赣南白面石地区铀资源潜力分析

白面石地区有着得天独厚的铀成矿地质背景,区内铀矿化是在富铀的白面石花岗岩体基础上发展起来的。富铀基底花岗岩的风化,使铀活化迁移,形成高铀含量砂岩层,是该区成矿的基础;北西向展布的双峰式火山岩浆喷溢、形成覆盖在高铀含量砂岩层之上的火山岩层,起着热盖和封闭作用,使铀聚积成矿,是成矿的关键;后期断裂作用及次火山岩的贯入,带来了丰富的热能,使铀再次活化迁移,铀矿化叠加变富。     

1965-2012年甘肃平凉地区大雪天气气候特征

利用甘肃平凉地区7个气象自动站1965-2012年的逐日气象整编资料, 统计出近48 a来大雪天气出现次数, 分析了平凉大雪天气的统计特征和气候变化规律, 然后用近14 a历史天气图资料对31次大雪过程进行对比分型, 总结出三类天气形势的特征. 结果表明: 1965-2012年48 a来, 平凉大雪天气出现次数总体变化趋势不显著; 大雪天气多集中出现在秋冬、冬春冷暖季节交替的时期, 冬春交替期间出现次数多于秋冬交替期间, 隆冬季节出现次数相对较少. 平凉产生大雪天气的主要天气形势有三类: 高原低槽型、西风带小槽型和阻高-横槽型, 三类形势中最多的是高原低槽型, 其他两类出现概率相差不到10个百分点.     

青海高原雪灾风险区划及对策建议

利用青海省50个气象台站逐日积雪深度资料、遥感监测积雪深度资料和牲畜死亡率资料,对遥感监测积雪数据进行了验证,证实遥感监测积雪数据能很好的反映青海积雪状况.利用积雪指标分析青海各地致灾强度大小.结果表明:青海三江源地区和祁连山区的部分地区致灾因子危险性最高,柴达木盆地的西部和东部农业区以及环湖的部分地区致灾因子危险性较低.通过分析积雪指标和牲畜死亡率的相关关系,确定了不同雪灾等级临界气象指标,对青海地区进行了雪灾风险区划.区划结果为:轻灾主要发生在柴达木盆地、东部农业区的大部和环湖的部分地区,这些地区发生轻灾的频率大都在50%以上;中灾和重灾在青海发生频率均不高,都在20%以下;三江源的大部尤其是囊谦、玉树和称多一带是特大雪灾的高发区,发生频率均在50%以上.     

气候变化感知对城市居民冰雪旅游环境责任行为的影响机制——以北京市为例

冰雪旅游是推动冰雪经济与旅游产业高质量融合发展的重要途径,现已成为文旅产业中最具潜力的领域之一。然而在全球气候变化的影响下,冰雪旅游发展面临严峻挑战。文章以北京市为例,运用结构方程模型对冰雪旅游情境中城市居民的气候变化感知、感知价值、旅游意向和环境责任行为等变量间的影响关系及其形成机制进行分析。研究发现：(1)气候变化感知分为气候变化表征和气候变化风险两个维度,且两者显著正向影响冰雪旅游感知价值。同时,气候变化风险显著正向影响旅游者环境责任行为。(2)冰雪旅游感知价值显著正向影响冰雪旅游意向和环境责任行为。(3)冰雪旅游意向显著正向影响环境责任行为。(4)旅游经历在气候变化感知对冰雪旅游意向和环境责任行为的影响关系中具有显著的正向调节作用。本研究对厘清冰雪旅游情境下气候变化感知对游客环境责任行为的复杂影响机理具有重要的理论价值,同时也能够在一定程度上为相关部门把握“后冬奥”黄金机遇,推动冰雪旅游高质量发展提供决策参考。     

黄河流域NDVI/土地利用对蒸散发时空变化的影响

基于蒸散发(ET)、归一化植被指数(NDVI)及土地利用数据利用M-K检验、Sen趋势分析等方法,研究2001—2015年黄河流域ET时空分布及不同植被覆盖/土地利用下的ET变化规律.结果 表明:(1)黄河流域年均ET呈东南高西北低的空间分布格局,与植被覆盖和土地利用的关系具有较好的一致性;(2)黄河流域ET、NDVI...     

