“A solar radiation database of Europe has been computed within the GRASS GIS software. The database provides monthly and yearly averages of global irradiation on horizontal and inclined surfaces, as well as climatic parameters needed for an assessment of the potential photovoltaic electricity generation. The database is available on-line by means of a set of dynamic web applications. In the first application, a user may browse solar radiation and other maps and query the selected climatic parameters. The second application provides daily profiles of irradiance for a chosen month and for a selected surface inclination and orientation. The third application provides estimates of solar electricity generation.”
Climate Change Science
- Tue, Jul 13, 10:15AM – 11:30AM, Room 31 A
- Learn how experts are using GIS and related technologies to conduct cutting edge scientific research to assess climate change and its effects.
- Buffering Parcels: GIS Based Method for GHG Emission Analysis
Raef Porter, SACOG
Like many of the 18 MPO’s in California, Sacramento Area Council of Governments (SACOG) is developing the technical capacity needed to implement SB375, which is part of AB32, the State’s greenhouse gas (GHG) reduction policy. SACOG creates and analyzes land use and transportation at parcel level to quantify transportation-related GHG emissions. Parcels are used, as opposed to zones, because they better capture the relationship between land use and transportation. In place of zones, SACOG buffers parcel/point land use data, and the resulting buffered files are used in the travel demand model. Once modeled, outputs are mapped to show where emissions are highest. In the Sacramento region, these maps show a correlation between the built environment (e.g. distance from employment centers) and GHG emissions. SACOG hopes similar GIS and modeling techniques are integrated into planning processes in other regions around California to help implement GHG reduction policies.
Measuring Greenhouse Gas Emissions with a Sustainability Tool
Jung A Uhm, SCAG
Frank Wen, Southern California Association of Governments
Hsi-Hwa Hu, Southern California Association of Governments
Simon Shoi, Southern California Association of Governments
With the recent passage of California Senate Bill No. 375, the need for an analytical tool that helps local planners in land use decisions is greater than ever. This presentation aims to introduce a Sustainability Tool and its use for the development of sustainable communities in Southern California region. A Sustainability Tool developed by Southern California Association of Governments is an ArcGIS based modeling and evaluation tool scripted by Python that enables users to visualize and evaluate the impacts of different land use scenarios on vehicle use and Greenhouse Gas emissions in real time. By demonstrating the benefits of sustainable land use strategies in reducing vehicle use and emissions, the tool is expected to play a central role in creating a sustainable land use strategy for the region through participation and consensus building.
Climate Change and Sustainable Communities
- Wed, Jul 14, 8:30AM – 9:45AM, Room 31 A
- GIS is helping municipalities, indigenous communities, and policy makers identify their sustainability goals and take practical steps to achieve these objectives. Learn how a variety of organizations are applying GIS to deal with the changing climate and plan sustainable communities.
- Planning For Climate Change – ClimateWise
Richard Nauman, National Center for Conservation Science and Policy
Our ClimateWise program uses GIS to incorporate climate modeling data in community-based climate change adaptation planning. Modeling efforts have produced a series of large, spatially explicit datasets projecting future climatic conditions. The volume of information produced by these efforts coupled with the technical difficulty of accessing the data, processing it, and displaying it in a GIS environment has limited their usefulness for non-technical audiences. We have developed Python scripts that use the built-in geoprocessing functionality of ArcGIS to access these files and produce cartographic and tabular output used in climate adaptation planning processes. When incorporated into a facilitated series of forums, these data have proven valuable communities creating climate change adaptation plans at the river basin scale. Our process integrates the needs of cultural, ecological, economic, social, and built sectors of communities and results in robust action plans that build resistance and resilience in human and natural systems.
Local Climate Change GIS-databased Visioning Tools for Community Decision-Making
Olaf Schroth, CALP/UBC
Philip Paar, Konrad-Zuse-Zentrum für Informationstechnik Berlin (ZIB)
Climate change has become the key topic in urban and landscape planning because today, planners have to decide on the mitigation and adaptation measures that future will bring into action. However, there is a gap between the state of research and its current consideration in planning. The reasons are the complexity of climate change impact and the uncertainties that are linked to it. In this context, GIS is a potential tool for capacity building. With regard to international case studies, GIS is used to identify the potential spatial consequences of different adaptation and mitigation scenarios. Especially, the model builder allows varying alternative scenarios, considering the impact of different adaptation and mitigation measures. The visualization using the globe metaphor illustrates the global context of local action.
Habitat International, Volume 33, Issue 4, October 2009, Pages 310-318
Takahiro Tanaka, Daniel Benjamin Abramson, and Yoshito Yamazaki
“Charrettes have become popular in the urban design field, especially for use among multidisciplinary teams of professionals and non-professional community stakeholders seeking to incorporate a rich array of expertise in short visioning activities. Geographic Information Systems are among the technologies with potential to provide sophisticated spatial information to charrette participants efficiently. This article reports on a charrette carried out jointly by teams from Kobe University and the University of Washington, Seattle, USA, using GIS to inform urban design in three neighborhoods affected by the Great Hanshin–Awaji Earthquake of 1995 in Kobe, Japan. The article describes the charrette itself, and discusses the utility of GIS, given the challenges of disaster recovery in a context of undeveloped institutions for public participation, and with participants of different linguistic and educational backgrounds. In combination with electronically storable drawing technology, GIS proved useful in enlarging the multidisciplinary and cross-cultural reach of urban design; in incorporating new layers of pre-prepared expert data, and in combining such data with dynamically-generated “advice maps” and design ideas. For GIS-based charrettes to become more widely useful in community-scale design in Japan, however, additional property-scale data need to be available.”
