| 来源类型 | Article |
| 规范类型 | 其他 |
| DOI | 10.1016/j.isprsjprs.2014.06.016 |
| Building a hybrid land cover map with crowdsourcing and geographically weighted regression. | |
| See L; Schepaschenko D; Lesiv M; McCallum I; Fritz S; Perger C; Vakolyuk M; Schepaschenko M | |
| 发表日期 | 2015 |
| 出处 | ISPRS Journal of Photogrammetry and Remote Sensing 103: 48-56 |
| 出版年 | 2015 |
| 语种 | 英语 |
| 摘要 | Land cover is of fundamental importance to many environmental applications and serves as critical baseline information for many large scale models e.g. in developing future scenarios of land use and climate change. Although there is an ongoing movement towards the development of higher resolution global land cover maps, medium resolution land cover products (e.g. GLC2000 and MODIS) are still very useful for modelling and assessment purposes. However, the current land cover products are not accurate enough for many applications so we need to develop approaches that can take existing land covers maps and produce a better overall product in a hybrid approach. This paper uses geographically weighted regression (GWR) and crowdsourced validation data from Geo-Wiki to create two hybrid global land cover maps that use medium resolution land cover products as an input. Two different methods were used: (a) the GWR was used to determine the best land cover product at each location; (b) the GWR was only used to determine the best land cover at those locations where all three land cover maps disagree, using the agreement of the land cover maps to determine land cover at the other cells. The results show that the hybrid land cover map developed using the first method resulted in a lower overall disagreement than the individual global land cover maps. The hybrid map produced by the second method was also better when compared to the GLC2000 and GlobCover but worse or similar in performance to the MODIS land cover product depending upon the metrics considered. The reason for this may be due to the use of the GLC2000 in the development of GlobCover, which may have resulted in areas where both maps agree with one another but not with MODIS, and where MODIS may in fact better represent land cover in those situations. These results serve to demonstrate that spatial analysis methods can be used to improve medium resolution global land cover information with existing products. |
| 主题 | Ecosystems Services and Management (ESM) |
| 关键词 | Land cover Validation Crowdsourcing Map integration Global land cover Geographically weighted regression |
| URL | http://pure.iiasa.ac.at/id/eprint/11475/ |
| 来源智库 | International Institute for Applied Systems Analysis (Austria) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/130178 |
| 推荐引用方式 GB/T 7714 | See L,Schepaschenko D,Lesiv M,et al. Building a hybrid land cover map with crowdsourcing and geographically weighted regression.. 2015. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Building%20a%20hybri（576KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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