Headwater stream systems are important components of the overall hydrologic system. Forestry best management practices (BMP) are effective at minimizing non point source pollution from forest harvesting activities. Streamside management zones (SMZ) are one BMP used to protect surface water quality by maintaining shade near streams, filtering runoff, and minimizing soil disturbance near streams. An evaluation of BMP effectiveness on the watershed scale was conducted at the University of Kentucky’s Robinson Forest. Six watersheds were harvested using a two-age deferment harvest with one of three SMZ configurations applied to each watershed. Two unharvested watersheds served as controls. Treatment 1 was based on the current Kentucky Forest Practice Guidelines for Water Quality Management and included a 16.8 m SMZ with 50% canopy retention for perennial streams, a 7.6 m SMZ with no canopy retention for intermittent streams, and no SMZ or canopy retention for ephemeral streams with unimproved crossings. Treatment 2 also included a 16.8 m perennial SMZ but increased canopy retention to 100%, as well as a 7.6 m intermittent SMZ with 25% canopy retention, and retention of channel bank trees and use of improved crossings for ephemeral streams. Treatment 3 required a 33.5 m perennial SMZ with 100% canopy retention, a 16.8 intermittent SMZ with 25% canopy retention, and a 7.6 m ephemeral SMZ with retention of channel bank trees and use of improved crossings. Total suspended solids (TSS) concentration and turbidity was measured in storm samples in perennial and ephemeral streams, and in non-storm samples in perennial and intermittent streams. Nitrate-N, ammonium-N, and dissolved oxygen concentrations were also measured in non-storm samples in perennial and intermittent streams. Temperature and water level were recorded every 15 minutes for the duration of the study. Results showed that treatment 3 was able to maintain TSS concentrations and turbidity levels similar to those measured in unharvested control watersheds. Increases in nitrate-N and mean daily temperature were measured for all treatments. Ammonium-N and dissolved oxygen concentrations were not different from unharvested control watersheds for any treatment. Storm hydrograph separation did not result in consistent changes post-harvest for any treatment.

Two wild blueberry fields were selected in central Nova Scotia, to characterize and quantify the spatial pattern of variability in soil properties, leaf nutrients and fruit yield, identification of yield influencing soil properties, and to develop management zones for site-specific fertilization. A combination of classical statistics, geostatistical analysis and mapping in Arc GIS 9.3 indicated substantial variation within field. The stepwise regression suggested that the soil EC, horizontal co-planar geometry (HCP), inorganic nitrogen and moisture content were major yield influencing factors. The cluster analysis of the soil variables with the fruit yield also indicated that HCP, inorganic nitrogen, EC, SOM, and ?v were closely grouped with the fruit yield at a similarity level greater than 70%. Based on the results of this study the wild blueberry fields can be divided into different management zones for variable rate fertilization to improve crop production, increase revenue, and reduce potential environmental contamination.

<div> Precision agriculture equipment enables treating different areas of a field differently (i.e., site-specific management). The first part of this work presents an algorithm for inferring the management zones of fields based on multiple years' yield data. It seeks regions that correspond to the same underlying yield distribution. Zones are assumed to be the same each year, but their distributions are allowed to change year-to-year to account for variability. Zones are estimated using stochastic expectation maximization and maximization of the posterior marginals. The underlying assumption is that the yields corresponding to a given zone will behave similarly, and are drawn from the same distribution. This requires only the yield data automatically collected during harvest. This method requires no crop-specific calibration.</div><div><br></div><div> The second part of this work presents the Open Ag Data Alliance (OADA) Application Programming Interface (API) framework. It is a generic specification that can be used by third parties’ APIs to reduce the complexity of interoperating with multiple entities. This is especially useful in intercloud scenarios, for example, moving data between a farmer, a processor, and a distributor. Several existing standards that were leveraged are identified, the graph-based data representation is illustrated, and key API specifications and features are highlighted. Some of the contributions of OADA include user-centric Representational State Transfer (REST) so users can select API clients, resource meta-data stored externally to the resource, live data graphs via change feeds, intercloud data push, and format indifference. A reference implementation is presented and use cases are demonstrated.</div>

The major study objectives include determining if a 50-foot streamside management zone (SMZ) as described in the Virginia BMP Manual (VDOF 2002) is generally sufficient to protect stream water quality, riparian soils, and stream bank integrity in headwater streams where forest harvesting has taken place, as well as comparing other SMZ widths with regard to the same environmental protection performance. In 2003, 16 forested watersheds were clear-cut harvested for commercial timber production. Four SMZ treatments were installed across four experimental blocks during harvest. Each of the 16 watersheds was subsequently site-prepared with prescribed burning and planted with loblolly pine (Pinus taeda). Within the watersheds, the established treatments were a 100-foot width with no thinning, a 50-foot width without thinning, a 50-foot width with thinning, and a 25-foot "stringer." Each of the four treatments was conducted within three of four blocks (Incomplete Block Design). After a two-year post-harvest monitoring period, it was determined that the SMZ treatments had no significant effect on water quality, channel geometry, or soil erosion in and around the streams. There was no apparent water quality degradation as a result of harvesting timber, and larger SMZs did not have an impact on any of the parameters studied. It was also apparent that leaving narrower SMZs or thinning within SMZs did not cause any apparent environmental degradation. It was also determined that landowners who leave SMZs on their property have very limited opportunities to manage timber within them for financial gain in the long term. / Ph. D.

