Modelling tropical cyclone risks for present and future climate change scenarios using geospatial techniques     

Muhammad Al-Amin Hoque  Stuart Phinn  Chris Roelfsema  Iraphne Childs 《International Journal of Digital Earth》2018,11(3):246-263

Tropical cyclones and their devastating impacts are of great concern to coastal communities globally. An appropriate approach integrating climate change scenarios at local scales is essential for producing detailed risk models to support cyclone mitigation measures. This study developed a simple cyclone risk-modelling approach under present and future climate change scenarios using geospatial techniques at local scales, and tested using a case study in Sarankhola Upazila from coastal Bangladesh. Linear storm-surge models were developed up to 100-year return periods. A local sea level rise scenario of 0.34?m for the year 2050 was integrated with surge models to assess the climate change impact. The resultant storm-surge models were used in the risk-modelling procedures. The developed risk models successfully identified the spatial extent and levels of risk that match with actual extent and levels within an acceptable limit of deviation. The result showed that cyclone risk areas increased with the increase of return period. The study also revealed that climate change scenario intensified the cyclone risk area by 5–10% in every return period. The findings indicate this approach has the potential to model cyclone risk in other similar coastal environments for developing mitigation plans and strategies.  相似文献   

Modelling coastal land use change by incorporating spatial autocorrelation into cellular automata models   总被引：1，自引：0，他引：1  

Yongjiu Feng  Qianqian Yang  Zhonghua Hong  Li Cui 《国际地球制图》2018,33(5):470-488

This paper presents a spatial autoregressive (SAR) method-based cellular automata (termed SAR-CA) model to simulate coastal land use change, by incorporating spatial autocorrelation into transition rules. The model captures the spatial relationships between explained and explanatory variables and then integrates them into CA transition rules. A conventional CA model (LogCA) based on logistic regression (LR) was studied as a comparison. These two CA models were applied to simulate urban land use change of coastal regions in Ningbo of China from 2000 to 2015. Compared to the LR method, the SAR model yielded smaller accumulated residuals that showed a random distribution in fitting the CA transition rules. The better-fitting SAR model performed well in simulating urban land use change and scored an overall accuracy of 85.3%, improving on the LogCA model by 3.6%. Landscape metrics showed that the pattern generated by the SAR-CA model has less difference with the observed pattern.  相似文献   

Soil salinity and vegetation cover change detection from multi-temporal remotely sensed imagery in Al Hassa Oasis in Saudi Arabia     

Amal Allbed  Lalit Kumar  Priyakant Sinha 《国际地球制图》2018,33(8):830-846

Detecting soil salinity changes and its impact on vegetation cover are necessary to understand the relationships between these changes in vegetation cover. This study aims to determine the changes in soil salinity and vegetation cover in Al Hassa Oasis over the past 28 years and investigates whether the salinity change causing the change in vegetation cover. Landsat time series data of years 1985, 2000 and 2013 were used to generate Normalized Difference Vegetation Index (NDVI) and Soil Salinity Index (SI) images, which were then used in image differencing to identify vegetation and salinity change/no-change for two periods. Soil salinity during 2000–2013 exhibits much higher increase compared to 1985–2000, while the vegetation cover declined to 6.31% for the same period. Additionally, highly significant (p < 0.0001) negative relationships found between the NDVI and SI differencing images, confirmed the potential long-term linkage between the changes in soil salinity and vegetation cover.  相似文献   

Subsidence in the Kathmandu Basin,before and after the 2015 Mw 7.8 Gorkha Earthquake,Nepal Revealed from Small Baseline Subset-DInSAR Analysis     

Suresh Krishnan P.V.  Jungkyo Jung 《地理信息系统科学与遥感》2018,55(4):604-621

Land subsidence in densely urbanized areas is a global problem that is primarily caused by excessive groundwater withdrawal. The Kathmandu Basin is one such area where subsidence due to groundwater depletion has been a major problem in recent years. Moreover, on 25 April 2015, this basin experienced large crustal movements caused by the Gorkha earthquake (Mw 7.8). Consequently, the effects of earthquake-induced deformation could affect the temporal and spatial nature of anthropogenic subsidence in the basin. However, this effect has not yet been fully studied. In this paper, we applied the SBAS-DInSAR technique to estimate the spatiotemporal displacement of land subsidence in the Kathmandu Basin before and after the Gorkha earthquake, using 16 ALOS-1 Phased Array L-band Synthetic Aperture Radar (PALSAR) images during the pre-seismic period and 26 Sentinel-1 A/B SAR images during the pre- and post-seismic periods. The results showed that the mean subsidence rate in the central part of the basin was about ?8.2 cm/year before the earthquake. The spatial extents of the subsiding areas were well-correlated with the spatial distributions of the compressible clay layers in the basin. We infer from time-series InSAR analysis that subsidence in the Kathmandu basin could be associated with fluvio-lacustrine (clay) deposits and local hydrogeological conditions. However, after the mainshock, the subsidence rate significantly increased to ?15 and ?12 cm/year during early post-seismic (108 days) and post-seismic (2015–2016) period, respectively. Based on a spatial analysis of the subsidence rate map, the entire basin uplifted during the co-seismic period has started to subside and become stable during the early-post-seismic period. This is because of the elastic rebound of co-seismic deformation. However, interestingly, the localized areas show increased subsidence rates during both the early-post- and post-seismic periods. Therefore, we believe that the large co-seismic deformation experienced in this basin might induce the local subsidence to increase in rate, caused by oscillations of the water table level in the clay layer.  相似文献   

