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资源与环境模型标准文档库及其与GIS集成 被引量:23
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作者 岳天祥 《地理学报》 EI CSCD 北大核心 2001年第1期107-112,共6页
论述了中国资源与环境模型标准文档库的结构和内容。通过研究总结数学模型及其研究现状发现 ,中国资源与环境模型标准文档库建设需要完善尚有缺陷的数学模型、创建尚缺少的数学模型 ;通过归纳现有数学模型与地理信息系统的现有集成方法... 论述了中国资源与环境模型标准文档库的结构和内容。通过研究总结数学模型及其研究现状发现 ,中国资源与环境模型标准文档库建设需要完善尚有缺陷的数学模型、创建尚缺少的数学模型 ;通过归纳现有数学模型与地理信息系统的现有集成方法发现 ,目前的集成方法不能满足区域可持续发展集成模型的需要 ,据此讨论了数学模型与地理信息系统有效集成需要深入研究的内容。最后 ,提出了通过大量案例研究 ,形成区域可持续发展集成模型和中国资源与环境模型标准文档库 2个软件包的可行研究思路。 展开更多
关键词 资源环境模型 标准文档库 数学模型 GIS集成 区域可持续发展
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资源环境综合模型的集成分析 被引量:3
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作者 范泽孟 岳天祥 《计算机工程与应用》 CSCD 北大核心 2006年第22期1-4,19,共5页
针对资源环境问题的复杂性和综合性,在对海量资源环境模型进行分析并构建了资源环境模型库系统(REMS)的基础上,运用综合集成的方法论理念,根据复杂性资源环境问题综合模拟分析过程中系列子模型各自所承担的模拟功能和重要性,从资源环境... 针对资源环境问题的复杂性和综合性,在对海量资源环境模型进行分析并构建了资源环境模型库系统(REMS)的基础上,运用综合集成的方法论理念,根据复杂性资源环境问题综合模拟分析过程中系列子模型各自所承担的模拟功能和重要性,从资源环境学科背景的研究角度,探索性地提出了资源环境综合模型的串联集成、并联集成、混联集成等三种通用的综合集成模式。以HLZ生态系统时空变化趋势及情景分析模型集成为例,对集成模式的有效性和可行性进行了论证分析。 展开更多
关键词 资源环境综合模型 综合集成 集成模式 HLZES模型
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1990年来中国城镇建设用地占用耕地的效率和驱动机理时空分析 被引量:12
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作者 范泽孟 李赛博 《生态学报》 CAS CSCD 北大核心 2021年第1期374-387,共14页
定量揭示城镇建设用地与耕地的时空变化关系和相互作用机理,是如何实现城镇建设用地需求与耕地资源保护二者间动态平衡的关键问题之一。基于1990—2015年全国城镇建设用地及耕地的空间数据,在对比分析中国31个省份近25年来的城镇建设用... 定量揭示城镇建设用地与耕地的时空变化关系和相互作用机理,是如何实现城镇建设用地需求与耕地资源保护二者间动态平衡的关键问题之一。基于1990—2015年全国城镇建设用地及耕地的空间数据,在对比分析中国31个省份近25年来的城镇建设用地及耕地时空格局变化的基础上,定量求算因城镇建设用地扩张导致耕地减少的速率,并引入数据包络分析法和地理探测器,实现自1990年以来中国城镇建设用地占用耕地的驱动效用机理。结果表明:1)在时间维度上,1990—2015年间,中国城镇建设用地增长2.6×10^(4) km^(2),增速107%,而扩张速率以2.4%/5 a逐渐降低。1990—2000年耕地呈增加趋势(增加2.96×10^(4) km^(2)),2000年后呈减少趋势,总体减少速率为0.29%/5 a。全国新增城镇建设用地占用2.12×10^(4) km^(2)耕地,占城镇新增总量的72.5%;2)在空间分布上,全国城镇建设用地扩张面积由东向西逐渐减小,但2010后的西部区域扩张速度呈上升趋势。耕地面积在西北和东北地区有所增加,东部和中部呈减少趋势,城镇建设用地占用耕地比例由东部向西部逐渐减弱,但中东部耕地被建设用地占用形式仍然严重;3)在城镇建设用地占用耕地的效用上,1990—2015年,全国城镇建设用地占用耕地的产出效益呈现降低趋势,其中产出效益超过0.8的省份主要分布在沿海地区,西北地区产出效益普遍较低。分析结果显示,经济发展因素是新增城镇建设用地占用耕地的主要驱动因素,其次为空间位置因素和政策措施,自2010年后政策因素的驱动作用强度呈增加趋势。 展开更多
关键词 城镇建设用地 耕地 驱动效应 时空分析 中国
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中蒙俄经济走廊荒漠化时空格局变化及其驱动因子 被引量:9
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作者 范泽孟 李赛博 《生态学报》 CAS CSCD 北大核心 2020年第13期4252-4263,共12页
针对如何定量揭示中蒙俄经济走廊荒漠化的时空变化规律及其驱动因子的影响作用,在构建荒漠化程度判别标准和指标体系的基础上,基于Google Earth Engine云计算平台,在对分类回归树(CART)、支持向量机(SVM)、随机森林(RF)和Albedo-NDVI 4... 针对如何定量揭示中蒙俄经济走廊荒漠化的时空变化规律及其驱动因子的影响作用,在构建荒漠化程度判别标准和指标体系的基础上,基于Google Earth Engine云计算平台,在对分类回归树(CART)、支持向量机(SVM)、随机森林(RF)和Albedo-NDVI 4个模型精度进行对比分析的基础上,选取精度最高的CART模型实现中蒙俄经济走廊区域2000—2015年的荒漠化的时空变化分析。另外,在拓展线性趋势法的基础上,构建荒漠化驱动因子定量评估模型,实现气候变化和人类活动对荒漠化驱动效应的定量测度。结果表明:1)CART模型在中蒙俄经济走廊区域荒漠化信息提取精度最高,总体精度和Kappa系数分别85%和0.754;2)极重度荒漠化区域主要分布在中国内蒙古自治区西部,蒙古国的南戈壁盟、东戈壁盟和中戈壁盟;3)2000—2015年间,中蒙俄经济走廊荒漠化总体呈扩张趋势,但极重度、重度和中度荒漠化面积呈缩减趋势。其中,中国的荒漠化面积呈明显缩减趋势,荒漠化程度净改善面积为15.18万km^2,而蒙古国和俄罗斯的荒漠化现象在加重。另外,中蒙俄经济走廊荒漠化恢复区域的气候变化驱动贡献率为68.8%;而荒漠化退化区域的人类活动驱动贡献率为69.68%,表明中蒙俄经济走廊荒漠化程度加重区域的驱动作用主要来自于人类活动。 展开更多
关键词 中蒙俄经济走廊 荒漠化 时空格局 驱动因子 Google Earth Engine
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黄土高原生态系统过渡带土地覆盖的时空变化分析 被引量:14
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作者 范泽孟 李婧 岳天祥 《自然资源学报》 CSSCI CSCD 北大核心 2013年第3期426-436,共11页
在全球气候变化及其生态环境效应研究中,生态系统过渡带作为气候变化和人类活动的敏感区域,其土地覆盖的时空变化分析逐渐成为土地利用科学研究的热点问题。基于GIS的时空分析方法,在对Holdridge生命地带模型的判别标准进行改进的基础上... 在全球气候变化及其生态环境效应研究中,生态系统过渡带作为气候变化和人类活动的敏感区域,其土地覆盖的时空变化分析逐渐成为土地利用科学研究的热点问题。基于GIS的时空分析方法,在对Holdridge生命地带模型的判别标准进行改进的基础上,构建了生态系统过渡带的时空分析模型。在建立土地覆盖正向和逆向转换规则的基础上,构建了土地覆盖正向和逆向转换指数模型。并以黄土高原为案例区,在定量识别生态系统过渡带类型及其空间格局的基础上,定量评价了各种生态系统过渡带类型土地覆盖的转换情况。模拟分析结果表明,黄土高原地区共有14种生态系统过渡带类型,其总面积占整个黄土高原的25.21%。在1985—2005年期间,黄土高原生态系统过渡带内的耕地面积平均每10 a减少0.93%,而湿地和水体、林地、草地的面积则平均每10 a分别增加3.47%、0.24%、0.06%。整个过渡带区域土地覆盖的转换率从28.53%降低到21.91%,且其正向转换和逆向转换面积总体上均呈减少的趋势。另外,黄土高原生态系统过渡带区域和非过渡带区域的土地覆盖转换率对比分析显示,过渡带区域土地覆盖的转换率高于非过渡带区域。 展开更多
关键词 土地覆盖变化 生态系统过渡带 土地覆盖转换 黄土高原
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中国气温未来情景的降尺度模拟 被引量:6
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作者 范泽孟 岳天祥 +1 位作者 陈传法 孙晓芳 《地理研究》 CSCD 北大核心 2011年第11期2043-2051,共9页
由于GCM模拟的气温数据分辨率不高,很难用于区域尺度上各种生态系统的模拟。本文基于长时间序列(1964~2007年)的全国气温观测数据,结合经纬度数据、以及DEM、坡向、坡度等系列地形特征数据,利用空间统计方法,在构建年平均气温降尺度模... 由于GCM模拟的气温数据分辨率不高,很难用于区域尺度上各种生态系统的模拟。本文基于长时间序列(1964~2007年)的全国气温观测数据,结合经纬度数据、以及DEM、坡向、坡度等系列地形特征数据,利用空间统计方法,在构建年平均气温降尺度模型的基础上,运用高精度曲面建模(HASM)方法对HadCM3的A1Fi、A2a和B2a三种情景1961~1990、2010~2039、2040~2069、2070~2099年时段的全国未来平均气温进行高精度曲面模拟。模拟结果显示,在四个时段内,A1Fi、A2a和B2a三种情景的全国未来平均气温均呈持续上升趋势。其中,平均气温在A1Fi情景中上升速度最快,B2a情景中增速最慢;A1Fi和A2a两种情景的平均气温均呈加速上升和增加趋势,而B2a情景的平均气温则呈减速上升和增加趋势。本文构建的降尺度模拟方法可以有效地实现IPCCGCM的低分辨率的气温未来情景数据降尺度转换成高分辨率气温数据。 展开更多
