Forest cover monitoring plays an important role in the implementation of climate change mitigation policies such as Kyoto protocol and Reducing Emissions from Deforestation and Forest Degradation (REDD). In this study, we have monitored land cover using the PALSAR (Phased Array type L-band Synthetic Aperture Radar) full polarimetric data based on incoherent target decomposition.

Satellite imagery with fine spectral and spatial resolution and high temporal resolution provides a unique opportunity to map and monitor biodiversity. The aim of this article is (i) to review the state of the use of high-resolution remote sensing for ecological studies in the Indian Himalayan Region (IHR) and (ii) to suggest further potential avenues of research in the region using this technology.

Polarimetry is a technique for quantitatively estimating the change in polarization in a backscattered electromagnetic signal (in this case a radar signal) with reference to the polarization of the incident signal for estimating the geophysical properties (roughness and dielectric constant) of surface elements. In this study, quadrapole Radarsat-2 data have been utilized for mapping geological elements in Archaean terrain based on their geophysical parameters preserved in the four polarization channels of Radarsat-2 data.

Urban structural units (USUs) are work (or similar) units in urbanized areas. In this study, USUs based on urban land use and land cover were used to explain and compare urban ecological conditions within Beijing. This study focused on the spatial pattern of land use for different USUs in urban areas. The results showed that 453 USUs belong to 12 primary USUs and to 38 different secondary USUs. The percentage of built-up area was highest in those regions with hotels, and lowest in areas with cemeteries.

Land cover classification using remotely sensed data requires robust classification methods for the accurate mapping of complex land cover area of different categories. In this regard, support vector machines (SVMs) have recently received increasing attention. However, small number of training samples remains a bottleneck to design suitable supervised classifiers. On the other hand, adequate number of unlabeled data is available in remote sensing images which can be employed as additional source of information about margins.

Land-use land-cover (LULC) changes are one of the major threats to biodiversity worldwide, since their principal consequences are the loss, fragmentation or degradation of the habitat available for most species. Therefore, in order to provide guidelines for environmental management at the regional scale and thus reverse the trend in degradation, transformations of natural remnants into anthropogenic land uses must be identified and quantified.

Adequate quantification of evapotranspiration (ET) is crucial to assess how climate change and land cover change (LCC) interact with the hydrological cycle of terrestrial ecosystems. The Mongolian Plateau plays a unique role in the global climate system due to its ecological vulnerability, high sensitivity to climate change and disturbances, and limited water resources. Here, we used a version of the Terrestrial Ecosystem Model that has been modified to use Penman–Monteith (PM) based algorithms to calculate ET.

To address severe grassland degradation problems, China has been implementing a number of national restoration programs, whose significant environmental effect has attracted the attention of many researchers. In this paper, land use and cover change (LUCC) in the Inner Mongolia grassland and the consequent change in net primary productivity (NPP) were studied by combining the land use data of the study area for 2001 and 2009 derived from the MODIS global land cover product and the CASA (Carnegie–Ames–Stanford Approach) model driven with MODIS-NDVI data.

Monitoring land-cover change is often done by simple overlay of two classified maps from different dates. However, such analysis tends to overestimate the rate of change. Main error sources are the mis-registration between classified maps and their thematic accuracies. This study proposes a change detection method with morphological post-processing to improve change detection accuracy in comparison with traditional post-classification by taking into account these error sources.

Despite numerous ecosystem services provided by urban trees, they are continually threatened by combined natural disturbances, invasive species, development and negligent management practices. This research characterizes the amount and cause of tree loss in Worcester, Massachusetts, in the northeast United States, and neighbouring towns between 2008 and 2010 using multi-source remotely sensed imagery and historical land cover maps (1976–2009).

While crop rotation patterns can be complex with multiple crops rotated over several years, the most common rotation practice in the Central United States is biannual rotation between corn and soybeans. We analyzed the changes in crop rotation patterns from 2003 to 2010 using the Cropland Data Layer (CDL), which provides remotely sensed land cover layers for agricultural crops in the Central United States.

The objective of this paper was to quantify long-term land use and land cover changes (LULCC) and to identify the spatial determinants of locations of most systematic transitions for the period 1957–2009 in the Jedeb watershed, Upper Blue Nile Basin. Black and white aerial photographs of 1957 and Landsat imageries of 1972 (MSS), 1986 (TM), 1994 (TM) and 2009 (TM) were used to derive ten land use and land cover classes by integrated use of Remote Sensing (RS) and Geographic Information System (GIS).