The Effects of Environmental Brand Attributes and Nature Imagery in Green Advertising

Following Hartmann and Apaolaza-Ibáñez’ [(2009). Green advertising revisited. Conditioning virtual nature experiences. International Journal of Advertising, 28(4), 715–739] approach, this experimental study compares the effects of three types of green print ads: a non-green ad, a functional green ad promoting environmental product attributes, and a combined nature ad featuring a pleasant nature image in addition to functional attributes. We extend prior research by simultaneously testing moderating and mediating mechanisms to explain brand attitudes and purchase intention. Using a quota sample of 456 consumers, findings suggest that the functional ad enhances perceptions of environmental brand benefits, which positively affect purchase intention partially mediated by brand attitudes. The combined nature ad, by contrast, activates an additional emotional process of virtually experiencing nature which positively influences brand attitudes and purchase intention beyond perceptions of environmental brand benefits. The effects of the combined nature ad are even stronger for highly involved consumers.     

Water quality assessment at Ömerli Dam using remote sensing techniques

Water quality at Omerli Dam, which is a vital potable water resource of Istanbul City, Turkey was assessed using the first four bands of Landsat 7-ETM satellite data, acquired in May 2001 and water quality parameters, such as chlorophyll-a, suspended solid matter, secchi disk and total phosphate measured at several measurement stations at Omerli Dam during satellite image acquisition time and archived at the Marine Pollution and Ecotoxicology laboratory of the Marmara Research Center, where this study was carried out. Establishing a relationship between this data, and the pixel reflectance values in the satellite image, chlorophyll-a, suspended solid matter, secchi disk and total phosphate maps were produced for the Omerli Dam.     

基于Landsat-8数据和劈窗算法的地表温度反演及城市热岛效应研究

陆地表面温度(Land Surface Temperature,LST)是地表能量平衡组分中的一个重要参数。随着卫星遥感技术的快速发展,遥感反演成为获取区域LST的一个重要手段。目前已有学者提出多种基于遥感数据反演LST的算法,其中劈窗算法被证明是一种精度较高的算法。基于Landsat-8卫星30 m空间分辨率的陆地成像仪(OLI)数据和100 m分辨率的热红外传感器(TIRS)数据,采用劈窗算法计算了无锡地区的LST,并采用地面实测水温数据和同步的MODIS温度产品对Landsat-8的计算结果进行了验证和对比分析。结果表明:基于Landsat-8数据和劈窗算法获取的LST精度较高,误差1K。在计算的LST结果基础上,进一步提取了热场变异指数来分析城市热岛空间分布特征,给出了城市热岛效应的定量化描述,并就不同地表覆盖类型对热岛效应的影响进行了分析。     

Detecting deforestation with a spectral change detection approach using multitemporal Landsat data: a case study of Kinabalu Park, Sabah, Malaysia

Tropical deforestation is occurring at an alarming rate, threatening the ecological integrity of protected areas. This makes it vital to regularly assess protected areas to confirm the efficacy of measures that protect that area from clearing. Satellite remote sensing offers a systematic and objective means for detecting and monitoring deforestation. This paper examines a spectral change approach to detect deforestation using pattern decomposition (PD) coefficients from multitemporal Landsat data. Our results show that the PD coefficients for soil and vegetation can be used to detect deforestation using change vector analysis (CVA). CVA analysis demonstrates that deforestation in the Kinabalu area, Sabah, Malaysia has significantly slowed from 1.2% in period 1 (1973 and 1991) to 0.1% in period 2 (1991 and 1996). A comparison of deforestation both inside and outside Kinabalu Park has highlighted the effectiveness of the park in protecting the tropical forest against clearing. However, the park is still facing pressure from the area immediately surrounding the park (the 1km buffer zone) where the deforestation rate has remained unchanged.     

Landsat ETM+ Images in the Estimation of Seasonal Lake Water Quality in Boreal River Basins

We investigated the use of Landsat ETM+ images in the monitoring of turbidity, colored dissolved organic matter (CDOM), and Secchi disk transparency (Z(SD)) in lakes of two river basins located in southern Finland. The ETM+ images were acquired in May, June, and September 2002 and were corrected for atmospheric disturbance using the simplified method of atmospheric correction (SMAC) model. The in situ measurements consisted of water sampling in the largest lake of the region, routine monitoring results for the whole study area, and Z(SD) observations made by volunteers. The ranges of the water quality variables in the dataset were as follows: turbidity, 0.6-25 FNU; absorption coefficient of CDOM at 400 nm, 1.0-12.2 m(-1); Z(SD), 0.5-5.5 m; and chlorophyll a concentration, 2.4-80 mug L(-1). The estimation accuracies of the image-specific empirical algorithms expressed as relative errors were 23.0% for turbidity, 17.4% for CDOM, and 21.1% for Z(SD). If concurrent in situ measurements had not been used for algorithm training, the average error would have been about 37%. The atmospheric correction improved the estimation accuracy only slightly compared with the use of top-of-atmospheric reflectances. The accuracy of the water quality estimates without concurrent in situ measurements could have been improved if in-image atmospheric parameters had been available. The underwater reflectance simulations of the ETM+ channel wavelengths using water quality typical for Finnish lakes (data from 1113 lakes) indicated that region-specific algorithms may be needed in other parts of the country, particularly in the case of Z(SD). Despite the limitations in the spectral and radiometric resolutions, ETM+ imagery can be an effective aid, particularly in the monitoring and management of small lakes (<1 km(2)), which are often not included in routine monitoring programs.     

