Completion of the National Land Cover Database (NLCD) 1992–2001 Land Cover Change Retrofit product
Fry, J.A.; Coan, Michael; Homer, Collin G.; Meyer, Debra K.; Wickham, J.D.
2009-01-01
The Multi-Resolution Land Characteristics Consortium has supported the development of two national digital land cover products: the National Land Cover Dataset (NLCD) 1992 and National Land Cover Database (NLCD) 2001. Substantial differences in imagery, legends, and methods between these two land cover products must be overcome in order to support direct comparison. The NLCD 1992-2001 Land Cover Change Retrofit product was developed to provide more accurate and useful land cover change data than would be possible by direct comparison of NLCD 1992 and NLCD 2001. For the change analysis method to be both national in scale and timely, implementation required production across many Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) path/rows simultaneously. To meet these requirements, a hybrid change analysis process was developed to incorporate both post-classification comparison and specialized ratio differencing change analysis techniques. At a resolution of 30 meters, the completed NLCD 1992-2001 Land Cover Change Retrofit product contains unchanged pixels from the NLCD 2001 land cover dataset that have been cross-walked to a modified Anderson Level I class code, and changed pixels labeled with a 'from-to' class code. Analysis of the results for the conterminous United States indicated that about 3 percent of the land cover dataset changed between 1992 and 2001.
Analysis of change in pinon-juniper woodlands based on aerial photography, 1930's-1980's
Alan R. Johnson; Bruce T. Milne; Peter Hraber
1999-01-01
We conducted an analysis of land cover change in selected piñon-juniper woodlands of New Mexico and Arizona, using aerial photographs from the 1930's through the 1980's. Both increases and decreases in woodland cover were observed. Fractal dimensions of woodland patches and cover-type changes were analyzed following the method of Krummel and others (1987)....
Jansen, Louisa J M; Carrai, Giancarlo; Morandini, Luca; Cerutti, Paolo O; Spisni, Andrea
2006-08-01
In the turmoil of a rapidly changing economy the Albanian government needs accurate and timely information for management of their natural resources and formulation of land-use policies. The transformation of the forestry sector has required major changes in the legal, regulatory and management framework. The World Bank financed Albanian National Forest Inventory project provides an analysis of spatially explicit land-cover/use change dynamics in the period 1991-2001 using the FAO/UNEP Land Cover Classification System for codification of classes, satellite remote sensing and field survey for data collection and elements of the object-oriented geo-database approach to handle changes as an evolution of land-cover/use objects, i.e. polygons, over time to facilitate change dynamics analysis. Analysis results at national level show the trend of natural resources depletion in the form of modifications and conversions that lead to a gradual shift from land-cover/use types with a tree cover to less dense tree covers or even a complete removal of trees. Policy failure (e.g., corruption, lack of law enforcement) is seen as the underlying cause. Another major trend is urbanisation of areas near large urban centres that change urban-rural linkages. Furthermore, after privatisation agricultural areas increased in the hills where environmental effects may be detrimental, while prime agricultural land in the plains is lost to urbanisation. At district level, the local variability of spatially explicit land-cover/use changes shows different types of natural resources depletion. The distribution of changes indicates a regional prevalence, thus a decentralised approach to the natural resources management could be advocated.
Influence of snow cover changes on surface radiation and heat balance based on the WRF model
NASA Astrophysics Data System (ADS)
Yu, Lingxue; Liu, Tingxiang; Bu, Kun; Yang, Jiuchun; Chang, Liping; Zhang, Shuwen
2017-10-01
The snow cover extent in mid-high latitude areas of the Northern Hemisphere has significantly declined corresponding to the global warming, especially since the 1970s. Snow-climate feedbacks play a critical role in regulating the global radiation balance and influencing surface heat flux exchange. However, the degree to which snow cover changes affect the radiation budget and energy balance on a regional scale and the difference between snow-climate and land use/cover change (LUCC)-climate feedbacks have been rarely studied. In this paper, we selected Heilongjiang Basin, where the snow cover has changed obviously, as our study area and used the WRF model to simulate the influences of snow cover changes on the surface radiation budget and heat balance. In the scenario simulation, the localized surface parameter data improved the accuracy by 10 % compared with the control group. The spatial and temporal analysis of the surface variables showed that the net surface radiation, sensible heat flux, Bowen ratio, temperature and percentage of snow cover were negatively correlated and that the ground heat flux and latent heat flux were positively correlated with the percentage of snow cover. The spatial analysis also showed that a significant relationship existed between the surface variables and land cover types, which was not obviously as that for snow cover changes. Finally, six typical study areas were selected to quantitatively analyse the influence of land cover types beneath the snow cover on heat absorption and transfer, which showed that when the land was snow covered, the conversion of forest to farmland can dramatically influence the net radiation and other surface variables, whereas the snow-free land showed significantly reduced influence. Furthermore, compared with typical land cover changes, e.g., the conversion of forest into farmland, the influence of snow cover changes on net radiation and sensible heat flux were 60 % higher than that of land cover changes, indicating the importance of snow cover changes in the surface-atmospheric feedback system.
INTEGRATING LANDSCAPE ASSESSMENT AND HYDROLOGIC MODELING FOR LAND COVER CHANGE ANALYSIS
This study is based on the assumption that land cover change and rainfall spatial variability affect the r-ainfall-runoff relationships on the watershed. Hydrologic response is an integrated indicator of watershed condition, and changes in land cover may affect the overall health...
Sharpe, Jennifer B.; Soong, David T.
2015-01-01
This study used the National Land Cover Dataset (NLCD) and developed an automated process for determining the area of the three land cover types, thereby allowing faster updating of future models, and for evaluating land cover changes by use of historical NLCD datasets. The study also carried out a raingage partitioning analysis so that the segmentation of land cover and rainfall in each modeled unit is directly applicable to the HSPF modeling. Historical and existing impervious, grass, and forest land acreages partitioned by percentages covered by two sets of raingages for the Lake Michigan diversion SCAs, gaged basins, and ungaged basins are presented.
NASA Astrophysics Data System (ADS)
Huo, L. Z.; Boschetti, L.
2016-12-01
Remote sensing has been successfully used for global mapping of changes in forest cover, but further analysis is needed to characterize those changes - and in particular to classify the total loss of forest loss (Gross Forest Cover Loss, GFCL) based on the cause (natural/human) and on the outcome of the change (regeneration to forest/transition to non-forest) (Kurtz et al., 2010). While natural forest disturbances (fires, insect outbreaks) and timber harvest generally involve a temporary change of land cover (vegetated to non-vegetated), they generally do not involve a change in land use, and it is expected that the forest cover loss is followed by recovery. Change of land use, such as the conversion of forest to agricultural or urban areas, is instead generally irreversible. The proper classification of forest cover loss is therefore necessary to properly model the long term effects of the disturbances on the carbon budget. The present study presents a spatial and temporal analysis of the forest cover loss due to urban expansion in the Conterminous United States. The Landsat-derived University of Maryland Global Forest Change product (Hansen et al, 2013) is used to identify all the areas of gross forest cover loss, which are subsequently classified into disturbance type (deforestation, stand-replacing natural disturbances, industrial forest clearcuts) using an object-oriented time series analysis (Huo and Boschetti, 2015). A further refinement of the classification is conducted to identify the areas of transition from forest land use to urban land use based on ancillary datasets such as the National Land Cover Database (Homer et al., 2015) and contextual image analysis techniques (analysis of object proximity, and detection of shapes). Results showed that over 4000 km2of forest were lost to urban area expansion in CONUS over the 2001 to 2010 period (1.8% of the gross forest cover loss). Most of the urban growth was concentrated in large urban areas: Atlanta, GA ranked first, followed by Houston, TX; Charlotte, NC; Jacksonville, FL; and Raleigh, NC. At the state level, the top 10 states with urban growth due to forest loss were GA, FL, TX, NC, SC, AL, LA, MS, VA and WA, which cumulatively accounted for 76 % of the total forest cover loss due to urban growth.
Simulation of Land-Cover Change in Taipei Metropolitan Area under Climate Change Impact
NASA Astrophysics Data System (ADS)
Huang, Kuo-Ching; Huang, Thomas C. C.
2014-02-01
Climate change causes environment change and shows up on land covers. Through observing the change of land use, researchers can find out the trend and potential mechanism of the land cover change. Effective adaptation policies can affect pattern of land cover change and may decrease the risks of climate change impacts. By simulating land use dynamics with scenario settings, this paper attempts to explore the relationship between climate change and land-cover change through efficient adaptation polices. It involves spatial statistical model in estimating possibility of land-cover change, cellular automata model in modeling land-cover dynamics, and scenario analysis in response to adaptation polices. The results show that, without any control, the critical eco-areas, such as estuarine areas, will be destroyed and people may move to the vulnerable and important economic development areas. In the other hand, under the limited development condition for adaptation, people migration to peri-urban and critical eco-areas may be deterred.
NASA Astrophysics Data System (ADS)
Amuti, T.; Luo, G.
2014-07-01
The combined effects of drought, warming and the changes in land cover have caused severe land degradation for several decades in the extremely arid desert oases of Southern Xinjiang, Northwest China. This study examined land cover changes during 1990-2008 to characterize and quantify the transformations in the typical oasis of Hotan. Land cover classifications of these images were performed based on the supervised classification scheme integrated with conventional vegetation and soil indexes. Change-detection techniques in remote sensing (RS) and a geographic information system (GIS) were applied to quantify temporal and spatial dynamics of land cover changes. The overall accuracies, Kappa coefficients, and average annual increase rate or decrease rate of land cover classes were calculated to assess classification results and changing rate of land cover. The analysis revealed that major trends of the land cover changes were the notable growth of the oasis and the reduction of the desert-oasis ecotone, which led to accelerated soil salinization and plant deterioration within the oasis. These changes were mainly attributed to the intensified human activities. The results indicated that the newly created agricultural land along the margins of the Hotan oasis could result in more potential areas of land degradation. If no effective measures are taken against the deterioration of the oasis environment, soil erosion caused by land cover change may proceed. The trend of desert moving further inward and the shrinking of the ecotone may lead to potential risks to the eco-environment of the Hotan oasis over the next decades.
Zhu, Zhe; Fu, Yingchun; Woodcock, Curtis; Olofsson, Pontus; Vogelmann, James; Holden, Christopher; Wang, Min; Dai, Shu; Yu, Yang
2016-01-01
An assessment of the consistency of surface reflectance from Landsat 8 with past Landsat sensors indicates biases in the visible bands of Landsat 8, especially the blue band. Landsat 8 NDVI values were found to have a larger bias than the EVI values; therefore, EVI was used in the analysis of greenness trends for Guangzhou. In spite of massive amounts of development in Guangzhou from 2000 to 2014, greenness was found to increase, mostly as a result of gradual change. Comparison of the greening magnitudes estimated from the approach presented here and a Simple Linear Trend (SLT) method indicated large differences for certain time intervals as the SLT method does not include consideration for abrupt land cover changes. Overall, this analysis demonstrates the importance of considering land cover change when analyzing trends in greenness from satellite time series in areas where land cover change is common.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ke, Yinghai; Coleman, Andre M.; Diefenderfer, Heida L.
We delineated 8 watersheds contributing to previously defined river reaches within the 1,468-km2 historical floodplain of the tidally influenced lower Columbia River and estuary. We assessed land-cover change at the watershed, reach, and restoration site scales by reclassifying remote-sensing data from the National Oceanic and Atmospheric Administration Coastal Change Analysis Program’s land cover/land change product into forest, wetland, and urban categories. The analysis showed a 198.3 km2 loss of forest cover during the first 6 years of the Columbia Estuary Ecosystem Restoration Program, 2001–2006. Total measured urbanization in the contributing watersheds of the estuary during the full 1996-2006 change analysismore » period was 48.4 km2. Trends in forest gain/loss and urbanization differed between watersheds. Wetland gains and losses were within the margin of error of the satellite imagery analysis. No significant land cover change was measured at restoration sites, although it was visible in aerial imagery, therefore, the 30-m land-cover product may not be appropriate for assessment of early-stage wetland restoration. These findings suggest that floodplain restoration sites in reaches downstream of watersheds with decreasing forest cover will be subject to increased sediment loads, and those downstream of urbanization will experience effects of increased impervious surfaces on hydrologic processes.« less
Effect of land cover change on snow free surface albedo across the continental United States
Wickham, J.; Nash, M.S.; Barnes, Christopher A.
2016-01-01
Land cover changes (e.g., forest to grassland) affect albedo, and changes in albedo can influence radiative forcing (warming, cooling). We empirically tested albedo response to land cover change for 130 locations across the continental United States using high resolution (30 m-×-30 m) land cover change data and moderate resolution (~ 500 m-×-500 m) albedo data. The land cover change data spanned 10 years (2001 − 2011) and the albedo data included observations every eight days for 13 years (2001 − 2013). Empirical testing was based on autoregressive time series analysis of snow free albedo for verified locations of land cover change. Approximately one-third of the autoregressive analyses for woody to herbaceous or forest to shrub change classes were not significant, indicating that albedo did not change significantly as a result of land cover change at these locations. In addition, ~ 80% of mean differences in albedo arising from land cover change were less than ± 0.02, a nominal benchmark for precision of albedo measurements that is related to significant changes in radiative forcing. Under snow free conditions, we found that land cover change does not guarantee a significant albedo response, and that the differences in mean albedo response for the majority of land cover change locations were small.
Land change variability and human-environment dynamics in the United States Great Plains
Drummond, M.A.; Auch, Roger F.; Karstensen, K.A.; Sayler, K. L.; Taylor, Janis L.; Loveland, Thomas R.
2012-01-01
Land use and land cover changes have complex linkages to climate variability and change, biophysical resources, and socioeconomic driving forces. To assess these land change dynamics and their causes in the Great Plains, we compare and contrast contemporary changes across 16 ecoregions using Landsat satellite data and statistical analysis. Large-area change analysis of agricultural regions is often hampered by change detection error and the tendency for land conversions to occur at the local-scale. To facilitate a regional-scale analysis, a statistical sampling design of randomly selected 10 km × 10 km blocks is used to efficiently identify the types and rates of land conversions for four time intervals between 1973 and 2000, stratified by relatively homogenous ecoregions. Nearly 8% of the overall Great Plains region underwent land-use and land-cover change during the study period, with a substantial amount of ecoregion variability that ranged from less than 2% to greater than 13%. Agricultural land cover declined by more than 2% overall, with variability contingent on the differential characteristics of regional human–environment systems. A large part of the Great Plains is in relatively stable land cover. However, other land systems with significant biophysical and climate limitations for agriculture have high rates of land change when pushed by economic, policy, technology, or climate forcing factors. The results indicate the regionally based potential for land cover to persist or fluctuate as land uses are adapted to spatially and temporally variable forcing factors.
Land-Cover Trends of the Sierra Nevada Ecoregion, 1973-2000
Raumann, Christian G.; Soulard, Christopher E.
2007-01-01
The U.S. Geological Survey has developed and is implementing the Land Cover Trends project to estimate and describe the temporal and spatial distribution and variability of contemporary land-use and land-cover change in the United States. As part of the Land Cover Trends project, the purpose of this study was to assess land-use/land-cover change in the Sierra Nevada ecoregion for the period 1973 to 2000 using a probability sampling technique and satellite imagery. We randomly selected 36 100-km2 sample blocks to derive thematic images of land-use/land-cover for five dates of Landsat imagery (1973, 1980, 1986, 1992, 2000). We visually interpreted as many as 11 land-use/land-cover classes using a 60-meter minimum mapping unit from the five dates of imagery yielding four periods for analysis. Change-detection results from post-classification comparison of our mapped data showed that landscape disturbance from fire was the dominant change from 1973-2000. The second most-common change was forest disturbance resulting from harvest of timber resources by way of clear-cutting. The rates of forest regeneration from temporary fire and harvest disturbances coincided with the rates of disturbance from the previous period. Relatively minor landscape changes were caused by new development and reservoir drawdown. Multiple linear regression analysis suggests that land ownership and the proportion of forest and developed cover types were significant determinants of the likelihood of direct human-induced change occurring in sampling units. Driving forces of change include land ownership, land management such as fire suppression policy, and demand for natural resources.
Giri, Chandra; Defourny, Pierre; Shrestha, Surendra
2003-01-01
Land use/land cover change, particularly that of tropical deforestation and forest degradation, has been occurring at an unprecedented rate and scale in Southeast Asia. The rapid rate of economic development, demographics and poverty are believed to be the underlying forces responsible for the change. Accurate and up-to-date information to support the above statement is, however, not available. The available data, if any, are outdated and are not comparable for various technical reasons. Time series analysis of land cover change and the identification of the driving forces responsible for these changes are needed for the sustainable management of natural resources and also for projecting future land cover trajectories. We analysed the multi-temporal and multi-seasonal NOAA Advanced Very High Resolution Radiometer (AVHRR) satellite data of 1985/86 and 1992 to (1) prepare historical land cover maps and (2) to identify areas undergoing major land cover transformations (called ‘hot spots’). The identified ‘hot spot’ areas were investigated in detail using high-resolution satellite sensor data such as Landsat and SPOT supplemented by intensive field surveys. Shifting cultivation, intensification of agricultural activities and change of cropping patterns, and conversion of forest to agricultural land were found to be the principal reasons for land use/land cover change in the Oudomxay province of Lao PDR, the Mekong Delta of Vietnam and the Loei province of Thailand, respectively. Moreover, typical land use/land cover change patterns of the ‘hot spot’ areas were also examined. In addition, we developed an operational methodology for land use/land cover change analysis at the national level with the help of national remote sensing institutions.
ASSESSING ACCURACY OF NET CHANGE DERIVED FROM LAND COVER MAPS
Net change derived from land-cover maps provides important descriptive information for environmental monitoring and is often used as an input or explanatory variable in environmental models. The sampling design and analysis for assessing net change accuracy differ from traditio...
An analysis of human-induced land transformations in the San Francisco Bay/Sacramento area
Kirtland, David A.; Gaydos, L.J.; Clarke, Keith; DeCola, Lee; Acevedo, William; Bell, Cindy
1994-01-01
Part of the U.S. Geological Survey's Global Change Research Program involvesstudying the area from the Pacific Ocean to the Sierra foothills to enhance understanding ofthe role that human activities play in global change. The study investigates the ways thathumans transform the land and the effects that changing the landscape may have on regionaland global systems. To accomplish this research, scientists are compiling records ofhistorical transformations in the region's land cover over the last 140 years, developing asimulation model to predict land cover change, and assembling a digital data set to analyzeand describe land transformations. The historical data regarding urban growth focusattention on the significant change the region underwent from 1850 to 1990. Animation isused to visualize a time series of the change in land cover. The historical change is beingused to calibrate a prototype cellular automata model, developed to predict changes in urbanland cover 100 years into the future. Future urban growth scenarios will be developed foranalyzing possible human-induced impacts on land cover at a regional scale. These data aidin documenting and understanding human-induced land transformations from both historical andpredictive perspectives. A descriptive analysis of the region is used to investigate therelationships among data characteristic of the region. These data consist of multilayertopography, climate, vegetation, and population data for a 256-km2 region of centralCalifornia. A variety of multivariate analysis tools are used to integrate the data inraster format from map contours, interpolated climate observations, satellite observations,and population estimates.
Modeling Land Use/Cover Changes in an African Rural Landscape
NASA Astrophysics Data System (ADS)
Kamusoko, C.; Aniya, M.
2006-12-01
Land use/cover changes are analyzed in the Bindura district of Zimbabwe, Africa through the integration of data from a time series of Landsat imagery (1973, 1989 and 2000), a household survey and GIS coverages. We employed a hybrid supervised/unsupervised classification approach to generate land use/cover maps from which landscape metrics were calculated. Population and other household variables were derived from a sample of surveyed villages, while road accessibility and slope were obtained from topographic maps and digital elevation model, respectively. Markov-cellular automata modeling approach that incorporates Markov chain analysis, cellular automata and multi-criteria evaluation (MCE) / multi-objective allocation (MOLA) procedures was used to simulate land use/cover changes. A GIS-based MCE technique computed transition potential maps, whereas transition areas were derived from the 1973-2000 land use/cover maps using the Markov chain analysis. A 5 x 5 cellular automata filter was used to develop a spatially explicit contiguity- weighting factor to change the cells based on its previous state and those of its neighbors, while MOLA resolved land use/cover class allocation conflicts. The kappa index of agreement was used for model validation. Observed trends in land use/cover changes indicate that deforestation and the encroachment of cultivation in woodland areas is a continuous trend in the study area. This suggests that economic activities driven by agricultural expansion were the main causes of landscape fragmentation, leading to landscape degradation. Rigorous calibration of transition potential maps done by a MCE algorithm and Markovian transition probabilities produced accurate inputs for the simulation of land use/cover changes. Overall standard kappa index of agreement ranged from 0.73 to 0.83, which is sufficient for simulating land use/cover changes in the study area. Land use/cover simulations under the 1989 and 2000 scenario indicated further landscape degradation in the rural areas of the Bindura district. Keywords: Zimbabwe, land use/cover changes, landscape fragmentation, GIS, land use/cover change modeling, multi-criteria evaluation/multi-objective allocation procedures, Markov-cellular automata
Mwalusepo, Sizah; Muli, Eliud; Faki, Asha; Raina, Suresh
2017-04-01
Land use and land cover changes will continue to affect resilient human communities and ecosystems as a result of climate change. However, an assessment of land use and land cover changes over time in Indian Ocean Islands is less documented. The land use/cover data changes over 10 years at smaller geographical scale across Unguja Island in Zanzibar were analyzed. Downscaling of the data was obtained from SERVIR through partnership with Kenya-based Regional Centre for Mapping of Resources for Development (RCMRD) database (http://www.servirglobal.net), and clipped down in ArcMap (Version 10.1) to Unguja Island. SERVIR and RCMRD Land Cover Dataset are mainly 30 m multispectral images include Landsat TM and ETM+Multispectral Images. Landscape ecology Statistics tool (LecoS) was used to analysis the land use and land cover changes. The data provide information on the status of the land use and land cover changes along the Unguja Island in Zanzibar. The data is of great significance to the future research on global change.
NASA Astrophysics Data System (ADS)
Biswas, T.; Maus, P.; Megown, K.
2011-12-01
The U.S. Forest Service (USFS) provided technical support to the Resource Information Management System (RIMS) unit of the Forest Department (FD) of Bangladesh in developing a method to monitor changes within the Sundarbans Reserve Forest using remote sensing and GIS technology to meet the Reducing Emissions from Deforestation and Degradation (REDD+) initiatives within Bangladesh. It included comparing the simple image differencing method with the Z-score outlier change detection method to examine changes within the mangroves of Bangladesh. Landsat data from three time periods (1989, 1999, 2009) were used to quantify change within four canopy cover classes (High, Medium, Low, and Very Low) within Sundarbans. The Z-score change analysis and image differencing was done for all the 6 reflective bands obtained from Landsat and two spectral indices NDVI and NDMI, derived from these bands for each year. Our results indicated very subtle changes in the mangrove forest within the past twenty years and the Z-score analysis was found to be more useful in capturing these subtle changes than the simple image difference method. Percent change in Z-score of NDVI provided the most meaningful index of vegetation change. It was used to summarize change for the entire study area by pixel, by canopy cover classes and the management compartment during this analysis. Our analysis showed less than 5% overall change in area within the mangroves for the entire study period. Percent change in forest canopy cover reduced from 4% in 1989-99 to 2% by 1999-2009 indicating an increase in forest canopy cover. Percent change in NDVI Z-score of each pixel was used to compute the overall percent change in z-score within the entire study area, mean percent change within each canopy cover class and management compartments from 1989 to 1999 and from 1999 to 2009. The above analysis provided insight to the spatial distribution of percent change in NDVI between the study periods and helped in identifying potential area for management intervention. The mean distribution of change from both study periods was observed within ± 20% SD.Our results were in agreement with the independent field study conducted by the US Forest Service earlier the same year for biomass and carbon stock estimation. The 10m field plots that showed a decline in carbon stock between 1995 and 2010 overall coincided with the compartments or region that showed a decline in forest canopy cover between 1999 and 2009 from the present analysis. These results led us to believe that the Z-score analysis can be a potential quantitatively rigorous tool to quantify change in ecosystems that are mostly stable and do not undergo drastic land use or land cover change. The field and remote sensing study together provided important scientific information and direction for future management of the forest resources, baseline information for long term monitoring of the forest, and identifying potential REDD+ Carbon financing projects in Sundarbans, as well as other potential REDD+ sites within forested area of Bangladesh. Given the rising concern and interest in REDD+ initiative we consider the Z-score analysis to be a potential tool in monitoring and providing a quick spatial assessment of change using remote sensing technology.
Many empirical studies have established the significant relationship between climate and runoff: climate change may potentially increase or decrease the surface runoff. Increased surface runoff can also increase the risk of soil erosion. Land cover change can alter rainfall-runof...
The effects of changing land cover on streamflow simulation in Puerto Rico
Van Beusekom, Ashley E.; Hay, Lauren E.; Viger, Roland; Gould, William A.; Collazo, Jaime; Henareh Khalyani, Azad
2014-01-01
This study quantitatively explores whether land cover changes have a substantive impact on simulated streamflow within the tropical island setting of Puerto Rico. The Precipitation Runoff Modeling System (PRMS) was used to compare streamflow simulations based on five static parameterizations of land cover with those based on dynamically varying parameters derived from four land cover scenes for the period 1953-2012. The PRMS simulations based on static land cover illustrated consistent differences in simulated streamflow across the island. It was determined that the scale of the analysis makes a difference: large regions with localized areas that have undergone dramatic land cover change may show negligible difference in total streamflow, but streamflow simulations using dynamic land cover parameters for a highly altered subwatershed clearly demonstrate the effects of changing land cover on simulated streamflow. Incorporating dynamic parameterization in these highly altered watersheds can reduce the predictive uncertainty in simulations of streamflow using PRMS. Hydrologic models that do not consider the projected changes in land cover may be inadequate for water resource management planning for future conditions.
NASA Astrophysics Data System (ADS)
Zhang, M.; Liu, S.
2017-12-01
Despite extensive studies on hydrological responses to forest cover change in small watersheds, the hydrological responses to forest change and associated mechanisms across multiple spatial scales have not been fully understood. This review thus examined about 312 watersheds worldwide to provide a generalized framework to evaluate hydrological responses to forest cover change and to identify the contribution of spatial scale, climate, forest type and hydrological regime in determining the intensity of forest change related hydrological responses in small (<1000 km2) and large watersheds (≥1000 km2). Key findings include: 1) the increase in annual runoff associated with forest cover loss is statistically significant at multiple spatial scales whereas the effect of forest cover gain is statistically inconsistent; 2) the sensitivity of annual runoff to forest cover change tends to attenuate as watershed size increases only in large watersheds; 3) annual runoff is more sensitive to forest cover change in water-limited watersheds than in energy-limited watersheds across all spatial scales; and 4) small mixed forest-dominated watersheds or large snow-dominated watersheds are more hydrologically resilient to forest cover change. These findings improve the understanding of hydrological response to forest cover change at different spatial scales and provide a scientific underpinning to future watershed management in the context of climate change and increasing anthropogenic disturbances.
Monitoring Urban Greenness Dynamics Using Multiple Endmember Spectral Mixture Analysis
Gan, Muye; Deng, Jinsong; Zheng, Xinyu; Hong, Yang; Wang, Ke
2014-01-01
Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents’ quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development. PMID:25375176
NASA Astrophysics Data System (ADS)
Marko, K.; Zulkarnain, F.; Kusratmoko, E.
2016-11-01
Land cover changes particular in urban catchment area has been rapidly occur. Land cover changes occur as a result of increasing demand for built-up area. Various kinds of environmental and hydrological problems e.g. floods and urban heat island can happen if the changes are uncontrolled. This study aims to predict land cover changes using coupling of Markov chains and cellular automata. One of the most rapid land cover changes is occurs at upper Ci Leungsi catchment area that located near Bekasi City and Jakarta Metropolitan Area. Markov chains has a good ability to predict the probability of change statistically while cellular automata believed as a powerful method in reading the spatial patterns of change. Temporal land cover data was obtained by remote sensing satellite imageries. In addition, this study also used multi-criteria analysis to determine which driving factor that could stimulate the changes such as proximity, elevation, and slope. Coupling of these two methods could give better prediction model rather than just using it separately. The prediction model was validated using existing 2015 land cover data and shown a satisfactory kappa coefficient. The most significant increasing land cover is built-up area from 24% to 53%.
Nigatu Wondrade; Dick, Øystein B; Tveite, Havard
2014-03-01
Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very peculiar in that the area of Lake Hawassa increased from 91.9 km(2) in 1973 to 95.2 km(2) in 2011, while that of Lake Cheleleka whose area was 11.3 km(2) in 1973 totally vanished in 2011 and transformed into mud-flat and grass dominated swamp. The "change and no change" analysis revealed that more than one third (548.0 km(2)) of the total area was exposed to change between 1973 and 2011. This study was useful in identifying the major land cover changes, and the analysis pursued provided a valuable insight into the ongoing changes in the area under investigation.
Euskirchen, E.S.; McGuire, A.D.; Chapin, F.S.
2007-01-01
The warming associated with changes in snow cover in northern high-latitude terrestrial regions represents an important energy feedback to the climate system. Here, we simulate snow cover-climate feedbacks (i.e. changes in snow cover on atmospheric heating) across the Pan-arctic over two distinct warming periods during the 20th century, 1910-1940 and 1970-2000. We offer evidence that increases in snow cover-climate feedbacks during 1970-2000 were nearly three times larger than during 1910-1940 because the recent snow-cover change occurred in spring, when radiation load is highest, rather than in autumn. Based on linear regression analysis, we also detected a greater sensitivity of snow cover-climate feedbacks to temperature trends during the more recent time period. Pan-arctic vegetation types differed substantially in snow cover-climate feedbacks. Those with a high seasonal contrast in albedo, such as tundra, showed much larger changes in atmospheric heating than did those with a low seasonal contrast in albedo, such as forests, even if the changes in snow-cover duration were similar across the vegetation types. These changes in energy exchange warrant careful consideration in studies of climate change, particularly with respect to associated shifts in vegetation between forests, grasslands, and tundra. ?? 2007 Blackwell Publishing Ltd.
NASA Astrophysics Data System (ADS)
Liu, Tingxiang; Zhang, Shuwen; Yu, Lingxue; Bu, Kun; Yang, Jiuchun; Chang, Liping
2017-05-01
The Northeast China is one of typical regions experiencing intensive human activities within short time worldwide. Particularly, as the significant changes of agriculture land and forest, typical characteristics of pattern and process of agroforestry ecotone change formed in recent decades. The intensive land use change of agroforestry ecotone has made significant change for regional land cover, which had significant impact on the regional climate system elements and the interactions among them. This paper took agroforestry ecotone of Nenjiang River Basin in China as study region and simulated temperature change based on land cover change from 1950s to 1978 and from 1978 to 2010. The analysis of temperature difference sensitivity to land cover change based on Weather Research and Forecasting (WRF) model showed that the land cover change from 1950s to 1978 induced warming effect over all the study area, including the change of grassland to agriculture land, grassland to deciduous broad-leaved forest, and deciduous broad-leaved forest to shrub land. The land cover change from 1978 to 2010 induced cooling effect over all the study area, including the change of deciduous broad-leaved forest to agriculture land, grassland to agriculture land, shrub land to agriculture land, and deciduous broad-leaved forest to grassland. In addition, the warming and cooling effect of land cover change was more significant in the region scale than specific land cover change area.
High dimensional land cover inference using remotely sensed modis data
NASA Astrophysics Data System (ADS)
Glanz, Hunter S.
Image segmentation persists as a major statistical problem, with the volume and complexity of data expanding alongside new technologies. Land cover classification, one of the most studied problems in Remote Sensing, provides an important example of image segmentation whose needs transcend the choice of a particular classification method. That is, the challenges associated with land cover classification pervade the analysis process from data pre-processing to estimation of a final land cover map. Many of the same challenges also plague the task of land cover change detection. Multispectral, multitemporal data with inherent spatial relationships have hardly received adequate treatment due to the large size of the data and the presence of missing values. In this work we propose a novel, concerted application of methods which provide a unified way to estimate model parameters, impute missing data, reduce dimensionality, classify land cover, and detect land cover changes. This comprehensive analysis adopts a Bayesian approach which incorporates prior knowledge to improve the interpretability, efficiency, and versatility of land cover classification and change detection. We explore a parsimonious, parametric model that allows for a natural application of principal components analysis to isolate important spectral characteristics while preserving temporal information. Moreover, it allows us to impute missing data and estimate parameters via expectation-maximization (EM). A significant byproduct of our framework includes a suite of training data assessment tools. To classify land cover, we employ a spanning tree approximation to a lattice Potts prior to incorporate spatial relationships in a judicious way and more efficiently access the posterior distribution of pixel labels. We then achieve exact inference of the labels via the centroid estimator. To detect land cover changes, we develop a new EM algorithm based on the same parametric model. We perform simulation studies to validate our models and methods, and conduct an extensive continental scale case study using MODIS data. The results show that we successfully classify land cover and recover the spatial patterns present in large scale data. Application of our change point method to an area in the Amazon successfully identifies the progression of deforestation through portions of the region.
Vegetation change in the American West has been the subject of much concern and controversy throughout the twentieth century. Over the years, a considerable number and variety of 'claims have been made regarding cause related to changes in land cover. The evidence for vegetat...
NASA Astrophysics Data System (ADS)
Akay, A. E.; Gencal, B.; Taş, İ.
2017-11-01
This short paper aims to detect spatiotemporal detection of land use/land cover change within Karacabey Flooded Forest region. Change detection analysis applied to Landsat 5 TM images representing July 2000 and a Landsat 8 OLI representing June 2017. Various image processing tools were implemented using ERDAS 9.2, ArcGIS 10.4.1, and ENVI programs to conduct spatiotemporal change detection over these two images such as band selection, corrections, subset, classification, recoding, accuracy assessment, and change detection analysis. Image classification revealed that there are five significant land use/land cover types, including forest, flooded forest, swamp, water, and other lands (i.e. agriculture, sand, roads, settlement, and open areas). The results indicated that there was increase in flooded forest, water, and other lands, while the cover of forest and swamp decreased.
Land-Cover Change in the East Central Texas Plains, 1973-2000
Karstensen, Krista A.
2009-01-01
Project Background: The Geographic Analysis and Monitoring (GAM) Program of the U.S. Geological Survey (USGS) Land Cover Trends project is focused on understanding the rates, trends, causes, and consequences of contemporary U.S. land-use and land-cover change. The objectives of the study are to: (1) develop a comprehensive methodology for using sampling and change analysis techniques and Landsat Multispectral Scanner (MSS) and Thematic Mapper (TM) data for measuring regional land-cover change across the United States, (2) characterize the types, rates and temporal variability of change for a 30-year period, (3) document regional driving forces and consequences of change, and (4) prepare a national synthesis of land-cover change (Loveland and others, 1999). Using the 1999 Environmental Protection Agency (EPA) Level III ecoregions derived from Omernik (1987) as the geographic framework, geospatial data collected between 1973 and 2000 were processed and analyzed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000, and 1973-2000. General land-cover classes such as water, developed, grassland/shrubland, and agriculture for these periods were interpreted from Landsat MSS, TM, and Enhanced Thematic Mapper Plus imagery to categorize land-cover change and evaluate using a modified Anderson Land-Use Land-Cover Classification System for image interpretation. The interpretation of these land-cover classes complement the program objective of looking at land-use change with cover serving as a surrogate for land use. The land-cover change rates are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change for the five time periods previously mentioned. Additionally, historical aerial photographs from similar timeframes and other ancillary data such as census statistics and published literature are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. For example, the scalar statistics can show the spatial extent of change per cover type with time, as well as the land-cover transformations from one land-cover type to another type occurring with time. Field data of the sample blocks include direct measurements of land cover, particularly ground-survey data collected for training and validation of image classifications (Loveland and others, 2002). The field experience allows for additional observations of the character and condition of the landscape, assistance in sample block interpretation, ground truthing of Landsat imagery, and helps determine the driving forces of change identified in an ecoregion. Management and maintenance of field data, beyond initial use for training and validation of image classifications, is important as improved methods for image classification are developed, and as present-day data become part of the historical legacy for which studies of land-cover change in the future will depend (Loveland and others, 2002). The results illustrate that there is no single profile of land-cover change; instead, there is significant geographic variability that results from land uses within ecoregions continuously adapting to the resource potential created by various environmental, technological, and socioeconomic factors.
