Accuracy comparison of gridded historical cultivated land data in Jiangsu and Anhui provinces

The spatial resolution of source data, the impact factor selection on the grid model and the size of the grid might be the main limitations of global land datasets applied on a regional scale. Quantitative studies of the impacts of rasterization on data accuracy can help improve data resolution and regional data accuracy. Through a case study of cropland data for Jiangsu and Anhui provinces in China, this research compared data accuracy with different data sources, rasterization methods, and grid sizes. First, we investigated the influence of different data sources on gridded data accuracy. The temporal trends of the History Database of the Global Environment(HYDE), Chinese Historical Cropland Data(CHCD), and Suwan Cropland Data(SWCD) datasets were more similar. However, different spatial resolutions of cropland source data in the CHCD and SWCD datasets revealed an average difference of 16.61% when provincial and county data were downscaled to a 10 × 10 km~2 grid for comparison. Second, the influence of selection of the potential arable land reclamation rate and temperature factors, as well as the different processing methods for water factors, on accuracy of gridded datasets was investigated. Applying the reclamation rate of potential cropland to grid-processing increased the diversity of spatial distribution but resulted in only a slightly greater standard deviation, which increased by 4.05. Temperature factors only produced relative disparities within 10% and absolute disparities within 2 km~2 over more than 90% of grid cells. For the different processing methods for water factors, the HYDE dataset distributed 70% more cropland in grid cells along riverbanks, at the abandoned Yellow River Estuary(located in Binhai County, Yancheng City, Jiangsu Province), and around Hongze Lake, than did the SWCD dataset. Finally, we explored the influence of different grid sizes. Absolute accuracy disparities by unit area for the year 2000 were within 0.1 km~2 at a 1 km~2 grid size, a 25% improvement over the 10 km~2 grid size. Compared to the outcomes of other similar studies, this demonstrates that some model hypotheses and grid-processing methods in international land datasets are truly incongruent with actual land reclamation processes, at least in China. Combining the model-based methods with historical empirical data may be a better way to improve the accuracy of regional scale datasets. Exploring methods for the above aspects improved the accuracy of historical cropland gridded datasets for finer regional scales.     

多源30 m分辨率土地覆被数据在蒙古高原的一致性分析和精度评价

蒙古高原土地覆被的变化表征着区域内生态环境的变化,许多环境问题的研究依赖于准确的土地覆被信息。因此,评估当前全球土地覆被数据在区域尺度上的准确性非常重要。本文以蒙古高原为研究区,从构成相似性、类型混淆程度、空间一致性、绝对精度4个方面,分析了GlobeLand30、GLC＿FCS30和FROM＿GLC 3种30m高分辨率全球土地覆被数据的一致性和准确性。结果表明：(1) 3种土地覆被数据都显示,草地和裸地是蒙古高原的主要土地覆被类型,任意2种数据的面积序列相关系数都优于0.95;(2) 3种土地覆被数据中完全一致的区域占蒙古高原总面积的61.87%,主要集中在土地表面异质性低的区域;(3) GLC＿FCS30数据的总体精度（78.33%）最高,GlobeLand30数据的总体精度（76.85%）次之,FROM＿GLC数据的总体精度（75.86%）最低;林地、草地、水体和裸地在3种土地覆被数据中的精度较高（75%以上）,灌丛、湿地等地类的精度较低（50%以下）。因此,对蒙古高原土地覆被进行全要素研究时,可以综合考虑选择总体精度最高的GLC＿FCS30数据。对特定地类研究的用户,可参考3种...     

