Studies of land surface dynamics in heterogeneous landscapes often require remote sensing datawith high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta Fusion (FSDAF) method, to generate synthesized frequent high spatial resolution images through blending two types of data, i.e., frequent coarse spatial resolution data, such as that from MODIS, and less frequent high spatial resolution data such as that from Landsat.

Coastal shorelines are naturally dynamic, shifting in response to coastal geomorphological processes. Globally, land use change associated with coastal urban development and growing human population pressures is accelerating coastal shoreline change. In southern Vietnam, coastal erosion currently is posing considerable risks to shoreline land use and coastal inhabitants.

Historic land‐cover/use change is important for studies on climate change, soil carbon, and biodiversity assessments. Available reconstructions focus on the net area difference between two time steps (net changes) instead of accounting for all area gains and losses (gross changes). This leads to a serious underestimation of land‐cover/use dynamics with impacts on the biogeochemical and environmental assessments based on these reconstructions.

Mesoamerican biodiversity is increasingly threatened by anthropogenic destruction of natural land cover. Habitat degradation and climate change are primary threats to specialized forest odonate species that are important model organisms for forest health and defining conservation units. The extreme niche specialization of Megaloprepus caerulatus, the world’s largest extant odonate, makes it well suited as an indicator for changing environmental conditions.

This paper explores which physical landscape components relate to subjective landscape dimensions. The ways in which people describe their surrounding cultural landscape was analyzed through an assessment of their representations of it. A special focus was placed on assessing the role of land cover as a means to communicate landscape meanings regarding a specific geographical region. The methodological framework was built on the basis of a questionnaire survey, multivariate statistical analysis and mapping approaches.

This paper provides a comparative analysis of land-use and land-cover (LULC) changes among three study areas with different biophysical environments in the Brazilian Amazon at multiple scales, from per-pixel, polygon, census sector, to study area. Landsat images acquired during the years of 1990/1991, 1999/2000, and 2008/2010 were used to examine LULC change trajectories with the post-classification comparison approach.

In this study we analyzed the response of monthly runoff to precedent climatic conditions at temporal scales of 1–48months in 88 catchments of the Ebro basin (northeast Spain). The standardized precipitation evapotranspiration index (SPEI) was used to summarize the climatic conditions at different time scales, and was correlated with the standardized streamflow index (SSI) calculated at the mouth of each catchment. The Ebro basin encompasses a gradient from Atlantic to Mediterranean climates, and has remarkable complexity in topography, geology and land cover.

Ecosystems provide multiple benefits to people, including climate regulation. Previous efforts to quantify this ecosystem service have been either largely conceptual or based on complex atmospheric models. Here, we review previous research on this topic and propose a new and simple analytical approach for estimating the physical regulation of climate by ecosystems. The proposed metric estimates how land‐cover change affects the loading of heat and moisture into the atmosphere, while also accounting for the relative contribution of wind‐transported heat and moisture.

As all biodiversity-related variables, ecological indicators are influenced by environmental factors working at different spatial scales. However, assessing the relationship between environmental factors and ecological indicators is limited to a set of spatial scales determined a priori.

Spatially explicit models depicting species occupancy offer a useful conservation tool for land managers. Using occurrence data collected in 2009 and 2010 from the Boise National Forest, Idaho, we developed distribution models for Flammulated Owls (Psiloscops flammeolus) and Northern Saw-whet Owls (Aegolius acadicus) to explore associations between habitat factors and owl occupancy. We then spatially applied these models in a Geographic Information System.

The spatio-temporal variation underlies and complicates studies related to earth surface processes. Subsequent to our previous studies reporting the temporal invariability of sediment concentration, this study further reports the spatial invariability of sediment concentration or the flow–sediment relationship in the hilly part of the Chinese Loess Plateau. The dense channel network dissects this area into numerous sub-watersheds, which are composed of entire slopes (a combination of the hill slope and the valley side slope).

Most existing multi-temporal classification studies use spectral information alone and ignore the temporal correlation between two-date images. This article proposes a new method to characterize the local temporal correlation using multi-temporal texture measured with a geostatistical function called the pseudo cross variogram (PCV). The derived multi-temporal texture, as an additional band, was combined with the spectral information in multi-temporal classification.