A new set of recently developed leaf area index (LAI) algorithms has been employed for producing a global LAI dataset at 1 km resolution and in time-steps of 10 days, using data from the Satellite pour l'observation de la terre (SPOT) VEGETATION (VGT) sensor. In this paper, this new LAI product is compared with the global MODIS Collection 4 LAI product over four validation sites in North Americ...

Inland saline wetlands are complex systems undergoing continuous changes in moisture and salinity and are especially vulnerable to human pressures. Remote sensing is helpful to identify vegetation change in semi-arid wetlands and to assess wetland degradation. Remote sensing-based monitoring requires identification of the spectral characteristics of soils and vegetation and their correspondence...

Identification and mapping of natural vegetation are major issues for biodiversity management and conservation. Remotely sensed data with very high spatial resolution are currently used to study vegetation, but most satellite sensors are limited to four spectral bands, which is insufficient to identify some natural vegetation formations. The study objectives are to discriminate natural vegetati...

Aims Mapping vegetation through remotely sensed images involves various considerations, processes and techniques. Increasing availability of remotely sensed images due to the rapid advancement of remote sensing technology expands the horizon of our choices of imagery sources. Various sources of imagery are known for their differences in spectral, spatial, radioactive and temporal characteristic...

Advances in remote sensing (RS) technology recent years have increased the interest including RS data into one-class classifiers (OCCs). However, this integration is complex given interdisciplinary issues involved. In context, review highlights advances and current challenges integrating OCCs to map vegetation classes. A systematic was performed for period 2013–2020. total of 136 articles were ...

Tree cover (TC) and biomass carbon stocks (CS) are key parameters for characterizing vegetation indispensable assessing the role of terrestrial ecosystems in global climate system. Land use, through land change management, affects both parameters. In this study, we quantify empirical relationship between TC CS demonstrate impacts use by combining spatially explicit estimates actual potential (i...

Fire risk is a major threat to life, property and natural resources in southern California. Recent fire disasters occurred in autumn 2003 and 2007. Fire risk management deals with these hazards, input data are collected, analyzed and evaluated. One of the most important input data is the vegetation density in the endangered areas. Here we describe methods to map vegetation density forming five ...

Information of paddy rice distribution is essential for food production and methane emission calculation. Phenology-based algorithms have been utilized in the mapping of paddy rice fields by identifying the unique flooding and seedling transplanting phases using multi-temporal moderate resolution (500 m to 1 km) images. In this study, we developed simple algorithms to identify paddy rice at a f...