关键词 气温 情景 降尺度模拟 HASM方法 中国
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中国降水未来情景的降尺度模拟 被引量:4
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作者 范泽孟 岳天祥 +1 位作者 陈传法 孙晓芳 《地理研究》 CSSCI CSCD 北大核心 2012年第12期2283-2291,共9页
基于长时间序列(1964~2007年)的全国降水观测数据,结合经纬度数据以及DEM、坡向、坡度等系列地形特征数据,利用空间统计方法,在构建年平均降水降尺度模型的基础上,运用高精度曲面建模(HASM)方法对经过降尺度分析的HadCM3的A1Fi、A2a和... 基于长时间序列(1964~2007年)的全国降水观测数据,结合经纬度数据以及DEM、坡向、坡度等系列地形特征数据,利用空间统计方法,在构建年平均降水降尺度模型的基础上,运用高精度曲面建模(HASM)方法对经过降尺度分析的HadCM3的A1Fi、A2a和B2a三种情景T1~T4时段的全国未来平均降水进行高精度曲面模拟。模拟结果显示,在T1~T4时段内,A1Fi、A2a和B2a三种情景的全国平均降水均呈持续增加趋势。其中,平均降水在A1Fi情景中增加速度最快,B2a情景中增加速度最慢;A1Fi和A2a两种情景的平均降水均呈加速增加趋势,而B2a情景的平均降水则呈减速增加趋势。模拟结果表明,本文构建的降尺度模拟方法可以有效地实现IPCC GCM的低分辨率的降水情景数据降尺度转换成高分辨率的降水数据。 展开更多
关键词 降水 情景 降尺度模拟 HASM方法 中国
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黑河流域植被类型分布模拟分析 被引量:4
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作者 周勋 范泽孟 岳天祥 《地球信息科学学报》 CSCD 北大核心 2017年第4期493-501,共9页
针对黑河流域植被类型空间分布的垂直地带性特征,本文基于支持向量机算法构建黑河流域植被类型空间分布的模拟分析模型,并运用Kappa系数和混淆矩阵检验方法对模拟精度进行检验。验证结果显示,模型总体精度(OA)值为75.54%,Kappa系数值为0... 针对黑河流域植被类型空间分布的垂直地带性特征,本文基于支持向量机算法构建黑河流域植被类型空间分布的模拟分析模型,并运用Kappa系数和混淆矩阵检验方法对模拟精度进行检验。验证结果显示,模型总体精度(OA)值为75.54%,Kappa系数值为0.66,表明了该方法在植被分布模拟上具有较好的结果,适用于区域尺度下植被类型分布的空间模拟。模拟结果表明,该方法对半灌木-矮半灌木荒漠和温带禾草-杂类草草甸草原类型的模拟精度最高,分别为(90.20%和90.02%);分布面积最大的植被类型(如半灌木-矮半灌木荒漠,灌木荒漠、嵩草-杂类草高寒草甸等)相比于其他面积较小的植被类型具有显著优异的模拟结果;人工经济作物、荒漠植被类型以及草原草甸等植被类型对于所选环境因子的敏感性更强,而灌丛类型和乔木类型的模拟结果在不同类型间的波动较大;空间分布上,环境要素差异性明显、植被类型丰富的上游地区具有更好的模拟结果,优于地势平坦、气候差异性小的黑河中下游地段,但模拟结果在景观形态上具有更高的破碎度。 展开更多
关键词 植被分布 植被型 支持向量机 空间模拟 黑河流域
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Spatio-temporal Distribution of Drought in the Belt and Road Area During 1998–2015 Based on TRMM Precipitation Data 被引量:7
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作者 BAI Yongqing WANG Juanle +4 位作者 WANG Yujie HAN Xuehua Bair Z. Tsydypov Altansukh Ochir Davaadorj Davaasuren 《Journal of Resources and Ecology》 CSCD 2017年第6期559-570,共12页
Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the ag... Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Based on the Tropical Rainfall Measuring Mission Satellite(TRMM) 3 B43 precipitation data, we used the Precipitation Abnormity Percentage drought model to study the monthly spatio-temporal distribution of drought in south region of N50° of the Belt and Road area. It was observed that drought during winter was mainly distributed in Northeast Asia, Southeast Asia, and South Asia, while it was mainly distributed in Central Asia and West Asia during summer. The occurrence of historical droughts indicates an obvious seasonal cycle. The regional variations in drought were analyzed using the Breaks for Additive Season and Trend tool(BFAST) in six sub-regions according to the spatial distribution of six economic corridors in the Belt and Road area. The average drought conditions over the 18 years show a slight decreasing trend in Northeast Asia, West Asia, North Africa, South Asia, Central and Eastern Europe, and a slight increasing trend in Central Asia. However, it was a fluctuating pattern of first increasing and then decreasing in Southeast Asia. The results indicate that the total drought area in the Belt and Road region showed a general decreasing trend at a rate of 40,260 km^2 per year from 1998 to 2015. 展开更多
关键词 drought distribution the Belt and Road TRMM Precipitation Abnormity Percentage BFAST
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Estimation of Grassland Production in Central and Eastern Mongolia from 2006 to 2015 via Remote Sensing 被引量:4
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作者 LI Ge WANG Juanle +1 位作者 WANG Yanjie WEI Haishuo 《Journal of Resources and Ecology》 CSCD 2019年第6期676-684,共9页
