The limited amount of studies addressing the long‐term effectiveness of restoration actions to combat land degradation is a constraint for current landscape restoration planning and implementation. Remote sensing data provide a unique opportunity for gathering information on the spatial and temporal variability of restoration processes and may contribute to fill this knowledge gap.

Population of two cities in Pakistan has already crossed the 10-million figure and for the rest of the areas in the country populations are also increasing rapidly. Urbanization has boosted the use of energy in the cities and so is greenhouse gas (GHG) emissions but the ground situation as to the extent, vulnerability, past trends and future scenarios are not unveiled for the cities of Pakistan. Dearth of data in Pakistan is a huge hindrance to the investigation of energy use and actual GHG emissions.

1. For north temperate lakes, the well-studied empirical relationship between phosphorus (as measured by total phosphorus, TP), the most commonly limiting nutrient and algal biomass (as measured by chlorophyll a, CHL) has been found to vary across a wide range of landscape settings. Variation in the parameters of these TP-CHL regressions has been attributed to such lake variables as nitrogen/phosphorus ratios, organic carbon and alkalinity, all of which are strongly related to catchment characteristics (e.g. natural land cover and human land use).

As part of the development of the 2011 National Land Cover Database (NLCD) tree canopy cover layer, a pilot project was launched to test the use of high-resolution photography coupled with extensive ancillary data to map the distribution of tree canopy cover over four study regions in the conterminous US. Two stochastic modeling techniques, random forests (RF) and stochastic gradient boosting (SGB), are compared.

In this study, a multi-scale approach was used for classifying land cover in a high resolution image of an urban area. Pixels and image segments were assigned the spectral, texture, size, and shape information of their super-objects (i.e. the segments that they are located within) from coarser segmentations of the same scene, and this set of super-object information was used as additional input data for image classification.

The integrated remote sensing (RS) and geographic information system (GIS) approach was utilized in this study to classify land use and land cover (LULC), detect changes based over time, and identify transition trends in the Marikina sub-watershed, Laguna de Bay watershed, Philippines. Landsat 5 Thematic Mapper (TM) imageries acquired in 1999 and 2006 were pre-processed and classified using a supervised classification technique with maximum likelihood classifier algorithm in RS and were used to develop maps of the sub-watershed and sub-subwatershed levels in a GIS platform.

The impacts of deforestation and land cover change upon underlying soils were examined on one hillside in central Armenia. Soil characteristics in three land cover areas—forest, coppice, and pasture—were recorded and soil samples were analyzed. Deforestation and land cover change were found to increase erosion rates. From soil horizon and structural characteristics, it can be estimated that 40 cm of soil have been lost in the pasture and 20 cm have been lost in the coppice compared to the forest. Soil organic carbon was also affected by deforestation and land cover change.

The Pampean region covers a large surface in central Argentina, but despite the extensive agricultural activities and the high nutrient levels recorded in streams of the region, few authors have analysed the influence of land use on water quality. Here, we evaluated the relationships among catchment attributes (size, morphometry and land cover) and water chemistry in 23 Pampean streams in different seasons (autumn, spring and summer) and at three spatial scales: whole catchment and two scales of riparian buffers (200 and 500 m adjacent to both stream margins).

After the industrial revolution, urban growth has been increasing, especially with technological advances. Urbanization is accelerating environmental pollution and also affects climate significantly because of land use or land cover changes. In this study, the Hydrological Simulation Program-Fortran (HSPF) model developed by the United States Environment Protection Agency (USEPA) is used for modeling the impervious areas of Eskişehir which is located in the Porsuk Stream Watershed in Inner Anatolia, Turkey.

Identifying the relative importance of climatic and other environmental controls on the interannual variability and trends in global land surface phenology and greenness is challenging. Firstly, quantifications of land surface phenology and greenness dynamics are impaired by differences between satellite data sets and phenology detection methods. Secondly, dynamic global vegetation models (DGVMs) that can be used to diagnose controls still reveal structural limitations and contrasting sensitivities to environmental drivers.

Large remote sensing datasets, that either cover large areas or have high spatial resolution, are often a burden of information mining for scientific studies. Here, we present an approach that conducts clustering after gray-level vector reduction. In this manner, the speed of clustering can be considerably improved. The approach features applying eigenspace transformation to the dataset followed by compressing the data in the eigenspace and storing them in coded matrices and vectors.

This paper explores the possibility of using non-geometric cadastral maps from the 17th and 18th century together with aerial photographs from 1945 and 1981 to analyse land-cover change in south-east Sweden. Habitats rich in plant species in the European rural landscape seem to be correlated with a long continuity of management. Accurate spatial data from historical data sources are fundamental to understand patterns of vegetation and biodiversity in the present-day landscape.