Changes in Forest Area Along Stream Networks in an Agricultural Catchment of the Great Barrier Reef Lagoon

Scenes from the series of multispectral sensors on the Landsat satellites were used to map recent changes (between 1972 and 2004) in forest cover within and adjacent to stream networks of an intensively farmed region of the southern Great Barrier Reef catchment (Australia). Unsupervised ISODATA classifications of Tasseled-Cap transformed data (at 57 m ground resolution) mapped forest and cleared areas within 150 m of Pisoneer catchment waterways with 72.2% overall accuracy (K(hat) = 0.469), when adjusted for the size of each class. Although the user's accuracy was higher for the forest class (82.1 +/- 8.4% at alpha = 0.05), large errors of commission (34.2 +/- 8.3%) substantially affected map accuracy for the cleared class. The main reasons for misclassification include: (1) failure to discriminate narrowly vegetated riparian strips; (2) misregistration of scenes; and (3) spectral similarity of ground cover. Error matrix probabilities were used to adjust the mapped area of classes, resulting in a decline of forest cover by 12.3% and increase of clearing by 18.5% (22.4 km(2) change; 95% confidence interval: 14.3-29.6 km(2)) between 1972 and 2004. Despite the mapping errors, Landsat data were able to identify broad patterns of land cover change that were verified from aerial photography. Most of the forest losses occurred in open forest to woodland habitat dominated by Eucalyptus, Corymbia, and Lophostemon species, which were largely replaced by sugarcane cropping. Melaleuca communities were similarly affected, though they have a much smaller distribution in the catchment.     

NEAR REAL-TIME MAPPING OF THE 1975 MISSISSIPPI RIVER FLOOD IN LOUISIANA USING LANDSAT IMAGERY1

ABSTRACT: The project described in this report was undertaken by the Louisiana State Planning Office to establish the extent of backwater flooding in Louisiana in April 1975. Band 7 Landsat imagery, enlarged to a scale of 1:250,000 was used to visually identify flooded areas. Inundated areas were delineated on overlays keyed to 1:250,000 U.S. Geological Survey topographic quadrangles. Tabular data identifying acres flooded, according to land use type, were derived by merging the flood map overlays with computerized 1972 land use data. Approximately 1.12 million acres of the state were inundated by flood waters. The total acreage and land use types affected by flooding were determined within 72 hours from the time the flood areas were imaged. Flooded maps were prepared for 26 parishes. Field observations were made by Louisiana Cooperative Extension Service county agents in order to determine the accuracy of parish flood maps and flood acreage figures by land use type. Results indicated that this was a fast, accurate, and relatively inexpensive method of compiling flood data for disaster planning and postflood analysis.     

National aeronautics and space administration

The United States National Aeronautics and Space Administration is an important real and potential source of global environmental data. This paper describes some of its capabilities as they relate to the their R&D and their data centers.     

Remote Assessment of Forest Health in Southern Arizona, USA: Evidence for Ozone-Induced Foliar Injury

This paper examines possible ozone-induced foliar injury to ponderosa pine areas in the Rincon Mountains of southern Arizona from 1972 to 1992. Spatiotemporal differences in a satellite-derived vegetation index (VI) are examined with respect to antecedent moisture conditions, temporal variations in ozone exposure levels, and measured foliar injury values from 1985. Seasonal ozone exposure levels (SUM60 and W126) increased from 1982 to 1998 and were significantly correlated (r = 0.49 and 0.53, α= 0.05) with annual population totals in the Tucson area. Extensive masking of satellite images from 1972, 1986, and 1992 resulted in two optimal change detection areas, with one site, TVWMica, exposed mostly to the Tucson air pollution plume, while the other site, EMica, was more protected from Tucson-derived pollution. An overall increase in VI from 1972 to 1992 at both sites appears to have been caused by an increase in moisture availability. Larger foliar injury values in 1985 were associated with a smaller increase in VI (i.e., a smaller increase in green leaf biomass) from 1972 to 1986. From 1972 to 1986 and from 1986 to 1992, VI values at TV/WMica increased at a slower rate compared to those at EMica. The reduced increase in “green-up” may have been caused partially by ozone-induced foliar injury and resulting decreases in green leaf biomass. However, these spatial differences in VI values may have also been caused by a number of other factors. Results nevertheless reveal the strong possibility of distinct, topographically based, spatial variations in ozone-induced foliar injury within the Rincons.     

RESERVOIR TROPHIC STATE EVALUATION USING LANISAT TM IMAGES1

ABSTRACT: Reservoir water quality is traditionally monitored and evaluated based on field data. Collecting and analyzing field water quality data are costly and time consuming tasks, and whether a limited number of field data truly characterize the spatial variation of the trophic state within a vast water body is often disputed. In this study we utilize Landsat TM data to estimate the water quality and trophic state of the Te‐Chi reservoir in Central Taiwan. A modified multi‐parameter model of Carlson's trophic state index (TSI) was developed for the Te‐chi reservoir. Water quality parameters (concentration of chlorophyll‐a, total phosphorous measurement, and secchi disk depth) required by the model are found to have high correlations with combinations of TM bands. Therefore, TM data are used to map the trophic state of the reservoir. TM‐derived TSI maps of the reservoir reveal that, in summer, the trophic state in the reservoir generally improves from upstream to downstream and that zones of distinct trophic state exist. A trophic state index based on secchi disk depth may give erroneous values in the upstream section of the reservoir pool due to high sediment concentration in the reservoir inflow. We conclude that the Te‐Chi reservoir is eutrophic or worse in summer and meso‐eutrophic in winter. Implementation of best management practices to reduce nonpoint source pollution in the upstream watershed is highly recommended. This study demonstrates the capability of mapping the trophic state in impounded water bodies using the Landsat TM data.