The Role of Disaggregation of Asset Values in Flood Loss Estimation: A Comparison of Different Modeling Approaches at the Mulde River,Germany

In loss estimation there is a spatial mismatch of hazard data that are commonly modeled on an explicit raster level and exposure data that are often available only for aggregated administrative units. Usually disaggregation methods that use ancillary information to distribute lumped exposure data in a finer spatial resolution help to bridge this gap. However, the actual influence of different mapping techniques and ancillary data on the final loss estimation has not been analyzed yet. In this paper three methods are applied to disaggregate residential building assets using two kinds of land use/land cover (LULC) data. The resulting disaggregated assets are validated and compared using census data of the residential building number on the community and constituency level. In addition, the disaggregated assets are taken to estimate residential building losses due to the flood in August 2002 in 21 municipalities on the River Mulde in Saxony, Germany. Losses are calculated with the help of four loss models. In general, disaggregation helps to decrease the error variance within the loss estimation. It must, however, be stated that the application of sophisticated disaggregation methods does not lead to significant improvements compared to the straightforward binary method. Therefore more effort should instead be put into the provision of high-resolution LULC data. Finally, the remaining uncertainties in loss estimation are high and demand further improvements in all modeling aspects.     

气候和土地利用/覆被变化对宁波地区生态系统产水服务的影响

提供水资源是重要的生态系统服务功能之一,对区域经济和生态系统的可持续发展具有重要作用.近年来,人类活动对水资源的需求量增加,加之水环境污染和水资源浪费现象严重,造成了部分地区的缺水问题.在此背景下,本文以宁波地区为例,研究气候变化和土地利用/覆被变化对生态系统产水服务的影响.首先,利用InVEST模型中的产水量模块,估算了区域的产水量.然后,利用情景分析的方法设计6种情景,分析了气候变化和土地利用/覆被变化对区域产水量的影响.最后,量化了气候和土地利用/覆被变化这2种因素对生态系统产水服务的贡献程度,并讨论了形成机制.研究表明:①2000—2015年,宁波地区的降水量增加了6.44%,潜在蒸散量减少了8.35%.城镇化导致建设用地面积增加了120%,耕地面积减少了22.37%.在气候变化和土地利用/覆被变化的共同作用下,平均产水量增加了10.91%.②气候变化对生态系统产水服务的影响更为显著,而土地利用/覆被变化的影响较小.其中,2000—2015年气候变化对宁波地区产水量的贡献率高达97.56%,而土地利用/覆被变化的贡献率仅为2.44%.③城镇生态系统的产水量高于其他生态系统类型,农田生态系统的产水量高于森林和草地生态系统.因此,城镇化会增加产水量,退耕还林还草会导致产水量的减少.     

Monitoring Environmental Changes in the Mediterranean Coastal Landscape: The Case of Cukurova, Turkey

This paper describes a remote sensing approach used to monitor temporal land use/cover (LULC) changes in Cukurova, an extensive coastal plain in the southeast Mediterranean coast of Turkey. The area has varied terrain ranging from low-lying alluvial deposits to rocky hills and mountains characterized by limestone outcrops. The ecological and economic importance of the area can be attributed to the existence of important coastal ecosystems (e.g., wetlands and sand dunes) and a wide range of industries located along the eastern coast. Temporal changes in the coastal landscape between 1984 and 2000 were evaluated using digital interpretation of remotely sensed satellite data. Pairwise comparison methods were used to quantify changes from 1984 to 1993 and 1993 to 2000 using multitemporal Landsat TM and ETM+ images, acquired in 1984, 1993, and 2000, respectively. Total change area was 2448 ha from 1984 to 1993 and increased more than twofold, to 6072 ha from 1993 to 2000. Change trends were determined using the information provided from individual change detection outputs of different periods. The most prominent changes were estimated to have occurred in agriculture, urban, and natural vegetation cover. Agriculture has increasingly grown over marginal areas, whereas urban development occurred at the expense of prime croplands across both time steps.     

中国南北过渡带生态系统碳储量时空变化及动态模拟

山地是全球变化的敏感地带,对生态安全与发展具有重要作用,山地生态系统服务变化和生态环境承载力是地理学与生态学的研究热点。以中国南北过渡带的主体秦巴山地为研究对象,采用CA-Markov模型与InVEST模型模拟和预测（2000—2040年）不同土地利用情景下秦巴山地生态系统碳储量变化,运用热点分析（Getis-Ord G_i^*）探讨秦巴山地生态系统碳储量的空间分布差异。结果表明：（1）2000—2040年,研究区土地利用/土地覆被变化主要是耕地、林地、草地和建设用地。（2）2000—2020年,碳储量增加1.12×10⁷ t;2020—2040年自然增长情景下,碳储量损失剧烈,减少50.24×10⁷ t;生态保护情景下,碳损失幅度明显变弱,减少29.52×10⁷ t,说明采取生态环境保护政策,能够有效控制碳储量减少。（3）土地利用/土地覆被与生态系统碳储量的变化呈现显著的一致性,土地利用数量变化决定了生态系统碳储量的质量和空间分布格局。（4）随着海拔抬升,碳储量呈现出“先增后减”的趋势;随着坡度升高,碳储量呈现出“W”型变化趋势。（5）热点分析结果显示,2000—2020年间,碳储量热点区和冷点区零散分布在研究区内;2040年自然增长情景下,碳储量冷热点分布范围有逐渐变大的趋势;2040年生态保护情景较2020年,秦巴山地生态系统碳储量的冷热点分布范围整体变化不大。     

