Many traditional drought assessments are conducted based on climate and hydrologic data. The availability and precision of data limit the spatial and temporal resolution and accuracy of derived drought indices. In this study, Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) were generated from Moderate Resolution Imaging Spectroradiometer (MODIS) products. The VCI was derived from Normalized Difference Vegetation Index (NDVI) that was calculated with near infrared and visible red band reflectance from MOD09Q1. The TCI was derived from land surface temperature (LST) product MOD11A2. The VCI and TCI were then combined with reference to the vegetation coverage information from MOD44B to generate the modified Vegetation Health Index (VHI). The modified VHI was applied to quantify the intensity of drought that took place in Illinois from 2000 to 2012. The results showed that the modified VHI identified the major droughts that occurred in Illinois from 2000 to 2012, especially the extreme one taking place in 2012. Moreover, the modified VHI led to the spatial distributions and temporal trends of drought severity, which were overall similar to those from the U.S. Drought Monitor (USDM) maps, but had more detailed spatial variability and much higher spatial resolution. The modified VHI also differentiated the drought impacts between the vegetated and non-vegetated areas, being a lack of the original VHI. Thus, the modified VHI takes advantage of spatially continuous and timely data from satellites and can be applied to conduct the monitoring and detection of drought intensity at local, regional, and national scales. The modified VHI can effectively synthesize the drought information of LST and NDVI to differentiate the effects of land use and land cover (LULC) types and provide the detailed spatial variability of drought intensity and thus enhance the understanding of relationship between drought condition and LULC types.

Including peanut (Arachis hypogaea L.) in crop rotations is common for eastern Virginia and the Carolinas, as it thrives in the long growing season and sandy soils. Boron (B) is widely deficient, and is more prone to leeching in sandy soils. Applied B has difficulty reaching growing points as B has reduced phloem mobility in peanuts. Current B fertilization recommendations are based on only three studies from the early 70s. Many changes have been made in cultivar breeding since then. This research examines if recommended B application rates and times are still necessary for optimal yield, plant health and seed quality for current cultivars. Two experiments in seven fields compared four total amounts of B applied (0, 0.3, 0.6, and 1.1 kg ha-1), and application time (planting; beginning peg, R2; full seed, R6; planting and R2; planting and R6), and runner and Virginia market types, newer and obsolete cultivars, with or without B fertilization. Leaf B was elevated only directly after fertilization (p=0.004, p<0.001), and in relation to total B applied (p<0.001), but seed B content was unaffected. Yield was not impacted by B rate or application time. Yield was higher (p=0.012) for newer cultivars when B fertilized, but no different than obsolete cultivars with B. Seed from obsolete cultivars had higher (p=0.010) B, no difference between market types or B fertilization. Germination of all seed was 97%. Based on this research, it is not necessary to apply B for optimal yield, plant health and seed quality for current cultivars. / Master of Science in Life Sciences

The relationship between the satellite-based Vegetation Condition Index (VCI) and frequently used agricultural drought indices like Palmer Drought Severity Index, Palmer’s Z-index, Standard Precipitation Index, percent normal and deciles was evaluated using a comparative correlation analysis. These indices were compared at the county level for all 254 Texas counties for the growing-season months (March to August) using monthly data from 1982-1999. The evaluation revealed that the VCI was most strongly correlated with the 6-month SPI and the PDSI. This suggests that the VCI is most similar to drought indices that account for antecedent moisture conditions. There was also significant spatial variability in the magnitude of the correlations between the VCI and the drought indices. The reasons for this variability were explored by utilizing additional data such as irrigation, prevalent landuse/landcover, water table depth, soil moisture levels and soil hydrologic/hydraulic properties. The results demonstrated that mean annual precipitation, soil moisture, landuse/landcover, and depth of the water table accounted for a significant amount of the spatial variability (explaining more than 75% of the variance) in the relationship between the VCI and traditional drought indices.

