scholarly journals An Evaluation of Forest Health Insect and Disease Survey Data and Satellite-Based Remote Sensing Forest Change Detection Methods: Case Studies in the United States

2018 ◽  
Vol 10 (8) ◽  
pp. 1184 ◽  
Author(s):  
Ian Housman ◽  
Robert Chastain ◽  
Mark Finco
Keyword(s):  
United States ◽  
Remote Sensing ◽  
New England ◽  
Forest Disturbance ◽  
Forest Health ◽  
Rio Grande ◽  
National Forest ◽  
Forest Change ◽  
Southern New England ◽  
Disease Survey

The Operational Remote Sensing (ORS) program leverages Landsat and MODIS data to detect forest disturbances across the conterminous United States (CONUS). The ORS program was initiated in 2014 as a collaboration between the US Department of Agriculture Forest Service Geospatial Technology and Applications Center (GTAC) and the Forest Health Assessment and Applied Sciences Team (FHAAST). The goal of the ORS program is to supplement the Insect and Disease Survey (IDS) and MODIS Real-Time Forest Disturbance (RTFD) programs with imagery-derived forest disturbance data that can be used to augment traditional IDS data. We developed three algorithms and produced ORS forest change products using both Landsat and MODIS data. These were assessed over Southern New England and the Rio Grande National Forest. Reference data were acquired using TimeSync to conduct an independent accuracy assessment of IDS, RTFD, and ORS products. Overall accuracy for all products ranged from 71.63% to 92.55% in the Southern New England study area and 63.48% to 79.13% in the Rio Grande National Forest study area. While the accuracies attained from the assessed products are somewhat low, these results are similar to comparable studies. Although many ORS products met or exceeded the overall accuracy of IDS and RTFD products, the differences were largely statistically insignificant at the 95% confidence interval. This demonstrates the current implementation of ORS is sufficient to provide data to augment IDS data.

scholarly journals An Evaluation of Forest Health Insect and Disease Survey Data and Satellite-Based Remote Sensing Forest Change Detection Methods: Case Studies in the United States

2018 ◽  
Author(s):  
Ian Housman ◽  
Robert Chastain ◽  
Mark Finco
Keyword(s):  
United States ◽  
Remote Sensing ◽  
New England ◽  
Forest Disturbance ◽  
Forest Health ◽  
Rio Grande ◽  
National Forest ◽  
Forest Change ◽  
Southern New England ◽  
Disease Survey

The Operational Remote Sensing (ORS) program leverages Landsat and MODIS data to detect forest disturbances across the conterminous United States (CONUS). The ORS program was initiated in 2014 as a collaboration between the US Department of Agriculture Forest Service Geospatial Technology and Applications Center (GTAC) and the Forest Health Assessment and Applied Sciences Team (FHAAST). The goal of the ORS program is to supplement the Insect and Disease Survey (IDS) and MODIS Real-Time Forest Disturbance (RTFD) programs with imagery-derived forest disturbance data that can be used to augment traditional IDS data. We developed three algorithms and produced ORS forest change products using both Landsat and MODIS data. These were assessed over Southern New England and the Rio Grande National Forest. Reference data were acquired using TimeSync to conduct an independent accuracy assessment of IDS, RTFD, and ORS products. Overall accuracy for all products ranged from 77.64% to 93.51% (kappa 0.09–0.59) in the Southern New England study area and 59.57% to 79.57% (kappa 0.09–0.45) in the Rio Grande National Forest study area. In general, ORS products met or exceeded the overall accuracy and kappa of IDS and RTFD products. This demonstrates the current implementation of ORS is sufficient to provide data to augment IDS data.

