Errors related to the automatized satellite-based change detection of boreal forests in Finland

The majority of the boreal forests in Finland are regularly thinned or clear-cut, and these actions are regulated by the Forest Act. To generate a near-real time tool for monitoring management actions, an automatic change detection modelling chain was developed using Sentinel-2 satellite images. In this paper, we focus mainly on the error evaluation of this automatized workflow to understand and mitigate incorrect change detections. Validation material related to clear-cut, thinned and unchanged areas was collected by visual evaluation of VHR images, which provided a feasible and relatively accurate way of evaluating forest characteristics without a need for prohibitively expensive fieldwork. This validation data was then compared to model predictions classified in similar change categories. The results indicate that clear-cuts can be distinguished very reliably, but thinned stands exhibit more variation. For thinned stands, coverage of broadleaved trees and detections from certain single dates were found to correlate with the success of the modelling results. In our understanding, this relates mainly to image quality regarding haziness and translucent clouds. However, if the growing season is short and cloudiness frequent, there is a clear trade-off between the availability of good-quality images and their preferred annual span. Gaining optimal results therefore depends both on the targeted change types, and the requirements of the mapping frequency.     

Multiple factors influence the consistency of cropland datasets in Africa

Accurate geo-information of cropland is critical for food security strategy development and grain production management, especially in Africa continent where most countries are food-insecure. Over the past decades, a series of African cropland maps have been derived from remotely-sensed data, existing comparison studies have shown that inconsistencies with statistics and discrepancies among these products are considerable. Yet, there is a knowledge gap about the factors that influence their consistency. The aim of this study is thus to estimate the consistency of five widely-used cropland datasets (MODIS Collection 5, GlobCover 2009, GlobeLand30, CCI-LC 2010, and Unified Cropland Layer) in Africa, and to explore the effects of several limiting factors (landscape fragmentation, climate and agricultural management) on spatial consistency. The results show that total cropland area for Africa derived from GlobeLand30 has the best fitness with FAO statistics, followed by MODIS Collection 5. GlobCover 2009, CCI-LC 2010, and Unified Cropland Layer have poor performances as indicated by larger deviations from statistics. In terms of spatial consistency, disagreement is about 37.9 % at continental scale, and the disparate proportion even exceeds 50 % in approximately 1/3 of the countries at national scale. We further found that there is a strong and significant correlation between spatial agreement and cropland fragmentation, suggesting that regions with higher landscape fragmentation generally have larger disparities. It is also noticed that places with better consistency are mainly distributed in regions with favorable natural environments and sufficient agricultural management such as well-developed irrigated technology. Proportions of complete agreement are thus located in favorable climate zones including Hot-summer Mediterranean climate (Csa), Subtropical highland climate (Cwb), and Temperate Mediterranean climate (Csb). The level of complete agreement keeps rising as the proportion of irrigated cropland increases. Spatial agreement among these datasets has the most significant relationship with cropland fragmentation, and a relatively small association with irrigation area, followed by climate conditions. These results can provide some insights into understanding how different factors influence the consistency of cropland datasets, and making an appropriate selection when using these datasets in different regions. We suggest that future cropland mapping activities should put more effort in those regions with significant disagreement in Sub-Saharan Africa.     

绝对重力测量在云南和北京观测到的重力时间变化

中国地震局地震研究所与德国汉诺威大学大地测量研究所于１９９０,１９９２和１９９５年共同在滇西地震预报实验场和昆明进行了３次绝对重力测量。此外,１９９０,１９９２年在北京,１９９０年在武汉也进行了绝对重力测量。通过对各次绝对测量的结果进行比较,并与其它重力仪获得的数据的对比估算了它们的可靠性,进而详细地讨论了各个测点的重力变化。     

近景摄影测量监测网的建立及其数据处理

介绍为采用近景摄影测量的方法进行储气罐容积测定与形变监测,而建立的监测网的精度要求,布网方法,观测与数据处理等问题。     

基于分形理论的面积精度估算

分形理论是研究非线性系统的重要工具。文中首先讨论栅格数据中面积精度估算的一般公式,然后基于分形理论进行了分析与研究３,选用了等面积的圆,正方形,复杂多边形和ｋｏｃｈ分形雪花图案四种图形进行了计算分析比较,得出了一些有益的结论。     

全站仪中的新技术在高层建筑垂直度监测中的应用

本文将全站仪中的新技术运用到垂直度监测中,提出了一种新的高大建筑物垂直度监测方法,并分析了其监测精度。理论和实际工程监测结果表明：该方法具有测量原理简单明了、精度高、可操作性强和灵活、方便、实用的特点,可以在高层建筑物的垂直度监测中推广应用。     

Linking socioeconomic classes and land cover data in Lima,Peru: Assessment through the application of remote sensing and GIS

The spatial differentiation of socioeconomic classes in a city can deliver insight into the nexus of urban development and the environment. The purpose of this paper is to identify poor and rich regions in large cities according to the predominant physical characteristics of the regions. Meaningful spatial information from urban systems can be derived using remote sensing and GIS tools, especially in large difficult-to-manage cities where the dynamics of development results in rapid changes to urban patterns. We use here very high resolution imagery data for the identification of homogeneous socioeconomic zones in a city. We formulate the categorization task as a GIS analysis of an image classified with conventional techniques. Experiments are conducted using a QuickBird image of a study area in Lima, Peru. We provide accuracy assessment of results compared to ground truth data. Results show an approximated allocation of socioeconomic zones within Lima. The methodology described could also be applied to other urban centers, particularly large cities of Latin America, which have characteristics similar to those of the study area.     

自动气象站的动态试验及其测量准确度

计算了自动气象站动态对比试验结果的相关系数和差值误差区间，从而论证了对比试验的可信度。提出了计算自动气象站测量结果的标准差、合格率、准确度的方法。并用隐含周期分析与自相关模型得出了自动气象站的某些测量结果优于人工观测结果的结论。     

运用DEM剖析土地利用空间数据转换的尺度效应

通过对不同土地利用类型进行尺度转换,定量分析了不同高程地区土地利用类型的精度损失趋势,同时结合景观格局指数,探讨了高程影响下数据转换中的尺度效应。研究表明,土地利用类型和高程之间存在尺度依赖性;依据原始矢量数据计算的土地利用景观格局指数,可以在一定程度上揭示精度损失变化特征的规律和成因。