基于GEE的地表覆盖与气候状态关联研究

为探究地表覆盖与气候状态间的关联性,本文选取2019年的Landsat影像数据,结合温度、降水量、PM_2.5浓度3种气候指标,利用GEE平台,结合NDVI、MNDWI、NDBI,采用SVM、RF、CART方法进行地表覆盖分类,探究气候指标与地表覆盖类型分布的关联性;提出了使用3种气候指标构建分类特征进行地表覆盖分类的方法,并通过消融试验分析了气候指标对地表覆盖分类精度的影响。结果表明:①RF有较好的分类结果,总体精度为96.0%;②3种气候指标均能提高地表覆盖分类精度,其中PM_2.5浓度效果最好;③温度与植被、水体关联性较大,PM_2.5浓度与城区、植被关联性较大,降水量与耕地关联性较大。     

大光斑波形数据在土地覆盖分类的适用性分析

针对GLAS地学激光测高系统是冰、云和陆地高程卫星(ICESat)的唯一监测工具,能够记录地表光斑内的地物信息,是否能应用于黄土高原土地覆盖分类的问题进行了研究。利用粒子群和最小二乘法相结合的方法对GLAS波形数据进行高斯分解,获取高斯波个数、波形总能量、波形信号起始和信号结束位置4个波形参数;基于波形自动分类方法对黄土高原水体、森林、城市用地、其他地类(裸地、低矮植被等)进行分类。通过基于覆盖相同研究区域的30 m地表覆盖数据(Globe Land30),验证分类的准确性。结果表明,GLAS大光斑波形数据对黄土高原的4种地类能够很好地进行区分,总分类精度高达87.68%,Kappa系数为65.79%。研究表明,GLAS波形数据可以作为获取土地覆盖信息的有效数据源,为研究黄土高原土地覆盖变化提供更丰富的数据支持。     

刍议《重庆历史地图集》第二卷的编制

以《重庆历史地图集》第二卷编制的具体情况为例,对图集的开本设计、内容结构设计、封面和版式设计、整体设计、创新源,以及图集编制取得的经验进行了论述,为以后类似图集的编制提供参考。     

The Effects of Land Cover Change on Regional Climate over the Eastern Part of Northwest China

A regional climate model(Reg CM4) is employed to investigate the impacts of land use/cover change(LUCC) on the climate over the eastern part of Northwest China(ENW) in the periods of 2001 and 2011. The results indicated that the LUCC in ENW, which was characterized by desert retreat, reforestation, and farmland expansion, led to significant local changes in surface air temperature(within ~0.3°C) and slight regional changes in precipitation(within ~15%) in summer. In the desert retreat area, the net absorbed shortwave radiation had a greater influence than evaporative cooling, leading to increases in the daily mean and maximum temperature. Besides, the daily mean and maximum temperatures increased in the reforestation area but decreased in the farmland expansion area. As surface albedo showed no significant change in these regions, the temperature increase in the reforestation area can be attributed to a decrease in evaporation, while the opposite effect appears to have been the case in the farmland expansion area.     

Interannual and Decadal Variations of Surface Solar Radiation over East China in the First Half of the 20th Century

Variability and long-term trends of sunshine duration(SSD) and total cloud cover(TCC) were studied based on surface observations from 10 meteorological stations over East China in the first half of the 20 th century. The correlation coefficients between SSD and diurnal temperature range(DTR), as well as TCC, were analyzed. SSD experienced a significant increasing trend(0.16 h d-1 per decade) from 1908 to 1936, and the maximum brightening was in autumn(0.33 h d-1 per decade). The good agreement between the variability of SSD and DTR, supported by the correlation coefficient between them of 0.72, implies that the SSD measurements were reliable. TCC showed a decreasing trend(-0.93% per decade) and was significantly inversely related to SSD(-0.74), indicating the variation of SSD was attributable to changes in cloud cover. The result was obviously different to that since the 1960 s, when clouds could not account for the decadal trend of surface solar radiation in China.     

Evaluating the economic damage of climate change on global coral reefs

This paper evaluates the global economic damage arising from the effects of climate change and associated carbon dioxide concentrations on the loss of coral reefs. We do this by first estimating the effects of sea surface temperature and carbon dioxide concentrations on coral cover. We develop a statistical relationship between coral coverage and sea surface temperature that indicates that the effects are dependent on the temperature range. For example, we find that increasing sea surface temperature causes coral coverage to decrease when sea surface temperature is higher than 26.85 °C, with the estimated reduction being 2.3% when sea surface temperature increases by 1%. In addition, we find that a 1% carbon dioxide increase induces a 0.6% reduction in global coral coverage. We also estimate the resultant loss in economic value based on a meta-analysis of the recreational and commercial value of reef coverage and a crude proportional approach for other value factors. The meta-analysis shows that the coral reef value decreases by 3.8% when coral cover falls by 1%. By combining these two steps we find that the lost value in terms of the global coral reef value under climate change scenarios ranges from US$3.95 to US$23.78 billion annually.     

