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At least 1,027 records · Page 57Linked to original sources

USGS2018

Vegetation cover, tidal amplitude and land area predict short-term marsh vulnerability in Coastal Louisiana

The loss of coastal marshes is a topic of great concern, because these habitats provide tangible ecosystem services and are at risk from sea-level rise and human activities. In recent years, significant effort has gone into understanding and modeling the relationships between the biological and physical factors that contribute to marsh stability. Simulation-based process models suggest that marsh stability is the product of a complex feedback between sediment supply, flooding regime and vegetation response, resulting in elevation gains sufficient to match the combination of relative sea-level rise and losses from erosion. However, there have been few direct, empirical tests of these models, because long-term datasets that have captured sufficient numbers of marsh loss events in the context of a rigorous monitoring program are rare. We use a multi-year data set collected by the Coastwide Reference Monitoring System (CRMS) that includes transitions of monitored vegetation plots to open water to build and test a predictive model of near-term marsh vulnerability. We found that despite the conclusions of previous process models, elevation change had no ability to predict the transition of vegetated marsh to open water. However, we found that the processes that drive elevation change were significant predictors of transitions. Specifically, vegetation cover in prior year, land area in the surrounding 1 km2 (an estimate of marsh fragmentation), and the interaction of tidal amplitude and position in tidal frame were all significant factors predicting marsh loss. This suggests that 1) elevation change is likely better a predictor of marsh loss at time scales longer than we consider in this study and 2) the significant predictive factors affect marsh vulnerability through pathways other than elevation change, such as resistance to erosion. In addition, we found that, while sensitivity of marsh vulnerability to the predictive factors varied spatially across coastal Louisiana, vegetation cover in prior year was the best single predictor of subsequent loss in most sites followed by changes in percent land and tidal amplitude. The model’s predicted land loss rates correlated well with land loss rates derived from satellite data, although agreement was spatially variable. These results indicate 1) monitoring the loss of small scale vegetation plots can inform patterns of land loss at larger scales 2) the drivers of land loss vary spatially across coastal Louisiana, and 3) relatively simple models have potential as highly informative tools for bioassessment, directing future research, and management planning.

Louisiana↗

USGS2012

Late twentieth century land-cover change in the basin and range ecoregions of the United States

As part of the US Geological Survey's Land Cover Trends project, land-use/land-cover change estimates between 1973 and 2000 are presented for the basin and range ecoregions, including Northern, Central, Mojave, and Sonoran. Landsat data were employed to estimate and characterize land-cover change from 1973, 1980, 1986, 1992, and 2000 using a post-classification comparison. Overall, spatial change was 2.5% (17,830 km 2 ). Change increased steadily between 1973 and 1986 but decreased slightly between 1992 and 2000. The grassland/shrubland class, frequently used for livestock grazing, constituted the majority of the study area and had a net decrease from an estimated 83.8% (587,024 km 2 ) in 1973 to 82.6% (578,242 km 2 ) in 2000. The most common land-use/land-cover conversions across the basin and range ecoregions were indicative of the changes associated with natural, nonmechanical disturbances (i.e., fire), and grassland/shrubland loss to development, agriculture, and mining. This comprehensive look at contemporary land-use/land-cover change provides critical insight into how the deserts of the United States have changed and can be used to inform adaptive management practices of public lands.

Regional Environmental Change↗

USGS2019

Denitrification in the river network of a mixed land use watershed: Unpacking the complexities

River networks have the potential to permanently remove nitrogen through denitrification. Few studies have measured denitrification rates within an entire river network or assessed how land use affect rates at larger spatial scales. We sampled 108 sites throughout the network of the Fox River watershed, Wisconsin, to determine if land use influence sediment denitrification rates, and to identify zones of elevated sediment denitrification rates (hot spots) within the river network. Partial least squares regression models identified variables from four levels of organization (river bed sediment, water column, riparian zone, and watershed) that best predicted denitrification rates throughout the river network. Nitrate availability was the most important predictor of denitrification rates, while land cover was not always a good predictor of local-scale nitrate concentrations. Thus, land cover and denitrification rate were not strongly related across the Fox River watershed. A direct relationship between denitrification rate and watershed land cover occurred only in the Wolf River sub-watershed, the least anthropogenically disturbed of the sub-watersheds. Denitrification hot spots were located throughout the river network, regardless of watershed land use, with hot spot location being determined primarily by nitrate availability. In the Fox River watershed, when nitrate was abundant, river bed sediment character influenced denitrification rate, with higher denitrification rates at sites with fine, organic sediments. These findings suggest that denitrification occurring throughout an entire river network, from headwater streams to larger rivers, can help reduce nitrogen loads to downstream water bodies.

