Urban environment has functioned not only for ecological reason but also for socioeconomic function, due to this reason extraction of urban vegetation in highly dense urban environment becomes more important to unders...Urban environment has functioned not only for ecological reason but also for socioeconomic function, due to this reason extraction of urban vegetation in highly dense urban environment becomes more important to understand the inhabitants’ satisfaction of urban green space. With a medium resolution of satellite imagery, the precision is very low. We used high resolution of WorldView-2 satellite to raise the accuracy. We chose Depok City in West Java as a case study area, analyse four multispectral bands, and apply TCT algorithm for getting vegetation density. The relationship between vegetation density and inhabitants’ satisfaction was calculated by Geo-statistical technique based on administrative boundary. We extracted three types of urban vegetation density: good, mid and low. The final result shows that the inhabitants are mostly satisfied with good density of urban vegetation in the city forest inside Campus University of Indonesia.展开更多
Mapping and assessment of mangrove environment are crucial since the mangrove has an important role in the process of human-environment interaction. In Indonesia alone, 25% of South East Asia's mangroves available...Mapping and assessment of mangrove environment are crucial since the mangrove has an important role in the process of human-environment interaction. In Indonesia alone, 25% of South East Asia's mangroves available are under threat. Recognizing the availability and the ability of new sensor of Landsat data, this study investigates the use of Landsat ETM + 7 and Landsat 8, acquired in 2002 and 2013 respectively, for assessing the extent of mangroves along the South Sulawesi’s coastline. For each year, a supervised classification of the mangrove was performed using open source GRASS GIS software. The resulting maps were then compared to quantify the change. Field work activities were conducted and confirmed with the changes that occurred in the study area.? Considering the accuracy assessment, our study shows that the RGB composite color-supervised classification is better than band ratio-supervised classification methods. By linking the open source software with the Landsat data and Google Earth satellite imagery that is available in public domain, mangroves forest conversion and changes can be observed remotely. Ground truth surveys confirmed that, decreases of mangroves forest is due to the expansion of fishpond activity. This technique could potentially allow rapid, inexpensive remote monitoring of cascading, indirect effects of human activities to mangroves forest.展开更多
Urban vegetations have infinite proven benefits for urban inhabitants including providing shade, improving air quality, and enhancing the look and feel of communities. But creating a complete inventory is a time consu...Urban vegetations have infinite proven benefits for urban inhabitants including providing shade, improving air quality, and enhancing the look and feel of communities. But creating a complete inventory is a time consuming and resource intensive process. The extraction of urban vegetation is a challenging task, especially to monitor the urban tree heights. In this study we present an efficient extraction method for mapping and monitoring urban tree heights using fused hyperspectral image and LiDAR data. Endmember distribution mapping using the spectral angle mapper technique is employed in this study. High convenience results achieved using fused hyperspectral and LiDAR data from this semiautomatics technique. This method could enable urban community organizations or local governments to map and monitor?urban’s tree height and its spatial distribution.展开更多
Identification and monitoring of species composition and richness isneeded to formulate effective mangrove management and conservationpriorities. Prior studies have used commercial satellite images which arecost prohi...Identification and monitoring of species composition and richness isneeded to formulate effective mangrove management and conservationpriorities. Prior studies have used commercial satellite images which arecost prohibitive for national and global applications. Here, we usedfreely available Landsat satellite data and new indices to discriminatemangrove species in Maros Regency, South Sulawesi, Indonesia andSegara Anakan, West Java, Indonesia. We use sensitive algorithm of theprincipal polar spectral (PPS) indices to discriminate mangroves species.PPS Indices were produced from a set of 3-dimensional Landsat 8Operational Land Imager (OLI) spectral indices (PPS Brightness, PPSGreenness, and PPS Wetness) determined by a polar change of theprincipal component axes of a spectral image of reference scene. Wequalitatively compare this set of PPS indices with the set of conventionalRGB multi-bands image composition and conventional NormalizedDifference Vegetation Indices (NDVI) for mangroves speciesdiscrimination. The comparisons indicate that the set of PPS indiceshave the potential for regional and possibly global applications inmangroves species mapping and monitoring.展开更多
文摘Urban environment has functioned not only for ecological reason but also for socioeconomic function, due to this reason extraction of urban vegetation in highly dense urban environment becomes more important to understand the inhabitants’ satisfaction of urban green space. With a medium resolution of satellite imagery, the precision is very low. We used high resolution of WorldView-2 satellite to raise the accuracy. We chose Depok City in West Java as a case study area, analyse four multispectral bands, and apply TCT algorithm for getting vegetation density. The relationship between vegetation density and inhabitants’ satisfaction was calculated by Geo-statistical technique based on administrative boundary. We extracted three types of urban vegetation density: good, mid and low. The final result shows that the inhabitants are mostly satisfied with good density of urban vegetation in the city forest inside Campus University of Indonesia.
文摘Mapping and assessment of mangrove environment are crucial since the mangrove has an important role in the process of human-environment interaction. In Indonesia alone, 25% of South East Asia's mangroves available are under threat. Recognizing the availability and the ability of new sensor of Landsat data, this study investigates the use of Landsat ETM + 7 and Landsat 8, acquired in 2002 and 2013 respectively, for assessing the extent of mangroves along the South Sulawesi’s coastline. For each year, a supervised classification of the mangrove was performed using open source GRASS GIS software. The resulting maps were then compared to quantify the change. Field work activities were conducted and confirmed with the changes that occurred in the study area.? Considering the accuracy assessment, our study shows that the RGB composite color-supervised classification is better than band ratio-supervised classification methods. By linking the open source software with the Landsat data and Google Earth satellite imagery that is available in public domain, mangroves forest conversion and changes can be observed remotely. Ground truth surveys confirmed that, decreases of mangroves forest is due to the expansion of fishpond activity. This technique could potentially allow rapid, inexpensive remote monitoring of cascading, indirect effects of human activities to mangroves forest.
文摘Urban vegetations have infinite proven benefits for urban inhabitants including providing shade, improving air quality, and enhancing the look and feel of communities. But creating a complete inventory is a time consuming and resource intensive process. The extraction of urban vegetation is a challenging task, especially to monitor the urban tree heights. In this study we present an efficient extraction method for mapping and monitoring urban tree heights using fused hyperspectral image and LiDAR data. Endmember distribution mapping using the spectral angle mapper technique is employed in this study. High convenience results achieved using fused hyperspectral and LiDAR data from this semiautomatics technique. This method could enable urban community organizations or local governments to map and monitor?urban’s tree height and its spatial distribution.
文摘Identification and monitoring of species composition and richness isneeded to formulate effective mangrove management and conservationpriorities. Prior studies have used commercial satellite images which arecost prohibitive for national and global applications. Here, we usedfreely available Landsat satellite data and new indices to discriminatemangrove species in Maros Regency, South Sulawesi, Indonesia andSegara Anakan, West Java, Indonesia. We use sensitive algorithm of theprincipal polar spectral (PPS) indices to discriminate mangroves species.PPS Indices were produced from a set of 3-dimensional Landsat 8Operational Land Imager (OLI) spectral indices (PPS Brightness, PPSGreenness, and PPS Wetness) determined by a polar change of theprincipal component axes of a spectral image of reference scene. Wequalitatively compare this set of PPS indices with the set of conventionalRGB multi-bands image composition and conventional NormalizedDifference Vegetation Indices (NDVI) for mangroves speciesdiscrimination. The comparisons indicate that the set of PPS indiceshave the potential for regional and possibly global applications inmangroves species mapping and monitoring.
