Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

Spatio-Temporal Change of Dispersal Areas of Greater Kudu (Tragelaphus strepsiceros) in Lake Bogoria Landscape, Kenya

Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last four decades. Greater Kudu (Tragelaphus strepsiceros) is endemic to Lake Bogoria landscape in Baringo County and constitutes a major tourist attraction for the region necessitating use of its photo on the County’s logo and thus a flagship species. Tourism plays a central role in Baringo County’s economy and is a major source of potential growth and employment creation. The study was carried out to assess spatio-temporal change of dispersal areas of Greater Kudu (GK) in Lake Bogoria landscape in the last four years for enhanced adaptive management and improved livelihoods. GK population distribution primary data collected in December 2022 and secondary data acquired from Lake Bogoria National Game Reserve (LBNGR) for 2019 and 2020 were digitized using in a Geographic Information System (GIS). Measures of dispersion and point pattern analysis (PPA) were used to analyze dispersal of GK population using GIS. Spatio-temporal change of GK dispersal in LBNR was evident thus the null hypothesis was rejected. It is recommended that anthropogenic activities contributing to GK’s habitat degradation be curbed by providing alternative livelihood sources and promoting community adoption of sustainable technologies for improved livelihoods.

Relationship between spatio-temporal evolution of soil pH and geological environment/surface cover in the eastern Nenjiang River Basin of Northeast China during the past 30 years

To illuminate the spatio-temporal variation characteristics and geochemical driving mechanism of soil pH in the Nenjiang River Basin,the National Multi-objective Regional Geochemical Survey data of topsoil,the Second National Soil Survey data and Normalized Difference Vegetation Index(NDVI)were analyzed.The areas of neutral and alkaline soil decreased by 21100 km^(2)and 30500 km^(2),respectively,while that of strongly alkaline,extremely alkaline,and strongly acidic soil increased by 19600 km^(2),18200 km^(2),and 15500 km^(2),respectively,during the past 30 years.NDVI decreased with the increase of soil pH when soil pH>8.0,and it was reversed when soil pH<5.0.There were significant differences in soil pH with various surface cover types,which showed an ascending order:Arbor<reed<maize<rice<high and medium-covered meadow<low-covered meadow<Puccinellia.The weathering products of minerals rich in K_(2)O,Na_(2)O,CaO,and MgO entered into the low plain and were enriched in different parts by water transportation and lake deposition,while Fe and Al remained in the low hilly areas,which was the geochemical driving mechanism.The results of this study will provide scientific basis for making scientific and rational decisions on soil acidification and salinization.

Leveraging Transfer Learning for Spatio-Temporal Human Activity Recognition from Video Sequences

Human Activity Recognition(HAR)is an active research area due to its applications in pervasive computing,human-computer interaction,artificial intelligence,health care,and social sciences.Moreover,dynamic environments and anthropometric differences between individuals make it harder to recognize actions.This study focused on human activity in video sequences acquired with an RGB camera because of its vast range of real-world applications.It uses two-stream ConvNet to extract spatial and temporal information and proposes a fine-tuned deep neural network.Moreover,the transfer learning paradigm is adopted to extract varied and fixed frames while reusing object identification information.Six state-of-the-art pre-trained models are exploited to find the best model for spatial feature extraction.For temporal sequence,this study uses dense optical flow following the two-stream ConvNet and Bidirectional Long Short TermMemory(BiLSTM)to capture longtermdependencies.Two state-of-the-art datasets,UCF101 and HMDB51,are used for evaluation purposes.In addition,seven state-of-the-art optimizers are used to fine-tune the proposed network parameters.Furthermore,this study utilizes an ensemble mechanism to aggregate spatial-temporal features using a four-stream Convolutional Neural Network(CNN),where two streams use RGB data.In contrast,the other uses optical flow images.Finally,the proposed ensemble approach using max hard voting outperforms state-ofthe-art methods with 96.30%and 90.07%accuracies on the UCF101 and HMDB51 datasets.