Master of Science / Department of Agronomy / William T. Schapaugh Jr / Yield in soybean (Glycine max (L.) Merr) needs to dramatically increase across the world to feed the growing population. Remote sensing and high-throughput phenotyping may provide a tool to better phenotype soybean genotypes. This research was conducted to: 1) examine the relationships between NDVI and CT with seed yield, maturity, lodging, and height, 2) determine if the time of day and growth stage have an effect on the spectral readings, 3) examine the relationships between spectral reflectance and traits associated with drought tolerance, and 4) evaluate how weather variables impact the ability of vegetative indices and canopy temperature to detect differences among genotypes. Ninety genotypes from the mapping population derived from the cross between KS4895 x Jackson were evaluated in Manhattan, KS, in 2013 and in McCune, Pittsburg, and Salina, KS in 2014. Genotypes were planted in a randomized complete bloc design in four-row, 3.4m long plots spaced 76 cm apart. Plant height, lodging, maturity and seed yield was collected on the center two rows of each plot. Spectral readings used to calculate a normalized differential vegetative index (NDVI) and canopy temperature (CT) were taken during reproductive growth. Nitrogen fixation trait and drought tolerance data was collected by the University of Arkansas. This population exhibited a substantial genetic variation for all traits evaluated. Correlations of NDVI and CT entry means with the agronomic traits were small and inconsistent. Time of day and growth stage were not important in differentiating genotypes. Differences in NDVI and CT did account for some genetic variation in drought tolerance traits, however, the strength of the associations were small. None of the weather variables were consistently associated with an increase or decrease in entry or error variance across the four environments. Stronger associations need to be established to use NDVI or CT to characterize differences in genotypes in a plant breeding program

Master of Science / Department of Agronomy / Antonio R. Asebedo / Current population trends project that current agricultural production will need to increase by 110% by the year 2050 to support the growing worldwide population. Many agriculturalists are looking at precision agriculture technology to help achieve this production increase. One technology that is being heavily researched is the integration of small unmanned aerial systems (sUAS) and their sensors into the agricultural sector. Much research has already been conducted in the agronomic sector utilizing sUAS. However, relatively few advancements involving sUAS have been made in the animal science industry. This thesis focuses on how sUAS can be incorporated into a diverse cropping and livestock operation. Chapter 1 - Evaluating Current Capabilities of sUAS and sUAS Mounted Sensors in Diverse Agricultural Operation: A Literature Review, focuses on the current capabilities of sUAS and explains how they are incorporated into cropping systems and livestock production. Chapter 2 - Wheat Variety Interaction on Multispectral Based Vegetative Indices, focuses on wheat variety interaction with yield, grain protein content, NDVI, NDRE and CCCI. Ten wheat varieties were tested in large plot studies; yield, protein and multispectral data were collected for Feekes 4, 7, 10 and 10.5. Wheat variety was statically significant across all vegetative indices, protein and yield during less than favorable growing conditions. Chapter 3 - Estimating Cattle Rectal Temperature Using Thermography, focuses on determining the ideal location for thermographic readings to be taken to predict rectal temperature of beef cattle. To establish if sUAS-based thermography could be utilized for cattle rectal temperature estimation, 35 crossbreed steers were selected and thermographic readings and rectal temperature data were collected and analyzed for correlation. This study found stronger relation in the animal’s eye than other facial features.

A nitrogen fertility study with Vaughn’s hybrid bermudagrass conducted on a Crider silt loam soil (fine, silty, mixed, active, mesic Typic Paleudalfs) over three (3) years (2008-2011) at the Highland Rim Research and Education Center near Springfield, Tennessee is evaluated in this manuscript. Nitrogen applications are evaluated in both irrigated and non-irrigated plots at five (5) different application rates: 0, 56, 112, 168, and 224 kg N ha-1. These rates are applied beginning in late April, and three (3) additional times upon harvests occurring in June, July, and August. Irrigation plots receive enough water to bring total weekly water up to 2.24 cm/plot whenever rainfall is less than that amount. Normalized difference vegetative index (NDVI) measurements are collected mid harvest and on harvest dates to investigate new nitrogen status indicators between Vaughn’s hybrid bermudagrass yields. Plant tissue samples are collected at harvest. Soil samples are collected mid harvest to investigate soil nitrate nitrogen and its relationship with bermudagrass yields. The results of the study show irrigation has no effect on yields during the period of this study. There is a significant effect resulting from the interaction between month and nitrogen application on yield. Investigation of this interaction reveals two (2) distinct periods of production potential during the growing season. A low to medium yielding period produces an average harvest yield maximum of 3.14 Mg ha-1. A medium to high yield period produces an average harvest yield maximum of 5.4 Mg ha-1. Based on an analysis of variance and mean separation, a nitrogen rate of 56 kg N ha-1 rate is recommended for harvests occurring during the low to medium yielding period, and a nitrogen rate of 113 kg N ha-1 is recommended for those occurring during the high to medium yielding period. NDVI is highly correlated with yield on date of harvest. The results also show NDVI is correlated with mid-harvest yields also, which suggests a possible development of using NDVI as a mid harvest nitrogen status indicator. The results show soil nitrate is not correlated with yield, but did indicate accumulation in the soil as the growing season progressed.

