Global hidden spillover effects among concurrent green initiatives.

Concurrently implemented green initiatives to combat global environmental crises may be curtailed or even sacrificed given the ongoing global economic contraction. We collected empirical data and information about green initiatives from 15 sites or countries worldwide. We systematically explored how specific policy, intended behaviors, and gains of given green initiative may interact with those of other green initiatives concurrently implemented in the same geographic area or involving the same recipients.

Mapping environmentally sustainable urban development within six US cities through object-based image change analysis of aerial orthoimagery.

The rapid expansion of cities and continuous urban population growth underscores a need for sustainable urban development. Sustainable development is that which addresses human needs, contributes to well-being, is economically viable, and utilizes natural resources at a degree sustainable by the surrounding environmental systems. Urban green spaces, green roofs, and solar panels are examples of environmentally sustainable urban development (ESUD), or development that focuses on environmental impact, but also presents the potential to achieve social and economic sustainability.

Evaluation of thermal infrared imaging from uninhabited aerial vehicles for arboreal wildlife surveillance.

An important component of wildlife management and conservation is monitoring the health and population size of wildlife species. Monitoring the population size of an animal group can inform researchers of habitat use, potential changes in habitat and resulting behavioral adaptations, individual health, and the effectiveness of conservation efforts. Arboreal monkeys are difficult to monitor as their habitat is often poorly accessible and most monkey species have some degree of camouflage, making them hard to observe in and below the tree canopy.

Evaluating Drought Impact on Postfire Recovery of Chaparral Across Southern California.

Chaparral shrubs in southern California may be vulnerable to frequent fire and severe drought. Drought may diminish postfire recovery or worsen impact of short-interval fires. Field-based studies have not shown the extent and magnitude of drought effects on recovery, which may vary among chaparral types and climatic zones.

Does short-interval fire inhibit postfire recovery of chaparral across southern California?

Regrowth after fire is critical to the persistence of chaparral shrub communities in southern California, which has been subject to frequent fire events in recent decades. Fires that recur at short intervals of 10 years or less have been considered an inhibitor of recovery and the major cause of 'community type-conversion' in chaparral, primarily based on studies of small extents and limited time periods. However, recent sub-regional investigations based on remote sensing suggest that short-interval fire (SIF) does not have ubiquitous impact on postfire chaparral recovery.

Assessment of volunteered geographic information for vegetation mapping.

Vegetation mapping requires extensive field data for training and validation. Volunteered geographic information in the form of geotagged photos of identified plants has the potential to serve as a supplemental data source for vegetation mapping projects. In this study, we compare the locations of specific taxa from the iNaturalist platform to locations identified on both a fine-scale vegetation map and high-resolution ortho-imagery in open-canopy shrubland in San Clemente Island, CA.

Evaluating uncertainty in Landsat-derived postfire recovery metrics due to terrain, soil, and shrub type variations in southern California.

Temporal trajectories of apparent vegetation abundance based on the multi-decadal Landsat image series provide valuable information on the postfire recovery of chaparral shrublands, which tend to mature within one decade. Signals of change in fractional shrub cover (FSC) extracted from time-sequential Normalized Difference Vegetation Index (NDVI) data can be systematically biased due to spatial variation in shrub type, soil substrate, or illumination differences associated with topography. We evaluate the effects of these variables in Landsat-derived metrics of FSC and postfire recovery, based upon three chaparral sites in southern California which contain shrub community ecotones, complex terrain, and soil variations.

Space-time chlorophyll-a retrieval in optically complex waters that accounts for remote sensing and modeling uncertainties and improves remote estimation accuracy.

Remote sensing reflectance (Rrs) values measured by satellite sensors involve large amounts of uncertainty leading to non-negligible noise in remote Chlorophyll-a (Chl-a) concentration estimation. This work distinguished between two main stages in the case of estimating distributions of Chl-a within the Gulf of St. Lawrence (Canada).

Monitoring forest cover change within different reserve types in southern Ghana.

Rapid population and economic growth quickly degrade and deplete forest resources in many developing countries, even within protected areas. Monitoring forest cover change is critical for assessing ecosystem changes and targeting conservation efforts. Yet the most biodiverse forests on the planet are also the most difficult to monitor remotely due to their frequent cloud cover.

