Drivers of forest change in Hoa Binh,Vietnam in the context of integration and globalization

This study identified spatial patterns of forest change in Hoa Binh, Vietnam, from 2005 to 2017 by integrating Landsat data and Geographic Information System (GIS) data. A Multiple Logistic Regression (MLR) model was adapted to analyse drivers of three types of forest change, including (i) deforestation and forest degradation, (ii) forest regrowth and (iii) plantation expansion. The results reveal that accessibility and local economic development were determinants of forest cover dynamics during the integration and globalization period and that increased population pressure and poverty were no longer the main factors in forest cover transition. Several key policies in this time period positively affected forest cover change, triggering private sector participation in developing the forest economy by including households and small and medium enterprises in particular. The findings of this study can provide learning points for the implementation of sustainable forest management policies in other Vietnamese provinces or in neighbouring countries. This research has provided an effective tool for visualizing human‐forest ecosystem interaction, and this tool can be applied to subsequent studies to determine causes of forest cover change at the provincial level in Vietnam.     

Groundwater vulnerability mapping: A GIS and fuzzy rule based integrated tool

Contamination of groundwater has become a major concern in recent years. Since testing of water quality of all domestic and irrigation wells within large watersheds is not economically feasible, one frequently used monitoring strategy is to develop contamination potential maps of groundwater, and then prioritize those wells located in the potentially highly contaminated areas for testing of contaminants. However, generation of contamination potential maps based on groundwater sensitivity and vulnerability is not an easy task due inherent uncertainty. Therefore, the overall goal of this research is to improve the methodology for the generation of contamination potential maps by using detailed landuse/pesticide and soil structure information in conjunction with selected parameters from the DRASTIC model. The specific objectives of this study are (i) to incorporate GIS, GPS, remote sensing and the fuzzy rule-based model to generate groundwater sensitivity maps, and (ii) compare the results of our new methodologies with the modified DRASTIC Index (DI) and field water quality data. In this study, three different models were developed (viz. DI_fuzz, VI_fuzz and VI_{fuzz_ped}) and were compared to the DI. Once the preliminary fuzzy logic-based (DI_fuzz) was generated using selected parameters from DI, the methodology was further refined through VI_fuzz and VI_{fuzz_ped} models that incorporated landuse/pesticide application and soil structure information, respectively. This study was conducted in Woodruff County of the Mississippi Delta region of Arkansas. Water quality data for 55 wells were used to evaluate the contamination potential maps. The sensitivity map generated by VI_{fuzz_ped} with soil structure showed significantly better coincidence results when compared with the field data.     

Groundwater vulnerability and risk mapping for the Basaltic aquifer of the Azraq basin of Jordan using GIS, Remote sensing and DRASTIC

Water consumption in Jordan already exceeds renewable freshwater resources by more than 20% and, after the year 2005, freshwater resources are likely to be fully utilised. Over 50% of supply derives from groundwater and this paper focuses on a small part of the northern Badia region of Jordan that is underlain by the Azraq groundwater basin where it has been estimated that annual abstraction stands at over 100% of the projected safe yield. While water supply is a crucial issue, there is also evidence to suggest that the quality of groundwater supplies is also under threat as a result of salinisation and an increase in the use of agrochemicals. Focusing on this area, this paper attempts to produce groundwater vulnerability and risk maps. These maps are designed to show areas of greatest potential for groundwater contamination on the basis of hydro-geological conditions and human impacts. All of the major geological and hydro-geological factors that affect and control groundwater movement into, through, and out of the study area were incorporated into the DRASTIC model. Parameters included; depth to groundwater, recharge, aquifer media, soil media, topography, and impact of the vadose zone. The hydraulic conductivity of the aquifer was not included in calculating the final DRASTIC index for potential contamination due to a lack of sufficient quantitative data. A Geographical Information System (GIS) was used to create a groundwater vulnerability map by overlaying the available hydro-geological data. The resulting vulnerability map was then integrated with a land use map as an additional parameter in the DRASTIC model to assess the potential risk of groundwater to pollution in the study area. The final DRASTIC model was tested using hydrochemical data from the aquifer. Around 84% of the study area was classified as being at moderate risk while the re mainder was classified as low risk. While the analysis of groundwater chemistry was not conclusive, it was encouraging to find that no well with high nitrate levels was found in the areas classified as being of low risk suggesting that the DRASTIC model for this area provided a conservative estimate of low risk areas. It is recognised that the approach adopted to produce the DRASTIC index was limited by the availability of data. However, in areas with limited secondary data, this index provides important objective information that could be used to inform local decision making.     

