(1. 中南大學(xué) 地球科學(xué)與信息物理學(xué)院，長(zhǎng)沙 410083；
2. 湖南科技大學(xué) 煤炭資源清潔利用與礦山環(huán)境保護(hù)湖南省重點(diǎn)實(shí)驗(yàn)室，湘潭 411201；
3. 中南大學(xué) 湖南省普通高校精密工程測(cè)量及形變?yōu)暮ΡO(jiān)測(cè)重點(diǎn)實(shí)驗(yàn)室，長(zhǎng)沙 410083)
摘 要: 利用10景ALOS PALSAR影像獲取山西云岡某礦區(qū)在2007年7月1日至2009年1月3日的地表時(shí)序沉降值，并使用Logistic模型擬合該礦區(qū)全盆地時(shí)序沉降。結(jié)果表明:通過(guò)交叉驗(yàn)證Logistic模型估計(jì)參數(shù)預(yù)測(cè)的時(shí)序沉降與InSAR監(jiān)測(cè)值后發(fā)現(xiàn)，兩者吻合較好，且其平均均值和均方根誤差分別為-0.4和2.5 cm，表明在整個(gè)下沉盆地內(nèi)，各點(diǎn)的動(dòng)態(tài)沉降均符合“S”型增長(zhǎng)，且Logistic模型能較好地描述該過(guò)程。統(tǒng)計(jì)該礦區(qū)全盆地Logistic模型形狀參數(shù)a和b后，發(fā)現(xiàn)參數(shù)a和b分別服從Weibull分布和隨機(jī)分布，且其數(shù)值變化較大，表明利用少量離散地表監(jiān)測(cè)數(shù)據(jù)擬合的Logistic模型參數(shù)預(yù)測(cè)的全盆地動(dòng)態(tài)沉降結(jié)果可靠性不高。最后，利用全盆地Logistic模型估計(jì)參數(shù)預(yù)測(cè)了該礦區(qū)2009年2月18日的地表沉降值，該值與InSAR監(jiān)測(cè)結(jié)果吻合較好，均方根誤差為2.15cm。
關(guān)鍵字: InSAR時(shí)序形變；開(kāi)采沉陷；時(shí)空演化；Logistic模型；遺傳算法；Levenberg-Marquard算法
（1. School of School of Earth Science and Geomatics Engineering,
Central South University, Changsha 410083, China;
2. Hunan Province Key Laboratory of Coal Resources Clean-utilization and
Mine Environment Protection, Hunan University of Science and Technology, Xiangtan 411201, China;
3. Key Laboratory of Precise Engineering Surveying and
Deformation Hazard Monitoring of Hunan Province, Central South University, Changsha 410083, China）
Abstract:10 ALOS PALSAR images were used to derive the mining ground time-series subsidence of one mining area in Yungang city, Shanxi Province, China, from July 1, 2007 to January 3, 2009, and the mining ground time-series subsidence was fitted with the Logistic model. The results show that the predicted time-series subsidence by the Logistic model has a good agreement with those of InSAR-measured with average mean and root mean square error of -0.4 and 2.5 cm, respectively, from the cross validation of both. The dynamic subsidence of all surface points in the whole basin agrees with S-shaped temporal evolution, and the Logistic model could describe this temporal evolution accurately. Subsequently, the shape parameters a and b of Logistic model are followed the Weibull and random distribution, respectively, and rapidly changes of parameters occur from their statistical histograms. This indicates that the predicted kinematic subsidence is unreliable if the parameters of Logistic model are yielded by the measurements of a few sparse observation points. At last, the subsidence of this mining area on February 28, 2009 was predicted, which have a good agreement with those of InSAR measured with root mean square error of 2.15 cm.
Key words: InSAR-derived time-series deformation; mining subsidence; spatio-temporal evolution; Logistic model; genetic algorithm; Levenberg-Marquard algorithm
