The diurnal and seasonal characteristics of urban heat island variation in Beijing city and surrounding areas and impact factors based on remote sensing satellite data

Based on the land surface temperature (LST), the land cover classification map,vegetation coverage, and surface evapotranspiration derived from EOS-MODIS satellite data, and by the use of GIS spatial analytic technique and multivariate statistical analysis method, the urban heat island (UHI) spatial distribution of the diurnal and seasonal variabilities and its driving forces are studied in Beijing city and surrounding areas in 2001. The relationships among UHI distribution and landcover categories, topographic factor, vegetation greenness, and surface evapotranspiration are analyzed. The results indicate that: (i) The significant UHI occur in Beijing city areas in the four seasons due to high heat capacity and multi-reflection of compression building, as well as with special topographic features of its three sides surrounded by mountains,especially in the summer. The UHI spatial distribution is corresponding with the urban geometry structure profile. The LST difference is approximately 4-6℃ between Beijing city and suburb areas, comparatively is 8- 10℃ between Beijing city area and outer suburb area in northwestern regions. (ii) The UHI distribution and intensity in daytime are different from nighttime in Beijing city area, the nighttime UHI is obvious. However, in the daytime, the significant UHI mainly appears in the summer, the autumn takes second place, and the UHI in the winter and the spring seem not obvious. The surface evapotranspiration in suburb areas is larger than that in urban areas in the summer, and high latent heat exchange is evident, which leads to LST difference between city area and suburb area. (iii) The reflection of surface landcover categories is sensitive to the UHI, the correlation between vegetation greenness and UHI shows obviously negative.The scatterplot shows that there is the negative correlation between NDVI and LST (R2 = 0.6481).The results demonstrate that the vegetation greenness is an important factor for reducing the UHI,and large-scale construction of greenbelts can considerably reduce the UHI effect.     

Effect of the Initial Vortex Structure on Intensity Change During Eyewall Replacement Cycle of Tropical Cyclones: A Numerical Study

This study investigates the effect of the initial tropical cyclone (TC) vortex structure on the intensity change during the eyewall replacement cycle (ERC) of TCs based on two idealized simulations using the Weather Research and Forecasting (WRF) model. Results show that an initially smaller TC with weaker outer winds experienced a much more drastic intensity change during the ERC than an initially larger TC with stronger outer winds. It is found that an initially larger TC vortex with stronger outer winds favored the development of more active spiral rainbands outside the outer eyewall, which slowed down the contraction and intensification of the outer eyewall and thus prolonged the duration of the concentric eyewall and slow intensity evolution. In contrast, the initially smaller TC with weaker outer winds corresponded to higher inertial stability in the inner core and weaker inertial stability but stronger filamentation outside the outer eyewall. These led to stronger boundary layer inflow, stronger updraft and convection in the outer eyewall, and suppressed convective activity outside the outer eyewall. These resulted in the rapid weakening during the formation of the outer eyewall, followed by a rapid re-intensification of the TC during the ERC. Our study demonstrates that accurate in- itialization of the TC structure in numerical models is crucial for predicting changes in TC intensity during the ERC. Additionally, monitoring the activity of spiral rainbands outside the outer eyewall can help to improve short-term intensity forecasts for TCs experiencing ERCs.     

Mapping and assessing crop diversity in the irrigated Fergana Valley,Uzbekistan

Crop diversity (e.g. the number of agricultural crop types and the level of evenness in area distribution) in the agricultural systems of arid Central Asia has recently been increased mainly to achieve food security of the rural population, however, not throughout the irrigation system. Site-specific factors that promote or hamper crop diversification after the dissolvent of the Soviet Union have hardly been assessed yet. While tapping the potential of remote sensing, the objective was to map and explain spatial patterns of current crop diversity by the example of the irrigated agricultural landscapes of the Fergana Valley, Uzbekistan. Multi-temporal Landsat and RapidEye satellite data formed the basis for creating annual and multi-annual crop maps for 2010–2012 while using supervised classifications. Applying the Simpson index of diversity (SID) to circular buffers with radii of 1.5 and 5 km elucidated the spatial distribution of crop diversity at both the local and landscape spatial scales. A variable importance analysis, rooted in the conditional forest algorithm, investigated potential environmental and socio-economic drivers of the spatial patterns of crop diversity. Overall accuracy of the annual crop maps ranged from 0.84 to 0.86 whilst the SID varied between 0.1 and 0.85. The findings confirmed the existence of areas under monocultures as well as of crop diverse patches. Higher crop diversity occurred in the more distal parts of the irrigation system and sparsely settled areas, especially due to orchards. In contrast, in water-secure and densely settled areas, cotton-wheat rotations dominated due to the state interventions in crop cultivation. Distances to irrigation infrastructure, settlements and the road network influenced crop diversity the most. Spatial explicit information on crop diversity per se has the potential to support policymaking and spatial planning towards crop diversification. Driver analysis as exemplified at the study region in Uzbekistan can help reaching the declared policy to increase crop diversity throughout the country and even beyond.     

