Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China t...Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model.In addition,given the undesirable outputs of agricultural production,we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure(GB-US-SBM)model,which combines global benchmark technology,undesirable output,super efficiency,and slacks-based measure.The results indicated that there was an upward trend in CLUE in China from 2000 to 2020,with an increase rate of 2.62%.The temporal evolution of CLUE in China could be classified into three distinct stages:a period of fluctuating decrease(2000-2007),a phase of gradual increase(2008-2014),and a period of rapid growth(2015-2020).The major grain-producing areas(MPAs)had a lower CLUE than their counterparts,namely,non-major grain-production areas(non-MPAs).The spatial agglomeration effect followed a northeast-southwest strip distribution;and the movement path of barycentre revealed a"P"shape,with Luoyang City,Henan Province,as the centre.In terms of influencing factors of CLUE,investment in science and technology played the most vital role in improving CLUE,while irrigation index had the most negative effect.It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs.Therefore,relevant departments should formulate policies to enhance the level of science and technology,improve irrigation condition,and promote sustainable utilization of cultivated land.展开更多
Using GIS spatial statistical analysis method, with ArcGIS software as an analysis tool, taking the diseased maize in Hedong District of Linyi City as the study object, the distribution characteristic of the diseased ...Using GIS spatial statistical analysis method, with ArcGIS software as an analysis tool, taking the diseased maize in Hedong District of Linyi City as the study object, the distribution characteristic of the diseased crops this time in spatial location was analyzed. The results showed that the diseased crops mainly dis- tributed along with river tributaries and downstream of main rivers. The correlation between adjacent diseased plots was little, so the infection of pests and diseases were excluded, and the major reason of incidence might be river pollution.展开更多
文摘煤矿长时间开采会导致上覆岩层在重力因素下产生刚性弯曲、断裂等,进而造成一系列安全隐患。如何高效地对煤矿区进行地表形变监测,对煤矿安全、自然生态有着十分重要的意义。文章结合小基线集干涉测量(small baseline subset InSAR,SBAS-InSAR)技术与瞬变电磁测深法对煤矿区进行沉降监测。此外,采用标准差椭圆分析了沉降体空间形变规律与特征,利用长短时记忆网络(long short term memory network,LSTM)模型预测了沉降体形变趋势。分析结果表明:通过瞬变电磁法与干涉测量结合,地表形变范围基本与瞬变电磁反演的采空区吻合,标准差椭圆分析出形变中心向西南方移动376 m,沉降形态也在向似圆状过渡;LSTM模型可以预测两个月的形变,误差为2 mm,可以实现煤矿区形变趋势的短期预测。
基金supported by the National Natural Science Foundation of China(72373117)the Chinese Universities Scientific Fund(Z1010422003)+1 种基金the Major Project of the Key Research Base of Humanities and Social Sciences of the Ministry of Education(22JJD790052)the Qinchuangyuan Project of Shaanxi Province(QCYRCXM-2022-145).
文摘Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model.In addition,given the undesirable outputs of agricultural production,we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure(GB-US-SBM)model,which combines global benchmark technology,undesirable output,super efficiency,and slacks-based measure.The results indicated that there was an upward trend in CLUE in China from 2000 to 2020,with an increase rate of 2.62%.The temporal evolution of CLUE in China could be classified into three distinct stages:a period of fluctuating decrease(2000-2007),a phase of gradual increase(2008-2014),and a period of rapid growth(2015-2020).The major grain-producing areas(MPAs)had a lower CLUE than their counterparts,namely,non-major grain-production areas(non-MPAs).The spatial agglomeration effect followed a northeast-southwest strip distribution;and the movement path of barycentre revealed a"P"shape,with Luoyang City,Henan Province,as the centre.In terms of influencing factors of CLUE,investment in science and technology played the most vital role in improving CLUE,while irrigation index had the most negative effect.It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs.Therefore,relevant departments should formulate policies to enhance the level of science and technology,improve irrigation condition,and promote sustainable utilization of cultivated land.
文摘Using GIS spatial statistical analysis method, with ArcGIS software as an analysis tool, taking the diseased maize in Hedong District of Linyi City as the study object, the distribution characteristic of the diseased crops this time in spatial location was analyzed. The results showed that the diseased crops mainly dis- tributed along with river tributaries and downstream of main rivers. The correlation between adjacent diseased plots was little, so the infection of pests and diseases were excluded, and the major reason of incidence might be river pollution.
