Spatiotemporal patterns in urbanization efficiency within the Yangtze River Economic Belt between 2005 and 2014

The question of how to generate maximum socio-economic benefits while at the same time minimizing input from urban land resources lies at the core of regional ecological civilization construction. We apply stochastic frontier analysis (SFA) in this study to municipal input-output data for the period between 2005 and 2014 to evaluate the urbanization efficiency of 110 cities within the Yangtze River Economic Belt (YREB) and then further assess the spatial association characteristics of these values. The results of this study initially reveal that the urbanization efficiency of the YREB increased from 0.34 to 0.53 between 2005 and 2014, a significant growth at a cumulative rate of 54.07%. Data show that the efficiency growth rate of cities within the upper reaches of the Yangtze River has been faster than that of their counterparts in the middle and lower reaches, and that there is also a great deal of additional potential for growth in urbanization efficiency across the whole area. Secondly, results show that urbanization efficiency conforms to a “bar-like” distribution across the whole area, gradually decreasing from the east to the west. This trend highlights great intra-provincial differences, but also striking inter-provincial variation within the upper, middle, and lower reaches of the Yangtze River. The total urbanization efficiency of cities within the lower reaches of the river has been the highest, followed successively by those within the middle and upper reaches. Finally, values for Moran’s I within this area remained higher than zero over the study period and have increased annually; this result indicates a positive spatial correlation between the urbanization efficiency of cities and annual increments in agglomeration level. Our use of the local indicators of spatial association (LISA) statistic has enabled us to quantify characteristics of “small agglomeration and large dispersion”. Thus, “high- high” (H-H) agglomeration areas can be seen to have spread outwards from around Zhejiang Province and the city of Shanghai, while areas characterized by “low-low” (L-L) patterns are mainly concentrated in the north of Anhui Province and in Sichuan Province. The framework and results of this research are of considerable significance to our understanding of both land use sustainability and balanced development.     

Spatial non-stationary characteristics between grass yield and its influencing factors in the Ningxia temperate grasslands based on a mixed geographically weighted regression model

Spatial models are effective in obtaining local details on grassland biomass, and their accuracy has important practical significance for the stable management of grasses and livestock. To this end, the present study utilized measured quadrat data of grass yield across different regions in the main growing season of temperate grasslands in Ningxia of China (August 2020), combined with hydrometeorology, elevation, net primary productivity (NPP), and other auxiliary data over the same period. Accordingly, non-stationary characteristics of the spatial scale, and the effects of influencing factors on grass yield were analyzed using a mixed geographically weighted regression (MGWR) model. The results showed that the model was suitable for correlation analysis. The spatial scale of ratio resident-area index (PRI) was the largest, followed by the digital elevation model, NPP, distance from gully, distance from river, average July rainfall, and daily temperature range; whereas the spatial scales of night light, distance from roads, and relative humidity (RH) were the most limited. All influencing factors maintained positive and negative effects on grass yield, save for the strictly negative effect of RH. The regression results revealed a multiscale differential spatial response regularity of different influencing factors on grass yield. Regression parameters revealed that the results of Ordinary least squares (OLS) (Adjusted R² = 0.642) and geographically weighted regression (GWR) (Adjusted R² = 0.797) models were worse than those of MGWR (Adjusted R² = 0.889) models. Based on the results of the RMSE and radius index, the simulation effect also was MGWR > GWR > OLS models. Ultimately, the MGWR model held the strongest prediction performance (R² = 0.8306). Spatially, the grass yield was high in the south and west, and low in the north and east of the study area. The results of this study provide a new technical support for rapid and accurate estimation of grassland yield to dynamically adjust grazing decision in the semi-arid loess hilly region.     

