Agricultural activities have dramatically altered our planet's land surface. To understand the extent and spatial distribution of these changes, we have developed a new global data set of croplands and pastures circa 2000 by combining agricultural inventory data and satellite-derived land cover data. The agricultural inventory data, with much greater spatial detail than previously available, is used to train a land cover classification data set obtained by merging two different satellite-derived products (Boston University's MODIS-derived land cover product and the GLC2000 data set).

We studied landscape dynamics for three time periods (

Forest cover monitoring plays an important role in the implementation of climate change mitigation policies such as Kyoto protocol and Reducing Emissions from Deforestation and Forest Degradation (REDD). In this study, we have monitored land cover using the PALSAR (Phased Array type L-band Synthetic Aperture Radar) full polarimetric data based on incoherent target decomposition.

The relationship among land cover, topography, built structure and stream water quality in the Portland Metro region of Oregon and Clark County, Washington areas, USA, is analyzed using ordinary least squares (OLS) and geographically weighted (GWR) multiple regression models. Two scales of analysis, a sectional watershed and a buffer, offered a local and a global investigation of the sources of stream pollutants. Model accuracy, measured by R² values, fluctuated according to the scale, season, and regression method used.

We analysed coexistence patterns between two mesocarnivores, Geoffroy's cat (Leopardus geoffroyi: Felidae) and culpeo fox (Pseudalopex culpaeus: Canidae), in northern Patagonia, Argentina. We examined spatial distribution influenced by land cover, anthropogenic disturbance and invasive hare presence, and analysed temporal activity patterns and dietary composition. If competitive exclusion accounts for carnivore coexistence in this system, we predicted segregation would occur in one or more of these aspects as a mechanism for coexistence.

We explored the relative contributions of climatic and land-cover factors in explaining the distribution patterns of butterflies in a boreal region. Finland, northern Europe. Data from a national butterfly atlas survey carried out during 1991-2003, with a 10-km grain grid system, were used in these analyses. We used generalized additive models (GAM) and hierarchical partitioning (HP) to explore the main environmental correlates (climate and land-cover) of the realized niches of 98 butterfly species.

An investigation was done to determine the occurrence and composition of avian fauna community in the urbanizing city of Nairobi, Kenya. We conducted bird counts in sample sites randomly distributed over the Nairobi landscape within a two-year period. The proportion of seven different land cover types derived from within a 500� m radius of classified satellite image described the habitat condition of each sample site.

Resource development can have significant consequences for the distribution of vegetation cover and for species persistence. Modelling changes to anthropogenic disturbance regimes over time can provide profound insights into the mechanisms that drive land cover change. We analyzed the spatial patterns of anthropogenic disturbance before and after a period of significant oil and gas extraction in two boreal forest subregions in Alberta, Canada.

Polarimetry is a technique for quantitatively estimating the change in polarization in a backscattered electromagnetic signal (in this case a radar signal) with reference to the polarization of the incident signal for estimating the geophysical properties (roughness and dielectric constant) of surface elements. In this study, quadrapole Radarsat-2 data have been utilized for mapping geological elements in Archaean terrain based on their geophysical parameters preserved in the four polarization channels of Radarsat-2 data.

Measures to select despeckling filter to remove speckles from TerraSAR-X image have been evaluated for an area having varied land cover classes. Gamma, Lee, Sigma, Mean, Median and Frost filters were applied in different window sizes. These images are visually compared and four parameters viz. Noise Mean Value (NMV), Noise Variance (NV), Mean Square Difference (MSD) and Equivalent Numbers of Looks (ENL) are calculated.

Geographically isolated wetlands (GIWs) are common features of the Dougherty Plain physiographic region in southwestern Georgia. Due to lack of protection at the state and federal levels, these wetlands are threatened by intensive agricultural and silvicultural land uses common in the region.

Updating land cover maps from remotely sensed data in a timely manner is important for many areas of scientific research. Unfortunately, traditional classification procedures are very labor intensive and subjective because of the required human interaction. Based on the strategy of updating land cover data only for the changed area, we proposed an integrated, automated approach to update land cover maps without human interaction.