A população de plantas é um dos fatores que impacta fortemente na produtividade da cultura do milho (Zea mays); justá-la localmente é uma das estratégias para gerenciar a variabilidade das lavouras e otimizar o uso de recursos do ambiente que não estão sob o controle do produtor rural, como o tipo de solo e a capacidade de retenção de água. O objetivo desse estudo foi investigar a produtividade de híbridos de milho submetidos à semeadura em taxas variáveis (STV) em unidades de gestão diferenciada (UGD). Foi utilizado o total de dez híbridos de milho testados em cinco níveis de populações de plantas a partir da população regularmente recomendada (60%, 80%, 100%, 120% e 140%). Foram conduzidos cinco experimentos em talhões comerciais entre os anos de 2012 e 2015, no Brasil, na região Centro-Oeste (Maracajú -MS), durante a segunda safra de verão (safrinha) e na região Sul (Piraí do Sul - PR), durante a safra de verão. A pesquisa foi dividida em duas etapas principais: (1) delimitação das UGD e (2) implantação dos experimentos em faixas variando híbridos e população de plantas ao longo das UGD. Foram utilizados mapas históricos de produtividade (MP), mapa de condutividade elétrica do solo (CE) e mapa de altitude como atributos que deram origem às UGD. Dois métodos distintos de agrupamentos foram analisados: o método de \"cluster\" por \"K-means\" e o método pela média normalizada. As análises das UGD foram realizadas com base na estatística descritiva. Os experimentos em faixas tiveram os dados de produtividade referentes aos híbridos, população e UGD submetidos às análises de variância pelo F-teste e ANOVA e análise de regressão em função dos níveis de população de plantas por área. Foi possível discriminar, através das UGD, diferentes níveis de produtividade, CE do solo e concentração de nutrientes (CE, pH, CTC Efetiva, Argila, Areia, V%, M.O, e K), indicando que os procedimentos utilizados nesse estudo para a definição de UGD foram eficientes. O método de formação de UGD pela média normalizada proporcionou maior homogeneidade interna das UGD comparativamente ao método de \"Cluster K-means\". A qualidade da distribuição longitudinal medida pelo espaçamento entre plantas (indicador da efetividade dos níveis de população) variou de 81% a 90% de espaçamentos aceitáveis entre os locais avaliados. A análise de variância foi significativa (P<0,05) para interação tripla entre híbridos, população de plantas e UGD assim com as regressões foram significativas e os melhores modelos tiveram ajuste quadrático para população e produtividade na área da região Centro-Oeste - MS. Nas áreas da região Sul os experimentos não foram significativos. A população de plantas ótima pode diferir em até 5743 pl ha-1 entre as diferentes UGD dentro de um mesmo talhão. Quanto menor a média de produtividade do talhão, mais restritiva é a faixa de população ótima. No entanto, não há uma recomendação simples a respeito da população de plantas ótima para cada UGD. / Plant population per unit area is one of the most important aspects under the farmer\'s control that can influence maize grain yield. As the availability of resources for the growth of plants (like water availability and soil attributes) are not uniform along the fields, and considering the unfeasibility to change the environment setting, plant population per area is a key aspect under the farmer\'s control to optimize the use of these resources. This study aims to carry a comprehensive study of the strategy of variable rate seeding (VRS) within zones of distinct resource availability (management zones - MZ). A seasonal experimental design was set consisting in selecting ten different hybrids and five ranks of plant populations starting with a local recommended seeding rate and offsetting it in 40% and 20% below and above this reference. Five field experiments were conducted in commercial fields from 2012 to 2015 in two regions with distinct growing seasons in Brazil. In the Midwest region (Maracaju - MS) where corn is grown as a secondary crop following soybean within one season, and in the Southern region (Piraí do Sul - PR) where corn is grown as primary crop during the summer season; both under rain fed and no-tillage system. This research was split into two main stages: (1) definition of management zones (MZ) within agricultural fields and (2) implementation of strip tests varying hybrids and plant populations across MZ. The attributes used to delineate MZ were soil electrical conductivity (EC), yield maps (YM) and elevation. Two methods were analyzed to delineate MZ: cluster K-means and standardized average. MZ were analyzed by descriptive statistics. On the experimental data gathered from each seasonexperiment, yield of the hybrids, plant density and MZ were submitted to analysis of variance by F-test, ANOVA and regression analysis. MZ were able to differentiate levels of yield, and soil properties (EC, pH, Effective CTC, clay, sand, V%, MO, and K), suggesting that the