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At least 937 records · Page 52Linked to original sources
USGS1985

Interim program for land cover mapping in Alaska utilizing Landsat digital data

The enactment of the Alaska National Interest Lands Conservation Act (ANILCA) in 1980 imposed mandates on all major land management agencies in Alaska to prepare comprehensive resource and management plans to assess wildlife habitat, oil and gas exploration and development, wild and scenic river, land disposals, timber production, and archaeological and cultural resources, To meet these objective, the U. S. Geological Survey (USGS) has embarked on a plan to classify land cover for the entire State of Alaska using Landsat digital data. the USGS, in cooperation with other agencies, has completely Landsat-derived land use and land cover classification of 115 million acres for the State of Alaska. With this work as a substantial foundation, the USGS has prepared a comprehensive plan for classifying the remaining areas of Alaska. The development of this program will lead to a complete interim land use and land cover classification system for Alaska and provide for the dissemination of map products, statistics, and acreage summaries for all areas of Alaska at 1:250,000 scale. It also allows for the dissemination of Landsat digital data for those areas.

Alaska↗
USGS2000

Implementation strategy for production of National Land-Cover Data (NLCD) from the Landsat 7 Thematic Mapper satellite

As environmental programs within and outside the federal government continue to move away from point-based studies to larger and larger spatial (not cartographic) scale, the need for land-cover and other geographic data have become ineluctable. The national land-cover mapping project of MRLC marks the first consistently classified conterminous land-cover data set, effectively replacing USGS' Land Use Data Analysis (LUDA) system derived from high altitidue aerial photography acquired in the early 1970's. Because of the continually changing nature of the earth's surface due to anthropogenic activities and other factors, a single point-in-time land-cover product is insufficient for many applications. Production of a second point-in-time land-cover product is proposed as a database. That proposed database design includes: (1) second, independently classified land-cover data set derived from Landsat 7 Thematic Mapper data; (2) the land-cover product being produced under the current effort, (3) selected spectral-based change estimates (e.g., temporal NDVI), (4) thirty-meter DEMS; and (5) selected landscape metrics. Development of the database for the conterminous United States will start after evaluation of the prototype.

Technical Report↗
USGS1995

Non-native animals on public lands

Non-native plants and animals have become part of our surroundings, in cities, agricultural areas, and wildlands. While there are many beneficial purposes for non-native animals, such as for food and sport hunting and as agricultural animals, the introduction of some has had major negative economic consequences (Palmer 1899), and adverse effects on native wildlife, plants, and habitats. The British ecologist Charles Elton, in a major review of introduced species, described the increasing number of invasions as constituting "one of the great historical convulsions in the world's flora and fauna" (Elton 1958, p. 31). Non-native species are significant problems on large areas of state and federal public lands, and areas set aside to protect native plant and animal communities are not immune to such harm. Science and conservation journals have devoted entire issues to the threats posed by non-native plants and animals in nature reserves (e.g., Usher et al. 1988). In a compilation of threats to U.S. national parks, non-native plants and animals were the most often reported threat, and were reported by the most areas; feral cats ( Felis catus ), feral dogs ( Canis familiaris ), and wild pigs ( Sus scrofa ) were the non-native animals cited most often (NPCA 1977). Non-native species present serious threats, but at the same time, coordinated efforts on public lands offer the best possibility for controlling some harmful non-native species, and protecting both native plant and animal communities and human interests and needs. We compiled information on non-native animals on public and private land-management areas by conducting a mail survey to assess their occurrence and management status in land-management areas. Survey results represent contributions from 937 national parks, national forests, national wildlife refuges, Bureau of Land Management field areas, and state and private land-management areas. The results reflect those species that land managers considered of greatest concern, and their general distribution on public lands. Non-native invertebrate animals, particularly forest insects and agricultural pests, cause severe economic and environmental damage as well (OTA 1993), but were not the focus of this survey.

