We quantified potential biases associated with lakes monitored using non-probability based sampling by six state agencies in the USA (Michigan, Wisconsin, Iowa, Ohio, Maine, and New Hampshire). To identify biases, we compared state-monitored lakes to a census population of lakes derived from the National Hydrography Dataset. We then estimated the probability of lakes being sampled using general...

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird s...

Soil erosion involves detachment and transport of soil particles from top soil layers, degrading soil quality and reducing the productivity of affected lands. Soil eroded from the upland catchment causes depletion of fertile agricultural land and the resulting sediment deposited at the river networks creates river morphological change and reservoir sedimentation problems. However, land managers...

Land use/land cover (LULC) change is one of the most important indicators in understanding the interactions between humans and the environment. Traditionally, when LULC maps are produced yearly, most existing remote-sensing methods have to collect ground reference data annually, as the classifiers have to be trained individually in each corresponding year. This study presented a novel strategy ...

The relationship between landuse/landcover (LULC) changes and land degradation in two Mediterranean sites is investigated using remotely sensed and ancillary data. The areas of study, the Xaló river catchment in the north of the Alicante province in southeast Spain and the Aegean island of Lesbos, Greece, have both been subjected to changes in LULC, such as abandonment, overgrazing, forest fire...

0099-1112/07/7309–1029/$3.00/0 © 2007 American Society for Photogrammetry and Remote Sensing Abstract This study established spectral matching techniques (SMTs) to determine land-use and land-cover (LULC) and irrigated area classes from historical time-series (HTS-LULC) AVHRR 0.1-degree pathfinder satellite sensor data. The approach for HTS-LULC mapping and characterization was to develop “targ...

A study of the spatial and temporal changes in land use and land cover (LULC) was conducted using Remote Sensing and GIS. We analyzed the LULC of Bharathapuzha river basin, south India using multispectral LANDSAT imageries of 1973-2005 time periods. 31% depletion in the natural vegetation cover and 8.7% depletion in wetland agriculture area were seen in the basin during the period. On the other...

Forests in Washington State generate substantial economic revenue from commercial timber harvesting on private lands. To investigate the rates, causes, and spatial and temporal patterns of forest harvest on private tracts throughout the Cascade Mountains, we relied on a new generation of annual land-use/land-cover (LULC) products created from the application of the Continuous Change Detection a...

In the context of defining a procedure for near real time land use/land cover (LULC) mapping with seasonal updated products, this research examines the use of time-series and phenological indicators from MODIS NDVI. 16-day NDVI composites from MODIS (MOD13Q1) covering the period from 2001 to the present were acquired for three test sites located in different parts of Europe. The newly proposed ...

Accurate quantification of land use/cover change (LULCC) is important for efficient environmental management, especially in regions that are extremely affected by climate variability and continuous population growth such as West Africa. In this context, accurate LULC classification and statistically sound change area estimates are essential for a better understanding of LULCC processes. This st...