The earth surface is monitored periodically by numerous satellite sensors which have different spectral response functions, image acquisition heights, atmosphere correction schemes, overpass times, and sun/view angle geometries. Temporal and spatial variations of land surface properties, such as vegetation index, Leaf Area Index (LAI), land surface temperature, and soil moisture, have been provided by long-term time series of various remote sensing datasets. Inter-sensor translation equations are required to build long-term time series by the combination of multiple sensors from historical to advanced and new satellite datasets. In the first chapter, inter-sensor translation equations of band reflectances and two vegetation indices (e.g. Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI)) were derived using linear regression equations relative to Moderate Resolution Imaging Spectroradiometer (MODIS) values. The consistency and validation of inter-sensor transforms were investigated through statistical student's t-test and the root mean square error (RMSE).In the second chapter, cross-sensor extension of EVI and a 2-band EVI (without the blue band; EVI2) were investigated based on the continuity of both EVI's. Sensor specific red-blue coherencies were examined for the possibility of the EVI and EVI2 extension from MODIS sensor. The EVI continuity to MODIS was particularly problematic for the Visible Infrared Imager / Radiometer Suite (VIIRS) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) that have dissimilar blue bands from that of MODIS. The cross-sensor extension and compatibility of EVI2 were improved and provided the possibility to be lengthened to the Advanced Very High Resolution Radiometer (AVHRR) using its translation equation.Finally, we evaluated the use of sensor-specific EVI and NDVI data sets, using a time sequence of Hyperion images over Amazon rainforest in Tapajos National Forest, Brazil for the 2001 and 2002 dry seasons. We computed NDVI, EVI, and EVI2 with the convolution data of different global monitoring and high temporal resolution sensor systems (AVHRR, MODIS, VIIRS, SPOT-VGT, and SeaWiFS) from Hyperion, and evaluated their spectral deviations and continuity in the characterization of tropical forest phenology. Our analyses show that EVI2 maintains the desirable properties of increased sensitivity in high biomass forests across all sensor systems evaluated.

This thesis deals with the production capabilities of stubble catch crops and their effect on yield of subsequent of spring barley. The field experiment was conducted on clayey-loamy fluvizem in the maize-growing region from 2006 to 2013. Experiments involved altogether ten different catch crops. Vegetation intercropping was established after the harvest of winter wheat in two periods (immediately after harvest crop and in mid-September). Spring barely was sown after these catch crops. Nitrogen fertilization was omitted to highlight the effect of catch crops on all variants in 2010. Analysis of the amount of fresh matter and dry matter stubble catch crops was conducted in the years 2006 - 2013 and the vegetation index NDVI was evaluated in the final year of monitoring. Another part belonged to classify the yield of spring barley grown after catch crops. A negative relationship between the yield of catch crop and that of spring barley was observed in the variant without nitrogen fertilization. Growing of catch crops on yield of spring barley had a positive impact in case of application of nitrogen.

