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https://github.com/usdaforestservice/collab_nvcs

Development of a Collaborative key to NVCS
https://github.com/usdaforestservice/collab_nvcs

Last synced: about 1 year ago
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Development of a Collaborative key to NVCS

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README 

          
# NVCS



This Python project is Stage 1 of an effort to populate a new condition

attribute, NVCS_CD, to NIMS and FIADB condition tables. NVCS_CD is a

classification variable describing the present vegetative community (very

similar to forest type). NVCS stands for National Vegetation Classification

Standard.



This initial version contains separate code bases for different FIA regional

groups.  For additional information see the relevant README in the regional

codebase folders:

    * NVCS-EAST



## Dependencies

- Python 3

- Cx_Oracle Python module



## Set-Up (Windows)

1. Download and install Python 3.*:



   - Go to [python.org](https://www.python.org/downloads)

   and download the "Windows x86 executable installer"



   - Run the installer.



2. Download and install cx_Oracle:



   - Go to [pypi.python.org](https://pypi.python.org/pypi/cx_Oracle "Cx_Oracle Downloads")



   - Open a command prompt and type:

   ```

   python -m pip install cx_Oracle

   ```



3. Extract the attached zip file.  I extracted it to %userprofile%\\NVCS.



4. Make sure your Windows ORACLE_HOME environment variable is set or appears on the PATH environment variable.  Otherwise cx_Oracle may fail to resolve

   the net service name, for example ORACLE_HOME=C:\\oracle64\\product\\12.2.0\\client\\bin



5. Test the database connection:



   - Open a python command prompt.

    ```python

    import cx_Oracle

    con = cx_Oracle.connect('/@FIADB01P')

    #If you get the >>> back then it worked and you can close the connection:

    con.close()

    ```



## Background



The U.S. National Vegetation Classification (USNVC) Standard was adopted by the

Federal Geographic Data Committee as a federal standard for reporting

vegetation information. NatureServe and the U.S. Forest Service (USFS) are

collaborating to implement the USNVC in the USFS Forest Inventory and Analysis

(FIA) Program. The USNVC uses an ecological vegetation approach that integrates

ecological and human factors with all vegetation layers into separate 8-level

hierarchy of types for both natural and cultural (plantation) forests. The goal

of our project is to classify conditions on FIA "Phase 2" (P2) plots across the

U.S. to the macrogroup level for natural forests and to type for plantation

forests. In this first phase, for eastern U.S. forests, NatureServe scientists

first completed a narrative-based key that used available FIA attributes,

including tree and environmental data, tree life-history data (nativity,

wetland indicator status, ruderality), and ecoregional information, to assign

P2 plot conditions to 27 macrogroup and 11 plantation types. The process of

computerizing the key was iterative. NRS-FIA staff (Kevin Nimerfro) developed a

computer algorithm based on this key, then produced summary outputs of

macrogroup and plantation types and distributions, which NatureServe staff

compared with published descriptions of the types. The final version of the key

was validated for natural forests using P2 FIA plots previously assigned to

USNVC groups and macrogroups by experts working with the LandFire program. By

assigning a macrogroup and plantation type to each forested condition, FIA can

report forest type data for eastern U.S. forests using the USNVC standard.γ€€

This information will facilitate collaborations with other agencies using the

USNVC.γ€€FIA data also improve the USNVC by providing valuable quantitative data

on macrogroup tree composition and distribution.



As the first phase of a national strategy, this project developed and

documented an approach for attributing FIA P2 forested conditions with the

USNVC macrogroups in the eastern half of the US (US Forest Service Regions 8

and 9), from Minnesota to Maine, south to Louisiana and eastern Texas to

Florida. The region extends as far west as the tallgrass prairie ecoregion

(Ecoregions 250, 255), including a small eastern portion of the Great Plains

states of Kansas, Nebraska, North Dakota, and South Dakota; the prairie

province extends further west in Oklahoma and Texas, so larger proportions of

these two states are included. FIA plots in ecoregions of western portions of

these six plains states do not yet have Macrogroup classification keys. A

future goal is to develop keys and code for attributing macrogroup to the

western half of the US, at which time those western portion of NRS-FIA and

SRS-FIA states will also be completed.



NatureServe scientists Don Faber Langendoen and Shannon Menard first completed

a narrative-based key that used available FIA attributes and tree species and

life-history data to assign P2 plot conditions to 27 macrogroup types and 11

plantation types in eastern US. The process of computerizing the key was

conducted primarily by Kevin Nimerfro. Once the first iteration of the key was

completed, it was translated into a Python program (by Kevin Nimerfro), which

is used to assign macrogroup codes to plot conditions. The Python program was

generated from a set of configuration files that describe the logic and flow of

the couplets in the key hierarchy. These configuration files allow for frequent

code changes including restructuring of the hierarchy. Likewise, it will be

easy to extend the key (e.g. include the Western U.S.) or develop a separate

key for another region of interest (e.g. a single state) – once NatureServe

develops new keys for the West.