A geostatistical analysis of soil, vegetation, and image data characterizing land surface variation

The elucidation of spatial variation in the landscape can indicate potential wildlife habitats or breeding sites for vectors, such as ticks or mosquitoes, which cause a range of diseases. Information from remotely sensed data could aid the delineation of vegetation distribution on the ground in areas where local knowledge is limited. The data from digital images are often difficult to interpret because of pixel-to-pixel variation, that is, noise, and complex variation at more than one spatial scale. Landsat Thematic Mapper Plus (ETM+) and Satellite Pour l'Observation de La Terre (SPOT) image data were analyzed for an area close to Douna in Mali, West Africa. The variograms of the normalized difference vegetation index (NDVI) from both types of image data were nested. The parameters of the nested variogram function from the Landsat ETM+ data were used to design the sampling for a ground survey of soil and vegetation data. Variograms of the soil and vegetation data showed that their variation was anisotropic and their scales of variation were similar to those of NDVI from the SPOT data. The short- and long-range components of variation in the SPOT data were filtered out separately by factorial kriging. The map of the short-range component appears to represent the patterns of vegetation and associated shallow slopes and drainage channels of the tiger bush system. The map of the long-range component also appeared to relate to broader patterns in the tiger bush and to gentle undulations in the topography. The results suggest that the types of image data analyzed in this study could be used to identify areas with more moisture in semiarid regions that could support wildlife and also be potential vector breeding sites.

Biotic carbon feedbacks in a materially-closed soil-vegetation-atmosphere system

The magnitude and direction of the coupled feedbacks between the biotic and abiotic components of the terrestrial carbon cycle is a major source of uncertainty in coupled climate–carbon-cycle models1, 2, 3. Materially closed, energetically open biological systems continuously and simultaneously allow the two-way feedback loop between the biotic and abiotic components to take place4, 5, 6, 7, but so far have not been used to their full potential in ecological research, owing to the challenge of achieving sustainable model systems6, 7. We show that using materially closed soil–vegetation–atmosphere systems with pro rata carbon amounts for the main terrestrial carbon pools enables the establishment of conditions that balance plant carbon assimilation, and autotrophic and heterotrophic respiration fluxes over periods suitable to investigate short-term biotic carbon feedbacks. Using this approach, we tested an alternative way of assessing the impact of increased CO2 and temperature on biotic carbon feedbacks. The results show that without nutrient and water limitations, the short-term biotic responses could potentially buffer a temperature increase of 2.3 °C without significant positive feedbacks to atmospheric CO2. We argue that such closed-system research represents an important test-bed platform for model validation and parameterization of plant and soil biotic responses to environmental changes.

Delineation of specific management areas for coffee cultivation based on the soil-relief relationship and numerical classification

Predicting and mapping productivity areas allows crop producers to improve their planning of agricultural activities. The primary aims of this work were the identification and mapping of specific management areas allowing coffee bean quality to be predicted from soil attributes and their relationships to relief. The study area was located in the Southeast of the Minas Gerais state, Brazil. A grid containing a total of 145 uniformly spaced nodes 50 m apart was established over an area of 31. 7 ha from which samples were collected at depths of 0. 00-0. 20 m in order to determine physical and chemical attributes of the soil. These data were analysed in conjunction with plant attributes including production, proportion of beans retained by different sieves and drink quality. The results of principal component analysis (PCA) in combination with geostatistical data showed the attributes clay content and available iron to be the best choices for identifying four crop production environments. Environment A, which exhibited high clay and available iron contents, and low pH and base saturation, was that providing the highest yield (30. 4l ha-1) and best coffee beverage quality (61 sacks ha-1). Based on the results, we believe that multivariate analysis, geostatistics and the soil-relief relationships contained in the digital elevation model (DEM) can be effectively used in combination for the hybrid mapping of areas of varying suitability for coffee production. © 2012 Springer Science+Business Media New York.

Validation and comparison of two soil-vegetation-atmosphere transfer models for tropical Africa

This study aims to compare and validate two soil-vegetation-atmosphere-transfer (SVAT) schemes: TERRA-ML and the Community Land Model (CLM). Both SVAT schemes are run in standalone mode (decoupled from an atmospheric model) and forced with meteorological in-situ measurements obtained at several tropical African sites. Model performance is quantified by comparing simulated sensible and latent heat fluxes with eddy-covariance measurements. Our analysis indicates that the Community Land Model corresponds more closely to the micrometeorological observations, reflecting the advantages of the higher model complexity and physical realism. Deficiencies in TERRA-ML are addressed and its performance is improved: (1) adjusting input data (root depth) to region-specific values (tropical evergreen forest) resolves dry-season underestimation of evapotranspiration; (2) adjusting the leaf area index and albedo (depending on hard-coded model constants) resolves overestimations of both latent and sensible heat fluxes; and (3) an unrealistic flux partitioning caused by overestimated superficial water contents is reduced by adjusting the hydraulic conductivity parameterization. CLM is by default more versatile in its global application on different vegetation types and climates. On the other hand, with its lower degree of complexity, TERRA-ML is much less computationally demanding, which leads to faster calculation times in a coupled climate simulation.