Slonecker, E. Terrence; Milheim, Lesley E.; Claggett, Peter
2009-01-01
Landscape indicators, derived from land-use and land-cover data, hydrology, nitrate deposition, and elevation data, were used by Jones and others (2001a) to calculate the ecological consequences of land-cover change. Nitrate loading and physical bird habitat were modeled from 1973 and 1992 land-cover and other spatial data for the Mid-Atlantic region. Utilizing the same methods, this study extends the analysis another decade with the use of the 2001 National Land Cover Dataset. Land-cover statistics and trends are calculated for three time periods: 1973-1992, 1992-2001 and 1973-2001. In addition, high-resolution aerial photographs (1 meter or better ground-sample distance) were acquired and analyzed for thirteen pairs of adjacent USGS 7.5 minute quadrangle maps in areas where distinct positive or negative changes to nitrogen loading and bird habitat were previously calculated. During the entire 30 year period, the data show that there was extensive loss of agriculture and forest area and a major increase in urban land-cover classes. However, the majority of the conversion of other classes to urban occurred during the 1992-2001 period. During the 1973-1992 period, there was only moderate increase in urban area, while there was an inverse relationship between agricultural change and forest change. In general, forest gain and agricultural loss was found in areas of improving landscape indicators, and forest loss and agricultural gain was found to occur in areas of declining indicators related to habitat and nitrogen loadings, which was generally confirmed by the aerial photographic analysis. In terms of the specific model results, bird habitat, which is mainly related to the extent of forest cover, declined overall with forest extent, but was also affected more in the decline of habitat quality. Nitrate loading, which is mainly related to agricultural land cover actually improved from 1992-2001, and in the overall study, mainly due to the conversion of agriculture to forests and urban. The high-resolution imagery analysis was significant in that it confirmed, at a very local level, the specific land-cover changes that were driving the landscape metrics and model results that were calculated from moderate resolution land-cover data and models. These were generally subtle changes in patch size of agriculture, forest, and urban areas, but had substantial effects on bird habitat and nitrogen loadings. This analysis of high-resolution imagery demonstrates and confirms the important ability of moderate-resolution land-cover data to capture significant landscape-level activity that is directly related to specific metrics of ecological significance. It also demonstrates consistent landscape-scale relationships between data derived from high-resolution, moderate-resolution and landscape-model sources. Finally, many of the areas of improvement and decline in bird habitat and nitrogen loadings appear to be potentially regional in nature and likely reflect some local trend in landscape activity. Although the use of ecoregions as sampling units has been criticized in recent years, these results show that basic changes in Level 1 land-cover categories, such as forest and agriculture, may still reflect ecoregional patterns and considerations at some scale of mapping and analysis. This is a potentially important area for future landscape-indicator research. This and other follow-on research opportunities are discussed.
Quantifying Structural and Compositional Changes in Forest Cover in NW Yunnan, China
NASA Astrophysics Data System (ADS)
Hakkenberg, C.
2012-12-01
NW Yunnan, China is a region renowned for high levels of biodiversity, endemism and genetically distinct refugial plant populations. It is also a focal area for China's national reforestation efforts like the Natural Forest Protection Program (NFPP), intended to control erosion in the Upper Yangtze watershed. As part of a larger project to investigate the role of reforestation programs in facilitating the emergence of increasingly species-rich forest communities on a previously degraded and depauperate land mosaic in montane SW China, this study uses a series of Landsat TM images to quantify the spatial pattern and rate of structural and compositional change in forests recovering from medium to large-scale disturbances in the area over the past 25 years. Beyond the fundamental need to assess the outcomes of one of the world's largest reforestation programs, this research offers approaches to confronting two critical methodological issues: (1) techniques for characterizing subtle changes in the nature of vegetation cover, and (2) reducing change detection uncertainty due to persistent cloud cover and shadow. To address difficulties in accurately assessing the structure and composition of vegetative regrowth, a biophysical model was parameterized with over 300 ground-truthed canopy cover assessment points to determine pattern and rate of long-term vegetation changes. To combat pervasive shadow and cloud cover, an interactive generalized additive model (GAM) model based on topographic and spatial predictors was used to overcome some of the constraints of satellite image analysis in Himalayan regions characterized by extreme topography and extensive cloud cover during the summer monsoon. The change detection is assessed for accuracy using ground-truthed observations in a variety of forest cover types and topographic positions. Results indicate effectiveness in reducing the areal extent of unclassified regions and increasing total change detection accuracy. In addition to quantifying forest cover change in this section of NW Yunnan, the analysis attempts to qualify that change - distinguishing among distinct disturbance histories and post-recovery successional pathways.
NASA Astrophysics Data System (ADS)
Zomlot, Z.; Verbeiren, B.; Huysmans, M.; Batelaan, O.
2017-11-01
Land use/land cover (LULC) change is a consequence of human-induced global environmental change. It is also considered one of the major factors affecting groundwater recharge. Uncertainties and inconsistencies in LULC maps are one of the difficulties that LULC timeseries analysis face and which have a significant effect on hydrological impact analysis. Therefore, an accuracy assessment approach of LULC timeseries is needed for a more reliable hydrological analysis and prediction. The objective of this paper is to assess the impact of land use uncertainty and to improve the accuracy of a timeseries of CORINE (coordination of information on the environment) land cover maps by using a new approach of identifying spatial-temporal LULC change trajectories as a pre-processing tool. This ensures consistency of model input when dealing with land-use dynamics and as such improves the accuracy of land use maps and consequently groundwater recharge estimation. As a case study the impact of consistent land use changes from 1990 until 2013 on groundwater recharge for the Flanders-Brussels region is assessed. The change trajectory analysis successfully assigned a rational trajectory to 99% of all pixels. The methodology is shown to be powerful in correcting interpretation inconsistencies and overestimation errors in CORINE land cover maps. The overall kappa (cell-by-cell map comparison) improved from 0.6 to 0.8 and from 0.2 to 0.7 for forest and pasture land use classes respectively. The study shows that the inconsistencies in the land use maps introduce uncertainty in groundwater recharge estimation in a range of 10-30%. The analysis showed that during the period of 1990-2013 the LULC changes were mainly driven by urban expansion. The results show that the resolution at which the spatial analysis is performed is important; the recharge differences using original and corrected CORINE land cover maps increase considerably with increasing spatial resolution. This study indicates that improving consistency of land use map timeseries is of critical importance for assessing land use change and its environmental impact.
NASA Astrophysics Data System (ADS)
Surdu, C. M.; Duguay, C. R.; Brown, L. C.; Fernández Prieto, D.
2014-01-01
Air temperature and winter precipitation changes over the last five decades have impacted the timing, duration, and thickness of the ice cover on Arctic lakes as shown by recent studies. In the case of shallow tundra lakes, many of which are less than 3 m deep, warmer climate conditions could result in thinner ice covers and consequently, in a smaller fraction of lakes freezing to their bed in winter. However, these changes have not yet been comprehensively documented. The analysis of a 20 yr time series of European remote sensing satellite ERS-1/2 synthetic aperture radar (SAR) data and a numerical lake ice model were employed to determine the response of ice cover (thickness, freezing to the bed, and phenology) on shallow lakes of the North Slope of Alaska (NSA) to climate conditions over the last six decades. Given the large area covered by these lakes, changes in the regional climate and weather are related to regime shifts in the ice cover of the lakes. Analysis of available SAR data from 1991 to 2011, from a sub-region of the NSA near Barrow, shows a reduction in the fraction of lakes that freeze to the bed in late winter. This finding is in good agreement with the decrease in ice thickness simulated with the Canadian Lake Ice Model (CLIMo), a lower fraction of lakes frozen to the bed corresponding to a thinner ice cover. Observed changes of the ice cover show a trend toward increasing floating ice fractions from 1991 to 2011, with the greatest change occurring in April, when the grounded ice fraction declined by 22% (α = 0.01). Model results indicate a trend toward thinner ice covers by 18-22 cm (no-snow and 53% snow depth scenarios, α = 0.01) during the 1991-2011 period and by 21-38 cm (α = 0.001) from 1950 to 2011. The longer trend analysis (1950-2011) also shows a decrease in the ice cover duration by ~24 days consequent to later freeze-up dates by 5.9 days (α = 0.1) and earlier break-up dates by 17.7-18.6 days (α = 0.001).
Satellite Earth observation data to identify anthropogenic pressures in selected protected areas
NASA Astrophysics Data System (ADS)
Nagendra, Harini; Mairota, Paola; Marangi, Carmela; Lucas, Richard; Dimopoulos, Panayotis; Honrado, João Pradinho; Niphadkar, Madhura; Mücher, Caspar A.; Tomaselli, Valeria; Panitsa, Maria; Tarantino, Cristina; Manakos, Ioannis; Blonda, Palma
2015-05-01
Protected areas are experiencing increased levels of human pressure. To enable appropriate conservation action, it is critical to map and monitor changes in the type and extent of land cover/use and habitat classes, which can be related to human pressures over time. Satellite Earth observation (EO) data and techniques offer the opportunity to detect such changes. Yet association with field information and expert interpretation by ecologists is required to interpret, qualify and link these changes to human pressure. There is thus an urgent need to harmonize the technical background of experts in the field of EO data analysis with the terminology of ecologists, protected area management authorities and policy makers in order to provide meaningful, context-specific value-added EO products. This paper builds on the DPSIR framework, providing a terminology to relate the concepts of state, pressures, and drivers with the application of EO analysis. The type of pressure can be inferred through the detection of changes in state (i.e. changes in land cover and/or habitat type and/or condition). Four broad categories of changes in state are identified, i.e. land cover/habitat conversion, land cover/habitat modification, habitat fragmentation and changes in landscape connectivity, and changes in plant community structure. These categories of change in state can be mapped through EO analyses, with the goal of using expert judgement to relate changes in state to causal direct anthropogenic pressures. Drawing on expert knowledge, a set of protected areas located in diverse socio-ecological contexts and subject to a variety of pressures are analysed to (a) link the four categories of changes in state of land cover/habitats to the drivers (anthropogenic pressure), as relevant to specific target land cover and habitat classes; (b) identify (for pressure mapping) the most appropriate spatial and temporal EO data sources as well as interpretations from ecologists and field data useful in connection with EO data analysis. We provide detailed examples for two protected areas, demonstrating the use of EO data for detection of land cover/habitat change, coupled with expert interpretation to relate such change to specific anthropogenic pressures. We conclude with a discussion of the limitations and feasibility of using EO data and techniques to identify anthropogenic pressures, suggesting additional research efforts required in this direction.
NASA Technical Reports Server (NTRS)
Roberts, Dar A.; Chadwick, Oliver A.; Batista, Getulio T.
2003-01-01
LBA research from the first phase of LBA focused on three broad categories: 1) mapping land cover and quantifying rates of change, persistence of pasture, and area of recovering forest; 2) evaluating the role of environmental factors and land-use history on soil biogeochemistry; and 3) quantifying the natural and human controls on stream nutrient concentrations. The focus of the research was regional, concentrating primarily in the state of RondBnia, but also included land-cover mapping in the vicinity of Maraba, Para, and Manaus, Amazonas. Remote sensing analysis utilized Landsat Thematic Mapper (TM) and Multispectral Scanner (MS S) data to map historical patterns of land-cover change. Specific questions addressed by the remote sensing component of the research included: 1) what is the areal extent of dominant land-cover classes? 2) what are the rates of change of dominant land cover through processes of deforestation, disturbance and regeneration? and 3) what are the dynamic properties of each class that characterize temporal variability, duration, and frequency of repeat disturbance? Biogeochemical analysis focused on natural variability and impacts of land-use/land-cover changes on soil and stream biogeochemical properties at the regional scale. An emphasis was given to specific soil properties considered to be primary limiting factors regionally, including phosphorus, nitrogen, base cations and cation-exchange properties. Stream sampling emphasized the relative effects of the rates and timing of land-cover change on stream nutrients, demonstrating that vegetation conversion alone does not impact nutrients as much as subsequent land use and urbanization.
LaFontaine, Jacob H.; Hay, Lauren E.; Viger, Roland; Regan, R. Steve; Markstrom, Steven
2015-01-01
The hydrologic response to statistically downscaled general circulation model simulations of daily surface climate and land cover through 2099 was assessed for the Apalachicola-Chattahoochee-Flint River Basin located in the southeastern United States. Projections of climate, urbanization, vegetation, and surface-depression storage capacity were used as inputs to the Precipitation-Runoff Modeling System to simulate projected impacts on hydrologic response. Surface runoff substantially increased when land cover change was applied. However, once the surface depression storage was added to mitigate the land cover change and increases of surface runoff (due to urbanization), the groundwater flow component then increased. For hydrologic studies that include projections of land cover change (urbanization in particular), any analysis of runoff beyond the change in total runoff should include effects of stormwater management practices as these features affect flow timing and magnitude and may be useful in mitigating land cover change impacts on streamflow. Potential changes in water availability and how biota may respond to changes in flow regime in response to climate and land cover change may prove challenging for managers attempting to balance the needs of future development and the environment. However, these models are still useful for assessing the relative impacts of climate and land cover change and for evaluating tradeoffs when managing to mitigate different stressors.
Image-based change estimation for land cover and land use monitoring
Jeremy Webb; C. Kenneth Brewer; Nicholas Daniels; Chris Maderia; Randy Hamilton; Mark Finco; Kevin A. Megown; Andrew J. Lister
2012-01-01
The Image-based Change Estimation (ICE) project resulted from the need to provide estimates and information for land cover and land use change over large areas. The procedure uses Forest Inventory and Analysis (FIA) plot locations interpreted using two different dates of imagery from the National Agriculture Imagery Program (NAIP). In order to determine a suitable...
Synergy of Optical and SAR Data for Mapping and Monitoring Mangroves
NASA Astrophysics Data System (ADS)
Monzon, A. K.; Reyes, S. R.; Veridiano, R. K.; Tumaneng, R.; De Alban, J. D.
2016-06-01
Quantitative information on mangrove cover extents is essential in producing relevant resource management plans and conservation strategies. In the Philippines, mangrove rehabilitation was made a priority in relation to disaster risk response and mitigation following the calamities in the coastal communities during typhoon Haiyan/Yolanda; hence, baseline information on the extent of remaining mangrove cover was essential for effective site interventions. Although mangrove cover maps for the country already exists, analysis of mangrove cover changes were limited to the application of fixed annual deforestation rates due to the challenge of acquiring consistent temporal cloud-free optical satellite data over large landscapes. This study presents an initial analysis of SAR and optical imagery combined with field-based observations for detecting mangrove cover extent and changes through a straightforward graphical approach. The analysis is part of a larger study evaluating the synergistic use of time-series L-band SAR and optical data for mapping and monitoring of mangroves. Image segmentation was implemented on the 25-meter ALOS/PALSAR image mosaics, in which the generated objects were subjected to statistical analysis using the software R. In combination with selected Landsat bands, the class statistics from the image bands were used to generate decision trees and thresholds for the hierarchical image classification. The results were compared with global mangrove cover dataset and validated using collected ground truth data. This study developed an integrated replicable approach for analyzing future radar and optical datasets, essential in national level mangrove cover change monitoring and assessment for long-term conservation targets and strategies.
Perspectives of Maine Forest Cover Change from Landsat Imagery and Forest Inventory Analysis (FIA)
Steven Sader; Michael Hoppus; Jacob Metzler; Suming Jin
2005-01-01
A forest change detection map was developed to document forest gains and losses during the decade of the 1990s. The effectiveness of the Landsat imagery and methods for detecting Maine forest cover change are indicated by the good accuracy assessment results: forest-no change, forest loss, and forest gain accuracy were 90, 88, and 92% respectively, and the good...
NASA Astrophysics Data System (ADS)
Badjana, Hèou Maléki; Helmschrot, Jörg; Selsam, Peter; Wala, Kpérkouma; Flügel, Wolfgang-Albert; Afouda, Abel; Akpagana, Koffi
2015-10-01
In this study, land cover changes between 1972 and 2013 were investigated in the Binah River watershed (North of Togo and Benin) using remote sensing and geographic information system technologies. Multitemporal satellite images—Landsat MSS (1972), TM (1987), and OLI-TIRS (2013)—were processed using object-based image analysis and post-classification comparison methods including landscape metrics and changes trajectories analysis. Land cover maps referring to five main land cover classes, namely, agricultural land, forest land, savannah, settlements, and water bodies, were produced for each acquisition date. The overall accuracies were 76.64% (1972), 83.52% (1987), and 88.84% (2013) with respective Kappa statistics of 0.69, 0.78, and 0.86. The assessment of the spatiotemporal pattern of land cover changes indicates that savannah, the main vegetation type, has undergone the most dominant change, decreasing from 67% of the basin area in 1972 to 56% in 1987 and 33% in 2013. At the same time, agricultural land has significantly increased from 15% in 1972 to 24% in 1987 and 43% in 2013, while some proportions of agricultural land were converted to savannah relating to fallow agriculture. In total, more than 55% of the landscape experienced changes between 1972 and 2013. These changes are primarily due to human activities and population growth. In addition, agricultural activities significantly contributed to the increase in the number of patches, degree of division, and splitting index of forest and savannah vegetations and the decrease in their effective mesh sizes. These results indicate further fragmentation of forest and savannah vegetations between 1972 and 2013. Further research is needed to quantitatively evaluate the influences of individual factors of human activities and to separate these from the impacts of climate change-driven disturbances.
NASA Astrophysics Data System (ADS)
Rover, J.; Goldhaber, M. B.; Holen, C.; Dittmeier, R.; Wika, S.; Steinwand, D.; Dahal, D.; Tolk, B.; Quenzer, R.; Nelson, K.; Wylie, B. K.; Coan, M.
2015-12-01
Multi-year land cover mapping from remotely sensed data poses challenges. Producing land cover products at spatial and temporal scales required for assessing longer-term trends in land cover change are typically a resource-limited process. A recently developed approach utilizes open source software libraries to automatically generate datasets, decision tree classifications, and data products while requiring minimal user interaction. Users are only required to supply coordinates for an area of interest, land cover from an existing source such as National Land Cover Database and percent slope from a digital terrain model for the same area of interest, two target acquisition year-day windows, and the years of interest between 1984 and present. The algorithm queries the Landsat archive for Landsat data intersecting the area and dates of interest. Cloud-free pixels meeting the user's criteria are mosaicked to create composite images for training the classifiers and applying the classifiers. Stratification of training data is determined by the user and redefined during an iterative process of reviewing classifiers and resulting predictions. The algorithm outputs include yearly land cover raster format data, graphics, and supporting databases for further analysis. Additional analytical tools are also incorporated into the automated land cover system and enable statistical analysis after data are generated. Applications tested include the impact of land cover change and water permanence. For example, land cover conversions in areas where shrubland and grassland were replaced by shale oil pads during hydrofracking of the Bakken Formation were quantified. Analytical analysis of spatial and temporal changes in surface water included identifying wetlands in the Prairie Pothole Region of North Dakota with potential connectivity to ground water, indicating subsurface permeability and geochemistry.
Development of national database on long-term deforestation (1930-2014) in Bangladesh
NASA Astrophysics Data System (ADS)
Reddy, C. Sudhakar; Pasha, S. Vazeed; Jha, C. S.; Diwakar, P. G.; Dadhwal, V. K.
2016-04-01
The aim of the present study is to prepare a nation-wide spatial database on forest cover to assess and monitor the land use changes associated with deforestation in Bangladesh. The multi-source data were interpreted to get the forest cover map of 1930, 1975, 1985, 1995, 2006 and 2014. The spatial information generated on total area under forest cover, rate of deforestation and afforestation, changes across forest types, forest canopy density, replacement land use in deforested area and deforestation hotspots. This spatial analysis has indicated that forest cover is undergoing significant negative change in area and quality. We report that forests in Bangladesh covered an area of 23,140 km2 in 1930 which has decreased to 14,086 km2 in 2014, a net loss of 9054 km2 (39.1%) in eight decades. Analysis of annual rate of gross deforestation for the recent period indicates 0.77% during 2006-2014. During the past eight decades, semi-evergreen forests show loss of 56.4% of forest cover followed by moist deciduous forests (51.5%), dry deciduous forests (43.1%) and mangroves (6.5%). The loss of 23.5% of dense forest cover was found from 1975 to 2014. Dense semi-evergreen forests shows more negative change (36.9%) followed by dense moist deciduous forest (32.7%) from 1975 to 2014. Annual rate of deforestation is higher in dense forests compared to open forests from 2006 to 2014 and indicates increased threat due to anthropogenic pressures. The spatial analysis of forest cover change in mangroves has shown a lower rate of deforestation. Most of the forest conversions have led to the degradation of forests to scrub and transition to agriculture and plantation. The study has identified the 'deforestation hotspots' can help in strategic planning for conservation and management of forest resources.
Estimation of late twentieth century land-cover change in California
Sleeter, Benjamin M.; Wilson, Tamara S.; Soulard, Christopher E.; Liu, Jinxun
2011-01-01
We present the first comprehensive multi-temporal analysis of land-cover change for California across its major ecological regions and primary land-cover types. Recently completed satellite-based estimates of land-cover and land-use change information for large portions of the United States allow for consistent measurement and comparison across heterogeneous landscapes. Landsat data were employed within a pure-panel stratified one-stage cluster sample to estimate and characterize land-cover change for 1973–2000. Results indicate anthropogenic and natural disturbances, such as forest cutting and fire, were the dominant changes, followed by large fluctuations between agriculture and rangelands. Contrary to common perception, agriculture remained relatively stable over the 27-year period with an estimated loss of 1.0% of agricultural land. The largest net declines occurred in the grasslands/shrubs class at 5,131 km2 and forest class at 4,722 km2. Developed lands increased by 37.6%, composing an estimated 4.2% of the state’s land cover by 2000.
Mapping Tropical Forest Change in the Greater Marañón and Ucayali regions of Peru using CLASlite
NASA Astrophysics Data System (ADS)
Perez-Leiva, P.; Knapp, D. E.; Clark, J. K.; Asner, G. P.
2012-12-01
The Carnegie Landsat Analysis System-lite (CLASlite) was used to map and monitor tropical forest change in two large tropical watersheds in Peru: Greater Marañón and Ucayali. CLASlite uses radiometric and atmospheric correction algorithms as well as an Automated Monte Carlo Unmixing (AutoMCU) to obtain consistent fractional land cover per-pixel at high spatial resolution. Fractional land cover is automatically extracted from universal spectral libraries which allow for a differentiation between live photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare substrate (S). Fractional cover information is directly translated to maps of forest cover based in the physical characteristics of the forest canopy. Rates of deforestation and disturbance are estimated through analysis of change in fractional land cover over time. The Greater Marañón and Ucayali watersheds were studied over the period 1985 to 2012, through analysis of 1900 multi-spectral images from Landsat 4, 5 and 7. These images were processed and analyzed using CLASlite to obtain fractional cover and forest cover information for each year within the period. Annualization of the collected maps provided detailed information on the gross rates of disturbance and deforestation throughout the region. Further, net deforestation and disturbance maps were used to show the general forest change in these watersheds over the past 25 years. We found that deforestation accounts for just ~50% of the total forest losses, and that forest disturbance (degradation) is critically important to consider when making forest change estimates associated with losses in habitat and carbon in the region. These results also provide spatially-detailed, temporally-specific information on forest change for nearly three decades. Information provided by this study will assist decision-makers in Peru to improve their regional environmental management. The results, unprecedented in spatial and temporal scope, are another example showing the fidelity of tropical deforestation and forest degradation monitoring made routine using the CLASlite system.
Ikiel, Cercis; Ustaoglu, Beyza; Dutucu, Ayse Atalay; Kilic, Derya Evrim
2013-02-01
The aim of this study is to research natural land cover change caused by the permanent effects of human activities in Duzce plain and its surroundings, and to determine the current status of the land cover. For this purpose, two Landsat TM images were used in the study for the years 1987 and 2010. These images are analysed by using data image processing techniques in ERDAS Imagine©10.0 and ArcGIS©10.0 software. Land cover change nomenclature is classified according to the Coordination of Information on the Environment Level 2 Classification (1--urban fabric, 2--industrial, commercial and transport units, 3--heterogeneous agricultural areas, 4--forests, and 5--inland wetlands). Furthermore, the image analysis results are confirmed by the field research. According to the results, a decrease of 33.5 % was recorded in forest areas from 24,840.7 to 16,529.0 ha; an increase of 11.2 % was recorded in heterogeneous agricultural areas from 47,702.7 to 53,051.7 ha. Natural vegetation, which is the large part of land cover in the research area, has been changing rapidly because of rapid urbanisation and agricultural activities. As a result, it is concluded that significant changes have occurred on the natural land cover between the years 1987 and 2010 in the Duzce plain and its surroundings.
Using the FORE-SCE model to project land-cover change in the southeastern United States
Sohl, Terry; Sayler, Kristi L.
2008-01-01
A wide variety of ecological applications require spatially explicit current and projected land-use and land-cover data. The southeastern United States has experienced massive land-use change since European settlement and continues to experience extremely high rates of forest cutting, significant urban development, and changes in agricultural land use. Forest-cover patterns and structure are projected to change dramatically in the southeastern United States in the next 50 years due to population growth and demand for wood products [Wear, D.N., Greis, J.G. (Eds.), 2002. Southern Forest Resource Assessment. General Technical Report SRS-53. U.S. Department of Agriculture, Forest Service, Southern Research Station, Asheville, NC, 635 pp]. Along with our climate partners, we are examining the potential effects of southeastern U.S. land-cover change on regional climate. The U.S. Geological Survey (USGS) Land Cover Trends project is analyzing contemporary (1973-2000) land-cover change in the conterminous United States, providing ecoregion-by-ecoregion estimates of the rates of change, descriptive transition matrices, and changes in landscape metrics. The FORecasting SCEnarios of future land-cover (FORE-SCE) model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land-cover change through 2050 for the southeastern United States. Prescriptions for future proportions of land cover for this application were provided by ecoregion-based extrapolations of historical change. Logistic regression was used to develop relationships between suspected drivers of land-cover change and land cover, resulting in the development of probability-of-occurrence surfaces for each unique land-cover type. Forest stand age was initially established with Forest Inventory and Analysis (FIA) data and tracked through model iterations. The spatial allocation procedure placed patches of new land cover on the landscape until the scenario prescriptions were met, using measured Land Cover Trends data to guide patch characteristics and the probability surfaces to guide placement. The approach provides an efficient method for extrapolating historical land-cover trends and is amenable to the incorporation of more detailed and focused studies for the establishment of scenario prescriptions.
Mosaics of Change: Cross-Scale Forest Cover Dynamics and Drivers in Tibetan Yunnan, China
NASA Astrophysics Data System (ADS)
Van Den Hoek, Jamon
In reaction to devastating floods on the Yangtze River in the summer of 1998, the Chinese Central Government introduced a logging ban as part of the Natural Forest Protection Program (NFPP) with the goal of dramatically increasing national forest cover. Since then, over 11 billion USD has been allocated to the program, but the NFPP's success at promoting reforestation is unclear as neither the extent of forest cover change, nor the potential factors influencing the spatial variability of change have been examined. This research employs a case study in northwest Yunnan Province, southwest China, to evaluate the spatial variability of forest cover change under the NFPP and investigate drivers that have influenced recent patterns of change. I employ a mixed methods, cross-scale research framework that includes the analysis of areal trajectories and spatial variability of Landsat-5 imagery-derived forest cover change at three administrative levels before and after the NFPP's introduction; landscape ecology-based metrics to measure the shifting patterns of forest cover change at the patch level; and household interview data on village-level forest resource use patterns and processes in three neighboring villages. Prefecture- and county-level analyses suggest rather stable forest cover across the three-county study area since the introduction of the ban, though township-level measures of forest cover change show a degree of spatial variability as well as a temporal delay in policy implementation effectiveness. Village-level remote sensing analysis shows comparable amounts of forest cover change between study villages but disparate forest resource use patterns in terms of location and amount. Though all research villages continue to exploit local forests for firewood and timber relatively unfettered by policy restrictions, villagers with tourism-derived income are able to buy forest products collected in outside forests much more often; this redistributes local-scale deforestation to the benefit of local and detriment of distant forests. Tourism is often heralded as the solution to rural development challenges in China's southwest, but this research shows the unintended consequences that may result from inconsistent participation at the village-level, consequences which merely redirect, not reduce, forest use pressures, and that are contrary to the goals of state policy.
Spatial and Temporal Analysis of Industrial Forest Clearcuts in the Conterminous United States
NASA Astrophysics Data System (ADS)
Huo, L. Z.; Boschetti, L.
2015-12-01
Remote sensing has been widely used for mapping and characterizing changes in forest cover, but the available remote sensing forest change products are not discriminating between deforestation (permanent transition from forest to non forest) and industrial forest management (logging followed by regrowth, with no land cover/ land use class change) (Hansen et al, 2010). Current estimates of carbon-equivalent emissions report the contribution of deforestation as 12% of total anthropogenic carbon emissions (van der Werf et al., 2009), but accurate monitoring of forest carbon balance should discriminate between land use change related to forest natural disturbances, and forest management. The total change in forest cover (Gross Forest Cover Loss, GFLC) needs to be characterized based on the cause (natural/human) and on the outcome of the change (regeneration to forest/transition to non/forest)(Kurtz et al, 2010). This paper presents the methodology used to classify the forest loss detected by the University of Maryland Global Forest Change product (Hansen, 2013) into deforestation, disturbances (fires, insect outbreaks) and industrial forest clearcuts. The industrial forest clearcuts were subsequently analysed by converting the pixel based detections into objects, and applying patch level metrics (e.g. size, compactness, straightness of boundaries) and contextual measures. The analysis is stratified by region and by dominant forest specie, to highlight changes in the rate of forest resource utilization in the 2003-2013 period covered by the Maryland Forest Cover Change Product. References Hansen, M.C., Stehman, S.V., & Potapov, P.V. (2010). Reply to Wernick et al.: Global scale quantification of forest change. Proceedings of the National Academy of Sciences, 107, E148-E148 Hansen, M.C., Potapov, P.V., Moore, R et al., (2013), "High resolution Global Maps for the 21stCentury Forest Cover Change", Science 342: 850-853 Kurz, W.A. (2010). An ecosystem context for global gross forest cover loss estimates. Proceedings of the National Academy of Sciences, 107, 9025-9026 van der Werf, G.R., Morton, D.C., DeFries, R.S., Olivier, J.G., Kasibhatla, P.S., Jackson, R.B., Collatz, G.J., & Randerson, J. (2009). CO2 emissions from forest loss. Nature Geoscience, 2, 737-738
Nordberg, Maj-Liz; Evertson, Joakim
2003-12-01
Vegetation cover-change analysis requires selection of an appropriate set of variables for measuring and characterizing change. Satellite sensors like Landsat TM offer the advantages of wide spatial coverage while providing land-cover information. This facilitates the monitoring of surface processes. This study discusses change detection in mountainous dry-heath communities in Jämtland County, Sweden, using satellite data. Landsat-5 TM and Landsat-7 ETM+ data from 1984, 1994 and 2000, respectively, were used. Different change detection methods were compared after the images had been radiometrically normalized, georeferenced and corrected for topographic effects. For detection of the classes change--no change the NDVI image differencing method was the most accurate with an overall accuracy of 94% (K = 0.87). Additional change information was extracted from an alternative method called NDVI regression analysis and vegetation change in 3 categories within mountainous dry-heath communities were detected. By applying a fuzzy set thresholding technique the overall accuracy was improved from of 65% (K = 0.45) to 74% (K = 0.59). The methods used generate a change product showing the location of changed areas in sensitive mountainous heath communities, and it also indicates the extent of the change (high, moderate and unchanged vegetation cover decrease). A total of 17% of the dry and extremely dry-heath vegetation within the study area has changed between 1984 and 2000. On average 4% of the studied heath communities have been classified as high change, i.e. have experienced "high vegetation cover decrease" during the period. The results show that the low alpine zone of the southern part of the study area shows the highest amount of "high vegetation cover decrease". The results also show that the main change occurred between 1994 and 2000.
NASA Astrophysics Data System (ADS)
Liu, Pei; Han, Ruimei; Wang, Shuangting
2014-11-01
According to the merits of remotely sensed data in depicting regional land cover and Land changes, multi- objective information processing is employed to remote sensing images to analyze and simulate land cover in mining areas. In this paper, multi-temporal remotely sensed data were selected to monitor the pattern, distri- bution and trend of LUCC and predict its impacts on ecological environment and human settlement in mining area. The monitor, analysis and simulation of LUCC in this coal mining areas are divided into five steps. The are information integration of optical and SAR data, LULC types extraction with SVM classifier, LULC trends simulation with CA Markov model, landscape temporal changes monitoring and analysis with confusion matrixes and landscape indices. The results demonstrate that the improved data fusion algorithm could make full use of information extracted from optical and SAR data; SVM classifier has an efficient and stable ability to obtain land cover maps, which could provide a good basis for both land cover change analysis and trend simulation; CA Markov model is able to predict LULC trends with good performance, and it is an effective way to integrate remotely sensed data with spatial-temporal model for analysis of land use / cover change and corresponding environmental impacts in mining area. Confusion matrixes are combined with landscape indices to evaluation and analysis show that, there was a sustained downward trend in agricultural land and bare land, but a continues growth trend tendency in water body, forest and other lands, and building area showing a wave like change, first increased and then decreased; mining landscape has undergone a from small to large and large to small process of fragmentation, agricultural land is the strongest influenced landscape type in this area, and human activities are the primary cause, so the problem should be pay more attentions by government and other organizations.
Land-cover change in the Lower Mississippi Valley, 1973-2000
Karstensen, Krista A.; Sayler, Kristi L.
2009-01-01
The Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. The project is coordinated by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in conjunction with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA). Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 were processed to characterize ecosystem responses to land-use changes. The 27-year study period was divided into four temporal periods: 1973 to1980, 1980 to 1986, 1986 to 1992, 1992 to 2000 and overall from 1973 to 2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize and evaluate land-cover change using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation.The rates of land-cover change were estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images were used to interpret land-cover change. The sample block data then were incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion.