Wisconsin↗

USGS2017

Climate impacts on agricultural land use in the USA: the role of socio-economic scenarios

We examine the impacts of climate on net returns from crop and livestock production and the resulting impact on land-use change across the contiguous USA. We first estimate an econometric model to project effects of weather fluctuations on crop and livestock net returns and then use a semi-reduced form land-use share model to study agricultural land-use changes under future climate and socio-economic scenarios. Estimation results show that crop net returns are more sensitive to thermal and less sensitive to moisture variability than livestock net returns; other agricultural land uses substitute cropland use when 30-year averaged degree-days or precipitation are not beneficial for crop production. Under future climate and socio-economic scenarios, we project that crop and livestock net returns are both increasing, but with crop net returns increasing at a higher rate; cropland increases with declines of marginal and pastureland by the end of the twenty-first century. Projections also show that impacts of future climate on agricultural land uses are substantially different and a larger variation of land-use change is evident when socio-economic scenarios are incorporated into the climate impact analysis.

Climatic Change↗

USGS2012

Ecosystem services from converted land: the importance of tree cover in Amazonian pastures

Deforestation is responsible for a substantial fraction of global carbon emissions and changes in surface energy budgets that affect climate. Deforestation losses include wildlife and human habitat, and myriad forest products on which rural and urban societies depend for food, fiber, fuel, fresh water, medicine, and recreation. Ecosystem services gained in the transition from forests to pasture and croplands, however, are often ignored in assessments of the impact of land cover change. The role of converted lands in tropical areas in terms of carbon uptake and storage is largely unknown. Pastures represent the fastest-growing form of converted land use in the tropics, even in some areas of rapid urban expansion. Tree biomass stored in these areas spans a broad range, depending on tree cover. Trees in pasture increase carbon storage, provide shade for cattle, and increase productivity of forage material. As a result, increasing fractional tree cover can provide benefits land managers as well as important ecosystem services such as reducing conversion pressure on forests adjacent to pastures. This study presents an estimation of fractional tree cover in pasture in a dynamic region on the verge of large-scale land use change. An appropriate sampling interval is established for similar studies, one that balances the need for independent samples of sufficient number to characterize a pasture in terms of fractional tree cover. This information represents a useful policy tool for government organizations and NGOs interested in encouraging ecosystem services on converted lands. Using high spatial resolution remotely sensed imagery, fractional tree cover in pasture is quantified for the municipality of Rio Branco, Brazil. A semivariogram and devolving spatial resolution are employed to determine the coarsest sampling interval that may be used, minimizing effects of spatial autocorrelation. The coarsest sampling interval that minimizes spatial dependence was about 22 m. The area-weighted fractional tree cover for the study area was 1.85 %, corrected for a slight bias associated with the coarser sampling resolution. The pastures sampled for fractional tree cover were divided between ‘high’ and ‘low’ tree cover, which may be the result of intentional incorporation of arboreal species in pasture. Further research involving those ranchers that have a higher fractional tree cover may indicate ways to promote the practice on a broader scale in the region.

Urban Ecosystems↗

USGS1995

Recent data and information system initiatives for remotely sensed measurements of the land surface

As part of the International Satellite Land Satellite Climatology Program (ISLSCP) Workshop on Remote Sensing of the Land Surface for Studies of Global Change, five invited presentations were given on recent data initiatives relevant to the ISLSCP community. The presentations are summarized in this paper along with some observations by the authors on data systems for the land sciences community. The invited presentations are by no means all inclusive but were selected as examples of current data activities, representing a range of topics associated with data for land sciences including: the generation of global and local scale data sets, the reworking of historical data sets, new data initiatives and some programmatic aspects of land data base development. This paper serves to provide information on these data initiatives and to air some of the issues concerning land science data systems that were raised at the meeting.