Book chapter↗
USGS2020

Land-use change and future water demand in California’s central coast

Understanding future land-use related water demand is important for planners and resource managers in identifying potential shortages and crafting mitigation strategies. This is especially the case for regions dependent on limited local groundwater supplies. For the groundwater dependent Central Coast of California, we developed two scenarios of future land use and water demand based on sampling from a historical land change record: a business-as-usual scenario (BAU; 1992–2016) and a recent-modern scenario (RM; 2002–2016). We modeled the scenarios in the stochastic, empirically based, spatially explicit LUCAS state-and-transition simulation model at a high resolution (270-m) for the years 2001–2100 across 10 Monte Carlo simulations, applying current land zoning restrictions. Under the BAU scenario, regional water demand increased by an estimated ~222.7 Mm 3 by 2100, driven by the continuation of perennial cropland expansion as well as higher than modern urbanization rates. Since 2000, mandates have been in place restricting new development unless adequate water resources could be identified. Despite these restrictions, water demand dramatically increased in the RM scenario by 310.6 Mm 3 by century’s end, driven by the projected continuation of dramatic orchard and vineyard expansion trends. Overall, increased perennial cropland leads to a near doubling to tripling perennial water demand by 2100. Our scenario projections can provide water managers and policy makers with information on diverging land use and water use futures based on observed land change and water use trends, helping to better inform land and resource management decisions.

California↗
USGS2016

Assessing the sensitivity of avian species abundance to land cover and climate

Climate projections for the Midwestern United States predict southerly climates to shift northward. These shifts in climate could alter distributions of species across North America through changes in climate (i.e., temperature and precipitation), or through climate-induced changes on land cover. Our objective was to determine the relative impacts of land cover and climate on the abundance of five bird species in the Central United States that have habitat requirements ranging from grassland and shrubland to forest. We substituted space for time to examine potential impacts of a changing climate by assessing climate and land cover relationships over a broad latitudinal gradient. We found positive and negative relationships of climate and land cover factors with avian abundances. Habitat variables drove patterns of abundance in migratory and resident species, although climate was also influential in predicting abundance for some species occupying more open habitat (i.e., prairie warbler, blue-winged warbler, and northern bobwhite). Abundance of northern bobwhite increased with winter temperature and was the species exhibiting the most significant effect of climate. Models for birds primarily occupying early successional habitats performed better with a combination of habitat and climate variables whereas models of species found in contiguous forest performed best with land cover alone. These varied species-specific responses present unique challenges to land managers trying to balance species conservation over a variety of land covers. Management activities focused on increasing forest cover may play a role in mitigating effects of future climate by providing habitat refugia to species vulnerable to projected changes. Conservation efforts would be best served focusing on areas with high species abundances and an array of habitats. Future work managing forests for resilience and resistance to climate change could benefit species already susceptible to climate impacts.

Ecosphere↗
USGS2015

Impacts of climate change on land-use and wetland productivity in the Prairie Pothole Region of North America

Wetland productivity in the Prairie Pothole Region (PPR) of North America is closely linked to climate. A warmer and drier climate, as predicted, will negatively affect the productivity of PPR wetlands and the services they provide. The effect of climate change on wetland productivity, however, will not only depend on natural processes (e.g., evapotranspiration), but also on human responses. Agricultural land use, the predominant use in the PPR, is unlikely to remain static as climate change affects crop yields and prices. Land use in uplands surrounding wetlands will further affect wetland water budgets and hence wetland productivity. The net impact of climate change on wetland productivity will therefore depend on both the direct effects of climate change on wetlands and the indirect effects on upland land use. We examine the effect of climate change and land-use response on semipermanent wetland productivity by combining an economic model of agricultural land-use change with an ecological model of wetland dynamics. Our results suggest that the climate change scenarios evaluated are likely to have profound effects on land use in the North and South Dakota PPR, with wheat displacing other crops and pasture. The combined pressure of land-use and climate change significantly reduces wetland productivity. In a climate scenario with a +4 °C increase in temperature, our model predicts that almost the entire region may lack the wetland productivity necessary to support wetland-dependent species.