NASA Astrophysics Data System (ADS)
Hester, David Barry
The objective of this research was to develop methods for urban land cover analysis using QuickBird high spatial resolution satellite imagery. Such imagery has emerged as a rich commercially available remote sensing data source and has enjoyed high-profile broadcast news media and Internet applications, but methods of quantitative analysis have not been thoroughly explored. The research described here consists of three studies focused on the use of pan-sharpened 61-cm spatial resolution QuickBird imagery, the spatial resolution of which is the highest of any commercial satellite. In the first study, a per-pixel land cover classification method is developed for use with this imagery. This method utilizes a per-pixel classification approach to generate an accurate six-category high spatial resolution land cover map of a developing suburban area. The primary objective of the second study was to develop an accurate land cover change detection method for use with QuickBird land cover products. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and meaningful high spatial resolution land cover change analysis. The third study described here is an urban planning application of the high spatial resolution QuickBird-based land cover product developed in the first study. This work both meaningfully connects this exciting new data source to urban watershed management and makes an important empirical contribution to the study of suburban watersheds. Its analysis of residential roads and driveways as well as retail parking lots sheds valuable light on the impact of transportation-related land use on the suburban landscape. Broadly, these studies provide new methods for using state-of-the-art remote sensing data to inform land cover analysis and urban planning. These methods are widely adaptable and produce land cover products that are both meaningful and accurate. As additional high spatial resolution satellites are launched and the cost of high resolution imagery continues to decline, this research makes an important contribution to this exciting era in the science of remote sensing.
Ecological lessons from an island that has experienced it all
Ariel E. Lugo
2006-01-01
Puerto Rico has gone through significant land cover change, going from an island that was forested to one that was agrarian and then finally becoming an urban island. Coastal wetlands experienced dramatic changes as alterations occurred in land cover and an eco-systematic analysis of these changes leads to the proposal of the following five ecological lessons learned...
McElhone, P.; Wood, P.W.; Dawson, D.
2007-01-01
The cerulean warbler (Dendroica cerulea) is one of the highest priority bird species in the eastern United States because populations have declined 4.3% annually during 1966?2005 based on Breeding Bird Survey (BBS) data. Habitat loss and fragmentation due to land use changes is thought to be one of the major factors contributing to the decline. BBS routes, the primary source for monitoring bird population trends, include 50 sampling stops every 0.8 km. Although data from BBS routes are extrapolated to determine regional trends in bird populations, it is important to understand the effects of habitat changes at the stop-level along BBS routes. Route-level analysis of habitat changes may mask important changes that are occurring at a smaller scale particularly for the cerulean warbler which displays several micro-scale habitat preferences. We are examining cerulean warbler habitat and population changes in its core breeding range of the Ohio Hills and Cumberland Plateau physiographic regions. We quantified land cover changes within 300 m of BBS routes in the core cerulean warbler breeding range of Ohio, West Virginia, and Kentucky by digitizing aerial photographs from two time periods: the 1980s and 2004. We also quantified land cover changes within 300 m of BBS routes with the National Land Cover Dataset (NLCD) from 1992 and 2001. The hand-digitized aerial photos will be compared with the NLCD to determine how similar the two methods are in quantifying land cover changes. We then compared stop-level land cover changes with stop level changes in cerulean warbler detections within the same time periods along the BBS routes. This will allow for a more detailed analysis of how well habitat changes along BBS routes reflect the changes in cerulean warbler populations.
Review of Land Use and Land Cover Change research progress
NASA Astrophysics Data System (ADS)
Chang, Yue; Hou, Kang; Li, Xuxiang; Zhang, Yunwei; Chen, Pei
2018-02-01
Land Use and Land Cover Change (LUCC) can reflect the pattern of human land use in a region, and plays an important role in space soil and water conservation. The study on the change of land use patterns in the world is of great significance to cope with global climate change and sustainable development. This paper reviews the main research progress of LUCC at home and abroad, and suggests that land use change has been shifted from land use planning and management to land use change impact and driving factors. The development of remote sensing technology provides the basis and data for LUCC with dynamic monitoring and quantitative analysis. However, there is no uniform standard for land use classification at present, which brings a lot of inconvenience to the collection and analysis of land cover data. Globeland30 is an important milestone contribution to the study of international LUCC system. More attention should be paid to the accuracy and results contrasting test of land use classification obtained by remote sensing technology.
Land-Cover Change in the Central Irregular Plains, 1973-2000
Karstensen, Krista A.
2009-01-01
Spearheaded by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in collaboration with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA), the Land Cover Trends is a research project focused on understanding the rates, trends, causes, and consequences of contemporary United States land-use and land-cover change. Using the EPA Level III ecoregions as the geographic framework, scientists process geospatial data collected between 1973 and 2000 to characterize ecosystem responses to land-use changes. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000 and 1973-2000. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize land-cover change and evaluate using a modified Anderson Land Use Land Cover Classification System for image interpretation. The rates of land-cover change are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change. Additionally, historical aerial photographs from similar timeframes and other ancillary data such as census statistics and published literature are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. These change statistics are applicable for different levels of scale, including total change for the individual sample blocks and change estimates for the entire ecoregion. The results illustrate that there is no single profile of land-cover change but instead point to geographic variability that results from land uses within ecoregions continuously adapting to various factors including environmental, technological, and socioeconomic.
NASA Astrophysics Data System (ADS)
Qaisar, Maha
2016-07-01
Due to the present land use practices and climate variability, drastic shifts in regional climate and land covers are easily seen and their future reduction and gain are too well predicted. Therefore, there is an increasing need for data on land-cover changes at narrow and broad spatial scales. In this study, a remote sensing-based technique for land-cover-change analysis is applied to the lower Sindh areas for the last decade. Landsat satellite products were analyzed on an alternate yearly basis, from 1990 to 2016. Then Land-cover-change magnitudes were measured and mapped for alternate years. Land Surface Temperature (LST) is one of the critical elements in the natural phenomena of surface energy and water balance at local and global extent. However, LST was computed by using Landsat thermal bands via brightness temperature and a vegetation index. Normalized difference vegetation index (NDVI) was interpreted and maps were achieved. LST reflected NDVI patterns with complexity of vegetation patterns. Along with this, Object Based Image Analysis (OBIA) was done for classifying 5 major classes of water, vegetation, urban, marshy lands and barren lands with significant map layouts. Pakistan Meteorological Department provided the climate data in which rainfall, temperature and air temperature are included. Once the LST and OBIA are performed, overlay analysis was done to correlate the results of LST with OBIA and LST with meteorological data to ascertain the changes in land covers due to increasing centigrade of LST. However, satellite derived LST was also correlated with climate data for environmental analysis and to estimate Land Surface Temperature for assessing the inverse impacts of climate variability. This study's results demonstrate the land-cover changes in Lower Areas of Sindh including the Indus Delta mostly involve variations in land-cover conditions due to inter-annual climatic variability and temporary shifts in seasonality. However it is too concluded that transitory alteration of the biophysical characteristics of the surface driven by variations in rainfall is the prevailing progression. Moreover, future work will focus on finer-scale analysis and validations of patterns of changes due to rapid urbanization and population explosion in poverty stricken areas of Sindh which are posing an adverse impact on the land utilization and in turn increasing the land surface temperature and ultimately more stress on the low lying areas of Sindh i.e. Indus Delta will be losing its productivity and capacity to bear biodiversity whether the fauna or flora. Hence, this regional scale problem will become a global concern. Therefore, it is needed to stop the menace in its starting phase to mitigate the problem and to bring minds on this horrendous situation.
Development of LANDSAT Derived Forest Cover Information for Integration into Adirondack Park GIS
NASA Technical Reports Server (NTRS)
Curran, R. P.; Banta, J. S.
1982-01-01
Based upon observed changes in timber harvest practices partially attributable to forest biomass removable for energy supply purposes, the Adirondack Park Agency began in 1979 a multi-year project to implement a digital geographic information system (GIS). An initial developmental task was an inventory of forest cover information and analysis of forest resource change and availability. While developing the GIS, a pilot project was undertaken to evaluate the usefulness of LANDSAT derived land cover information for this purpose, and to explore the integration of LANDSAT data into the GIS. The prototype LANDSAT analysis project involved: (1) the use of both recent and historic data to derive land cover information for two dates; and (2) comparison of land cover over time to determine quantitative and geographic changes. The "recent data," 1978 full foliage data over portions of four LANDSAT scenes, was classified, using ground truth derived training samples in various forested and non-forested categories. Forested categories include the following: northern hardwoods, pine, spruce-fir, and pine plantation, while nonforested categories include wet-conifer, pasture, grassland, urban, exposed soil, agriculture, and water.
Design and analysis for thematic map accuracy assessment: Fundamental principles
Stephen V. Stehman; Raymond L. Czaplewski
1998-01-01
Land-cover maps are used in numerous natural resource applications to describe the spatial distribution and pattern of land-cover, to estimate areal extent of various cover classes, or as input into habitat suitability models, land-cover change analyses, hydrological models, and risk analyses. Accuracy assessment quantifies data quality so that map users may evaluate...
USDA-ARS?s Scientific Manuscript database
A retrospective land cover analysis covering the time period from the early 1970s to early 1990s was conducted to gain a sense of the dynamics of land cover changes on the Little Washita River and Fort Cobb Reservoir experimental watersheds (LWREW, FCREW), located in southwestern Oklahoma. This stu...
NASA Technical Reports Server (NTRS)
Potter, Christopher
2013-01-01
The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in perennial vegetation cover at marshland sites in Northern California reported to have undergone restoration between 1999 and 2009. Results showed extensive contiguous areas of restored marshland plant cover at 10 of the 14 sites selected. Gains in either woody shrub cover and/or from recovery of herbaceous cover that remains productive and evergreen on a year-round basis could be mapped out from the image results. However, LEDAPS may not be highly sensitive changes in wetlands that have been restored mainly with seasonal herbaceous cover (e.g., vernal pools), due to the ephemeral nature of the plant greenness signal. Based on this evaluation, the LEDAPS methodology would be capable of fulfilling a pressing need for consistent, continual, low-cost monitoring of changes in marshland ecosystems of the Pacific Flyway.
Karstensen, Krista A.; Warner, Kelly L.
2010-01-01
The Land-Cover Trends project is a collaborative effort between the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS), the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA) to understand the rates, trends, causes, and consequences of contemporary land-use and land-cover change in the United States. The data produced from this research can lead to an enriched understanding of the drivers of future landuse change, effects on environmental systems, and any associated feedbacks. USGS scientists are using the EPA Level III ecoregions as the geographic framework to process geospatial data collected between 1973 and 2000 to characterize ecosystem responses to land-use changes. General land-cover classes for these periods were interpreted from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery to categorize and evaluate land-cover change using a modified Anderson Land-Use/Land-Cover Classification System for image interpretation.
Slonecker, Terrence
2008-01-01
The advancement of geographic science in the area of land surface status and trends and land cover change is at the core of the current geographic scientific research of the U.S. Geological Survey (USGS) (McMahon and others, 2005). Perhaps the least developed or articulated aspects of USGS land change science have been the identification and analysis of the ecological consequences of land cover change. Changes in land use and land cover significantly affect the ability of ecosystems to provide essential ecological goods and services, which, in turn, affect the economic, public health, and social benefits that these ecosystems provide. One of the great scientific challenges for geographic science is to understand and calibrate the effects of land use and land cover change and the complex interaction between human and biotic systems at a variety of natural, geographic, and political scales. Understanding the dynamics of land surface change requires an increased understanding of the complex nature of human-environmental systems and will require a suite of scientific tools that include traditional geographic data and analysis methods, such as remote sensing and geographic information systems (GIS), as well as innovative approaches to understanding the dynamics of complex systems. One such approach that has gained much recent scientific attention is the landscape indicator, or landscape assessment, approach, which has been developed with the emergence of the science of landscape ecology.
Land-Cover Trends of the Southern California Mountains Ecoregion
Soulard, Christopher E.; Raumann, Christian G.; Wilson, Tamara S.
2007-01-01
This report presents an assessment of land-use and land-cover (LU/LC) change in the Southern California Mountains ecoregion for the period 1973-2001. The Southern California Mountains is one of 84 Level-III ecoregions as defined by the U.S. Environmental Protection Agency (EPA). Ecoregions have served as a spatial framework for environmental resource management, denoting areas that contain a geographically distinct assemblage of biotic and abiotic phenomena including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The established Land Cover Trends methodology generates estimates of change for ecoregions using a probability sampling approach and change-detection analysis of thematic land-cover images derived from Landsat satellite imagery.
Weiqi Zhou; Austin Troy; Morgan Grove
2008-01-01
Accurate and timely information about land cover pattern and change in urban areas is crucial for urban land management decision-making, ecosystem monitoring and urban planning. This paper presents the methods and results of an object-based classification and post-classification change detection of multitemporal high-spatial resolution Emerge aerial imagery in the...
The characteristics and interpretability of land surface change and implications for project design
Sohl, Terry L.; Gallant, Alisa L.; Loveland, Thomas R.
2004-01-01
The need for comprehensive, accurate information on land-cover change has never been greater. While remotely sensed imagery affords the opportunity to provide information on land-cover change over large geographic expanses at a relatively low cost, the characteristics of land-surface change bring into question the suitability of many commonly used methodologies. Algorithm-based methodologies to detect change generally cannot provide the same level of accuracy as the analyses done by human interpreters. Results from the Land Cover Trends project, a cooperative venture that includes the U.S. Geological Survey, Environmental Protection Agency, and National Aeronautics and Space Administration, have shown that land-cover conversion is a relatively rare event, occurs locally in small patches, varies geographically and temporally, and is spectrally ambiguous. Based on these characteristics of change and the type of information required, manual interpretation was selected as the primary means of detecting change in the Land Cover Trends project. Mixtures of algorithm-based detection and manual interpretation may often prove to be the most feasible and appropriate design for change-detection applications. Serious examination of the expected characteristics and measurability of change must be considered during the design and implementation phase of any change analysis project.
NASA Astrophysics Data System (ADS)
Broothaerts, Nils; López-Sáez, José Antonio; Verstraeten, Gert
2017-04-01
Reconstructing and quantifying human impact is an important step to understand human-environment interactions in the past. Quantitative measures of human impact on the landscape are needed to fully understand long-term influence of anthropogenic land cover changes on the global climate, ecosystems and geomorphic processes. Nevertheless, quantifying past human impact is not straightforward. Recently, multivariate statistical analysis of fossil pollen records have been proposed to characterize vegetation changes and to get insights in past human impact. Although statistical analysis of fossil pollen data can provide useful insights in anthropogenic driven vegetation changes, still it cannot be used as an absolute quantification of past human impact. To overcome this shortcoming, in this study fossil pollen records were included in a multivariate statistical analysis (cluster analysis and non-metric multidimensional scaling (NMDS)) together with modern pollen data and modern vegetation data. The information on the modern pollen and vegetation dataset can be used to get a better interpretation of the representativeness of the fossil pollen records, and can result in a full quantification of human impact in the past. This methodology was applied in two contrasting environments: SW Turkey and Central Spain. For each region, fossil pollen data from different study sites were integrated, together with modern pollen data and information on modern vegetation. In this way, arboreal cover, grazing pressure and agricultural activities in the past were reconstructed and quantified. The data from SW Turkey provides new integrated information on changing human impact through time in the Sagalassos territory, and shows that human impact was most intense during the Hellenistic and Roman Period (ca. 2200-1750 cal a BP) and decreased and changed in nature afterwards. The data from central Spain shows for several sites that arboreal cover decreases bellow 5% from the Feudal period onwards (ca. 850 cal a BP) related to increasing human impact in the landscape. At other study sites arboreal cover remained above 25% beside significant human impact. Overall, the presented examples from two contrasting environments shows how cluster analysis and NMDS of modern and fossil pollen data can help to provide quantitative insights in anthropogenic land cover changes. Our study extensively discuss and illustrate the possibilities and limitations of statistical analysis of pollen data to quantify human induced land use changes.
NASA Astrophysics Data System (ADS)
Surdu, C. M.; Duguay, C. R.; Brown, L. C.; Fernández Prieto, D.
2013-07-01
Air temperature and winter precipitation changes over the last five decades have impacted the timing, duration, and thickness of the ice cover on Arctic lakes as shown by recent studies. In the case of shallow tundra lakes, many of which are less than 3 m deep, warmer climate conditions could result in thinner ice covers and consequently, to a smaller fraction of lakes freezing to their bed in winter. However, these changes have not yet been comprehensively documented. The analysis of a 20 yr time series of ERS-1/2 synthetic aperture radar (SAR) data and a numerical lake ice model were employed to determine the response of ice cover (thickness, freezing to the bed, and phenology) on shallow lakes of the North Slope of Alaska (NSA) to climate conditions over the last six decades. Analysis of available SAR data from 1991-2011, from a sub-region of the NSA near Barrow, shows a reduction in the fraction of lakes that freeze to the bed in late winter. This finding is in good agreement with the decrease in ice thickness simulated with the Canadian Lake Ice Model (CLIMo), a lower fraction of lakes frozen to the bed corresponding to a thinner ice cover. Observed changes of the ice cover show a trend toward increasing floating ice fractions from 1991 to 2011, with the greatest change occurring in April, when the grounded ice fraction declined by 22% (α = 0.01). Model results indicate a trend toward thinner ice covers by 18-22 cm (no-snow and 53% snow depth scenarios, α = 0.01) during the 1991-2011 period and by 21-38 cm (α = 0.001) from 1950-2011. The longer trend analysis (1950-2011) also shows a decrease in the ice cover duration by ∼24 days consequent to later freeze-up dates by 5.9 days (α = 0.1) and earlier break-up dates by 17.7-18.6 days (α = 0.001).
NASA Astrophysics Data System (ADS)
Masek, J.; Rao, A.; Gao, F.; Davis, P.; Jackson, G.; Huang, C.; Weinstein, B.
2008-12-01
The Land Cover Change Community-based Processing and Analysis System (LC-ComPS) combines grid technology, existing science modules, and dynamic workflows to enable users to complete advanced land data processing on data available from local and distributed archives. Changes in land cover represent a direct link between human activities and the global environment, and in turn affect Earth's climate. Thus characterizing land cover change has become a major goal for Earth observation science. Many science algorithms exist to generate new products (e.g., surface reflectance, change detection) used to study land cover change. The overall objective of the LC-ComPS is to release a set of tools and services to the land science community that can be implemented as a flexible LC-ComPS to produce surface reflectance and land-cover change information with ground resolution on the order of Landsat-class instruments. This package includes software modules for pre-processing Landsat-type satellite imagery (calibration, atmospheric correction, orthorectification, precision registration, BRDF correction) for performing land-cover change analysis and includes pre-built workflow chains to automatically generate surface reflectance and land-cover change products based on user input. In order to meet the project objectives, the team created the infrastructure (i.e., client-server system with graphical and machine interfaces) to expand the use of these existing science algorithm capabilities in a community with distributed, large data archives and processing centers. Because of the distributed nature of the user community, grid technology was chosen to unite the dispersed community resources. At that time, grid computing was not used consistently and operationally within the Earth science research community. Therefore, there was a learning curve to configure and implement the underlying public key infrastructure (PKI) interfaces, required for the user authentication, secure file transfer and remote job execution on the grid network of machines. In addition, science support was needed to vet that the grid technology did not have any adverse affects of the science module outputs. Other open source, unproven technologies, such as a workflow package to manage jobs submitted by the user, were infused into the overall system with successful results. This presentation will discuss the basic capabilities of LC-ComPS, explain how the technology was infused, and provide lessons learned for using and integrating the various technologies while developing and operating the system, and finally outline plans moving forward (maintenance and operations decisions) based on the experience to date.
NASA Astrophysics Data System (ADS)
Akay, S. S.; Sertel, E.
2016-06-01
Urban land cover/use changes like urbanization and urban sprawl have been impacting the urban ecosystems significantly therefore determination of urban land cover/use changes is an important task to understand trends and status of urban ecosystems, to support urban planning and to aid decision-making for urban-based projects. High resolution satellite images could be used to accurately, periodically and quickly map urban land cover/use and their changes by time. This paper aims to determine urban land cover/use changes in Gaziantep city centre between 2010 and 2105 using object based images analysis and high resolution SPOT 5 and SPOT 6 images. 2.5 m SPOT 5 image obtained in 5th of June 2010 and 1.5 m SPOT 6 image obtained in 7th of July 2015 were used in this research to precisely determine land changes in five-year period. In addition to satellite images, various ancillary data namely Normalized Difference Vegetation Index (NDVI), Difference Water Index (NDWI) maps, cadastral maps, OpenStreetMaps, road maps and Land Cover maps, were integrated into the classification process to produce high accuracy urban land cover/use maps for these two years. Both images were geometrically corrected to fulfil the 1/10,000 scale geometric accuracy. Decision tree based object oriented classification was applied to identify twenty different urban land cover/use classes defined in European Urban Atlas project. Not only satellite images and satellite image-derived indices but also different thematic maps were integrated into decision tree analysis to create rule sets for accurate mapping of each class. Rule sets of each satellite image for the object based classification involves spectral, spatial and geometric parameter to automatically produce urban map of the city centre region. Total area of each class per related year and their changes in five-year period were determined and change trend in terms of class transformation were presented. Classification accuracy assessment was conducted by creating a confusion matrix to illustrate the thematic accuracy of each class.
An Analysis of Shoreline Change At Little Lagoon, Alabama
2006-06-14
AN ANALYSIS OF SHORELINE CHANGE AT LITTLE LAGOON, ALABAMA By Glen R. Gibson THESIS...control number. 1. REPORT DATE 14 JUN 2006 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE An Analysis Of Shoreline Change At...correlation analysis conducted on the gulf shoreline and Little Lagoon’s southern shoreline showed that although weak overall correlation values
Climate Change for Agriculture, Forest Cover and 3d Urban Models
NASA Astrophysics Data System (ADS)
Kapoor, M.; Bassir, D.
2014-11-01
This research demonstrates the important role of the remote sensing in finding out the different parameters behind the agricultural crop change, forest cover and urban 3D models. Standalone software is developed to view and analysis the different factors effecting the change in crop productions. Open-source libraries from the Open Source Geospatial Foundation have been used for the development of the shape-file viewer. Software can be used to get the attribute information, scale, zoom in/out and pan the shapefiles. Environmental changes due to pollution and population that are increasing the urbanisation and decreasing the forest cover on the earth. Satellite imagery such as Landsat 5(1984) to Landsat TRIS/8 (2014), Landsat Data Continuity Mission (LDCM) and NDVI are used to analyse the different parameters that are effecting the agricultural crop production change and forest change. It is advisable for the development of good quality of NDVI and forest cover maps to use data collected from the same processing methods for the complete region. Management practices have been developed from the analysed data for the betterment of the crop and saving the forest cover
Multicriteria analysis for sources of renewable energy using data from remote sensing
NASA Astrophysics Data System (ADS)
Matejicek, L.
2015-04-01
Renewable energy sources are major components of the strategy to reduce harmful emissions and to replace depleting fossil energy resources. Data from remote sensing can provide information for multicriteria analysis for sources of renewable energy. Advanced land cover quantification makes it possible to search for suitable sites. Multicriteria analysis, together with other data, is used to determine the energy potential and socially acceptability of suggested locations. The described case study is focused on an area of surface coal mines in the northwestern region of the Czech Republic, where the impacts of surface mining and reclamation constitute a dominant force in land cover changes. High resolution satellite images represent the main input datasets for identification of suitable sites. Solar mapping, wind predictions, the location of weirs in watersheds, road maps and demographic information complement the data from remote sensing for multicriteria analysis, which is implemented in a geographic information system (GIS). The input spatial datasets for multicriteria analysis in GIS are reclassified to a common scale and processed with raster algebra tools to identify suitable sites for sources of renewable energy. The selection of suitable sites is limited by the CORINE land cover database to mining and agricultural areas. The case study is focused on long term land cover changes in the 1985-2015 period. Multicriteria analysis based on CORINE data shows moderate changes in mapping of suitable sites for utilization of selected sources of renewable energy in 1990, 2000, 2006 and 2012. The results represent map layers showing the energy potential on a scale of a few preference classes (1-7), where the first class is linked to minimum preference and the last class to maximum preference. The attached histograms show the moderate variability of preference classes due to land cover changes caused by mining activities. The results also show a slight increase in the more preferred classes for utilization of sources of renewable energy due to an increase area of reclaimed sites. Using data from remote sensing, such as the multispectral images and the CORINE land cover datasets, can reduce the financial resources currently required for finding and assessing suitable areas.
NASA Astrophysics Data System (ADS)
Zhang, Jixian; Zhengjun, Liu; Xiaoxia, Sun
2009-12-01
The eco-environment in the Three Gorges Reservoir Area (TGRA) in China has received much attention due to the construction of the Three Gorges Hydropower Station. Land use/land cover changes (LUCC) are a major cause of ecological environmental changes. In this paper, the spatial landscape dynamics from 1978 to 2005 in this area are monitored and recent changes are analyzed, using the Landsat TM (MSS) images of 1978, 1988, 1995, 2000 and 2005. Vegetation cover fractions for a vegetation cover analysis are retrieved from MODIS/Terra imagery from 2000 to 2006, being the period before and after the rising water level of the reservoir. Several analytical indices have been used to analyze spatial and temporal changes. Results indicate that cropland, woodland, and grassland areas reduced continuously over the past 30 years, while river and built-up area increased by 2.79% and 4.45% from 2000 to 2005, respectively. The built-up area increased at the cost of decreased cropland, woodland and grassland. The vegetation cover fraction increased slightly. We conclude that significant changes in land use/land cover have occurred in the Three Gorges Reservoir Area. The main cause is a continuous economic and urban/rural development, followed by environmental management policies after construction of the Three Gorges Dam.
Space-time analysis of snow cover change in the Romanian Carpathians (2001-2016)
NASA Astrophysics Data System (ADS)
Micu, Dana; Cosmin Sandric, Ionut
2017-04-01
Snow cover is recognized as an essential climate variable, highly sensitive to the ongoing climate warming, which plays an important role in regulating mountain ecosystems. Evidence from the existing weather stations located above 800 m over the last 50 years points out that the climate of the Romanian Carpathians is visibly changing, showing an ongoing and consistent warming process. Quantifying and attributing the changes in snow cover on various spatial and temporal scales have a great environmental and socio-economic importance for this mountain region. The study is revealing the inter-seasonal changes in the timing and distribution of snow cover across the Romanian Carpathians, by combining gridded snow data (CARPATCLIM dataset, 1961-2010) and remote sensing data (2001-2016) in specific space-time assessment at regional scale. The geostatistical approach applied in this study, based on a GIS hotspot analysis, takes advantage of all the dimensions in the datasets, in order to understand the space-time trends in this climate variable at monthly time-scale. The MODIS AQUA and TERRA images available from 2001 to 2016 have been processed using ArcGIS for Desktop and Python programming language. All the images were masked out with the Carpathians boundary. Only the pixels with snow have been retained for analysis. The regional trends in snow cover distribution and timing have been analysed using Space-Time cube with ArcGIS for Desktop, according with Esri documentation using the Mann-Kendall trend test on every location with data as an independent bin time-series test. The study aimed also to assess the location of emerging hotspots of snow cover change in Carpathians. These hotspots have been calculated using Getis-Ord Gi* statistic for each bin using Hot Spot Analysis implemented in ArcGIS for Desktop. On regional scale, snow cover appear highly sensitive to the decreasing trends in air temperatures and land surface temperatures, combined with the decrease in seasonal precipitation, especially at lower elevations in all the three divisions of the Romanian Carpathians (generally below 1,700-1,800 m). The space-time patterns of snow cover change are dominated by a significant decreasing trend of snow days and earlier spring snow melt. The key findings of this study provides robust indication of a decreasing snow trends across the Carpathian Mountain region and could provide valuable spatial and temporal snow information for other related research fields as well as for an effective environmental monitoring in the mountain ecosystems of the Carpathian region
Spectral reflectance relationships to leaf water stress
NASA Technical Reports Server (NTRS)
Ripple, William J.
1986-01-01
Spectral reflectance data were collected from detached snapbean leaves in the laboratory with a multiband radiometer. Four experiments were designed to study the spectral response resulting from changes in leaf cover, relative water content of leaves, and leaf water potential. Spectral regions included in the analysis were red (630-690 nm), NIR (760-900 nm), and mid-IR (2.08-2.35 microns). The red and mid-IR bands showed sensitivity to changes in both leaf cover and relative water content of leaves. The NIR was only highly sensitive to changes in leaf cover. Results provided evidence that mid-IR reflectance was governed primarily by leaf moisture content, although soil reflectance was an important factor when leaf cover was less than 100 percent. High correlations between leaf water potentials and reflectance were attributed to covariances with relative water content of leaves and leaf cover.
Land-Cover Trends of the Central Basin and Range Ecoregion
Soulard, Christopher E.
2006-01-01
The U.S. Geological Survey (USGS) Land Cover Trends research project is focused on understanding the amounts, rates, trends, causes, and implications of contemporary land-use and land-cover (LU/LC) change in the United States. This project is supported by the USGS Geographic Analysis and Monitoring Program in collaboration with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA). LU/LC change is a pervasive process that modifies landscape characteristics and affects a broad range of socioeconomic, biologic, and hydrologic systems. Understanding the impacts and feedbacks of LU/LC change on environmental systems requires an understanding of the rates, patterns, and driving forces of past, present, and future LU/LC change. The objectives of the Land Cover Trends project are to (1) determine and describe the amount, rates, and trends of contemporary LU/LC change by ecoregion for the period 1973-2000 for the conterminous United States, (2) document the causes, driving forces, and implications of change, and (3) synthesize individual ecoregion results into a national assessment of LU/LC change. The Land Cover Trends research team includes staff from the USGS National Center for Earth Resources Observation and Science (EROS), Rocky Mountain Geographic Science Center, Eastern Geographic Science Center, Mid-Continent Geographic Science Center, and the Western Geographic Science Center. Other partners include researchers at South Dakota State University, University of Southern Mississippi, and State University of New York College of Environmental Science and Forestry. This report presents an assessment of LU/LC change in the Central Basin and Range ecoregion for the period 1973-2000. The Central Basin and Range ecoregion is one of 84 Level-III ecoregions as defined by the Environmental Protection Agency. Ecoregions have served as a spatial framework for environmental resource management and to denote areas that contain a geographically distinct assemblage of biotic and abiotic phenomena including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The established Land Cover Trends methodology generates estimates of LU/LC change using a probability sampling approach and change-detection analysis of thematic land-cover images derived from Landsat satellite imagery.
NASA Astrophysics Data System (ADS)
Sexton, J.; Huang, C.; Channan, S.; Feng, M.; Song, X.; Kim, D.; Song, D.; Vermote, E.; Masek, J.; Townshend, J. R.
2013-12-01
Monitoring, analysis, and management of forests require measurements of forest cover that are both spatio-temporally consistent and resolved globally at sub-hectare resolution. The Global Forest Cover Change project, a cooperation between the University of Maryland Global Land Cover Facility and NASA Goddard Space Flight Center, is providing the first long-term, sub-hectare, globally consistent data records of forest cover, change, and fragmentation in circa-1975, -1990, -2000, and -2005 epochs. These data are derived from the Global Land Survey collection of Landsat images in the respective epochs, atmospherically corrected to surface reflectance in 1990, 2000, and 2005 using the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) implementation of the 6S radiative transfer algorithm, with ancillary information from MODIS Land products, ASTER Global Digital Elevation Model (GDEM), and climatological data layers. Forest cover and change were estimated by a novel continuous-field approach, which produced for the 2000 and 2005 epochs the world's first global, 30-m resolution database of tree cover. Surface reflectance estimates were validated against coincident MODIS measurements, the results of which have been corroborated by subsequent, independent validations against measurements from AERONET sites. Uncertainties in tree- and forest-cover values were estimated in each pixel as a compounding of within-sample uncertainty and accuracy relative to a sample of independent measurements from small-footprint lidar. Accuracy of forest cover and change estimates was further validated relative to expert-interpreted high-resolution imagery, from which unbiased estimates of forest cover and change have been produced at national and eco-regional scales. These first-of-kind Earth Science Data Records--surface reflectance in 1990, 2000, and 2005 and forest cover, change, and fragmentation in and between 1975, 1990, 2000, and 2005--are hosted at native, Landsat resolution for free public access at the Global Land Cover Facility website (www.landcover.org). Global mosaic of circa-2000, Landsat-based estimates of tree cover. Gaps due to clouds and/or snow in each scene were filled first with Landsat-based data from overlapping paths, and the remaining gaps were filled with data from the MODIS VCF Tree Cover layer in 2000.
Land Cover Change and Remote Sensing in the Classroom: An Exercise to Study Urban Growth
ERIC Educational Resources Information Center
Delahunty, Tina; Lewis-Gonzales, Sarah; Phelps, Jack; Sawicki, Ben; Roberts, Charles; Carpenter, Penny
2012-01-01
The processes and implications of urban growth are studied in a variety of disciplines as urban growth affects both the physical and human landscape. Remote sensing methods provide ways to visualize and mathematically represent urban growth; and resultant land cover change data enable both quantitative and qualitative analysis. This article helps…
A comprehensive change detection method for updating the National Land Cover Database to circa 2011
Jin, Suming; Yang, Limin; Danielson, Patrick; Homer, Collin G.; Fry, Joyce; Xian, George
2013-01-01
The importance of characterizing, quantifying, and monitoring land cover, land use, and their changes has been widely recognized by global and environmental change studies. Since the early 1990s, three U.S. National Land Cover Database (NLCD) products (circa 1992, 2001, and 2006) have been released as free downloads for users. The NLCD 2006 also provides land cover change products between 2001 and 2006. To continue providing updated national land cover and change datasets, a new initiative in developing NLCD 2011 is currently underway. We present a new Comprehensive Change Detection Method (CCDM) designed as a key component for the development of NLCD 2011 and the research results from two exemplar studies. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (CV, RCVMAX, dNBR, and dNDVI) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. For NLCD 2011, the improved and enhanced change products obtained from the CCDM provide critical information on location, magnitude, and direction of potential change areas and serve as a basis for further characterizing land cover changes for the nation. An accuracy assessment from the two study areas show 100% agreement between CCDM mapped no-change class with reference dataset, and 18% and 82% disagreement for the change class for WRS path/row p22r39 and p33r33, respectively. The strength of the CCDM is that the method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and anthropogenic disturbances potentially associated with land cover changes on different landscapes.
NASA Astrophysics Data System (ADS)
Drummond, Mark A.; Stier, Michael P.; Auch, Roger F.; Taylor, Janis L.; Griffith, Glenn E.; Riegle, Jodi L.; Hester, David J.; Soulard, Christopher E.; McBeth, Jamie L.
2015-11-01
The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8 % of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15 % of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83 %. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3 % of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.
Drummond, Mark A.; Stier, Michael P.; Auch, Roger F.; Taylor, Janis L.; Griffith, Glenn E.; Hester, David J.; Riegle, Jodi L.; Soulard, Christopher E.; McBeth, Jamie L.
2015-01-01
The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8 % of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15 % of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83 %. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3 % of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.
Drummond, Mark A; Stier, Michael P; Auch, Roger F; Taylor, Janis L; Griffith, Glenn E; Riegle, Jodi L; Hester, David J; Soulard, Christopher E; McBeth, Jamie L
2015-11-01
The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8% of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15% of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83%. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3% of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.
Relationships between aerodynamic roughness and land use and land cover in Baltimore, Maryland
Nicholas, F.W.; Lewis, J.E.
1980-01-01
Urbanization changes the radiative, thermal, hydrologic, and aerodynamic properties of the Earth's surface. Knowledge of these surface characteristics, therefore, is essential to urban climate analysis. Aerodynamic or surface roughness of urban areas is not well documented, however, because of practical constraints in measuring the wind profile in the presence of large buildings. Using an empirical method designed by Lettau, and an analysis of variance of surface roughness values calculated for 324 samples averaging 0.8 hectare (ha) of land use and land cover sample in Baltimore, Md., a strong statistical relation was found between aerodynamic roughness and urban land use and land cover types. Assessment of three land use and land cover systems indicates that some of these types have significantly different surface roughness characteristics. The tests further indicate that statistically significant differences exist in estimated surface roughness values when categories (classes) from different land use and land cover classification systems are used as surrogates. A Level III extension of the U.S. Geological Survey Level II land use and land cover classification system provided the most reliable results. An evaluation of the physical association between the aerodynamic properties of land use and land cover and the surface climate by numerical simulation of the surface energy balance indicates that changes in surface roughness within the range of values typical of the Level III categories induce important changes in the surface climate.