Relação entre vegetação e solo em um gradiente florestal na Estação Ecológica do Panga, Uberlândia (MG)

Relacionou-se a composição física (granulometria) e química (macronutrientes e parâmetros de fertilidade) do solo com um gradiente florestal formado por mata de galeria, mata mesófila semidecídua de encosta e cerradão, na Estação Ecológica do Panga, Uberlândia - MG. Foram analisadas 211 amostras de solo, coletadas a uma profundidade de 0-20 cm. As fitofisionomias são estatisticamente distintas entre si quanto a cálcio, magnésio, potássio, fósforo, alumínio, saturação por alumínio, saturação por bases e matéria orgânica, enquanto que, para outros atributos edáficos, podem ser encontrados pares fitofisionômicos semelhantes. Algumas espécies vegetais encontram-se distribuídas no gradiente florestal seguindo a variação da composição físico-química do solo, enquanto outras se apresentam indiferentes ao gradiente edáfico. Há evidências de que o solo representa um importante papel para a estruturação vegetal ao longo do gradiente florestal estudado.

Influência do solo e topografia sobre as variações da composição florística e estrutura da comunidade arbóreo-arbustiva de uma floresta estacional semidecidual em Ingaí, MG

Foi realizado um levantamento da comunidade arbóreo-arbustiva, da topografia e dos solos de um fragmento de floresta estacional semidecidual com o objetivo de verificar as possíveis correlações entre variações da estrutura fisionômica e composição de espécies e variações do regime de água e fertilidade química dos solos. O fragmento florestal, com área de 17 ha, localiza-se às margens do rio Ingaí (21º24' S e 44º55' W), no município de Ingaí, MG. Foram realizados um levantamento plani-altimétrico da área e uma classificação detalhada dos solos da floresta. Foram alocadas 25 parcelas de 20 × 20 m para amostrar os indivíduos arbóreo-arbustivos com diâmetro à altura do peito (DAP) > ou = 5 cm. Amostras do solo superficial (0-20 cm de profundidade) foram coletadas nas parcelas para análises das propriedades químicas e texturais. Foram registrados nas parcelas 2.683 indivíduos distribuídos em 140 espécies, 90 gêneros e 41 famílias, bem como quatro subgrupos de solos e seis classes de drenagem. Uma análise de correspondência canônica (CCA) dos padrões emergentes das variáveis ambientais e da abundância das espécies indicou que estas se distribuem no fragmento sob forte influência do regime de água e da fertilidade química dos solos. Além disso, várias espécies produziram correlações significativas entre sua abundância nas parcelas e as classes de drenagem e saturação por bases dos solos, sugerindo que água e nutrientes minerais são as principais variáveis ambientais determinando a distribuição das espécies na floresta.

RELAÇÕES SOLO–VEGETAÇÃO EM “ILHAS” FLORESTAIS SAVANAS ADJACENTES, NO NORDESTE DE RORAIMA

Studies on soils of forest islands within the savanna domain are key for understanding processes of landscape formation and evolution. We characterized the morphological, physical and chemical properties of soils at four different forest fragments that occur in the savanna-forest mosaic of northeastern Roraima, north Amazonia. The methodology was based on transects crossing the entire island, from east-west and northsouth direction, digging up five soil profiles for sampling and classification. In addition, the neighboring savannas were also sampled following the same strategy, at 100 m long transects departing from the border, allowing comparisons to be made. Latosols were the dominant soil class in all four islands, followed by Ultisols and Plinthosols. All soils were dystric, with low CEC and acid. Better chemical and physical conditions were observed in forested soils compared with surrounding savannas, in a given soil class. Thus, in spite of no variation on soil class at different phytophysionomies at a given gradient, specific chemical and physical attributes were significantly varied, exerting a positive effect for the establishment of forest vegetation. Despite their occurrence side-by-side in the savanna-forest mosaic, the present-day climate agrees with the existence of savanna in the flat landforms, whereas forest islands are conditioned by subtle, yet significant, soil physico-chemical variations, with no need to invoke any paleoclimate for explaining this relationship. Further in depth studies may contribute for testing the hypothesis that Quaternary shifts of the expansion and contraction of forest may represent paleoclimate relicts isolated within the savanna domain.

