Land uses are changing rapidly in Vietnam’s upland northern borderlands. Regional development platforms such as the Greater Mekong Subregion, state-propelled market integration and reforestation programs, and lowland entrepreneurs and migrants are all impacting this frontier landscape. Drawing on a mixed methods approach using remote sensing data from 2000 to 2009 and ethnographic fieldwork, we examine how land-use and land-cover change (LULCC) has occurred across three borderland provinces—Lai Châu, Lào Cai and Hà Giang—with high proportions of ethnic minority semi-subsistence farmers.

Resource development can have significant consequences for the distribution of vegetation cover and for species persistence. Modelling changes to anthropogenic disturbance regimes over time can provide profound insights into the mechanisms that drive land cover change. We analyzed the spatial patterns of anthropogenic disturbance before and after a period of significant oil and gas extraction in two boreal forest subregions in Alberta, Canada.

Critical to effective urban climate adaptation is a clearer understanding of the sensitivities of resource demand to changing climatic conditions and land cover situations. We used Bayesian Maximum Entropy (BME) stochastic procedures to estimate temperature and precipitation at the very small scale of urban Census Block Groups (CBGs) in Phoenix, Arizona and Portland, Oregon, and then compared average household water use patterns by climate conditions and land cover characteristics between and within the two cities.

In Malaysia, areas under oil palm plantations have increased dramatically since the early twentieth century and have resulted in multiple conversions of land change. This paper presents a spatial and temporal model for simulation of oil palm expansion in the Kuala Langat district, Malaysia. The model is an integration of cellular automata (CA), multi-criteria evaluation (MCE), and Markov chain (MC) analysis while MCE provides transition rules of CA iterations and MC analysis assigns a transition probability to each single pixel at the time steps.

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.

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.

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.

Within the investigated river basins the deforestation ranged from 0-45.5%, dependent on the amount of windstorm damage. Our water temperature readings revealed that the canopy elimination above the streams in the areas damaged by the windstorm caused increase in daily and annual water temperature and also wider daily water temperature range, than those in the undisturbed reference stream, which caused the decline of cold stenotherm species abundance. The stream basins deforestation was collinear with FPOM and UFPOM concentrations, water temperature gradient and nitrate concentrations.

Anthropogenic land‐cover change is driving biodiversity loss worldwide. At the epicenter of this crisis lies Southeast Asia, where biodiversity‐rich forests are being converted to oil‐palm monocultures. As demand for palm oil increases, there is an urgent need to find strategies that maintain biodiversity in plantations. Previous studies found that retaining forest patches within plantations benefited some terrestrial taxa but not others. However, no study has focused on aquatic taxa such as fishes, despite their importance to human well‐being.