procedures to define MZ used in this study were efficient. The standardized average provides greater internal homogeneity of MZ compared with the Cluster K-means. The quality of regular spacing between plants (indicator of seed rate quality) was 90% to 81% at all locations. The analyses of variance were significant (P < 0.05) for triple interaction between hybrids, plant population, and for the MZ at the Midwest region. For fields studied in the South the tests were not significant. The optimal plant population at the Midwest region can vary by up to 5743 pl ha-1 across MZ within the same field. Lower yield averages have a narrow optimal plant population interval. However, there is no simple recommendation regarding the optimal plant population across MZ.

A população de plantas é um dos fatores que impacta fortemente na produtividade da cultura do milho (Zea mays); justá-la localmente é uma das estratégias para gerenciar a variabilidade das lavouras e otimizar o uso de recursos do ambiente que não estão sob o controle do produtor rural, como o tipo de solo e a capacidade de retenção de água. O objetivo desse estudo foi investigar a produtividade de híbridos de milho submetidos à semeadura em taxas variáveis (STV) em unidades de gestão diferenciada (UGD). Foi utilizado o total de dez híbridos de milho testados em cinco níveis de populações de plantas a partir da população regularmente recomendada (60%, 80%, 100%, 120% e 140%). Foram conduzidos cinco experimentos em talhões comerciais entre os anos de 2012 e 2015, no Brasil, na região Centro-Oeste (Maracajú -MS), durante a segunda safra de verão (safrinha) e na região Sul (Piraí do Sul - PR), durante a safra de verão. A pesquisa foi dividida em duas etapas principais: (1) delimitação das UGD e (2) implantação dos experimentos em faixas variando híbridos e população de plantas ao longo das UGD. Foram utilizados mapas históricos de produtividade (MP), mapa de condutividade elétrica do solo (CE) e mapa de altitude como atributos que deram origem às UGD. Dois métodos distintos de agrupamentos foram analisados: o método de \"cluster\" por \"K-means\" e o método pela média normalizada. As análises das UGD foram realizadas com base na estatística descritiva. Os experimentos em faixas tiveram os dados de produtividade referentes aos híbridos, população e UGD submetidos às análises de variância pelo F-teste e ANOVA e análise de regressão em função dos níveis de população de plantas por área. Foi possível discriminar, através das UGD, diferentes níveis de produtividade, CE do solo e concentração de nutrientes (CE, pH, CTC Efetiva, Argila, Areia, V%, M.O, e K), indicando que os procedimentos utilizados nesse estudo para a definição de UGD foram eficientes. O método de formação de UGD pela média normalizada proporcionou maior homogeneidade interna das UGD comparativamente ao método de \"Cluster K-means\". A qualidade da distribuição longitudinal medida pelo espaçamento entre plantas (indicador da efetividade dos níveis de população) variou de 81% a 90% de espaçamentos aceitáveis entre os locais avaliados. A análise de variância foi significativa (P<0,05) para interação tripla entre híbridos, população de plantas e UGD assim com as regressões foram significativas e os melhores modelos tiveram ajuste quadrático para população e produtividade na área da região Centro-Oeste - MS. Nas áreas da região Sul os experimentos não foram significativos. A população de plantas ótima pode diferir em até 5743 pl ha-1 entre as diferentes UGD dentro de um mesmo talhão. Quanto menor a média de produtividade do talhão, mais restritiva é a faixa de população ótima. No entanto, não há uma recomendação simples a respeito da população de plantas ótima para cada UGD. / Plant population per unit area is one of the most important aspects under the farmer\'s control that can influence maize grain yield. As the availability of resources for the growth of plants (like water availability and soil attributes) are not uniform along the fields, and considering the unfeasibility to change the environment setting, plant population per area is a key aspect under the farmer\'s control to optimize the use of these resources. This study aims to carry a comprehensive study of the strategy of variable rate seeding (VRS) within zones of distinct resource availability (management zones - MZ). A seasonal experimental design was set consisting in selecting ten different hybrids and five ranks of plant populations starting with a local recommended seeding rate and offsetting it in 40% and 20% below and above this reference. Five field experiments were conducted in commercial fields from 2012 to 2015 in two regions with distinct growing seasons in Brazil. In the Midwest region (Maracaju - MS) where corn is grown as a secondary crop following soybean within one season, and in the Southern region (Piraí do Sul - PR) where corn is grown as primary crop during the summer season; both under rain fed and no-tillage system. This