A landscape perspective is generally recognized as essential for conservation biology. The main underlying reason is that species respond to features of the landscape at various spatial scales, for example habitat area, connectivity, and matrix habitats. However, there is also an “historical” component of a landscape perspective, which has not received similar attention. The underlying reasons for historical effects are that humans have influenced landscapes during several millennia and that species and communities may respond slowly to land use change.

Lao People’s Democratic Republic (PDR) has been experiencing significant forest depletion since the 1980s, but there is little evidence to demonstrate the major causes and underlying drivers for the forest cover changes. In this study, we investigated the relationship between forest cover decrease and increase in the south of Lao PDR between 2006 and 2012 and selected physical and socio-economic factors.

Mapping large areas for planning and conservation is a challenge undergoing rapid transformation. For centuries, the creation of broad-extent maps was the near-exclusive domain of expert specialist cartographers, who painstakingly delineated regions of relative homogeneity with respect to a given set of criteria. In the satellite era, it has become possible to rapidly create and update categorizations of Earth’s surface with improved speed and flexibility. Land cover datasets and landscape metrics offer a vast set of information for viewing and quantifying land cover across large areas.

Section 404 of the U.S. Clean Water Act includes most wetlands in its jurisdiction and requires wetland mitigation to compensate for permitted wetland losses. These mitigation wetlands can provide ecosystem services similar to original wetlands if properly constructed. Improvement of wetland monitoring requirements coupled with economic assessment is critical for effective implementation of the mitigation policy. The economic assessment when left out of evaluation of mitigation policy could result in mitigation wetlands being given too little weight in policy decisions.

Islands across the world have evolved at the interface between land and sea, thus comprising landscapes and seascapes. Many islands have also been influenced by anthropogenic factors, which have given rise to mosaics of anthromes (sensu Ellis and Ramankutty). These elements of landscapes, seascapes, and cultural impacts in varied proportions, generate unique environments which merit a unique term: islandscapes. The use of the term islandscape is advocated as the only term which encompasses all of the constituent components of an island, in a holistic manner.

Halgurd Sakran National Park (HSNP) is Iraq’s first designated national park, located in the Kurdistan Region, which has suffered multiple armed conflicts over the past decades. This study assesses how vegetation dynamics have affected the landscape structure and composition of the core zone of the park over the last 31 years. Spatio-temporal changes in land cover were mapped for three points in time using remote sensing, geographic information systems (GIS), and landscape metrics.

Over the past several decades, Saudi cities have experienced rapid urban developments and land use and land cover (LULC) changes. These developments will have numerous short- and long-term consequences including increasing the land surface temperature (LST) of these cities. This study investigated the effects of LULC changes on the LST for the eastern coastal city of Dammam. Using Landsat imagery, the study first detected the LULC using the maximum likelihood classification method and derived the LSTs for the years 1990, 2002, and 2014.

We describe a future land cover scenario construction process developed under consultation with a group of stakeholders from our study area. We developed a simple geographic information system (GIS) method to modify a land cover dataset and then used qualitative data extracted from the stakeholder storyline to modify it. These identified variables related to our study area’s land use regulation system as the major driver in the placement of new urban growth on the landscape; and the accommodation of new population as the determinant of its growth rate.

High-precision land-cover-land-use GIS mapping was performed in four major townships in Maine’s Aroostook River Valley, using on-screen digitization and direct interpretation of very high spatial resolution satellite multispectral imagery (15–60 cm) and high spatial resolution LiDAR data (2 m) and the field mapping method. The project not only provides the first-ever high-precision land-use maps for northern Maine, but it also yields accurate hectarage estimates of different land-use types, in particular grassland, defined as fallow land, pasture, and hay field.

We build upon much of the accumulated knowledge of the widely used SLEUTH urban land change model and offer advances. First, we use SLEUTH’s exclusion/attraction layer to identify and test different urban land cover change drivers; second, we leverage SLEUTH’s self-modification capability to incorporate a demographic model; and third, we develop a validation procedure to quantify the influence of land cover change drivers and assess uncertainty.

Rosetta Promontory, Egypt has been suffering from a continuous erosion problem. The dramatic retreatment was observed during the last century. It is basically due to the construction of Aswan High Dam in 1964, which reduced the flow and sediment discharges. In this paper, four Landsat images (two Thematic Mapper and two Enhanced Thematic Mapper) covering the period from 1984 to 2014 were used.

In Southeast Asia land use change associated with forest loss and degradation is a major source of greenhouse gas (GHG) emissions. This is of particular concern where deforestation occurs on peat soils. A business-as-usual (BAU) land change model was developed using Dinamica EGO© for a REDD+ Demonstration Activity area in south-east Jambi Province, Sumatra, Indonesia containing Berbak National Park (NP). The model output will be used as baseline land change predictions for comparison with alternative land cover management scenarios as part of a REDD+ feasibility study.