Monitoring Ecological Restoration with Imagery Tools (MERIT): Python-based Decision Support Tools Integrated into ArcGIS for Satellite and UAS Image Processing, Analysis, and Classification

Abstract

Monitoring the impacts of ecosystem restoration strategies requires both short-term and long-term land surface monitoring. The combined use of unmanned aerial systems (UAS) and satellite imagery enable effective landscape and natural resource management. However, processing, analyzing, and creating derivative imagery products can be time consuming, manually intensive, and cost prohibitive. In order to provide fast, accurate, and standardized UAS and satellite imagery processing, we have developed a suite of easy-to-use tools integrated into the graphical user interface (GUI) of ArcMap and ArcGIS Pro as well as open-source solutions using NodeOpenDroneMap. We built the Monitoring Ecological Restoration with Imagery Tools (MERIT) using Python and leveraging third-party libraries and open-source software capabilities typically unavailable within ArcGIS. MERIT will save US Army Corps of Engineers (USACE) districts significant time in data acquisition, processing, and analysis by allowing a user to move from image acquisition and preprocessing to a final output for decision-making with one application. Although we designed MERIT for use in wetlands research, many tools have regional or global relevancy for a variety of environmental monitoring initiatives.

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Document Details

Document Type
Technical Report
Publication Date
Apr 13, 2021
Accession Number
AD1127684

Entities

People

  • Kristofer D. Lasko
  • Sean P. Griffin

Organizations

  • Engineer Research and Development Center

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Space

DTIC Thesaurus Topics

  • Change Detection
  • Computer Programming
  • Computer Programs
  • Computers
  • Detection
  • Ecology
  • Environmental Monitoring
  • Geographic Information Systems
  • Graphical User Interface
  • Image Processing
  • Information Science
  • Information Systems
  • Machine Learning
  • Organizational Structure
  • Remote Sensing
  • Satellite Imaging
  • Supervised Machine Learning
  • Unmanned Aerial Systems
  • User Interface
  • Web Browsers
  • Wetlands

Fields of Study

  • Environmental science

Readers

  • Computer Vision.
  • Database Systems and Applications
  • Wetland-Land-Environmental Management.

Technology Areas

  • Autonomy
  • Space