Labeling research in support of through-the-season area estimation

The development of LANDSAT-based through-the-season labeling procedures for corn and soybeans is discussed. A model for predicting labeling accuracy within key time periods throughout the growing season is outlined. Two methods for establishing the starting point of one key time period, viz., early season, are described. In addition, spectral-temporal characteristics for separating crops in the early season time period are discussed

Soil erosion in the Alps : causes and risk assessment

The issue of soil erosion in the Alps has long been neglected due to the low economic value of the agricultural land. However, soil stability is a key parameter which affects ecosystem services like slope stability, water budgets (drinking water reservoirs as well as flood prevention), vegetation productivity, ecosystem biodiversity and nutrient production. In alpine regions, spatial estimates on soil erosion are difficult to derive because the highly heterogeneous biogeophysical structure impedes measurement of soil erosion and the applicability of soil erosion models. However, remote sensing and geographic information system (GIS) methods allow for spatial estimation of soil erosion by direct detection of erosion features and supply of input data for soil erosion models. Thus, the main objective of this work is to address the problem of soil erosion risk assessment in the Alps on catchment scale with remote sensing and GIS tools. Regarding soil erosion processes the focus is on soil erosion by water (here sheet erosion) and gravity (here landslides). For these two processes we address i) the monitoring and mapping of the erosion features and related causal factors ii) soil erosion risk assessment with special emphasis on iii) the validation of existing models for alpine areas. All investigations were accomplished in the Urseren Valley (Central Swiss Alps) where the valley slopes are dramatically affected by sheet erosion and landslides. For landslides, a natural susceptibility of the catchment has been indicated by bivariate and multivariate statistical analysis. Geology, slope and stream density are the most significant static landslide causal factors. Static factors are here defined as factors that do not change their attributes during the considered time span of the study (45 years), e.g. geology, stream network. The occurrence of landslides might be significantly increased by the combined effects of global climate and land use change. Thus, our hypothesis is that more recent changes in land use and climate affected the spatial and temporal occurrence of landslides. The increase of the landslide area of 92% within 45 years in the study site confirmed our hypothesis. In order to identify the cause for the trend in landslide occurrence time-series of landslide causal factors were analysed. The analysis revealed increasing trends in the frequency and intensity of extreme rainfall events and stocking of pasture animals. These developments presumably enhanced landslide hazard. Moreover, changes in land-cover and land use were shown to have affected landslide occurrence. For instance, abandoned areas and areas with recently emerging shrub vegetation show very low landslide densities. Detailed spatial analysis of the land use with GIS and interviews with farmers confirmed the strong influence of the land use management practises on slope stability. The definite identification and quantification of the impact of these non-stationary landslide causal factors (dynamic factors) on the landslide trend was not possible due to the simultaneous change of several factors. The consideration of dynamic factors in statistical landslide susceptibility assessments is still unsolved. The latter may lead to erroneous model predictions, especially in times of dramatic environmental change. Thus, we evaluated the effect of dynamic landslide causal factors on the validity of landslide susceptibility maps for spatial and temporal predictions. For this purpose, a logistic regression model based on data of the year 2000 was set up. The resulting landslide susceptibility map was valid for spatial predictions. However, the model failed to predict the landslides that occurred in a subsequent event. In order to handle this weakness of statistic landslide modelling a multitemporal approach was developed. It is based on establishing logistic regression models for two points in time (here 1959 and 2000). Both models could correctly classify >70% of the independent spatial validation dataset. By subtracting the 1959 susceptibility map from the 2000 susceptibility map a deviation susceptibility map was obtained. Our interpretation was that these susceptibility deviations indicate the effect of dynamic causal factors on the landslide probability. The deviation map explained 85% of new independent landslides occurring after 2000. Thus, we believe it to be a suitable tool to add a time element to a susceptibility map pointing to areas with changing susceptibility due to recently changing environmental conditions or human interactions. In contrast to landslides that are a direct threat to buildings and infrastructure, sheet erosion attracts less attention because it is often an unseen process. Nonetheless, sheet erosion may account for a major proportion of soil loss. Soil loss by sheet erosion is related to high spatial variability, however, in contrast to arable fields for alpine grasslands erosion damages are long lasting and visible over longer time periods. A crucial erosion triggering parameter that can be derived from satellite imagery is fractional vegetation cover (FVC). Measurements of the radiogenic isotope Cs-137, which is a common tracer for soil erosion, confirm the importance of FVC for soil erosion yield in alpine areas. Linear spectral unmixing (LSU), mixture tuned matched filtering (MTMF) and the spectral index NDVI are applied for estimating fractional abundance of vegetation and bare soil. To account for the small scale heterogeneity of the alpine landscape very high resolved multispectral QuickBird imagery is used. The performance of LSU and MTMF for estimating percent vegetation cover is good (r²=0.85, r²=0.71 respectively). A poorer performance is achieved for bare soil (r²=0.28, r²=0.39 respectively) because compared to vegetation, bare soil has a less characteristic spectral signature in the wavelength domain detected by the QuickBird sensor. Apart from monitoring erosion controlling factors, quantification of soil erosion by applying soil erosion risk models is done. The performance of the two established models Universal Soil Loss Equation (USLE) and Pan-European Soil Erosion Risk Assessment (PESERA) for their suitability to model erosion for mountain environments is tested. Cs-137 is used to verify the resulting erosion rates from USLE and PESERA. PESERA yields no correlation to measured Cs-137 long term erosion rates and shows lower sensitivity to FVC. Thus, USLE is used to model the entire study site. The LSU-derived FVC map is used to adapt the C factor of the USLE. Compared to the low erosion rates computed with the former available low resolution dataset (1:25000) the satellite supported USLE map shows “hotspots” of soil erosion of up to 16 t ha-1 a-1. In general, Cs-137 in combination with the USLE is a very suitable method to assess soil erosion for larger areas, as both give estimates on long-term soil erosion. Especially for inaccessible alpine areas, GIS and remote sensing proved to be powerful tools that can be used for repetitive measurements of erosion features and causal factors. In times of global change it is of crucial importance to account for temporal developments. However, the evaluation of the applied soil erosion risk models revealed that the implementation of temporal aspects, such as varying climate, land use and vegetation cover is still insufficient. Thus, the proposed validation strategies (spatial, temporal and via Cs-137) are essential. Further case studies in alpine regions are needed to test the methods elaborated for the Urseren Valley. However, the presented approaches are promising with respect to improve the monitoring and identification of soil erosion risk areas in alpine regions

