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1.
城市绿化覆盖是城市生态系统的重要组成部分,合理的绿化率和绿化布局可以改善城市环境,提高城市人居适宜性。研究中将2005、2010、2015年北京市土地利用(LUC)数据中的城市居民用地作为城区范围,应用Landsat 5、GF-1影像数据和MODIS产品,利用支持向量机的监督分类方法,提取了2005、2010、2015年的北京市城市绿化覆盖数据,并获取了同期的植被指数(NDVI)数据;继而以城市绿化覆盖率、绿化覆盖均匀度和植被指数为评价指标,在公里栅格和行政区2个尺度上探讨了北京市城市绿化覆盖的空间分布格局和时间变化动态特征。研究表明:① 3个指标在空间和时间2个维度、区县和栅格2个尺度上都表现一致。这反映北京市过去10年中,在绿化面积增加的同时,绿化的空间布局得到优化改善,绿化的质量得到提高。② 2005-2015年,北京市城市绿化覆盖面积由518.93 km2 增加到1405.54 km2,绿化覆盖率由39.9%增加到49.13%,绿化覆盖均匀度由0.598增加到0.653,植被指数由0.42增加至0.5。③ 北京市城市绿化建设存在明显的时空差异。中心城区绿化建设缓慢,成效不明显;重大绿化建设成果主要集中在城市边缘地区和远郊区县。城市绿化改善过程主要发生在2005-2010年。 相似文献
2.
对生态地理学的概念进行了详细讨论和辨析,并将它与相近学科如生物地理学、生态地理区划、宏生态学等进行了比较分析,界定了生态地理学的概念。研究认为:生态地理学是生态学和地理学的交叉学科,是研究生态系统各组分关系和生态过程的地理空间分布格局或/和时间演变规律及其与地理环境耦合机制的学科。生态地理学的目的是揭示不同环境梯度下或不同时间尺度上生态系统各组分关系和生态过程的普适性规律及其成因。同时,结合国内外野外实验平台介绍,在全球变化等研究领域列举了经典案例进行分析:① 全球不同气候带森林凋落物分解和碳汇功能的研究;② 中国不同陆地生态系统碳通量和碳汇功能研究;③ 中国东北样带和南北样带陆地生态系统的脆弱性与适应性研究;④ 中国北方草地样带尺度的生态系统生态学研究。主要目的是在辨析生态地理学概念的基础上指出未来发展方向,推动生态地理学的发展。 相似文献
3.
随着化肥、农膜等在农业生产中的过量投入,耕地面源污染的程度随之加重。文章选取塔里木河流域上游和田地区为研究区域,依据P-S-R框架理论,构建和田地区耕地面源污染生态风险评价指标体系,加入土壤理化数据,使用生态风险评价模型对和田地区1980 年及2016 年耕地面源污染状况进行生态风险评价,运用耕地生态风险模型、生态风险转移矩阵、Arcgis分析和田地区耕地面源污染时空分异状况。研究结论如下:和田地区1980 年耕地生态风险等级均为II级或III级,呈“中间高,两侧低”分布;2016 年耕地生态风险等级上升至IV级或V级,呈“倒W型”分布,各县耕地面源污染程度较1980 年均有较大幅度的上升,其中墨玉县和于田县在2016 年耕地生态风险等级达到最高的V级,而民丰县因自身生态环境的强脆弱性,同样需要提高关注。根据面源污染“从源头治理”的原则,应切实推进和田地区耕地生态环境保护与治理,提高政府重视程度,增强技术指导,开展试点工作,改善和田地区耕地面源污染现状。 相似文献
4.
文章分析了2013年南海南部4个季节航次的叶绿素a (Chl a)调查数据, 结果显示: 150m以浅水柱Chl a质量浓度均值分别为早春0.14mg•m-3、初夏0.12mg•m-3、初秋0.18mg•m-3、初冬0.16mg•m-3。早春和初夏偏低的原因与早春风速小, 初夏水温高, 不利于水体的垂直混合, 限制了深层海水中丰富的营养盐向上层水体补充有关。4个季节中海水次表层Chl a质量浓度最大值层(SCML)均出现在50m和75m, 这两个水层的Chl a质量浓度差异小, 季节变化不大, 平均值变化范围分别为0.24~0.26mg•m-3和0.22~0.26mg•m-3。受混合层深度和温跃层上界深度的共同影响, 50m水层Chl a质量浓度主要受制于深层富营养盐海水的向上补充, 75m水层Chl a质量浓度受水温的影响明显。 相似文献
5.
试论新世纪地理信息科学的发展 总被引:1,自引:0,他引:1
本文重点分析了当前国内外地理信息科学的形成与发展趋势和地理信息科学不断发展的历程 ,提出近期发展的前沿 ,以及当前地理信息产业化面临的一些重要问题。最后提出对地理信息科学发展的意见。 相似文献
6.
