Detecting the Locations of Brazilian Pepper Trees in the Everglades with a Hyperspectral Sensor

2004 ◽  
Vol 18 (2) ◽  
pp. 437-442 ◽  
Author(s):  
Lawrence W. Lass ◽  
Timothy S. Prather
Keyword(s):  
Remote Sensing ◽  
National Park ◽  
The United States ◽  
Ground Survey ◽  
Scattered Trees ◽  
Brazilian Pepper ◽  
Sensor Detection ◽  
Complete Access ◽  
Western Half ◽  
Hyperspectral Sensor

Brazilian pepper is a small evergreen tree that forms dense colonies. It was introduced for horticultural use in the United States in the early 1800s and was widely distributed in Florida in the late 1920s. Previous remote-sensing projects to detect Brazilian pepper achieved moderate success and warranted additional research using a hyperspectral sensor. Detection with remote sensing is desirable because complete access to ground survey crews is not practical. The western half of the Everglades National Park was imaged at a 5-m spatial resolution with a hyperspectral sensor by Earth Search Sciences Inc. of Kalispell, MT, on December 12, 2000, and January 10, 2001. The sensor has 128 channels and spectral resolution between 450 and 2,500 nm. The purpose of this research was to develop spectral reflectance curves for Brazilian pepper and establish the accuracy of classified images. Classified images showed that a hyperspectral sensor could detect a “pure” Brazilian pepper pixel representing the center of an infestation but not “mixed” Brazilian pepper pixels at the sparsely populated edges. To define the sparse populations, images were classified using a spatial buffer (15- to 100-m radius) based on a low–omissional error image. A 25-m buffer reduced the amount of commissional error for Brazilian pepper in mangrove-dominated forest to 8.2% and buttonwood-dominated forest to 0%. Wider buffers did not significantly improve image accuracy when compared with the 25-m buffer distance. Results indicate that removal crews using hyperspectral images will be able to reliably find the colonies of Brazilian pepper but will not be able to use the images to find isolated scattered trees.

Shale Resources, Parks Conservation, and Contested Public Lands in North Dakota’s Theodore Roosevelt National Park: Is Fracking Booming?

2020 ◽  
Vol 4 (1) ◽  
pp. 1-13
Author(s):  
Miriam R. Aczel ◽  
Karen E. Makuch
Keyword(s):  
National Park ◽  
Oil And Gas ◽  
The United States ◽  
Federal Agencies ◽  
Cultural Significance ◽  
Theodore Roosevelt ◽  
Natural Beauty ◽  
Theodore Roosevelt National Park ◽  
Bakken Shale

This case study analyzes the potential impacts of weakening the National Park Service’s (NPS) “9B Regulations” enacted in 1978, which established a federal regulatory framework governing hydrocarbon rights and extraction to protect natural resources within the parks. We focus on potential risks to national parklands resulting from Executive Orders 13771—Reducing Regulation and Controlling Regulatory Costs [1]—and 13783—Promoting Energy Independence and Economic Growth [2]—and subsequent recent revisions and further deregulation. To establish context, we briefly overview the history of the United States NPS and other relevant federal agencies’ roles and responsibilities in protecting federal lands that have been set aside due to their value as areas of natural beauty or historical or cultural significance [3]. We present a case study of Theodore Roosevelt National Park (TRNP) situated within the Bakken Shale Formation—a lucrative region of oil and gas deposits—to examine potential impacts if areas of TRNP, particularly areas designated as “wilderness,” are opened to resource extraction, or if the development in other areas of the Bakken near or adjacent to the park’s boundaries expands [4]. We have chosen TRNP because of its biodiversity and rich environmental resources and location in the hydrocarbon-rich Bakken Shale. We discuss where federal agencies’ responsibility for the protection of these lands for future generations and their responsibility for oversight of mineral and petroleum resources development by private contractors have the potential for conflict.

From Competition to Cooperation: A History of Canada–US National Park Relations

2019 ◽  
Author(s):  
Terence Young ◽  
Alan MacEachern ◽  
Lary Dilsaver
Keyword(s):  
National Parks ◽  
National Park ◽  
The United States ◽  
The Us ◽  
Park Service ◽  
Settler Societies ◽  
History Of ◽  
Relationship Of ◽  
Flow Of Information ◽  
The Relationship

This essay explores the evolving international relationship of the two national park agencies that in 1968 began to offer joint training classes for protected-area managers from around the world. Within the British settler societies that dominated nineteenth century park-making, the United States’ National Park Service (NPS) and Canada’s National Parks Branch were the most closely linked and most frequently cooperative. Contrary to campfire myths and nationalist narratives, however, the relationship was not a one-way flow of information and motivation from the US to Canada. Indeed, the latter boasted a park bureaucracy before the NPS was established. The relationship of the two nations’ park leaders in the half century leading up to 1968 demonstrates the complexity of defining the influences on park management and its diffusion from one country to another.