North Dakota, South Dakota↗
USGS2018

Divergent effects of land-use, propagule pressure, and climate on woody riparian invasion

Landscape-scale analyses of biological invasion are needed to understand the relative importance of environmental drivers that vary at larger scales, such as climate, propagule pressure, resource availability, and human disturbance. One poorly understood landscape-scale question is, how does human land-use influence riparian plant invasion? To evaluate the relative importance of land-use, climate, propagule pressure, and water availability in riparian invasion, we examined tamarisk ( Tamarix ramosissima, T. chinensis , hybrids), Russian olive ( Elaeagnus angustifolia ), and Siberian elm ( Ulmus pumila ) occurrence, abundance, and dominance in 238 riparian sites in developed, cultivated, and undeveloped areas of four western USA river basins (281,946 km 2 ). Temperature and propagule pressure from individuals planted nearby largely drove invasive species occurrence, whereas factors likely to affect resource availability (e.g., land-use, precipitation, streamflow intermittency) were more important to abundance and dominance, supporting the argument that species distribution models based on occurrence alone may fail to identify conditions where invasive species have the greatest impact. The role of land-use varied among taxa: urban and suburban land-use increased Siberian elm occurrence, abundance, and dominance, and urban land-use increased Russian olive occurrence, whereas suburban land-use reduced tamarisk dominance. Surprisingly, Siberian elm, which has received scant prior scientific and management attention, occurred as or more frequently than tamarisk and Russian olive (except in undeveloped areas of the Colorado River headwaters) and had higher density and dominance than tamarisk and Russian olive in developed areas. More research is needed to understand the impacts of this largely unrecognized invader on riparian ecosystem services, particularly in urban and suburban areas.

Colorado, New Mexico↗
USGS2016

Analysis of local slopes at the InSight landing site on Mars

To evaluate the topography of the surface within the InSight candidate landing ellipses, we generated Digital Terrain Models (DTMs) at lander scales and those appropriate for entry, descent, and landing simulations, along with orthoimages of both images in each stereopair, and adirectional slope images. These products were used to assess the distribution of slopes for each candidate ellipse and terrain type in the landing site region, paying particular attention to how these slopes impact InSight landing and engineering safety, and results are reported here. Overall, this region has extremely low slopes at 1-meter baseline scales and meets the safety constraints of the InSight lander. The majority of the landing ellipse has a mean slope at 1-meter baselines of 3.2°. In addition, a mosaic of HRSC, CTX, and HiRISE DTMs within the final landing ellipse (ellipse 9) was generated to support entry, descent, and landing simulations and evaluations. Several methods were tested to generate this mosaic and the NASA Ames Stereo Pipeline program dem_mosaic produced the best results. For the HRSC-CTX-HiRISE DTM mosaic, more than 99 % of the mosaic has slopes less than 15°, and the introduction of artificially high slopes along image seams was minimized.

Space Science Reviews↗
USGS2008

A multi-model framework for simulating wildlife population response to land-use and climate change

Reliable assessments of how human activities will affect wildlife populations are essential for making scientifically defensible resource management decisions. A principle challenge of predicting effects of proposed management, development, or conservation actions is the need to incorporate multiple biotic and abiotic factors, including land-use and climate change, that interact to affect wildlife habitat and populations through time. Here we demonstrate how models of land-use, climate change, and other dynamic factors can be integrated into a coherent framework for predicting wildlife population trends. Our framework starts with land-use and climate change models developed for a region of interest. Vegetation changes through time under alternative future scenarios are predicted using an individual-based plant community model. These predictions are combined with spatially explicit animal habitat models to map changes in the distribution and quality of wildlife habitat expected under the various scenarios. Animal population responses to habitat changes and other factors are then projected using a flexible, individual-based animal population model. As an example application, we simulated animal population trends under three future land-use scenarios and four climate change scenarios in the Cascade Range of western Oregon. We chose two birds with contrasting habitat preferences for our simulations: winter wrens (Troglodytes troglodytes), which are most abundant in mature conifer forests, and song sparrows (Melospiza melodia), which prefer more open, shrubby habitats. We used climate and land-use predictions from previously published studies, as well as previously published predictions of vegetation responses using FORCLIM, an individual-based forest dynamics simulator. Vegetation predictions were integrated with other factors in PATCH, a spatially explicit, individual-based animal population simulator. Through incorporating effects of landscape history and limited dispersal, our framework predicted population changes that typically exceeded those expected based on changes in mean habitat suitability alone. Although land-use had greater impacts on habitat quality than did climate change in our simulations, we found that small changes in vital rates resulting from climate change or other stressors can have large consequences for population trajectories. The ability to integrate bottom-up demographic processes like these with top-down constraints imposed by climate and land-use in a dynamic modeling environment is a key advantage of our approach. The resulting framework should allow researchers to synthesize existing empirical evidence, and to explore complex interactions that are difficult or impossible to capture through piecemeal modeling approaches. ?? 2008 Elsevier B.V.