Integrating multi-source remotely sensed datasets to examine the impact of tree height and pattern information on crimes in Milwaukee,Wisconsin

There have been a great number of debates about the impacts of trees on crimes: some researchers believed that trees are a crime facilitator because of the concealment provision for potential criminals, while others argued that they are a crime deterrent because of the increased surveillance possibility and the therapeutic effect on psychological fatigue. To better answer this question, this study incorporated detailed tree features by using multi-source remotely sensed data at a very high resolution into environmental criminology analysis across the entire City of Milwaukee. Trees were extracted from aerial photographs, and broken down into two categories based on their heights to consider the effects of tree height on view obstruction. By controlling for confounding socioeconomic variables, the relationship between crimes and a series of composition and configuration indicators of trees with different height were investigated by using global and local spatial regressions. Results from classic and spatial statistical techniques finds complicated relationship between crimes and trees, which can be summarized in two aspects. First, the mixed effects of trees can be observed among different crime types. Second, the trends of spatial nonstationarity of the composition and configuration of trees with different heights were observed across the entire study area. The study outcomes could provide reasonable implications for making appropriate policies for crime prevention through environmental design to strengthen neighborhoods and communities in a city.     

利用遥感与GIS分析珠江三角洲农田流失的空间分布规律及影响因素 --以东莞市为例

近年珠江三角洲出现了迅速的城市化的过程,大量的农田被推平作为非农业用地,其中有相当一部分的土地资源被不合理地浪费掉.分析这种土地利用变化的过程,可以为有效地利用土地资源提供规划依据.本文利用遥感与GIS相结合的方法,探讨了东莞市农田流失的时空分布规律.通过熵的计算,对快速的城市扩张过程进行了定量化的监测.并利用重力模型,研究造成这种现象的影响因素.研究发现,东莞市某些镇近年来的农田流失尤为严重.     

Analysis of village accessibility and its impact on land use dynamics in a mountainous province of northern Vietnam

Surveys carried out in mountainous areas of northern Vietnam at research sites selected across a gradient of market integration, revealed strong relationships between the location of the village with respect to the national road network and the nature of its land-use systems, its poverty level and more generally its potential for development. We developed and tested in Bac Kan province a method to give an objective and quantitative definition of accessibility over a large geographic area. Accessibility maps integrated in a provincial GIS showed that despite recent improvements to the road network, some remote areas do not benefit from recent development.     

Classifying urban land use by integrating remote sensing and social media data

Urban land use information plays an important role in urban management, government policy-making, and population activity monitoring. However, the accurate classification of urban functional zones is challenging due to the complexity of urban systems. Many studies have focused on urban land use classification by considering features that are extracted from either high spatial resolution (HSR) remote sensing images or social media data, but few studies consider both features due to the lack of available models. In our study, we propose a novel scene classification framework to identify dominant urban land use type at the level of traffic analysis zone by integrating probabilistic topic models and support vector machine. A land use word dictionary inside the framework was built by fusing natural–physical features from HSR images and socioeconomic semantic features from multisource social media data. In addition to comparing with manual interpretation data, we designed several experiments to test the land use classification accuracy of our proposed model with different combinations of previously acquired semantic features. The classification results (overall accuracy = 0.865, Kappa = 0.828) demonstrate the effectiveness of our strategy that blends features extracted from multisource geospatial data as semantic features to train the classification model. This method can be applied to help urban planners analyze fine urban structures and monitor urban land use changes, and additional data from multiple sources will be blended into this proposed framework in the future.     