Dynamic Spatio-Temporal Modeling in Disease Mapping

Spatio-temporal models are valuable tools for disease mapping and understanding the geographical distribution of diseases and temporal dynamics. Spatio-temporal models have been proven empirically to be very complex and this complexity has led many to oversimply and model the spatial and temporal dependencies independently. Unlike common practice, this study formulated a new spatio-temporal model in a Bayesian hierarchical framework that accounts for spatial and temporal dependencies jointly. The spatial and temporal dependencies were dynamically modelled via the matern exponential covariance function. The temporal aspect was captured by the parameters of the exponential with a first-order autoregressive structure. Inferences about the parameters were obtained via Markov Chain Monte Carlo (MCMC) techniques and the spatio-temporal maps were obtained by mapping stable posterior means from the specific location and time from the best model that includes the significant risk factors. The model formulated was fitted to both simulation data and Kenya meningitis incidence data from 2013 to 2019 along with two covariates;Gross County Product (GCP) and average rainfall. The study found that both average rainfall and GCP had a significant positive association with meningitis occurrence. Also, regarding geographical distribution, the spatio-temporal maps showed that meningitis is not evenly distributed across the country as some counties reported a high number of cases compared with other counties.

Spatio-Temporal Analysis of Drought in the North-Eastern Coastal Region of Vietnam Using the Standardized Precipitation Index (SPI)

Spatio-temporal analysis of drought provides valuable information for drought management and damage mitigation. In this study, the Standardized Precipitation Index at the time scale of 6 months (SPI-6) is selected to reflect drought conditions in the North-Eastern coastal region of Vietnam. The drought events and their characteristics from 1981 to 2019 are detected at 9 meteorological stations and 10 Chirps rainfall stations. The spatio-temporal variation of drought in the study region is analyzed on the basis of the number, duration, severity, intensity, and peak of the detected drought events at the 19 stations. The results show that from 1981 to 2019 the drought events mainly occurred with 1-season duration and moderate intensity and peak. The number, duration, severity, and peak of the drought events were the greatest in the period 2001-2010 and were the smallest in the period 2011-2019. Among the 19 stations, the drought duration tends to decrease at 11 stations, increase at 7 stations, and has a slight variant at 1 station;the drought severity tends to decrease at 14 stations, increase at 4 stations, and has not a significant trend at 1 station;the drought intensity tends to decrease at 17 stations, increase at 1 station, and has a slight variant at 1 station;and the drought peak tends to decrease at 18 stations and increase at 1 station.

“stppSim”: A Novel Analytical Tool for Creating Synthetic Spatio-Temporal Point Data

In crime science, understanding the dynamics and interactions between crime events is crucial for comprehending the underlying factors that drive their occurrences. Nonetheless, gaining access to detailed spatiotemporal crime records from law enforcement faces significant challenges due to confidentiality concerns. In response to these challenges, this paper introduces an innovative analytical tool named “stppSim,” designed to synthesize fine-grained spatiotemporal point records while safeguarding the privacy of individual locations. By utilizing the open-source R platform, this tool ensures easy accessibility for researchers, facilitating download, re-use, and potential advancements in various research domains beyond crime science.

Spatio-temporal GIS和GPS优化集成在城市交通管制中的应用研究

本文基于城市交通日益恶化现状和3S集成的迅速发展,表述了Spatio-temporal GIS的定义、时空路径、人类活动的四种时空关系及其坐标系统模型的建立;并根据GPS空间定位、空间导航的原理和模型,将Spatio-temporal GIS和GPS的功能优化集成,阐述了其对城市交通信息的收集、分析、显示等功能;最后论述了Spatio-temporal GIS和GPS的集成对城市交通预警、报警、协调等管制作用。

Characteristics,Processes,and Causes of the Spatio-temporal Variabilities of the East Asian Monsoon System