Remote Sensing of Environment↗

USGS2011

Valuing ecosystem and economic services across land-use scenarios in the Prairie Pothole Regions of the Dakotas, USA

This study uses biophysical values derived for the Prairie Pothole Region (PPR) of North and South Dakota, in conjunction with value transfer methods, to assess environmental and economic tradeoffs under different policy-relevant land-use scenarios over a 20-year period. The ecosystem service valuation is carried out by comparing the biophysical and economic values of three focal services (i.e. carbon sequestration, reduction in sedimentation, and waterfowl production) across three focal land uses in the region [i.e. native prairie grasslands, lands enrolled in the Conservation Reserve and Wetlands Reserve Programs (CRP/WRP), and cropland]. This study finds that CRP/WRP lands cannot mitigate (hectare for hectare) the loss of native prairie from a social welfare standpoint. Land use scenarios where native prairie loss was minimized, and CRP/WRP lands were increased, provided the most societal benefit. The scenario modeling projected native prairie conversion to cropland over the next 20 years would result in a social welfare loss valued at over $4 billion when considering the study's three ecosystem services, and a net loss of about $3.4 billion when reductions in commodity production are accounted for.

North Dakota;South Dakota↗

USGS2019

A strategy for defining the reference for land health and degradation assessments

Much of the confusion about the definition of reference conditions for land health and degradation assessments is due to differences in policy and management objectives. Selection of a historic reference where it is not necessary, such as in the definition of future land degradation neutrality, can add significant cost and uncertainty to land management projects that require some knowledge of the current status of the land relative to its potential. This paper (1) provides a review of conditions under which historic reference information is and is not required to meet management and policy objectives, (2) summarizes current approaches to defining the reference for land health and degradation assessments, and (3) presents a protocol, “Describing Indicators of Rangeland Health” (DIRH) for collecting and organizing data that can be used to define a historic reference. This protocol builds on the framework and indicators presented in the “Interpreting Indicators of Rangeland Health” (IIRH). IIRH uses a combination of scientific and local knowledge to generate soil- and climate-specific assessments of three attributes of land health. It is used in a number of countries. In the United States, data are aggregated over 30,000 locations to provide national assessments.

Ecological Indicators↗

USGS2026

Vulnerability of different Colorado Plateau land types to drivers of change

Public lands are challenged by a range of pressures—changing climate, increasing visitation, resource extraction—and their effects can span spatial scales, often crossing land management jurisdictional boundaries. Research approaches which explicitly span jurisdictions can support strategies to contend with regional pressures. We assess management-relevant drivers of change—aridification, livestock grazing, invasive species, surface disturbance, and fire—across a patchwork of land management units and agencies on the Colorado Plateau, focusing on southeastern Utah, USA. We use vulnerability analysis, first evaluating exposure to drivers across the landscape, then quantifying sensitivity to each driver across different land types, defined by mapped Ecological Site Groups, a system for classifying landscapes according to physical factors including climate, soils, and topographic setting. We address the questions: 1) how are drivers spatially distributed across the study region; and, 2) based on exposure and sensitivity, are certain land types more vulnerable to these drivers? We find that the study region has high exposure and sensitivity—and thus high vulnerability—to aridification and grazing, but low exposure and vulnerability to other drivers. Although more sensitive land types were not generally more exposed, identifying which areas are most sensitive can guide adaptive measures, like where new uses or disturbances would be least harmful and which areas could be prioritized for restoration. The method we demonstrate is a flexible tool for assessing landscape-scale impacts, is built on nationally available datasets, and can be tailored to different datasets and sensitivity metrics.

Utah↗

USGS2005

Cenozoic ice sheet history from East Antarctic Wilkes Land continental margin sediments

