基于HJ-1高光谱的曹家坝矿山水环境识别与监测

Identification and Monitoring for Water Environment in Caojiaba Mine Based on HJ-1 Hyper-spectrum

矿山资源开发过程中存在较为严重的水环境问题,但常规的地面调查方法在时效性和广度上存在局限。为解决这一问题,本文基于我国自主发射的环境一号卫星(HJ-1),获取了曹家坝矿山宽幅30 km范围内的高光谱遥感数据,通过数据读取、辐射定标、气候校正和尺寸配准的方式控制图元误差为0.5 mm,平均精度达到0.42,有效避免重影和错位问题。同时,基于水体光谱特征和颜色作为水环境水质监测的标志物,通过波段运算和灰度法分别对植被和水体遥感图像解译,精确反映了矿区水环境高光谱遥感结果,有效提高了矿区水环境监测时效性和广度。

There are serious water environment problems in the process of mining resource development,but the conventional ground investigation methods are limited in timeliness and breadth.To solve this problem,based on the environment of our country's independent launch a satellite(HJ-1),obtained the Cao Guba mine 30 km wide range of hyperspectral remote sensing data,the data read,radiation calibration,climate correction and the way of registration to the size of the control chart yuan error is 0.5 mm,the average accuracy of 0.42,effectively avoid ghosting and mismatch.At the same time,based on the spectral characteristics and colors of water as the markers of water quality monitoring,vegetation and water remote sensing images were respectively translated by band calculation and gray scale method,which accurately reflected the hyperspectral remote sensing results of mining water environment and effectively improved the timeliness and breadth of mining water environmental monitoring.