Research activities on land-use/cover change in the past ten years in China using space technology

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Detecting Arctic snow and ice cover with FY-1D global data

Chinese meteorological satellite FY-1D can obtain global data from four spectral channels which include visible channel(0.58-0.68 μm) and infrared channels(0.84-0.89 μm,10.3-11.3 μm,11.5-12.5 μm).2366 snow and ice samples,2024 cloud samples,1602 land samples and 1648 water samples were selected randomly from Arctic imageries.Land and water can be detected by spectral features.Snow-ice and cloud can be classified by textural features.The classifier is Bayes classifier.By synthesizing five d ays classifying result of Arctic snow and ice cover area,complete Arctic snow and ice cover area can be obtained.The result agrees with NOAA/NESDIS IMS products up to 70%.     

近30年来长江源区土地覆被变化特征分析

长江源区是我国重要的水源涵养地。本文利用20世纪70年代中后期、90年代初期、2004年和2008年共4期土地覆被数据,通过土地覆被转类途径与幅度、土地覆被状况指数和土地覆被转类指数,分析评价了长江源区近30年来土地覆被与生态状况的时空变化特征。结果表明：草地是长江源区主要的土地覆被类型,2008年草地面积占该区总面积的66.93%。在70年代中后期-90年代初期、90年代初期-2004年和2004-2008年的3个时段内,土地覆被状况指数变化率分别为-0.15、-0.24和0.01;土地覆被转类指数分别为-0.20、-0.66和0.08。近30年来,长江源区土地覆被和生态状况总体经历了变差-显著变差-略有好转的过程。2004-2008年,长江源区年平均温度比前期（70年代中后期-2004年）升高了0.57℃,年平均降水量比前期增加了17.63mm。区域气候变化有助于自然生态系统的恢复。后期生态保护与建设工程的实施,对植被恢复产生了一定的积极作用。     

An assessment of land cover change as a source of information for conservation planning in the Vhembe Biosphere Reserve

Determining changes in land use/land cover (LULCC) can be used to assess and monitor habitat loss as one of the five global priority causes of biodiversity loss. In South Africa, two national land-cover (NLC) datasets have been developed from satellite imagery obtained in circa 1990 and 2013/2014. The Vhembe Biosphere Reserve (VBR), designated in 2009, is located in the north of the Limpopo Province in South Africa and has a surface area of 30,457 km². The aim of biosphere reserves is to provide a landscape-scale framework for conservation and sustainable development of an area. The area within a biosphere reserve is prioritised by designating it into one of three zones 1) Core, 2) Buffer, and 3) Transitional Zones. Two national parks and six provincial reserves (PAs) are the current and form part of the proposed updated core areas (pCAs) of the VBR. Intensity analyses was used to assess LULCC in the VBR. The pCAs cover 39.7% of the surface area of the VBR. The PAs cover 39.7% and only 15.8% of the surface area of the pCAs and VBR respectively. Based on the NLC 2013/2014 a majority of the VBR, pCAs and PAs consisted of indigenous vegetation dominated by Woodland/Open bush, Grassland, and Thicket/Dense bush. The extent of transformed land in the VBR declined from 1990 to 2013 by 1697.7 km². The total amount of change and mean annual change in the VBR was 53.1% and 2.31% respectively. The overexploitation of fuel wood by rural communities in rural areas of the VBR, was partly responsible for the targeted loss of Woodland/Open bush to Thicket/Dense bush and Grasslands. The unquantified presence of novel vegetation and alien invasive plants means that the NLC 1990 and 2013/2014 overestimates the quantity and distribution of the remaining indigenous vegetation in the VBR. In order to address this the distribution of alien and indigenous invasive plant species in the VBR needs to be determined and used to update future NLCs. Assuming a worse-case-scenario of all the coal deposits in the VBR, including the Kruger National Park, being mined it would amount to 24.7% of the surface area of the VBR. Only 6.8% of the area of all the coal deposits in the VBR was transformed with 93.2% currently remaining untransformed. It is recommended that transformation of indigenous vegetation to one of the seven transformed land cover categories and more specifically from coal mining should be restricted to the VBR's Transition Zones.     

应用高精度卫星图像进行城市植被覆盖调查:以厦门市为例

With the technological improvements of satellite sensors, we will acquire more informationabout the earth so that we have reached a new application epoch of observation on earthenvironmental change and cartography. But with the enhancement of spatial resolution, somequestions have arisen in the application of using traditional image processing and classificationmethods. Aiming for such questions, we studied the application of IKONOS very high resolutionimage (1 m) in Xiamen City on Urban Vegetation Cover Investigation and discussed the differencebetween the very high resolution image and traditional low spatial resolution image at classification,information abstraction etc. It is an advantageous test for the large-scale application of very highresolution data in the future.