Mongolia is an important part of the Belt and Road Initiative"China-Mongolia-Russia Economic Corridor"and a region that has been severely affected by global climate change.Changes in grassland production hav... Mongolia is an important part of the Belt and Road Initiative"China-Mongolia-Russia Economic Corridor"and a region that has been severely affected by global climate change.Changes in grassland production have had a profound impact on the sustainable development of the region.Our study explored an optimal model for estimating grassland production in Mongolia and discovered its temporal and spatial distributions.Three estimation models were established using a statistical analysis method based on EVI,MSAVI,NDVI,and PsnNet from Moderate Resolution Imaging Spectroradiometer(MODIS)remote sensing data and measured data.A model evaluation and accuracy comparison showed that an exponential model based on MSAVI was the best simulation(model accuracy 78%).This was selected to estimate the grassland production in central and eastern Mongolia from 2006 to 2015.The results show that the grassland production in the study area had a significantly fluctuating trend for the decade study;a slight overall increasing trend was observed.For the first five years,the grassland production decreased slowly,whereas in the latter five years,significant fluctuations were observed.The grassland production(per unit yield)gradually increased from the southwest to northeast.In most provinces of the study area,the production was above 1000 kg ha with the largest production in Hentiy,at 3944.35 kg ha.The grassland production(total yield)varied greatly among the provinces,with Kent showing the highest production,2341.76x1〇4 t.Results also indicate that the trend in grassland production along the China-Mongolia railway was generally consistent with that of the six provinces studied. 展开更多
关键词 grassland production MODIS remote sensing estimation model Mongolia
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Predicting Potential Geographic Distribution of Tibetan Incarvillea younghusbandii Using the Maxent Model 被引量:4
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作者 KAN Aike YANG Xiao +4 位作者 LI Guoqing WANG Yingjie TESREN Luobu ZENG Yelong CHENG Zhenlong 《Journal of Resources and Ecology》 CSCD 2018年第6期681-689,共9页
Incarvillea younghusbandii is a well-known Tibetan medicinal plant with considerable development and research value distributed widely throughout the Tibetan plateau.It is important to study spatial distribution patte... Incarvillea younghusbandii is a well-known Tibetan medicinal plant with considerable development and research value distributed widely throughout the Tibetan plateau.It is important to study spatial distribution patterns of the plant in order to develop effective protection measures.Based on field survey work and environmental data, the potential geographic distribution of Incarvillea younghusbandii was delineated using a Maximum Entropy (Maxent)model with 28environmental variables that screened for climate,topography,human activity and biological factors.Our results showed that the main geographic range of Incarvillea younghusbandii included the valley between the Yarlung Zangbo river and the Duoxiong Zangbo river,the valley in the middle section of the Himalaya Mountains,and the area between the north side of the east section of the Himalayas and the south bank of the middle reach of the Yarlung Zangbo river.Distribution may spread to parts of the eastern Himalayas.The Jackknife test indicated that soil types,ratio of precipitation to air temperature,extreme atmospheric pressure differences and annual precipitation were the most important predictive factors for the model,while other variables made relatively small contributions. 展开更多
关键词 Maxent Model Incarvillea younghusbandii Himalaya Mountains potential distribution
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Impact of Land Use Changes on Habitat Quality in Altay Region 被引量:4
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作者 WANG Baixue CHENG Weiming LAN Shengxin 《Journal of Resources and Ecology》 CSCD 2021年第6期715-728,共14页
Altay region is located in the northern part of Xinjiang,and has complex and diverse internal geomorphic types,undulating terrain and a fragile ecosystem.Studying the impact of land use changes on habitat quality is o... Altay region is located in the northern part of Xinjiang,and has complex and diverse internal geomorphic types,undulating terrain and a fragile ecosystem.Studying the impact of land use changes on habitat quality is of great significance to regional ecological protection and development,rational planning and utilization,and ensuring the sustainable development of the ecological environment.Based on the InVEST model,combined with land use panel data and topographic relief data of the Altay region,this paper studied the habitat quality from 