Recent advances in the study of the characteristics, processes, and causes of spatio-temporal variabilities of the East Asian monsoon （EAM） system are reviewed in this paper. The understanding of the EAM system has improved in many aspects： the basic characteristics of horizontal and vertical structures, the annual cycle of the East Asian summer monsoon （EASM） system and the East Asian winter monsoon （EAWM） system, the characteristics of the spatio-temporal variabilities of the EASM system and the EAWM system, and especially the multiple modes of the EAM system and their spatio-temporal variabilities. Some new results have also been achieved in understanding the atmosphere-ocean interaction and atmosphere-land interaction processes that affect the variability of the EAM system. Based on recent studies, the EAM system can be seen as more than a circulation system, it can be viewed as an atmosphere-ocean-land coupled system, namely, the EAM climate system. In addition, further progress has been made in diagnosing the internal physical mechanisms of EAM climate system variability, especially regarding the characteristics and properties of the East Asia-Pacific （EAP） teleconnection over East Asia and the North Pacific, the ＂Silk Road＂ teleconnection along the westerly jet stream in the upper troposphere over the Asian continent, and the dynamical effects of quasi-stationary planetary wave activity on EAM system variability. At the end of the paper, some scientific problems regarding understanding the EAM system variability are proposed for further study.

Spatio-Temporal Changes in the Rice Planting Area and Their Relationship to Climate Change in Northeast China: A Model-Based Analysis

Rice is one of the most important grain crops in Northeast China （NEC） and its cultivation is sensitive to climate change. This study aimed to explore the spatio-temporal changes in the NEC rice planting area over the period of 1980-2010 and to analyze their relationship to climate change. To do so, the CLUE-S （conversion of land use and its effects at small region extent） model was ifrst updated and used to simulate dynamic changes in the rice planting area in NEC to understand spatio-temporal change trends during three periods： 1980-1990, 1990-2000 and 2000-2010. The changing results in individual periods were then linked to climatic variables to investigate the climatic drivers of these changes. Results showed that the NEC rice planting area expanded quickly and increased by nearly 4.5 times during 1980-2010. The concentration of newly planted rice areas in NEC constantly moved northward and the changes were strongly dependent on latitude. This conifrmed that climate change, increases in temperature in particular, greatly inlfuenced the shift in the rice planting area. The shift in the north limit of the NEC rice planting area generally followed a 1＆#176;C isoline migration pattern, but with an obvious time-lag effect. These ifndings can help policy makers and crop producers take proper adaptation measures even when exposed to the global warming situation in NEC.

Spatio-Temporal Changes of Soil Salinity in Arid Areas of South Xinjiang Using Electromagnetic Induction

The aim of this paper was to research the spatio-temporal changes in total soluble salt content （TS） in a typical arid region of South Xinjiang, China, where the climate is arid and soil salinization happens easily. The total soluble salt content was interpreted by measurements made in the horizontal mode with EM38 and EM31. The electromagnetic induction （EM） surveys were made three times with the apparent soil electrical conductivity （ECa） measurements taken at 3 873 locations in Nov. 2008, 4 807 locations in Apr. 2009 and 6 324 locations in Nov. 2009, respectively. For interpreting the ECa measurements into total soluble salt content, calibtion sites were needed for EM survey of each time, e.g., 66 sites were selected in Nov. 2008 to measure ECa, and soils-core samples were taken by different depth layers of 0-10, 10-20 and 20-40 cm at the same time. On every time duplicate samples were taken at five sites to allevaite the local-scale variability, and soil temperatures in different layers through the profiles were also measured. Factors including TS, pH, water content, bulk density were analyzed by lab experiments. ECa calibration equations were obtained by linear regression analysis, which indicated that soil salinity was one primary concern to ECa with a determination coefficient of 0.792 in 0-10 cm layer, 0.711 in 10-20 cm layer and 0.544 in 20-40 cm layer, respectively. The maps of spatial distribution were predicted by Kriging interpolation, which showed that the high soil salinity was located near the drainage canal, which validated the trend effect caused by the irrigation canal and the drainage canal. And by comparing the soil salinity in different layers, the soluble salt accumulated to the top soil surface only in the area where the soil salinization was serious, and in the other areas, the soil salinity trended to increase from the top soil surface to 40 cm depth. Temporal changes showed that the soil salinity in November was higher than that in April, and the soil salinization trended to aggravate, especially in the top soil layer of 0-10 cm.