Recovery of coral cover in records spanning 44 yr for reefs in Kāne`ohe Bay, Oa`hu, Hawai`i
NASA Astrophysics Data System (ADS)
Stimson, John
2018-03-01
Published and unpublished long-term studies are assembled to examine trends in coral cover and the dependence of change in coral cover on the initial coral cover in Kāne`ohe Bay over the last 44 yr. Each study showed there had been periods of increase in coral cover in the bay and showed that the rate of change in cover has been inversely dependent on the initial cover at a site. When coral cover is high on upper reef slopes, the fragile structure of reefs in this sheltered bay often collapses, resulting in a decrease in coral cover. The rate of change in coral cover was also inversely dependent on cover in one of the two studies that included analysis of reef-flat corals; the cause of decrease in cover in this habitat is thought to be attributable to particularly low sea levels in Hawai`i in the late 1990s and 2009-2010. The inverse relationship between initial coral cover and change in cover, and the intersections of the regression lines of these variables with the x-axis at intermediate values of coral cover, is indicative of resilience in this ecosystem over the last 44 yr. In the 1970s, the invasive macroscopic green alga Dictyosphaeria cavernosa covered a high percentage of coral habitat and commonly displaced corals from the reef slope and outer reef flats; the change was cited as an example of a phase shift on a reef. This alga has virtually disappeared from the bay, thus increasing the space available to corals; its disappearance is coincident with the increase in coral cover. Other species of macroalgae, including alien species, have not replaced D. cavernosa as major space competitors. The increase in coral cover and virtual disappearance of D. cavernosa constitute an example of a phase-shift reversal.
Characteristics of phonation onset in a two-layer vocal fold model.
Zhang, Zhaoyan
2009-02-01
Characteristics of phonation onset were investigated in a two-layer body-cover continuum model of the vocal folds as a function of the biomechanical and geometric properties of the vocal folds. The analysis showed that an increase in either the body or cover stiffness generally increased the phonation threshold pressure and phonation onset frequency, although the effectiveness of varying body or cover stiffness as a pitch control mechanism varied depending on the body-cover stiffness ratio. Increasing body-cover stiffness ratio reduced the vibration amplitude of the body layer, and the vocal fold motion was gradually restricted to the medial surface, resulting in more effective flow modulation and higher sound production efficiency. The fluid-structure interaction induced synchronization of more than one group of eigenmodes so that two or more eigenmodes may be simultaneously destabilized toward phonation onset. At certain conditions, a slight change in vocal fold stiffness or geometry may cause phonation onset to occur as eigenmode synchronization due to a different pair of eigenmodes, leading to sudden changes in phonation onset frequency, vocal fold vibration pattern, and sound production efficiency. Although observed in a linear stability analysis, a similar mechanism may also play a role in register changes at finite-amplitude oscillations.
Simulating urban land cover changes at sub-pixel level in a coastal city
NASA Astrophysics Data System (ADS)
Zhao, Xiaofeng; Deng, Lei; Feng, Huihui; Zhao, Yanchuang
2014-10-01
The simulation of urban expansion or land cover changes is a major theme in both geographic information science and landscape ecology. Yet till now, almost all of previous studies were based on grid computations at pixel level. With the prevalence of spectral mixture analysis in urban land cover research, the simulation of urban land cover at sub-pixel level is being put into agenda. This study provided a new approach of land cover simulation at sub-pixel level. Landsat TM/ETM+ images of Xiamen city, China on both the January of 2002 and 2007 were used to acquire land cover data through supervised classification. Then the two classified land cover data were utilized to extract the transformation rule between 2002 and 2007 using logistic regression. The transformation possibility of each land cover type in a certain pixel was taken as its percent in the same pixel after normalization. And cellular automata (CA) based grid computation was carried out to acquire simulated land cover on 2007. The simulated 2007 sub-pixel land cover was testified with a validated sub-pixel land cover achieved by spectral mixture analysis in our previous studies on the same date. And finally the sub-pixel land cover of 2017 was simulated for urban planning and management. The results showed that our method is useful in land cover simulation at sub-pixel level. Although the simulation accuracy is not quite satisfactory for all the land cover types, it provides an important idea and a good start in the CA-based urban land cover simulation.
Land Cover Change in the Boston Mountains, 1973-2000
Karstensen, Krista A.
2009-01-01
The U.S. Geological Survey (USGS) Land Cover Trends project is focused on understanding the rates, trends, causes, and consequences of contemporary U.S. land-cover change. The objectives of the study are to: (1) to develop a comprehensive methodology for using sampling and change analysis techniques and Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) data to measure regional land-cover change across the United States; (2) to characterize the types, rates, and temporal variability of change for a 30-year period; (3) to document regional driving forces and consequences of change; and (4) to prepare a national synthesis of land-cover change (Loveland and others, 1999). The 1999 Environmental Protection Agency (EPA) Level III ecoregions derived from Omernik (1987) provide the geographic framework for the geospatial data collected between 1973 and 2000. The 27-year study period was divided into five temporal periods: 1973-1980, 1980-1986, 1986-1992, 1992-2000, and 1973-2000, and the data are evaluated using a modified Anderson Land Use Land Cover Classification System (Anderson and others, 1976) for image interpretation. The rates of land-cover change are estimated using a stratified, random sampling of 10-kilometer (km) by 10-km blocks allocated within each ecoregion. For each sample block, satellite images are used to interpret land-cover change for the five time periods previously mentioned. Additionally, historic aerial photographs from similar time frames and other ancillary data, such as census statistics and published literature, are used. The sample block data are then incorporated into statistical analyses to generate an overall change matrix for the ecoregion. Field data of the sample blocks include direct measurements of land cover, particularly ground-survey data collected for training and validation of image classifications (Loveland and others, 2002). The field experience allows for additional observations of the character and condition of the landscape, assistance in sample block interpretation, ground truthing of Landsat imagery, and determination of the driving forces of change identified in an ecoregion.
Status and trends of land change in the United States--1973 to 2000
,
2012-01-01
U.S. Geological Survey (USGS) Professional Paper 1794 is a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the United States between 1973 and 2000. Volumes A, B, C, and D provide analyses for the Western United States, the Great Plains, the Midwest–South Central United States, and the Eastern United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation. This report is only one of the products produced by USGS on land-use and land-cover change in the United States. Other reports and land-cover statistics are available online at http://landcovertrends.usgs.gov.
NASA Astrophysics Data System (ADS)
Ban, Yifang; Gong, Peng; Gamba, Paolo; Taubenbock, Hannes; Du, Peijun
2016-08-01
The overall objective of this research is to investigate multi-temporal, multi-scale, multi-sensor satellite data for analysis of urbanization and environmental/climate impact in China to support sustainable planning. Multi- temporal multi-scale SAR and optical data have been evaluated for urban information extraction using innovative methods and algorithms, including KTH- Pavia Urban Extractor, Pavia UEXT, and an "exclusion- inclusion" framework for urban extent extraction, and KTH-SEG, a novel object-based classification method for detailed urban land cover mapping. Various pixel- based and object-based change detection algorithms were also developed to extract urban changes. Several Chinese cities including Beijing, Shanghai and Guangzhou are selected as study areas. Spatio-temporal urbanization patterns and environmental impact at regional, metropolitan and city core were evaluated through ecosystem service, landscape metrics, spatial indices, and/or their combinations. The relationship between land surface temperature and land-cover classes was also analyzed.The urban extraction results showed that urban areas and small towns could be well extracted using multitemporal SAR data with the KTH-Pavia Urban Extractor and UEXT. The fusion of SAR data at multiple scales from multiple sensors was proven to improve urban extraction. For urban land cover mapping, the results show that the fusion of multitemporal SAR and optical data could produce detailed land cover maps with improved accuracy than that of SAR or optical data alone. Pixel-based and object-based change detection algorithms developed with the project were effective to extract urban changes. Comparing the urban land cover results from mulitemporal multisensor data, the environmental impact analysis indicates major losses for food supply, noise reduction, runoff mitigation, waste treatment and global climate regulation services through landscape structural changes in terms of decreases in service area, edge contamination and fragmentation. In terms ofclimate impact, the results indicate that land surface temperature can be related to land use/land cover classes.
Multi-Scale Fractal Analysis of Image Texture and Pattern
NASA Technical Reports Server (NTRS)
Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.
1999-01-01
Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images is the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimension-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.
Multi-Scale Fractal Analysis of Image Texture and Pattern
NASA Technical Reports Server (NTRS)
Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.
1999-01-01
Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images of the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimensional-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.
Impacts of land cover transitions on surface temperature in China based on satellite observations
NASA Astrophysics Data System (ADS)
Zhang, Yuzhen; Liang, Shunlin
2018-02-01
China has experienced intense land use and land cover changes during the past several decades, which have exerted significant influences on climate change. Previous studies exploring related climatic effects have focused mainly on one or two specific land use changes, or have considered all land use and land cover change types together without distinguishing their individual impacts, and few have examined the physical processes of the mechanism through which land use changes affect surface temperature. However, in this study, we considered satellite-derived data of multiple land cover changes and transitions in China. The objective was to obtain observational evidence of the climatic effects of land cover transitions in China by exploring how they affect surface temperature and to what degree they influence it through the modification of biophysical processes, with an emphasis on changes in surface albedo and evapotranspiration (ET). To achieve this goal, we quantified the changes in albedo, ET, and surface temperature in the transition areas, examined their correlations with temperature change, and calculated the contributions of different land use transitions to surface temperature change via changes in albedo and ET. Results suggested that land cover transitions from cropland to urban land increased land surface temperature (LST) during both daytime and nighttime by 0.18 and 0.01 K, respectively. Conversely, the transition of forest to cropland tended to decrease surface temperature by 0.53 K during the day and by 0.07 K at night, mainly through changes in surface albedo. Decreases in both daytime and nighttime LST were observed over regions of grassland to forest transition, corresponding to average values of 0.44 and 0.20 K, respectively, predominantly controlled by changes in ET. These results highlight the necessity to consider the individual climatic effects of different land cover transitions or conversions in climate research studies. This short-term analysis of land cover transitions in China means our estimates should represent local temperature effects. Changes in ET and albedo explained <60% of the variation in LST change caused by land cover transitions; thus, additional factors that affect surface climate need consideration in future studies.
NASA Astrophysics Data System (ADS)
Lucas, M.; Trauernicht, C.; Carlson, K. M.; Miura, T.; Giambelluca, T. W.; Chen, Q.
2017-12-01
The past decades in Hawaii have seen large scale land use change and land cover shifts. However, much these dynamics are only described anecdotally or studied at a single locale, with little information on the extent, rate, or direction of change. This lack of data hinders any effort to assess, plan, and prioritize land management. To improve assessments of statewide vegetation and land cover change, this project developed high resolution, sub-pixel, percent cover maps of forest, grassland and bare earth at annual time steps from 1999 to 2016. Vegetation cover was quantified using archived LANDSAT imagery and a custom remote-sensing algorithm developed in the Google Earth Engine platform. A statistical trend analysis of annual maps of the these three proportional land covers were then used to detect land cover transitions across the archipelago. The aim of this work focused on quantifying the total area of change, annual rates of change and final vegetation cover outcomes statewide. Additionally these findings were attributed to past and current land uses and management history by compiling spatial datasets of development, agriculture, forest restoration sites and burned areas statewide. Results indicated that nearly 10% of the state's land surfaces are suspected to have transitioned between the three cover classes during the study period. Total statewide net change resulted in a gain in forest cover with largest areas of change occurring in unmanaged areas, current and past pastoral land, commercial forestry and abandoned cultivated land. The fastest annual rates of change were forest increases that occurred in restoration areas and commercial forestry. These findings indicate that Hawaii is going through a forest transition, primarily driven by agricultural abandonment with likely feedbacks from invasive species, but also influenced by the establishment of forestry production on former agricultural lands that show potential for native forest restoration. These results directly link land management history to land cover outcomes using an innovative approach to quantify change. It is also the first study to quantify forest transition dynamics in Hawaii and points to the need for similar assessments in post-agricultural landscapes on other oceanic islands.
Development of deforestation and land cover database for Bhutan (1930-2014).
Reddy, C Sudhakar; Satish, K V; Jha, C S; Diwakar, P G; Murthy, Y V N Krishna; Dadhwal, V K
2016-12-01
Bhutan is a mountainous country located in the Himalayan biodiversity hotspot. This study has quantified the total area under land cover types, estimated the rate of forest cover change, analyzed the changes across forest types, and modeled forest cover change hotpots in Bhutan. The topographical maps and satellite remote sensing images were analyzed to get the spatial patterns of forest and associated land cover changes over the past eight decades (1930-1977-1987-1995-2005-2014). Forest is the largest land cover in Bhutan and constitutes 68.3% of the total geographical area in 2014. Subtropical broad leaved hill forest is predominant type occupies 34.1% of forest area in Bhutan, followed by montane dry temperate (20.9%), montane wet temperate (18.9%), Himalayan moist temperate (10%), and tropical moist sal (8.1%) in 2014. The major forest cover loss is observed in subtropical broad leaved hill forest (64.5 km 2 ) and moist sal forest (9.9 km 2 ) from 1977 to 2014. The deforested areas have mainly been converted into agriculture and contributed for 60.9% of forest loss from 1930 to 2014. In spite of major decline of forest cover in time interval of 1930-1977, there is no net rate of deforestation is recorded in Bhutan since 1995. Forest cover change analysis has been carried out to evaluate the conservation effectiveness in "Protected Areas" of Bhutan. Hotspots that have undergone high transformation in forest cover for afforestation and deforestation were highlighted in the study for conservation prioritisation. Forest conservation policies in Bhutan are highly effective in controlling deforestation as compared to neighboring Asian countries and such service would help in mitigating climate change.
NASA Astrophysics Data System (ADS)
Zoran, Maria A.; Dida, Adrian I.
2017-10-01
Urban green areas are experiencing rapid land cover change caused by human-induced land degradation and extreme climatic events. Vegetation index time series provide a useful way to monitor urban vegetation phenological variations. This study quantitatively describes Normalized Difference Vegetation Index NDVI) /Enhanced Vegetation Index (EVI) and Leaf Area Index (LAI) temporal changes for Bucharest metropolitan region land cover in Romania from the perspective of vegetation phenology and its relation with climate changes and extreme climate events. The time series from 2000 to 2016 of the NOAA AVHRR and MODIS Terra/Aqua satellite data were analyzed to extract anomalies. Time series of climatic variables were also analyzed through anomaly detection techniques and the Fourier Transform. Correlations between NDVI/EVI time series and climatic variables were computed. Temperature, rainfall and radiation were significantly correlated with almost all land-cover classes for the harmonic analysis amplitude term. However, vegetation phenology was not correlated with climatic variables for the harmonic analysis phase term suggesting a delay between climatic variations and vegetation response. Training and validation were based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2000- 2016 was assessed to be of 87%, with a reasonable balance between change commission errors (19.3%), change omission errors (24.7%), and Kappa coefficient of 0.73. This paper demonstrates the potential of moderate - and high resolution, multispectral imagery to map and monitor the evolution of the physical urban green land cover under climate and anthropogenic pressure.
Jiang, Penghui; Cheng, Liang; Li, Manchun; Zhao, Ruifeng; Duan, Yuewei
2015-02-15
Large-scale changes in land use and land cover over long timescales can induce significant variations in soil physicochemical properties, particularly in the riparian zones of arid regions. Frequent reclamation of wetlands and grasslands and intensive agricultural activity have induced significant changes in both land use/cover and soil physicochemical properties in the riparian zones of the middle Heihe River basin of China. The present study aims to explore whether land use/land cover change (LUCC) can well explain the variations in soil properties in the riparian zones of the middle Heihe River basin. To achieve this, we mapped LUCC and quantified the type of land use change using remote sensing images, topographic maps, and GIS analysis techniques. Forty-two sites were selected for soil and vegetation sampling. Then, physical and chemical experiments were employed to determine soil moisture, soil bulk density, soil pH, soil organic carbon, total nitrogen, total potassium, total phosphorous, available nitrogen, available potassium, and available phosphorous. The Independent-Samples Kruskal-Wallis Test, principal component analysis, and a scatter matrix were used to analyze the effects of LUCC on soil properties. The results indicate that the majority of the parameters investigated were affected significantly by LUCC. In particular, soil moisture and soil organic carbon can be explained well by land cover change and land use change, respectively. Furthermore, changes in soil moisture could be attributed primarily to land cover changes. Changes in soil organic carbon were correlated closely with the following land use change types: wetlands-arable, forest-grasslands, and grasslands-desert. Other parameters, including pH and total K, were also found to exhibit significant correlations with LUCC. However, changes in soil nutrients were shown to be induced most probably by human agricultural activity (i.e. fertilize, irrigation, tillage, etc.), rather than by simple conversions from one land use/cover types to the others. Copyright © 2014 Elsevier B.V. All rights reserved.
Operational monitoring of land-cover change using multitemporal remote sensing data
NASA Astrophysics Data System (ADS)
Rogan, John
2005-11-01
Land-cover change, manifested as either land-cover modification and/or conversion, can occur at all spatial scales, and changes at local scales can have profound, cumulative impacts at broader scales. The implication of operational land-cover monitoring is that researchers have access to a continuous stream of remote sensing data, with the long term goal of providing for consistent and repetitive mapping. Effective large area monitoring of land-cover (i.e., >1000 km2) can only be accomplished by using remotely sensed images as an indirect data source in land-cover change mapping and as a source for land-cover change model projections. Large area monitoring programs face several challenges: (1) choice of appropriate classification scheme/map legend over large, topographically and phenologically diverse areas; (2) issues concerning data consistency and map accuracy (i.e., calibration and validation); (3) very large data volumes; (4) time consuming data processing and interpretation. Therefore, this dissertation research broadly addresses these challenges in the context of examining state-of-the-art image pre-processing, spectral enhancement, classification, and accuracy assessment techniques to assist the California Land-cover Mapping and Monitoring Program (LCMMP). The results of this dissertation revealed that spatially varying haze can be effectively corrected from Landsat data for the purposes of change detection. The Multitemporal Spectral Mixture Analysis (MSMA) spectral enhancement technique produced more accurate land-cover maps than those derived from the Multitemporal Kauth Thomas (MKT) transformation in northern and southern California study areas. A comparison of machine learning classifiers showed that Fuzzy ARTMAP outperformed two classification tree algorithms, based on map accuracy and algorithm robustness. Variation in spatial data error (positional and thematic) was explored in relation to environmental variables using geostatistical interpolation techniques. Finally, the land-cover modification maps generated for three time intervals (1985--1990--1996--2000), with nine change-classes revealed important variations in land-cover gain and loss between northern and southern California study areas.
NASA Astrophysics Data System (ADS)
Wijaya, A.; Sugardiman Budiharto, R. A.; Tosiani, A.; Murdiyarso, D.; Verchot, L. V.
2015-04-01
Indonesia possesses the third largest tropical forests coverage following Brazilian Amazon and Congo Basin regions. This country, however, suffered from the highest deforestation rate surpassing deforestation in the Brazilian Amazon in 2012. National capacity for forest change assessment and monitoring has been well-established in Indonesia and the availability of national forest inventory data could largely assist the country to report their forest carbon stocks and change over more than two decades. This work focuses for refining forest cover change mapping and deforestation estimate at national scale applying over 10,000 scenes of Landsat scenes, acquired in 1990, 1996, 2000, 2003, 2006, 2009, 2011 and 2012. Pre-processing of the data includes, geometric corrections and image mosaicking. The classification of mosaic Landsat data used multi-stage visual observation approaches, verified using ground observations and comparison with other published materials. There are 23 land cover classes identified from land cover data, presenting spatial information of forests, agriculture, plantations, non-vegetated lands and other land use categories. We estimated the magnitude of forest cover change and assessed drivers of forest cover change over time. Forest change trajectories analysis was also conducted to observe dynamics of forest cover across time. This study found that careful interpretations of satellite data can provide reliable information on forest cover and change. Deforestation trend in Indonesia was lower in 2000-2012 compared to 1990-2000 periods. We also found that over 50% of forests loss in 1990 remains unproductive in 2012. Major drivers of forest conversion in Indonesia range from shrubs/open land, subsistence agriculture, oil palm expansion, plantation forest and mining. The results were compared with other available datasets and we obtained that the MOF data yields reliable estimate of deforestation.
Hamada, Yuki; Stow, Douglas A; Roberts, Dar A; Franklin, Janet; Kyriakidis, Phaedon C
2013-04-01
Arid and semi-arid shrublands have significant biological and economical values and have been experiencing dramatic changes due to human activities. In California, California sage scrub (CSS) is one of the most endangered plant communities in the US and requires close monitoring in order to conserve this important biological resource. We investigate the utility of remote-sensing approaches--object-based image analysis applied to pansharpened QuickBird imagery (QBPS/OBIA) and multiple endmember spectral mixture analysis (MESMA) applied to SPOT imagery (SPOT/MESMA)--for estimating fractional cover of true shrub, subshrub, herb, and bare ground within CSS communities of southern California. We also explore the effectiveness of life-form cover maps for assessing CSS conditions. Overall and combined shrub cover (i.e., true shrub and subshrub) were estimated more accurately using QBPS/OBIA (mean absolute error or MAE, 8.9 %) than SPOT/MESMA (MAE, 11.4 %). Life-form cover from QBPS/OBIA at a 25 × 25 m grid cell size seems most desirable for assessing CSS because of its higher accuracy and spatial detail in cover estimates and amenability to extracting other vegetation information (e.g., size, shape, and density of shrub patches). Maps derived from SPOT/MESMA at a 50 × 50 m scale are effective for retrospective analysis of life-form cover change because their comparable accuracies to QBPS/OBIA and availability of SPOT archives data dating back to the mid-1980s. The framework in this study can be applied to other physiognomically comparable shrubland communities.
Coskun, H Gonca; Alganci, Ugur; Usta, Gokce
2008-11-13
Accurate and timely information about land use and land cover (LULC) and its changes in urban areas are crucial for urban land management decision-making, ecosystem monitoring and urban planning. Also, monitoring and representation of urban sprawl and its effects on the LULC patterns and hydrological processes of an urbanized watershed is an essential part of water resource planning and management. This paper presents an image analysis study using multi temporal digital satellite imagery of LULC and changes in the Kucukcekmece Watershed (Metropolitan Istanbul, Turkey) from 1992 to 2006. The Kucukcekmece Basin includes portions of the Kucukcekmece District within the municipality of Istanbul so it faces a dramatic urbanization. An urban monitoring analysis approach was first used to implement a land cover classification. A change detection method controlled with ground truth information was then used to determine changes in land cover. During the study period, the variability and magnitude of hydrological components based on land-use patterns were cumulatively influenced by urban sprawl in the watershed. The proposed approach, which uses a combination of Remote Sensing (RS) and Geographical Information System (GIS) techniques, is an effective tool that enhances land-use monitoring, planning, and management of urbanized watersheds.
Coskun, H. Gonca; Alganci, Ugur; Usta, Gokce
2008-01-01
Accurate and timely information about land use and land cover (LULC) and its changes in urban areas are crucial for urban land management decision-making, ecosystem monitoring and urban planning. Also, monitoring and representation of urban sprawl and its effects on the LULC patterns and hydrological processes of an urbanized watershed is an essential part of water resource planning and management. This paper presents an image analysis study using multi temporal digital satellite imagery of LULC and changes in the Kucukcekmece Watershed (Metropolitan Istanbul, Turkey) from 1992 to 2006. The Kucukcekmece Basin includes portions of the Kucukcekmece District within the municipality of Istanbul so it faces a dramatic urbanization. An urban monitoring analysis approach was first used to implement a land cover classification. A change detection method controlled with ground truth information was then used to determine changes in land cover. During the study period, the variability and magnitude of hydrological components based on land-use patterns were cumulatively influenced by urban sprawl in the watershed. The proposed approach, which uses a combination of Remote Sensing (RS) and Geographical Information System (GIS) techniques, is an effective tool that enhances land-use monitoring, planning, and management of urbanized watersheds. PMID:27873924
Time series change detection: Algorithms for land cover change
NASA Astrophysics Data System (ADS)
Boriah, Shyam
The climate and earth sciences have recently undergone a rapid transformation from a data-poor to a data-rich environment. In particular, climate and ecosystem related observations from remote sensors on satellites, as well as outputs of climate or earth system models from large-scale computational platforms, provide terabytes of temporal, spatial and spatio-temporal data. These massive and information-rich datasets offer huge potential for advancing the science of land cover change, climate change and anthropogenic impacts. One important area where remote sensing data can play a key role is in the study of land cover change. Specifically, the conversion of natural land cover into humandominated cover types continues to be a change of global proportions with many unknown environmental consequences. In addition, being able to assess the carbon risk of changes in forest cover is of critical importance for both economic and scientific reasons. In fact, changes in forests account for as much as 20% of the greenhouse gas emissions in the atmosphere, an amount second only to fossil fuel emissions. Thus, there is a need in the earth science domain to systematically study land cover change in order to understand its impact on local climate, radiation balance, biogeochemistry, hydrology, and the diversity and abundance of terrestrial species. Land cover conversions include tree harvests in forested regions, urbanization, and agricultural intensification in former woodland and natural grassland areas. These types of conversions also have significant public policy implications due to issues such as water supply management and atmospheric CO2 output. In spite of the importance of this problem and the considerable advances made over the last few years in high-resolution satellite data, data mining, and online mapping tools and services, end users still lack practical tools to help them manage and transform this data into actionable knowledge of changes in forest ecosystems that can be used for decision making and policy planning purposes. In particular, previous change detection studies have primarily relied on examining differences between two or more satellite images acquired on different dates. Thus, a technological solution that detects global land cover change using high temporal resolution time series data will represent a paradigm-shift in the field of land cover change studies. To realize these ambitious goals, a number of computational challenges in spatio-temporal data mining need to be addressed. Specifically, analysis and discovery approaches need to be cognizant of climate and ecosystem data characteristics such as seasonality, non-stationarity/inter-region variability, multi-scale nature, spatio-temporal autocorrelation, high-dimensionality and massive data size. This dissertation, a step in that direction, translates earth science challenges to computer science problems, and provides computational solutions to address these problems. In particular, three key technical capabilities are developed: (1) Algorithms for time series change detection that are effective and can scale up to handle the large size of earth science data; (2) Change detection algorithms that can handle large numbers of missing and noisy values present in satellite data sets; and (3) Spatio-temporal analysis techniques to identify the scale and scope of disturbance events.
Influence of Western Tibetan Plateau Summer Snow Cover on East Asian Summer Rainfall
NASA Astrophysics Data System (ADS)
Wang, Zhibiao; Wu, Renguang; Chen, Shangfeng; Huang, Gang; Liu, Ge; Zhu, Lihua
2018-03-01
The influence of boreal winter-spring eastern Tibetan Plateau snow anomalies on the East Asian summer rainfall variability has been the focus of previous studies. The present study documents the impacts of boreal summer western and southern Tibetan Plateau snow cover anomalies on summer rainfall over East Asia. Analysis shows that more snow cover in the western and southern Tibetan Plateau induces anomalous cooling in the overlying atmospheric column. The induced atmospheric circulation changes are different corresponding to more snow cover in the western and southern Tibetan Plateau. The atmospheric circulation changes accompanying the western Plateau snow cover anomalies are more obvious over the midlatitude Asia, whereas those corresponding to the southern Plateau snow cover anomalies are more prominent over the tropics. As such, the western and southern Tibetan Plateau snow cover anomalies influence the East Asian summer circulation and precipitation through different pathways. Nevertheless, the East Asian summer circulation and precipitation anomalies induced by the western and southern Plateau snow cover anomalies tend to display similar distribution so that they are more pronounced when the western and southern Plateau snow cover anomalies work in coherence. Analysis indicates that the summer snow cover anomalies over the Tibetan Plateau may be related to late spring snow anomalies due to the persistence. The late spring snow anomalies are related to an obvious wave train originating from the western North Atlantic that may be partly associated with sea surface temperature anomalies in the North Atlantic Ocean.
Steen, Paul J.; Wiley, Michael J.; Schaeffer, Jeffrey S.
2010-01-01
Future alterations in land cover and climate are likely to cause substantial changes in the ranges of fish species. Predictive distribution models are an important tool for assessing the probability that these changes will cause increases or decreases in or the extirpation of species. Classification tree models that predict the probability of game fish presence were applied to the streams of the Muskegon River watershed, Michigan. The models were used to study three potential future scenarios: (1) land cover change only, (2) land cover change and a 3°C increase in air temperature by 2100, and (3) land cover change and a 5°C increase in air temperature by 2100. The analysis indicated that the expected change in air temperature and subsequent change in water temperatures would result in the decline of coldwater fish in the Muskegon watershed by the end of the 21st century while cool- and warmwater species would significantly increase their ranges. The greatest decline detected was a 90% reduction in the probability that brook trout Salvelinus fontinalis would occur in Bigelow Creek. The greatest increase was a 276% increase in the probability that northern pike Esox lucius would occur in the Middle Branch River. Changes in land cover are expected to cause large changes in a few fish species, such as walleye Sander vitreus and Chinook salmon Oncorhynchus tshawytscha, but not to drive major changes in species composition. Managers can alter stream environmental conditions to maximize the probability that species will reside in particular stream reaches through application of the classification tree models. Such models represent a good way to predict future changes, as they give quantitative estimates of the n-dimensional niches for particular species.
Land-cover change in the Ozark Highlands, 1973-2000
Karstensen, Krista A.
2010-01-01
Led by the Geographic Analysis and Monitoring Program of the U.S. Geological Survey (USGS) in collaboration with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA), the Land-Cover Trends Project was initiated in 1999 and aims to document the types, geographic distributions, and rates of land-cover change on a region by region basis for the conterminous United States, and to determine some of the key drivers and consequences of the change (Loveland and others, 2002). For 1973, 1980, 1986, 1992, and 2000 land-cover maps derived from the Landsat series are classified by visual interpretation, inspection of historical aerial photography and ground survey, into 11 land-cover classes. The classes are defined to capture land cover that is discernable in Landsat data. A stratified probability-based sampling methodology undertaken within the 84 Omernik Level III Ecoregions (Omernik, 1987) was used to locate the blocks, with 9 to 48 blocks per ecoregion. The sampling was designed to enable a statistically robust 'scaling up' of the sample-classification data to estimate areal land-cover change within each ecoregion (Loveland and others, 2002; Stehman and others, 2005). At the time of writing, approximately 90 percent of the 84 conterminous United States ecoregions have been processed by the Land-Cover Trends Project. Results from these completed ecoregions illustrate that across the conterminous United States there is no single profile of land-cover/land-use change, rather, there are varying pulses affected by clusters of change agents (Loveland and others, 2002). Land-Cover Trends Project results for the conterminous United States to-date are being used for collaborative environmental change research with partners such as; the National Science Foundation, the National Oceanic and Atmospheric Administration, and the U.S. Fish and Wildlife Service. The strategy has also been adapted for use in a NASA global deforestation initiative, and elements of the project design are being used in the North American Carbon Program's assessment of forest disturbance.
NASA Astrophysics Data System (ADS)
Regi, Mauro; Redaelli, Gianluca; Francia, Patrizia; De Lauretis, Marcello
2017-06-01
In the present study we investigated the possible relationship between the ULF geomagnetic activity and the variations of several atmospheric parameters. In particular, we compared the ULF activity in the Pc1-2 frequency band (100 mHz-5 Hz), computed from geomagnetic field measurements at Terra Nova Bay in Antarctica, with the tropospheric temperature T, specific humidity Q, and cloud cover (high cloud cover, medium cloud cover, and low cloud cover) obtained from reanalysis data set. The statistical analysis was conducted during the years 2003-2010, using correlation and Superposed Epoch Analysis approaches. The results show that the atmospheric parameters significantly change following the increase of geomagnetic activity within 2 days. These changes are evident in particular when the interplanetary magnetic field Bz component is oriented southward (Bz<0) and the By component duskward (By>0). We suggest that both the precipitation of electrons induced by Pc1-2 activity and the intensification of the polar cap potential difference, modulating the microphysical processes in the clouds, can affect the atmosphere conditions.
Gould, William A.; Martinuzzi, Sebastián; Pares-Ramos, Isabel K.; Murphy, Sheila F.; Stallard, Robert F.; Murphy, Sheila F.; Stallard, Robert F.
2012-01-01
We assessed current and historic land use and land cover in the Luquillo Mountains and surrounding area in eastern Puerto Rico, including four small subwatersheds that are study watersheds of the U.S. Geological Survey's Water, Energy, and Biogeochemical Budgets (WEBB) program. This region occupies an area of 1,616 square kilometers, about 18 percent of the total land in Puerto Rico. Closed forests occupy about 37 percent of the area, woodlands and shrublands 7 percent, nonforest vegetation 43 percent, urban development 10 percent, and water and natural barrens total less than 2 percent. The area has been classified into three main land-use categories by integrating recent census information (population density per barrio in the year 2000) with satellite image analyses (degree of developed area versus natural land cover). Urban land use (in this analysis, land with more than 20 percent developed cover within a 1-square-kilometer area and population density greater than 500 people per square kilometer) covered 16 percent of eastern Puerto Rico. Suburban land use (more than 80 percent natural land cover, more than 500 people per square kilometer, and primarily residential) covers 50 percent of the area. Rural land use (more than 80 percent natural land cover, less than 500 people per square kilometer, and primarily active or abandoned agricultural, wetland, steep slope, or protected conservation areas) covered 34 percent of the area. Our analysis of land-cover change indicates that in the 1990s, forest cover increased at the expense of woodlands and grasslands. Urban development increased by 16 percent during that time. The most pronounced change in the last seven decades has been the shift from a nonforested to a forested landscape and the intensification of the ring of urbanization that surrounds the long-protected Luquillo Experimental Forest.
Sharma, Mohit; Areendran, G; Raj, Krishna; Sharma, Ankita; Joshi, P K
2016-10-01
Forests in the mountains are a treasure trove; harbour a large biodiversity; and provide fodder, firewood, timber and non-timber forest products; all of these are essential for human survival in the highest mountains on earth. The present paper attempts a spatiotemporal assessment of forest fragmentation and changes in land use land cover (LULC) pattern using multitemporal satellite data over a time span of around a decade (2000-2009), within the third highest protected area (PA) in the world. The fragmentation analysis using Landscape Fragmentation Tool (LFT) depicts a decrease in large core, edge and patches areas by 5.93, 3.64 and 0.66 %, respectively, while an increase in non-forest and perforated areas by 6.59 and 4.01 %, respectively. The land cover dynamics shows a decrease in open forest, alpine scrub, alpine meadows, snow and hill shadow areas by 2.81, 0.39, 8.18, 3.46 and 0.60 %, respectively, and there is an increase in dense forest and glacier area by 4.79 and 10.65 %, respectively. The change analysis shows a major transformation in areas from open forest to dense forest and from alpine meadows to alpine scrub. In order to quantify changes induced by forest fragmentation and to characterize composition and configuration of LULC mosaics, fragmentation indices were computed using Fragstats at class level, showing the signs of accelerated fragmentation. The outcome of the analysis revealed the effectiveness of geospatial tools coupled with landscape ecology in characterization and quantification of forest fragmentation and land cover changes. The present study provides a baseline database for sustainable conservation planning that will benefit the subsistence livelihoods in the region. Recommendations made based on the present analysis will help to recover forest and halt the pessimistic effects of fragmentation and land cover changes on biodiversity and ecosystem services in the region.