The long-term history of glaciation along the East Antarctic Wilkes Land margin, from the time of the first arrival of the ice sheet to the margin, through the significant periods of Cenozoic climate change is inferred using an integrated geophysical and geological approach. We postulate that the first arrival of the ice sheet to the Wilkes Land margin resulted in the development of a large unconformity (WL-U3) between 33.42 and 30 Ma during the early Oligocene cooling climate trend. Above WL-U3, substantial margin progradation takes place with early glacial strata (e.g., outwash deposits) deposited as low-angle prograding foresets by temperate glaciers. The change in geometry of the prograding wedge across unconformity WL-U8 is interpreted to represent the transition, at the end of the middle Miocene "climatic optimum" (14-10 Ma), from a subpolar regime with dynamic ice sheets (i.e., ice sheets come and go) to a regime with persistent but oscillatory ice sheets. The steep foresets above WL-U8 likely consist of ice proximal sediments (i.e., water-lain till and debris flows) deposited when grounded ice-sheets extended into the shelf. On the continental rise, shelf progradation above WL-U3 results in an up-section increase in the energy of the depositional environment (i.e., seismic facies indicative of more proximal turbidite and of bottom contour current deposition from the deposition of the lower WL-S5 sequence to WL-S7). Maximum rates of sediment delivery to the rise occur during the development of sequences WL-S6 and WL-S7, which we infer to be of middle Miocene age. During deposition of the two uppermost sequences, WL-S8 and WL-S9, there is a marked decrease in the sediment supply to the lower continental rise and a shift in the depocenters to more proximal areas of the margin. We believe WL-S8 records sedimentation during the final transition from a dynamic to a persistent but oscillatory ice sheet in this margin (14-10 Ma). Sequence WL-S9 forms under a polar regime during the Pliocene-Pleistocene, when most sediment delivered to the margin is trapped in the outer shelf and slope-forming steep prograding wedges. During the warmer but still polar, Holocene, biogenic sediment accumulates quickly in deep inner-shelf basins during the high-stand intervals. These sediments contain an ultrahigh resolution (annual to millennial) record of climate variability. Validation of our inferences about the nature and timing of Wilkes Land glacial sequences can be achieved by deep sampling (i.e., using IODP-type techniques). The most complete record of the long-term history of glaciation in this margin can be obtained by sampling both (1) the shelf, which contains the direct (presence or no presence of ice) but low-resolution record of glaciation, and (2) the rise, which contains the distal (cold vs. warm) but more complete record of glaciation. The Wilkes Land margin is the only known Antarctic margin where the presumed "onset" of glaciation unconformity (WL-U3) can be traced from shelf to the abyssal plain, allowing links between the proximal and the distal records of glaciation to be established. Additionally, the eastern segment of the Wilkes Land margin may be more sensitive to climate change because the East Antarctic Ice Sheet (EAIS) is grounded below sea level. Therefore, the Wilkes Land margin is not only an ideal location to obtain the long-term EAIS history but also to obtain the shorter-term record of ice sheet fluctuations at times that the East Antarctic Ice Sheet is thought to have been more stable (after 15 Ma-recent). ?? 2004 Elsevier B.V. All rights reserved.

Global and Planetary Change↗

USGS2008

Seasonal temperature responses to land-use change in the western United States

In the western United States, more than 79 000??km2 has been converted to irrigated agriculture and urban areas. These changes have the potential to alter surface temperature by modifying the energy budget at the land-atmosphere interface. This study reports the seasonally varying temperature responses of four regional climate models (RCMs) - RSM, RegCM3, MM5-CLM3, and DRCM - to conversion of potential natural vegetation to modern land-cover and land-use over a 1-year period. Three of the RCMs supplemented soil moisture, producing large decreases in the August mean (- 1.4 to - 3.1????C) and maximum (- 2.9 to - 6.1????C) 2-m air temperatures where natural vegetation was converted to irrigated agriculture. Conversion to irrigated agriculture also resulted in large increases in relative humidity (9% to 36% absolute change). Modeled changes in the August minimum 2-m air temperature were not as pronounced or consistent across the models. Converting natural vegetation to urban land-cover produced less pronounced temperature effects in all models, with the magnitude of the effect dependent upon the preexisting vegetation type and urban parameterizations. Overall, the RCM results indicate that the temperature impacts of land-use change are most pronounced during the summer months, when surface heating is strongest and differences in surface soil moisture between irrigated land and natural vegetation are largest. ?? 2007 Elsevier B.V. All rights reserved.

Global and Planetary Change↗

USGS2012

Developing spatially explicit footprints of plausible land-use scenarios in the Santa Cruz Watershed, Arizona and Sonora