Patterns of mortality in a montane mixed-conifer forest in San Diego County, California.

We examine spatial patterns of conifer tree mortality and their changes over time for the montane mixed-conifer forests of San Diego County. These forest areas have recently experienced extensive tree mortality due to multiple factors. A spatial contextual image processing approach was utilized with high spatial resolution digital airborne imagery to map dead trees for the years 1997, 2000, 2002, and 2005 for three study areas: Palomar, Volcan, and Laguna mountains.

Use of ultra-high spatial resolution aerial imagery in the estimation of chaparral wildfire fuel loads.

Development of methods that more accurately estimate spatial distributions of fuel loads in shrublands allows for improved understanding of ecological processes such as wildfire behavior and postburn recovery. The goal of this study is to develop and test remote sensing methods to upscale field estimates of shrubland fuel to broader-scale biomass estimates using ultra-high spatial resolution imagery captured by a light-sport aircraft. The study is conducted on chaparral shrublands located in eastern San Diego County, CA, USA.

A Pattern-Based Definition of Urban Context Using Remote Sensing and GIS.

In Sub-Saharan Africa rapid urban growth combined with rising poverty is creating diverse urban environments, the nature of which are not adequately captured by a simple urban-rural dichotomy. This paper proposes an alternative classification scheme for urban mapping based on a gradient approach for the southern portion of the West African country of Ghana. Landsat Enhanced Thematic Mapper Plus (ETM+) and European Remote Sensing Satellite-2 (ERS-2) synthetic aperture radar (SAR) imagery are used to generate a pattern based definition of the urban context.

Histogram Curve Matching Approaches for Object-based Image Classification of Land Cover and Land Use.

The classification of image-objects is usually done using parametric statistical measures of central tendency and/or dispersion (e.g., mean or standard deviation).

Urban Vegetation Cover and Vegetation Change in Accra, Ghana: Connection to Housing Quality.

The objectives are to (1) quantify, map, and analyze vegetation cover distributions and changes across Accra, Ghana, for 2002 and 2010; and (2) examine the statistical relationship between vegetation cover and a housing quality index (HQI) for 2000 at the neighborhood level. Pixel-level vegetation cover maps derived using threshold classification of 2002 and 2010 QuickBird normalized difference vegetation index images have very high overall accuracies and yield an estimate of 5.9 percent vegetation cover reduction over the study area between 2002 and 2010.

Assessing and monitoring semi-arid shrublands using object-based image analysis and multiple endmember spectral mixture analysis.

Arid and semi-arid shrublands have significant biological and economical values and have been experiencing dramatic changes due to human activities. In California, California sage scrub (CSS) is one of the most endangered plant communities in the US and requires close monitoring in order to conserve this important biological resource. We investigate the utility of remote-sensing approaches--object-based image analysis applied to pansharpened QuickBird imagery (QBPS/OBIA) and multiple endmember spectral mixture analysis (MESMA) applied to SPOT imagery (SPOT/MESMA)--for estimating fractional cover of true shrub, subshrub, herb, and bare ground within CSS communities of southern California.

Frequency distribution signatures and classification of within-object pixels.

The premise of geographic object-based image analysis (GEOBIA) is that image objects are composed of aggregates of pixels that correspond to earth surface features of interest. Most commonly, image-derived objects (segments) or objects associated with predefined land units (e.g.

Connecting the Dots Between Health, Poverty and Place in Accra, Ghana.

West Africa has a rapidly growing population, an increasing fraction of which lives in urban informal settlements characterized by inadequate infrastructure and relatively high health risks. Little is known, however, about the spatial or health characteristics of cities in this region or about the spatial inequalities in health within them. In this article we show how we have been creating a data-rich field laboratory in Accra, Ghana, to connect the dots between health, poverty, and place in a large city in West Africa.

Assessing the Utility of Satellite Imagery with Differing Spatial Resolutions for Deriving Proxy Measures of Slum Presence in Accra, Ghana.

