Thesis (M. Sc.)--University of Adelaide, Dept. of Botany, 1987. / Includes bibliographical references (leaves 113-120).

Project report (M. For.)--Virginia Polytechnic Institute and State University. M.S. 1993. / Abstract. Includes bibliographical references (leaves 32-62). Also available via the Internet.

Understanding variations in remote sensing data with illumination and sensor angle changes is important in agricultural crop monitoring. This research investigated field bidirectional reflectance factor (BRF) in crop differentiation and PROSAIL leaf area index (LAI) estimation. BRF and LAI data were collected for planophile and erectophile crops at three growth stages. In the solar principal plane, BRF differed optimally at 860 nm 60 days after planting (DAP) for canola and pea, at 860 nm 45 and 60 DAP for wheat and barley, and at 860 nm and 670 nm 45 and 60 DAP for planophiles versus erectophiles. The field BRF data helped better understand PROSAIL LAI estimation. NDVI was preferred for estimating LAI, however the MTVI2 vegetation index showed high sensitivity to view angles, particularly for erectophiles. The hotspot was important for crop differentiation and LAI. Availability of more along-track, off-nadir looking spaceborne sensors was recommended for agricultural crop monitoring. / xiii, 161 leaves : ill., map ; 29 cm

Orientador: Jurandir Zullo Junior / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Agrícola / Made available in DSpace on 2018-08-22T19:23:28Z (GMT). No. of bitstreams: 1 Lazarim_CamilaGiorgi_M.pdf: 45631852 bytes, checksum: 657cbb93f5038306a09d246ea6a15804 (MD5) Previous issue date: 2013 / Resumo: A obtenção de valores precisos e confiáveis, em uma quantidade adequada, e com a maior agilidade possível da temperatura da superfície terrestre é estratégica para aplicações de grande interesse como os estudos de mudanças climáticas e o monitoramento agrometeorólogico. As redes meteorológicas de superfície, automáticas e manuais, são de grande utilidade e imprescindíveis, mas, normalmente, apresentam limitações que dificultam a sua utilização efetiva e confiável em escala regional, tais como: i) Distribuição espacial inadequada; ii) Grande diversidade de equipamentos para medidas; iii) Difíceis condições de manutenção e acesso a dados. Os dados provenientes dos sensores remotos, a bordo dos satélites orbitais, representam uma alternativa que deve ser considerada visando o aumento da densidade, confiabilidade e agilidade de obtenção dos dados de temperatura da superfície terrestre em estudos regionais. A estimativa da evapotranspiração é um parâmetro de grande importância no monitoramento da irrigação, na simulação de balanços hídricos, no acompanhamento do desenvolvimento e produção de uma cultura agrícola, e em estudos climáticos. A utilização da temperatura de superfície como dado inicial simplifica os modelos de estimativa de evapotranspiração de uma determinada área de interesse. Esse é o caso do método S-SEBI (Simplified Surface Energy Balance Index), que se fundamenta no fluxo de calor entre a superfície do solo e a atmosfera. Sendo assim, o objetivo desse trabalho foi estimar a evapotranspiração, através do algoritmo S-SEBI, e a temperatura de superfície, utilizando um modelo adaptado dos algoritmos propostos por Sobrino et al. (1997) e Ulivieri et al. (1994) modificados por Ouaidrari et al. (2002). Isto foi feito através da avaliação do comportamento dessas equações propostas ao longo do ano, modificando constantes e dados de entrada, visando à utilização efetiva delas no monitoramento agrometeorológico. Assim, foi obtida uma equação adaptada que teve resultados significativos na estimativa da temperatura de superfície e, a partir desse dado, foi estimada a evapotranspiração que apresentou valores superestimados / Abstract: Obtaining accurate and reliable Earth's surface temperature values, adequate in quantity and with the greatest flexibility possible is of great strategic interest for applications such as studies of climate change and agrometeorological monitoring. The surface meteorological networks - both automatic and manual - are very useful and indispensable, but often have limitations that hinder their effective and reliable use in regional scale, such as: i) inadequate spatial distribution, ii) Wide range of equipment iii) Conditions of maintenance and data access. Data coming from remote sensors on board orbiting satellites represent an alternative that should be considered in order to increase the density, reliability and speed of data attainment from surface temperature in regional studies. The evapotranspiration is a parameter of great importance in monitoring the irrigation and the development and production of a crop, the water balance simulation, and climate studies. The use of surface temperature as initial data simplifies the models that estimate hourly and daily evapotranspiration for a certain area of interest. This is the case of the method SEBI S-(Simplified Surface Energy Balance Index), which is based on the heat flux between the ground surface and the atmosphere. Therefore, the objective of this work was to estimate the evapotranspiration through the S-SEBI algorithm and the surface temperature, using a model adapted from the algorithms proposed by Sobrino et al. (1997) and Ulivieri et al. (1994) modified by Ouaidrari et al. (2002). This was done by evaluating their behavior of these proposed equations over the year and modifying the constants and the input data, for their effective use in agrometeorological monitoring. Therefore, was obtained an equation adapted which had significant results in the estimated surface temperature and, from this data was estimated the evapotranspiration which presented overestimated values / Mestrado / Planejamento e Desenvolvimento Rural Sustentável / Mestra em Engenharia Agrícola