Dynamic land use change simulation using cellular automata with spatially nonstationary transition rules   总被引：2，自引：0，他引：2  

Yongjiu Feng  Xiaohua Tong 《地理信息系统科学与遥感》2018,55(5):678-698

The dynamic relationships between land use change and its driving forces vary spatially and can be identified by geographically weighted regression (GWR). We present a novel cellular automata (GWR-CA) model that incorporates GWR-derived spatially varying relationships to simulate land use change. Our GWR-CA model is characterized by spatially nonstationary transition rules that fully address local interactions in land use change. More importantly, each driving factor in our GWR model contains effects that both promote and resist land use change. We applied GWR-CA to simulate rapid land use change in Suzhou City on the Yangtze River Delta from 2000 to 2015. The GWR coefficients were visualized to highlight their spatial patterns and local variation, which are closely associated with their effects on land use change. The transition rules indicate low land conversion potential in the city’s center and outer suburbs, but higher land conversion potential in the inner near suburbs along the belt expressway. Residual statistics show that GWR fits the input data better than logistic regression (LR). Compared with an LR-based CA model, GWR-CA improves overall accuracy by 4.1% and captures 5.5% more urban growth, suggesting that GWR-CA may be superior in modeling land use change. Our results demonstrate that the GWR-CA model is effective in capturing spatially varying land transition rules to produce more realistic results, and is suitable for simulating land use change and urban expansion in rapidly urbanizing regions.  相似文献   

利用GRACE数据检测日本Mw9.0地震同震和震后重力变化     

尹鹏  张永志  焦佳爽  南康康  王慧玲 《测绘通报》2018,(1):38-43

基于德国地学中心（GFZ）发布的GRACE RL05月重力场模型数据,考虑全球陆地同化系统陆地水储量的影响,采用300 km的扇形滤波,利用叠积法提取了日本Mw9.0地震的同震和震后重力时变信号,并利用最小二乘拟合的方法计算了两个同震重力变化极值点在地震前后85个月的重力年变率。结果表明：土壤水分和雪水引起的重力变化为-0.34~0.09 μgal;利用GRACE数据检测到的同震重力变化为-5.3~4.2 μgal,与基于PSGRN/PSCMP模型计算的结果在空间分布和量级上具有较好的一致性;震后5 a震中附近区域的重力整体上呈现增加趋势,断层上盘所在的日本海域与下盘所在的太平洋区域重力增加的最大值分别为2.6、4.5 μgal,下盘重力增加较大,可能与断层下盘所在地层的黏滞性相对较低有关。  相似文献   

Historical manufacturing volatility and local sustainability efforts: A link to the past     

《Global Environmental Change》2022

Renewed attention to the role of subnational efforts in addressing myriad environmental challenges necessitates a greater understanding of the factors associated with program adoption. Given observed relationships between adoption of sustainability practices and the presence of carbon-intensive industry, and separately the observed persistence of industrial history in a given place, we explore the link between historical manufacturing employment volatility and current sustainability plan adoption at the local level. Our analysis suggests that the magnitude of changes in manufacturing employment is inversely related to the likelihood of sustainability plan adoption. Our analysis further suggests that, given the same pace of change, counties with shrinking manufacturing employment are more likely to adopt sustainability plans than those with growing employment. Lastly, we find that the link between past industrial transitions and local sustainability commitment is moderated by local disaster experience and priority for environmental protection. Collectively, the findings also shed light on potential—and otherwise unobservable—barriers to transitions to sustainable practices at the local level. In particular, the inverse relationship between pace of employment change and plan adoption suggests that minimizing the rapidity of contemporary transitions may counterintuitively ease the eventual adoption of sustainability-related policies.  相似文献   

