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.
Journal of Geographical Sciences - The risk posed by natural disasters can be largely reflected by hazard and vulnerability. The analysis of long-term hazard series can reveal the mechanisms by... 相似文献
Despite decades of recognition and worry about diversity, our discipline remains persistently white. That is, it is dominated by white bodies and it continues to conform to norms, practices, and ideologies of whiteness. This is a loss. At best, it limits the possibilities and impact of our work as geographers. At worst, it perpetuates harmful exclusions in our discipline: its working environments, its institutions, and its knowledge production. This remains deeply concerning for many geographers, and there has been important research, commentary, and institutional activity over the years. Yet, research shows us that little meaningful progress has been made. We know that mentoring is one vital part of the journey toward change. As such, we reflect here on our experience developing a research collective built on a transformative mentoring practice. We outline the key challenges, strategies, and tentative successes of the collective in supporting women of color undergraduate, graduate, and faculty geographers, arguing that such feminist formations are a vital part of the path to intellectual racial justice in our field. Key Words: diversity, feminist geography, higher education, mentoring, race.相似文献
