Consumption of Ecosystem Services in Laos

The exponential increase of ecosystem utilization has instigated a serious conflict between ecosystem services and residents’ needs. The Belt and Road Initiative has greatly influenced Laotian production and living, and the scientific assessment of the consumption of ecosystem services in Laos is important for exploring residents’ influence on the ecosystem. Based on data for the Laotian consumption of agricultural products, fruits and livestock products during 1961-2013, normalized by either harvest index or feed conversion ratio, this study draws three main conclusions. 1) Ecosystem service consumption in Laos is centered on the consumption of farmland, forestry and grassland ecosystem services, which account for over 80%, over 10% and under 2%, showing downward, upward and constant trends, respectively. The consumption of these ecosystem services shows a trend of increasing first, then fluctuating, and finally increasing. 2) The consumption of ecosystem services in Laos was characterized by the mode of “dominance of consumption of the farmland ecosystem services” from 1961 to 2008, and the mode of “balanced development of consumption of farmland, forest and grassland ecosystem services” from 2008 to 2013, with a trend of transformation from the former into the latter. 3) The formation and change in the consumption mode of Laotian ecosystem services have been affected by both supply and trade. Laos developed agriculture mainly during the period from 1961 to 2008, forming the mode of “dominance of consumption of the farmland ecosystem services”. This development benefited from the enriched varieties of imports as well as the increased value of trade and import volume. However, the consumption of ecosystem services in Laos after 2008 changed from the mode of “dominance of consumption of the farmland ecosystem services” to one of “balanced development of consumption of farmland, forest and grassland ecosystem services”. This study provides an empirical reference for research on the consumption of ecosystem services.     

Analysis of Spatio-temporal Land Surface Temperature and Normalized Difference Vegetation Index Changes in the Andassa Watershed,Blue Nile Basin,Ethiopia

Analysis of the nexus between vegetation dynamics and climatic parameters like surface temperature is essential in environmental and ecological studies and for monitoring of the natural resources. This study explored the spatio-temporal distribution of land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) and the relationship between them in the Andassa watershed from 1986 to 2016 periods using Landsat data. Monthly average air temperature data of three meteorological sites were used for validating the results. The findings of the study showed that the LST of the Andassa watershed has increased during the study periods. Overall, average LST has been rising with an increasing rate of 0.081°C per year. Other results of this study also showed that there has been a dynamic change in vegetation cover of the watershed in all seasons. There was also a negative correlation between LST and NDVI in all the studied years. From this study we can understand that there has been degradation of vegetation and intensification of LST from 1986 to 2016.     

Body motion in liquid under ice plate with snow cover

The motion of a submarine in liquid under an ice plate covered with flooded snow is considered. The ice is modelled as an elastic plate and the snow cover is modelled as a viscous layer on the top of the plate. The submarine is modelled as a slender solid of revolution with scale 1:300. The experimental and theoretical study of the influence of the viscous snow layer on deflections of the floating ice plate is conducted. The viscous layer reduces the amplitudes of flexural-gravity waves. The greatest influence of the viscous layer on the plate deflections is achieved for velocities of the submarine, where the waves of maximum amplitude are generated. Theoretical results are in good qualitative and quantitative agreement with the model experiments.     

新疆地区土地覆被遥感数据的一致性研究

鉴于新疆地区对中国乃至中亚有着特殊的战略意义,本文针对不同数据源及分类系统在土地覆被数据的空间分布上缺乏互通性问题,结合2010年目视解译土地利用现状遥感监测数据、GlobeLand30和GlobCover2009共3种土地覆被数据,采用类型相似分析、类型混淆分析、混淆矩阵分析、空间一致性分析4种方法开展精度评价及一致性分析,以期对土地覆被数据在中国西北干旱区的适用性及适用范围提供有效建议。结果表明,3种土地覆被数据对新疆地区土地覆被类型构成基本一致,且对裸地类型的辨识度最高;新疆地区中高度一致区域占新疆总面积的95%;3种数据两两对比时,总体精度在64.11%~72.57%之间,其中目视解译数据/GlobeLand 30组合表现出最高水平,且仍有提高空间,反映出目前相同卫星传感器是提升精度评价结果的重要因素之一,且不同分类系统、分类方法、空间分辨率及卫星过境时间等因素对精度评价结果也会产生巨大影响。为解决此类问题,利用多源土地覆被遥感数据的融合技术提高数据精度,或是利用深度学习对遥感影像资料进行精确地解译和判读,将是今后全球土地覆被制图及应用领域的主要发展趋势。     

GPS天线相位中心校正对GRACE卫星精密定轨的影响

使用GRACE卫星星载GPS观测数据,研究地面获取的先验PCV模型和利用残差法估计的在轨PCV模型对低轨卫星精密定轨的影响,并采用GFZ精密轨道对比和SLR检核手段对其进行评估。结果表明,使用先验PCV模型会降低GRACE卫星定轨精度,相反利用在轨PCV模型可以提高定轨精度,提升数量级可达mm级。     

Statistical analysis of surface urban heat island intensity variations: A case study of Babol city,Iran

