Statistics of GPS ionospheric scintillation and irregularities over polar regions at solar minimum

A statistical study of the occurrence characteristic of GPS ionospheric scintillation and irregularity in the polar latitude is presented. These measurements were made at Ny-Alesund, Svalbard [78.9°N, 11.9°E; 75.8°N corrected geomagnetic latitude (CGMLat)] and Larsemann Hills, East Antarctica (69.4°S, 76.4°E; 74.6°S CGMLat) during 2007–2008. It is found that the GPS phase scintillation and irregularity activity mainly takes place in the months 10, 11 and 12 at Ny-Alesund, and in the months 5, 6 at Larsemann Hills. The seasonal pattern of phase scintillation with respect to the station indicates that the GPS phase scintillation occurrence is a local winter phenomenon, which shows consistent results with past studies of 250 MHz satellite beacon measurements. The occurrence rates of GPS amplitude scintillation at the two stations are below 1%. A comparison with the interplanetary magnetic field (IMF) B _y and B _z components shows that the phase scintillation occurrence level is higher during the period from later afternoon to sunset (16–19 h) at Ny-Alesund, and from sunset to pre-midnight (18–23 h) at Larsemann Hills for negative IMF components. The findings seem to indicate that the dependence of scintillation and irregularity occurrence on geomagnetic activity appears to be associated with the magnetic local time (MLT).     

A MATLAB-based Kriged Kalman Filter software for interpolating missing data in GNSS coordinate time series

GNSS coordinate time series data for permanent reference stations often suffer from random, or even continuous, missing data. Missing data interpolation is necessary due to the fact that some data processing methods require evenly spaced data. Traditional missing data interpolation methods usually use single point time series, without considering spatial correlations between points. We present a MATLAB software for dynamic spatiotemporal interpolation of GNSS missing data based on the Kriged Kalman Filter model. With the graphical user interface, users can load source GNSS data, set parameters, view the interpolated series and save the final results. The SCIGN GPS data indicate that the software is an effective tool for GNSS coordinate time series missing data interpolation.     

Study on Sampling Rule and Simplification of LiDAR Point Cloud Based on Terrain Complexity

It is difficult to obtain digital elevation model (DEM) in the mountainous regions. As an emerging technology, Light Detection and Ranging (LiDAR) is an enabling technology. However, the amount of points obtained by LiDAR is huge. When processing LiDAR point cloud, huge data will lead to a rapid decline in data processing speed, so it is necessary to thin LiDAR point cloud. In this paper, a new terrain sampling rule had been built based on the integrated terrain complexity, and then based on the rule a LiDAR point cloud simplification method, which was referred as to TCthin, had been proposed. The TCthin method was evaluated by experiments in which XUthin and Lasthin were selected as the TCthin’s comparative methods. The TCthin’s simplification degree was estimated by the simplification rate value, and the TCthin’s simplification quality was evaluated by Root Mean Square Deviation. The experimental results show that the TCthin method can thin LiDAR point cloud effectively and improve the simplification quality, and at 5 m, 10 m, 30 m scale levels, the TCthin method has a good applicability in the areas with different terrain complexity. This study has theoretical and practical value in sampling theory, thinning LiDAR point cloud, building high-precision DEM and so on.     

基于TerrSolid对机载雷达DEM重提取方法研究

DEM的提取是激光雷达数据采集的重要用途之一,但由于目前算法的局限性,无法高精度地自动分类,如何在算法分类的基础上重新进行人工分类,以一定的原则和标准进行重提取从而得到更高精度的DEM,仍然是专业领域的一大难题。本文对某.LAS数据重提取,极大提高了其DEM的精度,为今后相关单位和个人使用TerrSolid软件对机载雷达DEM重提取提供一些经验。     

Patterns of carbon sequestration in forests of western ghats and study of applicability of remote sensing in generating carbon credits through afforestation/reforestation

Satellite remote sensing is a proven tool for mapping landuse patterns and estimating vegetation biomass/carbon. Present study aims at estimating the potential of forests of Radhanagari WLS (Western Ghats, India) to sequester the atmospheric carbon-di-oxide, using ground based observations coupled with satellite remote sensing. The study area was stratified for dominant forest types based on the structure and composition of vegetation and elevation variations. Permanent sample plots were laid down in these homogeneous vegetation strata (HVS) to make different observations during time 1 and time 2. Carbon sequestration by plantations was also studied and compared with natural forests. Species and area-specific biomass equations were used for estimating carbon pool and sequestration. Among natural forests ‘mixed moist deciduous’ forests exhibited highest sequestration rate (8%), whereas, plantation as obvious had a comparatively higher sequestration rate than natural forests (20.27%). Total carbon sequestration by forests of the Radhanagari WLS between 2004 and 2006 is 78742.09 tons. Eligible land for reforestation activity under clean development mechanism (CDM) of Kyoto Protocol was identified using satellite remote sensing using 1989 and 2005 datasets and it was observed that the potential land that can be used for reforestation activity is 10080 ha.     

全要素地形图作为背景在规划业务系统中的应用与实现

全要素地形图中的地理信息准确、规范、丰富,地形图比例尺与规划深度和出图比例相一致,而且精度能满足规划要求。打散入库后的全要素地形图和规划审批人员习惯的"蓝晒图"效果一致,且更新及时、方便,具有较强的现势性,在规划编制、规划审批等各个业务环节中起到了重要作用。本文详细阐述了全要素地形图的处理、转换、入库和更新过程,并对过程中应注意的问题提出了自己的意见和建议。     

Integrating terrain and vegetation indices for identifying potential soil erosion risk area

The present paper offers an innovative method to monitor the change in soil erosion potential by integrating terrain and vegetation indices derived from remote sensing data. Three terrain indices namely, topographic wetness index (TWI), stream power index (SPI) and slope length factor (LS), were derived from the digital elevation model. Normalized vegetation index (NDVI) was derived for the year 1988 and 2004 using remote sensing images. K-mean clustering was performed on staked indices to categorize the study area into four soil erosion potential classes. The validation of derived erosion potential map using USLE model showed a good agreement. Results indicated that there was a significant change in the erosion potential of the watershed and a gradual shifting of lower erosion potential class to next higher erosion potential class over the study period.