Little research has been conducted on how differing spatial resolutions or classification techniques affect image-driven identification and categorization of slum neighborhoods in developing nations. This study assesses the correlation between satellite-derived land cover and census-derived socioeconomic variables in Accra, Ghana to determine whether the relationship between these variables is altered with a change in spatial resolution or scale. ASTER and Landsat TM satellite images are each used to classify land cover using spectral mixture analysis (SMA), and land cover proportions are summarized across Enumeration Areas in Accra and compared to socioeconomic data for the same areas.

Comparison of Object-Based Image Analysis Approaches to Mapping New Buildings in Accra, Ghana Using Multi-Temporal QuickBird Satellite Imagery.

The goal of this study was to map and quantify the number of newly constructed buildings in Accra, Ghana between 2002 and 2010 based on high spatial resolution satellite image data. Two semi-automated feature detection approaches for detecting and mapping newly constructed buildings based on QuickBird very high spatial resolution satellite imagery were analyzed: (1) post-classification comparison; and (2) bi-temporal layerstack classification. Feature Analyst software based on a spatial contextual classifier and ENVI Feature Extraction that uses a true object-based image analysis approach of image segmentation and segment classification were evaluated.

The effect of input data transformations on object-based image analysis.

The effect of using spectral transform images as input data on segmentation quality and its potential effect on products generated by object-based image analysis are explored in the context of land cover classification in Accra, Ghana. Five image data transformations are compared to untransformed spectral bands in terms of their effect on segmentation quality and final product accuracy. The relationship between segmentation quality and product accuracy is also briefly explored.

Geographic object-based delineation of neighborhoods of Accra, Ghana using QuickBird satellite imagery.

The objective was to test GEographic Object-based Image Analysis (GEOBIA) techniques for delineating neighborhoods of Accra, Ghana using QuickBird multispectral imagery. Two approaches to aggregating census enumeration areas (EAs) based on image-derived measures of vegetation objects were tested: (1) merging adjacent EAs according to vegetation measures and (2) image segmentation. Both approaches exploit readily available functions within commercial GEOBIA software.

Monitoring habitat preserves in southern California using high spatial resolution multispectral imagery.

Habitat preserve systems have been established adjacent to the densely populated regions of southern California to support indigenous plant and animal species that are listed as rare, threatened, or endangered. Monitoring the condition of habitat across these broad preserves is necessary to ensure their long-term viability and may be effectively accomplished using remote sensing techniques with high spatial resolution visible and near-infrared (VNIR) multispectral imagery. The utility of 1 m spatial resolution VNIR imagery for detailed change detection and monitoring of Mediterranean-type ecosystems is assessed here.

Assessment of the Spatial Co-registration of Multitemporal Imagery from Large Format Digital Cameras in the Context of Detailed Change Detection.

Large format digital camera (LFDC) systems are becoming more broadly available and regularly collect image data over large areas. Spectral and radiometric attributes of imagery from LFDC systems make this type of image data appropriate for semi-automated change detection. However, achieving accurate spatial co-registration between multitemporal image sets is necessary for semi-automated change detection.

Can we spot a neighborhood from the air? Defining neighborhood structure in Accra, Ghana.

Slums are home to a large fraction of urban residents in cities of developing nations, but little attempt has been made to go beyond a simple slum/non-slum dichotomy, nor to identify slums more quantitatively than through local reputation. We use census data from Accra, Ghana, to create an index that applies the UN-Habitat criteria for a place to be a slum. We use this index to identify neighborhoods on a continuum of slum characteristics and on that basis are able to locate the worst slums in Accra.

ETHNIC RESIDENTIAL PATTERNS AS PREDICTORS OF INTRA-URBAN CHILD MORTALITY INEQUALITY IN ACCRA, GHANA.

As cities of developing nations absorb an increasing fraction of the world's population increase, questions have arisen about the potential for emerging inequalities in health within places that are already suffering from inadequate infrastructure. In this paper we explore the pattern of child mortality inequalities (as a proxy for overall health levels) within a large sub-Saharan African city-Accra, Ghana-and then we examine the extent to which existing residential patterns by ethnicity may be predictive of any observed intra-urban inequalities in child mortality. We find that the spatial variability in child mortality in Accra is especially associated with the pattern of residential separation of the Ga from other ethnic groups, with the Ga having higher levels of mortality than other ethnic groups.