The SLEUTH urban growth model is applied to a binational dryland watershed to envision and evaluate plausible future scenarios of land use change into the year 2050. Our objective was to create a suite of geospatial footprints portraying potential land use change that can be used to aid binational decision-makers in assessing the impacts relative to sustainability of natural resources and potential socio-ecological consequences of proposed land-use management. Three alternatives are designed to simulate different conditions: (i) a Current Trends Scenario of unmanaged exponential growth, (ii) a Conservation Scenario with managed growth to protect the environment, and (iii) a Megalopolis Scenario in which growth is accentuated around a defined international trade corridor. The model was calibrated with historical data extracted from a time series of satellite images. Model materials, methodology, and results are presented. Our Current Trends Scenario predicts the footprint of urban growth to approximately triple from 2009 to 2050, which is corroborated by local population estimates. The Conservation Scenario results in protecting 46% more of the Evergreen class (more than 150,000 acres) than the Current Trends Scenario and approximately 95,000 acres of Barren Land, Crops, Deciduous Forest (Mesquite Bosque), Grassland/Herbaceous, Urban/Recreational Grasses, and Wetlands classes combined. The Megalopolis Scenario results also depict the preservation of some of these land-use classes compared to the Current Trends Scenario, most notably in the environmentally important headwaters region. Connectivity and areal extent of land cover types that provide wildlife habitat were preserved under the alternative scenarios when compared to Current Trends.

Arizona;Sonora↗

USGS2009

Estimating accuracy of land-cover composition from two-stage cluster sampling

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), root mean square error (RMSE), and correlation (CORR) to quantify accuracy of land-cover composition for a general two-stage cluster sampling design, and for the special case of simple random sampling without replacement (SRSWOR) at each stage. The bias of the estimators for the two-stage SRSWOR design is evaluated via a simulation study. The estimators of RMSE and CORR have small bias except when sample size is small and the land-cover class is rare. The estimator of MAD is biased for both rare and common land-cover classes except when sample size is large. A general recommendation is that rare land-cover classes require large sample sizes to ensure that the accuracy estimators have small bias. ?? 2009 Elsevier Inc.

Remote Sensing of Environment↗

USGS2013

Accuracy assessment of NLCD 2006 land cover and impervious surface

Release of NLCD 2006 provides the first wall-to-wall land-cover change database for the conterminous United States from Landsat Thematic Mapper (TM) data. Accuracy assessment of NLCD 2006 focused on four primary products: 2001 land cover, 2006 land cover, land-cover change between 2001 and 2006, and impervious surface change between 2001 and 2006. The accuracy assessment was conducted by selecting a stratified random sample of pixels with the reference classification interpreted from multi-temporal high resolution digital imagery. The NLCD Level II (16 classes) overall accuracies for the 2001 and 2006 land cover were 79% and 78%, respectively, with Level II user's accuracies exceeding 80% for water, high density urban, all upland forest classes, shrubland, and cropland for both dates. Level I (8 classes) accuracies were 85% for NLCD 2001 and 84% for NLCD 2006. The high overall and user's accuracies for the individual dates translated into high user's accuracies for the 2001–2006 change reporting themes water gain and loss, forest loss, urban gain, and the no-change reporting themes for water, urban, forest, and agriculture. The main factor limiting higher accuracies for the change reporting themes appeared to be difficulty in distinguishing the context of grass. We discuss the need for more research on land-cover change accuracy assessment.

Remote Sensing of Environment↗

USGS2017

Thematic accuracy assessment of the 2011 National Land Cover Database (NLCD)

Accuracy assessment is a standard protocol of National Land Cover Database (NLCD) mapping. Here we report agreement statistics between map and reference labels for NLCD 2011, which includes land cover for ca. 2001, ca. 2006, and ca. 2011. The two main objectives were assessment of agreement between map and reference labels for the three, single-date NLCD land cover products at Level II and Level I of the classification hierarchy, and agreement for 17 land cover change reporting themes based on Level I classes (e.g., forest loss; forest gain; forest, no change) for three change periods (2001–2006, 2006–2011, and 2001–2011). The single-date overall accuracies were 82%, 83%, and 83% at Level II and 88%, 89%, and 89% at Level I for 2011, 2006, and 2001, respectively. Many class-specific user's accuracies met or exceeded a previously established nominal accuracy benchmark of 85%. Overall accuracies for 2006 and 2001 land cover components of NLCD 2011 were approximately 4% higher (at Level II and Level I) than the overall accuracies for the same components of NLCD 2006. The high Level I overall, user's, and producer's accuracies for the single-date eras in NLCD 2011 did not translate into high class-specific user's and producer's accuracies for many of the 17 change reporting themes. User's accuracies were high for the no change reporting themes, commonly exceeding 85%, but were typically much lower for the reporting themes that represented change. Only forest loss, forest gain, and urban gain had user's accuracies that exceeded 70%. Lower user's accuracies for the other change reporting themes may be attributable to the difficulty in determining the context of grass (e.g., open urban, grassland, agriculture) and between the components of the forest-shrubland-grassland gradient at either the mapping phase, reference label assignment phase, or both. NLCD 2011 user's accuracies for forest loss, forest gain, and urban gain compare favorably with results from other land cover change accuracy assessments.