Orientador: Hélio Grassi Filho / Coorientador: Célia Regina Zimback / Banca: Maria Helena Moraes Spinelli / Banca: Paulo Milton Barbosa Landim / Banca: Diego Augusto de Campos Moraes / Banca: Aline Azevedo Narario / Resumo: A atual demanda por informações precisas e de baixo custo de obtenção causa um aumento na procura por serviços remotos, como o geoprocessamento, a geoestatística e o aprendizado de máquinas. Este trabalho objetiva a obtenção de informações relacionadas a leituras de teores de clorofila, a partir de um banco de dados de campo e por imagens de satélite aplicadas a uma área de cultivo de aveia preta, com baixos custos. Com um banco de dados preciso sobre o teor de clorofila, acredita-se ser possível reduzir custos na implantação e execução de sistemas de irrigação. Diversos autores já realizaram a comparação entre o teor de clorofila e a disponibilidade de água e outros já pontuaram o grande benefício da irrigação sobre diversos cultivares. Com a hipótese de que é possível através da utilização de técnicas de baixo custo a obtenção de valores de teor de clorofila, o trabalho utilizou de técnicas de geoestatística para procurar uma correlação entre os dados físicos e os índices de vegetação gerados a partir de imagens do satélite Landsat 5. Ao encontrar resultados insatisfatórios, partiu-se para um estudo dos dados em treinamento de máquinas e mineração de dados. Após passar por vários processos, o algoritmo Gradient Boosting Machine (GBM) possibilitou a geração de uma imagem com valores estimados clorofila bastante semelhante aos reais obtidos em campo. / Abstract: The nowadays demand for accurate and low-cost obtained information has increased the demand for remote services, such as geoprocessing, geostatistics and machine learning. This work aims to increase the accuracy of information related to readings of chlorophyll content from a field database and satellite images, applied to a black oat growing area. With a precise database on chlorophyll content, it is believed that it is possible to reduce costs in the implementation and execution of irrigation systems. Several authors have already made the comparison between chlorophyll content and water availability and others have already pointed out the great benefit of irrigation on several cultivars. With the hypothesis that is possible through the use of low cost techniques the obtaining values of chlorophyll content, the work used geostatistics techniques to search for a correlation between the physical data and the vegetation indexes generated from images of Landsat 5 satellite .When finding unsatisfactory results, we started with a study of data in machine training and data mining. And after passing through several processes, the Gradient Boosting Machine (GBM) algorithm allowed the generation of an image with estimated chlorophyll values very similar to those obtained in the field. / Doutor

Subtropical deforestation in Latin America is thought to be driven by demand for agricultural land, particularly to grow soybeans. However, existing remote sensing methods that can differentiate crop types to verify this hypothesis require high spatial or spectral resolution data, or extensive ground truth information to develop training sites, none of which are freely available for much of the world. I developed a new method of crop classification based on the phenological signatures of crops extracted from multi-temporal MODIS vegetation indices. I tested and refined this method using the USDA Cropland Data Layer from Kansas, USA as a reference. I then applied the method to classify crop types for a study site in Pellegrini, Santiago Del Estero, Argentina. The results show that this method is unable to effectively separate summer crops in Pellegrini, but can differentiate summer crops and non-summer crops. Unmet assumptions about agricultural practices are primarily responsible for the ineffective summer crop classification, underlining the need for researchers to have a complete understanding of ground conditions when designing a remote sensing analysis.