research was split into two main stages: (1) definition of management zones (MZ) within agricultural fields and (2) implementation of strip tests varying hybrids and plant populations across MZ. The attributes used to delineate MZ were soil electrical conductivity (EC), yield maps (YM) and elevation. Two methods were analyzed to delineate MZ: cluster K-means and standardized average. MZ were analyzed by descriptive statistics. On the experimental data gathered from each seasonexperiment, yield of the hybrids, plant density and MZ were submitted to analysis of variance by F-test, ANOVA and regression analysis. MZ were able to differentiate levels of yield, and soil properties (EC, pH, Effective CTC, clay, sand, V%, MO, and K), suggesting that the procedures to define MZ used in this study were efficient. The standardized average provides greater internal homogeneity of MZ compared with the Cluster K-means. The quality of regular spacing between plants (indicator of seed rate quality) was 90% to 81% at all locations. The analyses of variance were significant (P < 0.05) for triple interaction between hybrids, plant population, and for the MZ at the Midwest region. For fields studied in the South the tests were not significant. The optimal plant population at the Midwest region can vary by up to 5743 pl ha-1 across MZ within the same field. Lower yield averages have a narrow optimal plant population interval. However, there is no simple recommendation regarding the optimal plant population across MZ.

A definição de zonas de manejo no contexto da agricultura de precisão requer muitas etapas, desde a coleta de dados até a avaliação dos mapas. No entanto, existe diferente número de etapas, ferramentas, métodos, algoritmos e softwares usados, apresentadas pelos pesquisadores. Neste contexto, o objetivo do trabalho é propor um modelo de referência para o processo de definição de zonas de manejo em agricultura de precisão. O modelo de referência proposto para o processo de está dividido em algumas etapas observadas na maioria dos trabalhos analisados. A Business Process Model and Notation (BPMN) foi utilizada para formalizar o modelo de referência composto dos cinco subprocessos: coleta de dados, seleção de atributos, filtragem de dados, agrupamento e avaliação dos mapas. Adicionalmente são apresentadas as atividades, os fluxos e desvios de cada subprocesso, apresentando os conceitos, pré-requisitos e limitações dos métodos aplicáveis em cada uma das atividades, além de apresentar possíveis variações na execução das atividades, ampliando as opções disponíveis para a definição de zonas de manejo. Um estudo de caso é apresentado para avaliar a aplicabilidade do modelo de referência proposto, descrevendo a utilização dos subprocessos e atividades propostas. A BPMN mostrou ser adequada para representar os subprocessos, atividades, fluxos e desvios do processo. O estudo de caso comprovou a aplicabilidade do modelo proposto, através de seu uso em um talhão contendo diferentes grades amostrais, erros de coleta e pares de atributos com forte correlação, enfatizando a importância das atividades propostas. Por fim o modelo de referência proposto foi capaz de gerar um conjunto de mapas de zonas de manejo e indicar o mapa mais adequado aos objetivos da agricultura de precisão. / Management zone delineation in the context of precision agriculture requires many steps, from data collection to management zone maps evaluation. However, there are different numbers of steps shown by researchers, besides tools, methods, algorithms and software used. In this context, the aim of this work is to propose a reference model process for management zone delineation in precision agriculture. The proposed reference model process is divided into some steps observed in most of the works analyzed. Business Process Model and Notation (BPMN) was used to formalize the reference model composed of the five subprocesses: data collection, feature selection, data filtering, clustering and maps evaluation. In addition, the model presents activities, flows and gateways for each subprocess, presenting concepts, prerequisites, limitations of the applicable methods for each activity and possible variations to the implementation of the activities, increasing the options available for management zone delineation. A case study is presented to evaluate the applicability of the reference model proposed, describing the use of the subprocesses and activities proposed. The BPMN showed to be adequate to represent subprocess, activities, flows and gateways of the process. The case study demonstrated the applicability of the model proposed through its use in a field with different sample grids, errors from collection and strong correlation between pairs of attributes, emphasizing the importance of the activities proposed. Finally, the model proposed was able to generate a set of management zone maps and to indicate the most appropriate for precision agriculture objectives.

