Volume Estimation of Land Surface Change Based on GaoFen-7

Volume of change provides a comprehensive and objective reflection of land surface transformation, meeting the emerging demand for feature change monitoring in the era of big data. However, existing land surface monitoring methods often focus on a single dimension, either horizontal or vertical, making it challenging to achieve quantitative volumetric change monitoring. Accurate volumetric change measurements are indispensable in many fields, such as monitoring open-pit coal mines. Therefore, the main content and conclusions of this paper are as follows: (1) A method for Automatic Control Points Extraction from ICESat-2/ATL08 products was developed, integrating Land cover types and Phenological information (ACPELP), achieving a mean absolute error (MAE) of 1.05 m in the horizontal direction and 1.99 m in the vertical direction for stereo change measurements. This method helps correct image positioning errors, enabling the acquisition of geospatially aligned GaoFen-7 (GF-7) imagery. (2) A function-based classification system for open-pit coal mines was established, enabling precise extraction of stereoscopic change region to support accurate volumetric calculations. (3) A method for calculating the mining and stripping volume of open-pit coal mines based on GF-7 imagery is proposed. The method utilizes photogrammetry to extract elevation features and combines spectral features with elevation data to estimate stripping volumes, achieving an excellent error rate (ER) of 0.26%. The results indicate that our method is cost-effective and highly practical, filling the gap in accurate and comprehensive monitoring of land surface changes.