TOWARDS A BETTTER UNDERSTANDING OF FOREST CHANGE PROCESSES IN THE CONTIGUOUS U.S.

Estimates of forest canopy areal extent, configuration and change have been developed from satellite based imagery and ground based inventories to improve understanding of forest dynamics and how they interact with other earth systems across many scales. The number of these types of studies has grown in recent years. Yet, few have assessed the multiple change processes underlying observed forest canopy dynamics across large spatio-temporal extents. To support these types of assessments, a more detailed and integrated understanding of the geographic patterns of the multiple forest change processes across the contiguous US (CONUS) is needed. This study examined a novel data set from the North American Forest dynamics (NAFD) project that provides a dense temporal record (1984-2005) of forest canopy history across the U.S., United States Forest Service (USFS) ground inventory data, and ancillary geospatial data sets on forest change processes (wind, insect, fire, harvest and conversion to suburban/urban land uses) across the CONUS to develop a more robust understanding of the implications of the shifting dynamics of forest change processes and our ability to measure their effect on forest canopy dynamics. A geodatabase of forest change processes was created to support synoptic and specific quantitative analysis of change processes support through space and time. Using the geodatabase, patterns of forest canopy losses from NAFD and USFS data and the underlying causal process were analyzed across multiple scales. This research has shown that the overlap of multiple disturbance processes leads to complex patterns across the nation's forested landscape that can only be fully understood in relation to forest canopy losses at fine scales. Regional statistics confounded the direction and magnitude of forest canopy loss from multiple change processes operating on the landscape. Data gaps and uncertainty associated with process data prevent a full quantitative analysis of the proportion of forest area affected by each forest change process considered here. Fine scale data were critical for interpreting the highly variable NAFD canopy change observations and their ability to capture the continuously changing spatial and temporal characteristics of forest change processes across the CONUS

United States Forest Disturbance Trends Observed Using Landsat Time Series

Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing U.S. land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest disturbance across the conterminous United States for 1985-2005. The geographic sample design used a probability-based scheme to encompass major forest types and maximize geographic dispersion. For each sample location disturbance was identified in the Landsat series using the Vegetation Change Tracker (VCT) algorithm. The NAFD analysis indicates that, on average, 2.77 Mha/yr of forests were disturbed annually, representing 1.09%/yr of US forestland. These satellite-based national disturbance rates estimates tend to be lower than those derived from land management inventories, reflecting both methodological and definitional differences. In particular the VCT approach used with a biennial time step has limited sensitivity to low-intensity disturbances. Unlike prior satellite studies, our biennial forest disturbance rates vary by nearly a factor of two between high and low years. High western US disturbance rates were associated with active fire years and insect activity, while variability in the east is more strongly related to harvest rates in managed forests. We note that generating a geographic sample based on representing forest type and variability may be problematic since the spatial pattern of disturbance does not necessarily correlate with forest type. We also find that the prevalence of diffuse, non-stand clearing disturbance in US forests makes the application of a biennial geographic sample problematic. Future satellite-based studies of disturbance at regional and national scales should focus on wall-to-wall analyses with annual time step for improved accuracy

Forest Area Change in the Shifting Landscape Mosaic of the Continental United States from 2001 to 2016

The landscape context (i.e., anthropogenic setting) of forest change partly determines the social-ecological outcomes of the change. Furthermore, forest change occurs within, is constrained by, and contributes to a dynamic landscape context. We illustrate how information about local landscape context can be incorporated into regional assessments of forest area change. We examined the status and change of forest area in the continental United States from 2001 to 2016, quantifying landscape context by using a landscape mosaic classification that describes the dominance and interface (i.e., juxtaposition) of developed and agriculture land in relation to forest and other land. The mosaic class changed for five percent of total land area and three percent of total forest area. The least stable classes were those comprising the developed interface. Forest loss rates were highest in developed-dominated landscapes, but the forest area in those landscapes increased by 18 percent as the expansion of developed landscapes assimilated more forest area than was lost from earlier developed landscapes. Conversely, forest loss rates were lowest in agriculture-dominated landscapes where there was a net loss of five percent of forest area, even as the area of those landscapes also increased. Exposure of all land to nearby forest removal, fire, and stress was highest in natural-dominated landscapes, while exposure to nearby increases in developed and agriculture land was highest in developed- and agriculture-dominated landscapes. We discuss applications of our approach for mapping, monitoring, and modeling landscape and land use change

