<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Remote Sensing | 朱子恒</title><link>https://ziheng.ac.cn/zh/tags/remote-sensing/</link><atom:link href="https://ziheng.ac.cn/zh/tags/remote-sensing/index.xml" rel="self" type="application/rss+xml"/><description>Remote Sensing</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>zh-Hans</language><lastBuildDate>Mon, 23 Feb 2026 00:00:00 +0000</lastBuildDate><image><url>https://ziheng.ac.cn/media/icon_hu9134938122768028176.png</url><title>Remote Sensing</title><link>https://ziheng.ac.cn/zh/tags/remote-sensing/</link></image><item><title>增强改进森林经营碳抵消可信度的动态事后基线</title><link>https://ziheng.ac.cn/zh/publication/ifm_offsets/</link><pubDate>Mon, 23 Feb 2026 00:00:00 +0000</pubDate><guid>https://ziheng.ac.cn/zh/publication/ifm_offsets/</guid><description>&lt;p>本文结合卫星观测、因果推断和机器学习方法，为改进森林经营碳抵消项目构建动态事后基线，并评估其额外性与碳信用可信度。&lt;/p>
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&lt;img src="./paper.png" alt="Environmental Science &amp; Technology 论文首页">
&lt;figcaption>图 1：ES&amp;T 论文首页。&lt;/figcaption>
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