Relationship Between Edaphic Factors and Vegetation in Savannas of the Brazilian Midwest Region

The Brazilian savanna is a mosaic of phytophysiognomies influenced by edaphic and topographic factors that range from the occurrence of fires to anthropic disturbance. The goal of this study was a comparative analysis between two cerrado areas in southeastern Goiás, relating the floristic composition and structure of the vegetation to soil properties to better understand the physiognomic characteristics of the region. Twenty-five 20 × 20 m plots were used. All plants with circumference at breast height of more than 15 cm were measured. Soil samples collected at a depth of 0-20 cm were subjected to physical and chemical analyses. Canonical correspondence analysis (CCA) was used to detect possible correlations between the soil properties and species abundance and distribution. The density and total basal area were 1,647 ind/ha and 15.57 m2/ha, respectively, in Ouroana. At this site, 107 species were sampled. In Montes Claros de Goiás, the density and total basal area were 781 ind/ha and 17.62 m2/ha, and 120 species were sampled. The soil texture of Ouroana was sandy and significantly different from the medium to clayey texture of Montes Claros. The soils of both areas are dystrophic, however, more fertile in Montes Claros and aluminum-toxic in Ouroana. The species of vegetation were distributed according to soil fertility levels. The CCAs grouped species according to soil properties that defined location and abundance as well as the phytophysiognomies of the studied areas.

Emergent geomorphic-vegetation interactions on a subalpine alluvial fan

Following perturbation, an ecosystem (flora, fauna, soil) should evolve as a function of time at a rate conditioned by external variables (relief, climate, geology). More recently, biogeomorphologists have focused upon the notion of co-development of geomorphic processes with ecosystems over very short through to very long (evolutionary) timescales. Alpine environments have been a particular focus of this co-development. However, work in this field has tended to adopt a simplified view of the relationship between perturbation and succession, including: how the landform and ecosystem itself conditions the impact of a perturbation to create a complex spatial response impact; and how perturbations are not simply ecosystem destroyers but can be a significant source of ecosystem resources. What this means is that at the within landform scale, there may well be a complex and dynamic topographic and sedimentological template that co-develops with soil, flora and fauna. Here, we present and test a conceptual model of this template for a subalpine alluvial fan. We combine detailed floristic inventory with soil inventory, determination of edaphic variables and analysis of historical aerial imagery. Spatial variation in the probability of perturbation of sites on the fan surface was associated with down fan variability in the across-fan distribution of fan ages, fan surface channel characteristics and fan surface sedimentology. Floristic survey confirmed that these edaphic factors distinguished site floristic richness and plant communities up until the point that the soil-vegetation system was sufficiently developed to sustain plant communities regardless of edaphic conditions. Thus, the primary explanatory variable was the estimated age of each site, which could be tied back into perturbation history and its spatial expression due to the geometry of the fan: distinct plant communities were emergent both across fan and down fan, a distribution maintained by the way in which the fan dissipates potentially perturbing events.

Effects of sub-pixel heterogeneity on the retrieval of soil moisture from passive microwave radiometry

A simple formulation relating the L-band microwave brightness temperature detected by a passive microwave radiometer to the near surface soil moisture was developed using MICRO-SWEAT, a coupled microwave emission model and soil-vegetation-atmosphere-transfer (SVAT) scheme. This simple model provides an ideal tool with which to explore the impact of sub-pixel heterogeneity on the retrieval of soil moisture from microwave brightness temperatures. In the case of a bare soil pixel, the relationship between apparent emissivity and surface soil moisture is approximately linear, with the clay content of the soil influencing just the intercept of this relationship. It is shown that there are no errors in the retrieved soil moisture from a bare soil pixel that is heterogeneous in soil moisture and texture. However, in the case of a vegetated pixel, the slope of the relationship between apparent emissivity and surface soil moisture decreases with increasing vegetation. Therefore for a pixel that is heterogeneous in vegetation and soil moisture, errors can be introduced into the retrieved soil moisture. Generally, under moderate conditions, the retrieved soil moisture is within 3% of the actual soil moisture. Examples illustrating this discussion use data collected during the Southern Great Plains '97 Experiment (SGP97).

Soil Influence on Forest Vegetation Productivity and Patterns in the Eastern Cascades of Southern Oregon

Thesis (Master's)--University of Washington, 2016-06

The investigation of vegetation change using remote sensing to detect and monitor migration of landfill gas