Ecological Modelling↗
USGS2013

Land-cover change in the conterminous United States from 1973 to 2000

Land-cover change in the conterminous United States was quantified by interpreting change from satellite imagery for a sample stratified by 84 ecoregions. Gross and net changes between 11 land-cover classes were estimated for 5 dates of Landsat imagery (1973, 1980, 1986, 1992, and 2000). An estimated 673,000 km 2 (8.6%) of the United States’ land area experienced a change in land cover at least one time during the study period. Forest cover experienced the largest net decline of any class with 97,000 km2 lost between 1973 and 2000. The large decline in forest cover was prominent in the two regions with the highest percent of overall change, the Marine West Coast Forests (24.5% of the region experienced a change in at least one time period) and the Eastern Temperate Forests (11.4% of the region with at least one change). Agriculture declined by approximately 90,000 km 2 with the largest annual net loss of 12,000 km 2 yr −1 occurring between 1986 and 1992. Developed area increased by 33% and with the rate of conversion to developed accelerating rate over time. The time interval with the highest annual rate of change of 47,000 km 2 yr −1 (0.6% per year) was 1986–1992. This national synthesis documents a spatially and temporally dynamic era of land change between 1973 and 2000. These results quantify land change based on a nationally consistent monitoring protocol and contribute fundamental estimates critical to developing understanding of the causes and consequences of land change in the conterminous United States.

Global Environmental Change↗
USGS2017

Can private land conservation reduce wildfire risk to homes? A case study in San Diego County, California, USA

The purchase of private land for conservation purposes is a common way to prevent the exploitation of sensitive ecological areas. However, private land conservation can also provide other benefits, one of these being natural hazard reduction. Here, we investigated the impacts of private land conservation on fire risk to homes in San Diego County, California. We coupled an econometric land use change model with a model that estimates the probability of house loss due to fire in order to compare fire risk at the county and municipality scale under alternative private land purchasing schemes and over a 20 year time horizon. We found that conservation purchases could reduce fire risk on this landscape, and the amount of risk reduction was related to the targeting approach used to choose which parcels were conserved. Conservation land purchases that targeted parcels designated as high fire hazard resulted in lower fire risk to homes than purchases that targeted low costs or high likelihood to subdivide. This result was driven by (1) preventing home placement in fire prone areas and (2) taking land off the market, and hence increasing development densities in other areas. These results raise the possibility that resource conservation and fire hazard reduction may benefit from combining efforts. With adequate planning, future conservation purchases could have synergistic effects beyond just protecting ecologically sensitive areas.

California↗
USGS2008

Landsat continuity: Issues and opportunities for land cover monitoring

Initiated in 1972, the Landsat program has provided a continuous record of earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and indispensable for monitoring, management, and scientific activities. Recent technical problems with the two existing Landsat satellites, and delays in the development and launch of a successor, increase the likelihood that a gap in Landsat continuity may occur. In this communication, we identify the key features of the Landsat program that have resulted in the extensive use of Landsat data for large area land cover mapping and monitoring. We then augment this list of key features by examining the data needs of existing large area land cover monitoring programs. Subsequently, we use this list as a basis for reviewing the current constellation of earth observation satellites to identify potential alternative data sources for large area land cover applications. Notions of a virtual constellation of satellites to meet large area land cover mapping and monitoring needs are also presented. Finally, research priorities that would facilitate the integration of these alternative data sources into existing large area land cover monitoring programs are identified. Continuity of the Landsat program and the measurements provided are critical for scientific, environmental, economic, and social purposes. It is difficult to overstate the importance of Landsat; there are no other systems in orbit, or planned for launch in the short-term, that can duplicate or approach replication, of the measurements and information conferred by Landsat. While technical and political options are being pursued, there is no satellite image data stream poised to enter the National Satellite Land Remote Sensing Data Archive should system failures occur to Landsat-5 and -7.