scholarly journals Assessment of High Resolution Air Temperature Fields at Rocky Mountain National Park by Combining Scarce Point Measurements with Elevation and Remote Sensing Data

2020 ◽  
Vol 13 (1) ◽  
pp. 113
Author(s):  
Antonio-Juan Collados-Lara ◽  
Steven R. Fassnacht ◽  
Eulogio Pardo-Igúzquiza ◽  
David Pulido-Velazquez
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Air Temperature ◽  
Land Surface ◽  
National Park ◽  
Rocky Mountain ◽  
Rocky Mountain National Park ◽  
Temperature Fields ◽  
Lapse Rate ◽  
Validation Experiment

There is necessity of considering air temperature to simulate the hydrology and management within water resources systems. In many cases, a big issue is considering the scarcity of data due to poor accessibility and limited funds. This paper proposes a methodology to obtain high resolution air temperature fields by combining scarce point measurements with elevation data and land surface temperature (LST) data from remote sensing. The available station data (SNOTEL stations) are sparse at Rocky Mountain National Park, necessitating the inclusion of correlated and well-sampled variables to assess the spatial variability of air temperature. Different geostatistical approaches and weighted solutions thereof were employed to obtain air temperature fields. These estimates were compared with two relatively direct solutions, the LST (MODIS) and a lapse rate-based interpolation technique. The methodology was evaluated using data from different seasons. The performance of the techniques was assessed through a cross validation experiment. In both cases, the weighted kriging with external drift solution (considering LST and elevation) showed the best results, with a mean squared error of 3.7 and 3.6 °C2 for the application and validation, respectively.

Thermal remote sensing of snow cover to identify the extent of hydrothermal areas in Yellowstone National Park

2012 ◽  
Author(s):  
Christopher M. U. Neale ◽  
S. Sivarajan ◽  
A. Masih ◽  
C. Jaworowski ◽  
H. Heasler
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Yellowstone National Park ◽  
National Park ◽  
Thermal Remote Sensing

Foundation News: Impact of the pandemic on the GWB drinking water project in the Nepal Himalaya region

2021 ◽  
Vol 40 (4) ◽  
pp. 242-243
Author(s):  
Kirsten Nicholson ◽  
Klaus Neumann ◽  
Subodh Sharma ◽  
Lakpa Thering Sherpa
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
National Park ◽  
The United States ◽  
High Mountain ◽  
Geologic Mapping ◽  
Global Pandemic ◽  
Vulnerability To Climate Change ◽  
Sagarmatha National Park ◽  
Water Vulnerability

In 2019, after almost a decade of working on water quality in the Himalayas, we submitted a proposal to Geoscientists Without Borders® (GWB) titled “Understanding high mountain aquifers to source drinking water in Sagarmatha National Park.” The project involves a combination of water-quality and quantity measurements, geologic mapping, and an electrical resistivity tomography survey. The goal of the project is to help two communities (Phortse and Lobuche within Sagarmatha National Park in Nepal) minimize their water vulnerability to climate change and earthquakes. The project team includes researchers and students from the United States and Nepal, as well as nongovernmental organizations, government agencies, and community councils. In the proposal, we identified physical health and altitude as the primary risks that could hinder the success of the project. Like everyone else in early 2019, we had no way to foresee the events of 2020, which would almost completely derail our project. Health has turned out to be the major hinderance. The irony of the global pandemic is how much it has impacted the work of the U.S.-based team and how little it has impacted the necessity of the project.

scholarly journals Estimating annual water storage variations in medium-scale (2000–10 000 km<sup>2</sup>) basins using microwave-based soil moisture retrievals

2017 ◽  
Vol 21 (3) ◽  
pp. 1849-1862 ◽  
Author(s):  
Wade T. Crow ◽  
Eunjin Han ◽  
Dongryeol Ryu ◽  
Christopher R. Hain ◽  
Martha C. Anderson
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Water Budget ◽  
Surface Soil ◽  
Water Storage ◽  
Microwave Remote Sensing ◽  
The United States ◽  
Surface Soil Moisture ◽  
Medium Scale ◽  
Annual Water

Abstract. Due to their shallow vertical support, remotely sensed surface soil moisture retrievals are commonly regarded as being of limited value for water budget applications requiring the characterization of temporal variations in total terrestrial water storage (dS ∕ dt). However, advances in our ability to estimate evapotranspiration remotely now allow for the direct evaluation of approaches for quantifying dS ∕ dt via water budget closure considerations. By applying an annual water budget analysis within a series of medium-scale (2000–10 000 km2) basins within the United States, we demonstrate that, despite their clear theoretical limitations, surface soil moisture retrievals derived from passive microwave remote sensing contain statistically significant information concerning dS ∕ dt. This suggests the possibility of using (relatively) higher-resolution microwave remote sensing products to enhance the spatial resolution of dS ∕ dt estimates acquired from gravity remote sensing.