First, the field survey campaigns have been carried out from March 22, 2007 to December 27, 2007 around 5-15 days in the interval in the study area of Nansha Island. The field work includes the survey of spatial distribution of various land use and crop types and the ground measurements of the crop biophysical parameters (such as the plant height, leave area index, fresh biomass, and plant water content) and the soil parameters (such as the soil water content and surface roughness parameters) of rice field and sugarcane field. And at the same time, the ENVISAT ASAR data were acquired from March 22, 2007 to December 27, 2007 in the interval of 35 days. During the acquisition dates of the ENVISAT ASAR data, the field surveys were also conducted. / Fourth, the sufficient ground measurements and simultaneous C-band HH- and VV-polarized SAR data of sugarcane crop have enriched the knowledge of understanding the temporal radar scatter mechanisms in sugarcane canopies. The C-band VV-polarized radar backscatters are larger than those of HH-polarization during the sugarcane growth cycle, and the difference is around 0.5 dB to 2 dB. The theoretical model MIMICS was adapted in modeling the scattering terms in sugarcane fields to interpret the temporal behavior of radar backscatters. For more robotic operation, the empirical regression models were used in estimation of the sugarcane LAI and fresh biomass, and mapping the sugarcane growth situation. The accuracies of the sugarcane LAI map and Biomass map are 0.74 and 0.70, respectively. / In conclusion, the C-band ENVISAT ASAR data can be efficiently used in the Pearl River Delta to monitor the crop growth, including the crop spatial distribution, crop acreages, and crop growth situation evaluation. The efficient crop growth monitoring program can not only help instruct the flexible farming actions, but also estimate the crop yield production for the decision-making government. (Abstract shortened by UMI.) / Second, field surveys were combined with the ENVISAT ASAR data to map the agricultural area. The analysis of the temporal radar backscatter characteristics of various land cover categories demonstrated that the time series of C-band SAR data is efficient in separating the eight land cover categories (rice paddy, sugarcane, banana, lotus ponds, mangrove wetlands, fish ponds, seawater, and buildings) in the PRD. The decision tree classifier is also approved to work efficiently on satellite SAR images with an overall accuracy of 77% and the Kappa coefficient of 0.74. The acreages of the land cover categories were also derived from the classification result with accuracies from 70% to 90%. / The Pearl River Delta is a typical developing region. It lies in the cloud-prone and rainy area of south China with multi-species of crops cultured in the agriculture areas. With a goal of developing an efficient, timely and accurate crop growth monitoring program in this area, field measurement, satellite SAR remote sensing technique, quantitative analysis of the crop biophysical parameters, and radar backscatter modeling methods have been integrated to study the multi-temporal and multi-polarized SAR data in estimating plant parameters (LAI, fresh biomass) of rice and sugarcane crop, and mapping the agricultural land cover categories of the study area in the PRD. / Third, in the study of rice growth monitoring, the trends of the relationships between C-band radar backscattering coefficients and rice parameters (plant height, LAI, fresh biomass, et al.) are proved to be constant with the reports in previous literatures. It was demonstrated that the differences between HH- and VV-polarized backscatter are not so evident (around 0.5 dB) in rice paddy canopies during the crop growth cycle. Moreover, by inducting a semi-empirical soil surface scattering component, a modified Water Cloud Model was developed to simulate the radar backscatter in rice crop canopies in different ground background situations (water surface, and soil surface) and to estimate the rice LAI and above ground fresh Biomass with reasonable accuracy. The rice growth conditions were displayed by LAI map and Biomass map generated from the model estimation, and the accuracies of the LAI and Biomass level classification are 0.77 and 0.71. / Wang, Dan. / Advisers: Hui Lin; Jin-Song Chen. / Source: Dissertation Abstracts International, Volume: 72-11, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 132-138). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.