Spatiotemporal Pattern of Urban Forest Leaf Area Index in Response to Rapid Urbanization and Urban Greening

Rapid urbanization and urban greening have caused great changes to urban forests in China. Understanding spatiotemporal patterns of urban forest leaf area index (LAI) under rapid urbanization and urban greening is important for urban forest planning and management. We evaluated the potential for estimating urban forest LAI spatiotemporally by using Landsat TM imagery. We collected three scenes of Landsat TM (thematic mapper) images acquired in 1997, 2004 and 2010 and conducted a field survey to collect urban forest LAI. Finally, spatiotemporal maps of the urban forest LAI were created using a NDVI-based urban forest LAI predictive model. Our results show that normalized differential vegetation index (NDVI) could be used as a predictor for urban forest LAI similar to natural forests. Both rapid urbanization and urban greening contribute to the changing process of urban forest LAI. The urban forest has changed considerably from 1997 to 2010. Urban vegetated pixels decreased gradually from 1997 to 2010 due to intensive urbanization. Leaf area for the study area was 216.4, 145.2 and 173.7 km2 in the years 1997, 2004 and 2010, respectively. Urban forest LAI decreased sharply from 1997 to 2004 and increased slightly from 2004 to 2010 because of numerous greening policies. The urban forest LAI class distributions were skewed toward low values in 1997 and 2004. Moreover, the LAI presented a decreasing trend from suburban to downtown areas. We demonstrate the usefulness of TM remote-sensing in understanding spatiotemporal changing patterns of urban forest LAI under rapid urbanization and urban greening

Identifying and categorizing risks of new product development in a small technology-driven company

New product development (NPD), as a locus of the innovative potential of organizations, plays an essential role in small technology-driven company survival. To address the research gap and fulfill the companies’ needs, this survey aims to post and verify a new, simple and not time-consuming methodology for risk identification and categorization of industrial products development. To check the hypothesis that NPD project technical, cost and schedule sets of risks could be categorized as both threats and opportunities, an experiment was conducted in a small Serbian enterprise that has developed 52 innovative solid state based lighting products for outdoor lighting infrastructure. There were 69 identified risks (51 threats and 18 opportunities) that through 76 factors influence new products’ technical characteristics, schedule and cost. Explorative factor analysis was applied to reduce and compress the data and 26 composite factors were obtained as valid predictors of the NPD project results. Regarding the technical characteristics risks, the threats can be grouped into four factors consisting of six risk types, while opportunities can be grouped into two factors consisting of four risk categories. The risks influencing the schedule disturbance that act as threats are grouped into eight factors consisting of ten risk types, while those that could be used in opportunities are grouped in four factors with eight risks identified. The risks influencing the costs that threaten the project are recognized as five factors described by seven risks, while those that act as opportunities are grouped into three factors described by five variables in total