Search

Rational construction of a well-facilitated farmland become necessary for food security and modern agriculture in China. In farmland construction, the automatic management of spatial data can benefit to accurately distinguish well-facilitated farmland from the various land types. Various discriminating ways of well-facilitated farmland are adopted due to the different influence factors of agricultural production in in different regions, where the spatial distribution and structural features of well-facilitated farmland are quite different from place to place across the country. Most of the previous studies focus mainly on policies, benefit evaluation, preliminary planning and design in the well-facilitated farmland construction. There is still lacking on the studies of the discrimination and analysis for the regional structural features of the well-facilitated farmland. In this paper, a framework of an index system was constructed to identify the spatial distribution and structural features of the well-facilitated farmland using the law of spatial differentiation together with the related national standards and strategic planning, ranging from the scale and shape of farmlands, irrigation and drainage facilities, traffic accessibility, and farmland protection ratio. The identifying system was designed on the basis of the index framework with C#. NET and Arc Object. Subsequently, the proposed system was verified for its availability by taking a case study of a Loess Plateau and a southern mountainous region. The results were as follows: (1) In the Loess Plateau area, the standard rate of the farmland scale, farmland shape, irrigation and drainage facilities, traffic accessibility was 87.01%, 83.12%, 80.52%, 90.91% and 83.12%, respectively. The well-facilitated farmland area can be identified by the system was 38.33 hm² with the total discriminating precision was 94.38%. There were some farmlands that did not meet the requirements of the well-facilitated farmland, such as incomplete irrigation and drainage facilities, the irregular shapes of the fields that distributed in the branch furrow and furrow head around the farmland. (2) In the southern mountainous area, the standard rate of all spatial features was 100%. The well-facilitated farmland area that identified by the system was 30.07 hm², which was 10.34 hm² higher than that of the state-approved well-facilitated farmland. The high identified areas can be because some fields that meet the requirements of well-facilitated farmland have not been classed as the permanent basic farmland in some administrative regions. When regardless of this classification, the total discrimination precision was 100%. This index system can be used in different scenarios, such as macro monitoring and evaluation, project design and inspection of the well-facilitated farmland. This system was also applied for the Northeast Plain, North China Plain, Loess Plateau and southern mountainous regions, while the key elements of the spatial features of well-facilitated farmland construction can be detected with a reliable discriminant resolution. When combining with the remote sensing technology, the index system can help automatic management to know the real-time spatial data of well-facilitated farmland construction. Therefore, the developed system can be successfully applied to identify the extract well-facilitated farmland in the construction area, and then to analyze the obtained spatial data in real time, finally to implement automatic management for well-facilitated farmland construction. Furthermore, the proposed system in this paper can offer a promising reference to the current comprehensive supervision platform, and improve the management effectiveness of well-facilitated farmland construction in modern agriculture. [ABSTRACT FROM AUTHOR]

Understanding the historical change trajectory of Land Use/Land Cover Change (LUCC) is helpful to analyze the land use trends under the interference of human activities and changes in the natural environment, thereby helping decision makers to eliminate the negative impact of unreasonable land use patterns to the greatest extent. Yellow River Basin is the fifth longest river in the world, its ecological environment continues to deteriorate due to the rapid population growth and urban expansion, which has become one of the regions with the most serious soil erosion in China. Aiming to promote the ecological quality and high-quality development of social economy under the human interference and natural environment change, we analyzed the spatiotemporal dynamic of the LUCC in the Yellow River Basin (Henan section) from the watershed scale and proposed policy recommendations. We introduced the chord diagram visualization model to intuitively show the flow, direction and diversity of land cover changes, which would enrich the visual research method system of the land cover quantity transfer trajectory. The land use change index, chord diagram model and gravity center transfer model were used in this paper to analyze the spatial-temporal evolution trajectory and policy implications of the land use pattern in the Yellow River Basin (Henan section) in the past 30 years based on the land use remote sensing data in 1990, 2000, 2010 and 2018. The results showed that: 1) Ecological conservation land (35%) was mainly concentrated in the mountainous areas with higher elevation in the middle reaches; food security land (55%) and production and living land (10%) were mainly distributed in the central and eastern plains. 2) The outflows and inflows of dry land from 1990 to 2018 showed significant dominance; paddy field, water and grassland were dominated by outflow; urban land, rural settlements and other construction land were dominated by inflow. 3) The land use change in central cities had significant regional driving effects throughout the period. 4) The gravity center of food security land and ecological conservation land moved to the West and the area showed a decreasing trend, which proved that the high-quality cultivated land in the plain area in the lower reaches decreased and the ecosystem service function gradually weakened; The shift of gravity center of urban land to the East indicated that the social and economic development in the lower reaches were gradually active. The shift of gravity center of rural residential and other construction land to the West indicated that the population scale in the middle reaches was gradually increasing. [ABSTRACT FROM AUTHOR]