Submitted by ALINE ROMBEGA TITO ROSA null (alinertr@gmail.com) on 2016-09-27T19:33:05Z No. of bitstreams: 1 Dissertação_Mestrado_Aline_Defesa_Imprimir_ Correçoes pós_defesa.pdf: 7184094 bytes, checksum: 3966b28270489d6c194f4b55ae0f9101 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-09-29T16:53:21Z (GMT) No. of bitstreams: 1 rosa_art_me_jabo.pdf: 7184094 bytes, checksum: 3966b28270489d6c194f4b55ae0f9101 (MD5) / Made available in DSpace on 2016-09-29T16:53:21Z (GMT). No. of bitstreams: 1 rosa_art_me_jabo.pdf: 7184094 bytes, checksum: 3966b28270489d6c194f4b55ae0f9101 (MD5) Previous issue date: 2016-07-29 / As pastagens no Brasil ocupam mais de 172 milhões de hectares, no qual 50% deste total já se encontram em alguma fase de degradação, com perda de matéria orgânica do solo e consequente elevação das emissões de carbono para a atmosfera. Neste sentido, informações quantitativas dos níveis de degradação das pastagens e do ambiente podem apoiar políticas de gestão ambiental. Este estudo teve o intuito de avaliar a aplicabilidade e eficácia do uso do sensoriamento remoto e geoprocessamento no diagnóstico de áreas de pastagens degradadas e sua correlação com a qualidade física do solo, na bacia do rio Uberaba, Veríssimo – MG. Os dados de sensoriamento remoto foram analisados utilizando três modelos matemáticos de regressão, sendo dois não lineares com distribuição ondulatória e um linear. O modelo de regressão cúbica, a partir das séries temporais do Moderate Resolution Imaging Spectroradiometer (MODIS), descreveu melhor o comportamento médio do pixel ao longo do ano, elucidando em média 75,7% dos dados válidos, apresentando inexistência de perda amostral em decorrência dos efeitos atmosféricos; principalmente presença de nuvens. Em todas as áreas de pastagens avaliadas foi observada densidade do solo acima dos valores críticos descritos na literatura, o que confere condições restritivas ao crescimento e desenvolvimento do sistema radicular, à infiltração e ao transporte de água, bem como às trocas gasosas entre o solo e a atmosfera. Ainda, foi evidenciada redução da proporção de macro microporos, comprometendo a adequada aeração, permeabilidade e armazenamento de água. Portanto, os resultados apontam que o método de diagnóstico das áreas de pastagens a partir de séries temporais do MODIS MOD13Q1 foi mais adequado na determinação do padrão de comportamento do pixel ao longo do ano; as áreas de pastagens do município de Veríssimo-MG apresentaram padrões espectrais distintos, permitindo a classificação e correlação com os níveis de degradação; as análises dos atributos físicos revelam que todas as áreas avaliadas apresentam sinais de degradação, inclusive as áreas com presença de pasto sadio; os solos das diferentes fisionomias de pastagens apresentaram intenso processo de compactação, com redução da porosidade, decorrente principalmente do efeito do pisoteio do gado. / Pastures in Brazil occupy more than 172 million hectares, in which 50% are already in some stage of degradation with loss of soil organic matter and the consequent rise in carbon emissions to the atmosphere. Thus, quantitative information of the degradation levels of pastures and the environment can support environmental management policies. This study aimed to evaluate the applicability and effectiveness of remote sensing and GIS use in the diagnosis of degraded pastures areas and its correlation with the soil physical quality in the basin of Uberaba river, Veríssimo - MG. The remote sensing data were analyzed using three mathematical regression models, two nonlinear wave with a linear distribution and linear .The cubic regression model, from temporal series of Moderate Resolution Imaging Spectroradiometer (MODIS), best described the average behavior of the pixel throughout the year, elucidating on average 75.7% of the valid data, showing absence of sample loss due to atmospheric effects; mainly the presence of clouds. In all areas evaluated pasture was observed soil density above the critical values reported in the literature, which gives restrictive conditions for growth and root development, infiltration and water transport and gas exchange between soil and atmosphere. Furthermore, there was a decrease in the proportion of macro micropores, compromising the proper aeration, water permeability and storage. Therefore, the results indicate that the diagnostic method of pasturelands from MODIS MOD13Q1 the time series was more appropriate in determining the pixel pattern of behavior throughout the year; the areas of Veríssimo-MG pastures showed distinct spectral patterns, allowing classification and correlation with the levels of degradation; the analysis of physical attributes reveal that all evaluated areas show signs of degradation, including areas with presence of healthy pasture; the soils of different pastures physiognomies showed intense process of compaction, reducing the porosity, mainly due to the effect of cattle trampling.