VARIAÇÃO SAZONAL DO CARBONO ORGÂNICO DISSOLVIDO (COD) E PROPRIEDADES ÓPTICAS DA MATÉRIA ORGÂNICA EM DIFERENTES SISTEMAS DE PASTAGEM E DE SOJA NO ESTADO DE MATO GROSSO

O objetivo deste estudo é caracterizar uma quantidade e qualidade do carbono orgânico dissolvido (COD) em diferentes condições hídricas nos sistemas de produção de massa e soja no estado de Mato Grosso. Como amostrogens foram realizadas nas estações úmidas (Fevereiro-março) e nas estações secas (setembro-outubro). Uma concentração de COD e seus bens de fluorescência óptica medidos a partir de amostras coletadas em diferentes ecossistemas não Estado de Mato Grosso (Cerrado, Pantanal, Amazônia e ecótono Cerrado / Amazônia). A concentração de COD variou significativamente entre diferentes sistemas e períodos hidrológicos. O IF (Índice de fluorescência) variaram significativamente apenas entre como estações hidrológicas.Os valores de IF caracterizam principalmente fontes alóctones de matéria orgânica. Uma análise de SR também indicou significativas entre locais, ecossistemas e estações hidrológicas. Uma análise das propriedades ópticas sugerem uma grande quantidade de nossos dispositivos de controle, o que sugere uma presença de lixiviados ea rápida e ineficiente decomposição das plantas aquáticas. Nas áreas de soja, picos de alta intensidade, foram identificados para o componente de tirosina sem bioma Cerrado. Com isso, uma concentração de COD, e os índices referentes à sua qualidade, diferiu entre ecossistemas de estudo e períodos hidrológicos.Uma análise das propriedades ópticas sugerem uma grande quantidade de nossos dispositivos de controle, o que sugere uma presença de lixiviados ea rápida e ineficiente decomposição das plantas aquáticas. Nas áreas de soja, picos de alta intensidade, foram identificados para o componente de tirosina sem bioma Cerrado. Com isso, uma concentração de COD, e os índices referentes à sua qualidade, diferiu entre ecossistemas de estudo e períodos hidrológicos. Uma análise das propriedades ópticas sugerem uma grande quantidade de nossos dispositivos de controle, o que sugere uma presença de lixiviados ea rápida e ineficiente decomposição das plantas aquáticas.Nas áreas de soja, picos de alta intensidade, foram identificados para o componente de tirosina sem bioma Cerrado. Com isso, uma concentração de COD, e os índices referentes à sua qualidade, diferiu entre ecossistemas de estudo e períodos hidrológicos.O objetivo deste estudo é caracterizar a quantidade e a qualidade do carbono orgânico dissolvido (COD) em diferentes condições hídricas nos sistemas de produção de pastagem e soja no estado de Mato Grosso. As amostragens foram realizadas nas estações úmidas(Fevereiro-março) e nas estações secas (setembro-outubro). A concentração de COD e suas propriedades de fluorescência óptica foram medidos a partir de amostras coletadas em diferentes ecossistemas no Estado de Mato Grosso (Cerrado, Pantanal, Amazônia e ecótono Cerrado/Amazônia). A concentração de COD variou significativamente entre diferentes sistemas e períodos hidrológicos. O IF (Índice de fluorescência) variaram significativamente apenas entre as estações hidrológicas. Os valores de IF caracterizam principalmente fontes alóctones de matéria orgânica. A análise de SR também indicou diferenças significativas entre locais, ecossistemas e estações hidrológicas. A análise das propriedades ópticas sugeriu uma grande quantidade de componentes húmicos nos sistemas de pastagem, o que sugere a presença de lixiviados e a rápida e ineficiente decomposição das plantas aquáticas. Nas áreas de soja, picos de alta intensidade foram identificados para o componente de tirosina no bioma Cerrado. Com isso, a concentração de COD, e os índices referentes a sua qualidade, diferiu entre ecossistemas de estudo e períodos hidrológicos