民国中期湖南洞庭湖区耕地空间格局重建

土地覆被变化是影响气候系统的重要因素,在全球气候变化研究中具有重要的研究意义,网格化的历史土地利用数据集广泛应用于各类全球变化模式。本文以民国中期军事地形图为基础数据源,以现代行政区划为底图,重建了该时期湖南洞庭湖地区耕地的空间分布。同时为了与最新的HYDE 3.1数据集进行对比,在此基础上获得空间分辨率为10 km×10 km的耕地数据,结果表明：① 民国中期湖南洞庭湖区总耕地面积约为11 432.01 km ²,占研究区域面积的44%,其中汉寿县、华容县、鼎城区和澧县等地耕地面积分布最多,且以围堤耕地为主。分布相对较少的地区有临澧县、汨罗市、岳阳县,以非围堤耕地为主;② 该时段内洞庭湖区耕地垦殖率较大,最大值超过90%,其中高垦区（垦殖率>40%）范围占研究区面积61%,且主要分布在河湖港汊和冲积平原地貌单元上;中低垦区（<=40%）范围占研究区面积39%,主要分布在环湖丘陵地貌单元上;③ 与HYDE 3.1数据对比发现,单位格网（10 km×10 km）内重建的耕地面积结果误差大于40%的比例为17%,且表现为受河流分布影响为主。湖区相对周围重建结果差异更大,HYDE 3.1数据集重建区域尺度较大,较难考虑到小区域范围的水系分布状况,导致其在湖南洞庭湖区重建精度相对较低。     

High resolution land cover datasets integration and application based on Landsat and Globcover data from 1975 to 2010 in Siberia

Land cover is recognized as one of the fundamental terrestrial datasets required in land system change and other ecosystem related researches across the globe. The regional differentiation and spatial-temporal variation of land cover has significant impact on regional natural environment and socio-economic sustainable development. Under this context, we reconstructed the history land cover data in Siberia to provide a comparable datasets to the land cover datasets in China and abroad. In this paper, the European Space Agency(ESA) Global Land Cover Map(GlobCover), Landsat Thematic Mapper(TM), Enhanced Thematic Mapper(ETM), Multispectral Scanner(MSS) images, Google Earth images and other additional data were used to produce the land cover datasets in 1975 and 2010 in Siberia. Data evaluation show that the total user′s accuracy of land cover data in 2010 was 86.96%, which was higher than ESA GlobCover data in Siberia. The analysis on the land cover changes found that there were no big land cover changes in Siberia from 1975 to 2010 with only a few conversions between different natural forest types. The mainly changes are the conversion from deciduous needleleaf forest to deciduous broadleaf forest, deciduous needleleaf forest to mixed forest, savannas to deciduous needleleaf forest etc., indicating that the dominant driving factor of land cover changes in Siberia was natural element rather than human activities at some extent, which was very different from China. However, our purpose was not just to produce the land cover datasets at two time period or explore the driving factors of land cover changes in Siberia, we also paid attention on the significance and application of the datasets in various fields such as global climate change, geopolitics, cross-border cooperation and so on.     

基于小流域抽样单元的中国FROM-GLC30数据精度评价

土地覆盖数据是全球环境变化相关研究和应用的重要数据基础,在诸多领域中被广泛运用.FROM-GLC30 2017数据是最新的全球高分辨率(30m)公开土地覆盖数据集之一.土地覆盖数据集的精度是其在不同领域应用中的重要问题.本研究旨在探讨FROM-GLC30 2017数据集精度在全国范围内的空间分布,并比较不同土地覆盖类型...     

基于普查和手机定位数据的乡镇尺度人口空间化方法研究

人口在空间上的实际分布是人口地理学研究的基础和热点问题。目前全球不同尺度的人口空间化数据产品因生产方法、数据源等有较大差异,空间化产品的一致性存在较大差异,尤其是共性需求集中的1 km数据产品。本文以京津冀地区为研究区,基于2000年乡镇尺度的人口普查数据和可开放获得的手机定位数据,利用光影投射法计算人口分布权重,结合面积权重法和指数平滑法得到京津冀地区1 km分辨率的人口空间化结果PJ2000。该产品较好地反映了京津冀人口实际分布细节特征。经精度评定,PJ2000人口空间化的总体精度为90%,人口空间化相对误差小于0.5的乡镇（街道）数约占87%,PJ2000与2000年乡镇街道人口统计数据pop2000的相关系数r高达0.95。结果证明,结合乡镇尺度人口统计数据和手机定位数据等多源数据所构建的人口空间化模型,所获1 km分辨率人口密度数据集精度得到显著提高。     