NASA Astrophysics Data System (ADS)
Turubanova, S.; Potapov, P.; Krylov, A.; Tyukavina, A.; McCarty, J. L.; Radeloff, V. C.; Hansen, M. C.
2015-04-01
Dramatic political and economic changes in Eastern European countries following the dissolution of the "Eastern Bloc" and the collapse of the Soviet Union greatly affected land-cover and land-use trends. In particular, changes in forest cover dynamics may be attributed to the collapse of the planned economy, agricultural land abandonment, economy liberalization, and market conditions. However, changes in forest cover are hard to quantify given inconsistent forest statistics collected by different countries over the last 30 years. The objective of our research was to consistently quantify forest cover change across Eastern Europe from 1985 until 2012 using the complete Landsat data archive. We developed an algorithm for processing imagery from different Landsat platforms and sensors (TM and ETM+), aggregating these images into a common set of multi-temporal metrics, and mapping annual gross forest cover loss and decadal gross forest cover gain. Our results show that forest cover area increased from 1985 to 2012 by 4.7% across the region. Average annual gross forest cover loss was 0.41% of total forest cover area, with a statistically significant increase from 1985 to 2012. Most forest disturbance recovered fast, with only 12% of the areas of forest loss prior to 1995 not being recovered by 2012. Timber harvesting was the main cause of forest loss. Logging area declined after the collapse of socialism in the late 1980s, increased in the early 2000s, and decreased in most countries after 2007 due to the global economic crisis. By 2012, Central and Baltic Eastern European countries showed higher logging rates compared to their Western neighbours. Comparing our results with official forest cover and change estimates showed agreement in total forest area for year 2010, but with substantial disagreement between Landsat-based and official net forest cover area change. Landsat-based logging areas exhibit strong relationship with reported roundwood production at national scale. Our results allow national and sub-national level analysis of forest cover extent, change, and logging intensity and are available on-line as a baseline for further analyses of forest dynamics and its drivers.
NASA Astrophysics Data System (ADS)
Rahaman, S. A.; Aruchamy, S.; Balasubramani, K.; Jegankumar, R.
2017-05-01
Nowadays land use/ land cover in mountain landscape is in critical condition; it leads to high risky and uncertain environments. These areas are facing multiple stresses including degradation of land resources; vagaries of climate and depletion of water resources continuously affect land use practices and livelihoods. To understand the Land use/Land cover (Lu/Lc) changes in a semi-arid mountain landscape, Kallar watershed of Bhavani basin, in southern India has been chosen. Most of the hilly part in the study area covers with forest, plantation, orchards and vegetables and which are highly affected by severe soil erosion, landslide, frequent rainfall failures and associated drought. The foothill regions are mainly utilized for agriculture practices; due to water scarcity and meagre income, the productive agriculture lands are converted into settlement plots and wasteland. Hence, land use/land cover change deduction; a stochastic processed based method is indispensable for future prediction. For identification of land use/land cover, and vegetation changes, Landsat TM, ETM (1995, 2005) and IRS P6- LISS IV (2015) images were used. Through CAMarkov chain analysis, Lu/Lc changes in past three decades (1995, 2005, and 2015) were identified and projected for (2020 and 2025); Normalized Difference Vegetation Index (NDVI) were used to find the vegetation changes. The result shows that, maximum changes occur in the plantation and slight changes found in forest cover in the hilly terrain. In foothill areas, agriculture lands were decreased while wastelands and settlement plots were increased. The outcome of the results helps to farmer and policy makers to draw optimal lands use planning and better management strategies for sustainable development of natural resources.
NASA Astrophysics Data System (ADS)
Healey, S. P.; Oduor, P.; Cohen, W. B.; Yang, Z.; Ouko, E.; Gorelick, N.; Wilson, S.
2017-12-01
Every country's land is distributed among different cover types, such as: agriculture; forests; rangeland; urban areas; and barren lands. Changes in the distribution of these classes can inform us about many things, including: population pressure; effectiveness of preservation efforts; desertification; and stability of the food supply. Good assessment of these changes can also support wise planning, use, and preservation of natural resources. We are using the Landsat archive in two ways to provide needed information about land cover change since the year 2000 in seven East African countries (Ethiopia, Kenya, Malawi, Rwanda, Tanzania, Uganda, and Zambia). First, we are working with local experts to interpret historical land cover change from historical imagery at a probabilistic sample of 2000 locations in each country. This will provide a statistical estimate of land cover change since 2000. Second, we will use the same data to calibrate and validate annual land cover maps for each country. Because spatial context can be critical to development planning through the identification of hot spots, these maps will be a useful complement to the statistical, country-level estimates of change. The Landsat platform is an ideal tool for mapping land cover change because it combines a mix of appropriate spatial and spectral resolution with unparalleled length of service (Landsat 1 launched in 1972). Pilot tests have shown that time series analysis accessing the entire Landsat archive (i.e., many images per year) improves classification accuracy and stability. It is anticipated that this project will meet the civil needs of both governmental and non-governmental users across a range of disciplines.
Roman, Lara A; Fristensky, Jason P; Eisenman, Theodore S; Greenfield, Eric J; Lundgren, Robert E; Cerwinka, Chloe E; Hewitt, David A; Welsh, Caitlin C
2017-12-01
Many municipalities are setting ambitious tree canopy cover goals to increase the extent of their urban forests. A historical perspective on urban forest development can help cities strategize how to establish and achieve appropriate tree cover targets. To understand how long-term urban forest change occurs, we examined the history of trees on an urban college campus: the University of Pennsylvania in Philadelphia, PA. Using a mixed methods approach, including qualitative assessments of archival records (1870-2017), complemented by quantitative analysis of tree cover from aerial imagery (1970-2012), our analysis revealed drastic canopy cover increase in the late 20th and early 21st centuries along with the principle mechanisms of that change. We organized the historical narrative into periods reflecting campus planting actions and management approaches; these periods are also connected to broader urban greening and city planning movements, such as City Beautiful and urban sustainability. University faculty in botany, landscape architecture, and urban design contributed to the design of campus green spaces, developed comprehensive landscape plans, and advocated for campus trees. A 1977 Landscape Development Plan was particularly influential, setting forth design principles and planting recommendations that enabled the dramatic canopy cover gains we observed, and continue to guide landscape management today. Our results indicate that increasing urban tree cover requires generational time scales and systematic management coupled with a clear urban design vision and long-term commitments. With the campus as a microcosm of broader trends in urban forest development, we conclude with a discussion of implications for municipal tree cover planning.
NASA Astrophysics Data System (ADS)
Roman, Lara A.; Fristensky, Jason P.; Eisenman, Theodore S.; Greenfield, Eric J.; Lundgren, Robert E.; Cerwinka, Chloe E.; Hewitt, David A.; Welsh, Caitlin C.
2017-12-01
Many municipalities are setting ambitious tree canopy cover goals to increase the extent of their urban forests. A historical perspective on urban forest development can help cities strategize how to establish and achieve appropriate tree cover targets. To understand how long-term urban forest change occurs, we examined the history of trees on an urban college campus: the University of Pennsylvania in Philadelphia, PA. Using a mixed methods approach, including qualitative assessments of archival records (1870-2017), complemented by quantitative analysis of tree cover from aerial imagery (1970-2012), our analysis revealed drastic canopy cover increase in the late 20th and early 21st centuries along with the principle mechanisms of that change. We organized the historical narrative into periods reflecting campus planting actions and management approaches; these periods are also connected to broader urban greening and city planning movements, such as City Beautiful and urban sustainability. University faculty in botany, landscape architecture, and urban design contributed to the design of campus green spaces, developed comprehensive landscape plans, and advocated for campus trees. A 1977 Landscape Development Plan was particularly influential, setting forth design principles and planting recommendations that enabled the dramatic canopy cover gains we observed, and continue to guide landscape management today. Our results indicate that increasing urban tree cover requires generational time scales and systematic management coupled with a clear urban design vision and long-term commitments. With the campus as a microcosm of broader trends in urban forest development, we conclude with a discussion of implications for municipal tree cover planning.
Bodart, Catherine; Brink, Andreas B; Donnay, François; Lupi, Andrea; Mayaux, Philippe; Achard, Frédéric
2013-01-01
Aim This study provides regional estimates of forest cover in dry African ecoregions and the changes in forest cover that occurred there between 1990 and 2000, using a systematic sample of medium-resolution satellite imagery which was processed consistently across the continent. Location The study area corresponds to the dry forests and woodlands of Africa between the humid forests and the semi-arid regions. This area covers the Sudanian and Zambezian ecoregions. Methods A systematic sample of 1600 Landsat satellite imagery subsets, each 20 km × 20 km in size, were analysed for two reference years: 1990 and 2000. At each sample site and for both years, dense tree cover, open tree cover, other wooded land and other vegetation cover were identified from the analysis of satellite imagery, which comprised multidate segmentation and automatic classification steps followed by visual control by national forestry experts. Results Land cover and land-cover changes were estimated at continental and ecoregion scales and compared with existing pan-continental, regional and local studies. The overall accuracy of our land-cover maps was estimated at 87%. Between 1990 and 2000, 3.3 million hectares (Mha) of dense tree cover, 5.8 Mha of open tree cover and 8.9 Mha of other wooded land were lost, with a further 3.9 Mha degraded from dense to open tree cover. These results are substantially lower than the 34 Mha of forest loss reported in the FAO's 2010 Global Forest Resources Assessment for the same period and area. Main conclusions Our method generates the first consistent and robust estimates of forest cover and change in dry Africa with known statistical precision at continental and ecoregion scales. These results reduce the uncertainty regarding vegetation cover and its dynamics in these previously poorly studied ecosystems and provide crucial information for both science and environmental policies. PMID:23935237
Giri, Chandra; Long, Jordan
2014-01-01
Detailed and accurate land cover and land cover change information is needed for South America because the continent is in constant flux, experiencing some of the highest rates of land cover change and forest loss in the world. The land cover data available for the entire continent are too coarse (250 m to 1 km) for resource managers, government and non-government organizations, and Earth scientists to develop conservation strategies, formulate resource management options, and monitor land cover dynamics. We used Landsat 30 m satellite data of 2010 and prepared the land cover database of South America using state-of-the-science remote sensing techniques. We produced regionally consistent and locally relevant land cover information by processing a large volume of data covering the entire continent. Our analysis revealed that in 2010, 50% of South America was covered by forests, 2.5% was covered by water, and 0.02% was covered by snow and ice. The percent forest area of South America varies from 9.5% in Uruguay to 96.5% in French Guiana. We used very high resolution (<5 m) satellite data to validate the land cover product. The overall accuracy of the 2010 South American 30-m land cover map is 89% with a Kappa coefficient of 79%. Accuracy of barren areas needs to improve possibly using multi-temporal Landsat data. An update of land cover and change database of South America with additional land cover classes is needed. The results from this study are useful for developing resource management strategies, formulating biodiversity conservation strategies, and regular land cover monitoring and forecasting.
NASA Astrophysics Data System (ADS)
Tyukavina, A.; Potapov, P.; Hansen, M.; Talero, Y.; Turubanova, S.; Pickering, J.; Pickens, A. H.; Quyen, N. H.; Spirovska Kono, M.
2017-12-01
Timely forest monitoring data produced following good practice guidance are required for national reporting on greenhouse gas emissions, national forest resource assessments, and monitoring for REDD+ projects. Remote sensing provides a cost-efficient supplement to national forest inventories, and is often the single viable source of data on forest extent for countries still in the process of establishing field-based inventories. Operational forest monitoring using remotely sensed data requires technical capacity to store, process, and analyze high volumes of satellite imagery. The University of Maryland Global Land Analysis and Discovery (UMD GLAD) lab possesses such technical capacity and is seeking to transfer it to national agencies responsible for forest reporting, national academic institutions, and NGOs. Our projects in South and Southeast Asia include regional forest monitoring in the lower Mekong region in support of the Regional Land Cover Monitoring System (funded by the NASA SERVIR program) and building capacity for forest monitoring in Nepal, Bangladesh, Vietnam, Cambodia, Laos, and Thailand (funded by the SilvaCarbon program). Our forest monitoring approach is a regional scale adaptation of methods developed for the global analysis (Hansen et al. 2013). The methodology to track large-scale clearing of natural forests (e.g. in Brazil and Indonesia) is well established; however, the methods for small-scale disturbance mapping and tree cover rotation assessment are still in development. In Bangladesh our mapping of tree cover change between 2000-2014 revealed that 54% of the tree canopy cover was outside forests, and the majority of canopy changes were smaller than 0.1 ha. Landsat's 30-m resolution was therefore insufficient to monitor changes in tree cover. By using a probability sample of high resolution (circa 1 m) imagery we were able to quantify change in tree canopy cover outside forests (including village woodlots, tree plantations and agroforestry) and in different forest types. Our result shows that while the net tree cover change in Bangladesh is rather small, the gross dynamics are significant and can vary by forest type.
Effects of Conservation Policies on Forest Cover Change in Giant Panda Habitat Regions, China
Li, Yu; Viña, Andrés; Yang, Wu; Chen, Xiaodong; Zhang, Jindong; Ouyang, Zhiyun; Liang, Zai; Liu, Jianguo
2014-01-01
After long periods of deforestation, forest transition has occurred globally, but the causes of forest transition in different countries are highly variable. Conservation policies may play important roles in facilitating forest transition around the world, including China. To restore forests and protect the remaining natural forests, the Chinese government initiated two nationwide conservation policies in the late 1990s -- the Natural Forest Conservation Program (NFCP) and the Grain-To-Green Program (GTGP). While some studies have discussed the environmental and socioeconomic effects of each of these policies independently and others have attributed forest recovery to both policies without rigorous and quantitative analysis, it is necessary to rigorously quantify the outcomes of these two conservation policies simultaneously because the two policies have been implemented at the same time. To fill the knowledge gap, this study quantitatively evaluated the effects of the two conservation policies on forest cover change between 2001 and 2008 in 108 townships located in two important giant panda habitat regions -- the Qinling Mountains region in Shaanxi Province and the Sichuan Giant Panda Sanctuary in Sichuan Province. Forest cover change was evaluated using a land-cover product (MCD12Q1) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). This product proved to be highly accurate in the study region (overall accuracy was ca. 87%, using 425 ground truth points collected in the field), thus suitable for the forest change analysis performed. Results showed that within the timeframe evaluated, most townships in both regions exhibited either increases or no changes in forest cover. After accounting for a variety of socioeconomic and biophysical attributes, an Ordinary Least Square (OLS) regression model suggests that the two policies had statistically significant positive effects on forest cover change after seven years of implementation, while population density, percent agricultural population, road density, and initial forest cover (i.e. in 2001) had significant negative effects. The methods and results from this study will be useful for continuing the implementation of these conservation policies, for the development of future giant panda habitat conservation projects, and for achieving forest sustainability in China and elsewhere. PMID:26146431
Effects of Conservation Policies on Forest Cover Change in Giant Panda Habitat Regions, China.
Li, Yu; Viña, Andrés; Yang, Wu; Chen, Xiaodong; Zhang, Jindong; Ouyang, Zhiyun; Liang, Zai; Liu, Jianguo
2013-07-01
After long periods of deforestation, forest transition has occurred globally, but the causes of forest transition in different countries are highly variable. Conservation policies may play important roles in facilitating forest transition around the world, including China. To restore forests and protect the remaining natural forests, the Chinese government initiated two nationwide conservation policies in the late 1990s -- the Natural Forest Conservation Program (NFCP) and the Grain-To-Green Program (GTGP). While some studies have discussed the environmental and socioeconomic effects of each of these policies independently and others have attributed forest recovery to both policies without rigorous and quantitative analysis, it is necessary to rigorously quantify the outcomes of these two conservation policies simultaneously because the two policies have been implemented at the same time. To fill the knowledge gap, this study quantitatively evaluated the effects of the two conservation policies on forest cover change between 2001 and 2008 in 108 townships located in two important giant panda habitat regions -- the Qinling Mountains region in Shaanxi Province and the Sichuan Giant Panda Sanctuary in Sichuan Province. Forest cover change was evaluated using a land-cover product (MCD12Q1) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). This product proved to be highly accurate in the study region (overall accuracy was ca. 87%, using 425 ground truth points collected in the field), thus suitable for the forest change analysis performed. Results showed that within the timeframe evaluated, most townships in both regions exhibited either increases or no changes in forest cover. After accounting for a variety of socioeconomic and biophysical attributes, an Ordinary Least Square (OLS) regression model suggests that the two policies had statistically significant positive effects on forest cover change after seven years of implementation, while population density, percent agricultural population, road density, and initial forest cover (i.e. in 2001) had significant negative effects. The methods and results from this study will be useful for continuing the implementation of these conservation policies, for the development of future giant panda habitat conservation projects, and for achieving forest sustainability in China and elsewhere.
The Land Cover Dynamics and Conversion of Agricultural Land in Northwestern Bangladesh, 1973-2003.
NASA Astrophysics Data System (ADS)
Pervez, M.; Seelan, S. K.; Rundquist, B. C.
2006-05-01
The importance of land cover information describing the nature and extent of land resources and changes over time is increasing; this is especially true in Bangladesh, where land cover is changing rapidly. This paper presents research into the land cover dynamics of northwestern Bangladesh for the period 1973-2003 using Landsat satellite images in combination with field survey data collected in January and February 2005. Land cover maps were produced for eight different years during the study period with an average 73 percent overall classification accuracy. The classification results and post-classification change analysis showed that agriculture is the dominant land cover (occupying 74.5 percent of the study area) and is being reduced at a rate of about 3,000 ha per year. In addition, 6.7 percent of the agricultural land is vulnerable to temporary water logging annually. Despite this loss of agricultural land, irrigated agriculture increased substantially until 2000, but has since declined because of diminishing water availability and uncontrolled extraction of groundwater driven by population pressures and the extended need for food. A good agreement (r = 0.73) was found between increases in irrigated land and the depletion of the shallow groundwater table, a factor affecting widely practiced small-scale irrigation in northwestern Bangladesh. Results quantified the land cover change patterns and the stresses placed on natural resources; additionally, they demonstrated an accurate and economical means to map and analyze changes in land cover over time at a regional scale, which can assist decision makers in land and natural resources management decisions.
Tan, Z.; Liu, S.; Johnston, C.A.; Liu, J.; Tieszen, L.L.
2006-01-01
Our ability to forecast the role of ecosystem processes in mitigating global greenhouse effects relies on understanding the driving forces on terrestrial C dynamics. This study evaluated the controls on soil organic C (SOC) changes from 1973 to 2000 in the northwest Great Plains. SOC source-sink relationships were quantified using the General Ensemble Biogeochemical Modeling System (GEMS) based on 40 randomly located 10 × 10 km2 sample blocks. These sample blocks were aggregated into cropland, grassland, and forestland groups based on land cover composition within each sample block. Canonical correlation analysis indicated that SOC source-sink relationship from 1973 to 2000 was significantly related to the land cover type while the change rates mainly depended on the baseline SOC level and annual precipitation. Of all selected driving factors, the baseline SOC and nitrogen levels controlled the SOC change rates for the forestland and cropland groups, while annual precipitation determined the C source-sink relationship for the grassland group in which noticeable SOC sink strength was attributed to the conversion from cropped area to grass cover. Canonical correlation analysis also showed that grassland ecosystems are more complicated than others in the ecoregion, which may be difficult to identify on a field scale. Current model simulations need further adjustments to the model input variables for the grass cover-dominated ecosystems in the ecoregion.
Gong, Jian; Yang, Jianxin; Tang, Wenwu
2015-11-09
Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution-severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investigations on how these ecological risks induced by land use practices change over space and time in response to alternative policy intervention remain inadequate. In this article, we conducted spatially explicit landscape ecological risk analysis in Ezhou City, China. Our study area is a national ecologically representative region experiencing drastic land use and land cover change, and is regulated by multiple policies represented by farmland protection, ecological conservation, and urban development. We employed landscape metrics to consider the influence of potential landscape-level disturbance for the evaluation of landscape ecological risks. Using spatiotemporal simulation, we designed scenarios to examine spatiotemporal patterns in landscape ecological risks in response to policy intervention. Our study demonstrated that spatially explicit landscape ecological risk analysis combined with simulation-driven scenario analysis is of particular importance for guiding the sustainable development of ecologically vulnerable land systems.
Gong, Jian; Yang, Jianxin; Tang, Wenwu
2015-01-01
Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution—severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investigations on how these ecological risks induced by land use practices change over space and time in response to alternative policy intervention remain inadequate. In this article, we conducted spatially explicit landscape ecological risk analysis in Ezhou City, China. Our study area is a national ecologically representative region experiencing drastic land use and land cover change, and is regulated by multiple policies represented by farmland protection, ecological conservation, and urban development. We employed landscape metrics to consider the influence of potential landscape-level disturbance for the evaluation of landscape ecological risks. Using spatiotemporal simulation, we designed scenarios to examine spatiotemporal patterns in landscape ecological risks in response to policy intervention. Our study demonstrated that spatially explicit landscape ecological risk analysis combined with simulation-driven scenario analysis is of particular importance for guiding the sustainable development of ecologically vulnerable land systems. PMID:26569270
NASA Astrophysics Data System (ADS)
Bayramov, Emil; Mammadov, Ramiz
2016-07-01
The main goals of this research are the object-based landcover classification of LANDSAT-8 multi-spectral satellite images in 2014 and 2015, quantification of Normalized Difference Vegetation Indices (NDVI) rates within the land-cover classes, change detection analysis between the NDVIs derived from multi-temporal LANDSAT-8 satellite images and the quantification of those changes within the land-cover classes and detection of changes between land-cover classes. The object-based classification accuracy of the land-cover classes was validated through the standard confusion matrix which revealed 80 % of land-cover classification accuracy for both years. The analysis revealed that the area of agricultural lands increased from 30911 sq. km. in 2014 to 31999 sq. km. in 2015. The area of barelands increased from 3933 sq. km. in 2014 to 4187 sq. km. in 2015. The area of forests increased from 8211 sq. km. in 2014 to 9175 sq. km. in 2015. The area of grasslands decreased from 27176 sq. km. in 2014 to 23294 sq. km. in 2015. The area of urban areas increased from 12479 sq. km. in 2014 to 12956 sq. km. in 2015. The decrease in the area of grasslands was mainly explained by the landuse shifts of grasslands to agricultural and urban lands. The quantification of low and medium NDVI rates revealed the increase within the agricultural, urban and forest land-cover classes in 2015. However, the high NDVI rates within agricultural, urban and forest land-cover classes in 2015 revealed to be lower relative to 2014. The change detection analysis between landscover types of 2014 and 2015 allowed to determine that 7740 sq. km. of grasslands shifted to agricultural landcover type whereas 5442sq. km. of agricultural lands shifted to rangelands. This means that the spatio-temporal patters of agricultural activities occurred in Azerbaijan because some of the areas reduced agricultural activities whereas some of them changed their landuse type to agricultural. Based on the achieved results, it is possible to conclude that the area of agricultural lands in Azerbaijan increased from 2014 to 2015. The crop productivity also increased in the croplands, however some of the areas showed lower productivity in 2015 relative to 2014.
Multitemporal spatial pattern analysis of Tulum's tropical coastal landscape
NASA Astrophysics Data System (ADS)
Ramírez-Forero, Sandra Carolina; López-Caloca, Alejandra; Silván-Cárdenas, José Luis
2011-11-01
The tropical coastal landscape of Tulum in Quintana Roo, Mexico has a high ecological, economical, social and cultural value, it provides environmental and tourism services at global, national, regional and local levels. The landscape of the area is heterogeneous and presents random fragmentation patterns. In recent years, tourist services of the region has been increased promoting an accelerate expansion of hotels, transportation and recreation infrastructure altering the complex landscape. It is important to understand the environmental dynamics through temporal changes on the spatial patterns and to propose a better management of this ecological area to the authorities. This paper addresses a multi-temporal analysis of land cover changes from 1993 to 2000 in Tulum using Thematic Mapper data acquired by Landsat-5. Two independent methodologies were applied for the analysis of changes in the landscape and for the definition of fragmentation patterns. First, an Iteratively Multivariate Alteration Detection (IR-MAD) algorithm was used to detect and localize land cover change/no-change areas. Second, the post-classification change detection evaluated using the Support Vector Machine (SVM) algorithm. Landscape metrics were calculated from the results of IR-MAD and SVM. The analysis of the metrics indicated, among other things, a higher fragmentation pattern along roadways.
GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...
Homer, Collin G.; Dewitz, Jon; Yang, Limin; Jin, Suming; Danielson, Patrick; Xian, George Z.; Coulston, John; Herold, Nathaniel; Wickham, James; Megown, Kevin
2015-01-01
The National Land Cover Database (NLCD) provides nationwide data on land cover and land cover change at the native 30-m spatial resolution of the Landsat Thematic Mapper (TM). The database is designed to provide five-year cyclical updating of United States land cover and associated changes. The recent release of NLCD 2011 products now represents a decade of consistently produced land cover and impervious surface for the Nation across three periods: 2001, 2006, and 2011 (Homer et al., 2007; Fry et al., 2011). Tree canopy cover has also been produced for 2011 (Coluston et al., 2012; Coluston et al., 2013). With the release of NLCD 2011, the database provides the ability to move beyond simple change detection to monitoring and trend assessments. NLCD 2011 represents the latest evolution of NLCD products, continuing its focus on consistency, production, efficiency, and product accuracy. NLCD products are designed for widespread application in biology, climate, education, land management, hydrology, environmental planning, risk and disease analysis, telecommunications and visualization, and are available for no cost at http://www.mrlc.gov. NLCD is produced by a Federal agency consortium called the Multi-Resolution Land Characteristics Consortium (MRLC) (Wickham et al., 2014). In the consortium arrangement, the U.S. Geological Survey (USGS) leads NLCD land cover and imperviousness production for the bulk of the Nation; the National Oceanic and Atmospheric Administration (NOAA) completes NLCD land cover for the conterminous U.S. (CONUS) coastal zones; and the U.S. Forest Service (USFS) designs and produces the NLCD tree canopy cover product. Other MRLC partners collaborate through resource or data contribution to ensure NLCD products meet their respective program needs (Wickham et al., 2014).
Forest Cover Change Analysis in Inner Mongolia Using Remote Sensing Data
NASA Astrophysics Data System (ADS)
Xie, S.; Gong, J.; Huang, X.
2018-04-01
Forest is the lung of the earth, and it has important effect on maintaining the ecological balance of the whole earth. This study was conducted in Inner Mongolia during the year 1990-2015. Land use and land cover data were used to obtain forest cover change of Inner Mongolia. In addition, protected area data, road data, ASTER GDEM data were combined with forest cover change data to analyze the relationship between them. Moreover, patch density and landscape shape index were calculated to analyze forest change in perspective of landscape aspect. The results indicated that forest area increased overall during the study period. However, a few cities still had a phenomenon of reduced forest area. Results also demonstrated that the construction of protected area had positive effect on protecting forest while roads may disturbed forest due to human activities. In addition, forest patches in most of cities of Inner Mongolia tended to be larger and less fragmented. This paper reflected forest change in Inner Mongolia objectively, which is helpful for policy making by government.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lawrence, Peter J.; Feddema, Johannes J.; Bonan, Gordon B.
To assess the climate impacts of historical and projected land cover change and land use in the Community Climate System Model (CCSM4) we have developed new time series of transient Community Land Model (CLM4) Plant Functional Type (PFT) parameters and wood harvest parameters. The new parameters capture the dynamics of the Coupled Model Inter-comparison Project phase 5 (CMIP5) land cover change and wood harvest trajectories for the historical period from 1850 to 2005, and for the four Representative Concentration Pathways (RCP) periods from 2006 to 2100. Analysis of the biogeochemical impacts of land cover change in CCSM4 with the parametersmore » found the model produced an historical cumulative land use flux of 148.4 PgC from 1850 to 2005, which was in good agreement with other global estimates of around 156 PgC for the same period. The biogeophysical impacts of only applying the transient land cover change parameters in CCSM4 were cooling of the near surface atmospheric over land by -0.1OC, through increased surface albedo and reduced shortwave radiation absorption. When combined with other transient climate forcings, the higher albedo from land cover change was overwhelmed at global scales by decreases in snow albedo from black carbon deposition and from high latitude warming. At regional scales however the land cover change forcing persisted resulting in reduced warming, with the biggest impacts in eastern North America. The future CCSM4 RCP simulations showed that the CLM4 transient PFT and wood harvest parameters could be used to represent a wide range of human land cover change and land use scenarios. Furthermore, these simulations ranged from the RCP 4.5 reforestation scenario that was able to draw down 82.6 PgC from the atmosphere, to the RCP 8.5 wide scale deforestation scenario that released 171.6 PgC to the atmosphere.« less
Optimal use of land surface temperature data to detect changes in tropical forest cover
NASA Astrophysics Data System (ADS)
van Leeuwen, Thijs T.; Frank, Andrew J.; Jin, Yufang; Smyth, Padhraic; Goulden, Michael L.; van der Werf, Guido R.; Randerson, James T.
2011-06-01
Rapid and accurate assessment of global forest cover change is needed to focus conservation efforts and to better understand how deforestation is contributing to the buildup of atmospheric CO2. Here we examined different ways to use land surface temperature (LST) to detect changes in tropical forest cover. In our analysis we used monthly 0.05° × 0.05° Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations of LST and Program for the Estimation of Deforestation in the Brazilian Amazon (PRODES) estimates of forest cover change. We also compared MODIS LST observations with an independent estimate of forest cover loss derived from MODIS and Landsat observations. Our study domain of approximately 10° × 10° included the Brazilian state of Mato Grosso. For optimal use of LST data to detect changes in tropical forest cover in our study area, we found that using data sampled during the end of the dry season (˜1-2 months after minimum monthly precipitation) had the greatest predictive skill. During this part of the year, precipitation was low, surface humidity was at a minimum, and the difference between day and night LST was the largest. We used this information to develop a simple temporal sampling algorithm appropriate for use in pantropical deforestation classifiers. Combined with the normalized difference vegetation index, a logistic regression model using day-night LST did moderately well at predicting forest cover change. Annual changes in day-night LST decreased during 2006-2009 relative to 2001-2005 in many regions within the Amazon, providing independent confirmation of lower deforestation levels during the latter part of this decade as reported by PRODES.
NASA Astrophysics Data System (ADS)
sugihara, K.; Nakatsugawa, M.
2013-12-01
The water quality characteristics of ice-covered, stagnant, eutrophic water bodies have not been clarified because of insufficient observations. It has been pointed out that climate change has been shortening the duration of ice-cover; however, the influence of climate change on water quality has not been clarified. This study clarifies the water quality characteristics of stagnant, eutrophic water bodies that freeze in winter, based on our surveys and simulations, and examines how climate change may influence those characteristics. We made fixed-point observation using self-registering equipment and vertical water sampling. Self-registering equipment measured water temperature and dissolved oxygen(DO).vertical water sampling analyzed biological oxygen demand(BOD), total nitrogen(T-N), nitrate nitrogen(NO3-N), nitrite nitrogen(NO2-N), ammonium nitrogen(NH4-N), total phosphorus(TP), orthophosphoric phosphorus(PO4-P) and chlorophyll-a(Chl-a). The survey found that climate-change-related increases in water temperature were suppressed by ice covering the water area, which also blocked oxygen supply. It was also clarified that the bottom sediment consumed oxygen and turned the water layers anaerobic beginning from the bottom layer, and that nutrient salts eluted from the bottom sediment. The eluted nutrient salts were stored in the water body until the ice melted. The ice-covered period of water bodies has been shortening, a finding based on the analysis of weather and water quality data from 1998 to 2008. Climate change was surveyed as having caused decreases in nutrient salts concentration because of the shortened ice-covered period. However, BOD in spring showed a tendency to increase because of the proliferation of phytoplankton that was promoted by the climate-change-related increase in water temperature. To forecast the water quality by using these findings, particularly the influence of climate change, we constructed a water quality simulation model that incorporates the freezing-over of water bodies. The constructed model shows good temporal and spatial reproducibility and enables water quality to be forecast throughout the year, including during the ice-covered period. The forecasts using the model agree well with the survey results of shortened ice period and climate-change-related increase in the BOD in spring. From the result of calculations and observations, it is suggested that water quality of spring has been deteriorate because of freezing period to be shortened due to temperature rising.
Wetland Restoration Response Analysis using MODIS and Groundwater Data
Melesse, Assefa M.; Nangia, Vijay; Wang, Xixi; McClain, Michael
2007-01-01
Vegetation cover and groundwater level changes over the period of restoration are the two most important indicators of the level of success in wetland ecohydrological restoration. As a result of the regular presence of water and dense vegetation, the highest evapotranspiration (latent heat) rates usually occur within wetlands. Vegetation cover and evapotranspiration of large areas of restoration like that of Kissimmee River basin, South Florida will be best estimated using remote sensing technique than point measurements. Kissimmee River basin has been the area of ecological restoration for some years. The current ecohydrological restoration activities were evaluated through fractional vegetation cover (FVC) changes and latent heat flux using Moderate Resolution Imaging Spectroradiometer (MODIS) data. Groundwater level data were also analyzed for selected eight groundwater monitoring wells in the basin. Results have shown that the average fractional vegetation cover and latent heat along 10 km buffer of Kissimmee River between Lake Kissimmee and Lake Okeechobee was higher in 2004 than in 2000. It is evident that over the 5-year period of time, vegetated and areas covered with wetlands have increased significantly especially along the restoration corridor. Analysis of groundwater level data (2000-2004) from eight monitoring wells showed that, the average monthly level of groundwater was increased by 20 cm and 34 cm between 2000 and 2004, and 2000 and 2003, respectively. This change was more evident for wells along the river. PMID:28903205
Liu, J.; Liu, S.; Loveland, Thomas R.; Tieszen, L.L.
2008-01-01
Land cover change is one of the key driving forces for ecosystem carbon (C) dynamics. We present an approach for using sequential remotely sensed land cover observations and a biogeochemical model to estimate contemporary and future ecosystem carbon trends. We applied the General Ensemble Biogeochemical Modelling System (GEMS) for the Laurentian Plains and Hills ecoregion in the northeastern United States for the period of 1975-2025. The land cover changes, especially forest stand-replacing events, were detected on 30 randomly located 10-km by 10-km sample blocks, and were assimilated by GEMS for biogeochemical simulations. In GEMS, each unique combination of major controlling variables (including land cover change history) forms a geo-referenced simulation unit. For a forest simulation unit, a Monte Carlo process is used to determine forest type, forest age, forest biomass, and soil C, based on the Forest Inventory and Analysis (FIA) data and the U.S. General Soil Map (STATSGO) data. Ensemble simulations are performed for each simulation unit to incorporate input data uncertainty. Results show that on average forests of the Laurentian Plains and Hills ecoregion have been sequestrating 4.2 Tg C (1 teragram = 1012 gram) per year, including 1.9 Tg C removed from the ecosystem as the consequences of land cover change. ?? 2008 Elsevier B.V.
Erasmus, B. F. N.; Archibald, S.