Effects of wildfire on national park visitation and the regional economy: a natural experiment in the Northern Rockies

2013 ◽  
Vol 22 (8) ◽  
pp. 1155 ◽  
Author(s):  
John W. Duffield ◽  
Chris J. Neher ◽  
David A. Patterson ◽  
Aaron M. Deskins
Keyword(s):  
United States ◽  
National Park ◽  
Net Present Value ◽  
Wildland Fire ◽  
The United States ◽  
Management Policy ◽  
Demand Models ◽  
Value Loss ◽  
Park Service ◽  
Observed Behaviour

Federal wildland fire management policy in the United States directs the use of value-based methods to guide priorities. However, the economic literature on the effect of wildland fire on nonmarket uses, such as recreation, is limited. This paper introduces a new approach to measuring the effect of wildfire on recreational use by utilising newly available long-term datasets on the location and size of wildland fire in the United States and observed behaviour over time as revealed through comprehensive National Park Service (NPS) visitor data. We estimate travel cost economic demand models that can be aggregated at the site-landscape level for Yellowstone National Park (YNP). The marginal recreation benefit per acre of fire avoided in, or proximate to, the park is US$43.82 per acre (US$108.29 per hectare) and the net present value loss for the 1986–2011 period is estimated to be US$206 million. We also estimate marginal regional economic impacts at US$36.69 per acre (US$90.66 per hectare) and US$159 million based on foregone non-resident spending in the 17-county Great Yellowstone Area (GYA). These methods are applicable where time-series recreation data exist, such as for other parks and ecosystems represented in the 397-unit NPS system.

scholarly journals Accuracies Achieved in Classifying Five Leading World Crop Types and their Growth Stages Using Optimal Earth Observing-1 Hyperion Hyperspectral Narrowbands on Google Earth Engine

2018 ◽  
Vol 10 (12) ◽  
pp. 2027 ◽  
Author(s):  
Itiya Aneece ◽  
Prasad Thenkabail
Keyword(s):  
United States ◽  
Remote Sensing ◽  
Hyperspectral Imaging ◽  
The United States ◽  
Google Earth ◽  
Growth Stages ◽  
Agricultural Crops ◽  
Spectral Library ◽  
Crop Types ◽  
Google Earth Engine

As the global population increases, we face increasing demand for food and nutrition. Remote sensing can help monitor food availability to assess global food security rapidly and accurately enough to inform decision-making. However, advances in remote sensing technology are still often limited to multispectral broadband sensors. Although these sensors have many applications, they can be limited in studying agricultural crop characteristics such as differentiating crop types and their growth stages with a high degree of accuracy and detail. In contrast, hyperspectral data contain continuous narrowbands that provide data in terms of spectral signatures rather than a few data points along the spectrum, and hence can help advance the study of crop characteristics. To better understand and advance this idea, we conducted a detailed study of five leading world crops (corn, soybean, winter wheat, rice, and cotton) that occupy 75% and 54% of principal crop areas in the United States and the world respectively. The study was conducted in seven agroecological zones of the United States using 99 Earth Observing-1 (EO-1) Hyperion hyperspectral images from 2008–2015 at 30 m resolution. The authors first developed a first-of-its-kind comprehensive Hyperion-derived Hyperspectral Imaging Spectral Library of Agricultural crops (HISA) of these crops in the US based on USDA Cropland Data Layer (CDL) reference data. Principal Component Analysis was used to eliminate redundant bands by using factor loadings to determine which bands most influenced the first few principal components. This resulted in the establishment of 30 optimal hyperspectral narrowbands (OHNBs) for the study of agricultural crops. The rest of the 242 Hyperion HNBs were redundant, uncalibrated, or noisy. Crop types and crop growth stages were classified using linear discriminant analysis (LDA) and support vector machines (SVM) in the Google Earth Engine cloud computing platform using the 30 optimal HNBs (OHNBs). The best overall accuracies were between 75% to 95% in classifying crop types and their growth stages, which were achieved using 15–20 HNBs in the majority of cases. However, in complex cases (e.g., 4 or more crops in a Hyperion image) 25–30 HNBs were required to achieve optimal accuracies. Beyond 25–30 bands, accuracies asymptote. This research makes a significant contribution towards understanding modeling, mapping, and monitoring agricultural crops using data from upcoming hyperspectral satellites, such as NASA’s Surface Biology and Geology mission (formerly HyspIRI mission) and the recently launched HysIS (Indian Hyperspectral Imaging Satellite, 55 bands over 400–950 nm in VNIR and 165 bands over 900–2500 nm in SWIR), and contributions in advancing the building of a novel, first-of-its-kind global hyperspectral imaging spectral-library of agricultural crops (GHISA: www.usgs.gov/WGSC/GHISA).

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