Integration of VIIRS Observations with GEDI-Lidar Measurements to Monitor Forest Structure Dynamics from 2013 to 2020 across the Conterminous United States

Consistent and spatially explicit periodic monitoring of forest structure is essential for estimating forest-related carbon emissions, analyzing forest degradation, and supporting sustainable forest management policies. To date, few products are available that allow for continental to global operational monitoring of changes in canopy structure. In this study, we explored the synergy between the NASA’s spaceborne Global Ecosystem Dynamics Investigation (GEDI) waveform LiDAR and the Visible Infrared Imaging Radiometer Suite (VIIRS) data to produce spatially explicit and consistent annual maps of canopy height (CH), percent canopy cover (PCC), plant area index (PAI), and foliage height diversity (FHD) across the conterminous United States (CONUS) at a 1-km resolution for 2013–2020. The accuracies of the annual maps were assessed using forest structure attribute derived from airborne laser scanning (ALS) data acquired between 2013 and 2020 for the 48 National Ecological Observatory Network (NEON) field sites distributed across the CONUS. The root mean square error (RMSE) values of the annual canopy height maps as compared with the ALS reference data varied from a minimum of 3.31-m for 2020 to a maximum of 4.19-m for 2017. Similarly, the RMSE values for PCC ranged between 8% (2020) and 11% (all other years). Qualitative evaluations of the annual maps using time series of very high-resolution images further suggested that the VIIRS-derived products could capture both large and “more” subtle changes in forest structure associated with partial harvesting, wind damage, wildfires, and other environmental stresses. The methods developed in this study are expected to enable multi-decadal analysis of forest structure and its dynamics using consistent satellite observations from moderate resolution sensors such as VIIRS onboard JPSS satellites

Integration of VIIRS Observations with GEDI-Lidar Measurements to Monitor Forest Structure Dynamics from 2013 to 2020 across the Conterminous United States

Consistent and spatially explicit periodic monitoring of forest structure is essential for estimating forest-related carbon emissions, analyzing forest degradation, and supporting sustainable forest management policies. To date, few products are available that allow for continental to global operational monitoring of changes in canopy structure. In this study, we explored the synergy between the NASA’s spaceborne Global Ecosystem Dynamics Investigation (GEDI) waveform LiDAR and the Visible Infrared Imaging Radiometer Suite (VIIRS) data to produce spatially explicit and consistent annual maps of canopy height (CH), percent canopy cover (PCC), plant area index (PAI), and foliage height diversity (FHD) across the conterminous United States (CONUS) at a 1-km resolution for 2013–2020. The accuracies of the annual maps were assessed using forest structure attribute derived from airborne laser scanning (ALS) data acquired between 2013 and 2020 for the 48 National Ecological Observatory Network (NEON) field sites distributed across the CONUS. The root mean square error (RMSE) values of the annual canopy height maps as compared with the ALS reference data varied from a minimum of 3.31-m for 2020 to a maximum of 4.19-m for 2017. Similarly, the RMSE values for PCC ranged between 8% (2020) and 11% (all other years). Qualitative evaluations of the annual maps using time series of very high-resolution images further suggested that the VIIRS-derived products could capture both large and “more” subtle changes in forest structure associated with partial harvesting, wind damage, wildfires, and other environmental stresses. The methods developed in this study are expected to enable multi-decadal analysis of forest structure and its dynamics using consistent satellite observations from moderate resolution sensors such as VIIRS onboard JPSS satellites.https://doi.org/10.3390/rs1410232

Forest connectivity from binary and grayscale maps

GeoTIFF images used in the paper "Improving forest connectivity assessments using tree cover density maps" which were derived from the Copernicus 2018 Tree Cover Density dataset. Forest connectivity was derived with the open-source software GWB, see the included readme.txt for further information.</p

Regional dynamics of forest canopy change and underlying causal processes in the contiguous U.S.

