After a major flood in Jakarta in 2007, the government of Indonesia partnered with a consortium of Dutch engineers and designers to produce a solution. In 2013, this consortium proposed a plan for the Great Garuda, a megaproject that combined a deep seawall and private real estate, both in an archipelago of reclaimed islands that would be shaped like the mythical garuda eagle, Indonesia's national symbol. Despite a range of infeasibilities and opposition, the Great Garuda became the most prominent vision for the city's future. This article argues that the promotion of the Great Garuda was a process of ‘hyper‐planning’, which projected the city as a national triumph and a global spectacle. The plan served the political objective of creating the mere possibility of a ‘new Jakarta’ apart from the perceived chaos of the current capital. Further, the plan functioned as a performative object through its iconic imagery and its circulations. The process of hyper‐planning simultaneously projected a future of urban success, but also displaced the contingencies of the future to the private sector, beyond the purview of the state. 相似文献
We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (Glob-Cover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.
