Search

Multi-criteria decision-making (MCDM) is an important means for evaluating resources and environment, and sensitivity analysis can enhance understand the robustness of evaluation results. Spatial visualization has been used in sensitivity analysis of MCDM, but the sensitivity results are still generally summarized by presenting traditional statistical measurements that omit the spatial information. To address this issue, this paper proposed a novel spatially measurement approach of sensitivity analysis by introducing the spatial barycenter model (SBM), which overcame the limitations of existing statistical methods and provided the spatial directivity of uncertainty for the MCDM results. According to our proposed method and its application in farmland quality evaluation (FQE) in an arid area of China, the mean of the absolute average change rate (MACR) and the SBM were applied to test the sensitivity of farmland quality to different evaluation factors from both numerical and spatial perspectives. From the numerical perspective, the soil organic matter and irrigation capacity were the most sensitive factors determined by the MACR. From the spatial perspective, the ≥10 °C accumulated temperature (AT) and precipitation were the most sensitive factors measured by the SBM. Based on the SBM, the spatial configuration of farmland quality index was most sensitive to increase of AT in a northwesterly direction. Calculating the SBM is computationally inexpensive and provides a straightforward indication of spatial direction for the changes of FQE results with changes of parameters. This means it can provide improved understandings and new insights into the comprehensive measurement of sensitivity analysis and agricultural production layout. [ABSTRACT FROM AUTHOR]

Agricultural production is constrained by farmland and water resources, especially in China with limited per capita resources. Understanding of the geographic changes between national crop production and resource availability with the spatial shift of crop production has been limited in recent decades. To solve this issue, we quantified the changes in geographic relationships between crop production and farmland-water resources in China from 1990 to 2015 by a spatial imbalance measurement model. Results found a clear spatial concentration trend of crop production in China, which increased the pressure on the limited farmland and water resources in the main production areas. The geographic imbalances between the total production of crops and farmland resources (∑SMI_PF) alleviated slightly, whereas that of water resources (∑SMI_PW) increased by 9.12%. The rice production moved toward the north of the country with less water but abundant farmland resources, which led to a decrease of 1.34% in ∑SMI_PF and an increase of 14.20% in ∑SMI_PW. The shift of wheat production to the south was conducive to alleviating the pressure on water resources, but the production concentration still increased the demand for farmland and water resources, resulting in an increase in ∑SMI_PF and ∑SMI_PW by 39.96% and 10.01%, respectively. Of the five crops, adjustments to the spatial distribution of corn production had the most significant effect on reducing pressure on farmland and water resources and ∑SMI_PF and ∑SMI_PW decreased by 11.23% and 1.43%, respectively. Our results provided a reference for adjustments in crop production distribution and for policy formulation to sustainably utilize farmland and water resources. [ABSTRACT FROM AUTHOR]

Highlights • Coupling characteristic of water and soil information was measured by a new index. • Actual evapotranspiration was highly correlated to winter wheat yield and area. • Soil fertility evaluation score is not significantly correlated to winter wheat production. • Coupling index of water and soil has a higher explanation power on the winter wheat yield. • Spatial pattern of coupling index is in accordance with that of winter wheat production. Abstract Crop production responses to water and soil characteristics is important to understand and manage regional agricultural production. However, the coupling characteristic of these factors was less quantified and it lacks a deep understanding of its effect on the crop production. North China Region (NCR), an important food production region in China but also one of the most water-stressed areas, was selected as the study area. Based on the remote sensing monitoring techniques, region evapotranspiration model, multi-criteria evaluation model, the spatial distribution of winter wheat, actual evapotranspiration (ET), and soil fertility score (SF) was measured in sequence. This study proposed a novel coupling index of water consumption and soil fertility (CWS) to measure the coupling characteristic of ET and SF, and correlated it to the winter wheat yield and area. The results indicated a significant correlation between the CWS and winter wheat production but a non-significant correlation between SF and yield and area. CWS in NCR presented a global pattern of high values in the south but low values in the north, in accordance with that of winter wheat production. Coupling the information of water and soil, the CWS showed a higher correlation to winter wheat yield with the correlation coefficient of 0.588 than solely that of the ET with 0.437. A relative lower correlation of CWS than that of ET implied that ignore of soil fertility but emphasis on the water restrictions would limit the high crop yield and influence the optimal allocation of water and soil resources. Our finding demonstrated the effectiveness of CWS and its higher relation to the winter wheat production in NCR. Information of spatial coupling and mismatching between the winter wheat production and CWS was suggested to be considered as a guide of better spatial optimal allocation of winter wheat. [ABSTRACT FROM AUTHOR]

• A two-level nested model was developed to depict karst positive and negative terrains. • Visualization indicators and morphological method quantified terrain characteristics. • Accuracy test validated a high consistency between our model and visual extraction. • Positive and negative terrains presented the spatial difference of cultivated land. Topography affects the resource distribution and limits physical living and production conditions in mountainous regions. Depicting the specific positive and negative terrains in karst region would support for understanding ecosystem process and land resources managing in ecologically fragile areas. However, positive and negative terrains, specific topographic types in karst region, have been difficult to extract by the automatic machine quantitative method. The novelty of this study is developing a two-level nested (TLN) model to quantify and extract positive and negative terrains features of karst through utilizing visualization indicators, openness and the sky-view factor (SVF), combing an insight of morphological analysis. The algorithms of the two visualization indicators detected the surface morphological changes in 3D sphere and realized self-adaptive of complicated topographic changes. There were three main modules included in the two-level nested model: optimum radius analysis of selected indicators, optimum threshold judgement of positive and negative terrains edges and a morphological postprocessing module. The two-level chained process designed in the second module reached the quantitative potential critical thresholds detection and optimizing expression of positive and negative terrains boundaries, which integrated analyzing the variation trend of openness difference, SVF value and SVF change. Through the TLN framework, the accuracy and stability of positive and negative terrains boundaries extraction by openness and SVF were further strengthened. The TLN model was tested in seven counties where the karst terrain morphologies were quite different. The boundaries extracted by our TLN model were compared with the visual interpretation results, and the accuracy assessment validated that the overlapping areas of test and reference results were more than 90% and the boundaries' distance deviations were less than one grid. Positive terrain was predominant in all study areas and the proportions varied from 75.33 to 85.23%. Different positive and negative terrains percentages and formations indicated different phases in landform and ecosystem evolution process. The largest proportion of cultivated land appeared in the 0–150 m buffer ring where mutations were detected, which implied an increased ecological risk of karst region. Therefore, it is urgent to resolve the increasingly serious ecological and environmental issues while ensure agricultural production and economic development. The positive and negative terrains distribution patterns could provide theoretical reference for a rational land use planning in the future. [ABSTRACT FROM AUTHOR]