Comparing the utility of image algebra operations for characterizing landscape changes: the case of the Mediterranean coast

The aim of this study is to compare various image algebra procedures for their efficiency in locating and identifying different types of landscape changes on the margin of a Mediterranean coastal plain, Cukurova, Turkey. Image differencing and ratioing were applied to the reflective bands of Landsat TM datasets acquired in 1984 and 2006. Normalized Difference Vegetation index (NDVI) and Principal Component Analysis (PCA) differencing were also applied. The resulting images were tested for their capacity to detect nine change phenomena, which were a priori defined in a three-level classification scheme. These change phenomena included agricultural encroachment, sand dune afforestation, coastline changes and removal/expansion of reed beds. The percentage overall accuracies of different algebra products for each phenomenon were calculated and compared. The results showed that some of the changes such as sand dune afforestation and reed bed expansion were detected with accuracies varying between 85 and 97% by the majority of the algebra operations, while some other changes such as logging could only be detected by mid-infrared (MIR) ratioing. For optimizing change detection in similar coastal landscapes, underlying causes of these changes were discussed and the guidelines for selecting band and algebra operations were provided.     

Socioeconomic Drivers of Deforestation in the Northern Ecuadorian Amazon

Investigations of land use/land cover (LULC) change and forest management are limited by a lack of understanding of how socioeconomic factors affect land use. This lack also constrains the predictions of future deforestation, which is especially important in the Amazon basin, where large tracts of natural forest are being converted to managed uses. Research presented in this article was conducted to address this lack of understanding. Its objectives are (a) to quantify deforestation in the Northern Ecuadorian Amazon (NEA) during the periods 1986–1996 and 1996–2002; and (b) to determine the significance and magnitude of the effects of socioeconomic factors on deforestation rates at both the parroquia (parish) and finca (farm) levels. Annual deforestation rates were quantified via satellite image processing and geographic information systems. Linear spatial lag regression analyses were then used to explore relationships between socioeconomic factors and deforestation. Socioeconomic factors were obtained, at the finca level, from a detailed household survey carried out in 1990 and 1999, and at the parroquia level from data in the 1990 and 2001 Ecuadorian censuses of population. We found that the average annual deforestation rate was 2.5% and 1.8%/year for 1986–1996 and 1996–2002, respectively. At the parroquia level, variables representing demographic factors (i.e., population density) and accessibility factors (i.e., road density), among others, were found to be significantly related to deforestation. At the farm level, the factors related to deforestation were household size, distance by road to main cities, education, and hired labor. The findings of this research demonstrate both the severity of deforestation in the Northern Ecuadorian Amazon and the array of factors affecting deforestation in the tropics.     

Temporal and spatial change detecting (1998–2003) and predicting of land use and land cover in Core corridor of Pearl River Delta (China) by using TM and ETM+ images

Land use/land cover (LULC) has a profound impact on economy, society and environment, especially in rapid developing areas. Rapid and prompt monitoring and predicting of LULC’s change are crucial and significant. Currently, integration of Geographical Information System (GIS) and Remote Sensing (RS) methods is one of the most important methods for detecting LULC’s change, which includes image processing (such as geometrical-rectifying, supervised-classification, etc.), change detection (post-classification), GIS-based spatial analysis, Markov chain and a Cellular Automata (CA) models, etc. The core corridor of Pearl River Delta was selected for studying LULC’s change in this paper by using the above methods for the reason that the area contributed 78.31% (1998)–81.4% (2003) of Gross Domestic Product (GDP) to the whole Pearl River Delta (PRD). The temporal and spatial LULC’s changes from 1998 to 2003 were detected by RS data. At the same time, urban expansion levels in the next 5 and 10 years were predicted temporally and spatially by using Markov chain and a simple Cellular Automata model respectively. Finally, urban expansion and farmland loss were discussed against the background of China’s urban expansion and cropland loss during 1990–2000. The result showed: (1) the rate of urban expansion was up to 8.91% during 1998–2003 from 169,078.32 to 184,146.48 ha; (2) the rate of farmland loss was 5.94% from 312,069.06 to 293,539.95 ha; (3) a lot of farmland converted to urban or development area, and more forest and grass field converted to farmland accordingly; (4) the spatial predicting result of urban expansion showed that urban area was enlarged ulteriorly compared with the previous results, and the directions of expansion is along the existing urban area and transportation lines.