The urban heat island is considered as one of the most important climate change phenomena in urban areas, which can result in remarkable negative effects on flora, concentration of pollutants, air quality, energy and water consumption, human health, ecological and economic impacts, and even on global warming. The variation analysis of the surface urban heat island intensity (SUHII) is important for understanding the effect of urbanization and urban planning. The objective of this study was to present a new strategy based on the Shannon’s entropy and Pearson chi-square statistic to investigate the spatial and temporal variations of the SUHII. In this study, Landsat TM, ETM+, OLI and TIRS images, MODIS products, meteorological data, topographic and population maps of the Babol city, Iran, from 1985 to 2017, and air temperature data recorded by ground recorder devices in 2017 were used. First, Single-Channel algorithm was used to estimate land surface temperature (LST), and the maximum likelihood classifier was employed to classify Landsat images. Then, based on LST maps, surface urban heat island ratio index was employed to calculate the SUHII. Further, several statistical methods, such as the degree-of-freedom, degree-of-sprawl and degree-of-goodness, were used to analyse the SUHII variation along different geographic directions and in various time periods. Finally, correlation between various parameters such as air temperature, SUHII, population variation and degree-of-goodness index values were investigated. The results indicated that the SUHII value increased by 24% in Babol over different time periods. The correlation coefficient yielded 0.82 between the values of the difference between the mean air temperature of the urban and suburbs and the SUHII values for the geographic directions. Furthermore, the correlation coefficient between the population variation and the degree-of-goodness index values reached 0.8. The results suggested that the SUHII variation of Babol city had a high degree-of-freedom, high degree-of-sprawl and negative degree-of-goodness.     

我国南方西南和中东部区域两次持续性低温雨雪过程与关键环流系统的关系研究

利用NCEP再分析资料和国家气象信息中心提供的753站逐日气温和降水资料,对比分析了我国南方西南和中东部区域两次持续10 d以上的低温雨雪过程,结果表明:(1)两次过程中欧亚大陆中高纬东亚大槽均加深,但环流形势有差异。西南过程呈现"北高南低"形势,关键脊区在贝加尔湖,而中东部区域过程"北高南低"和"西高东低"形势共存,关键脊区从乌拉尔山延伸至贝加尔湖。两次过程异常的环流与北大西洋向东传播的波列有关。(2)西南过程关键脊区提前过程3 d发展并东移至贝加尔湖,形成稳定形势;而中东部区域过程关键脊区提前过程一周发展,在开始日达最强。两次过程均伴随蒙古高压东移南压使地面降温,500 hPa关键脊区超前蒙古高压2 d变化。西南过程降温主要受到冷平流和绝热冷却影响,而中东部区域过程主要受到冷平流的影响。(3)西南过程水汽来自孟加拉湾,只受南支槽支配。中东部区域过程水汽来自孟加拉湾、南海和西太平洋,由南支槽和西太平副热带高压的共同影响。两次过程水汽正收支主要来自南边界。     

Classifier ensembles for land cover mapping using multitemporal SAR imagery

SAR data are almost independent from weather conditions, and thus are well suited for mapping of seasonally changing variables such as land cover. In regard to recent and upcoming missions, multitemporal and multi-frequency approaches become even more attractive. In the present study, classifier ensembles (i.e., boosted decision tree and random forests) are applied to multi-temporal C-band SAR data, from different study sites and years. A detailed accuracy assessment shows that classifier ensembles, in particularly random forests, outperform standard approaches like a single decision tree and a conventional maximum likelihood classifier by more than 10% independently from the site and year. They reach up to almost 84% of overall accuracy in rural areas with large plots. Visual interpretation confirms the statistical accuracy assessment and reveals that also typical random noise is considerably reduced. In addition the results demonstrate that random forests are less sensitive to the number of training samples and perform well even with only a small number. Random forests are computationally highly efficient and are hence considered very well suited for land cover classifications of future multifrequency and multitemporal stacks of SAR imagery.     

Optimizing support vector machine learning for semi-arid vegetation mapping by using clustering analysis

In remote sensing communities, support vector machine (SVM) learning has recently received increasing attention. SVM learning usually requires large memory and enormous amounts of computation time on large training sets. According to SVM algorithms, the SVM classification decision function is fully determined by support vectors, which compose a subset of the training sets. In this regard, a solution to optimize SVM learning is to efficiently reduce training sets. In this paper, a data reduction method based on agglomerative hierarchical clustering is proposed to obtain smaller training sets for SVM learning. Using a multiple angle remote sensing dataset of a semi-arid region, the effectiveness of the proposed method is evaluated by classification experiments with a series of reduced training sets. The experiments show that there is no loss of SVM accuracy when the original training set is reduced to 34% using the proposed approach. Maximum likelihood classification (MLC) also is applied on the reduced training sets. The results show that MLC can also maintain the classification accuracy. This implies that the most informative data instances can be retained by this approach.     

MODIS数据的水浇地提取

水浇地是土地覆盖分类系统中的一个重要类型, 依据水分亏缺指数(WDI)与土壤水分的相关性, 计算了监测时间内WDI的变化情况, 用降雨资料去除了由于降雨引起的WDI的变化, 进而提取了研究区的水浇地分布。结果表明：(1)提取出的水浇地在数量上与统计资料相比, 除山西省偏差相对较大外, 其余各省偏差均小于7%, 提取出的结果与统计资料具有可比性。(2)提取出的水浇地在空间上多成片出现在河流、湖泊、水库附近、灌区和绿洲上, 与已知的水浇地集中区一致。(3)利用TM影像对提取结果进行了初步判断, 其中山西省的正确率较低, 只有64%, 其余各省正确率均在70%以上, 新疆的正确率最高为92%。