Epiphytic orchids and their ecological niche under anthropogenic influence in central Himalayas,Nepal

The survival chance of epiphytic orchids today not only depends on the natural site conditions required by the orchids but also on anthropogenic changes in site conditions.This study answers two questions:(1) What is the ecological niche of the different epiphytic orchid species?(2) What are the ecological factors that threaten epiphytic orchid's population under anthropogenic disturbances? Our study area was the Kathmandu valley,Nepal,with its subtropical forest.We established 156 systematically selected sampling points in the Kathmandu area covering different types of ecosystems under human impacts such as densely populated area,agricultural land,mixed agricultural and settled area,old tree patches,and a natural forest in a national park.The ecological niche of the orchid species was analyzed with a principal component analysis(PCA).The correlations between the different site factors were statistically significant.Spearman's rank correlation matrices showed that the variables land-use intensities with altitude,and height with diameter in breast height(dbh) of host had the highest significant positive correlation coefficient(0.67 and 0.64 respectively).On the other hand,host bark p H and altitude as well as land use had a significantly strong negative correlation coefficient(-0.80 and-0.61,respectively).Different epiphytic orchid species interact differently with the given set ofenvironmental factors:for occurrence of Vanda cristata there is no single environmental factor of special influence,while for Rhynchostylis retusa high bark p H and high light availability are important.First two axis of the PCA explained more than 50% of the total variance.Most orchid species occupy a specific,narrow niche in this ecological space.The main causes of anthropogenic influence of orchid population in the Kathmandu Valley are loss of adequate host trees(species and size) and increasing air pollution,resulting in increasing host bark p H.     

基于NSIDC海冰产品的FY北极海冰数据集优化

北极海冰对全球气候起着非常重要的调制作用,海冰范围是海冰监测的基本参数。近40年,北极地区持续变暖,北极海冰显著减少,进而引发北极自然环境恶化、北半球极端天气频发、全球海平面上升等一系列环境和气候问题。准确获取北极海冰范围及其演变趋势,确定海冰变化对全球气候系统的响应,是研究和预测全球气候变化趋势的关键之一。HasISST和OISST海冰数据集在海冰监测中应用最为广泛,可为北极地区长时间序列海冰变化研究提供基础数据,但这2套数据集空间分辨率相对较低,应用于北极关键区对中国气候响应研究方面存在很大的局限,为解决这一问题和弥补国内海冰监测微波遥感数据的空白,2011年6月27日,国家卫星气象中心（National Satellite Meteorological Center, NSMC）发布了FY（Fengyun, FY）北极海冰数据集,该数据集利用搭载在FY卫星上的微波成像仪（Microwave Radiation Imager, MWRI）数据,使用Enhance NASA Team算法制作,该算法利用前向辐射传输模型模拟北极地区4种海表类型（海水、新生冰、一年冰和多年冰）在不同大气条件下MWRI辐射亮温,进而得到每种大气条件下0~100%的海冰覆盖度查找表（海冰覆盖度每次增加1%）,通过观测值与模拟值的比对得到海冰覆盖度,由该数据集计算得到的北极海冰范围在大部分区域与实际情况相符。该产品虽已进行通道间匹配误差修正和定位精度偏差订正,但由于其搭载的微波成像仪（Microwave Radiation Imager, MWRI）天线长度有限,造成传感器探测到的地物回波信号相对较弱,难以区分海冰和近岸附近的陆地,影响了该数据集的精度和应用。为解决这一问题,本文基于美国冰雪中心（National Snow and Ice Data Center, NSIDC）发布的海冰产品对FY海冰数据集进行优化,NSIDC产品利用判断矩阵对海岸线附近的像元进行识别,并对误差像元进行不同程度的修正,由NSIDC产品计算得到的北极海冰范围与实际情况更为符合。数据集优化大大提高了FY海冰数据集的精度,研究结果表明,优化后FY海冰数据集与NSIDC产品相关系数高达0.9997,且二者日、月、年平均最大海冰范围偏差仅为3.5%、1.9%、0.9%,且FY海冰数据集优化过程对其较好的空间分异特征无明显影响。该数据集可正确地反映北极海冰范围及其变化情况,且海岸线附近海冰的分布情况更准确,可为北极海冰变化研究提供可靠的基础数据。     