1995 to 2018.The results show that cultivated land,water area and construction land increased gradually from 1995 to 2018,while grassland and unused land decreased.Forestland remained stable in the first five periods,but increased significantly in 2018.During 1995-2018,all land use types were transferred,mainly between cultivated land,forestland,grassland and unused land in the flat and slightly undulating areas.Poor habitat quality was dominant during 1995-2018.Habitat quality decreased significantly in 2015,which was related to the rapid expansion of cultivated and construction land as threat sources,as well as the decrease of forest and grassland as sensitive factors.However,habitat quality improved significantly in 2018,because a large amount of cultivated land and unused land were converted into forest land and grassland with high habitat suitability.Land use type has an important influence on habitat quality.The distribution characteristics of habitat quality for topographic relief types from good to bad were:large undulating area>medium undulating area>small undulating area>flat area>slightly undulating area.The findings of this study are of great significance for coordinating social,economic,and ecological development in this region and in similar areas. 展开更多
关键词 land use change InVEST model habitat quality Altay region
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Spatial Structure and Development of Tourism Resources based on Point Pattern Analysis: A Case Study in Hainan Island, China 被引量:2
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作者 ZHANG Tongyan WANG Yingjie +2 位作者 WANG Yingying ZHANG Shengrui YU Hu 《Journal of Resources and Ecology》 CSCD 2022年第6期1058-1073,共16页
Tourism resources are the basic materials of tourism development, and they also provide the support for regional tourism spatial competition. The development of tourism depends on the degree to which tourism resources... Tourism resources are the basic materials of tourism development, and they also provide the support for regional tourism spatial competition. The development of tourism depends on the degree to which tourism resources are utilized, and it is of great guiding significance for their development and utilization to study their spatial structure. Based on a large sample of data on tourism resources, and starting from the characteristics of multi-type,multi-level and multi-combination, this paper puts forward a framework and method for analyzing the spatial structure of tourism resources. Taking Hainan Island as an example, this paper describes the spatial structure of tourism resources in Hainan Island by using the method of point pattern analysis, identifies the tourism resource development zones, and puts forward some suggestions for the development of tourism resources. The results are as follows:(1) The characteristic scale of the spatial structure of tourism resources in Hainan Island is 30.5 km, and there are significant differences in the distributions of all kinds of tourism resources.(2) Through the spatial structure map of tourism resources, the tourism resource development zones are identified, including three tourist central city levels, “one horizontal and three vertical” tourist belts and four tourist combination areas.(3) By combing the distribution of tourism resources and the development zones in Hainan Island, the cross-border characteristics of the tourism resources and development zones are obvious. In order to give full play to the spatial combination and superposition effect of tourism resources, a change from a single isolated development mode to the overall combined development between regions is suggested. On the provincial scale, it is relatively accurate to describe the spatial structure of tourism resources for point data with a large sample size. However, the method of point pattern analysis can not only accurately describe the spatial structure of tourism resources, but it can also provide reference for other types of regional spatial analyses. The research results provide a scientific basis for the spatial planning of regional tourism resources and have practical significance for the development of regional tourism. 展开更多
关键词 tourism resources spatial structure development area point pattern analysis method Hainan Island China
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Spatial Distribution and Dynamic Changes in Research Hotspots for Desertification in China based on Big Data from CNKI 被引量:2
