Geospatial Analysis of Tree Canopy Cover for Streams in the Contiguous United States


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Resource type: Composite Resource
Storage: The size of this resource is 1.8 GB
Created: Mar 21, 2021 at 4:11 a.m.
Last updated: Apr 01, 2021 at 6:07 p.m.
DOI: 10.4211/hs.205aff2822dc409ca0b0ab5d9a246e5b
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Abstract

The goal of this Resource is to estimate the fraction of stream length in the contiguous United States covered by dense tree canopy described in greater detail in the research paper Maghami et al. (2021). To find out more information about this Resource and the steps to reproduce this geospatial analysis, please refer to the readme file.

Subject Keywords

Resource Level Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Place/Area Name:
Contiguous US
North Latitude
49.3707°
East Longitude
-66.1168°
South Latitude
25.4667°
West Longitude
-126.0583°

Content

Readme.md

1- Introdcution

This readme file contains the nececssary information about this resource, and describes the steps to reproduce the results of the geospatioal analysis.
The required data and codes are included in the folder "Tree Canopy Cover for CONUS Streams".

The paper citation (Maghami et al., 2021):
Maghami, I., Sobral, V. A. L., Morsy, M. M., Lach, J. C., & Goodall, J. L. (2021). Exploring the Complementary Relationship between Solar and Hydro Energy Harvesting for Self-Powered Water Monitoring in Low-Light Conditions. Environmental Modelling & Software, https://doi.org/10.1016/j.envsoft.2021.105032.

2- Datasets and Software

To perform this geospatial analysis, the following datasets and software are used:

Datasets:

1- Percent Tree Canopy raster file available through the US Forest Service covering the contiguous United States (CONUS)
2- The National Hydrography Dataset Plus V2.0 stream network including about 2.7 million reaches covering the CONUS
3- 2-digit and 4-digit Hydrologic Unit Code (HUC) watersheds (i.e., HUC2 and HUC4)

Software:

1- GIS program: ArcMap 10.5.1
2- Programing language: Python 3

3- Steps:

Important Notes:
1. The codes and data are located in "Tools" subfolder.
2. Steps 1 through 3 are done locally on the personal computer of the creator of this Hydroshare resource and only the outputs of these steps which are the inputs for step 4 are avaialbe in this Hydroshare resource. Those input files are large so were not replicated in this HydroShare resource, but can be created following the steps 1 to 3 below.
3. The file "NHDPlus_TreeCanopy_Map.7z" located in the main folder containes a mxd file and other necessary files to show the the mean percent tree canopy during leaf-on conditions over NHDPlus network averaged based on the HUC4 watersheds in ArcMap. The output of the step 4d which is "3_out_mean_percent_treecanopy_HUC4.txt" is used to create this map.
4. Example to understand the codes and data files' naming convention: "1_out_Merged_results.txt" is the ouput of code "GeospatialAnalysis_1_createsMerged_resultstxtfile.py"

Step 1- Download the necessay data for the CONUS

1-a) Stream network:
National Hydrography Dataset Plus (NHDPlus) V2.0
https://nhdplus.com/NHDPlus/NHDPlusV2_home.php

1-b) Percent Tree Canopy:
The USDA Forest Service Remote Sensing Applications Center (RSAC)
https://data.fs.usda.gov/geodata/rastergateway/treecanopycover/

1-c) HUC2 and HUC4 polygons:
U.S. Geological Survey and USDA Natural Resources Conservation Service
https://datagateway.nrcs.usda.gov/Catalog/ProductDescription/WBD.html

Step 2- Calculate the mean perent tree canopy for each NHDPluss in ArcMap

2-a) Use Zonal Statistics to calculate mean value of the percent tree canopy raster file within the zones of NHDPlus dataset.
2-b) Export the results as "0_in_Export_Output_Joint.txt" which is the text file containing variety of features including Mean percent tree canopy, streamorder, lenght, and COMID.

Step 3- Using ArcMap, Determine which NHDPlus reach is located in which HUC4 watershed polygon:

3-a) Use spatial join tool, to join NHDPlus network and HUC4 Raster file (join method: center near closest polygon) it took about 30 minutes on a Intel(R) Core(TM) i7-7700 CPU @3.60GHz with 16.0 GB RAM with Windows 10 desktop.
3-b)- Once the spatial join is done, the content of the table could not be copied (the reason unknown to the developer). Instead, join table to table (the saptial joint table to NHDPlus networK) by right click...
3-c)- Then, export the results as "0_in_SpatialjointtblCOMIDhuc4.txt" which is a text file containing variety of features which also shows which NHDPlus's COMID is located in which HUC4 watershed polygon.

Step 4- Next, run the following codes using Python following the sequential order:

Note: Prior to run 4-a, unzip "0_in_Export_Output_Joint.7z" and "0_in_SpatialjointtblCOMIDhuc4.7z" and put the resulting txt files in the "inout" folder.

4-a) GeospatialAnalysis_0_prerequisite_cleansuprawdata.py

4-b) GeospatialAnalysis_1_createsMerged_resultstxtfile.py

4-c) GeospatialAnalysis_2_plotsNHDLen_pertreeCanopy_forStrmOrdrpdffile.py

4-d) GeospatialAnalysis_3_createsmean_percent_treecanopy_HUC4txtANDpertreecanopy_perlengthtxtfiles.py

4-e) GeospatialAnalysis_4_createsoutputs_HUC4csvfile.py

4-f) GeospatialAnalysis_5_plotsperctreecanopy_perclenNHDPlus_forhuc4spdffile.py

References

Related Resources

The content of this resource serves as the data for: https://doi.org/10.1016/j.envsoft.2021.105032

How to Cite

Maghami, I., J. Goodall, V. A. L. Sobral, M. Morsy, J. C. Lach (2021). Geospatial Analysis of Tree Canopy Cover for Streams in the Contiguous United States, HydroShare, https://doi.org/10.4211/hs.205aff2822dc409ca0b0ab5d9a246e5b

This resource is shared under the Creative Commons Attribution CC BY.

 http://creativecommons.org/licenses/by/4.0/
CC-BY

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