Evolution of cultivated land needs to be clarified in the driving mechanism for the sustainable land use in China. Most studies generally focused on the relationship between the evolutionary data and the driving mechanism in the evolution of cultivated land use. However, research on the drivers of marginal impact is rare, such as the spatial factor density that represented by the POI points. There can be a tipping point of marginal impact, when the quantity reaches a specific region, in the distance to the main road represented by the human factors. In this paper, the marginal effect analysis was used to make a preliminary evaluation, taking Southern Hubei as an example. Landsat remote sensing images were selected for the interpretation data of three periods from the year of 2000-2005, 2005-2010 and 2010-2015, including 15 types of POI spatial data. Firstly, the evaluation system of spatial factors was constructed from three aspects, including Euclidean distance indices, POI kernel density indices and locational indices. The Spatio-temporal evolution of cultivated land was systematically analyzed, together with dynamic change in the area from 2000 to 2015. Secondly, the principal component analysis was used to integrate the driving factors for the change of cultivated land. The extracted principal components were selected to construct the multiple Logistic regression models, including interaction terms. Lastly, an emphasis was put on the bidirectional marginal effect of spatial elements in the driving mechanism, and the change rule that illustrated by the graph of marginal effect. The results indicated that: (1) The evolution types of cultivated land showed the agglomeration of the same type, while the specific conversion type strongly depended on the spillover effect of neighboring land use. There was obvious evolution trend from cultivated land to construction, but others were not, possibly due to the influence from the macro-control policy of land use. From 2000 to 2015, the proportion of cultivated land converted to construction land increased from 28% to 44%, and then jumped to 96%, mainly concentrated in areas around towns and along major roads. (2) Marginal effects of spatial factors depend on types of cultivated land and periods. From 2000 to 2015, there was a gradual decrease in the variation range of marginal effect for different conversion types of cultivated land, while the homogeneous intersection point moved in the same direction for marginal effect curves of different transformation types. The dominated marginal effect of natural location factors was on the conversion of cultivated land to construction land, and cultivated land to water area, when the spatial elements of POI were different values. (3) The curve of spatial factors implied that there was a critical value of marginal effect. In the range of critical values, marginal effect changed significantly with the spatial factors, but outside the range, marginal effect tended to be stable. The qualitative and quantitative analysis on the marginal effect of spatial factors can offer a theoretical reference for the optimization of cultivated land layout, and the formulation of regional coordinated development strategy. [ABSTRACT FROM AUTHOR]