The Post-Deportation Human Rights Project: Participatory Action Research with Maya Transnational Families

2012 ◽  
Vol 34 (1) ◽  
pp. 22-26 ◽  
Author(s):  
M. Lykes ◽  
Erin McDonald ◽  
Cesar Boc
Keyword(s):  
United States ◽  
Human Rights ◽  
New England ◽  
Well Being ◽  
The United States ◽  
Immigrant Parents ◽  
Transnational Families ◽  
Southern New England ◽  
Immigrant Organizations ◽  
The Right

As the number of immigrants in the United States has increased dramatically in recent decades, so has the number of human rights violations against immigrants in the form of arrests without warrants, detention and deportation of parents without consideration of the well-being of their children, and incarceration without bail or the right to a public attorney. The Post-Deportation Human Rights Project (PDHRP) at Boston College was developed to investigate and respond to the legal and psychological effects of deportation policies on migrants living in or deported from the United States. This unique multidisciplinary project involves lawyers, social science faculty, and graduate students—all of whom are bilingual, one of whom is trilingual, and many of whom are bicultural—working together in partnership with local immigrant organizations to address the psychosocial impact of deportation on Latino and Maya families and communities. Our work includes psycho-educational and rights education workshops with immigrant parents and their children in southern New England as well as a cross-national project based in the U.S. and Guatemala supporting transnational families through participatory research, educational workshops, and legal resources.

ARNEWS assesses the health of Canada's forests

1995 ◽  
Vol 71 (5) ◽  
pp. 607-613 ◽  
Author(s):  
J. Peter Hall
Keyword(s):  
Sustainable Management ◽  
Large Scale ◽  
Forest Health ◽  
Warning System ◽  
Monitoring Network ◽  
National Forest ◽  
Forest Insect ◽  
Ecosystem Monitoring ◽  
Disease Survey ◽  
Observed Damage

In 1984 the Canadian Forest Service (CFS) established the Acid Rain National Early Warning System (ARNEWS) to monitor the state of health of Canada's forests. This program was implemented by the CFS Forest Insect and Disease Survey (FIDS) who survey the plots annually and determine the causes of observed damage. For the period, 1984-1994, the survey indicates that there has been no large-scale decline in the health of Canada's forests. Insects, diseases and abiotic conditions have impacted forests, and isolated cases of damage caused by air pollution have been observed. The presence of unknown damage is also being investigated to determine if pollution is involved. The results of this survey support the need for a national forest health monitoring network as part of sustainable management of Canadian forests. Key words: forest health, forest surveys, sustainable forestry, ecosystem monitoring

scholarly journals Object-Based Classification of Forest Disturbance Types in the Conterminous United States

2019 ◽  
Vol 11 (5) ◽  
pp. 477 ◽  
Author(s):  
Lian-Zhi Huo ◽  
Luigi Boschetti ◽  
Aaron Sparks
Keyword(s):  
United States ◽  
Forest Cover ◽  
Forest Disturbance ◽  
Global Scale ◽  
Management Policy ◽  
Forest Loss ◽  
Forest Cover Change ◽  
Forest Change ◽  
Goods And Services ◽  
Moderate Resolution Imaging Spectroradiometer

Forest ecosystems provide critical ecosystem goods and services, and any disturbance-induced changes can have cascading impacts on natural processes and human socioeconomic systems. Forest disturbance frequency, intensity, and spatial and temporal scale can be altered by changes in climate and human activity, but without baseline forest disturbance data, it is impossible to quantify the magnitude and extent of these changes. Methodologies for quantifying forest cover change have been developed at the regional-to-global scale via several approaches that utilize data from high (e.g., IKONOS, Quickbird), moderate (e.g., Landsat) and coarse (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) spatial resolution satellite imagery. While detection and quantification of forest cover change is an important first step, attribution of disturbance type is critical missing information for establishing baseline data and effective land management policy. The objective here was to prototype and test a semi-automated methodology for characterizing high-magnitude (>50% forest cover loss) forest disturbance agents (stress, fire, stem removal) across the conterminous United States (CONUS) from 2003–2011 using the existing University of Maryland Landsat-based Global Forest Change Product and Web-Enabled Landsat Data (WELD). The Forest Cover Change maps were segmented into objects based on temporal and spatial adjacency, and object-level spectral metrics were calculated based on WELD reflectance time series. A training set of objects with known disturbance type was developed via high-resolution imagery and expert interpretation, ingested into a Random Forest classifier, which was then used to attribute disturbance type to all 15,179,430 forest loss objects across CONUS. Accuracy assessments of the resulting classification was conducted with an independent dataset consisting of 4156 forest loss objects. Overall accuracy was 88.1%, with the highest omission and commission errors observed for fire (32.8%) and stress (31.9%) disturbances, respectively. Of the total 172,686 km2 of forest loss, 83.75% was attributed to stem removal, 10.92% to fire and 5.33% to stress. The semi-automated approach described in this paper provides a promising framework for the systematic characterization and monitoring of forest disturbance regimes.

