上海国土资源
上海國土資源
상해국토자원
SHANGHAI LAND&RESOURCES
2014年
4期
137-141
,共5页
地面沉降%地质灾害%水准测量%RTK测量%低海拔%预测检验
地麵沉降%地質災害%水準測量%RTK測量%低海拔%預測檢驗
지면침강%지질재해%수준측량%RTK측량%저해발%예측검험
land subsidence%geological hazard%leveling measurement%real time kinametic (RTK)%low altitude%forecast and inspection
利用1983年以来的水准复测资料和2005年实测的RTK地面高程资料,对水准点进行了拟合计算,得到了水准点的沉降速率和2005~2010年5年间的沉降量,以此拟合2010年RTK地面高程,预测了天津滨海新区因地面沉降引起的低海拔面积发展趋势,获得2010年低海拔区域预测面积。为验证预测结果的有效性和可靠性,2010年仍用RTK测量方法对低海拔区域面积进行了实测,表明预测值与实测面积的误差小于1.46%,该误差与RTK测量误差、水准点拟合误差和拟合实测之间的误差总和1.45%相当。说明预测误差主要由测量误差和计算误差引起,选择的预测模型基本正确,预测方法有效,得到的低海拔区域面积预测值可靠。
利用1983年以來的水準複測資料和2005年實測的RTK地麵高程資料,對水準點進行瞭擬閤計算,得到瞭水準點的沉降速率和2005~2010年5年間的沉降量,以此擬閤2010年RTK地麵高程,預測瞭天津濱海新區因地麵沉降引起的低海拔麵積髮展趨勢,穫得2010年低海拔區域預測麵積。為驗證預測結果的有效性和可靠性,2010年仍用RTK測量方法對低海拔區域麵積進行瞭實測,錶明預測值與實測麵積的誤差小于1.46%,該誤差與RTK測量誤差、水準點擬閤誤差和擬閤實測之間的誤差總和1.45%相噹。說明預測誤差主要由測量誤差和計算誤差引起,選擇的預測模型基本正確,預測方法有效,得到的低海拔區域麵積預測值可靠。
이용1983년이래적수준복측자료화2005년실측적RTK지면고정자료,대수준점진행료의합계산,득도료수준점적침강속솔화2005~2010년5년간적침강량,이차의합2010년RTK지면고정,예측료천진빈해신구인지면침강인기적저해발면적발전추세,획득2010년저해발구역예측면적。위험증예측결과적유효성화가고성,2010년잉용RTK측량방법대저해발구역면적진행료실측,표명예측치여실측면적적오차소우1.46%,해오차여RTK측량오차、수준점의합오차화의합실측지간적오차총화1.45%상당。설명예측오차주요유측량오차화계산오차인기,선택적예측모형기본정학,예측방법유효,득도적저해발구역면적예측치가고。
We had iftting calculated for the benchmark point by using the standard reiteration data since 1983 and real time kinematic (RTK) ground elevation data of 2005. It get the subsidence rate of the standard point and subsidence from 2005 to 2010 to iftting predicted RTK ground elevation of 2010. We also estimated the trend in the decreasing elevation of the land surface in the Binhai new area caused by land subsidence. And get the fold prediction of low altitude area in 2010. To verify the validity and reliability of the predictions made in 2010, we used the RTK method to measure the low-elevation area. A comparison of the forecasts with the measured low-elevation area shows that, relative to the measured area, the prediction error is less than 1.46% using the RTK method, and the difference between the leveling points iftting error and measured iftting error was 1.45%. This shows that the prediction error is mainly caused by measurement and calculation errors, and the choice of prediction model is essential y correct; therefore, the prediction method is effective, and the results from the low-elevation prediction area are reliable.