Discussion on “Spatial patterns of precipitation quantity and chemistry and air temperatures in the Adirondack region of New York”

2003 ◽  
Vol 37 (1) ◽  
pp. 129-133 ◽  
Author(s):  
Gopal Sistla ◽  
Kevin Civerolo ◽  
Phil Galvin
Keyword(s):  
New York ◽  
Spatial Patterns ◽  
Air Temperatures

scholarly journals Spatial patterns of mercury in biota of Adirondack, New York lakes

Ecotoxicology ◽  
2011 ◽  
Vol 20 (7) ◽  
pp. 1543-1554 ◽  
Author(s):  
Xue Yu ◽  
Charles T. Driscoll ◽  
Mario Montesdeoca ◽  
David Evers ◽  
Melissa Duron ◽  
...  
Keyword(s):  
New York ◽  
Spatial Patterns

scholarly journals A Study on the GIS Professional (GISP) Certification Program in the U.S.

2020 ◽  
Vol 9 (9) ◽  
pp. 523
Author(s):  
Dapeng Li ◽  
Yingru Li ◽  
Quynh C. Nguyen ◽  
Laura K. Siebeneck
Keyword(s):  
New York ◽  
Spatial Patterns ◽  
Urban Areas ◽  
The United States ◽  
Washington Dc ◽  
Certification Program ◽  
Managerial Role ◽  
Current State ◽  
Shed Light ◽  
The U.S

This study examines the characteristics of the members in the most popular Geographic Information Systems (GIS) Professional (GISP) certification program in the United States as well as the spatial patterns of the certified GISPs. The results show that the majority of GISPs (97.3%) are located in urban areas. About 75% of the GISPs are male. Among all the GISPs, 3971 GISPs (43.3%) play a managerial role, while 4983 individuals (54.5%) assume a non-administrative role. Among the GISPs with a non-administrative role, 348 GISPs (7%) fall within the GIS Developer group, 3392 GISPs (68%) belong to the GIS Analyst group, and 1243 GISPs (25%) play other roles. Additionally, in our analysis of spatial patterns, we identified two hotspots and two coldspots. The first hotspot is centered around Idaho and Wyoming, while the second hotspot includes Virginia, Washington DC, and Maryland. One coldspot is along Iowa, Missouri, Arkansas, and Louisiana in the central U.S., while the other coldspot includes states such as Connecticut, New Jersey, and New York on the east coast. The information presented in this study can help GIS educators and practitioners develop a better understanding of the current state of this certification program in the U.S and shed light on how to further improve the GISP certification program.

scholarly journals A Modification to the NOAH LSM to Simulate Heat Mitigation Strategies in the New York City Metropolitan Area

2009 ◽  
Vol 48 (2) ◽  
pp. 199-216 ◽  
Author(s):  
Barry H. Lynn ◽  
Toby N. Carlson ◽  
Cynthia Rosenzweig ◽  
Richard Goldberg ◽  
Leonard Druyan ◽  
...  
Keyword(s):  
New York ◽  
New York City ◽  
Thermal Stress ◽  
York City ◽  
Atmospheric Model ◽  
Mitigation Strategies ◽  
Local Exchange ◽  
Street Level ◽  
Air Temperatures ◽  
Roughness Lengths

Abstract A new approach to simulating the urban environment with a mesocale model has been developed to identify efficient strategies for mitigating increases in surface air temperatures associated with the urban heat island (UHI). A key step in this process is to define a “global” roughness for the cityscape and to use this roughness to diagnose 10-m temperature, moisture, and winds within an atmospheric model. This information is used to calculate local exchange coefficients for different city surface types (each with their own “local roughness” lengths); each surface’s energy balances, including surface air temperatures, humidity, and wind, are then readily obtained. The model was run for several summer days in 2001 for the New York City five-county area. The most effective strategy to reduce the surface radiometric and 2-m surface air temperatures was to increase the albedo of the city (impervious) surfaces. However, this caused increased thermal stress at street level, especially noontime thermal stress. As an alternative, the planting of trees reduced the UHI’s adverse effects of high temperatures and also reduced noontime thermal stress on city residents (and would also have reduced cooling energy requirements of small structures). Taking these results together, the analysis suggests that the best mitigation strategy is planting trees at street level and increasing the reflectivity of roofs.