Remote Sensing of Environment↗

USGS2024

Elemental composition and potential toxicity of the riverine macrophyte Podostemum ceratophyllum Michx. reflects land use in eastern North America

Land use influences surface water quality, often alleviating stoichiometric constraints on primary production and altering biogeochemical cycling. However, land use effects on nutrient content and potential trace metal accumulation in aquatic plants remain unclear, and high concentrations of metals and altered nutrient ratios could impact the health of herbivores and detritivores. We tested for land use effects on nutrient and trace metal accumulation in a widespread riverine macrophyte, Podostemum ceratophyllum , collected from 91 locations from Georgia to Maine, USA in 2014–2016. We quantified carbon (C), nitrogen (N), phosphorus (P), their molar and mass ratios, N and C stable isotopes, and 17 additional elements in dried plants collected from each location to estimate relationships between plant tissue content and watershed land use, which we quantified as agriculture, forest, and development. Decreasing forest cover was correlated with increasing δ 15 N, Mg, Mn, and P in Podostemum tissue. Increasing urban development was correlated with increasing δ 15 N, Mg and P, while increasing agriculture was correlated with a decrease in C: P and the concentrations of multiple metals, along with increases in P, Mg and δ 15 N. Decreases in ratios of N: P and C:P with increasing agriculture and urban development in the watershed indicate more rapid P storage relative to C and N in plant tissue, and increased resource quality of the plant to consumers in these watersheds. We also observed potentially toxic dietary concentrations of some trace metals (B, Cd, Tl, Zn) in plant tissue which could be related to the plant's natural herbivory defense system or to land use. We conclude that land use influences the elemental composition of P. ceratophyllum , and potentially the quality and toxicity of the plant to herbivores and detritivores in eastern North American rivers.

Science of the Total Environment↗

USGS2003

Effects of landscape characteristics on land-cover class accuracy

The effects of patch size and land-cover heterogeneity on classification accuracy were evaluated using reference data collected for the National Land-Cover Data (NLCD) set accuracy assessment. Logistic regression models quantified the relationship between classification accuracy and these landscape variables for each land-cover class at both the Anderson Levels I and II classification schemes employed in the NLCD. The general relationships were consistent, with the odds of correctly classifying a pixel increasing as patch size increased and decreasing as heterogeneity increased. Specific characteristics of these relationships, however, showed considerable diversity among the various classes. Odds ratios are reported to document these relationships. Interaction between the two landscape variables was not a significant influence on classification accuracy, indicating that the effect of heterogeneity was not impacted by the sample being in a small or large patch. Landscape variables remained significant predictors of class-specific accuracy even when adjusted for regional differences in the mapping and assessment processes or landscape characteristics. The land-cover class-specific analyses provide insight into sources of classification error and a capacity for predicting error based on a pixel's mapped land-cover class, patch size and surrounding land-cover heterogeneity.

Remote Sensing of Environment↗

USGS2003

Statistical sampling to characterize recent United States land-cover change

The U.S. Geological Survey, in conjunction with the U.S. Environmental Protection Agency, is conducting a study focused on developing methods for estimating changes in land-cover and landscape pattern for the conterminous United States from 1973 to 2000. Eleven land-cover and land-use classes are interpreted from Landsat imagery for five sampling dates. Because of the high cost and potential effect of classification error associated with developing change estimates from wall-to-wall land-cover maps, a probability sampling approach is employed. The basic sampling unit is a 20 x 20 km area, and land cover is obtained for each 60 x 60 m pixel within the sampling unit. The sampling design is stratified based on ecoregions, and land-cover change estimates are constructed for each stratum. The sampling design and analyses are documented, and estimates of change accompanied by standard errors are presented to demonstrate the methodology. Analyses of the completed strata suggest that the sampling unit should be reduced to a 10 x 10 km block, and poststratified estimation and regression estimation are viable options to improve precision of estimated change. ?? 2003 Elsevier Inc. All rights reserved.

Remote Sensing of Environment↗