基于地表能量平衡的厦门岛城市功能区人为热排放分析

人为热排放不仅是城市热岛形成的重要因子,而且是与能源消耗密切相关的指标,对其大小和变化特征进行分析有利于减缓城市热岛与节能减排。本文以厦门岛为研究区,利用2009年多时相的Landsat TM影像和地表能量平衡模型反演出不同季节的人为热排放,在此基础上结合IKONOS影像解译的城市功能区,分析不同类型城市功能区人为热排放的时空变化特征。结果表明：不同类型城市功能区的人为热排放均在夏季达到最大,春季最小;工业区的人为热排放一直高于其他类型的城市功能区;工业区人为热排放高值区主要集中厦门岛西部传统的重点工业区,交通区人为热排放高值区的空间分布与厦门岛“三纵四横”的交通干线分布格局相吻合,居住区人为热排放高值区主要集中在旧城区,商业及公共设施区人为热排放高值区主要集中在单体建筑大的商圈和公共设施;总体上厦门岛西部的人为热排放比东部要高。这种时空分布的差异性与用地类型、人口数量与经济发展程度密切相关,而且建筑物的密度、高度和下垫面的材料通过影响其他地表通量来改变人为热排放的大小。通过分析不同城市功能区人为热排放的时空变化特征,可以从更微观的角度理解城市热环境和能源利用现状,为促进城市可持续发展提供理论依据。     

Analysis on long-term change of sea surface temperature in the China Seas

Long-term change of sea surface temperature (SST) in the China Seas from 1900 to 2006 is examined based on two different observation datasets (HadISST1 and HadSST3). Similar to the Atlantic, SST in the China Seas has been well observed dur-ing the past 107 years. A comparison between the reconstructed (HadISST1) and un-interpolated (HadSST3) datasets shows that the SST warming trends from both datasets are consistent with each other in most of the China Seas. The warming trends are stronger in winter than in summer, with a maximum rate of SST increase exceeding 2.7℃ (100 year)-1 in the East China Sea and the Taiwan Strait during winter based on HadISST1. However, the SST from both datasets experienced a sudden decrease after 1999 in the China Seas. The estimated trend from HadISST1 is stronger than that from HadSST3 in the East China Sea and the east of Taiwan Island, where the difference in the linear SST warming trends are as large as about 1℃ (100 year)-1 when using respectively HadISST1 and HadSST3 datasets. When compared to the linear winter warming trend of the land surface air temperature (1.6℃ (100 year)-1), HadSST3 shows a more reasonable trend of less than 2.1℃ (100 year)-1 than HadISST1’s trend of larger than 2.7℃ (100 year)-1 at the mouth of the Yangtze River. The results also indicate large uncertainties in the estimate of SST warming patterns.     