Spatio-temporal Characteristics and Geographical Determinants of Air Quality in Cities at the Prefecture Level and Above in China

In recent years, the large scale and frequency of severe air pollution in China has become an important consideration in the construction of livable cities and the physical and mental health of urban residents. Based on the 2016-year urban air quality index(AQI) data published by the Ministry of Environmental Protection of China, this study analyzed the spatial and temporal characteristics of air quality and its influencing factors in 338 urban units nationwide. The analysis provides an effective scientific basis for formulating national air pollution control measures. Four key results are shown. 1) Generally, air quality in the 338 cities is poor, and the average annual values for urban AQI and air pollution in 2016 were 79.58% and 21.22%, respectively. 2) The air quality index presents seasonal changes, with winter > spring > autumn > summer and a u-shaped trend. 3) The spatial distribution of the urban air quality index shows clear north-south characteristic differences and a spatial agglomeration effect; the high value area of air pollution is mainly concentrated in the North China Plain and Xinjiang Uygur Autonomous Region. 4) An evaluation of the spatial econometric model shows that differences in urban air quality are due to social, economic, and natural factors.

Spatio-temporal Evolution of Marine Fishery Industry Ecosystem Vulnerability in the Bohai Rim Region

The building of the ocean power strategy and the implementation of the blue agriculture plan urgently need to strengthen the sustainable development of marine fishery.Taking vulnerability as the starting point, this paper constructs the vulnerability index system of marine fishery industry ecosystem from the aspects of sensitivity and response capacity, and combines the entropy method with the Topsis to comprehensively analyze the spatio-temporal evolution characteristics of vulnerability of marine fishery industry ecosystem in the Bohai Rim Region from 2001 to 2015.The results show that: 1) In the time dimension, from 2001 to 2015, the vulnerability of the marine fishery industry ecosystem in the Bohai Rim Region shows a fluctuant and degressive trend;2) In the spatial dimension, the spatial distribution of the marine fishery industry ecosystem vulnerability in the Bohai Rim Region presents the gradient characteristics which shows high vulnerability in the east and low vulnerability in the west.According to the evolution track of the system’s vulnerability level, the vulnerability of the marine fishery industry ecosystem is divided into ‘declining’ and ‘stable’ types of evolutionary structures;3) The development of marine fishery in the Bohai Rim Region needs to be derived from the marine fishery’s ecological environment and the industrial development mode and structure, which can improve the marine environment remediation efforts, optimize the marine fishery industry structure, vigorously focus on pelagic fishery, and enhance the introduction of marine fishery’s science and technology talents, etc.Then, the marine fishery’s development in the Bohai Rim Region will be moving in the green, circular and sustainable direction.

Spatio-temporal patterns of drought in North Xinjiang, China, 1961–2012 based on meteorological drought index

Drought, which is one of the most frequently occurring severe hazards with long time scales and cov- ering wide geographical areas, is a natural phenomenon resulting in significant economic losses in agriculture and industry. Drought is caused by an imbalance between the inputs of and the demand for water which is insufficient to meet the demands of human activities and the eco-environment. As a major arid and semi-arid area and an important agricultural region in Northwest China, North Xinjiang （NX） shows great vulnerability to drought. In this paper, the characteristics of inter-annual and seasonal drought were analyzed in terms of drought occurrence and drought coverage, by using the composite index of meteorological drought and the data of daily precipitation, air temperature, wind speed, relative humidity and sunshine duration from 38 meteorological stations during the period 1961-2012. Trend analysis, wavelet analysis and empirical orthogonal function were also applied to investigate change trend, period and regional characteristics, respectively. In NX, annual and seasonal drought occurrence and drought coverage all showed a decreasing trend that was most significant in winter （with rates of-0.26 month/10a and -15.46%, respectively）, and drought occurrence in spring and summer were more frequent than that in autumn and winter. Spatially, drought was severe in eastern regions but mild in western regions of NX. Annual and seasonal drought occurrence at 38 meteorological stations displayed decreasing trends and were most significant in ＂Shi- hezi-Urumqi-Changji＂, which can help to alleviate severe drought hazards for local agricultural production and improve human livelihood. NX can be approximately classified into three sub-regions （severe drought region, moder- ate drought region and mild drought region）, which were calculated from annual drought frequencies. The cross wavelet transform suggested that SOl （Southern Oscillation Index）, AOI （Arctic Oscillation Index）, AAOI （Antarctic Oscillation Index）, PAOI （Pacific/North American Oscillation Index） and NAOI （North Atlantic Oscillation Index） have significant correlation with the variation of drought occurrence in NX. To prevent and mitigate the occurrence of drought disasters in NX, agricultural and government managers should pay more attention to those drought events that occur in spring and summer.

