RAGBRAI Learn about the Land; Day 3, July 2009

Want to know what conditions to expect over the next stage of RAGBRAI? How hilly will it be, what towns and parks are between here and there, or what services are coming up in the next town?

RAGBRAI Learn about the Land; Day 4, July 2009

Want to know what conditions to expect over the next stage of RAGBRAI? How hilly will it be, what towns and parks are between here and there, or what services are coming up in the next town?

RAGBRAI Learn about the Land; Day 5, July 2009

Want to know what conditions to expect over the next stage of RAGBRAI? How hilly will it be, what towns and parks are between here and there, or what services are coming up in the next town?

RAGBRAI Learn about the Land; Day 6, July 2009

Want to know what conditions to expect over the next stage of RAGBRAI? How hilly will it be, what towns and parks are between here and there, or what services are coming up in the next town?

RAGBRAI Learn about the Land; Day 7, July 2009

Want to know what conditions to expect over the next stage of RAGBRAI? How hilly will it be, what towns and parks are between here and there, or what services are coming up in the next town?

RAGBRAI Learn about the Land; Day 1 thru Day 7, July 2009

Want to know what conditions to expect over the next stage of RAGBRAI? How hilly will it be, what towns and parks are between here and there, or what services are coming up in the next town?

Report on a review of the Fuel Inspection Program administered by the Iowa Department of Agriculture and Land Stewardship for the period July 1, 2005 through June 30, 2009

Report on a review of the Fuel Inspection Program administered by the Iowa Department of Agriculture and Land Stewardship for the period July 1, 2005 through June 30, 2009

Lobbying, political competition, and local land supply: recent evidence from Spain

We analyze whether local land supply is influenced by the degree of political competition, and interpret the findings as being indicative of the influence wielded by land development lobbies. We use a new database including both political and land supply data for more than 2,000 Spanish municipalities for the period 2003-2007. In Spain, land use policies are largely a local responsibility with municipalities having periodically to pass compre- hensive land use plans. The main policy variable in these plans, and the one analyzed here, is the amount of land classified for potential development. We measure local political competition as the margin of victory of the incumbent government. We instrument this variable using the number of votes obtained by parties represented in local government when standing at the first national legislative elections following the re-establishment of democracy, and the number of votes they actually obtained regionally at the national legislative elections. The results indicate that stiffer political competition does indeed reduce the amount of new land designated for development. This effect is found to be most marked in suburbs, in towns with a high percent of commuters and homeowners, and in municipalities governed by the left.

Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts

Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM's) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor's drift with an adaptive SOM has also been investigated

Lobbying, political competition, and local land supply: recent evidence from Spain

We analyze whether local land supply is influenced by the degree of political competition, and interpret the findings as being indicative of the influence wielded by land development lobbies. We use a new database including both political and land supply data for more than 2,000 Spanish municipalities for the period 2003-2007. In Spain, land use policies are largely a local responsibility with municipalities having periodically to pass compre- hensive land use plans. The main policy variable in these plans, and the one analyzed here, is the amount of land classified for potential development. We measure local political competition as the margin of victory of the incumbent government. We instrument this variable using the number of votes obtained by parties represented in local government when standing at the first national legislative elections following the re-establishment of democracy, and the number of votes they actually obtained regionally at the national legislative elections. The results indicate that stiffer political competition does indeed reduce the amount of new land designated for development. This effect is found to be most marked in suburbs, in towns with a high percent of commuters and homeowners, and in municipalities governed by the left.

Spatial and temporal variability of crop yield and some Rhodic Hapludox properties under no-tillage

Soil properties are closely related with crop production and spite of the measures implemented, spatial variation has been repeatedly observed and described. Identifying and describing spatial variations of soil properties and their effects on crop yield can be a powerful decision-making tool in specific land management systems. The objective of this research was to characterize the spatial and temporal variations in crop yield and chemical and physical properties of a Rhodic Hapludox soil under no-tillage. The studied area of 3.42 ha had been cultivated since 1985 under no-tillage crop rotation in summer and winter. Yield and soil property were sampled in a regular 10 x 10 m grid, with 302 sample points. Yields of several crops were analyzed (soybean, maize, triticale, hyacinth bean and castor bean) as well as soil chemical (pH, Soil Organic Matter (SOM), P, Ca2+, Mg2+, H + Al, B, Fe, Mn, Zn, CEC, sum of bases (SB), and base saturation (V %)) and soil physical properties (saturated hydraulic conductivity, texture, density, total porosity, and mechanical penetration resistance). Data were analyzed using geostatistical analysis procedures and maps based on interpolation by kriging. Great variation in crop yields was observed in the years evaluated. The yield values in the Northern region of the study area were high in some years. Crop yields and some physical and soil chemical properties were spatially correlated.

Sewage sludge application to agricultural land as soil physical conditioner

Water resource quality is a concern of today's society and, as a consequence, low pollutant wastewaters and sludges are being increasingly treated, resulting in continuous production of sewage sludge. Sewage sludge (SS) can be used as soil physical conditioner of agricultural or degraded lands, due to its organic C component. The objective of this research was to evaluate the long-term SS effects on soil physical quality of properties such as bulk density, porosity, permeability and water retention of degraded soils treated with annual SS applications. The SS rates were calculated according to the crop N demand. The field experiment consisted of three treatments: mineral fertilization, 10 and 20 Mg ha-1 of SS (once and twice the SS quantity to meet the maize N demand, respectively), in annual applications to the surface layer of a eutroferric Red Latosol. SS reduced bulk density, increased macroporosity and decreased microporosity after the third application, but did not significantly alter the soil permeability and physical quality as measured by the S index in the surface layer.

Report on the Iowa Department of Agriculture and Land Stewardship for the year ended June 30, 2010

Report on the Iowa Department of Agriculture and Land Stewardship for the year ended June 30, 2010