Navigating climate crises in the Great Barrier Reef     

《Global Environmental Change》2022

A dramatic escalation of extreme climate events is challenging the capacity of environmental governance regimes to sustain and improve ecosystem outcomes. It has been argued that actors within adaptive governance regimes can help to steer environmental systems toward sustainability in times of crisis. Yet there is little empirical evidence of how acute climate crises are navigated by actors operating within adaptive governance regimes, and the factors that influence their responses. Here, we qualitatively assessed the actions key governance actors took in response to back-to-back mass coral bleaching – an extreme climate event – of the Great Barrier Reef in 2016 and 2017, and explored their perceptions of barriers and catalysts to these responses. This research was, in part, a product of collaboration and knowledge co-production with Great Barrier Reef governance actors aimed at improving responses to climate crises in the region. We found five major categories of activity that actors engaged with in the wake of recurrent mass coral bleaching: assessing the scale and extent of bleaching, sharing information, communicating bleaching to the public, building local resilience, and addressing global threats. These actions were both catalyzed and hindered by a range of factors that fall within different domains of adaptive capacity; such as assets, social organization, and agency. We discuss the implications of our findings as they relate to existing research on adaptive capacity and adaptive governance. We conclude by coalescing insights from our interviews and a participant engagement process to highlight four key ways in which the ability of governance actors, and the Great Barrier Reef governance regime more broadly, can be better prepared for, and more effectively respond to extreme climate events. Our research provides empirical insight into how crises are experienced by governance actors in a large-scale environmental system, potentially providing lessons for similar systems across the globe.  相似文献   

Can we learn from the past? Towards better analogies and historical inference in society-environmental change research     

《Global Environmental Change》2022

In light of the challenges posed by contemporary environmental changes, interest in past environmental impacts and societies’ responses to them is burgeoning. The main strength of such research lies in its ability to analyze completed society-environment interactions. Scholars have argued that such analyses can improve our understanding of present challenges and offer useful lessons to guide adaptation responses. Yet despite considerable differences between past and present societies, our inherently limited knowledge of the past and our changing understanding of it, much of this research uses historical antecedents uncritically, assuming that past societal impacts and responses are directly analogous to contemporary ones. We argue that this approach is unsound both methodologically and theoretically, thus drawing insights that might offer an erroneous course of action.To illustrate the challenges in drawing historical analogies, we outline several fundamental differences between past and present societies as well as broader limitations of historical research. Based on these points, we argue that scholars who apply historical inference in their work should do so critically, while reflecting on the objectives of learning from the past and the limitations of this process. We suggest a number of ways to improve past-present analogies, such as defining more explicitly what we can learn from the past, clarifying the rationale for using the analogy, and reducing the number of variables compared between past and present.  相似文献   

Localized versus wide-ranging effects of the post-Soviet wars in the Caucasus on agricultural abandonment     

《Global Environmental Change》2022

Wars are frequent and can affect land use substantially, but the effects of wars can vary greatly depending on their characteristics, such as intensity or duration. Furthermore, the spatial scale of the effects can differ. The effects of wars may be localized and thus close to conflict locations if direct mechanisms matter most (e.g., abandonment because active fighting precludes farming), or wide-ranging, e.g., farther away from conflict locations, if indirect mechanisms predominate (e.g., no access to agricultural inputs). Our goal was to quantify how the very different wars in the Caucasus region during post-Soviet times most likely affected agricultural abandonment at different scales. We analyzed data on conflict locations plus Landsat-derived land-cover data from 1987 to 2015, and applied matching statistics, difference-in-differences estimators, and logistic panel regressions. We examined the localized versus wide-ranging effects of the different wars on permanent agricultural abandonment and inferred to direct and indirect mechanisms that may have resulted in agricultural abandonment. While permanent agricultural abandonment was overall surprisingly limited across the Caucasus, up to one third of abandonment was most likely related to the wars. Among the wars, the war in Chechnya was by far the most intense and longest, but its effect on abandonment was similar to the less intense and relatively short war in Abkhazia. 47 % and 45 % of agricultural abandonment was related to each war, respectively. The reason was that the effect of the war in Chechnya was more localized, and abandonment occurred near conflict locations, in contrast to Abkhazia, where the effect was wide-ranging and abandonment occurred farther away from conflict locations. In contrast, the war in South Ossetia showed no significant effect on abandonment, and the war in Nagorno-Karabakh had the surprising pattern that abandonment was higher where no war had occurred. For each of the wars, abandonment was predominately related to the nearest conflict locations, but in Abkhazia additional conflict locations within 10 km further increased the probability of abandonment. We infer that the direct mechanisms of the war such as bombing, and active fighting most likely resulted in a localized effect close to conflict locations in Chechnya and in Nagorno-Karabakh. However, in Nagorno-Karabakh subsidies for new settlers after the war, (i.e., a positive wide-ranging effect), potentially reduced the amount of abandonment there. In contrast, negative wide-ranging effects such as refugee movements and post-war restrictions on their return is related to broad-scale abandonment in Abkhazia. In summary, permanent agricultural abandonment was not necessarily higher in a war with a high overall intensity. Instead, the effect of a given war varied in scale, and was related to the relative importance of direct and localized versus indirect and wide-ranging mechanisms, including postwar events and policies, which is likely the case for other wars, too.  相似文献