Based on the δ13C and δ18O fluctuation of lacustrine carbonate, CaCO3 content and sporo-pollen data, a palaeoclimatic history of Bosten Lake during the Holocene has been outlined, several stages
of climatic changes are divided, and the following result es are obtained: (1) Palaeoclimatic changes revealed by carbonate
isotope around Bosten Lake are basically identical with that revealed by other geological records in Xinjiang. Environmental
changes presented apparent Westlies Style model: during cold period, relative humidity increased, δ18O, δ13C and CaCO3 appeared low; but in warm periods, the dry regime aggravated. (2) The temperature reflected by δ18O exist evident features being increase in the late period during the Holocene. Together with the δ13C, pollen and CaCO3 analyses, several cold and warm phases which are of broad regional significance can be identified. The warm peaks occurred
at about 11.0 ka B.P., 9.4 ka B.P., 7.5 ka B.P., 5.0 ka B.P., 3.0 ka B.P. and 2.0 ka B.P.; the cold peaks at 11.5 ka B.P.,
10.5 ka B.P., 8.8 ka B.P., 5.5 ka B.P., 3.3 ka B.P., 2.2 ka B.P. and 1.5 ka B.P.. (3) Several climatic events with the nature
of “abrupt climatic changes” are revealed in the periods of 11.0 ka B.P. −10.5 ka B.P., 9.4 ka B.P. −8.8 ka B.P., 5.5 ka B.P.
−5.0 ka B.P. and 2.0 ka B.P. −1.5 ka B.P.. (4) The results show that carbonate isotopic record of lacustrine sediment in arid
area is very sensitive to climatic changes, and may be play a very important role in understanding the features and mechanism
of palaeoclimatic changes. 相似文献
7.
Bjrn Grieger 《Global and Planetary Change》2002,34(3-4)
To drive an atmospheric general circulation model (AGCM), land surface boundary conditions like albedo and morphological roughness, which depend on the vegetation type present, have to be prescribed. For the late Quaternary there are some data available, but they are still sparse. Here an artificial neural network approach to assimilate these paleovegetation data is investigated. In contrast to a biome model the relation between climatological parameters and vegetation type is not based on biological knowledge but estimated from the available vegetation data and the AGCM climatology at the corresponding locations. For a test application, a data set for the modern vegetation reduced to the amount of data available for the Holocene climate optimum (about 6000 years B.P.) is used. From this, the neural network is able to reconstruct the complete global vegetation with a kappa value of 0.56. The most pronounced errors occur in Australia and South America in areas corresponding to large data gaps. 相似文献
8.
Upper Cretaceous platform carbonates of the Vocontian Basin (southeastern France) have been investigated in a cross-section from the proximal deposits exposed in the lower Rhône Valley to the distal part of the basin in the Southern Subalpine Ranges north of Nice. The stratigraphic interval studied in detail spans the uppermost Turonian and Coniacian.Palynofacies patterns were used to detect eustatic signals at a third-order scale and are the tool for correlation of proximal and distal platform deposits. The organic constituents observed in the studied samples have been grouped into a continental fraction, including higher plant debris (phytoclasts) and sporomorphs, and a marine fraction with dinoflagellate cysts, acritarchs, prasinophytes, and foraminiferal test linings. The main factors influencing the stratigraphic and spatial distribution of land-derived, allochthonous, and marine, relatively autochthonous, organic particles are the proximity of land, the organic productivity, the degree of biodegradation and the hydrodynamic conditions of the depositional system. Palynofacies parameters used for the sequence stratigraphic interpretation are: (1) the ratio of continental to marine constituents (CONT/MAR ratio); (2) the ratio of opaque to translucent phytoclasts (OP/TR ratio); (3) the phytoclast particle size and shape; and (4) the relative proportion and species diversity of marine plankton. Ternary diagrams illustrating significant proximality changes were used to decipher transgressive-regressive trends within the succession.High amounts of translucent phytoclasts and decreasing values of the CONT/MAR ratio occur during the phase of relative sea-level rise in the upper Turonian. The stratigraphic interval of maximum flooding around the Turonian/Coniacian boundary is marked by the highest abundance and species diversity of dinoflagellate cysts, and by high percentages of opaque, equidimensional particles within the phytoclast group. The OP/TR ratio is still high within the lower Coniacian representing the early highstand deposits, whereas the relative abundance of marine constituents is again decreasing. Sedimentary organic matter of the upper Coniacian is dominated by large, blade-shaped, mainly opaque phytoclasts, which are a characteristic palynofacies signature of late highstand deposits.The present study demonstrates the high potential of palynofacies analysis in high-resolution stratigraphy and correlation of sedimentary series of shallow epeiric seas. 相似文献
9.
Evaluation of geochemical impact of tsunami on Pichavaram mangrove ecosystem,southeast coast of India 总被引:1,自引:0,他引:1
The 26 December 2004-tsunami has deposited sediments in the Pichavaram mangrove ecosystem, east coast of India. Ten surface
and three core sediment samples were collected within 30 days of the event and analyzed for nutrients. Water samples were
also analyzed to see the impact of tsunami on the geochemical behavior of nutrients. An increase in the concentration of various
nutrients namely nitrate and phosphate was observed. The geochemistry of the mangrove forest was observed to be influenced
by a number of factors like rapid increase of aquaculture farms, agricultural practices and the anthropogenic discharge from
the nearby-inhabited areas. Further the sediment column was disturbed due to energetic tsunami waves, which has caused a sheer
increase in the dissolved oxygen in water. As a result, the change in the redox potential has resulted in change in the nutrients
absorbed/associated with the sediments. In addition, role of retreating water after tsunami on the nutrient geochemistry was
also evaluated. 相似文献
10.