2016-01-01
Woody encroachment in ‘open’ biomes like grasslands and savannahs is occurring globally. Both local and global drivers, including elevated CO2, have been implicated in these increases. The relative importance of different processes is unresolved as there are few multi-site, multi-land-use evaluations of woody plant encroachment. We measured 70 years of woody cover changes over a 1020 km2 area covering four land uses (commercial ranching, conservation with elephants, conservation without elephants and communal rangelands) across a rainfall gradient in South African savannahs. Different directions of woody cover change would be expected for each different land use, unless a global factor is causing the increases. Woody cover change was measured between 1940 and 2010 using the aerial photo record. Detection of woody cover from each aerial photograph was automated using eCognitions' Object-based image analysis (OBIA). Woody cover doubled in all land uses across the rainfall gradient, except in conservation areas with elephants in low-rainfall savannahs. Woody cover in 2010 in low-rainfall savannahs frequently exceeded the maximum woody cover threshold predicted for African savannahs. The results indicate that a global factor, of which elevated CO2 is the likely candidate, may be driving encroachment. Elephants in low-rainfall savannahs prevent encroachment and localized megafaunal extinction is a probable additional cause of encroachment. This article is part of the themed issue ‘Tropical grassy biomes: linking ecology, human use and conservation’. PMID:27502384
Stevens, Nicola; Erasmus, B F N; Archibald, S; Bond, W J
2016-09-19
Woody encroachment in 'open' biomes like grasslands and savannahs is occurring globally. Both local and global drivers, including elevated CO2, have been implicated in these increases. The relative importance of different processes is unresolved as there are few multi-site, multi-land-use evaluations of woody plant encroachment. We measured 70 years of woody cover changes over a 1020 km(2) area covering four land uses (commercial ranching, conservation with elephants, conservation without elephants and communal rangelands) across a rainfall gradient in South African savannahs. Different directions of woody cover change would be expected for each different land use, unless a global factor is causing the increases. Woody cover change was measured between 1940 and 2010 using the aerial photo record. Detection of woody cover from each aerial photograph was automated using eCognitions' Object-based image analysis (OBIA). Woody cover doubled in all land uses across the rainfall gradient, except in conservation areas with elephants in low-rainfall savannahs. Woody cover in 2010 in low-rainfall savannahs frequently exceeded the maximum woody cover threshold predicted for African savannahs. The results indicate that a global factor, of which elevated CO2 is the likely candidate, may be driving encroachment. Elephants in low-rainfall savannahs prevent encroachment and localized megafaunal extinction is a probable additional cause of encroachment.This article is part of the themed issue 'Tropical grassy biomes: linking ecology, human use and conservation'. © 2016 The Author(s).
Impacts of land cover changes on climate trends in Jiangxi province China.
Wang, Qi; Riemann, Dirk; Vogt, Steffen; Glaser, Rüdiger
2014-07-01
Land-use/land-cover (LULC) change is an important climatic force, and is also affected by climate change. In the present study, we aimed to assess the regional scale impact of LULC on climate change using Jiangxi Province, China, as a case study. To obtain reliable climate trends, we applied the standard normal homogeneity test (SNHT) to surface air temperature and precipitation data for the period 1951-1999. We also compared the temperature trends computed from Global Historical Climatology Network (GHCN) datasets and from our analysis. To examine the regional impacts of land surface types on surface air temperature and precipitation change integrating regional topography, we used the observation minus reanalysis (OMR) method. Precipitation series were found to be homogeneous. Comparison of GHCN and our analysis on adjusted temperatures indicated that the resulting climate trends varied slightly from dataset to dataset. OMR trends associated with surface vegetation types revealed a strong surface warming response to land barrenness and weak warming response to land greenness. A total of 81.1% of the surface warming over vegetation index areas (0-0.2) was attributed to surface vegetation type change and regional topography. The contribution of surface vegetation type change decreases as land cover greenness increases. The OMR precipitation trend has a weak dependence on surface vegetation type change. We suggest that LULC integrating regional topography should be considered as a force in regional climate modeling.
Canaz, Sibel; Aliefendioğlu, Yeşim; Tanrıvermiş, Harun
2017-09-15
In this study, the Istanbul Province was monitored using Landsat 5 TM, MSS, Landsat 7 ETM+, and Landsat 8 OLI imagery from the years 1986, 2000, 2009, 2011, 2013, and 2015 in order to assess land cover changes in the province. The aim of the study was to classify manmade structures, land, green, and water areas, and to observe the changes in the province using satellite images. After classification, the images were compared in selected years to observe land cover. Moreover, these changes were correlated with the property tax values of Istanbul by years. The findings of the study showed that manmade structure areas increased while vegetation areas decreased due to rapid population growth, urbanization, and industrial and commercial development in Istanbul. These changes also explain the transformation of land from rural and natural areas to residential use, and serve as a tool with which to assess land value increments. Land value capturing is critical for the analysis of the linkages between the changes in land cover, and for assessing land transformation and urban growth. Due to inadequate market data, real estate tax values were used to analyze the linkages between detection changes, land cover, and taxation. In fact, the declared tax values of land owners are generally lower than the actual market values and therefore it is not possible to transfer the value increasing of land in urban areas by using property taxation from the owner to local and central governments. The research results also show that the integration of remote sensing results with real estate market data give us to determine the tax base values of real estate more realistically. Copyright © 2017 Elsevier Ltd. All rights reserved.
Assessment of soil-vegetation cover condition in river basins applying remote sensing data
NASA Astrophysics Data System (ADS)
Mishchenko, Natalia; Petrosian, Janna; Shirkin, Leonid; Repkin, Roman
2017-04-01
Constant observation of vegetation and soil cover is one of the key issues of river basins ecologic monitoring. Lately remotely determining vegetation indices have been used for this purpose alongside with terrestrial data. It is necessary to consider that observation objects have been continuously changing and these changes are comprehensive and depend on temporal and dimensional parameters. Remote sensing data, embracing vast areas and reflecting various interrelations, allow excluding accidental and short-term changes though concentrating on the transformation of the observed river basin ecosystem environmental condition. The research objective is to assess spatial - temporal peculiarities and the dynamics of soil-vegetation condition of the Klyazma basin as whole and minor river basins within the area. Research objects are located in the centre of European Russia. Data used in our research include both statistic and published data, characterizing soil-vegetation cover of the area, space images («Landsat» ETM+ etc.) Research methods. 1. Dynamics analysis NDVI (Normalized difference vegetation index) 2. Remote data have been correlated to terrestrial measurement results of phytomass reserve, phytoproductivity, soil fertility characteristics, crop capacity (http://biodat.ru) 3. For the digital processing of space images software Erdas Imagine has been used, GIS analysis has been carried out applying Arc GIS. NDVI computation for each image pixel helped to map general condition of the Klyazma vegetation cover and to determine geographic ranges without vegetation or with depressed vegetation. For instance high vegetation index geographic range has been defined which corresponded to Vladimir Opolye characterized with the most fertile grey forest soil in the region. Comparative assessment of soil vegetation cover of minor river basins within the Klyazma basin, judging by the terrestrial data, revealed its better condition in the Koloksha basin which is also located in the area of grey forest soil. Besides here the maximum value of vegetation index for all phytocenosis was detected. In the research the most dynamically changing parts of the Klyazma basin have been determined according to NDVI dynamics analysis. Analyzing the reasons for such changes of NDVI the most significant ecologic processes in the region connected to the changes of vegetation cover condition have been revealed. Fields overgrowing and agricultural crops replacement are the most important of them.
Tran, Phong; Marincioni, Fausto; Shaw, Rajib
2010-11-01
Recent catastrophic floods in Viet Nam have been increasingly linked to land use and forest cover change in the uplands. Despite the doubts that many scientists have expressed on such nexus, this common view prompted both positive forest protection/reforestation programs and often-unwarranted blame on upland communities for their forest management practices. This study discusses the disparity between public perceptions and scientific evidences relating the causes of catastrophic floods. The former was drawn on the results of a questionnaire and focus groups discussions with key informants of different mountainous communities, whereas the latter was based on GIS and remote sensing analysis of land cover change, including a statistical analysis of hydro-meteorological data of the Huong river basin in Viet Nam. Results indicate that there is a gap between the common beliefs and the actual relationship between the forest cover change and catastrophic floods. Undeniably, the studied areas showed significant changes in land cover over the period 1989-2008, yet, 71% of the variance of catastrophic flood level in the downstream areas appeared related to variance in rainfall. Evidences from this study showed that the overall increasing trends of catastrophic flooding in the Huong river basin was mainly due to climate variability and to the development of main roads and dyke infrastructures in the lowlands. Forest management policies and programs, shaped on the common assumption that forest degradation in the upland is the main cause of catastrophic flood in the downstream areas, should be reassessed to avoid unnecessary strain on upland people. Copyright 2010 Elsevier Ltd. All rights reserved.
Development of 2010 national land cover database for the Nepal.
Uddin, Kabir; Shrestha, Him Lal; Murthy, M S R; Bajracharya, Birendra; Shrestha, Basanta; Gilani, Hammad; Pradhan, Sudip; Dangol, Bikash
2015-01-15
Land cover and its change analysis across the Hindu Kush Himalayan (HKH) region is realized as an urgent need to support diverse issues of environmental conservation. This study presents the first and most complete national land cover database of Nepal prepared using public domain Landsat TM data of 2010 and replicable methodology. The study estimated that 39.1% of Nepal is covered by forests and 29.83% by agriculture. Patch and edge forests constituting 23.4% of national forest cover revealed proximate biotic interferences over the forests. Core forests constituted 79.3% of forests of Protected areas where as 63% of area was under core forests in the outside protected area. Physiographic regions wise forest fragmentation analysis revealed specific conservation requirements for productive hill and mid mountain regions. Comparative analysis with Landsat TM based global land cover product showed difference of the order of 30-60% among different land cover classes stressing the need for significant improvements for national level adoption. The online web based land cover validation tool is developed for continual improvement of land cover product. The potential use of the data set for national and regional level sustainable land use planning strategies and meeting several global commitments also highlighted. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.
1999-01-01
This paper presents an overview of Project ATLANTA (ATlanta Land use ANalysis: Temperature and Air-quality) which is an investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970's has impacted the region's climate and air quality. The primary objectives for this research effort are: (1) To investigate and model the relationships between land cover change in the Atlanta metropolitan, and the development of the urban heat island phenomenon through time; (2) To investigate and model the temporal relationships between Atlanta urban growth and land cover change on air quality; and (3) To model the overall effects of urban development on surface energy budget characteristics across the Atlanta urban landscape through time. Our key goal is to derive a better scientific understanding of how land cover changes associated with urbanization in the Atlanta area, principally in transforming forest lands to urban land covers through time, has, and will, effect local and regional climate, surface energy flux, and air quality characteristics. Allied with this goal is the prospect that the results from this research can be applied by urban planners, environmental managers and other decision-makers, for determining how urbanization has impacted the climate and overall environment of the Atlanta area. Multiscaled remote sensing data, particularly high resolution thermal infrared data, are integral to this study for the analysis of thermal energy fluxes across the Atlanta urban landscape.
Spatiotemporal dynamics of LUCC from 2001 to 2010 in Yunnan Province, China
NASA Astrophysics Data System (ADS)
Li, Z. J.; Yu, J. S.; Yao, X. L.; Chen, X.; Li, Z. L.
2016-08-01
LUCC (Land use and land cover change) is increasingly regarded as an important component of global environmental change and sustainable development. In this study, regional land cover type maps were drawn using the MODIS products from 2001 and 2010 based on the modified classification scheme embodied by the characteristics of land cover in Yunnan. Dynamic change in each type of land cover was investigated by classification statistics, dynamic transfer matrices, and landscape pattern metrics. In addition, the driving factors of LUCC were discussed. The results showed that the land cover types of the Yunnan province, especially woodland (WL), cropland (CL) and grassland (GL), had experienced noticeable changes with an area of about 30% of land during the study period. And there was an obvious vertical distribution pattern for land cover types. The average altitude of different land cover types from the highest to the lowest were unused land (UUT), WL, GL, water (WT), urban and built-up areas (UB) and CL. The average slope for most of the land-cover types did not vary over the past 10 years. Stabilization and homogenization will be the direction of land cover in the future according to landscape metrics analysis. The regional differences of land use structure in the area are strongly influenced by such factors as the geographical position, level of economic development and land use policy. The new policy of land use, Construction of Mountainous Town, would be provided to achieve the economical and intensive utilization of land resources during the rapid development of urbanization and industrialization in Yunnan.
NASA Astrophysics Data System (ADS)
Pérez-Luque, Antonio J.; Herrero, Javier; Bonet, Francisco J.; Pérez-Pérez, Ramón
2016-04-01
Climate change is causing declines in snow-cover extent and duration in European mountain ranges. This is especially important in Mediterranean mountain ranges where the observed trends towards precipitation and higher temperatures can provoke problems of water scarcity. In this work, we analyzed temporal trends (2000 to 2014) of snow-related variables obtained from satellite and modelling data in Sierra Nevada, a Mediterranean high-mountain range located in Southern Spain, at 37°N. Snow cover indicators (snow-cover duration, snow-cover onset dates and snow-cover melting dates) were obtained by processing images of MOD10A2 MODIS product using an automated workflow. Precipitation data were obtained using WiMMed, a complete and fully distributed hydrological model that is used to map the annual rainfall and snowfall with a resolution of 30x30 m over the whole study area. It uses expert algorithms to interpolate precipitation and temperature at an hourly scale, and simulates partition of precipitation into snowfall with several methods. For each snow-related indicator (snow-covers and snowfall), a trend analysis was applied at the MODIS pixel scale during the study period (2000-2014). We applied Mann-Kendall test and Theil-Sen slope estimation in each of the pixels comprising Sierra Nevada. The trend analysis assesses the intensity, magnitude and degree of statistical significance during the period analysed. The spatial pattern of these trends was explored according to elevation ranges. Finally, we explored the relationship between trends of snow-cover related indicators and precipitation trends. Our results show that snow-cover has undergone significant changes in the last 14 years. 80 % of the pixels covering Sierra Nevada showed a negative trend in the duration of snow-cover. We also observed a delay in the snow-cover onset date (68.03 % pixels showing a positive trend in the snow-cover onset date) and an advance in the melt date (80.72 % of pixels followed a negative trend for the snow-cover melting date). Precipitation does not show a significant trend for these years, even though its inter-annual variability has been outstanding. The maximum mean annual precipitation of 906 mm/year doubles the mean precipitation, which somehow compensates for the occurrence of a sequence of dry years with a minimum of 250 mm/year. The assessment of the spatial pattern of snow cover duration shows that both the trend and the slope of the trend becomes more pronounced with elevation. At higher elevations the snow-cover duration decreased an average of 3 days from 2000-2014. This research has been funded by ECOPOTENTIAL (Improving future ecosystem benefits through Earth Observations) Horizon 2020 EU project, and Sierra Nevada Global Change Observatory (LTER-site)
Science priorities for the human dimensions of global change
NASA Technical Reports Server (NTRS)
1994-01-01
The topics covered include the following: defining research needs; understanding land use change; improving policy analysis -- research on the decision-making process; designing policy instruments and institutions to address energy-related environmental problems; assessing impacts, vulnerability, and adaptation to global changes; and understanding population dynamics and global change.
Pisano, L; Zumpano, V; Malek, Ž; Rosskopf, C M; Parise, M
2017-12-01
Land cover is one of the most important conditioning factors in landslide susceptibility analysis. Usually it is considered as a static factor, but it has proven to be dynamic, with changes occurring even in few decades. In this work the influence of land cover changes on landslide susceptibility are analyzed for the past and for future scenarios. For the application, an area representative of the hilly-low mountain sectors of the Italian Southern Apennines was chosen (Rivo basin, in Molise Region). With this purpose landslide inventories and land cover maps were produced for the years 1954, 1981 and 2007. Two alternative future scenarios were created for 2050, one which follows the past trend (2050-trend), and another one more extreme, foreseeing a decrease of forested and cultivated areas (2050-alternative). The landslide susceptibility analysis was performed using the Spatial Multi-Criteria Evaluation method for different time steps, investigating changes to susceptibility over time. The results show that environmental dynamics, such as land cover change, affect slope stability in time. In fact there is a decrease of susceptibility in the past and in the future 2050-trend scenario. This is due to the increase of forest or cultivated areas, that is probably determined by a better land management, water and soil control respect to other land cover types such as shrubland, pasture or bareland. Conversely the results revealed by the alternative scenario (2050-alternative), show how the decrease in forest and cultivated areas leads to an increase in landslide susceptibility. This can be related to the assumed worst climatic condition leading to a minor agricultural activity and lower extension of forested areas, possibly associated also to the effects of forest fires. The results suggest that conscious landscape management might contribute to determine a significant reduction in landslide susceptibility. Copyright © 2017 Elsevier B.V. All rights reserved.
Mahmoud, Shereif H.; Alazba, A. A.
2015-01-01
The hydrological response to land cover changes induced by human activities in arid regions has attracted increased research interest in recent decades. The study reported herein assessed the spatial and quantitative changes in surface runoff resulting from land cover change in the Al-Baha region of Saudi Arabia between 1990 and 2000 using an ArcGIS-surface runoff model and predicted land cover and surface runoff depth in 2030 using Markov chain analysis. Land cover maps for 1990 and 2000 were derived from satellite images using ArcGIS 10.1. The findings reveal a 26% decrease in forest and shrubland area, 28% increase in irrigated cropland, 1.5% increase in sparsely vegetated land and 0.5% increase in bare soil between 1990 and 2000. Overall, land cover changes resulted in a significant decrease in runoff depth values in most of the region. The decrease in surface runoff depth ranged from 25-106 mm/year in a 7020-km2 area, whereas the increase in such depth reached only 10 mm/year in a 243-km2 area. A maximum increase of 73 mm/year was seen in a limited area. The surface runoff depth decreased to the greatest extent in the central region of the study area due to the huge transition in land cover classes associated with the construction of 25 rainwater harvesting dams. The land cover prediction revealed a greater than twofold increase in irrigated cropland during the 2000-2030 period, whereas forest and shrubland are anticipated to occupy just 225 km2 of land area by 2030, a significant decrease from the 747 km2 they occupied in 2000. Overall, changes in land cover are predicted to result in an annual increase in irrigated cropland and dramatic decline in forest area in the study area over the next few decades. The increase in surface runoff depth is likely to have significant implications for irrigation activities. PMID:25923712
NASA Technical Reports Server (NTRS)
Madrinan, Max Jacobo Moreno; Cordova, Africa Flores; Olivares, Francisco Delgado; Irwin, Dan
2012-01-01
Basin development and consequent change in basin land cover have been often associated with an increased turbidity in coastal waters because of sediment yield and nutrients loading. The later leads to phytoplankton abundance further exacerbating water turbidity. This subsequently affects biological and physical processes in coastal estuaries by interfering with sun light penetration to coral reefs and sea grass, and even affecting public health. Therefore, consistent estimation of land cover changes and turbidity trend lines is crucial to design environmental and restoration management plans, to predict fate of possible pollutants, and to estimate sedimentary fluxes into the ocean. Ground solely methods to estimate land cover change would be unpractical and traditional methods of monitoring in situ water turbidity can be very expensive and time consuming. Accurate monitoring on the status and trends of basin land cover as well as the water quality of the receiving water bodies are required for analysis of relationships between the two variables. Use of remote sensing (RS) technology provides a great benefit for both fields of study, facilitating monitoring of changes in a timely and cost effective manner and covering wide areas with long term measurements. In this study, the Magdalena River basin and fixed geographical locations in the estuarine waters of its delta are used as a case to study the temporal trend lines of both, land cover change and the reflectance of the water turbidity using satellite technology. Land cover data from a combined product between sensors Terra and Aqua (MCD12Q1) from MODIS will be adapted to the conditions in the Magdalena basin to estimate changes in land cover since year 2000 to 2009. Surface reflectance data from a MODIS, Terra (MOD09GQ), band 1, will be used in lieu of in situ water turbidity for the time period between 2000 and present. Results will be compared with available existing data.
NASA Astrophysics Data System (ADS)
Gómez-Nieto, Israel; Martín, María del Pilar; Salas, Francisco Javier; Gallardo, Marta
2013-04-01
Understanding the interaction between natural and socio-economic factors that determine fire regime is essential to make accurate projections and impact assessments. However, this requires having accurate historical, systematic, homogeneous and spatially explicit information on fire occurrence. Fire databases usually have serious limitations in this regard; therefore other sources of information, such as remote sensing, have emerged as alternatives to generate optimal fire maps on various spatial and temporal scales. Several national and international projects work in order to generate information to study the factors that determine the current fire regime and its future evolution. This work is included in the framework of the project "Forest fires under climate, social and economic Changes in Europe, the Mediterranean and other fire-affected areas of the World" (FUME http://www.fumeproject.eu), which aims to study the changes and factors related to fire regimes through time to determine the potential impacts on vegetation in Mediterranean regions and concrete steps to address future risk scenarios. We analyzed the changes in the fire regime in Madrid region (Spain) in the past three decades (1984-2010) and its relation to land use changes. We identified and mapped fires that have occurred in the region during those years using Landsat satellite images by combining digital techniques and visual analysis. The results show a clear cyclical behaviour of the fire, with years of high incidence (as 1985, 2000 and 2003, highlighted by the number of fires and the area concerned, over 2000 ha) followed by another with a clear occurrence decrease. At the same time, we analyzed the land use changes that have occurred in Madrid region between the early 80s and mid-2000s using as reference the CORINE Land-cover maps (1990, 2000 and 2006) and the Vegetation and Land Use map of the Community of Madrid, 1982. We studied the relationship between fire regimes and observed land-use and land-cover changes in the periods analyzed, it was determined that between years 1984 and 2006 most of the burned area remained pre-fire cover type (above 80% of the area). However, in areas that experienced change, the most important transitions were recorded in wooded areas, especially conifers, which became shrubs or sparsely vegetated areas, followed by non-irrigated crops, which were replaced by grasslands or industrial areas, and sparse vegetation which changed to shrubs. Finally, the analysis of land-use changes over burned areas situated shrubland as the most favored type of cover, either as a result of a vegetative degradation process after intense burning of wooded areas, especially conifers, or as stage of natural increase in areas previously covered by sparsely vegetation.
NASA Astrophysics Data System (ADS)
Yue, H.; Liu, Y.
2018-04-01
As a key factor affecting the biogeochemical cycle of human existence, terrestrial vegetation is vulnerable to natural environment and human activities, with obvious temporal and spatial characteristics. The change of vegetation cover will affect the ecological balance and environmental quality to a great extent. Therefore, the research on the causes and influencing factors of vegetation cover has become the focus of attention of scholars at home and abroad. In the evolution of human activities and natural environment, the vegetation coverage in Shaanxi has changed accordingly. Using MODIS/NDVI 2000-2014 time series data, using the method of raster pixel trend analysis, stability evaluation, rescaled range analysis and correlation analysis, the climatic factors in Shaanxi province were studied in the near 15 years vegetation spatial and temporal variation and influence of vegetation NDVI changes. The results show that NDVI in Shaanxi province in the near 15 years increased by 0.081, the increase of NDVI in Northern Shaanxi was obvious, and negative growth was found in some areas of Guanzhong, southern Shaanxi NDVI overall still maintained at a high level; the trend of vegetation change in Shaanxi province has obvious spatial differences, most of the province is a slight tendency to improve vegetation, there are many obvious improvement areas in Northern Shaanxi Province. Guanzhong area vegetation area decreased, the small range of variation of vegetation in Shaanxi province; the most stable areas are mainly concentrated in the southern, southern Yanan, Yulin, Xi'an area of Weinan changed greatly; Shaanxi Province in recent 15 a, the temperature and precipitation have shown an increasing trend, and the vegetation NDVI is more closely related to the average annual rainfall, with increase of 0.48 °C/10 years and 69.5 mm per year.
NASA Astrophysics Data System (ADS)
de Noblet, N.; Pitman, A.; Participants, Lucid
2009-04-01
The project "Land-Use and Climate, IDentification of robust impacts" (LUCID) was conceived under the auspices of IGBP-iLEAPS and GEWEX-GLASS, to address the robustness of 'local' and possible remote impacts of land-use induced land-cover changes (LCC). LUCID explores, using methodologies that major climate modelling groups recognise, those impacts of LCC that are robust - that is, above the noise generated by model variability and consistent across a suite of climate models. To start with, seven climate models were run, in ensemble mode (5 realisations per 31-years long experiment), with prescribed observed sea-surface temperatures (SSTs) and sea ice extent (SIc). Pre-industrial and present-day simulations were used to explore the impacts of biogeophysical impacts of human-induced land cover change. The imposed LCC perturbation led to statistically significant changes in latent heat flux and near-surface temperature over the regions of land cover change, but few significant changes in precipitation. Our results show no common remote impacts of land cover change. They also highlight a dilemma for both historical hind-casts and future projections; land cover change is regionally important, but it is not feasible within the time frame of the next IPCC (AR5) assessment to implement this change commonly across multiple models. Further analysis are in progress and will be presented to identify the continental regions where changes in LCC may have been more important than the combined changes in SSTs, SIc and CO2 between the pre-industrial times and nowadays.
NASA Astrophysics Data System (ADS)
Jia, S.
2015-12-01
As an effective method of extracting land cover fractions based on spectral endmembers, spectral mixture analysis (SMA) has been applied using remotely sensed imagery in different spatial, temporal, and spectral resolutions. A number of studies focused on arid/semiarid ecosystem have used SMA to obtain the land cover fractions of GV, NPV/litter, and bare soil (BS) using MODIS reflectance products to understand ecosystem phenology, track vegetation dynamics, and evaluate the impact of major disturbances. However, several challenges remain in the application of SMA in studying ecosystem phenology, including obtaining high quality endmembers and increasing computational efficiency when considering to long time series that cover a broad spatial extent. Okin (2007) proposes a variation of SMA, named as relative spectra mixture analysis (RSMA) to address the latter challenge by calculating the relative change of fraction of GV, NPV/litter, and BS compared with a baseline date. This approach assumes that the baseline image contains the spectral information of the bare soil that can be used as an endmember for spectral mixture analysis though it is mixed with the spectral reflectance of other non-soil land cover types. Using the baseline image, one can obtain the change of fractions of GV, NPV/litter, BS, and snow compared with the baseline image. However, RSMA results depend on the selection of baseline date and the fractional components during this date. In this study, we modified the strategy of implementing RSMA by introducing a step of obtaining a soil map as the baseline image using multiple-endmember SMA (MESMA) before applying RSMA. The fractions of land cover components from this modified RSMA are also validated using the field observations from two study area in semiarid savanna and grassland of Queensland, Australia.
NASA Technical Reports Server (NTRS)
Townshend, John R.; Masek, Jeffrey G.; Huang, ChengQuan; Vermote, Eric F.; Gao, Feng; Channan, Saurabh; Sexton, Joseph O.; Feng, Min; Narasimhan, Ramghuram; Kim, Dohyung;
2012-01-01
The compilation of global Landsat data-sets and the ever-lowering costs of computing now make it feasible to monitor the Earth's land cover at Landsat resolutions of 30 m. In this article, we describe the methods to create global products of forest cover and cover change at Landsat resolutions. Nevertheless, there are many challenges in ensuring the creation of high-quality products. And we propose various ways in which the challenges can be overcome. Among the challenges are the need for atmospheric correction, incorrect calibration coefficients in some of the data-sets, the different phenologies between compilations, the need for terrain correction, the lack of consistent reference data for training and accuracy assessment, and the need for highly automated characterization and change detection. We propose and evaluate the creation and use of surface reflectance products, improved selection of scenes to reduce phenological differences, terrain illumination correction, automated training selection, and the use of information extraction procedures robust to errors in training data along with several other issues. At several stages we use Moderate Resolution Spectroradiometer data and products to assist our analysis. A global working prototype product of forest cover and forest cover change is included.
Updating Landsat-derived land-cover maps using change detection and masking techniques
NASA Technical Reports Server (NTRS)
Likens, W.; Maw, K.
1982-01-01
The California Integrated Remote Sensing System's San Bernardino County Project was devised to study the utilization of a data base at a number of jurisdictional levels. The present paper discusses the implementation of change-detection and masking techniques in the updating of Landsat-derived land-cover maps. A baseline landcover classification was first created from a 1976 image, then the adjusted 1976 image was compared with a 1979 scene by the techniques of (1) multidate image classification, (2) difference image-distribution tails thresholding, (3) difference image classification, and (4) multi-dimensional chi-square analysis of a difference image. The union of the results of methods 1, 3 and 4 was used to create a mask of possible change areas between 1976 and 1979, which served to limit analysis of the update image and reduce comparison errors in unchanged areas. The techniques of spatial smoothing of change-detection products, and of combining results of difference change-detection algorithms are also shown to improve Landsat change-detection accuracies.
LeClerc, Emma; Wiersma, Yolanda F
2017-04-01
This study investigates land cover change near the abandoned Pine Point Mine in Canada's Northwest Territories. Industrial mineral development transforms local environments, and the effects of such disturbances are often long-lasting, particularly in subarctic, boreal environments where vegetation conversion can take decades. Located in the Boreal Plains Ecozone, the Pine Point Mine was an extensive open pit operation that underwent little reclamation when it shut down in 1988. We apply remote sensing and landscape ecology methods to quantify land cover change in the 20 years following the mine's closure. Using a time series of near-anniversary Landsat images, we performed a supervised classification to differentiate seven land cover classes. We used raster algebra and landscape metrics to track changes in land cover composition and configuration in the 20 years since the mine shut down. We compared our results with a site in Wood Buffalo National Park that was never subjected to extensive anthropogenic disturbance. This space-for-time substitution provided an analog for how the ecosystem in the Pine Point region might have developed in the absence of industrial mineral development. We found that the dense conifer class was dominant in the park and exhibited larger and more contiguous patches than at the mine site. Bare land at the mine site showed little conversion through time. While the combination of raster algebra and landscape metrics allowed us to track broad changes in land cover composition and configuration, improved access to affordable, high-resolution imagery is necessary to effectively monitor land cover dynamics at abandoned mines.
NASA Technical Reports Server (NTRS)
Potter, Christopher S.
2014-01-01
The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology was applied to detected changes in forest vegetation cover for areas burned by wildfires in the Sierra Nevada Mountains of California between the periods of 1975- 79 and 1995-1999. Results for areas burned by wildfire between 1995 and 1999 confirmed the importance of regrowing forest vegetation over 17% of the combined burned areas. A notable fraction (12%) of the entire 5-km (unburned) buffer area outside the 1995-199 fires perimeters showed decline in forest cover, and not nearly as many regrowing forest areas, covering only 3% of all the 1995-1999 buffer areas combined. Areas burned by wildfire between 1975 and 1979 confirmed the importance of disturbed (or declining evergreen) vegetation covering 13% of the combined 1975- 1979 burned areas. Based on comparison of these results to ground-based survey data, the LEDAPS methodology should be capable of fulfilling much of the need for consistent, low-cost monitoring of changes due to climate and biological factors in western forest regrowth following stand-replacing disturbances.
Geospatial analysis of land use change in the Savannah River Basin using Google Earth Engine
NASA Astrophysics Data System (ADS)
Zurqani, Hamdi A.; Post, Christopher J.; Mikhailova, Elena A.; Schlautman, Mark A.; Sharp, Julia L.
2018-07-01
Climate and land use/cover change are among the most pervasive issues facing the Southeastern United States, including the Savannah River basin in South Carolina and Georgia. Land use directly affects the natural environment across the Savannah River basin and it is important to analyze these impacts. The objectives of this study are to: 1) determine the classes and the distribution of land cover in the Savannah River basin; 2) identify the spatial and the temporal change of the land cover that occurs as a consequence of land use change in the area; and 3) discuss the potential effects of land use change in the Savannah River basin. The land cover maps were produced using random forest supervised classification at four time periods for a total of thirteen common land cover classes with overall accuracy assessments of 79.18% (1999), 79.41% (2005), 76.04% (2009), and 76.11% (2015). The major land use change observed was due to the deforestation and reforestation of forest areas during the entire study period. The change detection results using the normalized difference vegetation index (NDVI) indicated that the proportion areas of the deforestation were 5.93% (1999-2005), 4.63% (2005-2009), and 3.76% (2009-2015), while the proportion areas of the reforestation were 1.57% (1999-2005), 0.44% (2005-2009), and 1.53% (2009-2015). These results not only indicate land use change, but also demonstrate the advantage of utilizing Google Earth Engine and the public archive database in its platform to track and monitor this change over time.
Peculiarities of changes in the soil cover of landscapes adjacent to a megalopolis
NASA Astrophysics Data System (ADS)
Lazareva, Margarita; Aparin, Boris; Sukhacheva, Elena
2017-04-01
The progressive growth of cities has a significant impact on the soil cover of territories adjacent to the same. Megalopolises are centers of anthropogenic impact on the soils. Generally, forms and intensity of the urban impact on the soil cover weaken with increasing distance from the city's boundaries. In this respect, ample opportunities for the analysis of urban impact on the adjacent territories are provided by the study of the soil cover in the Leningrad Region (the LR). Saint Petersburg is a major European megalopolis, which is the administrative center of the LR. The time period of Saint Petersburg's impact on the environment does not exceed 300 years, which allows us to identify very clearly the character and areas of its impact on the soil cover. Over the past decades, there have been significant changes in the soils and the soil cover of the LR. In a large territory, there appeared new anthropogenic soils and soil cover organization forms, having no natural analogues, with a dramatic increase in the surface area of degraded soils. To access the current state of soil cover, to identify the role of anthropogenic factors of changes in this state; to carry out land reclamation, remediation and rehabilitation measures; to perform land cadastral valuation etc., we need an information resource containing data on the current state of soils and soil cover in the LR, the key element of which should be a map. We carried out mapping and created a 1:200 000 digital soil map (DSM) for the LR's territories. Diagnostics of soil contours were performed using traditionally drawn-up (paper) maps of soils and soil-formation factors; satellite images (Google, Yandex); data of remote sensing (Spot 5, Landsat 7,8); digital maps of main soil-formation factors (topographical ones, etc.). The digital soil map of the LR has been created in the geographic information system - QGIS. The map clarifies the contours of natural soils and soil combinations, and shows, for the first time, the contours of: - non-soil formations; - soils of the initial soil formation; - soils of agricultural lands within their existing boundaries; - soils and soil combinations that are specific for human settlements and horticultural land plots; - fallow lands; - anthropogenically disturbed soils. During the analysis of the created digital medium-scale soil map, we identified some changes in the soil cover of the territories adjacent to Saint Petersburg. Virtually in all the landscapes, we found a large number of soil cover structures, the components of which, along with natural soils, are anthropogenically disturbed soils, anthropogenic soils and non-soil formations. We revealed that the human impact on the soil cover is manifested within the range that varies from insignificant changes in soil parameters to radical transformations of the soil profile, complete destruction of soil and "creation" of new soil forms and soil cover organization forms. We have developed a typology of anthropogenically changed and anthropogenically created soil cover structures, taking into consideration the types of the economic impact on and the quality of environmental functions performed by the soils.
Dewan, Ashraf M; Yamaguchi, Yasushi
2009-03-01
This paper illustrates the result of land use/cover change in Dhaka Metropolitan of Bangladesh using topographic maps and multi-temporal remotely sensed data from 1960 to 2005. The Maximum likelihood supervised classification technique was used to extract information from satellite data, and post-classification change detection method was employed to detect and monitor land use/cover change. Derived land use/cover maps were further validated by using high resolution images such as SPOT, IRS, IKONOS and field data. The overall accuracy of land cover change maps, generated from Landsat and IRS-1D data, ranged from 85% to 90%. The analysis indicated that the urban expansion of Dhaka Metropolitan resulted in the considerable reduction of wetlands, cultivated land, vegetation and water bodies. The maps showed that between 1960 and 2005 built-up areas increased approximately 15,924 ha, while agricultural land decreased 7,614 ha, vegetation decreased 2,336 ha, wetland/lowland decreased 6,385 ha, and water bodies decreased about 864 ha. The amount of urban land increased from 11% (in 1960) to 344% in 2005. Similarly, the growth of landfill/bare soils category was about 256% in the same period. Much of the city's rapid growth in population has been accommodated in informal settlements with little attempt being made to limit the risk of environmental impairments. The study quantified the patterns of land use/cover change for the last 45 years for Dhaka Metropolitan that forms valuable resources for urban planners and decision makers to devise sustainable land use and environmental planning.
