A land-use-based modelling chain to assess the impacts of Natural Water Retention Measures on Europe’s Green Infrastructure

This article details the process of integrating models to answer a specific policy-driven question: ‘What could be the impact of proposed Natural Water Retention Measures (NWRMs) on Europe’s Green Infrastructure (GI)?’ It describes the new Land Use Modelling Platform (LUMP), now enabling a high spatial scale (100-m) and large coverage (pan-European), whereby several sector-specific models contribute to assessing the impact of regional-level policy on a given spatial topic of concern. The configuration (land claims and land allocations modules) and calibration (accessibility and biophysical suitability) of the LUMP are explained. Four NWRM scenarios (riparian areas, afforestation, grassland and baseline scenario) are configured to run the simulations. For the reference: year 2006, the spatial representation of GI is based on land-use features of a refined version of the CORINE Land Cover (CLC), and resumed as connected components made of nodes and links.

Mathematical morphological image processing and network graph theory model, available from the free software package GUIDOS (the Joint Research Center of the European Commission), enabled the measurement of the GI connectivity and identified most critical links. Results show that the competition for land claimed by different economic sectors, combined with policy-driven rule-sets for the implementation of different NWRMs, yields very different results for the 2030 land-use projections, and subsequently for the morphology of GI. Three indicators associated with the morphology of GI are computed in order to assess the model outputs for 2030. The indicators are computed to answer the following questions: (1) How is the quantity of GI affected by each of the NWRM, and what proportion of that GI is most valuable? (2) What is the location of the most critical nodes and connectors of GI, and what land-use conversions occur under these? (3) Are the average components getting larger or smaller?

Whereas the grassland measure results in the largest net increase of GI, the afforestation measure results in the overall largest number of hectares of key nodes and links within the network. Land conversions occur under the critical GI nodes and links, with a large increase in agricultural areas, especially for the riparian measure under critical nodes and the grassland measure under critical links. Also predominant is the swapping of land from pasture to forest under critical links with the afforestation measure. The riparian measure most increases the average size of GI components, and all three measures contribute to bridging two large components which were divided in the 2006 land-use map, thus increasing the size of the largest component by more than 50%.     

Predicting human mobility with activity changes

Human mobility patterns can provide valuable information in understanding the impact of human behavioral regularities in urban systems, usually with a specific focus on traffic prediction, public health or urban planning. While existing studies on human movement have placed huge emphasis on spatial location to predict where people go next, the time dimension component is usually being treated with oversimplification or even being neglected. Time dimension is crucial to understanding and detecting human activity changes, which play a negative role in prediction and thus may affect the predictive accuracy. This study aims to predict human movement from a spatio-temporal perspective by taking into account the impact of activity changes. We analyze and define changes of human activity and propose an algorithm to detect such changes, based on which a Markov chain model is used to predict human movement. The Microsoft GeoLife dataset is used to test our methodology, and the data of two selected users is used to evaluate the performance of the prediction. We compare the predictive accuracy (R²) derived from the data with and without implementing the activity change detection. The results show that the R² is improved from 0.295 to 0.762 for the user with obvious activity changes and from 0.965 to 0.971 for the user without obvious activity changes. The method proposed by this study improves the accuracy in analyzing and predicting human movement and lays the foundation for related urban studies.     

1) I. A. H. S. / A. I. H. S.

Abstract

A simple method is used to study the response of runoff in the Sahel to climate change. The statistical characteristics of rainfall are calculated over the western part of the Sahel for the period 1961–1990, using the BADOPLU network. Daily rainfall is simulated using a Markov process with Weibull distribution for rainfall depths. Runoff is modelled using a conceptual SCS model and the curve numbers are calculated for West Africa. Climate change is provided by simulations using the Arpège GCM (Scenario A1B), and a perturbation method is used on the parameters which describe the rainfall. Changes in rainfall are assumed to occur through increases in frequency, not intensity. Using Arpège, runoff is mainly found to increase, in depth and in number of events, by the end of the 21st century. Changes in evaporation and land use are not included in the analysis. The impact of this 21st century potential climate change (rainfall) on the runoff is found to be of the same magnitude as the impact of changes in land use.     

Simulating hourly rainfall occurrence within an equatorial rainforest,Borneo Island / Simulation de l'occurrence de pluie horaire au sein de la forêt équatoriale,Ile de Bornéo

Abstract

The ability to simulate characteristics of the diurnal cycle of rainfall occurrence, and its evolution over the seasons is important to the forecasting of hydrological impacts resulting from land-use and climate changes within the humid tropics. This stochastic modelling study uses a generalized linear model (GLM) solution to second-order Markov chain models, as these discrete models are better at describing binary occurrence processes on an hourly time-scale than continuous-time approaches such as stochastic state-space models. We show that transition probabilities derived by the Markov chain method need to be time-varying rather than stationary to simulate the evolution of the diurnal cycle of rainfall occurrence over a Southeast Asian monsoon sequence. The conceptual and pragmatic links between discrete diurnal processes and continuous processes occurring over seasonal periods are thereby simulated within the same model.     

