A spatio-temporal prediction method of large-scale ground subsidence considering spatial heterogeneity

نویسندگان

چکیده

å¤§é€ŸçŽ‡ã€ä¸å‡åŒ€çš„åœ°é¢æ²‰é™å·²ç»å¨èƒåˆ°äººç±»çš„ç”Ÿäº§æ´»åŠ¨ï¼Œé«˜ç²¾åº¦çš„æ²‰é™é¢„æµ‹ç»“æžœå¯¹äºŽåœ°è´¨ç¾å®³çš„ç²¾å‡†é˜²æŽ§å ·æœ‰é‡è¦æ„ä¹‰ã€‚ä¸ºæŽŒæ¡åœ°é¢æ²‰é™çš„æ¼”åŒ–è§„å¾‹ï¼Œåˆ©ç”¨çŽ°åœºè§‚æµ‹æ•°æ®æˆ–InSARæ•°æ®å¼€å±•äº†å¤šé¡¹é¢„æµ‹ç ”ç©¶ã€‚ç„¶è€Œï¼Œç”±äºŽç©ºé—´å¼‚è´¨æ€§çš„å­˜åœ¨ï¼Œå¤§èŒƒå›´åœ°é¢æ²‰é™çš„å‡†ç¡®é¢„æµ‹ä»ç„¶æ˜¯ä¸€é¡¹æŒ‘æˆ˜ã€‚åœ¨è¿™é¡¹ç ”ç©¶ä¸­ï¼Œä»Žæ•°æ®é©±åŠ¨çš„è§’åº¦æå‡ºäº†ä¸€ç§é¡¾åŠç©ºé—´å¼‚è´¨æ€§çš„å¤§èŒƒå›´åœ°é¢æ²‰é™æ—¶ç©ºé¢„æµ‹æ–¹æ³•STLSTM(Spatio-temporal Long Short-Term Memoryï¼‰ã€‚é¦–å ˆï¼Œé€šè¿‡èšç±»è¯†åˆ«åœ°ç†ç©ºé—´ä¸­çš„å‡è´¨å­åŒºï¼›ç„¶åŽï¼Œåœ¨æ¯ä¸ªå­åŒºä¸­ï¼Œä¸€ä¸ªç‰¹åˆ«çš„é•¿çŸ­æœŸè®°å¿†LSTM(Long Memoryï¼‰ç½‘ç»œè¢«ç”¨æ¥æ•æ‰å±€éƒ¨ä½ç½®çš„éžçº¿æ€§ç‰¹å¾ï¼›æœ€åŽï¼Œåˆ©ç”¨é¢„è®­ç»ƒçš„ç½‘ç»œå¯¹æœªæ¥æ—¶åˆ»çš„åœ°é¢æ²‰é™è¿›è¡Œå®šé‡é¢„æµ‹ã€‚åœ¨å®žéªŒéƒ¨åˆ†ï¼Œå“¨å µ1号影像数据被用来比较STLSTMä¸Žå ¶ä»–8ç§åŸºå‡†æ–¹æ³•çš„æ€§èƒ½ï¼Œåˆ©ç”¨ç©ºé—´ç»Ÿè®¡æŒ‡æ ‡åˆ†æžäº†æ¨¡åž‹çš„æœ‰æ•ˆæ€§ã€‚ç»“æžœè¡¨æ˜Žï¼ŒSTLSTM在152 så† è¾¾åˆ°äº†æœ€é«˜çš„é¢„æµ‹ç²¾åº¦ï¼ˆ71.4%ï¼‰ï¼Œä¸”èƒ½å¤Ÿæœ‰æ•ˆå¼±åŒ–ç©ºé—´å¼‚è´¨æ€§å¯¹å¤§åŒºåŸŸæ²‰é™é¢„æµ‹ä»»åŠ¡çš„å½±å“ã€‚æ€»ä¹‹ï¼Œè¿™é¡¹ç ”ç©¶å°†ç©ºé—´å¼‚è´¨æ€§å¤„ç†ç­–ç•¥èžåˆåˆ°æ·±åº¦å­¦ä¹ æ¨¡åž‹ä¸­ï¼Œå®žçŽ°äº†é«˜ç²¾åº¦ã€é«˜æ—¶æ•ˆçš„å¤§èŒƒå›´åœ°é¢æ²‰é™æ—¶ç©ºé¢„æµ‹ã€‚

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Spatial and Temporal Patterns in Large-Scale Traffic Speed Prediction

The ability to accurately predict traffic speed in a large and heterogeneous road network has many useful applications, such as route guidance and congestion avoidance. In principle, data driven methods such as Support Vector Regression (SVR) can predict traffic with high accuracy, because traffic tends to exhibit regular patterns over time. However, in practice, the prediction performance can ...

متن کامل

Large-Scale Spatio-Temporal Patterns of Mediterranean Cephalopod Diversity

Species diversity is widely recognized as an important trait of ecosystems' functioning and resilience. Understanding the causes of diversity patterns and their interaction with the environmental conditions is essential in order to effectively assess and preserve existing diversity. While diversity patterns of most recurrent groups such as fish are commonly studied, other important taxa such as...

متن کامل

Practical Large - Scale Spatio - Temporal Modeling of Particulate Matter Concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during ...

متن کامل

Large-scale temporal and spatial patterns

Phytoplankton constitute the main algal biomass in pelagic ecosystems and, therefore, play a fundamental role in the functioning of the marine trophic web. Information on long-term trends in marine phytoplankton may help to distinguish between biological responses to natural oscillations in climate and global warming, and to evaluate possible regional effects of eutrophication. The aim of this ...

متن کامل

Spatio-temporal Scale-Spaces

A family of spatio-temporal scale-spaces suitable for a moving observer is developed. The scale-spaces are required to be time causal for being usable for real time measurements, and to be “velocity adapted”, i.e. to have Galilean covariance to avoid favoring any particular motion. Furthermore standard scale-space axioms: linearity, positivity, continuity, translation invariance, scaling covari...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of remote sensing

سال: 2022

ISSN: ['1007-4619', '2095-9494']

DOI: https://doi.org/10.11834/jrs.20211445