NASA Astrophysics Data System (ADS)
Gibbes, C.; Southworth, J.; Waylen, P. R.
2013-05-01
How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.
Staver, A Carla; Archibald, Sally; Levin, Simon
2011-05-01
Savannas are known as ecosystems with tree cover below climate-defined equilibrium values. However, a predictive framework for understanding constraints on tree cover is lacking. We present (a) a spatially extensive analysis of tree cover and fire distribution in sub-Saharan Africa, and (b) a model, based on empirical results, demonstrating that savanna and forest may be alternative stable states in parts of Africa, with implications for understanding savanna distributions. Tree cover does not increase continuously with rainfall, but rather is constrained to low (<50%, "savanna") or high tree cover (>75%, "forest"). Intermediate tree cover rarely occurs. Fire, which prevents trees from establishing, differentiates high and low tree cover, especially in areas with rainfall between 1000 mm and 2000 mm. Fire is less important at low rainfall (<1000 mm), where rainfall limits tree cover, and at high rainfall (>2000 mm), where fire is rare. This pattern suggests that complex interactions between climate and disturbance produce emergent alternative states in tree cover. The relationship between tree cover and fire was incorporated into a dynamic model including grass, savanna tree saplings, and savanna trees. Only recruitment from sapling to adult tree varied depending on the amount of grass in the system. Based on our empirical analysis and previous work, fires spread only at tree cover of 40% or less, producing a sigmoidal fire probability distribution as a function of grass cover and therefore a sigmoidal sapling to tree recruitment function. This model demonstrates that, given relatively conservative and empirically supported assumptions about the establishment of trees in savannas, alternative stable states for the same set of environmental conditions (i.e., model parameters) are possible via a fire feedback mechanism. Integrating alternative stable state dynamics into models of biome distributions could improve our ability to predict changes in biome distributions and in carbon storage under climate and global change scenarios.
Long-Term Impact of the Farm Financial Analysis Training Curriculum on FSA Borrowers in Pennsylvania
ERIC Educational Resources Information Center
Balliet, Kenneth L.; Douglass, Mark B.; Hanson, Gregory
2010-01-01
The Farm Financial Analysis Training (FFAT) course covers fundamental skills and concepts in liquidity, profitability, solvency, and efficiency. The research reported here identifies and measures the impacts of FFAT on participants including: 1) perceived gains in knowledge, 2) changes in management behavior, 3) changes in specific farm assets and…
NASA Technical Reports Server (NTRS)
Potter, Christopher S.
2015-01-01
The Sierra Nevada of California is a region where large wildfires have been suppressed for over a century. A detailed geographic record of recent changes in vegetation cover across the Sierra Nevada remains a gap that can be filled with satellite remote sensing data. Results from Landsat image analysis over the past 25 years in the Upper Kings River basin showed that consistent, significant increases in the normalized difference vegetation index (NDVI) have not extended above 2000 m elevation, where cold temperatures presumably limit the growing season. Moreover, mean increases in NDVI since 1986 at elevations below 2000 m (which cover about half of the total basin area) have not exceeded 9%, even in the most extreme precipitation yearly comparisons. NDVI has decreased significantly at elevations above 2000 m throughout the basin in relatively wet year comparisons since the mid-1980s. These findings conflict with any assumptions that ET fluxes and river flows downstream could have been markedly altered by vegetation change over most of the Upper Kings River basin in recent decades.
Observations and Modelling of Alternative Tree Cover States of the Boreal Ecosystem
NASA Astrophysics Data System (ADS)
Abis, B.; Brovkin, V.
2017-12-01
Recently, multimodality of the tree cover distribution of the boreal forests has been detected, revealing the existence of three alternative vegetation modes. Identifying which are the regions with a potential for alternative tree cover states, and assessing which are the main factors underlying their existence, is important to project future change of natural vegetation cover and its effect on climate.Through the use of generalised additive models and phase-space analysis, we study the link between tree cover distribution and eight globally-observed environmental factors, such as rainfall, temperature, and permafrost distribution. Using a classification based on these factors, we show the location of areas with potentially alternative tree cover states under the same environmental conditions in the boreal region. Furthermore, to explain the multimodality found in the data and the asymmetry between North America and Eurasia, we study a conceptual model based on tree species competition, and use it to simulate the sensitivity of tree cover to changes in environmental factors.We find that the link between individual environmental variables and tree cover differs regionally. Nonetheless, environmental conditions uniquely determine the vegetation state among the three dominant modes in ˜95% of the cases. On the other hand, areas with potentially alternative tree cover states encompass ˜1.1 million km2, and correspond to possible transition zones with a reduced resilience to disturbances. Employing our conceptual model, we show that multimodality can be explained through competition between tree species with different adaptations to environmental factors and disturbances. Moreover, the model is able to reproduce the asymmetry in tree species distribution between Eurasia and North America. Finally, we find that changes in permafrost could be associated with bifurcation points of the model, corroborating the importance of permafrost in a changing climate.
Li, Chao; Kuang, Yaoqiu; Huang, Ningsheng; Zhang, Chao
2013-01-01
It is generally believed that there is an inverse relationship between population growth and vegetation cover. However, reports about vegetation protection and reforestation around the World have been continuously increasing in recent decades, which seems to indicate that this relationship may not be true. In this paper, we have taken 21 cities in Guangdong Province, China as the study area to test the long-term relationship between population growth and vegetation cover, using an AVHRR NDVI data set and the panel cointegrated regression method. The results show that there is a long-term inverted N-shaped curve relationship between population growth and vegetation cover in the region where there are frequent human activities and the influence of climate change on vegetation cover changes is relatively small. The two turning points of the inverted N-shaped curve for the case of Guangdong Province correspond to 2,200 persons·km−2 and 3,820 persons·km−2, and they can provide a reference range for similar regions of the World. It also states that the population urbanization may have a negative impact on the vegetation cover at the early stage, but have a positive impact at the later stage. In addition, the Panel Error Correction Model (PECM) is used to investigate the causality direction between population growth and vegetation cover. The results show that not only will the consuming destruction effect and planting construction effect induced by the population growth have a great impact on vegetation cover changes, but vegetation cover changes in turn will also affect the population growth in the long term. PMID:23435589
NASA Astrophysics Data System (ADS)
Hawkins, G. A.; Vivoni, E. R.
2011-12-01
Watershed management is challenged by rising concerns over climate change and its potential to interact with land cover alterations to impact regional water supplies and hydrologic processes. The inability to conduct experimental manipulations that address climate and land cover change at watershed scales limits the capacity of water managers to make decisions to protect future supplies. As a result, spatially-explicit, physically-based models possess value for predicting the possible consequences on watershed hydrology. In this study, we apply a distributed watershed model, the Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator (tRIBS), to the Beaver Creek basin in Arizona. This sub-basin of the Verde River is representative of the regional topography, land cover, soils distribution and availability of hydrologic data in forested regions of northern Arizona. As such, it can serve as a demonstration study in the broader region to illustrate the utility of distributed models for change assessment studies. Through a model application to summertime conditions, we compare the hydrologic response from three sources of meteorological input: (1) an available network of ground-based stations, (2) weather radar rainfall estimates, and (3) the North American Land Data Assimilation System (NLDAS). Comparisons focus on analysis of spatiotemporal distributions of precipitation, soil moisture, runoff generation, evapotranspiration and recharge from the root zone at high resolution for an assessment of sustainable water supplies for agricultural and domestic purposes. We also present a preliminary analysis of the impact of vegetation change arising from historical treatments in the Beaver Creek to inform the hydrologic consequences in the form of soil moisture and evapotranspiration patterns with differing degrees of proposed forest thinning. Our results are discussed in the context of improved hydrologic predictions for sustainability and decision-making under the uncertainties induced by combined climate and land cover change.
NASA Astrophysics Data System (ADS)
Rounds, Eric
The urban lowland areas of Vietnam have been at the forefront of economic liberalization over the last 30 years, while the more remote mountainous areas of the country have lagged behind. Upland areas in the Northern and Central portions of Vietnam in particular remain largely impoverished and disconnected from broader national and regional markets. To address this economic inequality in the uplands, recent economic development efforts such as the East-West Economic Corridor (EWEC) have aimed at expanding road infrastructure to remote areas in Central Vietnam. This study examines the impact of road expansion in the EWEC on a single village in Quang Tri, Vietnam. It draws from social economic data gathered during fieldwork and a historical land cover analysis to address how land use, land cover, and livelihoods have changed in recent decades. Moreover, the paper discusses the distal and proximate drivers of these changes. Findings show that the improved road connectivity provided by new roads has facilitated the transmission of distant market-related drivers into the study area, and that these drivers have fostered significant changes in land use, land cover, and livelihoods.
Souza-Filho, Pedro Walfir M; de Souza, Everaldo B; Silva Júnior, Renato O; Nascimento, Wilson R; Versiani de Mendonça, Breno R; Guimarães, José Tasso F; Dall'Agnol, Roberto; Siqueira, José Oswaldo
2016-02-01
Long-term human-induced impacts have significantly changed the Amazonian landscape. The most dramatic land cover and land use (LCLU) changes began in the early 1970s with the establishment of the Trans-Amazon Highway and large government projects associated with the expansion of agricultural settlement and cattle ranching, which cleared significant tropical forest cover in the areas of new and accelerated human development. Taking the changes in the LCLU over the past four decades as a basis, this study aims to determine the consequences of land cover (forest and savanna) and land use (pasturelands, mining and urban) changes on the hydroclimatology of the Itacaiúnas River watershed area of the located in the southeastern Amazon region. We analyzed a multi-decadal Landsat dataset from 1973, 1984, 1994, 2004 and 2013 and a 40-yr time series of water discharge from the Itacaiúnas River, as well as air temperature and relative humidity data over this drainage area for the same period. We employed standard Landsat image processing techniques in conjunction with a geographic object-based image analysis and multi-resolution classification approach. With the goal of detecting possible long-term trends, non-parametric Mann-Kendall test was applied, based on a Sen slope estimator on a 40-yr annual PREC, TMED and RH time series, considering the spatial average of the entire watershed. In the 1970s, the region was entirely covered by forest (99%) and savanna (∼0.3%). Four decades later, only ∼48% of the tropical forest remains, while pasturelands occupy approximately 50% of the watershed area. Moreover, in protected areas, nearly 97% of the tropical forest remains conserved, while the forest cover of non-protected areas is quite fragmented and, consequently, unevenly distributed, covering an area of only 30%. Based on observational data analysis, there is evidence that the conversion of forest cover to extensive and homogeneous pasturelands was accompanied by systematic modifications to the hydroclimatology cycle of the Itacaiúnas watershed, thus highlighting drier environmental conditions due to a rise in the region's air temperature, a decrease in the relative humidity, and an increase in river discharge. Copyright © 2015 Elsevier Ltd. All rights reserved.
Towards monitoring land-cover and land-use changes at a global scale: the global land survey 2005
Gutman, G.; Byrnes, Raymond A.; Masek, J.; Covington, S.; Justice, C.; Franks, S.; Headley, Rachel
2008-01-01
Land cover is a critical component of the Earth system, infl uencing land-atmosphere interactions, greenhouse gas fl uxes, ecosystem health, and availability of food, fi ber, and energy for human populations. The recent Integrated Global Observations of Land (IGOL) report calls for the generation of maps documenting global land cover at resolutions between 10m and 30m at least every fi ve years (Townshend et al., in press). Moreover, despite 35 years of Landsat observations, there has not been a unifi ed global analysis of land-cover trends nor has there been a global assessment of land-cover change at Landsat-like resolution. Since the 1990s, the National Aeronautics and Space Administration (NASA) and the U.S. Geological Survey (USGS) have supported development of data sets based on global Landsat observations (Tucker et al., 2004). These land survey data sets, usually referred to as GeoCover ™, provide global, orthorectifi ed, typically cloud-free Landsat imagery centered on the years 1975, 1990, and 2000, with a preference for leaf-on conditions. Collectively, these data sets provided a consistent set of observations to assess land-cover changes at a decadal scale. These data are freely available via the Internet from the USGS Center for Earth Resources Observation and Science (EROS) (see http://earthexplorer.usgs.gov or http://glovis.usgs.gov). This has resulted in unprecedented downloads of data, which are widely used in scientifi c studies of land-cover change (e.g., Boone et al., 2007; Harris et al., 2005; Hilbert, 2006; Huang et al. 2007; Jantz et al., 2005, Kim et al., 2007; Leimgruber, 2005; Masek et al., 2006). NASA and USGS are continuing to support land-cover change research through the development of GLS2005 - an additional global Landsat assessment circa 20051 . Going beyond the earlier initiatives, this data set will establish a baseline for monitoring changes on a 5-year interval and will pave the way toward continuous global land-cover monitoring at Landsat-like resolution in the next decade.
New estimates of changes in snow cover over Russia in recent decades
NASA Astrophysics Data System (ADS)
Bulygina, O.; Korshunova, N.; Razuvaev, V.; Groisman, P. Y.
2017-12-01
Snow covers plays critical roles in the energy and water balance of the Earth through its unique physical properties (high reflectivity and low thermal conductivity) and water storage. The main objective of this research is to monitoring snow cover change in Russia. The estimates of changes of major snow characteristics (snow cover duration, maximum winter snow depth, snow water equivalent) are described. Apart from the description of long-term averages of snow characteristics, the estimates of their change that are averaged over quasi-homogeneous climatic regions are derived and regional differences in the change of snow characteristics are studied. We used in our study daily snow observations for 820 Russian meteorological station from 1966 to 2017. All of these meteorological stations are of unprotected type. The water equivalent is analyzed from snow course survey data at 958 meteorological stations from 1966 to 2017. The time series are prepared by RIHMI-WDC. Regional analysis of snow cover data was carried out using quasi-homogeneous climatic regions. The area-averaging technique using station values converted to anomalies with respect to a common reference period (in this study, 1981-2010). Anomalies were arithmetically averaged first within 1°N x 2°E grid cells and thereafter by a weighted average value derived over the quasi-homogeneous climatic regions. This approach provides a more uniform spatial field for averaging. By using a denser network of meteorological stations, bringing into consideration snow course data and, we managed to specify changes in all observed major snow characteristics and to obtain estimates generalized for quasi-homogeneous climatic regions. The detected changes in the dates of the establishment and disappearance of the snow cover.
Yu, Ling-Xue; Zhang, Shu-Wen; Guan, Cong; Yan, Feng-Qin; Yang, Chao-Bin; Bu, Kun; Yang, Jiu-Chun; Chang, Li-Ping
2014-09-01
This paper extracted and verified the snow cover extent in Heilongjiang Basin from 2003 to 2012 based on MODIS Aqua and Terra data, and the seasonal and interannual variations of snow cover extent were analyzed. The result showed that the double-star composite data reduced the effects of clouds and the overall accuracy was more than 91%, which could meet the research requirements. There existed significant seasonal variation of snow cover extent. The snow cover area was almost zero in July and August while in January it expanded to the maximum, which accounted for more than 80% of the basin. According to the analysis on the interannual variability of snow cover, the maximum winter snow cover areas in 2003-2004 and 2009-2010 (>180 x 10(4) km2) were higher than that of 2011 (150 x 10(4) km2). Meanwhile, there were certain correlations between the interannual fluctuations of snow cover and the changes of average annual temperature and precipitation. The year with the low snow cover was corresponding to less annual rainfall and higher average temperature, and vice versa. The spring snow cover showed a decreasing trend from 2003 to 2012, which was closely linked with decreasing precipitation and increasing temperature.
Wickham, James D.; Homer, Collin G.; Vogelmann, James E.; McKerrow, Alexa; Mueller, Rick; Herold, Nate; Coluston, John
2014-01-01
The Multi-Resolution Land Characteristics (MRLC) Consortium demonstrates the national benefits of USA Federal collaboration. Starting in the mid-1990s as a small group with the straightforward goal of compiling a comprehensive national Landsat dataset that could be used to meet agencies’ needs, MRLC has grown into a group of 10 USA Federal Agencies that coordinate the production of five different products, including the National Land Cover Database (NLCD), the Coastal Change Analysis Program (C-CAP), the Cropland Data Layer (CDL), the Gap Analysis Program (GAP), and the Landscape Fire and Resource Management Planning Tools (LANDFIRE). As a set, the products include almost every aspect of land cover from impervious surface to detailed crop and vegetation types to fire fuel classes. Some products can be used for land cover change assessments because they cover multiple time periods. The MRLC Consortium has become a collaborative forum, where members share research, methodological approaches, and data to produce products using established protocols, and we believe it is a model for the production of integrated land cover products at national to continental scales. We provide a brief overview of each of the main products produced by MRLC and examples of how each product has been used. We follow that with a discussion of the impact of the MRLC program and a brief overview of future plans.
Roush, W.; Munroe, Jeffrey S.; Fagre, D.B.
2007-01-01
Repeat photography is a powerful tool for detection of landscape change over decadal timescales. Here a novel method is presented that applies spatial analysis software to digital photo-pairs, allowing vegetation change to be categorized and quantified. This method is applied to 12 sites within the alpine treeline ecotone of Glacier National Park, Montana, and is used to examine vegetation changes over timescales ranging from 71 to 93 years. Tree cover at the treeline ecotone increased in 10 out of the 12 photo-pairs (mean increase of 60%). Establishment occurred at all sites, infilling occurred at 11 sites. To demonstrate the utility of this method, patterns of tree establishment at treeline are described and the possible causes of changes within the treeline ecotone are discussed. Local factors undoubtedly affect the magnitude and type of the observed changes, however the ubiquity of the increase in tree cover implies a common forcing mechanism. Mean minimum summer temperatures have increased by 1.5??C over the past century and, coupled with variations in the amount of early spring snow water equivalent, likely account for much of the increase in tree cover at the treeline ecotone. Lastly, shortcomings of this method are presented along with possible solutions and areas for future research. ?? 2007 Regents of the University of Colorado.
NASA Astrophysics Data System (ADS)
Hu, Y.; Jia, G.
2009-12-01
Change vector analysis (CVA) is an effective approach for detecting and characterizing land-cover change by comparing pairs of multi-spectral and multi-temporal datasets over certain area derived from various satellite platforms. NDVI is considered as an effective detector for biophysical changes due to its sensitivity to red and near infrared signals, while land surface temperature (LST) is considered as a valuable indicator for changes of ground thermal conditions. Here we try to apply CVA over satellite derived LST datasets to detect changes of land surface thermal properties parallel to climate change and anthropogenic influence in a city cluster since 2001. In this study, monthly land surface temperature datasets from 2001-2008 derived from MODIS collection 5 were used to examine change pattern of thermal environment over the Bohai coastal region by using spectral change vector analysis. The results from principle component analysis (PCA) for LST show that the PC 1-3 contain over 80% information on monthly variations and these PCA components represent the main processes of land thermal environment change over the study area. Time series of CVA magnitude combined with land cover information show that greatest change occurred in urban and heavily populated area, featured with expansion of urban heat island, while moderate change appeared in grassland area in the north. However few changes were observed over large plain area and forest area. Strong signals also are related to economy level and especially the events of surface cover change, such as emergence of railway and port. Two main processes were also noticed about the changes of thermal environment. First, weak signal was detected in mostly natural area influenced by interannual climate change in temperate broadleaf forest area. Second, land surface temperature changes were controlled by human activities as 1) moderate change of LST happened in grassland influenced by grazing and 2) urban heat island was intensifier in major cities, such as Beijing and Tianjin. Further, the continual drier climate combined with human actions over past fifties years have intensified land thermal pattern change and the continuation will be an important aspects to understand land surface processes and local climate change. Land surface temperature trends from 2000-2008 over the Bohai coastal region
Land cover and land use changes can substantially alter hydrologic ecosystem services. Water availability and quality can change with modifications to the type or amount of surface vegetation, the permeability of soil and other surfaces, and the introduction of contaminants throu...
Land use and land cover change in the Greater Yellowstone Ecosystem: 1975-1995
Parmenter, A.W.; Hansen, A.; Kennedy, R.E.; Cohen, W.; Langner, U.; Lawrence, R.; Maxwell, B.; Gallant, Alisa; Aspinall, R.
2003-01-01
Shifts in the demographic and economic character of the Greater Yellowstone Ecosystem (GYE) are driving patterns of land cover and land use change in the region. Such changes may have important consequences for ecosystem functioning. The objective of this paper is to quantify the trajectories and rates of change in land cover and use across the GYE for the period 1975-1995 using satellite imagery. Spectral and geographic variables were used as inputs to classification tree regression analysis (CART) to find "rules" which defined land use and land cover classes on the landscape. The resulting CART functions were used to map land cover and land use across seven Landsat TM scenes for 1995. We then used a thresholding technique to identify locations that differed in spectral properties between the 1995 and 1985 time periods. These "changed" locations were classified using CART functions derived from spectral and geographic data from 1985. This was similarly done for the year 1975 based on Landsat MSS data. Differences between the 1975, 1985, and 1995 maps were considered change in land cover and use. We calibrated and tested the accuracy of our models using data acquired through manual interpretation of aerial photos. Elevation and vegetative indices derived from the remotely sensed satellite imagery explained the most variance in the land use and land cover classes (-i.e., defined the "rules" most often). Overall accuracies from our study were good, ranging from 94% at the coarsest level of detail to 74% at the finest. The largest changes over the study period were the increases in burned, urban, and mixed conifer-herbaceous classes and decreases in woody deciduous, mixed woody deciduous-herbaceous, and conifer habitats. These changes have important implications for ecological function and biodiversity. The expansion of mixed conifer classes may increase fuel loads and enhance risk to the growing number of rural homes. The reduction of woody deciduous cover types is likely reducing population sizes for the numerous plant and animal species that specialize on this habitat type. Some of these species are also negatively influenced by the increase of rural homes in and near woody deciduous habitats.
A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets
Giri, C.; Zhu, Z.; Reed, B.
2005-01-01
Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level. We compared the recently available Global Land Cover 2000 (GLC-2000) and MODerate resolution Imaging Spectrometer (MODIS) global land cover data to evaluate the similarities and differences in methodologies and results, and to identify areas of spatial agreement and disagreement. These two global land cover data sets were prepared using different data sources, classification systems, and methodologies, but using the same spatial resolution (i.e., 1 km) satellite data. Our analysis shows a general agreement at the class aggregate level except for savannas/shrublands, and wetlands. The disagreement, however, increases when comparing detailed land cover classes. Similarly, percent agreement between the two data sets was found to be highly variable among biomes. The identified areas of spatial agreement and disagreement will be useful for both data producers and users. Data producers may use the areas of spatial agreement for training area selection and pay special attention to areas of disagreement for further improvement in future land cover characterization and mapping. Users can conveniently use the findings in the areas of agreement, whereas users might need to verify the informaiton in the areas of disagreement with the help of secondary information. Learning from past experience and building on the existing infrastructure (e.g., regional networks), further research is necessary to (1) reduce ambiguity in land cover definitions, (2) increase availability of improved spatial, spectral, radiometric, and geometric resolution satellite data, and (3) develop advanced classification algorithms.
Decadal land cover change dynamics in Bhutan.
Gilani, Hammad; Shrestha, Him Lal; Murthy, M S R; Phuntso, Phuntso; Pradhan, Sudip; Bajracharya, Birendra; Shrestha, Basanta
2015-01-15
Land cover (LC) is one of the most important and easily detectable indicators of change in ecosystem services and livelihood support systems. This paper describes the decadal dynamics in LC changes at national and sub-national level in Bhutan derived by applying object-based image analysis (OBIA) techniques to 1990, 2000, and 2010 Landsat (30 m spatial resolution) data. Ten LC classes were defined in order to give a harmonized legend land cover classification system (LCCS). An accuracy of 83% was achieved for LC-2010 as determined from spot analysis using very high resolution satellite data from Google Earth Pro and limited field verification. At the national level, overall forest increased from 25,558 to 26,732 km(2) between 1990 and 2010, equivalent to an average annual growth rate of 59 km(2)/year (0.22%). There was an overall reduction in grassland, shrubland, and barren area, but the observations were highly dependent on time of acquisition of the satellite data and climatic conditions. The greatest change from non-forest to forest (277 km(2)) was in Bumthang district, followed by Wangdue Phodrang and Trashigang, with the least (1 km(2)) in Tsirang. Forest and scrub forest covers close to 75% of the land area of Bhutan, and just over half of the total area (51%) has some form of conservation status. This study indicates that numerous applications and analyses can be carried out to support improved land cover and land use (LCLU) management. It will be possible to replicate this study in the future as comparable new satellite data is scheduled to become available. Copyright © 2014 Elsevier Ltd. All rights reserved.
Measuring coral reef decline through meta-analyses
Côté, I.M; Gill, J.A; Gardner, T.A; Watkinson, A.R
2005-01-01
Coral reef ecosystems are in decline worldwide, owing to a variety of anthropogenic and natural causes. One of the most obvious signals of reef degradation is a reduction in live coral cover. Past and current rates of loss of coral are known for many individual reefs; however, until recently, no large-scale estimate was available. In this paper, we show how meta-analysis can be used to integrate existing small-scale estimates of change in coral and macroalgal cover, derived from in situ surveys of reefs, to generate a robust assessment of long-term patterns of large-scale ecological change. Using a large dataset from Caribbean reefs, we examine the possible biases inherent in meta-analytical studies and the sensitivity of the method to patchiness in data availability. Despite the fact that our meta-analysis included studies that used a variety of sampling methods, the regional estimate of change in coral cover we obtained is similar to that generated by a standardized survey programme that was implemented in 1991 in the Caribbean. We argue that for habitat types that are regularly and reasonably well surveyed in the course of ecological or conservation research, meta-analysis offers a cost-effective and rapid method for generating robust estimates of past and current states. PMID:15814352
Danielson, Patrick; Yang, Limin; Jin, Suming; Homer, Collin G.; Napton, Darrell
2016-01-01
We developed a method that analyzes the quality of the cultivated cropland class mapped in the USA National Land Cover Database (NLCD) 2006. The method integrates multiple geospatial datasets and a Multi Index Integrated Change Analysis (MIICA) change detection method that captures spectral changes to identify the spatial distribution and magnitude of potential commission and omission errors for the cultivated cropland class in NLCD 2006. The majority of the commission and omission errors in NLCD 2006 are in areas where cultivated cropland is not the most dominant land cover type. The errors are primarily attributed to the less accurate training dataset derived from the National Agricultural Statistics Service Cropland Data Layer dataset. In contrast, error rates are low in areas where cultivated cropland is the dominant land cover. Agreement between model-identified commission errors and independently interpreted reference data was high (79%). Agreement was low (40%) for omission error comparison. The majority of the commission errors in the NLCD 2006 cultivated crops were confused with low-intensity developed classes, while the majority of omission errors were from herbaceous and shrub classes. Some errors were caused by inaccurate land cover change from misclassification in NLCD 2001 and the subsequent land cover post-classification process.
Covering #SAE: A Mobile Reporting Class's Changing Patterns of Interaction on Twitter over Time
ERIC Educational Resources Information Center
Jones, Julie
2015-01-01
This study examined the social network that emerged on Twitter surrounding a mobile reporting class as they covered a national breaking news event. The work introduces pedagogical strategies that enhance students' learning opportunities. Through NodeXL and social network cluster analysis, six groups emerged from the Twitter interactions tied to…
Vegetation succession among and within structural layers following wildfire in managed forests
Lori J. Kayes; Paul D. Anderson; Klaus J. Puettmann
2010-01-01
In severely burned plantations, dynamics of (1) shrub, herbaceous, and cryptogam richness; (2) cover; (3) topographic, overstory, and site influences were characterized on two contrasting aspects 2 to 4 years following fire. Analysis of variance was used to examine change in structural layer richness and cover over time. Non-metric multidimensional scaling, multi-...
Making Sense of Global Reform in Initial Teacher Education: A Discussion Paper.
ERIC Educational Resources Information Center
1997
This is an analysis of the findings from three comparable national studies of current change in the provision of initial teacher education. These three studies are: the Mode of Teacher Education (MOTE) survey, covering England and Wales; the Research about Teacher Education (RATE) Project, covering the United States; and the Study of Initial…
Optimal use of land surface temperature data to detect changes in tropical forest cover
NASA Astrophysics Data System (ADS)
Van Leeuwen, T. T.; Frank, A. J.; Jin, Y.; Smyth, P.; Goulden, M.; van der Werf, G.; Randerson, J. T.
2011-12-01
Rapid and accurate assessment of global forest cover change is needed to focus conservation efforts and to better understand how deforestation is contributing to the build up of atmospheric CO2. Here we examined different ways to use remotely sensed land surface temperature (LST) to detect changes in tropical forest cover. In our analysis we used monthly 0.05×0.05 degree Terra MODerate Resolution Imaging Spectroradiometer (MODIS) observations of LST and PRODES (Program for the Estimation of Deforestation in the Brazilian Amazon) estimates of forest cover change. We also compared MODIS LST observations with an independent estimate of forest cover loss derived from MODIS and Landsat observations. Our study domain of approximately 10×10 degree included most of the Brazilian state of Mato Grosso. For optimal use of LST data to detect changes in tropical forest cover in our study area, we found that using data sampled during the end of the dry season (~1-2 months after minimum monthly precipitation) had the greatest predictive skill. During this part of the year, precipitation was low, surface humidity was at a minimum, and the difference between day and night LST was the largest. We used this information to develop a simple temporal sampling algorithm appropriate for use in pan-tropical deforestation classifiers. Combined with the normalized difference vegetation index (NDVI), a logistic regression model using day-night LST did moderately well at predicting forest cover change. Annual changes in day-night LST difference decreased during 2006-2009 relative to 2001-2005 in many regions within the Amazon, providing independent confirmation of lower deforestation levels during the latter part of this decade as reported by PRODES. The use of day-night LST differences may be particularly valuable for use with satellites that do not have spectral bands that allow for the estimation of NDVI or other vegetation indices.
Using historical photography to monitor and assess threats over time
Don Evans
2010-01-01
Analysis of aerial photography is perhaps the best way to assess changes in landcover conditions. In the United States, most national forests have repeat photography on approximately a 10-year cycle. Analysis of this rich photo record can reveal changes in insect damage, fuels buildup, unmanaged off-highway vehicle use, loss of open space, and other land-cover...
Daniel J. Manier; Richard D. Laven
2001-01-01
Using repeat photography, we conducted a qualitative and quantitative analysis of changes in forest cover on the western slope of the Rocky Mountains in Colorado. For the quantitative analysis, both images in a pair were classified using remote sensing and geographic information system (GIS) technologies. Comparisons were made using three landscape metrics: total...
Maestre, Fernando T.; Escolar, Cristina; Bardgett, Richard D.; Dungait, Jennifer A. J.; Gozalo, Beatriz; Ochoa, Victoria
2015-01-01
Soil communities dominated by lichens and mosses (biocrusts) play key roles in maintaining ecosystem structure and functioning in drylands worldwide. However, few studies have explicitly evaluated how climate change-induced impacts on biocrusts affect associated soil microbial communities. We report results from a field experiment conducted in a semiarid Pinus halepensis plantation, where we setup an experiment with two factors: cover of biocrusts (low [<15%] versus high [>50%]), and warming (control versus a ∼2°C temperature increase). Warming reduced the richness and cover (∼45%) of high biocrust cover areas 53 months after the onset of the experiment. This treatment did not change the ratios between the major microbial groups, as measured by phospholipid fatty acid analysis. Warming increased the physiological stress of the Gram negative bacterial community, as indicated by the cy17:0/16:1ω7 ratio. This response was modulated by the initial biocrust cover, as the increase in this ratio with warming was higher in areas with low cover. Our findings suggest that biocrusts can slow down the negative effects of warming on the physiological status of the Gram negative bacterial community. However, as warming will likely reduce the cover and diversity of biocrusts, these positive effects will be reduced under climate change. PMID:26379642
NASA Astrophysics Data System (ADS)
Zaitunah, A.; Samsuri; Ahmad, A. G.; Safitri, R. A.
2018-03-01
Watershed is an ecosystem area confined by topography and has function as a catcher, storage, and supplier of water, sediments, pollutants and nutrients in the river system and exit through a single outlet. Various activities around watershed areas of Besitang have changed the land cover and vegetation index (NDVI) that exist in the region. In order to detect changes in land cover and NDVI quickly and accurately, we used remote sensing technology and geographic information systems (GIS). The study aimed to assess changes in land cover and vegetation density (NDVI) between 2005 and 2015, as well as obtaining the density of vegetation (NDVI) on each of the land cover of 2005 and 2015. The research showed the extensive of forest area of 949.65 Ha and a decline of mangrove forest area covering an area of 2,884.06 Ha. The highest vegetation density reduced 39,714.58 Ha, and rather dense increased 24,410.72 Ha between 2005 and 2015. The land cover that have the highest NDVI value range with very dense vegetation density class is the primary dry forest (0.804 to 0.876), followed by secondary dry forest (0.737 to 0.804) for 2015. In 2015 the land cover has NDVI value range the primary dry forest (0.513 to 0.57), then secondary dry forest (0.456 to 0.513) with dense vegetation density class
David I. Board; Jeanne C. Chambers; Richard F. Miller; Peter J. Weisberg
2018-01-01
Increases in area burned and fire size have been reported across a wide range of forest and shrubland types in the Western United States in recent decades, but little is known about potential changes in fire regimes of piñon and juniper land cover types. We evaluated spatio-temporal patterns of fire in piñon and juniper land cover types from the National Gap Analysis...
NASA Astrophysics Data System (ADS)
Lyons, M. B.; Phinn, S. R.; Roelfsema, C. M.
2011-12-01
Long term global archives of high-moderate spatial resolution, multi-spectral satellite imagery are now readily accessible, but are not being fully utilised by management agencies due to the lack of appropriate methods to consistently produce accurate and timely management ready information. This work developed an object-based approach to map land cover and seagrass distribution in an Australian coastal environment for a 38 year Landsat image time-series archive. Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery were used without in-situ field data input to produce land and seagrass cover maps every year data was available, resulting in over 60 individual map products over the 38 year archive. Land cover was mapped annually and included several vegetation, bare ground, urban and agricultural classes. Seagrass distribution was also mapped annually, and in some years monthly, via horizontal projective foliage cover classes, sand and deepwater. Land cover products were validated using aerial photography and seagrass was validated with field survey data, producing several measures of accuracy. An average overall accuracy of 65% and 81% was reported for seagrass and land cover respectively, which is consistent with other studies in the area. This study is the first to show moderate spatial resolution, long term annual changes in land cover and seagrass in an Australian environment, without the use of in-situ data; and only one of a few similar studies globally. The land cover products identify several long term trends; such as significant increases in South East Queensland's urban density, vegetation clearing in rural and rural-residential areas, and inter-annual variation in dry vegetation types in western South East Queensland. The seagrass cover products show that there has been a minimal overall change in seagrass extent, but that seagrass cover level distribution is extremely dynamic; evidenced by large scale migrations of higher seagrass cover levels and several events of sudden, significant changes in cover level. These mapping products will allow management agencies to build a baseline assessment of their resources, understand past changes and help inform implementation and planning of management policy to address potential future changes.
NASA Astrophysics Data System (ADS)
Lyons, Mitchell B.; Phinn, Stuart R.; Roelfsema, Chris M.