Policy-relevant indicators for mapping the vulnerability of urban populations to extreme heat events: A case study of Philadelphia

The recent global increase in extreme heat events linked to climate change is projected to continue. The additive effect of urban heat islands from impervious surfaces and urban heat emissions (e.g., from transportation and building cooling) exacerbates extreme heat events in urban areas, exposing dense populations to extreme heat with implications for human health. Ground- and satellite-based data on urban and suburban temperatures and vegetation over a historical period can help identify temporal and geospatial trends in heat exposure. A set of indicators has been developed to map the exposure, social sensitivity, and vulnerability of urban populations to heat wave health impacts. Guided by an Advisory Group of local planners in the pilot city of Philadelphia, localized trends of increasing urban extreme heat events using MODIS Land Surface Temperature (LST) data, confirmed with urban and non-urban temperature monitor data were identified. For the Philadelphia study area, the number of heat-event days in the urban setting has increased from approximately 4 days in 1980 to almost 12 days in 2013, while the non-urban setting has consistently experienced 5 days of heat events per year across the time period. Warmer micro-climates with limited vegetative cooling and elevated LSTs were also identified. The exposure indicator was combined with areas of high social sensitivity (e.g., low-income and elderly) to create a vulnerability indicator, showing significant overlap between highly exposed and highly sensitive populations. As a measure of the adaptive capacity of local governments to reduce the urban heat island, evidence of targeted vegetation increases or reduced localized temperatures linked to urban greening and cooling programs were sought, though none were of a scale to be identified by the 1 km satellite data utilized. The indicators have helped local decision makers to understand patterns of vulnerability, and may be used in the future to target adaptation actions and measure results (LST reduction or vegetation increase) from existing adaptation actions.     

Frontiers of urbanization: Identifying and explaining urbanization hot spots in the south of Mexico City using human and remote sensing

This article applies a multi-method approach to develop a better measurement of urbanization dynamics using remote and human sensing based on a GIS platform. The results demonstrate the benefits of bringing human and remote sensing sources together in a framework of hot spot analysis for a megacity such as Mexico City. Furthermore, our analysis suggests that human and remote sensing work well together in detecting the expansion of illegal urban settlements. Looking at the driving factors of illegal settlements, the existence of strong association between the expansion of illegal urban settlements and socioeconomic factors such as unemployment, provides some answers and reveals new questions. Illegal urban growth often leads to the loss of ecological areas in the urban frontiers, especially in areas where the urbanization potential is high. As a consequence, there are conflicts with legal settlers who dislike the illegal expansion. This approach can be extended to and replicated in new urbanizing areas, in particular in Africa and Asia.     

Lots for greening: Identification of metropolitan vacant land and its potential use for cooling and agriculture in Phoenix,AZ, USA

The greening of vacant parcels for urban sustainability continues to gain attention from researchers and practitioners, including its use to ameliorate the urban heat island effect and food deserts. Planning for such uses requires accurate inventories of the amount and distribution of vacant parcels, which may prove difficult to produce for large, sprawling urban complexes. This study provides a systematic approach that combines remote sensing and cadastral data to distinguish different forms of vacant land for the Phoenix, Arizona metropolitan area while reducing computation time. The approach identifies vacant parcels for potential greening, focusing on privately owned land lacking buildings and impervious surfaces. The results for the Phoenix area reveal hot spots of these parcels, many of which reside along the fringe of the metropolis awaiting development. A large number of vacant parcels, however, reside within the metropolitan core and are suitable for greening as well, potentially serving to mitigate the urban heat island effect and food deserts in this region. The identification method and parcel results are detailed.     

Unplanned urban growth: land use/land cover change in the Guwahati Metropolitan Area,India

Unplanned urban growth, particularly in developing countries has led to changes in land use/land cover (LULC). Numerous Indian cities face problems of unplanned LULC change due to nominal or non-existent planning efforts compounded by rapid urban population growth. The Guwahati Metropolitan Area (GMA) is one such urban centre. The present study assesses the trajectories of LULC change using Landsat imageries acquired in 1976, 1989, 2002 and 2015. Natural and semi natural vegetated area and artificial and natural water bodies decreased while built-up areas, cultivated and managed areas, and natural and semi natural non-vegetated areas increased. The built-up area increased from 23.9 in 1976 to 115.1 km² in 2015 becoming the dominant land cover class accounting for 41.8% of the total geographical area. During this period, natural and semi natural vegetated land were reduced by 88.9 km² at an annual rate of 2.2 km². Over the years there was an increasing trend of built-up land and cultivated and managed areas in the peripheral areas of the city while natural and semi natural vegetated land diminished. Consequently, as in many other developing countries, there is an urgent need for the governmental authorities and other stakeholders to implement effective urban planning policies.     