长江三角洲碳排放与植被覆盖耦合协调时空格局及影响因素分析

通过构建评价指标体系和分析框架,利用综合指数法、耦合协调度模型和灰色关联度模型分析2005―2017年长江三角洲（长三角）碳排放与植被固碳耦合协调时空变化特征及驱动因素,并模拟政府决策优先级对耦合协调度趋势的影响。结果表明：长三角碳排放空间集聚特征显著,基本形成了以长江沿线和长三角东南沿海区域为核心的沿江沿海高排放带;长三角碳排放与植被固碳耦合协调度具有明显的空间分异特征,呈现出南京-上海沿线一般失调区域为核心的圈层结构特征;植被覆盖综合评价值高于碳排放综合评价值的地区耦合协调度普遍较高,人口的集聚和变化、城市建设和能源消耗对耦合协调度影响最大;同时,政府决策的优先级会显著影响耦合协调趋势。     

Retrieving multi-scale climatic variations from high dimensional time-series MODIS green vegetation cover in a tropical/subtropical mountainous island

【Title】
There are knowledge gaps in our understanding of vegetation responses to multi-scale climate-related variables in tropical/subtropical mountainous islands in the Asia-Pacific region. Therefore, this study investigated inter-annual vegetation dynamics and regular/irregular climate patterns in Taiwan. We applied principal component analysis （PCA） on 11 years （2001~2011） of high-dimensional monthly photosynthetically active vegetation cover （PV） derived from the Moderate Resolution Imaging Spectroradiometer （MODIS） and investigated the relationships between spatiotemporal patterns of the eigenvectors and loadings of each component through time and multi-scale climate-related variations. Results showed that the first five components contributed to 96.4% of the total variance. The first component （PC1, explaining 94.5% of variance） loadings, as expected, were significantly correlated with the temporal dynamics of the PV （r = 0.94）, which was mainly governed by regional climate. The temporal loadings of PC2 and PC3 （0.8% and 0.6% of variance, respectively） were significantly correlated with the temporal dynamics of the PV of forests （r = 0.72） and the farmlands （r = 0.80）, respectively. The low-order components （PC4 and PC5, 0.3% and 0.2% of variance, respectively） were closely related to the occurrence of drought （r = 0.49） and to irregular ENSO associated climate anomalies （r = -0.54）, respectively. Pronounced correlations were also observed between PC5 and the Southern Oscillation Index （SOI） with one to three months of time lags （r = -0.35 ~ -0.43, respectively）, revealing biophysical memory effects on the time-series pattern of the vegetation through ENSO-related rainfall patterns. Our findings reveal that the sensitivity of the ecosystems in this tropical/subtropical mountainous island may not only be regulated by regional climate and human activities but also be susceptible to large-scale climate anomalies which are crucial and comparable to previous large scale analyses. This study demonstrates that PCA can be an effective tool for analyzing seasonal and inter-annual variability of vegetation dynamics across this tropical/subtropical mountainous islandin the Pacific Ocean, which provides an opportunity to forecast the responses and feedbacks of terrestrial environments to future climate scenarios.     

An artificial neural network-based snow cover predictive modeling in the higher Himalayas

With trends indicating increase in temperature and decrease in winter precipitation, a significant negative trend in snow-covered areas has been identified in the last decade in the Himalayas. This requires a quantitative analysis of the snow cover in the higher Himalayas. In this study, a nonlinear autoregressive exogenous model, an artificial neural network （ANN）, was deployed to predict the snow cover in the Kaligandaki river basin for the next 30 years. Observed climatic data, and snow covered area was used to train and test the model that captures the gross features of snow under the current climate scenario. The range of the likely effects of climate change on seasonal snow was assessed in the Himalayas using downscaled temperature and precipitation change projection from - HadCM3, a global circulation model to project future climate scenario, under the AIB emission scenario, which describes a future world of very rapid economic growth with balance use between fossil and non-fossil energy sources. The results show that there is a reduction of 9% to 46% of snow cover in different elevation zones during the considered time period, i.e., 2Oll to 2040. The 4700 m to 52oo m elevation zone is the most affected area and the area higher than 5200 m is the least affected. Overall, however, it is clear from the analysis that seasonal snow in the Kaligandaki basin is likely to be subject to substantialchanges due to the impact of climate change.     

Radiative forcing over China due to albedo change caused by land cover change during 1990–2010

Land cover change affects surface radiation budget and energy balance by chang- ing surface albedo and further impacts the regional and global climate. In this article, high spatial and temporal resolution satellite products were used to analyze the driving mechanism for surface albedo change caused by land cover change during 1990-2010. In addition, the annual-scale radiative forcing caused by surface albedo changes in China＇s 50 ecological regions were calculated to reveal the biophysical mechanisms of land cover change affecting climate change at regional scale. Our results showed that the national land cover changes were mainly caused by land reclamation, grassland desertification and urbanization in past 20 years, which were almost induced by anthropogenic activities. Grassland and forest area decreased by 0.60% and 0.11%, respectively. The area of urban and farmland increased by 0.60% and 0.19%, respectively. The mean radiative forcing caused by land cover changes during 1990-2010 was 0.062 W/m2 in China, indicating a warming climate effect. However, spatial heterogeneity of radiative forcing was huge among different ecological regions. Farmland conversing to urban construction land, the main type of land cover change for the urban and suburban agricultural ecological region in Beijing-Tianjin-Tangshan region, caused an albedo reduction by 0.00456 and a maximum positive radiative forcing of 0.863 WIm2, which was presented as warming climate effects. Grassland and forest conversing to farmland, the main type of land cover change for the temperate humid agricultural and wetland ecological region in Sanjiang Plain, caused an albedo increase by 0.00152 and a maximum negative radiative forcing of 0.184 W/m2, implying cooling climate effects.