基于多时相Landsat影像的中亚地区植被覆盖遥感监测

针对中亚地区的强生态脆弱性、高敏感性特征,有必要开展广域、长期的植被覆盖监测以匹配"绿色丝绸之路"的可持续发展目标。鉴于此,联合Landsat 5和Landsat 8卫星数据集,利用Google Earth Engine(GEE)地理空间数据云计算平台,估算了中亚地区1993—2018年间共12期的植被覆盖度。结果表明:(1)中亚地区植被覆盖总体水平较低,但也具有较为显著的空间异质性。(2)中亚地区1993—2018年间多数区域植被覆盖趋势较为稳定,哈萨克斯坦丘陵、费尔干纳盆地等区域植被覆盖度呈增加趋势,乌拉尔河流域和锡尔河流域等区域植被覆盖趋势为负。(3)植被覆盖度时序特征上,中亚地区1993—2018年间总体植被覆盖度累积增加3%,其中吉尔吉斯斯坦和塔吉克斯坦植被覆盖分别增加3.96%和5.86%。(4)裸土区呈退缩趋势,面积总计减少25.9×104km2,低植被覆盖区、中植被覆盖区和高植被覆盖区范围在呈现出的振荡式增加。研究结合遥感大数据和地理云计算对中亚地区进行区域尺度的植被覆盖动态监测,能对中亚地区生态评估和演替分析提供技术支持和定量数据。     

Local provenance in rehabilitation of degraded landscapes: a case study from the Hawkesbury–Nepean catchment, Australia

Throughout Australia thousands of volunteers are engaged in Landcare projects that should help rehabilitate degraded landscapes. Many of these projects involve tree planting, but their seed is not necessarily of local provenance. Based on a survey of 85 Landcare groups working in the Hawkesbury–Nepean catchment, data were collected about Landcare groups' knowledge of their seed source, understanding of local provenance and the ecosystem in which they were planting trees and the source of funding for their projects. The findings from the study indicate that about one in five (21%) of the groups surveyed that introduced plant material were not aware of local provenance issues. Indirect indications were that a large number of Landcare groups state-wide may be doing more harm than good to the landscape while trying to rehabilitate it. The data also showed that one in seven (13%) of the groups funded by the Australian Government through the Natural Heritage Trust (NHT) had limited awareness of local provenance issues. With millions of dollars being spent on 'works on the ground', it would be prudent to allocate some funds to document and monitor current Landcare activities, so that the environmental outcomes can be quantified and more effective Landcare policies can be developed in the future.     

西双版纳土地利用/覆盖格局的热环境效应研究

利用Landsat TM/ETM＋数据的热红外波段,通过单通道算法,反演了中国热带西双版纳地区的地表温度,并对西双版纳地表温度演变的规律进行了分析,结果显示：（1）研究期间,西双版纳土地利用/覆盖发生了剧烈变化,有林地面积不断减少,旱地、灌木林、茶园与橡胶园面积不断增加;（2）旱地、荒草地、茶园、建设用地的地表真实温度的平均值较高,水体和有林地的平均温度较低;（3）旱地、灌木林、有林地、荒草地和橡胶园对区域的热效应贡献较大,水体、水浇地、建设用地、滩涂和水体的热效应贡献较小;有林地的热单元权重有不断减少的趋势,灌木林与旱地的热单元权重有不断增加的趋势;（4）西双版纳土地利用/覆盖的剧烈变化改变了区域地表温度的分布格局,最终可能会导致地方气候变化。需要进一步开展西双版纳地区LUCC—气候—生态系统耦合研究,深入研究区域LUCC特别是橡胶园的时空变化过程及其气候/生态效应、气候变化与LUCC过程的互馈机制,为实现区域可持续发展提供科学依据。     

