The land surface phenology (LSP) start of season (SOS) metric signals the seasonal onset of vegetation activity, including canopy growth and associated increases in land-atmosphere water, energy and carbon (CO₂) exchanges influencing weather and climate variability. The vegetation optical depth (VOD) parameter determined from satellite passive microwave remote sensing provides for global LSP monitoring that is sensitive to changes in vegetation canopy water content and biomass, and insensitive to atmosphere and solar illumination constraints.

Ultra-high-resolution digital aerial imagery has great potential to complement or replace ground measurements of vegetation cover for rangeland monitoring and assessment. This research investigated object-based image analysis (OBIA) techniques for classifying vegetation in southwestern USA arid rangelands with 4 cm resolution digital aerial imagery. We obtained high r-square values for the regressions relating ground- to image-based measures of percent cover (r-square values: 0.82–0.92).

This research was conducted in order to assess the environmental impacts of Finchaa irrigation project using GIS and remote sensing techniques. Because of the limited resources only some environmental parameters were selected. These parameters are natural vegetation, soil/land, water quality, climate and health conditions. The normalized vegetation index (NDVI) analysis was used to detect the spatial and temporal change of vegetation biomass in the study area. The result indicated that the natural vegetation biomass is declining.

Persistent organic pollutants (POPs) impact upon human and animal health and the wider environment. It is important to determine where POPs are found and the spatial pattern of POP variation. The concentrations of 90 molecules which are members of four families of POPs and two families of herbicides were measured within a region of Northern France as part of the French National Soil Monitoring Network (RMQS: Réseau de Mesures de la Qualité des Sols).

Unprecedented land use and land cover (LULC) changes in the Gilgel Tekeze catchment of the upper Nile River basin in Ethiopia may have far-reaching consequences for the long-term sustainability of the natural resources base. This study analyzed the dynamics and hydrologic effects of LULC changes between 1976 and 2003 as shown in satellite imagery. The effects of these LULC changes on the hydrologic response were investigated using the WetSpa model to estimate spatially distributed average annual evapotranspiration, surface runoff, and groundwater recharge.

The objective of this article is to develop and test a methodology capable of using medium spatial resolution satellite imagery to improve forest-area statistics derived from ground sampling. The methodology builds on the evidence that multitemporal Normalized Difference Vegetation Index (NDVI) images bring significant information on the spatial distribution of forest surfaces. Consequently, Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI images are potentially useful to improve forest-area assessment based on ground data.

Urban sprawl along the Mediterranean coast is characterized by single-family houses and domestic gardens. Many new residences are secondary homes for socio-demographically diverse tourists. We explore the differences between the residence types in terms of their garden structures and plant compositions using socioeconomic and legacy attributes. Outdoor areas of 245 primary and secondary homes were investigated to determine plant compositions, land cover and household characteristics. Then, the outdoor land cover was compared between the two residence types.

Spatially organized distribution patterns of species and communities are shaped by both autogenic processes (neutral mechanism theory) and exogenous processes (niche theory). In the latter, environmental variables that are themselves spatially organized induce spatial structure in the response variables. The relative importance of these processes has not yet been investigated in urban habitats.

Stopover use by migrating shorebirds is affected by patch-level characteristics of habitat, but the relative influence of broad-scale factors is poorly understood. We conducted surveys of ten 10-km-radius landscapes in north-central Oklahoma from 2007 through 2009 to examine the influence of the amount and composition of wetland habitats and surrounding land cover on shorebird use during migration.

In this study, an investigation was performed of the spatial relationships between the occurrences of four types of landslides (slides, flows, falls and creeps) and three categories of land cover (agricultural areas, artificial surfaces and forested and semi-natural areas) that are found in the Arno river basin of central Italy. The main purpose of the study was to test whether the landslides that are mapped within the basin are spatially clustered (i.e., have a spatial attraction) or randomly spatially distributed (i.e., spatially independent) on different types of land cover.

Spatial regression, incorporating spatial error or lag dependency, was performed to interpret determinants of hazardous chemicals at full sub-basin scale and at 500m riparian buffer scale in Qiantang River, eastern coastal China. Monitoring data from 41 monitoring stations were collected between 1996 and 2003 and pretreated for 7 variables—petroleum, hexavalent chromium, total cadmium, total lead, total mercury, total cyanide, and volatile phenol. Results showed that primary predictors and the predictive ability of spatial regression differed with variables and scales.

Improved change vector analysis (ICVA) has recently been promoted as an effective algorithm for multi-class change detection. Unlike the conventional change vector analysis (CVA) that works on two-dimensional data, the ICVA works on multidimensional data. However, ICVA has limitations when the change vector is fraught with similar direction cosine values. In this article, a new algorithm, named median change vector analysis (MCVA) has been proposed for multi-class change detection.