Remote Sensing of Environment↗
USGS2007

Improving land resource evaluation using fuzzy neural network ensembles

Land evaluation factors often contain continuous-, discrete- and nominal-valued attributes. In traditional land evaluation, these different attributes are usually graded into categorical indexes by land resource experts, and the evaluation results rely heavily on experts' experiences. In order to overcome the shortcoming, we presented a fuzzy neural network ensemble method that did not require grading the evaluation factors into categorical indexes and could evaluate land resources by using the three kinds of attribute values directly. A fuzzy back propagation neural network (BPNN), a fuzzy radial basis function neural network (RBFNN), a fuzzy BPNN ensemble, and a fuzzy RBFNN ensemble were used to evaluate the land resources in Guangdong Province. The evaluation results by using the fuzzy BPNN ensemble and the fuzzy RBFNN ensemble were much better than those by using the single fuzzy BPNN and the single fuzzy RBFNN, and the error rate of the single fuzzy RBFNN or fuzzy RBFNN ensemble was lower than that of the single fuzzy BPNN or fuzzy BPNN ensemble, respectively. By using the fuzzy neural network ensembles, the validity of land resource evaluation was improved and reliance on land evaluators' experiences was considerably reduced. ?? 2007 Soil Science Society of China.

Pedosphere↗
USGS2014

Influence of grazing and land use on stream-channel characteristics among small dairy farms in the Eastern United States

Rotational grazing (RG) is a livestock management practice that rotates grazing cattle on a scale of hours to days among small pastures termed paddocks. It may beneficially affect stream channels, relative to other livestock management practices. Such effects and other beneficial effects on hydrology are important to RG's potential to provide a highly multifunctional mode of livestock farming. Previous comparisons of effects of RG and confinement dairy (CD) on adjoining streams have been restricted in scale and scope. We examined 11 stream-channel characteristics on a representative sample of 37 small dairy farms that used either RG or CD production methods. Our objectives were: (1) to compare channel characteristics on RG and CD farms, as these production methods are implemented in practice, in New York, Pennsylvania and Wisconsin, USA; and (2) to examine land use on these farms that may affect stream-channel characteristics. To help interpret channel characteristic findings, we examined on-farm land use in riparian areas 50 m in width along both sides of stream reaches and whole-farm land use. In all states, stream-channel characteristics on RG and CD farms did not differ. Whole-farm land use differed significantly between farm types; CD farms allocated more land to annual row crops, whereas RG farms allocated more land to pasture and grassland. However, land cover in 50 m riparian areas was not different between farm types within states; in particular, many RG and CD farms had continuously grazed pastures in riparian areas, typically occupied by juvenile and non-lactating cows, which may have contributed sediment and nutrients to streams. This similarity in riparian management practices may explain the observed similarity of farm types with respect to stream-channel characteristics. To realize the potential benefits of RG on streams, best management practices that affect stream-channel characteristics, such as protection of riparian areas, may improve aggregate effects of RG on stream quality and also enhance other environment, economic and social benefits of RG.

Renewable Agriculture and Food Systems↗
USGS2003

Survey methods for assessing land cover map accuracy

The increasing availability of digital photographic materials has fueled efforts by agencies and organizations to generate land cover maps for states, regions, and the United States as a whole. Regardless of the information sources and classification methods used, land cover maps are subject to numerous sources of error. In order to understand the quality of the information contained in these maps, it is desirable to generate statistically valid estimates of accuracy rates describing misclassification errors. We explored a full sample survey framework for creating accuracy assessment study designs that balance statistical and operational considerations in relation to study objectives for a regional assessment of GAP land cover maps. We focused not only on appropriate sample designs and estimation approaches, but on aspects of the data collection process, such as gaining cooperation of land owners and using pixel clusters as an observation unit. The approach was tested in a pilot study to assess the accuracy of Iowa GAP land cover maps. A stratified two-stage cluster sampling design addressed sample size requirements for land covers and the need for geographic spread while minimizing operational effort. Recruitment methods used for private land owners yielded high response rates, minimizing a source of nonresponse error. Collecting data for a 9-pixel cluster centered on the sampled pixel was simple to implement, and provided better information on rarer vegetation classes as well as substantial gains in precision relative to observing data at a single-pixel.

