productivity; (2) as pasture and hay hectares decline, government set-aside programs are increasingly important for perennial vegetation within agricultural landscapes; and (3) although soil conservation practices have generally increased as agricultural land use has intensified, persistent links between poor environmental quality and farm programs suggest that implementation alone will not achieve environmental quality goals. Environmental improvement likely requires a shift from policies focused on the quantity of commodities produced to policies focused on pattern and process of production in multifunctional agricultural landscapes, and we discuss how policies that promote extensification abroad might inform domestic agricultural policy reform.

Spatio-Temporal Transformation in Agricultural Land-Use Pattern in Karachi Using Geo-Spatial Techniques: A Case Study along West Bank of Malir River

The study attempts to investigate spatio-temporal transformation along the west bank of Malir River in Karachi between 2005 and 2013, using geo-spatial techniques. The major objective of this study is to find out the changes occurring in the pattern of land use along Malir River in various administrative units of Karachi division. The study indicates changes in agricultural land during the period covered by the study. These changes which are all related to agricultural land are mainly explained by transformation occurring in terms of various land-use.Due to the unavailability of statistical data at grass root level, primary data have been collected from imageries to obtain different land-use categories. The results show that considerable changes have been witnessed in the entire study area. This kind of research is very useful for all agricultural areas around major cities of the Asia and Africa in terms of land-use change detection.

English

In the past two decades, population-environment research has focused on the hypothesis that house hold population has significant influence on agricultural land-use patterns and the health of the environment. This study is therefore aimed at providing land use planners in Nigeria with basic data and information that will be useful in identifying the prospects for and constraints to intensive cultivation systems in Obagaji area. The simple random sampling technique, using the table of random digits and availability sampling method were respectively employed to select settlements and farmers for investigations. Structured interview was utilized to generate data for the study. In order to capture the inputs to land in the study area, the level of agricultural land-use intensity was measured, using three surrogates, namely, proportion of farmland cultivated, frequency of cultivation and crop combination level. The study results showed that Obagaji area is a mixed cropping region where semi permanent cultivation with rotational bush fallow system dominates the existing cultivation systems. The characteristic features of agricultural practices in households with low number of family members in the area are: more extensive land-use systems, more of shifting elements than permanent cultivation, only very small proportion of land is under cultivation at any one time and very short cropping period on the field. The reverse is true for households with high number of family members. The direct variation in intensity of agricultural land use with regards to family size in the area is significant. Key words: Obagaji area, agricultural land, family size, farm labour.