scholarly journals How well does Predictive Soil Mapping represent soil geography? An investigation from the USA

2021 ◽  
Author(s):  
David G. Rossiter ◽  
Laura Poggio ◽  
Dylan Beaudette ◽  
Zamir Libohova
Keyword(s):  
New York ◽  
Soil Properties ◽  
Spatial Patterns ◽  
Landscape Metrics ◽  
New York State ◽  
Histogram Equalization ◽  
Soil Mapping ◽  
Partial Replacement ◽  
Field Surveys ◽  
The Usa

Abstract. We present methods to evaluate the spatial patterns of the geographic distribution of soil properties in the USA, as shown in gridded maps produced by Predictive Soil Mapping (PSM) at global (SoilGrids v2), national (Soil Properties and Class 100 m Grids of the USA), and regional (POLARIS soil properties) scales, and compare them to spatial patterns known from detailed field surveys (gSSURGO). The methods are illustrated with an example: topsoil pH for an area in central New York State. A companion report examines other areas, soil properties, and depth slices. A set of R Markdown scripts is referenced so that readers can apply the analysis for areas of their interest. For the test case we discover and discuss substan- tial discrepancies between PSM products, as well as large differences between the PSM products and legacy field surveys. These differences are in whole-map statistics, visually-identifiable landscape features, level of detail, range and strength of spatial autocorrelation, landscape metrics (Shannon diversity and evenness, shape, aggregation, mean fractal dimension, co-occurence vectors), and spatial patterns of property maps classified by histogram equalization. Histograms and variogram analysis revealed the smoothing effect of machine-learning models. Property class maps made by histogram equalization were substantially different, but there was no consistent trend in their landscape metrics. The model using only national points and covariates was not better than the global model, and in some cases introduced artefacts from a lithology covariate. Uncertainty (5–95% confidence intervals) provided by SoilGrids and POLARIS were unrealistically wide compared to gSSURGO low and high estimated values and show substantially different spatial patterns. We discuss the potential use of the PSM products as a (partial) replacement for field-based soil surveys.

scholarly journals Stemphylium Leaf Blight: A Re-Emerging Threat to Onion Production in Eastern North America

Plant Disease ◽  
2021 ◽  
Author(s):  
Frank Hay ◽  
Sara Marie Stricker ◽  
Bruce Gossen ◽  
Mary Ruth McDonald ◽  
Daniel Heck ◽  
...  
Keyword(s):  
New York ◽  
North America ◽  
Management Strategies ◽  
Early Spring ◽  
Leaf Blight ◽  
Eastern North America ◽  
Resistance Development ◽  
Air Temperatures ◽  
Pleospora Allii ◽  
Prediction Systems

Stemphylium leaf blight (SLB), caused by Stemphylium vesicarium, is a foliar disease of onion worldwide, and has recently become an important disease in the northeastern United States and Ontario, Canada. The symptoms begin as small, tan to brown lesions on the leaves that can progress to defoliate plants. Crop loss occurs through reduced photosynthetic area, resulting in smaller, lower-quality bulbs. Leaf necrosis caused by SLB also can compromise bulb storage, as green leaves are required for the uptake of sprout inhibitors applied prior to harvest. The pathogen can overwinter on infested onion residue and infected volunteer plants. Asymptomatic weedy hosts near onion fields may also be a source of inoculum. Production of ascospores of the teleomorph (Pleospora allii) peaks in early spring in northeastern North America, often before the crop is planted, and declines rapidly as daily mean air temperatures rise. Conidia usually are present throughout the growing season. Application of fungicides is a standard practice for management of the complex of fungi that can cause foliar diseases of onion in this region. Recent assessments have shown that populations of S. vesicarium in New York and Ontario are resistant to at least three single-site mode-of-action fungicides. Three disease prediction systems have been developed and evaluated that may enable growers to reduce the frequency and/or number of fungicide applications, but the loss of efficacious fungicides due to resistance development within S. vesicarium populations threatens sustainability. The lack of commercially acceptable onion cultivars with sufficient resistance to reduce the number of fungicides for SLB also limits the ability to manage SLB effectively. Integrated disease management strategies for SLB are essential to maintain profitable, sustainable onion production across eastern North America.

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