In this study we investigate the potential of fraction images derived from a linear spectral mixture model to detect vegetation phenology in Amazonia, and evaluate their relationships with the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices. Time series of MODIS 250-m data over three contrasting land cover types in the Amazon were used in conjunction with rainfall data, a land cover map and a forest inventory survey to support the interpretation of our findings.

Estimates of relevant source area of pollen (RSAP) and relative pollen productivity (PPE) are critical parameters for quantitative reconstructions of past vegetation and land cover. This study provides estimates for PPE relative to Poaceae for ten taxa, characterizing the cultural landscape of south Estonia and the RSAP for 40 lakes with an average radius of approximately 100m (22–274m, average 101m) in the region. We evaluate the effects on those estimates of various combinations of factors, such as the analytical methods (i.e.

This paper examines the newly constructed geographically scaled economic output measure, Gross Cell Product (GCP), of Australia and New Zealand to quantify the impacts of climate change in the region. The paper discusses advantages of using the GCP instead of the Gross Domestic Product. The paper reveals that the GCP falls sharply as temperature increases in the region. A 1°C increase in temperature would decrease the productivity with an elasticity of −2.4. A 1 per cent decrease in precipitation would decrease productivity with an elasticity of −2.3.

In Canada, fire danger is predicted by the Canadian Forest Fire Danger Rating System (CFFDRS). One of its subsystems is the Canadian Fire Weather Index (FWI) system, which has two slow-drying fuel moisture codes: the drought code (DC) and the duff moisture code (DMC). Both codes are used in this study as a surrogate of dead fuel moisture. We evaluate the capability of Moderate Resolution Imaging Spectrometer (MODIS) observations to map DC and DMC.

In situ measurements of soil moisture are invaluable for calibrating and validating land surface models and satellite-based soil moisture retrievals. In addition, longterm time series of in situ soil moisture measurements themselves can reveal trends in the water cycle related to climate or land cover change. Nevertheless, on a worldwide basis the number of meteorological networks and stations measuring soil moisture, in particular on a continuous basis, is still limited and the data they provide lack standardization of technique and protocol.

An algorithm for supervised classification of multisensor images is proposed. The mixture of experts (ME) architecture with dynamic weight allocation is used for multiclass classification. Here the classification is treated as a maximum likelihood problem and the synaptic weights of the expert network and gating network are updated by a stochastic multigradient approach. Data from an optical sensor with four bands and a synthetic aperture radar (SAR) image of the same scene has been fused and classified.

Oil exploitation and road development have strongly fragmented the coastal landscapes, leading to profound ecological consequences. The dynamic relationships between oil wells, roads, and landscape fragmentation indices in the Yellow River Delta, China were explored. Oil wells, roads and land cover were mapped from TM images in 1992, 2000, 2006, and 2009, respectively. Changes and relationships were compared among three selected typical sections using linear regression models.

Despite being recognized as a key baseline dataset for many applications, especially those relating to biogeochemical cycles, land cover products in their current form are limiting. Typically they lack the thematic detail necessary for driving the models that depend upon them. This study has demonstrated the ability to produce a highly detailed (both spatially and thematically) land cover/land use dataset over Russia – by combining existing datasets into a hybrid information system.

Sand dunes encroachment is a challenge that faces land development in North African countries. Movement of these dunes threatens cultivated lands, roads, and urban settlements. Geographic information system (GIS) provides a tool for cartographic modeling of risk of sand dunes encroachment. This study modeled the potential risk of sand dunes encroachment related to their terrain characteristics in the Western Desert of Egypt. The Food and Agricultural Organization's land cover map of Egypt derived from Landsat Thematic Mapper was used to locate the sand dunes bodies.

This article examines the transition from shifting cultivation to rubber production for a study area in northern Laos PDR using an agent-based model of land-cover change. A primary objective of the model was to assess changes in household-level inequality with the transition from shifting cultivation to rubber adoption. A secondary objective was to develop explanations for the rate of rubber adoption in the study area.

Lithology is an important characteristic of the terrestrial surface, whose properties influence chemical weathering rates. Specifically non-silicate minerals may contribute significantly to the weathering derived fluxes from silicate-dominated lithological classes. The Japanese Archipelago consists of predominantly silicate-dominated lithologies with a high proportion of volcanics.

Event based rainfall-runoff simulation is very important in water resources management. In this paper, an integrated watershed model considering important hydrological processes has been presented for the event based runoff simulation. Green–Ampt–Mein–Larson model has been used for the estimation of infiltration. For runoff estimation, kinematic wave equations are solved for a channel network using finite-element method. Remotely sensed data have been used for evaluating land use/land cover data.