Spatial-temporal pattern and population driving force of land use change in Liupan Mountains region, southern Ningxia, China

The Liupan Mountains is located in the southern Ningxia Hui Autonomous Region of China, which forms an important dividing line between landforms and bio-geographic regions. The populated part of the Liupan Mountains region has suffered tremendous ecological damages over time due to population pressure, excessive demand and inappropriate use of agricultural land resources. In this paper, datasets of land use between 1990 and 2000 were obtained from Landsat TM imagery, and then spatial models were used to characterize landscape conditions. Also, the relationship between the population density and land use/cover change （LUCC） was analyzed. Results indicate that cropland, forestland, and urban areas have increased by 44,186ha, 9001ha and 1550ha, respectively while the grassland area has appreciably decreased by 54,025ha in the study period. The decrease in grassland was most notable. Of the grassland lost, 49.4% was converted into cropland. The largest annual land conversion rate in the study area was less than 2%. These changes are attributed to industrial and agricultural development and population growth. To improve the eco-economic conditions in the study region, population control, urbanization and development of an ecological friendly agriculture were suggested.     

基于DEM的福建省土质滑坡敏感性评价

已有滑坡敏感性研究中对评价指标的选取可以归结为气象、水文、地形、地质、植被、人类活动等方面,这些因子指标来源不一,在缺少数据资料地区难以完整收集。针对这个问题,考虑到目前DEM数据的广泛可获得性及其对滑坡评价的重要性,本文仅利用DEM数据及其派生因子,研究土质滑坡敏感性评价的可行性。研究中把评价因子分为2组：第1组数据仅由DEM派生,包括高程、坡度、坡向、地形起伏度、曲率、水流强度指数（Stream Power Index, SPI）、沉积运输指数（Sediment Transport Index, STI）、地形湿度指数（Topographic Wetness Index, TWI）;第2组数据作为对照组,除了包括上述DEM派生的8个因子外,同时加入植被覆盖度、土地利用、土壤类型、年均降雨量因子。本文分别选取逻辑回归模型和证据权法,基于上述2组评价因子,以德化县为例对比2组因子评价结果,利用第1组和第2组数据进行滑坡敏感性评价,结果精度分别为73%和83%。结果表明,仅利用DEM数据进行土质滑坡敏感性评价方法可行,可以为缺乏资料区滑坡敏感性评价提供借鉴。     

Remote Sensing Data and SLEUTH Urban Growth Model: As Decision Support Tools for Urban Planning

Sri Lanka is experiencing speedy urbanization by converting the agriculture land and other natural land cover into built-up land. The urban population of Sri Lanka is expected to reach to 60% by 2030 from 14% in 2010. The rapid growth in urban population and urban areas in Sri Lanka may cause serious socioeconomic disparities, if they are not handled properly. Thus, planners in Sri Lanka are in need of information about past and future urban growth patterns to plan a better and sustainable urban future for Sri Lanka. In this paper, we analyzed the characteristics of past land use and land cover trends in Matara City of Sri Lanka from 1980 to 2010 to assess the historic urban dynamics. The land use change detection analysis based on remote sensing datasets reveal that the conversion of homestead/ garden and paddy into urban land is evident in Matara City. The historic urban trends are projected into the near future by using SLEUTH urban growth model to identify the hot spots of future urbanization and as well as the urban growth patterns in Matara City up to the basic administrative level, i.e., Grama Niladari Divisions (GND). The urban growth simulations for the year 2030 reveal that 29 GNDs out of 66 GNDs in Matara City will be totally converted into urban land. Whereas, 28 GNDs will have urban land cover from 75% to 99% by 2030. The urban growth simulations are further analyzed with respect to the proposed Matara city development plan by the Urban Development Authority (UDA) of Sri Lanka. The results show that the UDA’s city development plan of Matara will soon be outpaced by rapid urbanization. Based on the calibration and validation results, the SLEUTH model proved to be a useful planning tool to understand the near future urbanization of Sri Lankan cities.     