The Chapada do Araripe is inserted in one important environment at south of state of CearÃ, making edge with the states of Pernambuco and PiauÃ, acting as reload aquifer area that provides water to cariri cearense. ItÂs be inserted in one conservation unit, the Floresta Nacional do Araripe, more known as FLONA Araripe. ItÂs has a vegetation with characteristics well diversified, like Humid Forest, CerradÃo and Carrasco. At the local communities near of Flona, the main activities developed are rainfed agriculture and extrativism. The tradicional crops are cassava, bean and corn, which all cause strong impacts at natural vegetation. The necessity of constant monitoring and the scarcity of employees make troubles to implement conservation politics. By the way, the remote sensing is one of technologies which allows monitoring the vegetation dynamics at space and temporal scale. We aim to evaluate the dynamic of vegetation of the APA-Araripe through satellites images and the socio and environments of Comunidade Catolà at municipal district of Nova Olinda, state of CearÃ. The images utilized are plotted by satellite Landsat 5 TM, corresponding to orbit/point 217/65, provided by Instituto Nacional de Pesquisas Espaciais (INPE), with Geo Tif format. We used images from 1987 to 2011, which years selected were 1987, 1992, 1997, 2001, 2007 and 2011. Using the Erdas Imagine 9.0 software, we analyzed the Normal Difference Vegetation IndexÂs (NDVI) and Foliar Area IndexÂs (IAF). We applied questionnaires to get socio and environments data from the Comunidade CatolÃ. At this community, the fatherÂs schooling level is less than their childrens. The cassava crop is the main agriculture activitie, but the main source of income is provided by the government. At the forest monitoring, the NDVI showed more sensible to local rainfall seasonality and the IAF was less reliable during dry periods and the natural characteristics of the bioma influenced the vegetation indices used. The use of satellites images showed one efficient tool to monitoring antropogenic activites at the forest. / A Chapada do Araripe constitui-se, num importante ambiente no sul do Estado do CearÃ, limitando-se com Pernambuco e PiauÃ, atuando como Ãrea de recarga do aquÃfero que abastece o cariri cearense. Nela està inserida uma unidade de conservaÃÃo, a Floresta Nacional do Araripe, mais conhecida como FLONA Araripe. Possui uma vegetaÃÃo com caracterÃsticas bem diversificadas, com formaÃÃes de Floresta Ãmida, CerradÃo e Carrasco. Nas comunidades do entorno da FLONA, as principais atividades desenvolvidas sÃo a agricultura de sequeiro e o extrativismo. As lavouras tradicionalmente cultivadas sÃo a mandioca, o feijÃo e o milho, com prÃticas de cultivo rudimentares, na qual exerce forte pressÃo nos recursos naturais, principalmente na vegetaÃÃo nativa. A necessidade de monitoramento constante da Ãrea e a falta de funcionÃrios dificulta a implantaÃÃo de polÃticas de preservaÃÃo. Entretanto, o sensoriamento remoto à uma das tecnologias que permite o acompanhamento espaÃo/temporal da dinÃmica da vegetaÃÃo e das atividades antrÃpicas realizada na Ãrea de proteÃÃo. Objetiva-se avaliar a dinÃmica da vegetaÃÃo da APA-Araripe atravÃs de imagens de satÃlite, e os aspectos socioambientais da Comunidade Catolà no municÃpio de Nova Olinda-CE. As imagens utilizadas sÃo geradas pelo satÃlite Landsat 5 TM correspondente a Ãrbita/ponto 217/65 e sÃo liberadas pelo Instituto Nacional de Pesquisas Espaciais (INPE), no formato GeoTif. Foram utilizadas imagens do perÃodo de 1987 a 2011, sendo os anos de 1987, 1992, 1997, 2001, 2007 e 2011. Com o software ERDAS IMAGINE 9.0, foram avaliados o Ãndice de VegetaÃÃo da DiferenÃa Normalizada (NDVI) e o Ãndice de Ãrea Foliar (IAF). A obtenÃÃo dos dados socioambientais da comunidade foi atravÃs da aplicaÃÃo de questionÃrios. Na comunidade estudada, a escolaridade dos pais à inferior a dos filhos. O cultivo da mandioca à a principal atividade agrÃcola, mas a principal fonte de renda sÃo os programas do governo federal. No monitoramento da floresta, o NDVI mostrou-se sensÃvel a sazonalidade pluviomÃtrica da regiÃo e o IAF foi pouco confiÃvel no perÃodo de estiagem e a caracterÃstica do bioma influenciou nos Ãndices da vegetaÃÃo. O uso de imagens de satÃlites mostrou-se uma ferramenta eficaz no monitoramento de atividades antrÃpicas na floresta.