Mark W. Jackson

Quantitative phosphorus measurement: A field test procedure for archaeological site analysis at Piedras Negras, Guatemala

Currently there is a wide interest in the use of chemical analyses for the evaluation of anthropogenically altered soils and other archaeological deposits. Because soil phosphorus levels increase in areas of human habitation, and leave a permanent signature that can only be removed by erosion of the soil itself, phosphorus mapping has become a popular field procedure to indicate areas of habitation where overt evidence of ancient occupance is absent. We have developed a methodology to obtain accurate acid-extractable phosphorus concentrations (mg/kg) in calcareous soils under the primitive field conditions of Piedras Negras, Guatemala. Predicated on Mehlich-II acid extractant and colorimetric methods, this procedure processed 36 samples per hour at very low cost per sample. Based on eight replicate measurements of a group of samples, the coefficient of variation of the procedure was 8.3%. Subsequent analysis of 35 soil samples in a controlled laboratory revealed a moderate correlation of 0.44 between the Mehlich-extractable phosphorus and total phosphorus. The correlation was 0.91 between the Mehlich procedure and Olsen bicarbonate extractable phosphorus, indicating that Mehlich-based results are similar to those obtainable using a traditional extractable phosphorus method on soils of neutral to alkaline pH. There was a moderate correlation between Mehlich P and ring-test rating (r = 0.42). The wider dynamic range of the Mehlich extraction, coupled with the use of a battery-operated colorimeter, facilitated the finding of a refuse midden within an area of phosphate enriched soils. Further tests indicated that phosphorus concentrations measured in the field deviated by only 7% from those made under controlled laboratory conditions.

An Unmanned Aerial Vehicle for Rangeland Photography

Abstract Because of its perceived impracticality and expense, aerial photography from unmanned aerial vehicles (UAVs) remains virtually unused as a rangeland management tool. This underuse suggested 2 objectives. The first was to develop a UAV from off-the-shelf components that could acquire low-altitude large-scale photography for rangeland documentation. The second was to assess the UAV flight characteristics. A remotely controlled UAV suitable for 35-mm photography was built in 56 hours at a cost of

Mapping, Measuring, and Modeling Urban Growth

1 480. In a 2-year test period, the UAV successfully completed 100+ sorties at elevations ranging from 10 m to 1 000 m above ground. The average distance required for takeoff is 18.2 m whereas landing requires an average of 22.5 m. Average UAV airspeed at takeoff is about 11.4 m·s−1. Typical cruise speed during photograph acquisition is 13.8 m·s−1, resulting in 6.9 mm of blur from forward-image motion. The UAV is an inexpensive tool for monitoring rangeland condition from an aerial perspective. It is currently being used to map squarrose knapweed (Centaurea virgata Lam. ssp. squarrosa Gugl.) density at several rangeland sites in Utah.

Investigating SeaWinds Terrestrial Backscatter: Equatorial Savannas of South America

Immediately after World War II, developers in the United States took advantage of market demand and government incentives to build new housing subdivisions for returning soldiers anxious to marry, begin families, and resume civilian life. New developments such as Levittown (New York), Park Forest (Illinois) and Lakewood (California)1 sprang up and were quickly filled with affordable cookie-cutter homes for veterans seeking the American Dream of suburban home ownership (Hayden 2003). The baby boom followed. As a result of the boom and international immigration, the U.S. population grew from 151 million to 300 million between 1950 and 2007. To accommodate this expanding population growth, cities and towns in the U.S. rapidly spread into their rural hinterlands.

Students Assessment of a Semidirected Internship Program

Because tropical grasslands play an important role in the storage of global carbon, monitoring them is critical to evaluating global climate change. The goal of this research is to model seasonal SeaWinds Ku-band backscatter in five savanna areas of Colombia, Venezuela, and Brazil as a function of biophysical changes in the savanna landscape. Multiple regression modeling demonstrates that savanna Ku-band backscatter is a function of (1) savanna grass biomass/leaf area, (2) soil moisture, and (3) other soil characteristics. Fit for the regression models is excellent (R � 0.87 and 0.81, respectively, for the horizontal and vertical polarization case). The horizontal—vertical polarization difference is also moderately related to precipitation (R � 0.71). The results from this modeling are consistent with theory predicated on previous C- and X-band research. The possibility of monitoring savanna vegetation, soil moisture, and rainfall using Ku-band radar and scatterometry is discussed.

