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.

This study aims to assess CO₂ levels in China, based on the dry air column-averaged mixing ratios of CO₂ measured by the Scanning Imaging Absorption spectrometer for Atmospheric CartograpHY (SCIAMACHY) instrument on board ENVISAT and emission inventories. A land cover and statistical data set, the Regional emission inventory in Asia (REAS), was also used in this study. The results show that the spatial variations of the CO₂ concentration in the whole of China are obvious, and with clear seasonal fluctuation during 2003–2005.

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.

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.

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.

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).

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).

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.

Most of the plantation impact studies reported in literature normally use either one of the sensitivity-based approach or a hydrological model with few actually comparing the impact results from these different approaches. This paper investigates the impacts of increase or decrease in plantations and climate variability on streamflow using two approaches: the sensitivity-based approach (including a non-parametric model and six Budyko framework based models) and the hydrological modelling approach (using Xinanjiang and SIMHYD models) for three medium sized catchments in Australia.

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.

Sustainable forest management (SFM), an explicit policy objective in Canada, balances social, economic and environmental values. The status and trends of forest-associated species is one indicator of SFM, though it is under utilized due to challenges with indicator selection and data availability. This paper demonstrates and tests an indicator selection methodology which combines Breeding Bird Survey (BBS) data and LandSat land cover data to identify indicator guilds, or groups of indicator species, for a series of forest composition and configuration attributes in the Great Lakes St.

The study aim was to determine whether enhanced dry deposition of acidic atmospheric pollutants by broadleaf woodland expansion could increase the potential for acidification of surface waters in acid-sensitive areas. Dry sulphur (S) and nitrogen (N) deposition was modelled with the Fine Resolution Atmospheric Multi-pollutant Exchange (FRAME) model using a roughness length value calculated specifically for birchwoods.