scholarly journals Distribution of agricultural lands and land ownership in Russia

2021 ◽  
Vol 68 (4) ◽  
pp. 961-975
Author(s):  
Ivan Ryazantsev ◽  
Anna Ivolga

Among the countries of the world, Russia is one of the richest in agricultural land. However, a quantitative advantage is poorly transformed into a qualitative one. As a result, there has been a gradual decrease in productive land, a decline in crop yields, the use of highly productive lands as less valuable land categories, and land degradation. These negative processes cause severe damage to both the agricultural sector and the country's economy as a whole. One of the reasons for such drawbacks is the underdevelopment of land use processes and forms of land ownership, which discourage land productivity growth and rational use of agricultural lands. In this paper, the authors analyze the most critical challenges in the sphere of agricultural land distribution in Russia and suggest ways to improve the efficiency of land ownership and land use patterns.

2019 ◽  
Vol 8 (1) ◽  
pp. 87-91
Author(s):  
Bhanu Priya Chouhan ◽  
Monika Kannan

The world is undergoing the largest wave of urban growth in history. More than half of the world’s population now lives in towns and cities, and by 2030 this number will swell to about 5 billion. ‘Urbanization has the potential to usher in a new era of wellbeing, resource efficiency and economic growth. But due to increased population the pressure of demand also increases in urban areas’ (Drakakis-Smith, David, 1996). The loss of agricultural land to other land uses occasioned by urban growth is an issue of growing concern worldwide, particularly in the developing countries like India. This paper is an attempt to assess the impact of urbanization on land use and land cover patterns in Ajmer city. Recent trends indicate that the rural urban migration and religious significance of the place attracting thousands of tourists every year, have immensely contributed in the increasing population of city and is causing change in land use patterns. This accelerating urban sprawl has led to shrinking of the agricultural land and land holdings. Due to increased rate of urbanization, the agricultural areas have been transformed into residential and industrial areas (Retnaraj D,1994). There are several key factors which cause increase in population here such as Smart City Projects, potential for employment, higher education, more comfortable and quality housing, better health facilities, high living standard etc. Population pressure not only directly increases the demand for food, but also indirectly reduces its supply through building development, environmental degradation and marginalization of food production (Aldington T, 1997). Also, there are several issues which are associated with continuous increase in population i.e. land degradation, pollution, poverty, slums, unaffordable housing etc. Pollution, formulation of slums, transportation congestion, environmental hazards, land degradation and crime are some of the major impacts of urbanization on Ajmer city. This study involves mapping of land use patterns by analyzing data and satellite imagery taken at different time periods. The satellite images of year 2000 and 2017 are used. The change detection techniques are used with the help of Geographical Information System software like ERDAS and ArcGIS. The supervised classification of all the three satellite images is done by ERDAS software to demarcate and analyze land use change.


2021 ◽  
Vol 6 ◽  
pp. 1-24
Author(s):  
Christian F. Cloke 

Between 1984 and 1990, the Nemea Valley Archaeological Project (hereafter NVAP), systematically surveyed the Nemea, Asopos, and Longopotamos Valleys, around Nemea, Phlious, and Kleonai in the northeastern Peloponnesos (Figure 1).1 This survey, covering an area of roughly 80 square kilometers, was for its time cutting-edge, both in its intensive approach to surveying the totality of the walkable landscape, and its use of computers for recording and mapping finds.2 The fieldwalking and record-keeping methods employed, which treated individual artifacts as the basic units of analysis, have produced a robust dataset for evaluating settlement patterns, agricultural land-use, and other past human activities within their ecological, economic, social, and historical contexts. This chapter examines the NVAP survey territory and considers the contributions of intensive pedestrian survey to the crafting of a medium- to long-term history of the Greek countryside from the Archaic to Late Roman periods. Through detailed analyses of survey finds’ physical properties and spatial distribution, I assess past settlement patterns and agricultural methods, consider the dynamics of regional production and consumption of ceramics and other goods, and elucidate a range of activities carried out at rural sites.


2017 ◽  
Vol 08 (01) ◽  
pp. 1750005 ◽  
Author(s):  
KATHERINE CALVIN ◽  
MARSHALL WISE ◽  
PAGE KYLE ◽  
LEON CLARKE ◽  
JAE EDMONDS

We report results of a “hindcast” experiment focusing on the agricultural and land-use component of the Global Change Assessment Model (GCAM). We initialize GCAM to reproduce observed agriculture and land use in 1990 and forecast agriculture and land use patterns on one-year time steps to 2010. We report overall model performance for nine crops in 14 regions. We report areas where the hindcast is in relatively good agreement with observations and areas where the correspondence is poorer. We find that when given observed crop yields as input data, producers in GCAM implicitly have perfect foresight for yields leading to over compensation for year-to-year yield variation. We explore a simple model in which planting decisions are based on expectations but production depends on actual yields and find that this addresses the implicit perfect foresight problem. Second, while existing policies are implicitly calibrated into IAMs, changes in those policies over the period of analysis can have a dramatic effect on the fidelity of model output. Third, we demonstrate that IAMs can employ techniques similar to those used by the climate modeling community to evaluate model skill. We find that hindcasting has the potential to yield substantial benefits to the IAM community.


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