A High Definition Stream Survey (HDSS) is a method for the collection, classification, analysis, and reporting of continuous, georeferenced data. This methodology allows for the collection of a broad suite of physical and biological parameters. HDSS provides the data necessary to understand the distribution and extent of habitat in your stream, providing the foundation for planning and decision-making.

The HDSS methodology allows for the rapid and efficient collection of data. It is not uncommon for 12 to 15 miles of continuous data to be collected in a single day with the boat-mounted platform. While 4-6 miles in a single day with the backpack-mounted platform is common. This allows even the largest projects to be quickly accomplished with minimal time in the field.

Data collected during the survey are linked in a Geographic Information System (GIS) database providing a near 1-meter resolution of the conditions in and along the stream. This allows the user to easily locate, assess, and reference conditions along the stream corridor.

Additionally, the spatial metadata is embedded into the StreamView video providing the user with the ability to virtually walk and see the conditions along the stream corridor while knowing their location along the survey. This is easily done using ArcGIS, QGIS, and Remote Geosystems Geotagger at your desk.




The HDSS approach has been adapted to be used on different sampling platforms (Backpack, Kayak, Inflatable Boat, and Outboard Motorboat) to effectively sample different sizes and types of streams and rivers. The selection of the appropriate sampling platform will be determined by reconnaissance field observations prior to final contracting.

HDSS StreamView video produced from the surveys includes the above water video imagery, map of the survey locations and down-looking imagery and/or sonar. Using the StreamView video stream condition and habitat components are georeferenced, scored, and ranked according to their type and extent.


Data collection and classification is typically one of the most time-intensive and costly steps in conducting environmental studies. With traditional data collection methods once field data and classification is complete that classification is only good for what was actually classified; therefore, if additional classifications or information is required an additional revisit to the site is necessary, causing delays and increasing costs.

A major benefit of HDSS over other sampling methods is your ability to classify, reclassify, and review the data. A single survey answers multiple questions, addresses many objectives, and can later be reclassified to answer new or additional questions when needed. Furthermore, the data can easily be reviewed for verification and consistency.

By applying the HDSS approach, you benefit by:

  • Quickly and accurately determine the extent and distribution of problems within your river or stream.
  • Having the flexibility to answer questions after your field survey is completed.
  • Answering multiple management questions from a single survey.
  • Having the ability to apply new classifications to answer additional questions.
  • Have the ability to reclassify the data if new or novel techniques emerge.
  • Quickly prioritizing your management needs based on an understanding of river or stream.

A brief summary of the flexibility of HDSS data collection and classification methodology is provided below.

A survey was conducted on 1,24km (77 miles) of the Upper Delaware River to assess the condition of the stream corridor and develop habitat suitability models for multiple fish species and various life stages. With field data collection complete, we met with the contracting agents regarding data analysis, and the discussion was diverted to a noxious weed along the streambanks commonly known as Japanese knotweed. Managers were concerned with the effects of this noxious weed on water quality, due to the winter die-off of the species leading to increased streambank erosion, during the winter months. Little was known about the distribution of the species along the Upper Delaware River.

We had not incorporated a Japanese Knotweed study in the original survey design since we were not aware of or tasked to address this problem; however, we agreed to review the data to determine if the HDSS platform collected the appropriate data for analysis. After reviewing the data, we were able to classify the presence or absence of this species throughout the entire survey area. Following classification analysis was performed demonstrating its extensive distribution. This data is now being used to support legislative action for the control of this noxious weed.


Deliverables for a typical project include the StreamView video, GIS data, spreadsheets, maps, graphic summaries and a final report.

StreamView Videos

The StreamView videos are uniquely labeled and provided in a .mp4 file format for your entire survey. These videos have a forward facing, left bank, right bank, and downward high-definition view of the stream corridor, and a map indicating the location of the platform during the survey. Depending on the data collection platforms (i.e., boat or backpack) sonar and sidescan images are also included. Additionally, spatial metadata can be embedded into the StreamView video allowing you to simultaneously watch the StreamView video in ArcGIS, QGIS, and Remote Geosystems Geotagger systems.

GIS Data

The GIS data is provided in a series of geopackages with each geopackage containing a set of specific layers. Geopackages are a standardized method developed for the transfer of geospatial data. The geopackage format is easily utilized in QGIS, ArcGIS, and other software packages. The GIS data provides the mapping and classification scores for each meter of the stream.

Final Report

The report is provided outlining the Objectives, Methods, Results and Conclusions of the project. Additionally, graphic summaries of Site-of-Concern are provided which give decision-makers a way to compare and prioritize restoration efforts by weighting feasibility (cost, time) with likely improvement outcomes.