Journal of Environmental Planning and Management, Volume 51, Issue 6 November 2008 , pages 817 – 832
Krishna Prasad Vadrevu; K. V. S. Badarinath; Anuradha Eaturu
“Information on fires in different geographic regions of India is relatively scarce. This study quantifies spatial and temporal patterns in fire occurrences covering different states and districts in India. Two important scientific questions are answered in this study: (1) how are the fire events distributed across different geographical regions? (2) are there any specific districts where fire events clustered across space and time? To address these questions, Along Track Scanning Radiometer (ATSR) derived satellite fire counts from 1997-2006 were used and the datasets were analysed using spatial scan statistic. Spatial scan statistic provides a test statistic for most likely ‘hotspot’ spatial clusters, based on the likelihood ratio test and Monte Carlo simulation. Results from geographical analysis based on state boundaries suggested Maharastra state had the highest number of fires followed by Madhya Pradesh, Chattisgarh, Orissa, etc., during the 10-year period. Among the several districts, the spatial scan statistic identified the most likely cluster of fire events in Dausa, Karauli, Sawai Madhopur, Bharatpur and Alwar in addition to several other secondary clusters, with high statistical significance. These results are based on a large sample of cases, and they provide convincing evidence of spatial clustering of fire events in the Indian region. Results relating to hotspot areas of fire risk can guide policy makers towards the best management strategies for avoiding damages to forests, human life and personal property in the ‘hotspot’ districts.”
Health & Place, In Press, Accepted Manuscript, Available online 25 February 2010
Arul Earnest, John Beard, Geoff Morgan, Douglas Lincoln, Richard Summerhayes, Deborah Donoghue, Therese Dunn, David Muscatello, and Kerrie Mengersen
“In the field of disease mapping, little has been done to address the issue of analysing sparse health datasets. We hypothesised that by modelling two outcomes simultaneously, one would be able to better estimate the outcome with a sparse count. We tested this hypothesis utilising Bayesian models, studying both birth defects and caesarean sections using data from two large, linked birth registries in New South Wales from 1990 to 2004. We compared four spatial models across seven birth defects: spina bifida, ventricular septal defect, OS-atrial septal defect, patent ductus arteriosus, cleft lip and or palate, trisomy 21 and hypospadias. For three of the birth defects, the shared component model with a zero-inflated Poisson (ZIP) extension performed better than other simpler models, having a lower Deviance Information Criteria (DIC). With spina bifida, the ratio of relative risk associated with the shared component was 2.82 (95% CI: 1.46-5.67). We found that shared component models are potentially beneficial, but only if there is a reasonably strong spatial correlation in effects for the study and referent outcomes.”
Geomorphology, In Press, Accepted Manuscript, Available online 11 March 2010
Dan Bălteanu, Viorel Chendeş, Mihaela Sima, Petru Enciu
“The paper proposes a brief spatial analysis of landslides in Romania, completed by a landslide susceptibility model. Landslides constitute a very common geomorphic hazard in this country, mainly in the hilly regions which occupy around 30% of the Romanian territory. The landslide susceptibility assessment at national level was accomplished using a Landslide Susceptibility Index (LSI) computed in GIS, which considers and weights the main factors that control landslide activity: lithology, slope gradient, maximum rainfall in 24 hrs, land use, seismicity and local relief. Each factor was classified into 7-18 classes which were rated from 1 to 10 by means of expert judgement. A formula was devised to compute Landslide Susceptibility Index over each 100 m × 100 m pixel and the resulting values were ranked into 5 landslide susceptibility classes. This synthetic method of landslide susceptibility assessment, applied to the whole country of Romania, is an useful tool to evaluate the distribution of landslide-prone areas, as well as to validate and to enhance some results obtained in previous studies based on field research and map interpretation. The most landslide prone areas correspond to the Subcarpathians (an outer fringe of hilly terrain accompanying the Carpathians), as well as to the Moldavian Plateau in the east. The semi-quantitative approach has been validated with satisfactorily results in a particular sector using independent cartographic landslide inventories.”
Computers, Environment and Urban Systems, Article in Press, 2010
L.K. Wiginton, H.T. Nguyen, and J.M. Pearce
“Solar photovoltaic (PV) technology has matured to become a technically viable large-scale source of sustainable energy. Understanding the rooftop PV potential is critical for utility planning, accommodating grid capacity, deploying financing schemes and formulating future adaptive energy policies. This paper demonstrates techniques to merge the capabilities of geographic information systems and object-specific image recognition to determine the available rooftop area for PV deployment in an example large-scale region in south eastern Ontario. A five-step procedure has been developed for estimating total rooftop PV potential which involves geographical division of the region; sampling using the Feature Analyst extraction software; extrapolation using roof area-population relationships; reduction for shading, other uses and orientation; and conversion to power and energy outputs. Limitations faced in terms of the capabilities of the software and determining the appropriate fraction of roof area available are discussed. Because this aspect of the analysis uses an integral approach, PV potential will not be georeferenced, but rather presented as an agglomerate value for use in regional policy making. A relationship across the region was found between total roof area and population of 70.0 m2/capita ± 6.2%. With appropriate roof tops covered with commercial solar cells, the potential PV peak power output from the region considered is 5.74 GW (157% of the region’s peak power demands) and the potential annual energy production is 6909 GWh (5% of Ontario’s total annual demand). This suggests that 30% of Ontario’s energy demand can be met with province-wide rooftop PV deployment. This new understanding of roof area distribution and potential PV outputs will guide energy policy formulation in Ontario and will inform future research in solar PV deployment and its geographical potential.”