The successful development of an optimal canopy vegetation index dynamic model for obtaining higher yield can offer a technical approach for real-time and nondestructive diagnosis of rice (Oryza sativa L) growth and nitrogen (N) nutrition status. In this study, multiple rice cultivars and N treatments of experimental plots were carried out to obtain: normalized difference vegetation index (NDVI...

The active layer is the top layer of permafrost soils that thaws during the summer season due to increased ambient temperatures and solar radiation inputs. This layer is important because almost all biological activity takes place there during the summer. The depth of active layer thaw is influenced by climatic conditions. Vegetation has also been found to have a strong impact on active layer t...

With more than 80% of Brazilians living in cities, urbanization has had an important impact on climatic variations. São José dos Campos is located in a region experiencing rapid urbanization, which has produced a remarkable Urban Heat Island (UHI) effect. This effect influences the climate, environment and socio-economic development on a regional scale. In this study, the brightness temperature...

Drought is an increasingly common phenomenon in drylands as a consequence of climate change. We used 311 sites across a broad range of environmental conditions in Patagonian rangelands to evaluate how drought severity and temperature (abiotic factors) and vegetation structure (biotic factors) modulate the impact of a drought event on the annual integral of normalized difference vegetation index...

To determine the suitable indices for vegetation cover and production assessment based on the remote sensing data, simultaneous digital data with field data belonging to the spring rangeland of the Semirom-Isfahan province were analyzed. During two years of monitoring the annual, grass, forb, and shrub vegetation cover and the total production data from 86 were collected. The Global Positioning...

Terrestrial vegetation dynamics are closely influenced by a multitude of factors. This study investigated the relationships between vegetation patterns and their main influencing factors. The joint entropy method was employed to evaluate the dependence between normalized difference vegetation index (NDVI) and coupled variables in the middle reaches of Hei River basin. Based on the spatial distr...

The spatial variabi]Lity and co-variability of two different types of remote sensing derivatives that portray vegetation and geomorphic patterns are analyzed in the context of estimating regional-scale CO 2 flux from land surfaces in the arctic tundra. For a study area encompassing the Kuparuk River watershed of the North Slope of Alaska, we compare satellite-derived maps of the normalized diff...

Deconstructing the drivers of large-scale vegetation change is critical to predicting and managing projected climate and land use changes that will affect regional vegetation cover in degraded or threated ecosystems. We investigate the shared dynamics of spatially variable vegetation across three large watersheds in the southern Africa savanna. Dynamic Factor Analysis (DFA), a multivariate time...

To remotely monitor vegetation at temporal and spatial resolutions unobtainable with satellite-based systems, near remote sensing systems must be employed. To this extent we used Normalized Difference Vegetation Index NDVI sensors and normal digital cameras to monitor the greenness of six different but common and widespread High Arctic plant species/groups (graminoid/Salix polaris; Cassiope tet...