WeChat Mini Program
Old Version Features

基于RS和GIS的浙江省湖州市某区域矿山环境遥感监测

Mineral Exploration(2021)

中国地质大学(北京)

Cited 2|Views7
Abstract
基于2018年和2019年获取的浙江省湖州市国产高分辨卫星数据和DEM数字高程数据,结合浙江省的自然环境、矿产资源分布情况等资料,对浙江湖州市某区域进行了矿山环境遥感监测,该研究区主要为平原、台地、丘陵、小起伏山地;坡度主要集中在平坡、缓坡、斜坡区域.矿山占地主要集中在台地和丘陵地区,以缓坡为主;得出湖州市矿山露天开采难度较小,边坡较为稳定;总结出湖州市矿山环境治理模式为生态自然复绿型、矿山占地改造型、边开采边治理型等.查清了湖州市矿山环境现状及发展趋势,取得的成果可对矿产资源的合理开发和进一步制定矿山环境生态保护规划提供重要的科学依据.
More
求助PDF
上传PDF
Bibtex
收藏
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined