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Keyword: change detection

Unmanned aerial vehicle-based rangeland monitoring: Examining a century of vegetation changes

Publications Posted on: September 10, 2019
Rangelands comprise a large component of the terrestrial land surface and provide critical ecosystem services, but they are degrading rapidly. Long-term rangeland monitoring with detailed, nonsubjective, quantitative observations can be expensive and difficult to maintain over time. Unmanned aerial vehicles (UAVs) provide an alternative means to gather unbiased and consistent datasets with similar details to field-based monitoring data.

Northwest Forest Plan—the first 10 years (1994-2003): status and trend of late-successional and old-growth forest.

Publications Posted on: August 01, 2018
We monitored the status and trend of late-successional and old-growth forest (older forest) on 24 million ac of land managed by the Forest Service, Bureau of Land Management, and National Park Service in the Northwest Forest Plan (the Plan) area between 1994 and 2003. We developed baseline maps from satellite imagery of older forest conditions at the start of the Plan.

Implementation of the LandTrendr algorithm on Google Earth Engine

Publications Posted on: July 06, 2018
The LandTrendr (LT) algorithm has been used widely for analysis of change in Landsat spectral time series data, but requires significant pre-processing, data management, and computational resources, and is only accessible to the community in a proprietary programming language (IDL). Here, we introduce LT for the Google Earth Engine (GEE) platform.

Mapping forest change using stacked generalization: An ensemble approach

Publications Posted on: July 06, 2018
The ever-increasing volume and accessibility of remote sensing data has spawned many alternative approaches for mapping important environmental features and processes. For example, there are several viable but highly varied strategies for using time series of Landsat imagery to detect changes in forest cover.

Mean composite fire severity metrics computed with Google Earth engine offer improved accuracy and expanded mapping potential

Publications Posted on: June 12, 2018
Landsat-based fire severity datasets are an invaluable resource for monitoring and research purposes. These gridded fire severity datasets are generally produced with pre- and post-fire imagery to estimate the degree of fire-induced ecological change.

How similar are forest disturbance maps derived from different Landsat time series algorithms?

Publications Posted on: September 27, 2017
Disturbance is a critical ecological process in forested systems, and disturbance maps are important for understanding forest dynamics. Landsat data are a key remote sensing dataset for monitoring forest disturbance and there recently has been major growth in the development of disturbance mapping algorithms.

PACFISH/INFISH Biological Opinion (PIBO): Effectiveness Monitoring Program seven-year status report 1998 through 2004

Publications Posted on: May 12, 2016
The PACFISH/INFISH Biological Opinion (PIBO) Effectiveness Monitoring Program was initiated in 1998 to provide a consistent framework for monitoring aquatic and riparian resources on most Forest Service and Bureau of Land Management lands within the Upper Columbia River Basin.

Temporal transferability of LiDAR-based imputation of forest structure attributes

Publications Posted on: October 06, 2015
Forest inventory and planning decisions are frequently informed by LiDAR data. Repeated LiDAR acquisitions offer an opportunity to update forest inventories and potentially improve forest inventory estimates through time.

Novel Kalman filter algorithm for statistical monitoring of extensive landscapes with synoptic sensor data

Publications Posted on: September 29, 2015
Wall-to-wall remotely sensed data are increasingly available to monitor landscape dynamics over large geographic areas. However, statistical monitoring programs that use post-stratification cannot fully utilize those sensor data. The Kalman filter (KF) is an alternative statistical estimator. I develop a new KF algorithm that is numerically robust with large numbers of study variables and auxiliary sensor variables.

Field attributes and satellite indices for "The Relationship of Multispectral Satellite Imagery to Immediate Fire Effects"

Datasets Posted on: August 27, 2015
This data publication contains satellite image-derived burn severity indices as well as fire effects measured after eight large wildfire events in the Western United States.