Mapping fine‐scale urban housing prices by fusing remotely sensed imagery and social media data

The accurate mapping of urban housing prices at a fine scale is essential to policymaking and urban studies, such as adjusting economic factors and determining reasonable levels of residential subsidies. Previous studies focus mainly on housing price analysis at a macro scale, without fine‐scale study due to a lack of available data and effective models. By integrating a convolutional neural network for united mining (UMCNN) and random forest (RF), this study proposes an effective deep‐learning‐based framework for fusing multi‐source geospatial data, including high spatial resolution (HSR) remotely sensed imagery and several types of social media data, and maps urban housing prices at a very fine scale. With the collected housing price data from China's biggest online real estate market, we produced the spatial distribution of housing prices at a spatial resolution of 5 m in Shenzhen, China. By comparing with eight other multi‐source data mining techniques, the UMCNN obtained the highest housing price simulation accuracy (Pearson R = 0.922, OA = 85.82%). The results also demonstrated a complex spatial heterogeneity inside Shenzhen's housing price distribution. In future studies, we will work continuously on housing price policymaking and residential issues by including additional sources of spatial data.     

Drought prediction using in situ and remote sensing products with SVM over the Xiang River Basin,China

Natural Hazards - Droughts have caused many damages in many countries and might be aggravated around the world. Therefore, it is urgent to predict and monitor drought accurately. Soil moisture and...     

Destressing Mechanics Effect of Surrounding Rock Induced by Blasting Precondition at Deep Drift Development

Geotechnical and Geological Engineering - Using a detailed modeling simulation technology, a mechanics simulation model was constructed, including multiple development rounds, stress relief holes...     

Heat Islands of Small Towns and Villages in Moscow Region

Doklady Earth Sciences - Surface urban heat island, which are thermal anomalies in the field of surface temperatures, have been studied for the first time for different towns and villages of Moscow...     

New Data on the Chronostratigraphy of the Upper Pleistocene Loess–Soil Series in Southwestern Siberia

Doklady Earth Sciences - We have analyzed the modern status of the chronostratigraphic differentiation of the loess–paleosoil series in southwestern Siberia and the results of luminescence...     

浙中一次多风暴类型强对流天气成因及多普勒雷达特征

利用常规资料、区域自动站加密资料、探空资料、GFS 0.25°×0.25°逐6h的分析场数据和SB多普勒天气雷达资料对2018年5月18日发生在浙中地区的一次强对流天气过程进行分析。结果表明:此次过程产生了脉冲风暴、中等到强多单体风暴和飑线这3种风暴类型,分别出现冰雹、大范围强降水和雷雨大风等强天气。3种风暴的雷达回波在回波形态、强度、垂直结构、平均径向速度、垂直累积液态水含量VIL等特征如下:①脉冲风暴呈块状,初始回波高度在6～9km,强回波所在高度在-10℃等温线附近,强回波值达60dBz以上,VIL值出现跃升且最大值在50kg·m-2以上,冰雹出现在反射率因子核和VIL值迅速下降之后;②中等到强多单体风暴呈带状,大降水效率和"列车效应"是发生大范围强降水的主要原因,雷雨大风天气则与反射率因子核迅速下降、MARC、低层强辐散区有关;③飑线呈弓形回波形态,移速快,引起了大范围的雷雨大风天气。此次过程影响系统多,天气复杂,存在较大预报难点,在短时临近预报技术研究上有重要借鉴意义。     

浙江省涂膜柑橘贮藏期烂果风险区划及历史变化特征

为了了解浙江省涂膜柑橘贮藏期烂果风险的时空分布规律及其近60年的变化特征,利用1961—2016年常规站日气象观测资料,以涂膜柑橘贮藏腐烂阈值及各时段发生的频率为区划指标,采用距离权重反比法(IDW,Inverse Distance Weighted),开展了柑橘贮藏期烂果时间阈值风险区划,并分析了它的年代际变化。结果表明:2006年以后,浙江涂膜柑橘贮藏期烂果出现的时间越来越早,且从西南地区到东北地区柑橘贮藏期烂果出现时间逐渐推迟。最晚时间西南部地区在3月上旬,中西部地区和沿海南部地区在3月中旬,其他地区在3月下旬。21世纪10年代前6年与20世纪60年代相比较,丽水涂膜柑橘贮藏最早烂果时间从3月第1候提前到2月第4候,而最晚时间从4月第4候提前到第1候。区划结果将为橘农合理安排柑橘贮存、及时进行贩销提供参考和科学依据,从而减少对柑橘贮藏品质的影响。     

Synthetic information prediction system for crisis mine based on GIS

Reserves of some kinds of the crisis mines will be lack now or from now on, because of lacking seriously reserves of mineral resources and the crisis of exploring bases in support. So that it is urgent to predict, appraise, development and utilize the replaceable resources of the crisis mines. The mineral resources prediction software system of synthetic information is intelligent GIS which is used to quantitative prediction of large-scale synthetic information mineral target. It takes the geological body and the mineral resource body as a unit. And it analyzes the ore deposit genesis and metallotect, knows the spatial distribution laws of the ore deposit and ore body, and establish the prospecting model based on the concept of establishing the three-dimensional space of a mine. This paper will primarily discuss some important problems as follows: the secondary development of various kinds of data(including geology, geophysical prospecting, geochemical prospecting and remote sensing, etc); process synthetically and establish the synthetic information interpretative map base; correspond prospecting model with synthetic information of ore deposit; divided into statistical units of metallogenic information synthetic anomalies based on the synthetic information anomalies of ore control, then research the metallogenic information variable of unit synthetically and make quantitative prediction according to choose the quantitative prediction math model which is suitable to the demands of large-scale precision; at last, finish the target area optimization of ore deposit (body).     

华北构造区强震短期水氡异常空间图像演化及其前兆判别标志的研究

开展了水氡前兆异常参数提取方法的研究, 并以其提取的结果为输入, 对1985～2002年华北水氡异常参数分布做了全时空扫描, 继而将全部图像与华北地区构造活动性评估的数字化图像进行了叠加, 实现了水氡异常动态扫描与区域构造活动性背景的结合。 在此基础上, 1985年以来华北地区5级以上地震前的水氡短期图像演化情况做了全面分析, 提取出判别异常区的指标以及地震短期异常演化特征, 并提出了华北地区强震前水氡短期前兆的判别标志。     

基于GIS技术的大地电磁测深数据库系统设计与实现

大地电磁(Megnetotelluric,简称MT)测深数据子库是中国岩石圈三维结构数据库所属子库之一。本文阐述了结合GIS技术开发大地电磁测深数据库管理系统的必要性。讨论了新型大地电磁测深数据库及基于GIS平台的数据库管理系统的总体设计思想。在分析原ACCESS大地电磁测深数据库所存在问题的基础上,建立新的MT数据库实体-关系模型,并进一步把原有的MT数据库改造为SQL Server 2000数据库;同时,开发了基于GIS的MT数据库管理系统。本文介绍了基于GIS的MT数据库管理系统所具有的功能。