Evaluation of ERTS-1 data for inventory of forest and rangeland and detection of forest stress

The author has identified the following significant results. Results of photointerpretation indicated that ERTS is a good classifier of forest and nonforest lands (90 to 95 percent accurate). Photointerpreters could make this separation as accurately as signature analysis of the computer compatible tapes. Further breakdowns of cover types at each site could not be accurately classified by interpreters (60 percent) or computer analysts (74 percent). Exceptions were water, wet meadow, and coniferous stands. At no time could the large bark beetle infestations (many over 300 meters in size) be detected on ERTS images. The ERTS wavebands are too broad to distinguish the yellow, yellow-red, and red colors of the dying pine foliage from healthy green-yellow foliage. Forest disturbances could be detected on ERTS color composites about 90 percent of the time when compared with six-year-old photo index mosaics. ERTS enlargements (1:125,000 scale, preferably color prints) would be useful to forest managers of large ownerships over 5,000 hectares (12,500 acres) for broad area planning. Black-and-white enlargements can be used effectively as aerial navigation aids for precision aerial photography where maps are old or not available

A Primer for Monitoring Water Funds

This document is intended to assist people working on Water Funds to understand their information needs and become familiar with the strengths and weaknesses of various monitoring approaches. This primer is not intended to make people monitoring experts, but rather to help them become familiar with and conversant in the major issues so they can communicate effectively with experts to design a scientifically defensible monitoring program.The document highlights the critical information needs common to Water Fund projects and summarizes issues and steps to address in developing a Water Fund monitoring program. It explains key concepts and challenges; suggests monitoring parameters and an array of sampling designs to consider as a starting-point; and provides suggestions for further reading, links to helpful resources,and an annotated bibliography of studies on the impacts that result from activities commonly implemented in Water Fund projects

Earth Resources Laboratory research and technology

The accomplishments of the Earth Resources Laboratory's research and technology program are reported. Sensors and data systems, the AGRISTARS project, applied research and data analysis, joint research projects, test and evaluation studies, and space station support activities are addressed

Development of techniques for producing static strata maps and development of photointerpretation methods based on multitemporal LANDSAT data

The progress of research conducted in support of the Large Area Crop Inventory Experiment (LACIE) is documented. Specific tasks include (1) evaluation of the static stratification procedure and modification of that procedure if warranted, and (2) the development of alternative photointerpretative techniques to the present LACIE procedures for the identification and selection of training fields (areas)

Multispectral scanner data applications evaluation. Volume 1: User applications study