A definição de zonas de manejo no contexto da agricultura de precisão requer muitas etapas, desde a coleta de dados até a avaliação dos mapas. No entanto, existe diferente número de etapas, ferramentas, métodos, algoritmos e softwares usados, apresentadas pelos pesquisadores. Neste contexto, o objetivo do trabalho é propor um modelo de referência para o processo de definição de zonas de manejo em agricultura de precisão. O modelo de referência proposto para o processo de está dividido em algumas etapas observadas na maioria dos trabalhos analisados. A Business Process Model and Notation (BPMN) foi utilizada para formalizar o modelo de referência composto dos cinco subprocessos: coleta de dados, seleção de atributos, filtragem de dados, agrupamento e avaliação dos mapas. Adicionalmente são apresentadas as atividades, os fluxos e desvios de cada subprocesso, apresentando os conceitos, pré-requisitos e limitações dos métodos aplicáveis em cada uma das atividades, além de apresentar possíveis variações na execução das atividades, ampliando as opções disponíveis para a definição de zonas de manejo. Um estudo de caso é apresentado para avaliar a aplicabilidade do modelo de referência proposto, descrevendo a utilização dos subprocessos e atividades propostas. A BPMN mostrou ser adequada para representar os subprocessos, atividades, fluxos e desvios do processo. O estudo de caso comprovou a aplicabilidade do modelo proposto, através de seu uso em um talhão contendo diferentes grades amostrais, erros de coleta e pares de atributos com forte correlação, enfatizando a importância das atividades propostas. Por fim o modelo de referência proposto foi capaz de gerar um conjunto de mapas de zonas de manejo e indicar o mapa mais adequado aos objetivos da agricultura de precisão. / Management zone delineation in the context of precision agriculture requires many steps, from data collection to management zone maps evaluation. However, there are different numbers of steps shown by researchers, besides tools, methods, algorithms and software used. In this context, the aim of this work is to propose a reference model process for management zone delineation in precision agriculture. The proposed reference model process is divided into some steps observed in most of the works analyzed. Business Process Model and Notation (BPMN) was used to formalize the reference model composed of the five subprocesses: data collection, feature selection, data filtering, clustering and maps evaluation. In addition, the model presents activities, flows and gateways for each subprocess, presenting concepts, prerequisites, limitations of the applicable methods for each activity and possible variations to the implementation of the activities, increasing the options available for management zone delineation. A case study is presented to evaluate the applicability of the reference model proposed, describing the use of the subprocesses and activities proposed. The BPMN showed to be adequate to represent subprocess, activities, flows and gateways of the process. The case study demonstrated the applicability of the model proposed through its use in a field with different sample grids, errors from collection and strong correlation between pairs of attributes, emphasizing the importance of the activities proposed. Finally, the model proposed was able to generate a set of management zone maps and to indicate the most appropriate for precision agriculture objectives.