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作者 LIANG Yuting HU Yunfeng HAN Yueqi 《Journal of Resources and Ecology》 CSCD 2019年第6期692-703,共12页
Desertification research plays a key role in the survival and development of all mankind.The Normalized Comprehensive Hotspots Index(NCH)is a comprehensive index that reveals the spatial distribution of research hotsp... Desertification research plays a key role in the survival and development of all mankind.The Normalized Comprehensive Hotspots Index(NCH)is a comprehensive index that reveals the spatial distribution of research hotspots in a given research field based on the number of relevant scientific papers.This study uses Web Crawler technology to retrieve the full text of all Chinese journal articles spanning the 1980s-2018 in the Chinese Academic Journal full-text database(CAJ)from CNKI.Based on the 253,055 articles on desertification that were retrieved,we have constructed a research hotspot extraction model for desertification in China by means of the NCH Index.This model can reveal the spatial distribution and dynamic changes of research hotspots for desertification in China.This analysis shows the following:1)The spatial distribution of research hotspots on desertification in China can be effectively described by the NCH Index,although its application in other fields still needs to be verified and optimized.2)According to the NCH Index,the research hotspots for desertification are mainly distributed in the Agro-Pastoral Ecotone and grassland in Inner Mongolia,the desertification areas of Qaidam Basin in the Western Alpine Zone and the Oasis-Desert Ecotone in Xinjiang(including the extension of the central Tarim Basin to the foothills of the Kunlun Mountains,the sporadic areas around the Tianshan Mountains and the former hilly belt of the southern foothills of the Altai Mountains).Among these three,the Agro-Pastoral Ecotone in the middle and eastern part of Inner Mongolia includes the most prominent hotspots in the study of desertification.3)Since the 1980s,the research hotspots for desertification in China have shown a general downward trend,with a significant decline in 219 counties(10.37%of the study area).This trend is dominated by the projects carried out since 2002.The governance of desertification in the eastern part of the Inner Mongolia-Greater Khingan Range still needs to be strengthened.The distribution of desertification climate types reflects the distribution of desertification in a given region to some extent.The Normalized Comprehensive Hotspots Index provides a new approach for researchers in different fields to analyze research progress. 展开更多
关键词 big data web crawler research hotspots DESERTIFICATION spatial distribution trend analysis China
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Quantitative Assessment of the Effects of Climate Change and Human Activities on Grassland NPP in Altay Prefecture 被引量:2
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作者 TIAN Jie XIONG Junnan +4 位作者 ZHANG Yichi CHENG Weiming HE Yuchuan YE Chongchong HE Wen 《Journal of Resources and Ecology》 CSCD 2021年第6期743-756,共14页
Grassland degradation in Altay Prefecture is of considerable concern as it is a threat that hinders the sustainable development of the local economy and the stable operation of the livestock industry.Quantitative asse... Grassland degradation in Altay Prefecture is of considerable concern as it is a threat that hinders the sustainable development of the local economy and the stable operation of the livestock industry.Quantitative assessment of the relative contributions of climate change and human activities,which are considered as the dominant triggers of grassland degradation,to grassland variation is crucial for understanding the grassland degradation mechanism and mitigating the degraded grassland in Altay Prefecture.In this paper,the Carnegie-Ames-Stanford Approach model and the Thornthwaite memorial model were adopted to simulate the actual net primary productivity(NPP_(A))and potential net primary productivity(NPP_(P))in the Altay Prefecture from 2000 to 2019.Meanwhile,the difference between potential NPP and actual NPP was employed to reflect the effects of human activities(NPP_(H))on the grassland.On this basis,we validated the viability of the simulated NPP using the Pearson correlation coefficient,investigated the spatiotemporal variability of grassland productivity,and established comprehensive scenarios to quantitatively assess the relative roles of climate change and human activities on grassland in Altay prefecture.The results indicate three main points.