Shade distribution in Pacoima, California

We used Light Detection and Ranging (LiDAR) data to model urban form, mapping shade annual and diurnal cycle and estimate average cumulative solar exposure in Pacoima, Los Angeles County, California. 

, We obtained LiDAR data from the LARIAC (Los Angeles Region Imagery Acquisition Consortium captured in early 2020. The LiDAR data has a point density between 2–3 points per square meter creating DEM, DSM and CHM with 1- meter resolution. We used Cloudcompare software and ArcGIS Pro 2.9 software to classify and process LiDAR data into Digital Surface Models and shadow raster for both trees and built form separately. Cloudcompare software was used to filter lidar points to vegetation (high, medium, and low) as one layer of lidar points, and filtered buildings as a second layer. Both layers were then used with Lastools toolbox on ArcGIS Pro to generate digital surface and canopy height models to then be used to model shadow using solar parameters of zenith and altitude. The output of the tools yielded a raster with extent of shade and unshaded spaces identified and the spatial resolution was the same as the digital surface models. This raster was reclassified to binary values of shade and s..., , # Shade distribution in Pacoima, California

[https://doi.org/10.5061/dryad.pc866t20p](https://doi.org/10.5061/dryad.pc866t20p)

## Summary

The dataset accompanying this manuscript includes geospatial and point cloud data used for shade stemming of land surface and vegetation characteristics. 

The files are organized by data type and format as follows:

.las files:\
These are LiDAR point cloud files containing 3D elevation data (x, y, z coordinates) and intensity values. Each file represents a discrete tile of the study area used to derive surface and canopy models for the analysis.\
\
Example file: L4_6434_1910a.las

### File naming convention

L4\_ → LiDAR dataset level or flight line identifier\
6434\_ → Tile reference number based on map grid coordinates\
1910a → Row Reference #(1910) and a-d quadrant (a)

### Software Compatibility

.las files can be opened and analyzed in: ArcGIS Pro (using LAS dataset tools) QGIS (via the LAS or LAStools plugin) CloudCompare (for 3D visualizati...,

本研究借助激光雷达（Light Detection and Ranging, LiDAR）数据对城市形态进行建模，绘制了美国加利福尼亚州洛杉矶县帕科伊马区域的阴影年周期与日周期变化，并估算了该区域的平均累积太阳辐射量。

本研究的激光雷达数据采集自洛杉矶地区影像采集联盟（Los Angeles Region Imagery Acquisition Consortium, LARIAC），数据获取时间为2020年初。该激光雷达数据的点密度为每平方米2~3个点，可生成分辨率为1米的数字高程模型（Digital Elevation Model, DEM）、数字表面模型（Digital Surface Model, DSM）以及冠层高度模型（Canopy Height Model, CHM）。

本研究使用CloudCompare软件与ArcGIS Pro 2.9软件，分别针对植被与建筑两种地物，将激光雷达数据分类处理为数字表面模型与阴影栅格数据。其中，CloudCompare软件用于将激光雷达点云分为两类：一类为按高度划分为高、中、低三个等级的植被点云，另一类为过滤得到的建筑点云。随后，将这两类点云数据结合ArcGIS Pro中的Lastools工具箱，生成数字表面模型与冠层高度模型，再基于天顶角与高度角等太阳参数进行阴影建模。工具输出的栅格数据可识别阴影与非阴影区域的范围，其空间分辨率与数字表面模型保持一致。该栅格数据被重新分类为阴影与非阴影的二值化数据……

# 加利福尼亚州帕科伊马的阴影分布
[https://doi.org/10.5061/dryad.pc866t20p](https://doi.org/10.5061/dryad.pc866t20p)

## 摘要
本研究配套数据集包含用于地表与植被特征阴影建模的地理空间数据与点云数据。

数据集按数据类型与格式进行组织，具体如下：
### .las格式文件
此类文件为激光雷达点云数据，包含三维高程数据（x、y、z坐标）与强度值。每个文件对应研究区域的一个独立分块，用于提取分析所需的地表与冠层模型。
示例文件：L4_6434_1910a.las

### 文件命名规则
L4_ → 代表激光雷达数据集层级或飞行航线标识符
6434_ → 基于地图网格坐标的分块参考编号
1910a → 行参考编号（1910）与a-d象限（a）

### 软件兼容性
.las格式文件可通过以下软件打开并分析：
- ArcGIS Pro（使用LAS数据集工具）
- QGIS（通过LAS或LAStools插件）
- CloudCompare（用于三维可视化……）