Crossing-over between land cover and land use: Exploring spatially varying relationships in two large US metropolitan areas

Difficulties in identifying actual uses of land space from remote sensing-based land cover products often result in lost opportunities to enhance the capacity of applied research on human settlements. In an attempt to address these difficulties, this study investigates how land cover and land use are interrelated with each other and what determines the relationship patterns by analyzing detailed land use and land cover data for two large US metropolitan areas – the five-county Los Angeles and six-county Chicago regions – where a broad spectrum of human settlements, ranging from urban cores to less-urbanized edges, coexist. The analysis shows that the land cover-land use relationship substantially varies not only across regions but across neighborhoods within each region. Through multivariate regression, it is also found that the intraregional variation is highly associated with the neighborhood's stage of urbanization, median housing age, and other development characteristics, suggesting that the relationship pattern can largely be shaped by the history and evolution of urban design/development.     

黄河流域生态环境综合评价及其演变

在定性分析黄河流域自然生态环境特点的基础上，针对黄河流域不同的地理特征与生态环境特征，从气候环境、水文环境、土地覆盖、土壤侵蚀、土地利用和地形地貌等方面选择评价指标，在遥感与地理信息系统技术支持下，首先通过一系列的模型计算与遥感影像解译，分别生成黄河流域1980年代末期与1990年代末期数值型的生态环境背景因子，而后应用主成分分析法对生态环境质量进行了综合评价，得出了不同空间尺度下的反映黄河流域1980年代末期与1990年代末期生态环境质量的分级图，并对黄河流域近10年间的生态环境演变进行了分析。     

Incorporating spatial interaction patterns in classifying and understanding urban land use

Land use classification has benefited from the emerging big data, such as mobile phone records and taxi trajectories. Temporal activity variations derived from these data have been used to interpret and understand the land use of parcels from the perspective of social functions, complementing the outcome of traditional remote sensing methods. However, spatial interaction patterns between parcels, which could depict land uses from a perspective of connections, have rarely been examined and analysed. To leverage spatial interaction information contained in the above-mentioned massive data sets, we propose a novel unsupervised land use classification method with a new type of place signature. Based on the observation that spatial interaction patterns between places of two specific land uses are similar, the new place signature improves land use classification by trading off between aggregated temporal activity variations and detailed spatial interactions among places. The method is validated with a case study using taxi trip data from Shanghai.     

Administrative hierarchy and urban land expansion in transitional China

In a growing body of literature on urbanization in China, scholars have emphasized the proactive role of the Chinese local state in urban land expansion. Drawing upon official land use change data from 1998 to 2008, this study investigates the relationship between the hierarchical structure of the Chinese urban administrative system and urban land expansion. We find that urban land expansion coincides with administrative hierarchy, and cities with higher administrative levels (ranked by central government) tend to expand more rapidly while controlling for other economic and demographic drivers of urban expansion. Spatial regime models reveal that economic and demographic drivers of urban growth are also sensitive to a city's administrative rank. By quantifying the link between a city's rank and urban land expansion, we conclude that considering the hierarchical structure of the Chinese cities will result in a fuller understanding of the rapid urban growth in China.     

遥感与地理信息系统技术在长江下游江岸稳定性评价中的应用

应用多时相遥感动态分析方法对长江南京以下河段近四十多年来江岸变迁进行调查,并建成江岸变迁图形数据库。对多期航道水深测量资料进行动态分析,建成航道水深数据库。应用地理信息系统技术,研究河床时空演变规律,结合沿江地质地貌,护岸工程等消息,对长江下游江岸稳定性进行评价。     

Using high resolution satellite imagery to estimate cropped area in Guatemala and Haiti

Guatemala and Haiti are two of the most food insecure nations in the Western Hemisphere. Measurements of food availability and access are instrumental in developing targeted hunger reduction strategies yet no estimates of cropped area (a critical input in the calculation of food production) at either a national or sub-national-level exist. The purpose of this research is to produce estimates of cropped area for Guatemala and Haiti using an area frame sampling approach and very high resolution (∼1 m) satellite imagery. Related research has combined livelihood data with topographic information to construct cropped area estimates in other settings using generalized additive models. We expand this approach with the inclusion of specific population variables in place of the livelihood data. We produce estimates of cropped area for the two countries and sub-national units and our results highlight the significance and complexity of incorporating explicit population characteristics into models of cropped area.     

