Dong Ren-cai

Optimization of post-classification processing of high-resolution satellite image:A case study

The application of remote sensing monitoring techniques plays a crucial role in evaluating and governing the vast amount of ecological construction projects in China. However, extracting information of ecological engineering target through high-resolution satellite image is arduous due to the unique topography and complicated spatial pattern on the Loess Plateau of China. As a result, enhancing classification accuracy is a huge challenge to high-resolution image processing techniques. Image processing techniques have a definitive effect on image properties and the selection of different parameters may change the final classification accuracy during post-classification processing. The common method of eliminating noise and smoothing image is majority filtering. However, the filter function may modify the original classified image and the final accuracy. The aim of this study is to develop an efficient and accurate post-processing technique for acquiring information of soil and water conservation engineering, on the Loess Plateau of China, using SPOT image with 2.5 m resolution. We argue that it is vital to optimize satellite image filtering parameters for special areas and purposes, which focus on monitoring ecological construction projects. We want to know how image filtering influences final classified results and which filtering kernel is optimum. The study design used a series of window sizes to filter the original classified image, and then assess the accuracy of each output map and image quality. We measured the relationship between filtering window size and classification accuracy, and optimized the post-processing techniques of SPOT5 satellite images. We conclude that (1) smoothing with the majority filter is sensitive to the information accuracy of soil and water conservation engineering, and (2) for SPOT5 2.5 m image, the 5×5 pixel majority filter is most suitable kernel for extracting information of ecological construction sites in the Loess Plateau of China.

A database framework of digital forestry towards sustainable forestry development in China

Six forestry scientific and technological projects being actualized in China were the implementations of ecological construction and security, development of forestry biological technique and fine variety cultivation, protection and utilization of forest biological germplasm resources, development of forestry bio-industry and digital forestry, and construction of forestry innovation ability. Among them, digital forestry was an effective measure to improve the ability of forestry innovation, to realize resources sharing, and to develop sustainable forestry. Spatial database of digital forestry should be constructed according to the criteria and index system of forest sustainable management. Based on analyzing the status and advances of China’s digital forestry construction, a database framework of digital forestry towards sustainable forestry development was studied and established preparatorily. The database was divided into four layers as theory layer, system layer, status layer, and parameter layer. It was concluded that during the process of digital forestry platform construction, the relative social, economic, and politic data should be considered and collected, which meant that the database should represent not only the current forestry development, but also the social, politic, and economic situations. Constructing China’s digital forestry information platform under full utilization of idea and index system for sustainable forest management was urgent and important.