A six-month systems study of earth resource surveys from satellites was conducted and is reported. SKYLAB S-192 multispectral scanner (MSS) data were used as a baseline to aid in evaluating the characteristics of future systems using satellite MSS sensors. The study took the viewpoint that overall system (sensor and processing) characteristics and parameter values should be determined largely by user requirements for automatic information extraction performance in quasi-operational earth resources surveys, the other major factor being hardware limitations imposed by state-of-the-art technology and cost. The objective was to use actual aircraft and spacecraft MSS data to outline parametrically the trade-offs between user performance requirements and hardware performance and limitations so as to allow subsequent evaluation of compromises which must be made in deciding what system(s) to build

Unveiling the potential of proximal hyperspectral sensing for measuring herbage nutritive value in a pasture-based dairy farm system : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Agriculture and Horticulture at Massey University, Manawatū, New Zealand

The aim of this thesis was to unveil the potential of proximal hyperspectral sensing for measuring herbage nutritive value in a pasture based-dairy farm system. Hyperspectral canopy reflectance and herbage cuts as well as data on herbage and supplement allocation, and milk production were collected regularly from Dairy 1 farm at Massey University during the 2016-17 and 2017-18 production seasons. Milk, fat and protein yields and body condition score of cows were measured at monthly herd tests while live weights were recorded daily. Calibration equations determining herbage the nutritive value traits digestible organic matter in dry matter, metabolisable energy (ME), crude protein, neutral detergent fibre and acid detergent fibre from hyperspectral canopy reflectance data were developed and validated using partial least squares regression. Canopy reflectance calibration models were able to determine the various herbage nutritive value traits with R2 values ranging from 0.57 to 0.78. Variation of herbage nutritive value traits were mostly explained by month within production season (42.7% of variance among traits) followed by random error (33.4%), production season (13.1%) and paddock (10.7%). The relative importance of herbage nutritive value and other herbage quantity and climate-related variables in driving performance per cow in the herd was determined using multiple linear regression. Herbage metabolizable energy explained 20% to 30% of milk, fat and protein production per cow while herbage quantity and climate- related factors were relatively less important (below 15%). Random regression models were used to model lactation curves of milk, fat, protein and live weight to estimate daily ME requirements of individual cows. The daily ME estimated requirements was nearly a fifth above or below the daily mean ME supplied. The deviation of the daily ME estimated requirements of a cow from the actual ME supplied per cow in the herd was mostly explained by the observations made within a cow rather than between cows or breeds. Variation in herbage nutritive value in addition to the within and between cow variation of ME estimated requirements were high enough to justify the use of proximal hyperspectral sensing as measurement tool to assist with feed allocation decision-making. However, the potential of this technology could be further enhanced using more precise technologies to allocate herbage to individual cows or groups of cows. The potential benefits of more precise feed allocation will result in more efficient grazing management and thus improved utilisation of herbage and hence milk production

Source-tracking cadmium in New Zealand agricultural soils: a stable isotope approach

Cadmium (Cd) is a toxic heavy metal, which is accumulated by plants and animals and therefore enters the human food chain. In New Zealand (NZ), where Cd mainly originates from the application of phosphate fertilisers, stable isotopes can be used to trace the fate of Cd in soils and potentially the wider environment due to the limited number of sources in this setting. Prior to 1997, extraneous Cd added to soils in P fertilisers was essentially limited to a single source, the small pacific island of Nauru. Analysis of Cd isotope ratios (ɛ114/110Cd) in Nauru rock phosphate, pre-1997 superphosphate fertilisers, and Canterbury (Lismore Stony Silt Loam) topsoils (Winchmore Research Farm) has demonstrated their close similarity with respect to ɛ114/110Cd. We report a consistent ɛ114/110Cd signature in fertiliser-derived Cd throughout the latter twentieth century. This finding is useful because it allows the application of mixing models to determine the proportions of fertiliser-derived Cd in the wider environment. We believe this approach has good potential because we also found the ɛ114/110Cd in fertilisers to be distinct from unfertilised Canterbury subsoils. In our analysis of the Winchmore topsoil series (1949-2015), the ɛ114/110Cd remained quite constant following the change from Nauru to other rock phosphate sources in 1997, despite a corresponding shift in fertiliser ɛ114/110Cd at this time. We can conclude that to the present day, the Cd in topsoil at Winchmore still mainly originates from historical phosphate fertilisers. One implication of this finding is that the current applications of P fertiliser are not resulting in further Cd accumulation. We aim to continue our research into Cd fate, mobility and transformations in the NZ environment by applying Cd isotopes in soils and aquatic environments across the country