(1)The simulated NPP_(A) was highly consistent with the MOD17 A3 dataset in spatial distribution.(2)Regions with an increased NPP_(A) accounted for 70.53% of the total grassland,whereas 29.47% of the total grassland area experienced a decrease.At the temporal scale,the NPP_(A) presented a slightly increasing trend(0.83 g C m^(-2) yr^(-1))over the study period,while the trends of NPP_(P) and NPP_(H) were reduced(-1.31 and-2.15 g C m^(-2) yr^(-1)).(3)Compared with climate change,human activities played a key role in the process of grassland restoration,as 66.98% of restored grassland resulted from it.In contrast,inter-annual climate change is the primary cause of grassland degradation,as it influenced 55.70% of degraded grassland.These results could shed light on the mechanisms of grassland variation caused by climate change and human activities,and they can be applied to further develop efficient measures to combat desertification in Altay Prefecture. 展开更多
关键词 grassland degradation net primary productivity climate change human activities Altay Prefecture
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Spatial and Temporal Pattern Changes and Driving Forces:Analysis of Salinization in the Yellow River Delta from 2015 to 2020 被引量:1
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作者 HONG Mengmeng WANG Juanle HAN Baomin 《Journal of Resources and Ecology》 CSCD 2022年第5期786-796,共11页
China’s Yellow River Delta represents a typical area with moist semi-humid soil salinization,and its salinization has seriously affected the sustainable use of local resources.The use of remote sensing technology to ... China’s Yellow River Delta represents a typical area with moist semi-humid soil salinization,and its salinization has seriously affected the sustainable use of local resources.The use of remote sensing technology to understand changes in the spatial and temporal patterns of salinization is key to combating regional land degradation.In this study,a feature space model was constructed for remote sensing and monitoring land salinization using Landsat 8 OIL multi-spectral images.The feature parameters were paired to construct a feature space model;a total of eight feature space models were obtained.An accuracy analysis was conducted by combining salt-loving vegetation data with measured data,and the model demonstrating the highest accuracy was selected to develop salinization inversion maps for 2015 and 2020.The results showed that:(1)The total salinization area of the Yellow River Delta displayed a slight upward trend,increasing from 4244 km^(2) in 2015 to 4629 km^(2) in 2020.However,the area’s salting degree reduced substantially,and the areas of saline soil and severe salinization were reduced in size;(2)The areas with reduced salinization severity were mainly concentrated in areas surrounding cities,and primarily comprised wetlands and some regions around the Bohai Sea;(3)Numerous factors such as the implementation of the“Bohai Granary”cultivation engagement plan,increase in human activities to greening local residential living environments,and seawater intrusion caused by the reduction of sediment contents have impacted the distribution of salinization areas in the Yellow River Delta;(4)The characteristic space method of salinization monitoring has better applicability and can be promoted in humid-sub humid regions. 展开更多
关键词 SALINIZATION land degradation feature space salt-loving vegetation the Yellow River Delta
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Spatial Analysis and Biogeochemical Cycles: A Comparative Study of Kashin-Beck Disease Villages and Non-disease Villages in Linzhou County, Tibet 被引量:1
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作者 TIAN Yuan ZHAXinjie +2 位作者 GAO Xing DAI Erfu YU Chengqun 《Journal of Resources and Ecology》 CSCD 2020年第2期232-246,共15页