Single line correction method to remove aircraft roll errors in hyperspectral imagery

Abstract Internships can be a valuable experience for geography majors, helping them confirm their choice of an area of emphasis in the discipline, giving them real world experience, and providing contacts that can help them gain full-time employment. This article examines student perception of the relative effectiveness of a semidirected internship program. The program relies on students finding their own internship rather than on programmatic linkages between a department and an employer. Analysis of survey responses of students completing the internship program over a five-year period indicates that students viewed their intern experience very positively, with the least satisfaction related to the level of constructive criticism they received of their work and involvement in discussion of their completed work assignments.

Modelling housing unit density from land cover metrics: a Midwestern US example

Hyperspectral data acquired using airborne push-broom sensors frequently contain geometric distortion caused by aircraft motion. This paper presents a simple single reference line algorithm to correct push-broom imagery for geometric distortions resulting from aircraft roll during the scan period. If a straight line is not available throughout the entire image, multiple lines may be drawn to correct the entire image. The algorithm was applied to two hyperspectral urban images (Terre Haute, Indiana, USA and Provo, Utah, USA) acquired during summer 2006. The results demonstrate that this method is an effective way to correct many of the errors caused by the effect of aircraft roll on hyperspectral push-broom sensors. After performing the reference line correction one of the images was georeferenced using a DOQQ, and a RMSE value of 1.5 meters was achieved. The correction program used to implement the method was programmed in Python, and the program can be downloaded from the projects website.

Intraurban Population Estimation Using Remotely Sensed Imagery

Geographic applications frequently require the gathering and analysis of socioeconomic data. For many nations, these data are normally collected through a census. However, during the intercensal period (5–10 years), these data lose their currency and must be updated. The objective of this project was to estimate housing unit density from Landsat ETM+ imagery in the Terre Haute, IN, USA, region. Modelling was done for 1945 census blocks in the study area containing 30 972 housing units. Landtype, as represented by six cluster classes, was used as the primary surrogate for housing unit density. The percentage of each landtype within the census blocks was calculated. Other landscape metrics representing landtype patch dominance and diversity were also calculated on a per-block basis. Housing unit density within the census block was then modelled as a function of those percentages and metrics using discriminant analysis and multiple regression. The simple correlation between the observed and modelled housing unit density was 0.79. The mean residual error produced by the model was 0.37 housing units per hectare.

An Evaluation of Remote Sensing-derived Landscape Ecology Metrics for Reservoir Shoreline Environmental Monitoring

Of the Earth’s 6.5 billion human inhabitants, nearly three billion live in urban settlements (UNCHS, 2001). Natural increase, land tenure practices, political policy, environmental degradation, and the dynamics of regional / global economics are largely responsible for the ongoing population shift from rural agrarian regions to cities. This increased urbanization is not just a developing country phenomenon. Urban areas of North America in 1900 were home to only 50% of the continent’s population. In 2000, the percentage of North American urban inhabitants rose to 75%.

Spectral Modeling of Population Density: A Study of Utah's Wasatch Front

The goal of this study was to determine the value of including landscape ecology patterns and structure metrics extracted from high-resolution, remotely-sensed imagery in the development of a Shoreline Environmental Impact Index (SEII). Methods of combining landscape ecology metrics to create a meaningful Shoreline Environmental Impact Index included multiple linear regression, multiple discriminant analysis, genetic neural networks, and feed-forward, backpropagation neural networks. The landscape ratings produced by the SEII’s generated using these methods were then compared to landscape ratings by experts. There was very little difference in the performance of several SEII’s generated despite differences in metrics and their weighting chosen by the different methods. The ratings from all methods showed their ability to reflect the expert ratings with moderate accuracy: � 84 percent agreement. Conclusions indicate that the contributions of landscape metrics to the ability of an SEII to discriminate between levels of shoreline degradation are variable, dependent upon the method of combination. Any of the current forms of the SEII is suitable for generating general indication of shoreline health.