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

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1364
Author(s):  
Andrew J. Lister ◽  
Hans Andersen ◽  
Tracey Frescino ◽  
Demetrios Gatziolis ◽  
Sean Healey ◽  
...  
Keyword(s):  
United States ◽  
Remote Sensing ◽  
Natural Resource ◽  
Forest Inventory ◽  
The United States ◽  
National Forest ◽  
Forest Inventories ◽  
National Forest Inventories ◽  
Sampling Statistics

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’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’s experience with NFI-RS integration as a case study for other countries wishing to improve the efficiency of their NFI programs.

scholarly journals THE MARCH 1962 STORM ON THE ATLANTIC COAST OF THE UNITED STATES

2011 ◽  
Vol 1 (8) ◽  
pp. 32
Author(s):  
M.P. O'Brien ◽  
J.W. Johnson
Keyword(s):  
United States ◽  
New England ◽  
Storm Surge ◽  
Atlantic Coast ◽  
Large Diameter ◽  
The United States ◽  
Storm Damage ◽  
Southern New England ◽  
Cape Hatteras ◽  
Moving Storm

As far back as 1635, records show that the East Coast of the United States has repeatedly suffered from severe storm damage (McAleer , 1962). Most of these storms appear to have been of the hurricane type. Such storms generally form in the Atlantic to the east of the Bahama Islands and move eastward and then turn northward to sweep along the Atlantic Coast line (Fig. 1). Along the southern part of the Atlantic Coast the hurricanes move relatively slowly; damage results principally from flooding caused by direct wind action. North of Cape Hatteras the hurricanes move more rapidly (speeds of 40 to 50 miles per hour) and damage is largely due to sudden flooding from a rapidly moving storm surge (Simpson, 1962). The combination of storm surge, wind-driven water, and storm waves inundating large areas along the coast has on numerous occasions caused great damage and loss of life. The great Atlantic Coast storm of March 1962, however, differed in character from the usual hurricane. It proved to be the most disastrous winter coastal storm on record, causing damage from southern New England to Florida. This storm, of relatively large diameter and having gale force winds, remained nearly stationary off the Coast for almost 36 hours . The size and location of the storm, as further discussed below, was such that persistent strong northeasterly winds blowing over a relatively long fetch raised the spring tides (maximum range) to near-record levels. The tidal flooding which attended this storm was in many ways more disastrous than that which accompanies hurricanes (Cooperman and Rosendal, 1962). The storm surge in tropical cyclones generally recedes rapidly after one or two high tides, but the surge accompanying this storm occurred in many locations on four and five successive high tides .' The great destruction was caused by high waves and breakers superimposed on these high tides.

Traditions and Customs of Lancashire Popular Radicalism in Late Nineteenth-Century Industrial America

1992 ◽  
Vol 42 ◽  
pp. 5-19 ◽  
Author(s):  
Mary H. Blewett
Keyword(s):  
United States ◽  
New England ◽  
Rhode Island ◽  
The United States ◽  
Late Nineteenth Century ◽  
Textile Workers ◽  
Labor Politics ◽  
Southern New England ◽  
Before And After ◽  
Late Nineteenth

During a decade of constant turmoil in the 1870s, immigrant textile workers from Lancashire, England seized control of labor politics in the southern New England region of the United States. They were men and women who had immigrated in successive waves before and after the American Civil War to the United States, specifically to the textile cities of Fall River and New Bedford, Massachusetts and to the mill villages north of Providence, Rhode Island.

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