Comparing spatial distributions of infant mortality over time: Investigating the urban environment of Baltimore,Maryland in 1880 and 1920

Infant mortality is a sensitive indicator of urban environmental conditions, and investigating the geography of such an indicator provides insight into variables affecting public health in urban North America in 1880 and 1920. Geographic information systems (GIS) and spatial analysis now provide a means by which to view past infant mortality distributions from a new perspective, one not available at the time. This study makes use of data collected from the 1880 and 1920 Vital Statistics Death Records for Baltimore, Maryland - mapping each infant death to his or her place of residence. Previous work with the 1880 data indicates an uneven distribution of infant deaths with some degree of spatial clustering. The current study takes these findings a step further through the use of the local spatial autocorrelation statistic, Gi*, to identify the locations of clusters in one or both years. The aim of the comparison is to determine whether the location of infant mortality clusters remained the same over time indicating persistent environmental, and possibly demographic, challenges in certain neighborhoods. The data indicated hotspots of infant mortality in both years with persistence in the Fells Point area of Baltimore. The significant clusters appeared in neighborhoods with large African American and/or immigrant populations in both years. The hotspots in the primarily African American neighborhood were only significant in 1880 despite presenting some intriguing questions about what caused such a change, particular when the population in that part of the city did not change. This work offers insights into the spatial distribution of infant mortality in the past and clues regarding which parts of the city need additional investigation to better understand their social and environmental characteristics.     

布哈河河口三角洲1970-2010年间面积变化研究

通过对布哈河河口三角洲1970²010年间的5期MSS、TM、ETM遥感影像进行分析,发现其地貌形态发生了明显的变化,并对影响其变化的原因进行了探讨。结果表明:1)布哈河河口三角洲从1970到2000年呈扩张趋势,面积扩张达67.97 km2010年间的5期MSS、TM、ETM遥感影像进行分析,发现其地貌形态发生了明显的变化,并对影响其变化的原因进行了探讨。结果表明:1)布哈河河口三角洲从1970到2000年呈扩张趋势,面积扩张达67.97 km²,湖岸线扩张也十分明显,仅在19892,湖岸线扩张也十分明显,仅在1989²000年间平均推进量达0.56 km;2)布哈河河口三角洲在2000到2010年呈萎缩趋势,面积萎缩了9.85 km2000年间平均推进量达0.56 km;2)布哈河河口三角洲在2000到2010年呈萎缩趋势,面积萎缩了9.85 km²,湖岸线萎缩了0.44 km;3)造成三角洲形态变化是有诸多因素的,其主导因素为青海湖水位变动,其次是受到其它诸如河流输沙、人为干扰等因素的影响,这些影响的贡献度尚不明确,有待进一步探讨。布哈河作为青海湖国家级自然保护区的最大补给河流,对青海湖的生态、气候环境有很大程度的影响,研究其河口三角洲的地貌变化具有重要意义。     

Predicting air temperature simultaneously for multiple locations in an urban environment: A bottom up approach

Cities are characterized by high heterogeneity that results in varied microclimate effects. The current study introduces a new bottom–up approach linking the urban Canyon Air Temperature (CAT) model with spatially distributed inputs extracted from a GIS data-base and remote sensing products to predict intra-urban temperature variability simultaneously for multiple locations in an urban environment. To provide proof of concept, the model was applied for the city of Bat-Yam, Israel. Simulation shows a maximum nighttime urban heat island (UHI) intensity of 2–2.25 °C, relative to a rural reference point, during both summer and winter, with significant spatial variability related to the height-to-width ratio of urban street canyons and to the surface land cover. The CAT simulation also highlighted the important influence of the local wind regime on the development and persistence of the nocturnal UHI. We conclude that linking CAT to a GIS data-base supports simulations at the city scale that reflect the local intra-urban variability. The model can be used to investigate both macro and micro scale spatio-temporal characteristics of the UHI in various urban development scenarios, which may be applied to generate appropriate geographically-explicit mitigation and adaptation measures.