This study investigated Linzhou County in Tibet, which currently hosts the most serious outbreak of Kashin-Beck disease(KBD) in China. This study uses the geographical detector(GeoDetector) algorithm to measure the in... This study investigated Linzhou County in Tibet, which currently hosts the most serious outbreak of Kashin-Beck disease(KBD) in China. This study uses the geographical detector(GeoDetector) algorithm to measure the influences that several risk factors have on KBD prevalence and validates the spatial analysis results with environmental chemistry. Based on a comprehensive examination of 10 potentially related spatial factors and an environmental chemistry analysis of the soil-water-grain-human biogeochemical cycle in the local KBD and non-KBD villages, four main conclusions are drawn.(1) KBD in Linzhou County is a consequence of multiple interrelated environmental factors, of which the most important controlling factor is the stratum factor.(2) The concentrations of selenium(Se) in all environmental media(soil, water, and food) and human tissue in the KBD villages in Linzhou County are lower than those of the non-KBD villages.(3) The intake of Se and chromium(Cr) by local residents is seriously insufficient, especially the average daily dose by ingestion(ADD) for Se in the KBD village, which is only about 4% of the World Health Organization(WHO) recommended lower limit for adult elemental intake.(4) We speculate that the main cause for the local KBD outbreak is a lack of Se in the stratum. This absence leads to a serious Se deficiency in the local population through ecosystem migration and transformation, which will eventually lead to an endemic biogeochemical Se deficiency. 展开更多
关键词 Kashin-Beck disease TIBET spatial analysis biogeochemical cycle SELENIUM
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Spatiotemporal Pattern and Driving Force Analysis of Vegetation Variation in Altay Prefecture based on Google Earth Engine 被引量:1
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作者 HE Yuchuan XIONG Junnan +5 位作者 ABUDUMANAN·Ahemaitihali CHENG Weiming YE Chongchong HE Wen YONG Zhiwei TIAN Jie 《Journal of Resources and Ecology》 CSCD 2021年第6期729-742,共14页
Quantitative evaluation and driving mechanism analysis of vegetation dynamics are essential for promoting regional sustainable development.In the past 20 years,the ecological environment in Altay Prefecture has change... Quantitative evaluation and driving mechanism analysis of vegetation dynamics are essential for promoting regional sustainable development.In the past 20 years,the ecological environment in Altay Prefecture has changed significantly due to global warming.Meanwhile,with increasing human activities,the spatiotemporal pattern and driving forces of vegetation variation in the area are uncertain and difficult to accurately assess.Hence,we quantified the vegetation growth by using the Normalized Difference Vegetation Index(NDVI)on the Google Earth Engine(GEE).Then,the spatiotemporal patterns of vegetation from 2000 to 2019 were analyzed at the pixel scale.Finally,significance threshold segmentation was performed using meteorological data based on the correlation analysis results,and the contributions of climate change and human activities to vegetation variation were quantified.The results demonstrated that the vegetation coverage in Altay Prefecture is mainly concentrated in the north.The vegetation areas representing significant restoration and degradation from 2000 to 2019 accounted for 24.08% and 1.24% of Altay Prefecture,respectively.Moreover,spatial correlation analysis showed that the areas with significant correlations between NDVI and temperature,precipitation and sunlight hours accounted for 3.3%,6.9% and 20.3% of Altay Prefecture,respectively.In the significant restoration area,18.94% was dominated by multiple factors,while 3.4% was dominated by human activities,and 1.74% was dominated by climate change.Within the significant degradation area,abnormal degradation and climate change controlled 1.07% and 0.17%,respectively.This study revealed the dynamic changes of vegetation and their driving mechanisms in Altay Prefecture,and can provide scientific support for further research on life community mechanism theory and key remediation technology of mountain-water-forest-farmland-lake-grass in Altay Prefecture. 展开更多
关键词 vegetation variation climate change human activities driving mechanism Google Earth Engine Altay Prefecture
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Geographical and Botanical Variation in Concentrations of Molybdenum in Natural Pasture Plants and Surface Water and Yak Molybdenum Ingestion in North Tibet,China 被引量:1
