The case of the Zodiac Killer is one of the most widely known unsolved serial
killer cases in history. The unidentified killer murdered five known victims
and terrorized the state of California. He also communicated extensively with
the press and law enforcement. Besides his murders, Zodiac was known for his
use of ciphers. The first Zodiac cipher was solved within a week of its
publication, while the second cipher was solved by the authors after 51 years,
when it was discovered to be a transposition and homophonic substitution cipher
with unusual qualities. In this paper, we detail the historical significance of
this cipher and the numerous efforts which culminated in its solution.

Zodiac Killer 犯下了五起已知的谋杀案，引发了加利福尼亚州的恐慌，同时与新闻界和执法机构展开了广泛的交流，而其所使用的密码学奥秘历经几十年的努力破解出来，具有非凡的历史意义。

解决占星杀手的 340 个字符密码

The Solution of the Zodiac Killer's 340-Character Cipher

Tree canopy height is one of the most important indicators of forest biomass,
productivity, and species diversity, but it is challenging to measure
accurately from the ground and from space. Here, we used a U-Net model adapted
for regression to map the canopy height of all trees in the state of California
with very high-resolution aerial imagery (60 cm) from the USDA-NAIP program.
The U-Net model was trained using canopy height models computed from aerial
LiDAR data as a reference, along with corresponding RGB-NIR NAIP images
collected in 2020. We evaluated the performance of the deep-learning model
using 42 independent 1 km$^2$ sites across various forest types and landscape
variations in California. Our predictions of tree heights exhibited a mean
error of 2.9 m and showed relatively low systematic bias across the entire
range of tree heights present in California. In 2020, trees taller than 5 m
covered ~ 19.3% of California. Our model successfully estimated canopy heights
up to 50 m without saturation, outperforming existing canopy height products
from global models. The approach we used allowed for the reconstruction of the
three-dimensional structure of individual trees as observed from nadir-looking
optical airborne imagery, suggesting a relatively robust estimation and mapping
capability, even in the presence of image distortion. These findings
demonstrate the potential of large-scale mapping and monitoring of tree height,
as well as potential biomass estimation, using NAIP imagery.

利用 U-Net 模型和高分辨率航空影像对加利福尼亚州的所有树木的冠层高度进行了三维结构估测，在树高遥感建模方面取得了比全球模型更好的结果，表明了利用 National Agriculture Imagery Program 高分辨率影像进行大规模监测的潜力。