Spatio-temporal evolution of ecologically-sustainable land use in China's Loess Plateau and detection of its influencing factors

Ecological land(Eco-land) is a basic resource for human beings to survive, and eco-land use is a strategy, a way to manage the land resource. So, ecologically-sustainable land use is essential for human beings to survive. This paper investigates the spatiotemporal characteristics and mechanisms of urban-rural eco-land using a new and innovative integration way based on eco-land change data in China's Loess Plateau(LP) prefecture level cities and explores factors of eco-land change. The spatial difference characteristic of eco-land among different level cities in the LP is that: small cities > big cities > middle cities. From 2009 to 2016, the eco-land in the LP from the perspective of urban-rural areas has changed significantly. Significant differences of urban-rural eco-land were identified among various urban growth types, and all the cities in the LP were further classified into four types based on eco-land change trend, with type A and B cities identified as the vital zone and major zone. Taking the eco-fragile region Loess Plateau(LP) as an example, our results demonstrated that the migrants to cities in LP could relieve ecological pressures and promote restoration of ecological vegetation. We have demonstrated that urbanization and the influence of government policy can be discerned through the quantification of the spatial-temporal change of eco-land and suggest that combining both urban and rural eco-land can support more effective land use decisions and provide theoretical basis for the practical application of urban planning, policy-making and sustainable development. What's more, governments should strive to population mobility and restore vegetation to sustain this fragile ecological environment.

Spatio-temporal Variability of Northern Hemipheric Sea Level Pressure(SLP)and Precipitation over the Mid-to-Low Reaches of the Yangtze River

The spatio-temporal variability of Northern Hemisphere Sea Level Pressure （SLP） and precipitation over the mid-to-low reaches of the Yangtze River （PMLY） is analyzed jointly using the multi-taper/singular value decomposition method （MTM-SVD）. Statistically significant narrow frequency bands are obtained from the local fractional variance （LFV） spectrum. Significant interdecadal （i.e., 16-to-18-year periods） and interannual （i.e., 3-to-6-year periods） signals are identified. Moreover, a significant quasi-biennial signal is identified but only for PMLY data. The spatial joint evolution of patterns obtained for peaks in the LFV spectrum sheds light on relationships between SLP and PMLY： the Arctic Oscillation （AO） modulates the variability of the PMLY while the interannual variability of PMLY is in phase with the Northern Atlantic Oscillation （NAO） and the Northern Pacific Oscillation （NPO）.

Estimation of ocean primary productivity and its spatio-temporal variation mechanism for East China Sea based on VGPM model

According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for CaseⅠand CaseⅡwater bodies respectively. The monthly chlorophyll distribution in the East China Sea in 1998 was obtained from this improved model on calculation results of SeaBAM. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K 490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distributions in the East China Sea in 1998 were obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays the lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m 2 /d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m 2 /a. The research on the seasonal variety mechanism of primary productivity shows that several factors that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River diluted water variety, the euphotic depth, ocean current variety, etc. But the main influencing factors may be different in each local sea area.