Made available in DSpace on 2017-05-12T14:46:57Z (GMT). No. of bitstreams: 1 Kelyn Schenatto.pdf: 4212903 bytes, checksum: 0ba04350cc25aff5e6acb249938e5375 (MD5) Previous issue date: 2014-02-04 / Despite the benefits offered by the technology of precision agriculture (PA), the necessity of dense sampling grids and use of sophisticated equipment for the soil and plant handling make it financially unfeasible in many cases, especially for small producers. With the aimof making viable the PA, the definition of management zones (MZ) consists in dividing the plotin subregions that have similar physicochemical features, where it is possible to work in the conventional manner (without site-specific input application), differing them from the other sub-regions of the field. Thus we use concepts from PA, but adapting some procedures to the reality of the producer, not requiring the replacement of machinery traditionally used.Therefore, yield is usually correlated with physical and chemical properties through statistical and geostatistical methods, and attributes are selected to generate thematic maps, which are then used to define the MZ. In the generation of thematic maps step, are commonly used traditional interpolation methods (Inverse Distance - ID , inverse of the square distance - ISD, and kriging - KRI), and it is important to assess if the quality of thematic maps generated influences in the MZ drafting process and can not justify the interpolation data using robust methods such as KRI. Thus, the present study aimed to evaluate three interpolation methods (ID , ISD and KRI ) for generation of thematic maps used in the generation of MZ by clustering methods K-Means and Fuzzy C-Meas, in two experimental areas (9.9 ha and 15.5 ha), and been used data from four seasons (three crops of soybeans and one of corn). The KRI interpolation and ID showed similar UM. The agreement between the maps decreased when an increase in the number of classes, but with greater intensity with the Fuzzy C-Means method. Clustering algorithms K-Means and Fuzzy C-Means performed similar division on two UM. The best interpolation method was KRI following the ID, what justifies the choice of a more robust interpolation (KRI) to generate UM / Apesar dos benefícios proporcionados pela tecnologia de agricultura de precisão (AP), a necessidade de grades amostrais densas e uso de equipamentos sofisticados para o manejo do solo e da planta tornam o seu cultivo em muitos casos inviável financeiramente, principalmente para pequenos produtores. Com a finalidade de viabilizar a AP, a definição de unidades de manejo (UM) consiste em dividir o talhão em sub-regiões que possuam características físico-químicas semelhantes, onde se pode trabalhar de forma convencional (sem aplicação localizada de insumos), diferenciando-se das outras sub-regiões do talhão. Dessa forma, utilizam-se conceitos de AP, mas adaptam-se alguns procedimentos para a realidade do produtor, não havendo necessidade da substituição de máquinas tradicionalmente utilizadas. Para isso, são geralmente correlacionados atributos físicos e químicos com a produtividade das culturas e, por meio de métodos estatísticos e geoestatísticos, selecionam-se atributos que darão origem a mapas temáticos posteriormente utilizados para definição das UM. Na etapa de geração dos mapas temáticos, são normalmente utilizados métodos tradicionais de interpolação (inverso da distância ID, inverso da distância ao quadrado IDQ e krigagem KRI) e é importante avaliar se a qualidade dos mapas temáticos gerados influencia no processo de definição das UM, podendo desta forma não se justificar a interpolação de dados a partir do uso de métodos robustos como a KRI. O presente trabalho teve como objetivo a avaliação de três métodos de interpolação (ID, IQD e KRI) para definição dos mapas temáticos utilizados na confecção de UM pelos métodos de agrupamento K-Means e Fuzzy C-Means, em duas áreas experimentais (de 9,9 ha e 15,5 ha), sendo utilizados dados de quatro safras (três safras de soja e uma de milho). Os interpoladores ID e KRI apresentaram UM similares. A concordância entre os mapas diminuiu quando houve aumento do número de classes, mas teve maior intensidade com o método Fuzzy C-Means. Os algoritmos de agrupamento K-Means e Fuzzy C-Means se apresentaram similares na divisão em duas UM. O melhor método de interpolação foi a KRI, seguida do ID, o que justifica a escolha do interpolador mais robusto (KRI) na geração de UM

Soil landscape characterization into landform elements for precision agriculture has become an important issue. As soil properties and crop yields change over the landscape, delineating landform elements as a basis for site-specific application of crop inputs has become a reality. Two different methods of delineating landform elements from agricultural fields were tested and compared. The first method delineated landform elements from digital elevation maps with the use of the LandMapR(tm) software, the second method delineated classes from IKONOS high resolution panchromatic images using an unsupervised classification algorithm. The LandMapR(tm) model delineated landform elements from true elevation data collected in the field and was considered the reference dataset to which the image classification maps were compared to. The IKONOS imagery was processed using a combination of one filtering algorithm and one unsupervised classification method prior to being compared to the classified DEM. A total of 20 filtering algorithms and two unsupervised methods were used for each of the five study sites. The study sites consisted of four agricultural fields covered with crop stubble and one field in summer fallow. Image classification accuracy assessment was reported as overall, producer’s and user’s accuracy as well as Kappa statistic. Results showed that filtering algorithms and classification methods had no effects on image classification accuracies. Highest classification accuracy of image map to landform element map comparison achieved for all study sites was 17.9 %. Classification accuracy was affected by the heterogeneity of the ground surface cover found in each field. However, the classification accuracy of the fallow field was not superior to the stubble fields. / May 2006