巴丹吉林沙漠南缘的植物固沙问题

在野外考察的基础上,选择13个典型样地,研究了巴丹吉林沙漠南缘植被组成、群落特征和植被格局。结果表明：调查的样地中有荒漠植物31种,其中灌木12种,多年生草本11种,一二年生草本8种。种群密度3 000—14 000株·hm^-2,优势种在群落中地位显著,群落稳定性较差;植被斑块面积小、最大斑块指数低。沙漠南缘年降水量虽然仅100 mm左右,但有霸王（Zygophyllum xanthoxylon）、红砂（Reaumuria soongarica）和沙蒿（Artemisia desertorum）等灌木和半灌木天然植物群落分布,有白刺（Nitraria tangutorum）和膜果麻黄（Ephedra przewalskii）灌丛沙堆,沙丘上生长着沙拐枣（Calligonum mongolicum）、沙鞭（Psammochloa villosa）等种群生存,且在沙漠延伸带流动沙丘上已成功建立了梭梭（Haloxylon ammodendron）人工固沙植被,表明在巴丹吉林沙漠南缘建立以乡土植物为主的固沙植被是可行的。在未来研究中,应在山水林田湖草沙生命共同体理念下加强从区域尺度上解析水、植被和沙的关系,系统了解生态系统的原真性、完整性和连通性及生态系统稳定性维持等问题,优化生态景观格局,确定生态保护目标和建设规模,同时要加强对乡土植物适应干旱风沙机制和扩繁保育技术研究,以便为区域生态建设和生态保护提供科技支撑。     

Landscape Controls on Structural Variation in Eucalypt Vegetation Communities: Woronora Plateau,Australia

Quantification of landscape-based vegetation structural variation and pattern is a significant goal for a variety of ecological, monitoring and biodiversity studies. Vegetation structural metrics, derived from airborne laser scanning (ALS or aerial light detection and ranging—LiDAR) and QuickBird satellite imagery, were used to establish the degree of plot-based vegetation variation at a hillslope scale. Topographic position is an indicator of energy and water availability, and was quantified using DEM-based insolation and topographic wetness, respectively, stratifying areas into hot-warm-cold and wet-moist-dry topographic classes. A range of vegetation metrics—maximum and modal canopy height, crown cover, foliage cover, NDVI and semivariance—were compared among randomly selected plots from each topographic class. NDVI increases with increasing landscape wetness, whereas ALS-derived foliage cover decreases with increasing insolation. Foliage cover is well correlated with crown cover (R ² =0.65), and since foliage cover is readily calculable for whole-of-landscape application, it will provide valuable and complementary information to NDVI. Between-plot heterogeneity increases with increasing wetness and decreasing insolation, indicating that more sampling is required in these locations to capture the full range of landscape-based variability. Pattern analysis in landscape ecology is one of the fundamental requirements of landscape ecology, and the methods described here offer statistically significant, quantifiable and repeatable means to realise that goal at a fine spatial grain.     

Incorporating Spatial Dependence in Predictive Vegetation Models: Residual Interpolation Methods*

Predictive vegetation modeling can be used statistically to relate the distribution of vegetation across a landscape as a function of important environmental variables. Often these models are developed without considering the spatial pattern that is inherent in biogeographical data, resulting from either biotic processes or missing or misspecified environmental variables. Including spatial dependence explicitly in a predictive model can be an efficient way to improve model accuracy with the available data. In this study, model residuals were interpolated and added to model predictions, and the resulting prediction accuracies were assessed. Adding kriged residuals improved model accuracy more often than adding simulated residuals, although some alliances showed no improvement or worse accuracy when residuals were added. In general, the prediction accuracies that were not increased by adding kriged residuals were either rare in the sample or had high nonspatial model accuracy. Regression interpolation methods can be an important addition to current tools used in predictive vegetation models as they allow observations that are predicted well by environmental variables to be left alone, while adjusting over‐ and underpredicted observations based on local factors.     

基于TIC的多时相遥感影像相对辐射归化处理

采用不变点群法(temporally invariant cluster,TIC),由两时相影像的NDVI点密度图确定两个TIC中心并建立辐射归化处理方程,对影像的NDVI进行相对辐射归化处理。与其它辐射归化处理方法相比,该方法简单、有效且精度高,对轻微的植被物候变化敏感且影像不变特征点较少时也能进行辐射归化处理,可有效应用于土地利用/覆盖、植被物候及景观等变化监测。