Spatio-temporal dynamics of vegetation in Jungar Banner of China during 2000–2017

It is known that the exploitation of opencast coal mines has seriously damaged the environments in the semi-arid areas.Vegetation status can reliably reflect the ecological degeneration and restoration in the opencast mining areas in the semi-arid areas.Long-time series MODIS NDVI data are widely used to simulate the vegetation cover to reflect the disturbance and restoration of local ecosystems.In this study, both qualitative(linear regression method and coefficient of variation(CoV)) and quantitative(spatial buffer analysis, and change amplitude and the rate of change in the average NDVI) analyses were conducted to analyze the spatio-temporal dynamics of vegetation during 2000–2017 in Jungar Banner of Inner Mongolia Autonomous Region, China, at the large(Jungar Banner and three mine groups) and small(three types of functional areas: opencast coal mining excavation areas, reclamation areas and natural areas) scales.The results show that the rates of change in the average NDVI in the reclamation areas(20%–60%) and opencast coal mining excavation areas(10%–20%) were considerably higher than that in the natural areas(<7%).The vegetation in the reclamation areas experienced a trend of increase(3–5 a after reclamation)-decrease(the sixth year of reclamation)-stability.The vegetation in Jungar Banner has a spatial heterogeneity under the influences of mining and reclamation activities.The ratio of vegetation improvement area to vegetation degradation area in the west, southwest and east mine groups during 2000–2017 was 8:1, 20:1 and 33:1, respectively.The regions with the high CoV of NDVI above 0.45 were mainly distributed around the opencast coal mining excavation areas, and the regions with the CoV of NDVI above 0.25 were mostly located in areas with low(28.8%) and medium-low(10.2%) vegetation cover.The average disturbance distances of mining activities on vegetation in the three mine groups(west, southwest and east) were 800, 800 and 1000 m, respectively.The greater the scale of mining, the farther the disturbance distances of mining activities on vegetation.We conclude that vegetation reclamation will certainly compensate for the negative impacts of opencast coal mining activities on vegetation.Sufficient attention should be paid to the proportional allocation of plant species(herbs and shrubs) in the reclamation areas, and the restored vegetation in these areas needs to be protected for more than 6 a.Then, as the repair time increased, the vegetation condition of the reclamation areas would exceed that of the natural areas.

Spatio-temporal variation and propagation direction of coal fire in Jharia Coalfield,India by satellite-based multi-temporal night-time land surface temperature imaging

In this paper,the spatio-temporal variation and propagation direction of coal fire were studied in the Jharia Coalfield(JCF),India during 2006–2015 through satellite-based night-time land surface temperature(LST)imaging.The LST was retrieved from Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER)night-time thermal-infrared data by a robust split-window algorithm based on scene-specific regression coefficients,band-specific hybrid emissivity,and night-time atmospheric transmittance.The LST-profile-based coal fire detection algorithm was formulated through statistical analysis of the LST values along multiple transects across diverse coal fire locations in the JCF in order to compute date-specific threshold temperatures for separating thermally-anomalous and background pixels.This algorithm efficiently separates surface fire,subsurface fire,and thermally-anomalous transitional pixels.During the observation period,it was noticed that the coal fire area increased significantly,which resulted from new coal fire at many places owing to extensive opencast-mining operations.It was observed that the fire propagation occurred primarily along the dip direction of the coal seams.At places,lateral-propagation of limited spatial extent was also observed along the strike direction possibly due to spatial continuity of the coal seams along strike.Moreover,the opencast-mining activities carried out during 2009–2015 and the structurally weak planes facilitated the fire propagation.

EEG Source Localization Using Spatio-Temporal Neural Network

Source localization of focal electrical activity from scalp electroencephalogram (sEEG) signal is generally modeled as an inverse problem that is highly ill-posed. In this paper, a novel source localization method is proposed to model the EEG inverse problem using spatio-temporal long-short term memory recurrent neural networks (LSTM). The network model consists of two parts, sEEG encoding and source decoding, to model the sEEG signal and receive the regression of source location. As there does not exist enough annotated sEEG signals correspond to specific source locations, simulated data is generated with forward model using finite element method (FEM) to act as a part of training signals. A framework for source localization is proposed to estimate the source position based on simulated training data. Experiments are done on simulated testing data. The results on simulated data exhibit good robustness on noise signal, and the proposed network solves the EEG inverse problem with spatio-temporal deep network. The result show that the proposed method overcomes the highly ill-posed linear inverse problem with data driven learning.