遥感反演土壤蒸发/植被蒸腾二层模型在华北地区的应用

利用一种可操作的地表蒸散遥感反演二层模型,以我国华北平原为研究区,选择2004年的3月至6月华北地区主要农作物冬小麦的生长季节作为研究时段,利用MODIS遥感卫星数据,结合地面130多个气象台站的空气温湿度实测数据,实现了土壤蒸发和植被蒸腾的反演。采用国家生态网络禹城综合试验站利用涡度相关系统观测的地表总蒸散半小时平均的数据进行了模型验证,结果表明模型估算的地表可利用能量与地面实测数据的相关系数可以达到0.92,均方差为30.4w.m^-2;模型估算的地表总蒸散值与地面实测数据的相关系数为0.85,均方差为21.3 w.m^-2,由此证明了模型的可用性。     

基于作物空间分配模型的东北三省春玉米时空分布特征

利用1980-2010 年东北三省分县玉米播种面积与产量统计、耕地分布、农业灌溉分布以及作物适宜性分布等多源数据,结合基于交叉信息熵原理的作物空间分配模型（Spatial Production Allocation Model,SPAM）,在5'×5'的像元尺度模拟了春玉米种植面积与产量的时空分布,并重点分析了两者在纬向、经向,以及高程上的时空变化规律。结果显示：（1）玉米种植面积在2000 年前向北扩展至北纬44°~48°间,2000 年后在中南部出现大规模发展（北纬42°~44°）,并进一步向东扩展至东经123°~127°间,同时还表现为向低海拔（高程100 m以下）和较高海拔（高程200~350 m）扩展的态势;（2）单产在纬向上的增加区主要集中在北纬42°~48°,经向上的单产增加则相对均匀,高程上单产提升区主要集中在海拔350 m以下。（3）像元内玉米种植比例整体上由中低种植比例为主逐步演变为中高比例占据主体,并且中高种植比例像元对应的玉米单产水平整体上较高,反映了市场经济驱动下的玉米种植集聚化和规模化的发展趋势。     

History and necessity: the evolution of soil conservation technology in a Jamaican farming system

The soil conservation campaigns that have been a prominent feature of Jamaican agricultural policy since the 1950s are frequently presented as having failed to ameliorate the problem of soil erosion in hillside agriculture. A case study of a small farming community in the Blue Mountains explores the development of the soil conservation practices currently employed by farmers. The use of trash barriers in carrot farming is described and the origins of this technology and its subsequent adaptation are considered. The study concludes that extension interventions and government policy have influenced the development of current soil conservation practices; practices which have their roots in indigenous techniques. Other factors such as the adaptation of trash barriers to suit local conditions and their importance in soil fertility management also play a role in their widespread use in the study area. The study demonstrates that to understand the process of technical change in farming communities, it is necessary to consider a range of factors, external and internal, technical and social, that have over time influenced farmers' decision making.     

Spatial variability of soil moisture content and its relation to environmental indices in a semi-arid gully catchment of the Loess Plateau, China

The degree of spatial variability of soil moisture and the ability of environmental attributes to predict that variability were studied at the Da Nangou catchment (3·5 km²) in the semi-arid loess area of China. Soil moisture measurements were performed biweekly at five depths in the soil profile (0–5 cm, 10–15 cm, 20–25 cm, 40–45 cm and 70–75 cm) from May to October 1998 and from May to September 1999 using Delta-T theta probe. Results indicated that with increasing soil depth, the mean soil moisture content increases significantly for five layers and the coefficients of variation (CV) also increases with depth from 10–15 cm. It was observed that heavier rains and higher mean moisture contents are often associated with lower spatial variability (CV). Environmental attributes such as land use and topography play controlling roles in the spatial distribution of soil moisture content. However, the relative roles of these environmental indices vary with soil depth. The dominant controls on spatial variability of the time-averaged soil moisture changes from land use, aspect, relative elevation and hillslope position in the surface soil (0–5 cm) to relative elevation, hillslope position and aspect in the subsurface soil (10–15 cm, 20–25 cm), and to land use, relative elevation and slope gradient at larger depths (40–45 cm, 70–75 cm). The dynamic behavior of influences of different environmental indices on the layer-averaged soil moisture depends on several factors. In general, the correlation of soil moisture with slope gradient shows a more significant increase following a greater amount of antecedent precipitation (except for the extremely heavy storms), and declines afterwards. The relation of soil moisture with relative elevation and hillslope position exhibits an opposite trend. It was observed that the influence of land use corresponds to the difference in vegetative characteristics, with a stronger influence in June and August with a greater difference in vegetation. A significant influence of cos(aspect) was found during early spring and autumn with a rapid transient in solar irradiation. Finally, it was found that the sample size is adequate to estimate the catchment mean soil moisture at all five depths and on all 10 observations in 1999 (81 sites), while it is only enough for the upper soil layers (0–5 cm and 10–15 cm) in 1998 (26 sites).