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作者 TIAN Yuan YU Chengqun +3 位作者 ZHA Xinjie WU Jianshuang GAO Xing FENG Chujian 《Journal of Resources and Ecology》 CSCD 2018年第5期545-553,共9页
The North Tibet plateau is the world highest plateau with a unique alpine grassland and water environment. To obtain a better understanding of the correct supply of Molybdenum(Mo) to livestock in north Tibet,we inve... The North Tibet plateau is the world highest plateau with a unique alpine grassland and water environment. To obtain a better understanding of the correct supply of Molybdenum(Mo) to livestock in north Tibet,we investigated the content and geographical variation of Mo in different families of pasture plants(n=1017) and water(n=40),then discuss the Cuprum(Cu):Mo ratio in different plant families,and calculate the total Mo intake of the yak in north Tibet. The average Mo concentration in five families preferred for grazing are: Compositae(2.71 μg g^(-1)),Leguminosae(2.70 μg g^(-1)),Gramineae(2.48 μg g^(-1)),Cyperaceae(1.63 μg g^(-1)),and Rosaceae(1.51 μg g^(-1)). There was a strong geographical variation in Mo concentration(p 0.001). The mean value of Mo in north Tibet surface water from 15 sites is 0.89 μg L^(-1). The Mo ingestion by yak through these plants and water in north Tibet is about 9586 μg day^(-1) which means the toxicity of Mo does not exist in the average daily diet. However,the large geographical variation found may cause some toxicity of Mo in the average daily intake of north Tibet pasture plants in some areas. The Cu:Mo ratio of 2:60 is considered the limit for risk of Mo hyperactivity,while extremely high Cu:Mo ratios may lead to chronic copper poisoning. Our survey of plant samples found 43.29% below and 29.3% above the limiting Cu:Mo ratio of 60 indicating some risk to north Tibet livestock. 展开更多
关键词 North Tibet pasture plants water MOLYBDENUM copper
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Intelligent Identification of Building Patches and Assessment of Roof Greening Suitability in High-density Urban Areas:A Case Study of Chengdu 被引量:1
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作者 LUO Luhua CHEN Mingjie +8 位作者 DONG Lulu SU Wei LI Xin HU Xiaodong ZHANG Xin LI Chen CHENG Weiming SHI Hanning LUO Jiancheng 《Journal of Resources and Ecology》 CSCD 2022年第2期247-256,共10页
With the expansion of a city,the urban green space is occupied and the urban heat island effect is serious.Greening the roof surfaces of urban buildings is an effective way to increase the area of urban green space an... With the expansion of a city,the urban green space is occupied and the urban heat island effect is serious.Greening the roof surfaces of urban buildings is an effective way to increase the area of urban green space and improve the urban ecological environment.To provide effective data support for urban green space planning,this paper used high-resolution images to(1)obtain accurate building spots on the map of the study area through deep learning assisted manual correction;and(2)establish an evaluation index system of roof greening including the characteristics of the roof itself,the natural environment and the human society environment.The weight values of attributes not related to the roof itself were calculated by Analytic Hierarchy Process(AHP).The suitable green roof locations were evaluated by spatial join,weighted superposition and other spatial analysis methods.Taking the areas within the Chengdu city’s third ring road as the study area,the results show that an accurate building pattern obtained by deep learning greatly improves the efficiency of the experiment.The roof surfaces unsuitable for greening can be effectively classified by the method of feature extraction,with an accuracy of 86.58%.The roofs suitable for greening account for 48.08%,among which,the high-suitability roofs,medium-suitability roofs and low-suitability roofs represent 45.32%,38.95%and 15.73%.The high-suitability green buildings are mainly distributed in the first ring district and the western area outside the first ring district in Chengdu.This paper is useful for solving the current problem of the more saturated high-density urban area and allowing the expansion of the urban ecological environment. 展开更多
关键词 deep learning roof greening suitability assessment spatial join weighted overlay
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