Environmental and Ecological Statistics↗
USGS2004

Assessing development pressure in the Chesapeake Bay watershed: An evaluation of two land-use change models

Natural resource lands in the Chesapeake Bay watershed are increasingly susceptible to conversion into developed land uses, particularly as the demand for residential development grows. We assessed development pressure in the Baltimore-Washington, DC region, one of the major urban and suburban centers in the watershed. We explored the utility of two modeling approaches for forecasting future development trends and patterns by comparing results from a cellular automata model, SLEUTH (slope, land use, excluded land, urban extent, transportation), and a supply/demand/allocation model, the Western Futures Model. SLEUTH can be classified as a land-cover change model and produces projections on the basis of historic trends of changes in the extent and patterns of developed land and future land protection scenarios. The Western Futures Model derives forecasts from historic trends in housing units, a U.S. Census variable, and exogenously supplied future population projections. Each approach has strengths and weaknesses, and combining the two has advantages and limitations. ?? 2004 Kluwer Academic Publishers.

Environmental Monitoring and Assessment↗
USGS2012

Quantifying urban land cover change between 2001 and 2006 in the Gulf of Mexico region

We estimated urbanization rates (2001–2006) in the Gulf of Mexico region using the National Land Cover Database (NLCD) 2001 and 2006 impervious surface products. An improved method was used to update the NLCD impervious surface product in 2006 and associated land cover transition between 2001 and 2006. Our estimation reveals that impervious surface increased 416 km 2 with a growth rate of 5.8% between 2001 and 2006. Approximately 1110.1 km 2 of non-urban lands were converted into urban land, resulting in a 3.2% increase in the region. Hay/pasture, woody wetland, and evergreen forest represented the three most common land cover classes that transitioned to urban. Among these land cover transitions, more than 50% of the urbanization occurred within 50 km of the coast. Our analysis shows that the close-to-coast land cover transition trend, especially within 10 km off the coast, potentially imposes substantial long-term impacts on regional landscape and ecological conditions.

Gulf of Mexico↗
USGS2021

Ecosystem carbon balance in the Hawaiian Islands under different scenarios of future climate and land use change

The State of Hawai'i passed legislation to be carbon neutral by 2045, a goal that will partly depend on carbon sequestration by terrestrial ecosystems. However, there is considerable uncertainty surrounding the future direction and magnitude of the land carbon sink in the Hawaiian Islands. We used the Land Use and Carbon Scenario Simulator (LUCAS), a spatially explicit stochastic simulation model that integrates landscape change and carbon gain-loss, to assess how projected future changes in climate and land use will influence ecosystem carbon balance in the Hawaiian Islands under all combinations of two radiative forcing scenarios (RCPs 4.5 and 8.5) and two land use scenarios (low and high) over a 90 year timespan from 2010 to 2100. Collectively, terrestrial ecosystems of the Hawaiian Islands acted as a net carbon sink under low radiative forcing (RCP 4.5) for the entire 90 year simulation period, with low land use change further enhancing carbon sink strength. In contrast, Hawaiian terrestrial ecosystems transitioned from a net sink to a net source of CO 2 to the atmosphere under high radiative forcing (RCP 8.5), with high land use accelerating this transition and exacerbating net carbon loss. A sensitivity test of the CO 2 fertilization effect on plant productivity revealed it to be a major source of uncertainty in projections of ecosystem carbon balance, highlighting the need for greater mechanistic understanding of plant productivity responses to rising atmospheric CO 2 . Long-term model projections such as ours that incorporate the interactive effects of land use and climate change on regional ecosystem carbon balance will be critical to evaluating the potential of ecosystem-based climate mitigation strategies.

Hawaii↗