Decomposition of domestic wastes in an anaerobic environment results in the production of landfill gas. Public concern about landfill disposal and particularly the production of landfill gas has been heightened over the past decade. This has been due in large to the increased quantities of gas being generated as a result of modern disposal techniques, and also to their increasing effect on modern urban developments. In order to avert diasters, effective means of preventing gas migration are required. This, in turn requires accurate detection and monitoring of gas in the subsurface. Point sampling techniques have many drawbacks, and accurate measurement of gas is difficult. Some of the disadvantages of these techniques could be overcome by assessing the impact of gas on biological systems. This research explores the effects of landfill gas on plants, and hence on the spectral response of vegetation canopies. Examination of the landfill gas/vegetation relationship is covered, both by review of the literature and statistical analysis of field data. The work showed that, although vegetation health was related to landfill gas, it was not possible to define a simple correlation. In the landfill environment, contribution from other variables, such as soil characteristics, frequently confused the relationship. Two sites are investigated in detail, the sites contrasting in terms of the data available, site conditions, and the degree of damage to vegetation. Gas migration at the Panshanger site was dominantly upwards, affecting crops being grown on the landfill cap. The injury was expressed as an overall decline in plant health. Discriminant analysis was used to account for the variations in plant health, and hence the differences in spectral response of the crop canopy, using a combination of soil and gas variables. Damage to both woodland and crops at the Ware site was severe, and could be easily related to the presence of gas. Air photographs, aerial video, and airborne thematic mapper data were used to identify damage to vegetation, and relate this to soil type. The utility of different sensors for this type of application is assessed, and possible improvements that could lead to more widespread use are identified. The situations in which remote sensing data could be combined with ground survey are identified. In addition, a possible methodology for integrating the two approaches is suggested.

The relationship between vegetation and modern pollen assemblages on Mount Paggeo (NE Greece)

In this study, we investigated the relationship between vegetation and modern-pollen rain along the elevational gradient of Mount Paggeo. We apply multivariate data analysis to assess the relationship between vegetation and modern-pollen rain and quantify the representativeness of forest zones. This study represents the first statistical analysis of pollen-vegetation relationship along an elevational gradient in Greece. Hence, this paper improves confidence in interpretation of palynological records from north-eastern Greece and may refine past climate reconstructions for a more accurate comparison of data and modelling. Numerical classification and ordination were performed on pollen data to assess differences among plant communities that beech (Fagus sylvatica) dominates or co-dominates. The results show a strong relationship between altitude, arboreal cover, human impact and variations in pollen and nonpollen palynomorph taxa percentages.

An appropriate data set size for digital soil mapping in Erechim, Rio Grande do Sul, Brazil

Digital information generates the possibility of a high degree of redundancy in the data available for fitting predictive models used for Digital Soil Mapping (DSM). Among these models, the Decision Tree (DT) technique has been increasingly applied due to its capacity of dealing with large datasets. The purpose of this study was to evaluate the impact of the data volume used to generate the DT models on the quality of soil maps. An area of 889.33 km² was chosen in the Northern region of the State of Rio Grande do Sul. The soil-landscape relationship was obtained from reambulation of the studied area and the alignment of the units in the 1:50,000 scale topographic mapping. Six predictive covariates linked to the factors soil formation, relief and organisms, together with data sets of 1, 3, 5, 10, 15, 20 and 25 % of the total data volume, were used to generate the predictive DT models in the data mining program Waikato Environment for Knowledge Analysis (WEKA). In this study, sample densities below 5 % resulted in models with lower power of capturing the complexity of the spatial distribution of the soil in the study area. The relation between the data volume to be handled and the predictive capacity of the models was best for samples between 5 and 15 %. For the models based on these sample densities, the collected field data indicated an accuracy of predictive mapping close to 70 %.

Comparison between detailed digital and conventional soil maps of an area with complex geology

Since different pedologists will draw different soil maps of a same area, it is important to compare the differences between mapping by specialists and mapping techniques, as for example currently intensively discussed Digital Soil Mapping. Four detailed soil maps (scale 1:10.000) of a 182-ha sugarcane farm in the county of Rafard, São Paulo State, Brazil, were compared. The area has a large variation of soil formation factors. The maps were drawn independently by four soil scientists and compared with a fifth map obtained by a digital soil mapping technique. All pedologists were given the same set of information. As many field expeditions and soil pits as required by each surveyor were provided to define the mapping units (MUs). For the Digital Soil Map (DSM), spectral data were extracted from Landsat 5 Thematic Mapper (TM) imagery as well as six terrain attributes from the topographic map of the area. These data were summarized by principal component analysis to generate the map designs of groups through Fuzzy K-means clustering. Field observations were made to identify the soils in the MUs and classify them according to the Brazilian Soil Classification System (BSCS). To compare the conventional and digital (DSM) soil maps, they were crossed pairwise to generate confusion matrices that were mapped. The categorical analysis at each classification level of the BSCS showed that the agreement between the maps decreased towards the lower levels of classification and the great influence of the surveyor on both the mapping and definition of MUs in the soil map. The average correspondence between the conventional and DSM maps was similar. Therefore, the method used to obtain the DSM yielded similar results to those obtained by the conventional technique, while providing additional information about the landscape of each soil, useful for applications in future surveys of similar areas.