The history of forest change processes is written into forest age and distribution and affects earth systems at many scales. No one data set has been able to capture the full forest disturbance and land use record through time, so in this study, we combined multiple lines of evidence to examine trends, for six US regions, in forest area affected by harvest, fire, wind, insects, and forest conversion to urban/surburban use. We built an integrated geodatabase for the contiguous U.S. (CONUS) with data spanning the nation and decades, from remote sensing observations of forest canopy dynamics, geospatial data sets on disturbance and conversion, and statistical inventories, to evaluate relationships between canopy change observations and casual processes at multiple scales. Results show the variability of major change processes through regions across decades. Harvest affected more forest area than any other major change processes in the North East, North Central, Southeast, and South central regions. In the Pacific Coast and Intermountain West, more forest area was affected by harvest than forest fires. Canopy change rates at regional scales confounded the trends of individual forest change processes, showing the importance of landscape scale data. Local spikes in observed canopy change rates were attributed to wind and fire events, as well as volatile harvest regimes. This study improves the geographic model of forest change processes by updating regional trends for major disturbance and conversion processes and combining data on the dynamics of fire, wind, insects, harvest, and conversion into one integrated geodatabase for the CONUS.Keywords: NAFD, harvest, Forest disturbance, time-series, Landsa

United States Forest Disturbance Trends Observed Using Landsat Time Series

Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing US land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest disturbance across the conterminous United States for 1985-2005. The geographic sample design used a probability-based scheme to encompass major forest types and maximize geographic dispersion. For each sample location disturbance was identified in the Landsat series using the Vegetation Change Tracker (VCT) algorithm. The NAFD analysis indicates that, on average, 2.77 Mha y⁻¹ of forests were disturbed annually, representing 1.09% y⁻¹ of US forestland. These satellite-based national disturbance rates estimates tend to be lower than those derived from land management inventories, reflecting both methodological and definitional differences. In particular, the VCT approach used with a biennial time step has limited sensitivity to low-intensity disturbances. Unlike prior satellite studies, our biennial forest disturbance rates vary by nearly a factor of two between high and low years. High western US disturbance rates were associated with active fire years and insect activity, whereas variability in the east is more strongly related to harvest rates in managed forests. We note that generating a geographic sample based on representing forest type and variability may be problematic because the spatial pattern of disturbance does not necessarily correlate with forest type. We also find that the prevalence of diffuse, non-stand-clearing disturbance in US forests makes the application of a biennial geographic sample problematic. Future satellite-based studies of disturbance at regional and national scales should focus on wall-to-wall analyses with annual time step for improved accuracy.Keywords: remote sensing, landsat, forest ecology, forest disturbanc

Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory

Globally, forests are a crucial natural resource, and their sound management is critical for human and ecosystem health and well-being. Efforts to manage forests depend upon reliable data on the status of and trends in forest resources. When these data come from well-designed natural resource monitoring (NRM) systems, decision makers can make science-informed decisions. National forest inventories (NFIs) are a cornerstone of NRM systems, but require capacity and skills to implement. Efficiencies can be gained by incorporating auxiliary information derived from remote sensing (RS) into ground-based forest inventories. However, it can be difficult for countries embarking on NFI development to choose among the various RS integration options, and to develop a harmonized vision of how NFI and RS data can work together to meet monitoring needs. The NFI of the United States, which has been conducted by the USDA Forest Service&rsquo;s (USFS) Forest Inventory and Analysis (FIA) program for nearly a century, uses RS technology extensively. Here we review the history of the use of RS in FIA, beginning with general background on NFI, FIA, and sampling statistics, followed by a description of the evolution of RS technology usage, beginning with paper aerial photography and ending with present day applications and future directions. The goal of this review is to offer FIA&rsquo;s experience with NFI-RS integration as a case study for other countries wishing to improve the efficiency of their NFI programs