CASE STUDY: Identifying Forest Harvests

Description: Forest harvesting is one of the silvicultural activities that can be detected using the Landsat Forest Area Change Tools (SouthFACT). Forest managers are often interested in identifying and monitoring forest harvests to support forest management objectives. While harvesting methods can vary from complete final harvests to selective thinning, these harvests can often be identified using SouthFACT’s remote sensing products. This case study demonstrates how to use the Custom Request application and Forest Change Viewer to locate forest harvest sites.

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Harvesting in Eastern North Carolina During the Spring of 2016

The steps below describe and illustrate how to identify forest harvests using the SouthFACT applications between April and May of 2016 in Greene County, North Carolina. In this example, the user has a specific area and time window of interest, making the Custom Request application an ideal tool.

STEP 1: Create a Custom Request
STEP 2: Viewing the Results of the Custom Request
STEP 3: Interpreting the Change Products

 

 

STEP 1: Create a Custom Request

The Custom Request application can be found from the SouthFACT Home page.

After clicking the “Create Custom Request” button, a form is presented to fill out the details of the request. The user is asked to: (1) provide a name of the request (for user reference), (2) choose the area of interest, (3) choose dates for the change analysis, and (4) confirm the order by selecting the imagery scenes that best fit the request.

The Initial Date represents the baseline point in time from which forest change will be analyzed. Therefore, to identify forest harvests, it is recommended that a date be chosen that pre-dates the start of the harvesting operations(s). Alternatively, if monitoring the progression of an ongoing operation, an Initial Date should be selected that best fits the user’s time period of interest. The End Date represents the point in time that will be compared against Initial Date conditions to derive a forest change product.

 

When browsing and selecting a scene using the image slider, look for imagery with the least amount of cloud cover for the specific area of interest that best fits the desired date window of interest. Landsat data are available every (8) days from alternating satellite platforms. Imagery may not be available for the exact date of interest.

After submitting the Custom Request, a message will appear toward the top of the page confirming that the request has been received. Users will be notified by email once the change products are available. The status of the request can be viewed on the Custom Request Status page.

 

STEP 2: Viewing the Results of the Custom Request

Once the Custom Request has been processed, users will receive an email with a download link and the status on the Custom Request Status page will be updated to include a download link. Users have two options at this time to view the Custom Request change products produced: (1) download the data and view within a desktop GIS application and (2) view the results within the Forest Change Viewer.

On the desktop, unzip the file and use the (.lyr) files to symbolize the data products in (for ArcGIS). GeoTIFFs may also be viewed in Quantum GIS, Google Earth Pro, and similar desktop applications.

In the Viewer, results will be in the Custom Requests section…

 


STEP 3: Interpreting the Change Products

There are many different remote sensing methods for detecting change. SouthFACT currently uses three vegetation indices:

*Here we will focus on the Shortwave Infrared Differencing (SWIR) product because it tends to show drastic vegetation changes on the landscape well, particularly forest harvesting. We will also use the threshold symbology that only shows areas of drastic change (at least 60% change):

 

USING LANDCOVER AND CLOUD MASKS

Another useful tip for interpreting change on the landscape is to use the landcover masks to view certain landcover types. This can be done in the SouthFACT Map Viewer. In this use case we are interested in masking out areas with cloud interference in the Landsat data and in viewing only areas with forested landcover:

The map then shows areas of change that meet the selected mask criteria:

 

We can then zoom in to some of the large dark-red areas showing change and use an imagery basemap to examine further. Many of these areas are showing potential harvest sites: