Current methods for large-scale vegetation monitoring rely on multispectral remote sensing, which has serious limitation for the detection of vegetation stress. To contribute to the establishment of a generalized spectral approach for vegetation stress detection, this study compares the ability of high-spectral-resolution reflectance (R) and fluorescence (F) foliar measurements to detect vegeta...

To determine suitable indices for vegetation cover and production assessment based on remote sensing data, simultaneous digital data with field data belonged to summer rangeland of southern part of Isfahan province were analyzed. During 2 years of monitoring, annuals, grasses, forbs and shrubs vegetation cover and total production data from sixty 1 square meter plots in each site were collected...

given the critical role played by urban green spaces and the emergence of remote sensing as avaluable natural resource management tool, this study sought to identify trends in green spaces within thecontext of south africa’s transition period (1990 - 2000). using the city of port elizabeth as a case study, threesets of landsat - 5 thematic mapper images (1990, 1995 and 2000) were geo-processed,...

This paper reviews how remotely sensed data have been used to understand the impact of urbanization on global environmental change. We describe how these studies can support the policy and science communities’ increasing need for detailed and up-to-date information on the multiple dimensions of cities, including their social, biological, physical, and infrastructural characteristics. Because th...

the reflectance spectrum of green leaves is considerably affected by their biochemical and biophysical properties. it is possible to extract biochemical information from a continuous vegetation spectrum produced using hyperspectral sensors. the numerous absorption features present in the vegetation spectrum carry a considerable amount of information related to the content and the structure of t...

the objective of this research was to determine the best model and compare performances in terms of producing landuse maps from six supervised classification algorithms. as a result, different algorithms such as the minimum distance ofmean (mdm), mahalanobis distance (md), maximum likelihood (ml), artificial neural network (ann), spectral anglemapper (sam), and support vector machine (svm) were...