Combined analysis of precipitation and water deficit for drought hazard assessment

Abstract

The combined analysis of precipitation and water scarcity was done with the use of the Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI), developed as a monthly, two-variable SPI-SRI indicator to identify different classes of hydrometeorological conditions. Stochastic analysis of a long-term time series (1966–2005) of monthly SPI-SRI indicator values was performed using a first-order Markov chain model. This provided characteristics of regional features of drought formation, evolution and persistence, as well as tools for statistical long-term drought hazard prediction. The study was carried out on two subbasins of the Odra River (Poland) of different orography and land use: the mountainous Nysa K?odzka basin and the lowland, agricultural Prosna basin. Classification obtained with the SPI-SRI indicator was compared with the output from the NIZOWKA model that provided identification of hydrological drought events including drought duration and deficit volume. Severe and long-duration droughts corresponded to SPI-SRI Class 3 (dry meteorological and dry hydrological), while severe but short-term droughts (lasting less than 30 days) corresponded to SPI-SRI Class 4 (wet meteorological and dry hydrological). The results confirm that, in Poland, meteorologically dry conditions often shift to hydrologically dry conditions within the same month, droughts rarely last longer than 2 months and two separate drought events can be observed within the same year.     

A spectral gradient difference based approach for land cover change detection

Change detection with remotely sensed imagery plays an important role in land cover mapping, process analysis and dynamic information services. Euclidean distance, correlation and other mathematic metrics between spectral curves have been used to calculate change magnitude in most change detection methods. However, many pseudo changes would also be detected because of inter-class spectral variance, which remains a significant challenge for operational remote sensing applications. In general, different land cover types have their own spectral curves characterized by typical spectral values and shapes. These spectral values are widely used for designing change detection algorithms. However, the shape of spectral curves has not yet been fully considered. This paper proposes to use spectral gradient difference (SGD) to quantitatively describe the spectral shapes and the differences in shape between two spectra. Change magnitude calculated in the new spectral gradient space is used to detect the change/no-change areas. Then, a chain model is employed to represent the SGD pattern both qualitatively and quantitatively. Finally, the land cover change types are determined by pattern matching with the knowledgebase of reference SGD patterns. The effectiveness of this SGD-based change detection approach was verified by a simulation experiment and a case study of Landsat data. The results indicated that the SGD-based approach was superior to the traditional methods.     

基于权马尔可夫链模型的庐江县降水量预测

由于降水过程的随机性与不确定性,使得降水量预测存在一定的难度。对安徽省庐江县1952~2009年逐年降水资料进行了分析,采用样本-标准差分级法将这58年的逐年降水量序列分为枯水年,偏枯水年,平水年,偏丰水年,丰水年5个状态,采用权马尔可夫链模型预测了2010年的降水量,预测结果与实测结果相吻合。     

空间分类在连锁超市选址中的应用研究

空间数据挖掘是一种知识决策支持技术,本文以大型综合连锁超市为例,研究了空间分类挖掘方法在连锁超市选址预测中的应用问题。结合连锁超市定位理论,对实验数据进行了选择和处理。同时进行了基于关联的分类实验,得到指导和预测选址的知识,并对预测知识的准确性和可信度进行了检验,结果显示预测准确率和可信度较高。本文制定的挖掘方案可为连...     

Middle and late Pleistocene glaciations in the Campo Felice Basin (central Apennines, Italy)

The present paper refers to research conducted in the tectonic-karst depression of Campo Felice in the central Apennines (Italy), in which glacial, alluvial and lacustrine sediments have been preserved. Stratigraphic interpretations of sediments underlying the Campo Felice Plain are based on evidence obtained from nine continuous-core boreholes. The boreholes reach a depth of 120 m and provide evidence of five sedimentation cycles separated by erosion surfaces. Each cycle is interpreted as an initial response to a mainly warm stage, characterized by low-energy alluvial and colluvial deposition, pedogenesis, and limited episodes of marsh formation. In turn, a mainly cold stage follows during which a lake formed, and glaciers developed and expanded, leading to deposition of glacial and fluvioglacial deposits. The chronological framework is established by eleven accelerator mass spectrometer ¹⁴C ages and three ³⁹Ar-⁴⁰Ar ages on leucites from interbedded tephra layers. These age determinations indicate five glacial advances that respectively occurred during marine oxygen isotope stages 2, 3-4, 6, 10 and 14.     

基于WebServices的空间信息应用集成解决方案研究

 在对应用集成及其发展分析的基础上,将Web Services技术运用到空间信息应用集成,提出和建立了面向服务的空间信息应用集成框架,包括Web应用层、服务集成层、服务层和UDDI等4个组成部分。通过该框架,可以实现空间信息集成、服务集成和应用集成。论文解决了空间信息应用集成框架中的2个关键问题:(1)提出了分别从数据层次和业务层次对原有系统集成的解决方案,在数据层次上,提出了基于XML/GML的空间数据封装和基于Web服务接口的空间数据封装策略;在业务层次上,提出根据系统的功能模块和业务逻辑分别进行封装的策略;(2)提出了空间信息Web服务链接和服务组合的串联、并联和混联模式,通过三种模式服务链的设计,可以实现多个服务的链接和组合,从而完成空间信息以及应用集成。