In order to ensure China's food and ecological security, it's particularly necessary to perform desertification monitoring and early warning during the land consolidation projects execution. The study area was located in Kezuohouqi which is famous for the sandy land. Based on Landsat 8 OLI image data, desertification monitoring was achieved by the decision tree classification method. The desertification early warning system was constructed by PSR (pressure-state-response) model; the natural and human influencing factors of desertification were regarded as "pressure", the desertification monitoring results were regarded as "state", and the land consolidation projects were regarded as "response". The weight of each factor in the PSR model was set by expert scoring method, and DESI (desertification ecological security index) was adopted in this paper; the greater the index, the lower the risks of desertification. Based on the DESI, the results of desertification early warning were divided into 4 different levels through natural breakpoint method, namely, no desertification warning, slight desertification warning, medium desertification warning and severe desertification warning. In the end, the validity of land consolidation could be evaluated through calculating the area of different desertification early warning results in the land consolidation projects and conducting the comparison. The results showed that: 1) The area of desertification accounted for 88% of study area. To be exact, the area of medium and severe desertification accounted for 61% of the total area, and the extremely severe desertification was mainly concentrated in the western part of the study area whose area accounted for 6% of the total area. 2) The zonal differentiation of desertification early warning results was clear; the spatial distribution from east to west in Kezuohouqi in turn was no desertification warning, medium desertification warning, slight desertification warning, medium desertification warning, severe desertification warning, and then medium desertification warning. The area of medium desertification warning was the largest, and the distribution laws of severe warning desertification and extremely severe desertification were similar, but the severe warning desertification tended to gather in the northwest pastoral areas of Kezuohouqi, the slight warning and no warning areas were located in the eastern part of Kezuohouqi, and the land use pattern was mainly agricultural land. 3) In the land consolidation projects, high quality capital farmland construction and arable land consolidation were mainly distributed in the areas with no desertification warning. The potential land suitable for agriculture and the project of land reclamation were mainly distributed in slight desertification warning area and medium desertification warning area. There was the sever desertification warning land among the farmland consolidation, the potential land resources suitable for agriculture, and forage grass base construction projects, whose distribution style was sporadic. However, the severe desertification warning area in high quality capital farmland was not up to the mark and should be eliminated from the projects. Overall, in the context of land consolidation, the risk of further desertification is small. The severe desertification warning area would be a key point for land consolidation projects, and the government must put a high premium on the sever warning area. The results of desertification early warning in this paper can provide the reference for land consolidation and adjustment. [ABSTRACT FROM AUTHOR]

The livability evaluation of living space was an important topic, which had important guiding significance for improving the livability of living space.This study aimed to explore the theoretical logical relationship between the multi-function of land use and livability of living space, and make use of the research about multi-function of land use for the optimization practice of livability of living space. So, this paper discussed the theoretical logical relationships between multiple functions of land use and livability of living space from the perspective of human needed products and services supplied by land use, and the evaluation index system was built based on the relationship and previous research. And then, the scheme of index spatialization was designed based on the technology of geographical information system(GIS) and remote sensing(RS). At the same time, multi-source data like remote sensing, survey, statistical and other spatialdataset were integrated by analytic hierarchy process (AHP) to quantify the spatial distribution of living space in ZhangbeiCounty, Hebei Province. The results showed that the livability of living space in ZhangbeiCounty presented the trend that the high value center was concentrated in the ZhangbeiTown and the subcenterwas distributed in Ertai-ShagouTown. The living space area above relatively strong levelwas only 2.42% of all county area.The spatial distribution characteristics of 3 types of land use were significantly difference;livingbearing function presented a trend like network distribution takingmain traffic trunk line as high value axis and ZhangbeiCounty as high value center. Living support function presented 2 groupsof high value centerscontaining the ZhangbeiTownand the north of YoulougouTown, and Ertai-shagouTown. The high value center of mental purification function was distributed in the ZhangbeiTown and the subcenterwas distributed in the area along the southwest of ZhangbeiTown to DaheTown and Ertai-shagouTown. There was a large difference in the distribution of livability between towns and villages. Most of the areas of livability space in town land were above the moderate level, especially, the area the livability level of which belonged to the higher and highest accounted for 78.37% of the total area of the town land, and meanwhile, accounted for 74.94% of the total area with higher and highest level of living space. This area was mainly distributed in the town of Zhangbei, Ertaiand Shagou, and YoulougouVillage. Most of the livability areas in rural land were under the moderate level, and the area oflower and lowest level accounted for 78.39% of the total area of the rural land, whatwas more, accounted for 95.32% of the total area with lower and lowest level of living space. This area was mainly concentered in the town ofHailiutu, Erquanjing, Dahe, Danjinghe, and Liangmianjing. The spatial difference of the functional elements of land use was the main reason to the difference in livability of living space. So, according to the above results, some conclusions can be drawn in this research. The villages, which containlarge lower and lowest livability space area, are the key areas of primary concern inthe implementation process of the“Revitalizing the countryside” strategy; what’s more, the theory and method of land use multi-function can be applied to the study of livability evaluation of living space. [ABSTRACT FROM AUTHOR]