CG-LTDR地表覆盖数据对BCC_AVIM 1.0陆面温度模拟的影响研究

本文将CG-LTDR数据集中的地表覆盖数据产品应用于北京气候中心陆面模式（BCC_AVIM 1.0）中,并通过数值模拟分析不同覆盖类型的数据（冰川、湿地、湖泊、植被PFT）更新对模拟结果的影响。结果表明,新数据对不同地表类型的基本分布特征都有合理描述,但与模式中原有数据的差异明显,表现为冰川比例在格陵兰岛西部地区增加,湿地在大部分地区都减少,湖泊在北美和欧亚大陆中高纬地区的比例减少,但青藏高原及周边地区小幅增加,植被PFT的差异最明显。与采用模式原地表覆盖数据的控制试验相比,新数据引入所致的改变,主要局限于地表覆盖数据改变的区域。冰川数据更新使高纬冰川积雪区和青藏高原的温度降低,湿地数据提高了欧洲和北美主要水区的地面温度,湖泊数据有效降低了亚洲地区的温度,更新植被PFT的影响最广泛,使得南美、南非、东北亚、北美和澳洲大部分地区的温度升高,而中国华南江南地区以及南亚地区的温度降低,但在一些地区的模拟效果降低。数据全部更新引起的温度改变最明显,但并不是所有类型的简单叠加,尤其在地表复杂区域。不同的覆盖类型数据更新,可在一定程度上减少模式对于地表温度的模拟偏差（如格陵兰岛西部和青藏高原地区、欧洲内陆湖区的温度偏高）,因此需适当选用更新的数据。     

30年来蒙古国和内蒙古的LUCC区域分异

本文以欧空局300m土地覆盖数据集为基础,参考20世纪70年代至2005年2期蒙古高原遥感影像,建立20世纪70年代、2005年2期土地利用及动态数据库,结合土地利用变化数量模型,分析了蒙古国与内蒙古的土地利用类型转换情况。对比分析蒙古国和内蒙古近30年来的土地利用变化强度及各地类间的转移变化,揭示2个区域的LUCC分异规律,并对土地变化的驱动力进行分析。结果显示:在自然条件及人类扰动共同作用下,蒙古国及内蒙古均表现出草地面积逐年减少,草地退化趋势明显;裸地面积不断增加,沙漠化现象严重;农田及城镇建设用地面积持续增长;水域面积呈现衰减;未利用地是其他各种土地利用类型增加的主要来源;由于人类扰动差异,蒙古国林地面积略有减少,内蒙古林地面积大幅增加。气候干暖化、人口增长,政策及社会经济发展等是驱动蒙古高原土地利用变化的主要因素。     

卫星气候数据集的应用研究与发展分析

卫星气候数据集是卫星气候研究的基础。在规范卫星气候数据集基本概念的基础上,针对现有基本气候数据集（FCDR）和专题气候数据集（TCDR）的分类方式,无法反映卫星气候数据特点的问题,认为应将专题气候数据集进一步划分为单一遥感仪器专题气候数据集、多种遥感仪器融合专题气候数据集及卫星与多源资料融合专题气候数据集等几类。这种分类方法便于用户更好地了解和使用卫星气候数据。然后,重点围绕基本气候变量和基本卫星气候变量含义、卫星气候数据集生产规范、国内外主要卫星气候数据生产计划等方面,综述了卫星气候数据集建设及规范化生产已取得的最新研究进展。在此基础上,分析了卫星气候数据集建设和应用中存在的主要问题,展望了卫星气候数据集发展,同时对我国卫星气候数据集建设提出具体建议。     

Comparisons of several evaporation/precipitation datasets for the Bohai Sea based on salinity simulation

Evaporation (E) rate and precipitation (P) rate are two significant meteorological elements required in the ocean baroclinic modeling as external forcings. However, there are some uncertainties in the currently used E/P rates datasets, especially in terms of the data quality. In this study, we collected E/P rates data from ERA-40, NCEP/NCAR Reanalysis, HOAPS for the Bohai Sea and nine routine stations around Laizhou Bay, and made comparisons among them. It was found that the differences in E/P rates between land and sea are remarkable, which was due to the difference in underlying surfaces. Therefore, the traditional way of using E/P rates acquired on land directly at sea is not correct. Since no final conclusion has been reached concerning the net water transport between the Bohai Sea and the Yellow Sea, it is unfeasible to judge the adequacy of the four kinds of data by using the water budget equation. However, the E/P rates at ERA-40 sea points were considered to be the optimal in terms of temporal/spatial coverage and resolution for the hindcast of salinity variation in the Bohai Sea. Besides, using the 3-D hydrodynamic model HAMSOM (HAMburg Shelf Ocean Model), we performed numerical experiments with different E/P datasets and found that the E/P rates at sea points from ERA-40 dataset are better than those from NCEP/NCAR Reanalysis dataset. If NCEP/NCAR Reanalysis E/P rates are to be used, they need to be adjusted and tested prior to simulation so that more close-to-reality salinity values can be reproduced.     

