Knowledge Resource Center for Ecological Environment in Arid Area
| Remote sensing of leaf area index in Savannah grass using inversion of radiative transfer model on Landsat 8 imagery: case study Mpumalanga, South Africa | |
| Masemola;Cecilia Ramakgahlele | |
| 出版年 | 2015 |
| 英文摘要 | Savannahs regulate an agro-ecosystem crucial for the production of domestic livestock, one of the main sources of income worldwide as well as in South African rural communities. Nevertheless, globally these ecosystem functions are threatened by intense human exploitation, inappropriate land use and environmental changes. Leaf area index (LAI) defined as one half the total green leaf area per unit ground surface area, is an inventory of the plant green leaves that defines the actual size of the interface between the vegetation and the atmosphere. Thus, LAI spatial data could serve as an indicator of rangeland productivity. Consequently, the accurate and rapid estimation of LAI is a key requirement for farmers and policy makers to devise sustainable management strategies for rangeland resources. In this study, the main focus was to assess the utility and the accuracy of the PROSAILH radiative transfer model (RTM) to estimate LAI in the South African rangeland on the recently launched Landsat 8 sensor data. The Landsat 8 sensor has been a promising sensor for estimating grassland LAI as compared to its predecessors Landsat 5 to 7 sensors because of its increased radiometric resolution. For this purpose, two PROSAIL inversion methods and semi- empirical methods such as Normalized difference vegetation index (NDVI) were utilized to estimate LAI. The results showed that physically based approaches surpassed empirical approach with highest accuracy yielded by artificial neural network (ANN) inversion approach (RMSE=0.138), in contrast to the Look-Up Table (LUT) approach (RMSE=0.265). In conclusion, the results of this study proved that PROSAIL RTM approach on Landsat 8 data could be utilized to accurately estimate LAI at regional scale which could aid in rapid assessment and monitoring of the rangeland resources. Environmental Sciences M. Sc. (Environmental Science) |
| 英文关键词 | Leaf area index (LAI) Radiative transfer models PROSAIL LUT ANN Vegetation Indices Empirical methods Landsat 8 imagery 577.40968271 Landsat satellites Radiative transitions |
| 语种 | 英语 |
| URL | http://hdl.handle.net/10500/19734 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/249279 |
| 推荐引用方式 GB/T 7714 | Masemola;Cecilia Ramakgahlele. Remote sensing of leaf area index in Savannah grass using inversion of radiative transfer model on Landsat 8 imagery: case study Mpumalanga, South Africa[D],2015. |
| 条目包含的文件 | 条目无相关文件。 | |||||
| 个性服务 |
| 推荐该条目 |
| 保存到收藏夹 |
| 导出为Endnote文件 |
| 谷歌学术 |
| 谷歌学术中相似的文章 |
| [Masemola;Cecilia Ramakgahlele]的文章 |
| 百度学术 |
| 百度学术中相似的文章 |
| [Masemola;Cecilia Ramakgahlele]的文章 |
| 必应学术 |
| 必应学术中相似的文章 |
| [Masemola;Cecilia Ramakgahlele]的文章 |
| 相关权益政策 |
| 暂无数据 |
| 收藏/分享 |
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。