Spatial patterns and driving forces of land change in Tibetan-inhabited Three Rivers Headwaters region,China

The Three Rivers Headwaters Region(TRHR) plays a key role in regulating water supply and climate of East Asia. A comprehensive understanding of the processes and driving forces of the long-term land use dynamics of the TRHR is needed to guide sustainable land resource management and regional ecological conservation strategies. This study examined long-term land change patterns in the TRHR and investigated the driving forces of the change. First, Landsat TM/ETM+ images covering TRHR of four time points from 1987 to 2016 were used to derive land use patterns, and statistical metrics were applied to quantify the spatial and temporal changes. Second, Principal Component Analysis and correlation analysis were employed to analyze environmental and social-economic data to identify the driving forces of land use change. Third, potential influences of the religion of Tibetan Buddhism on land use change were explored using GIS analysis, questionnaire survey and field observation. Results showed that areas of barren land, agricultural land, and built-up land largely increased, while areas of grassland and forest greatly decreased, with the highest change rate occurring in the most recent decade of analysis(from 2007 to 2016). Among the three headwater regions, the Yellow River Headwater Region showed an overall higher changing speed than the other two headwater regions. The regional driving forces of change in TRHR includedsocial-economic development, climatic condition, pressure of population growth, and environmental protection activities. It was also found that Tibetan Buddhism can help slow down the changes caused by human activities.     

中国建设用地空间格局分析

全面准确地分析中国建设用地空间格局,是衡量城市景观的生态环境效应和制定区域发展战略的重要依据。为此,本文基于空间分辨率为12 m的2012年的全球城市足迹数据,分别在国家、经济区和城市群量化了中国建设用地空间格局。结果表明,12 m分辨率的数据能更细致和准确地刻画中国建设用地的特征。2012年中国建设用地面积为1.73×10⁵ km²,占中国陆地总面积的1.81%。从建设用地的空间格局来看,城市群尺度的建设用地破碎度最高,其建设用地平均斑块密度分别是国家和经济区平均水平的3.66倍和1.62倍。进一步分析表明,社会经济和地形因素共同影响建设用地空间格局。今后,应针对建设用地空间格局破碎问题,因地制宜地制定合理的措施,推动中国建设用地的合理发展。     

Last 150-year variability in Japanese anchovy (Engraulis japonicus) abundance based on the anaerobic sediments of the Yellow Sea Basin in the western North Pacific

Relatively short historical catch records show that anchovy populations have exhibited large variability over multi-decadal timescales. In order to understand the driving factors (anthropogenic and/or natural) of such variability, it is essential to develop long-term time series of the population prior to the occurrence of notable anthropogenic impact. Well-preserved fish scales in the sediments are regarded as useful indicators reflecting the fluctuations of fish populations over the last centuries. This study aims to validate the anchovy scale deposition rate as a proxy of local anchovy biomass in the Yellow Sea adjoining the western North Pacific. Our reconstructed results indicated that over the last 150 years, the population size of anchovy in the Yellow Sea has exhibited great fluctuations with periodicity of around 50 years, and the pattern of current recovery and collapse is similar to that of historical records. The pattern of large-scale population synchrony with remote ocean basins provides further evidence proving that fish population dynamics are strongly affected by global and basin-scale oceanic/climatic variability.