2012-07-01
Long term global archives of high-moderate spatial resolution, multi-spectral satellite imagery are now readily accessible, but are not being fully utilised by management agencies due to the lack of appropriate methods to consistently produce accurate and timely management ready information. This work developed an object-based remote sensing approach to map land cover and seagrass distribution in an Australian coastal environment for a 38 year Landsat image time-series archive (1972-2010). Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery were used without in situ field data input (but still using field knowledge) to produce land and seagrass cover maps every year data were available, resulting in over 60 map products over the 38 year archive. Land cover was mapped annually using vegetation, bare ground, urban and agricultural classes. Seagrass distribution was also mapped annually, and in some years monthly, via horizontal projected foliage cover classes, sand and deep water. Land cover products were validated using aerial photography and seagrass maps were validated with field survey data, producing several measures of accuracy. An average overall accuracy of 65% and 80% was reported for seagrass and land cover products respectively, which is consistent with other studies in the area. This study is the first to show moderate spatial resolution, long term annual changes in land cover and seagrass in an Australian environment, created without the use of in situ data; and only one of a few similar studies globally. The land cover products identify several long term trends; such as significant increases in South East Queensland's urban density and extent, vegetation clearing in rural and rural-residential areas, and inter-annual variation in dry vegetation types in western South East Queensland. The seagrass cover products show that there has been a minimal overall change in seagrass extent, but that seagrass cover level distribution is extremely dynamic; evidenced by large scale migrations of higher seagrass cover levels and several sudden and significant changes in cover level. These mapping products will allow management agencies to build a baseline assessment of their resources, understand past changes and help inform implementation and planning of management policy to address potential future changes.
Conservation of wildlife populations: factoring in incremental disturbance.
Stewart, Abbie; Komers, Petr E
2017-06-01
Progressive anthropogenic disturbance can alter ecosystem organization potentially causing shifts from one stable state to another. This potential for ecosystem shifts must be considered when establishing targets and objectives for conservation. We ask whether a predator-prey system response to incremental anthropogenic disturbance might shift along a disturbance gradient and, if it does, whether any disturbance thresholds are evident for this system. Development of linear corridors in forested areas increases wolf predation effectiveness, while high density of development provides a safe-haven for their prey. If wolves limit moose population growth, then wolves and moose should respond inversely to land cover disturbance. Using general linear model analysis, we test how the rate of change in moose ( Alces alces ) density and wolf ( Canis lupus ) harvest density are influenced by the rate of change in land cover and proportion of land cover disturbed within a 300,000 km 2 area in the boreal forest of Alberta, Canada. Using logistic regression, we test how the direction of change in moose density is influenced by measures of land cover change. In response to incremental land cover disturbance, moose declines occurred where <43% of land cover was disturbed; in such landscapes, there were high rates of increase in linear disturbance and wolf density increased. By contrast, moose increases occurred where >43% of land cover was disturbed and wolf density declined. Wolves and moose appeared to respond inversely to incremental disturbance with the balance between moose decline and wolf increase shifting at about 43% of land cover disturbed. Conservation decisions require quantification of disturbance rates and their relationships to predator-prey systems because ecosystem responses to anthropogenic disturbance shift across disturbance gradients.
Spatiotemporal analysis of land use and land cover change in the Brazilian Amazon
Li, Guiying; Moran, Emilio; Hetrick, Scott
2013-01-01
This paper provides a comparative analysis of land use and land cover (LULC) changes among three study areas with different biophysical environments in the Brazilian Amazon at multiple scales, from per-pixel, polygon, census sector, to study area. Landsat images acquired in the years of 1990/1991, 1999/2000, and 2008/2010 were used to examine LULC change trajectories with the post-classification comparison approach. A classification system composed of six classes – forest, savanna, other-vegetation (secondary succession and plantations), agro-pasture, impervious surface, and water, was designed for this study. A hierarchical-based classification method was used to classify Landsat images into thematic maps. This research shows different spatiotemporal change patterns, composition and rates among the three study areas and indicates the importance of analyzing LULC change at multiple scales. The LULC change analysis over time for entire study areas provides an overall picture of change trends, but detailed change trajectories and their spatial distributions can be better examined at a per-pixel scale. The LULC change at the polygon scale provides the information of the changes in patch sizes over time, while the LULC change at census sector scale gives new insights on how human-induced activities (e.g., urban expansion, roads, and land use history) affect LULC change patterns and rates. This research indicates the necessity to implement change detection at multiple scales for better understanding the mechanisms of LULC change patterns and rates. PMID:24127130
Forest Cover Change and Soil Erosion in Toledo's Rio Grande Watershed
NASA Astrophysics Data System (ADS)
Chicas, S.; Omine, K.
2015-04-01
Toledo, the southernmost district, is the hub of Belize's Mayan population, descendants of the ancient Mayan civilization. The Toledo District is primarily inhibited by Kekchi and Mopan Mayans whose subsistence needs are met by the Milpa slash-and-burn agricultural system and the extraction of forest resources. The poverty assessment in the country indicates that Toledo is the district with the highest percentage of household an individual indigence of 37.5 % and 49.7 % respectively. Forest cover change in the area can be attributed to rapid population growth among the Maya, together with increase in immigration from neighboring countries, logging, oil exploration and improvement and construction of roads. The forest cover change analysis show that from 2001 to 2011 there was a decrease of Lowland broad-leaved wet forest of 7.53 km sq, Shrubland of 4.66 km sq, and Wetland of 0.08 km sq. Forest cover change has resulted in soil erosion which is causing the deterioration of soils. The land cover types that are contributing the most to total erosion in the Rio Grande watershed are no-forest, lowland broad-leaved wet forest and submontane broad-leaved wet forest. In this study the Revised Universal Soil Loss Equation (RUSLE) was employed in a GIS platform to quantify and assess forest cover change and soil erosion. Soil erosion vulnerability maps in Toledo's Rio Grande watershed were also created. This study provides scientifically sound information in order to understand and respond effectively to the impacts of soil erosion in the study site.
Estimation of snow line elevation changes from MODIS snow cover data
NASA Astrophysics Data System (ADS)
Parajka, Juraj; Bezak, Nejc; Burkhart, John; Holko, Ladislav; Hundecha, Yeshewa; Krajči, Pavel; Mangini, Walter; Molnar, Peter; Sensoy, Aynur; Riboust, Phillippe; Rizzi, Jonathan; Thirel, Guillaume; Arheimer, Berit
2017-04-01
This contribution evaluates changes in snowline elevation during snowmelt runoff events in selected basins from Austria, France, Norway, Slovakia, Slovenia, Sweden, Switzerland and Turkey. The main objectives are to investigate the spatial and temporal differences in regional snowline elevation (RSLE) across Europe and to discuss the factors which control its change. The analysis is performed in two steps. In the first, the regional snowline elevation is processed from daily MODIS snow cover data (MOD10A1) by using the methodology of Krajčí et al., (2014). In the second step, the changes in RSLE are analysed for selected flood events in the period 2000-2015. The snowmelt runoff events are extracted from Catalogue of identified flood peaks from GRDC dataset (FLOOD TYPE experiment) available at http://www.water-switch-on.eu/sip-webclient/byod/#/resource/12056. The results will be discussed in terms of: (a) availability and potential of MODIS snow cover data for identifying RSLE changes during snowmelt runoff events, (b) spatial and temporal patterns of RSLE changes across Europe and (c) factor controlling the RSLE change. The analysis is performed as an experiment in Virtual Water Science Laboratory of SWITCH-ON Project (http://www.water-switch-on.eu/). All data, tools and results of the analysis will be open and accessible through the Spatial Information Platform of the Project (http://www.water-switch-on.eu/sip-webclient/byod/). We believe that such strategy will allow to improve and forward comparative research and cooperation between different partners in hydrology (Ceola et al., 2015). References Ceola, S., Arheimer, B., Baratti, E., Blöschl, G., Capell, R., Castellarin, A., Freer, J., Han, D., Hrachowitz, M., Hundecha, Y., Hutton, C., Lindström, G., Montanari, A., Nijzink, R., Parajka, J., Toth, E., Viglione, A., and Wagener, T.: Virtual laboratories: new opportunities for collaborative water science, Hydrol. Earth Syst. Sci., 19, 2101-2117, doi:10.5194/hess-19-2101-2015, 2015. Krajčí, P., Holko, L., Perdigão, R.A.P., Parajka, J., Estimation of regional snowline elevation (RSLE) from MODIS images for seasonally snow covered mountain basins,2014,Journal of Hydrology,519,1769-1778
NASA Astrophysics Data System (ADS)
Sanz, Inés; Aguilar, Cristina; Millares, Agustín
2013-04-01
In the last fifty years, forest fires and changes in land use and management practices have had a significant influenceon the evolution of soil loss processes in the Mediterranean area. Forest fires have immediate effects in hydrological processes mainly due to sudden changes in soil properties and vegetation cover. After a fire there is an increase in runoff processes and peak flows and thus in the amount and composition of the sediments produced. Silting in dams downstream is often reported so the description of the post-fire hydrological processes is crucial in order to optimize decision making. This study analyzes a micro-watershed of 25 ha in the south of Spain that suffered a fire in October 2010 burning around a 2 km2 area. As the erosive processes in this area are directly related to concentrated overland flow, an indirect assessment of soil loss is presented in this work based on evaluating changes in runoff in Mediterranean post-fire situations. For this, the study is divided into two main parts. Firstly, changes in soil properties and vegetation cover are evaluated. Secondly, the effects of these changes in the hydrological and erosive dynamics are assessed.The watershed had been monitored in previous studies so soil properties and the vegetation cover before the fire took place were already characterized. Besides, the hydrological response was also available through an already calibrated and validated physically-based distributed hydrological model. For the evaluation of soil properties, field measurement campaigns were designed. Philip Dunne's tests for the determination of saturated hydraulic conductivity, as well as moisture content and bulk density measurements were carried out in both unaltered and burned soil samples. Changes in the vegetation cover fraction were assessed through desktop analysis of Landsat-TM5 platform satellite images as well as through visual inspection in the field campaigns. The analysis of the hydraulic conductivity revealed a reduction in post-fire values of near 90 % over those previous to the fire. Regarding the vegetation cover, the recovery of the burned covers, mainly herbaceous with some bushes, turned out to quick due to the wet character of the year. Nevertheless, an apparent decrease in the cover fraction and thus in the vegetation storage capacity was reported. These changes were incorporated into a new hydrological model configuration and compared to the response previous to the fire. The results point out the rainfall pattern to be a determinant factor in post-fire situation with an increase in modeled runoff of up to 350% and even more in dry years. These results have direct implications in soil erodibility changes in hillslopes as well as a considerable increase in bedload processes in Mediterranean alluvial rivers.
Yin, Jie; Yin, Zhane; Zhong, Haidong; Xu, Shiyuan; Hu, Xiaomeng; Wang, Jun; Wu, Jianping
2011-06-01
This study explored the spatio-temporal dynamics and evolution of land use/cover changes and urban expansion in Shanghai metropolitan area, China, during the transitional economy period (1979-2009) using multi-temporal satellite images and geographic information systems (GIS). A maximum likelihood supervised classification algorithm was employed to extract information from four landsat images, with the post-classification change detection technique and GIS-based spatial analysis methods used to detect land-use and land-cover (LULC) changes. The overall Kappa indices of land use/cover change maps ranged from 0.79 to 0.89. Results indicated that urbanization has accelerated at an unprecedented scale and rate during the study period, leading to a considerable reduction in the area of farmland and green land. Findings further revealed that water bodies and bare land increased, obviously due to large-scale coastal development after 2000. The direction of urban expansion was along a north-south axis from 1979 to 2000, but after 2000 this growth changed to spread from both the existing urban area and along transport routes in all directions. Urban expansion and subsequent LULC changes in Shanghai have largely been driven by policy reform, population growth, and economic development. Rapid urban expansion through clearing of vegetation has led to a wide range of eco-environmental degradation.
Landscape change analysis and assessment (case studies in Slovakia and Bulgaria)
NASA Astrophysics Data System (ADS)
Feranec, Jan; Kopecka, Monika; Vatseva, Rumiana; Stoimenov, Anton; Otahel, Jan; Betak, Juraj; Husar, Karol
2009-03-01
Landscape change assessment was conducted in selected areas of Slovakia and Bulgaria in 1990-2000 using CORINE land cover (CLC) data layer analysis. Assessment of causes that led to these changes was undertaken, with an emphasis on those that determined the extensification of agriculture. The LC data were obtained under the CLC90 and I&CLC2000 projects, jointly managed by the European Environment Agency in Copenhagen, Denmark and the Joint Research Centre of the European Commission in Ispra, Italy. The CLC1990-2000-changes data layer was generated by overlaying the CLC90 and CLC2000 data layers for change in areas of a minimum 5 ha. The analysed causes of changes (driving forces) were then classified. Land cover (LC) changes characterizing urbanization processes occurred only in the Trnava and Tatras areas. Intensification of agriculture was also higher in these two areas. LC changes characterizing the extensification of agriculture were dominant in Plovdiv and Trnava. Deforestation and forestation were identified in all areas (Trnava, Tatras, Plovdiv, and Burgas). The basic reasons of these changes were related to the transformation of national economies from being centrally planned to market controlled, following the fall of socialism and before the countries joined the European Union.
Status and trends of land change in the Eastern United States—1973 to 2000
Sayler, Kristi L.; Acevedo, William; Taylor, Janis
2016-09-28
PrefaceU.S. Geological Survey (USGS) Professional Paper 1794–D is the fourth in a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the Eastern United States between 1973 and 2000. Volumes A, B, and C provide similar analyses for the Western United States, the Great Plains of the United States, and the Midwest–South Central United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation.Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Eastern United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Eastern United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of ecological goods and services and also the determination of risks to, and vulnerabilities of, human communities. Results from this project also are published in peer-reviewed journals, and they are further used to produce maps of change and other tools for land management, as well as to provide inputs for carbon-cycle modeling and other climate change research.This report is only one of the products produced by USGS on land-use and land-cover change in the United States. Other reports and land-cover statistics are available online at http://landcovertrends.usgs.gov.
Status and trends of land change in the Western United States--1973 to 2000
Sleeter, Benjamin M.; Wilson, Tamara S.; Acevedo, William
2012-12-05
U.S. Geological Survey (USGS) Professional Paper 1794–A is the first in a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the Western United States between 1973 and 2000. Volumes B, C, and D provide similar analyses for the Great Plains, the Midwest–South Central United States, and the Eastern United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation. Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Western United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Western United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of ecological goods and services and also the determination of risks to, and vulnerabilities of, human communities. Results from this project also are published in peer-reviewed journals, and they are further used to produce maps of change and other tools for land management, as well as to provide inputs for carbon-cycle modeling and other climate change research. This report is only one of the products produced by USGS on land-use and land-cover change in the United States. Other reports and land-cover statistics are available online at http://landcovertrends.usgs.gov.
Li, Yang; Sun, Qingye; Zhan, Jing; Yang, Yang; Wang, Dan
2017-03-01
Native soil amendment has been widely used to stabilize mine tailings and speed up the development of soil biogeochemical functions before revegetation; however, it remains poorly understood about the response of microbial communities to ecological restoration of mine tailings with soil-covered strategy. In this study, microbial communities along a 60-cm profile were investigated in mine tailings during ecological restoration of two revegetation strategies (directly revegetation and native soil covered) with different plant species. The mine tailings were covered by native soils as thick as 40 cm for more than 10 years, and the total nitrogen, total organic carbon, water content, and heavy metal (Fe, Cu, and Zn) contents in the 0-40 cm intervals of profiles were changed. In addition, increased microbial diversity and changed microbial community structure were also found in the 10-40 cm intervals of profiles in soil-covered area. Soil-covered strategy rather than plant species and soil depth was the main factor influencing the bacterial community, which explained the largest portion (29.96%) of the observed variation. Compared directly to revegetation, soil-covered strategy exhibited the higher relative abundance of Acidobacteria and Deltaproteobacteria and the lower relative abundance of Bacteroidetes, Gemmatimonadetes, Betaproteobacteria, and Gammaproteobacteria. PICRUSt analysis further demonstrated that soil-covered caused energy metabolic functional changes in carbon, nitrogen, and sulfur metabolism. Given all these, the soil-covered strategy may be used to fast-track the establishment of native microbial communities and is conducive to the rehabilitation of biogeochemical processes for establishing native plant species.
NASA Astrophysics Data System (ADS)
Lehnert, Lukas; Wesche, Karsten; Trachte, Katja; Reudenbach, Christoph; Miehe, Georg; Bendix, Jörg
2016-04-01
The Tibetan Plateau has been entitled "Third-Pole-Environment" because of its outstanding importance for the climate and the hydrology in East and South-east Asia. Its climatological and hydrological influences are strongly affected by the local grassland vegetation which is supposed to be subject to ongoing degradation. On a local scale, numerous studies focused on grassland degradation of the Tibetan pastures. However, because methods and scales substantially differed among previous studies, the overall pattern of the degradation in the Tibetan Plateau is unknown. Consequently, a satellite based approach was selected to cope with the spatial limitations. Therefore, a MODIS-based vegetation cover product was developed which is fully validated against 600 in situ measurements covering a wide extent of the Tibetan Plateau. The vegetation cover as a proxy for grassland degradation is modelled with low error rates using support vector machine regressions. To identify the changes in the vegetation cover, the trends seen in the new vegetation cover product since the beginning of the new millennium were analysed. The drivers of the vegetation changes were identified by the analysis of trends of climatic variables (precipitation and 2 m air temperature) and land-use (livestock numbers) over the same time. The results reveal that - in contrast to the prevailing opinion - pasture degradation on the Tibetan Plateau is not a generally proceeding process because areas of positive and negative changes are almost equal in extent. The positive and negative vegetation changes have regionally different triggers: While, from 2000 on, the vegetation cover has increased in the north-eastern part of the Tibetan Plateau due to increasing precipitation, it has declined in the central and western parts due to rising air temperature and declining precipitation. Increasing livestock numbers as a result of land use changes exacerbated the negative trends but, contrarily to the assumptions of former studies, were not their exclusive driver. Thus, it can be concluded that climate variability instead of overgrazing has been the primary cause for large scale vegetation cover changes on the Tibetan Plateau since the new millennium.
Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China
NASA Astrophysics Data System (ADS)
Maimaitiaili, Ayisulitan; Aji, xiaokaiti; Kondoh, Akihiko
2016-04-01
Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China Ayisulitan Maimaitiaili1, Xiaokaiti Aji2 Akihiko Kondoh2 1Graduate School of Science, Chiba University, Japan 2Center for Environmental Remote Sensing, Chiba University The spatio-temporal changes of Land Use/Cover (LUCC) and its driving forces in Kashgar region, Xinjiang Province, China, are investigated by using satellite remote sensing and a geographical information system (GIS). Main goal of this paper is to quantify the drivers of LUCC. First, considering lack of the Land Cover (LC) map in whole study area, we produced LC map by using Landsat images. Land use information from Landsat data was collected using maximum likelihood classification method. Land use change was studied based on the change detection method of land use types. Second, because the snow provides a key water resources for stream flow, agricultural production and drinking water for sustaining large population in Kashgar region, snow cover are estimated by Spot Vegetation data. Normalized Difference Snow Index (NDSI) algorithm are applied to make snow cover map, which is used to screen the LUCC and climate change. The best agreement is found with threshold value of NDSI≥0.2 to generate multi-temporal snow cover and snowmelt maps. Third, driving forces are systematically identified by LC maps and statistical data such as climate and socio-economic data, regarding to i) the climate changes and ii) socioeconomic development that the spatial correlation among LUCC, snow cover change, climate and socioeconomic changes are quantified by using liner regression model and negative / positive trend analysis. Our results showed that water bodies, bare land and grass land have decreasing notably. By contrast, crop land and urban area have continually increasing significantly, which are dominated in study area. The area of snow/ice have fluctuated and has strong seasonal trends, total annual snow cover has two peaks in 2005 and 2009. With increasing population from 2,324,375 in 1984 to 4,228,200 in 2014 and crop land reclamation from 6031.4 km2 in 1972 to 16549km2 in 2014 at the study area. Water resources consumption increased with support to large population and irrigate whole crop land area, caused the water shortages that the surface water bodies decreased from 2531.43km2 in the 1972s to 1067.05km2 in the 2014. The grass land with an acreage larger than 6749km2 in 1972 decreased to 922.6 km2 in 2014. The transformations between water bodies, garss land and bare land are remarkbale. The results also suggested high linearity between the LUCC and socioeconomic changes that specific land cover change be cause of the fact that socioeconomic development. In the recent 42 years, average annual temperature have been increasing significantly, although, precipitation have increased but partly weaken effect of the rising temperature, in addition snow cover more sensitive to precipitation than temperature. Results the change of climate showed a nagitive relationship between the NDSI with decrased of the snow cover and climate with increasing of the tempreature. Morover, the relationship between the LUCC and snow cover recorded higher linearity, because the temperature have increased, consequence influence on snow cover that provides melt water for study area which expanding crop land.
NASA Astrophysics Data System (ADS)
Castaneda, Hector
This work studies the changes of forest cover that have happened in the Lempa River Basin of El Salvador during the period 1979-2003. Although historically the trend has been towards the loss of forest cover since colonial times, over the period of study a large increase in forest cover was detected. The main tool of evaluation was the analysis of LANDSAT satellite imagery. Images for the dates 1979, 1990-91, and 2003 were classified into forest and noon-forest land covers. Then the changes in land cover were analyzed to determine what were the social, geophysical and climatic drivers determining why and where these new forest appeared. The results indicate that there has been an overall increase in forest cover from 20% in 1979 to 43% in 2003. Although there has been extensive deforestation, this has happened mostly around the main urban centers within the basin. In the more rural and remote areas, the tendency has been towards a resurgence in forest cover. The increase in forest was found to be significantly related to remittances, inaccessibility to roads and markets, density of urban populations, poverty and the civil war of the 1980s. Among the geospatial factors that determined where deforestation and reforestation happened were distance to roads and urban centers, slope, elevation, land use capability, and irrigation potential. The results indicate that the tendency in the future will be towards further reforestation but at a slower rate. Although reforestation and deforestation happened simultaneously, there are clear differences in the spatial patterns that each of these phenomena follow. In terms of climate, it was found areas subjected to inter-annual rainfall extremes due to El Nino Southern Oscillation, particularly areas with low agricultural potential, were more likely to be abandoned and left to revert to forest than those with more stable rainfall. The results of this study support the hypothesis that El Salvador is undergoing a Forest Transition process, that is a recuperation of forest cover due to urbanization, migration and economic growth.
A RETROSPECTIVE ANALYSIS OF MODEL UNCERTAINTY FOR FORECASTING HYDROLOGIC CHANGE
GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...
NASA Technical Reports Server (NTRS)
Potter, Christopher S.
2014-01-01
A detailed geographic record of recent vegetation regrowth and disturbance patterns in forests of the Sierra Nevada remains a gap that can be filled with remote sensing data. Landsat (TM) imagery was analyzed to detect 10 years of recent changes (between 2000 and 2009) in forest vegetation cover for areas burned by wildfires between years of 1995 to 1999 in the region. Results confirmed the prevalence of regrowing forest vegetation during the period 2000 and 2009 over 17% of the combined burned areas.
NASA Technical Reports Server (NTRS)
Potter, Christopher
2015-01-01
Landsat imagery was analyzed to understand changes in subalpine forest stands since the mid-1980s in the Sierra-Nevada region of California. At locations where long-term plot measurements have shown that stands are becoming denser in the number of small tree stems (compared to the early 1930s), the 30-year analysis of Landsat greenness index (NDVI) indicated that no consistent increases in canopy leaf cover have occurred at these same locations since the mid-1980s. Interannual variations in stand NDVI closely followed snow accumulation amounts recorded at nearby stations. In contrast, at eastern Sierra whitebark pine stand locations where it has been observed that widespread tree mortality has occurred, decreasing NDVI trends over the past 5-10 years were consistent with rapid loss of forest canopy cover. Landsat imagery was further analyzed to understand patterns of post-wildfire vegetation recovery, focusing on high burn severity (HBS) patches within burned areas dating from the late 1940s. Analysis of landscape metrics showed that the percentage of total HBS area comprised by the largest patch of recovered woody cover was relatively small in all fires that occurred since 1995, but increased rapidly with time since fire. Patch complexity of recovered woody cover decreased notably after more than 50 years of regrowth, but was not readily associated with time for fires that occurred since the mid 1990s. The aggregation level of patches with recovery of woody cover increased steadily with time since fire. The study approach using satellite remote sensing can be expanded to assess the consequences of stand-replacing wildfires in all forests of the region.
Zhai, De-Li; Cannon, Charles H; Dai, Zhi-Cong; Zhang, Cui-Ping; Xu, Jian-Chu
2015-01-01
Hainan, the largest tropical island in China, belongs to the Indo-Burma biodiversity hotspot. The Changhua watershed is a center of endemism for plants and birds and the cradle of Hainan's main rivers. However, this area has experienced recent and ongoing deforestation and habitat fragmentation. To quantify habitat loss and fragmentation of natural forests, as well as the land-cover changes in the Changhua watershed, we analyzed Landsat images obtained in 1988, 1995, and 2005. Land-cover dynamics analysis showed that natural forests increased in area (97,909 to 104,023 ha) from 1988 to 1995 but decreased rapidly to 76,306 ha over the next decade. Rubber plantations increased steadily throughout the study period while pulp plantations rapidly expanded after 1995. Similar patterns of land cover change were observed in protected areas, indicating a lack of enforcement. Natural forests conversion to rubber and pulp plantations has a general negative effect on biodiversity, primarily through habitat fragmentation. The fragmentation analysis showed that natural forests area was reduced and patch number increased, while patch size and connectivity decreased. These land-cover changes threatened local biodiversity, especially island endemic species. Both natural forests losses and fragmentation should be stopped by strict enforcement to prevent further damage. Preserving the remaining natural forests and enforcing the status of protected areas should be a management priority to maximize the watershed's biodiversity conservation value.
Global change and wilderness science
Peter M. Vitousek; John D. Aber; Christine L. Goodale; Gregory H. Aplet
2000-01-01
The breadth and scope of human-caused environmental change is well-established; the distribution and abundance of species, the vegetation cover of the land, and the chemistry of the atmosphere have been altered substantially and globally. How can science in wilderness areas contribute to the analysis of human-caused change? We use nitrate losses from forests to...
Changes in vegetation cover associated with urban planning efforts may affect regional meteorology and air quality. Here we use a comprehensive coupled meteorology-air quality model (WRF-CMAQ) to simulate the influence of planned land use changes from green infrastructure impleme...
NASA Astrophysics Data System (ADS)
Ma, J.; Dmochowski, J. E.
2016-12-01
Southern California's Santa Monica Mountain coastal range hosts chaparral and coastal sage scrub ecosystems with distinct, local variations in their fire regime, microclimate, and proximity to urbanization. The high biodiversity combined with ongoing human impact make monitoring the ecological and land cover changes crucial. Due to their extensive, continuous temporal coverage and high spatial resolution, Landsat data are well suited to this purpose. Landsat-derived time-series NDVI data and classification maps have been compiled to identify regions most sensitive to change in order to determine the effects of fire regime, geography, and urbanization on vegetative changes; and assess the encroachment of non-native grasses. Spatial analysis of the classification maps identified the factors more conducive to land-cover changes as native shrubs were replaced with non-native grasses. Understanding the dynamics that govern semi-arid resilience, overall greening, and fire regime is important to predicting and managing large scale ecosystem changes as pressures from global climate change and urbanization intensify.
NASA Astrophysics Data System (ADS)
Basnet, Bikash
Tracking land surface dynamics over cloud-prone areas with complex mountainous terrain and a landscape that is heterogeneous at a scale of approximately 10 m, is an important challenge in the remote sensing of tropical regions in developing nations, due to the small plot sizes. Persistent monitoring of natural resources in these regions at multiple spatial scales requires development of tools to identify emerging land cover transformation due to anthropogenic causes, such as agricultural expansion and climate change. Along with the cloud cover and obstructions by topographic distortions due to steep terrain, there are limitations to the accuracy of monitoring change using available historical satellite imagery, largely due to sparse data access and the lack of high quality ground truth for classifier training. One such complex region is the Lake Kivu region in Central Africa. This work addressed these problems to create an effective process for monitoring the Lake Kivu region located in Central Africa. The Lake Kivu region is a biodiversity hotspot with a complex and heterogeneous landscape and intensive agricultural development, where individual plot sizes are often at the scale of 10m. Procedures were developed that use optical data from satellite and aerial observations at multiple scales to tackle the monitoring challenges. First, a novel processing chain was developed to systematically monitor the spatio-temporal land cover dynamics of this region over the years 1988, 2001, and 2011 using Landsat data, complemented by ancillary data. Topographic compensation was performed on Landsat reflectances to avoid the strong illumination angle impacts and image compositing was used to compensate for frequent cloud cover and thus incomplete annual data availability in the archive. A systematic supervised classification, using the state-of-the-art machine learning classifier Random Forest, was applied to the composite Landsat imagery to obtain land cover thematic maps with overall accuracies of 90% and higher. Subsequent change analysis between these years found extensive conversions of the natural environment as a result of human related activities. The gross forest cover loss for 1988--2001 and 2001--2011 periods was 216.4 and 130.5 thousand hectares, respectively, signifying significant deforestation in the period of civil war and a relatively stable and lower deforestation rate later, possibly due to conservation and reforestation efforts in the region. The other dominant land cover changes in the region were aggressive subsistence farming and urban expansion displacing natural vegetation and arable lands. Despite limited data availability, this study fills the gap of much needed detailed and updated land cover change information for this biologically important region of Central Africa. While useful on a regional scale, Landsat data can be inadequate for more detailed studies of land cover change. Based on an increasing availability of high resolution imagery and light detection and ranging (LiDAR) data from manned and unmanned aerial platforms (<1m resolution), a study was performed leading to a novel generic framework for land cover monitoring at fine spatial scales. The approach fuses high spatial resolution aerial imagery and LiDAR data to produce land cover maps with high spatial detail using object-based image analysis techniques. The classification framework was tested for a scene with both natural and cultural features and was found to be more than 90 percent accurate, sufficient for detailed land cover change studies.
III SBC Guidelines on the Analysis and Issuance of Electrocardiographic Reports - Executive Summary
Pastore, Carlos Alberto; Samesima, Nelson; Pereira-Filho, Horacio Gomes
2016-01-01
The third version of the guidelines covers recently described topics, such as ion channel diseases, acute ischemic changes, the electrocardiogram in athletes, and analysis of ventricular repolarization. It sought to revise the criteria for overloads, conduction disorders, and analysis of data for internet transmission. PMID:27982266
The dynamics of human-induced land cover change in miombo ecosystems of southern Africa
NASA Astrophysics Data System (ADS)
Jaiteh, Malanding Sambou
Understanding human-induced land cover change in the miombo require the consistent, geographically-referenced, data on temporal land cover characteristics as well as biophysical and socioeconomic drivers of land use, the major cause of land cover change. The overall goal of this research to examine the applications of high-resolution satellite remote sensing data in studying the dynamics of human-induced land cover change in the miombo. Specific objectives are to: (1) evaluate the applications of computer-assisted classification of Landsat Thematic Mapper (TM) data for land cover mapping in the miombo and (2) analyze spatial and temporal patterns of landscape change locations in the miombo. Stepwise Thematic Classification, STC (a hybrid supervised-unsupervised classification) procedure for classifying Landsat TM data was developed and tested using Landsat TM data. Classification accuracy results were compared to those from supervised and unsupervised classification. The STC provided the highest classification accuracy i.e., 83.9% correspondence between classified and referenced data compared to 44.2% and 34.5% for unsupervised and supervised classification respectively. Improvements in the classification process can be attributed to thematic stratification of the image data into spectrally homogenous (thematic) groups and step-by-step classification of the groups using supervised or unsupervised classification techniques. Supervised classification failed to classify 18% of the scene evidence that training data used did not adequately represent all of the variability in the data. Application of the procedure in drier miombo produced overall classification accuracy of 63%. This is much lower than that of wetter miombo. The results clearly demonstrate that digital classification of Landsat TM can be successfully implemented in the miombo without intensive fieldwork. Spatial characteristics of land cover change in agricultural and forested landscapes in central Malawi were analyzed for the period 1984 to 1995 spatial pattern analysis methods. Shifting cultivation areas, Agriculture in forested landscape, experienced highest rate of woodland cover fragmentation with mean patch size of closed woodland cover decreasing from 20ha to 7.5ha. Permanent bare (cropland and settlement) in intensive agricultural matrix landscapes increased 52% largely through the conversion of fallow areas. Protected National Park area remained fairly unchanged although closed woodland area increased by 4%, mainly from regeneration of open woodland. This study provided evidence that changes in spatial characteristics in the miombo differ with landscape. Land use change (i.e. conversion to cropland) is the primary driving force behind changes in landscape spatial patterns. Also, results revealed that exclusion of intense human use (i.e. cultivation and woodcutting) through regulations and/or fencing increased both closed woodland area (through regeneration of open woodland) and overall connectivity in the landscape. Spatial characteristics of land cover change were analyzed at locations in Malawi (wetter miombo) and Zimbabwe (drier miombo). Results indicate land cover dynamics differ both between and within case study sites. In communal areas in the Kasungu scene, land cover change is dominated by woodland fragmentation to open vegetation. Change in private commercial lands was dominantly expansion of bare (settlement and cropland) areas primarily at the expense of open vegetation (fallow land).
Physical and Radiative Characteristics and Long Term Variability of the Okhotsk Sea Ice Cover
NASA Technical Reports Server (NTRS)
Nishio, Fumihiko; Comiso, Josefino C.; Gersten, Robert; Nakayama, Masashige; Ukita, Jinro; Gasiewski, Al; Stanko, Boba; Naoki, Kazuhiro
2007-01-01
Much of what we know about the large scale characteristics of the Okhotsk Sea ice cover comes from ice concentration maps derived from passive microwave data. To understand what these satellite data represents in a highly divergent and rapidly changing environment like the Okhotsk Sea, we analyzed concurrent satellite, aircraft, and ship data and characterized the sea ice cover at different scales from meters to tens of kilometers. Through comparative analysis of surface features using co-registered data from visible, infrared and microwave channels we evaluated how the general radiative and physical characteristics of the ice cover changes as well as quantify the distribution of different ice types in the region. Ice concentration maps from AMSR-E using the standard sets of channels, and also only the 89 GHz channel for optimal resolution, are compared with aircraft and high resolution visible data and while the standard set provides consistent results, the 89 GHz provides the means to observe mesoscale patterns and some unique features of the ice cover. Analysis of MODIS data reveals that thick ice types represents about 37% of the ice cover indicating that young and new ice represent a large fraction of the lice cover that averages about 90% ice concentration, according to passive microwave data. A rapid decline of -9% and -12 % per decade is observed suggesting warming signals but further studies are required because of aforementioned characteristics and because the length of the ice season is decreasing by only 2 to 4 days per decade.
Spatial and temporal land cover changes in Terminos Lagoon Reserve, Mexico.
Soto-Galera, Ernesto; Piera, Jaume; López, Pilar
2010-06-01
Terminos Lagoon ecosystem is the largest fluvial-lagoon estuarine system in the country and one of the most important reserves of coastal flora and fauna in Mexico. Since the seventies, part of the main infrastructure for country's oil extraction is located in this area. Its high biodiversity has motivated different type of studies including deforestation processes and land use planning. In this work we used satellite image analysis to determine land cover changes in the area from 1974 to 2001. Our results indicate that tropical forest and mangroves presented the most extensive losses in its coverage. In contrast, urban areas and induced grassland increased considerably. In 2001 more than half of the ecosystem area showed changes from its original land cover, and a third part of it was deteriorated. The main causes of deforestation were both the increase in grassland and the growth of urban areas. However, deforestation was attenuated by natural reforestation and plant canopy recovery. We conclude that the introduction of cattle and urban development were the main causes for the land cover changes; however, the oil industry activity located in the ecosystem, has promoted indirectly to urban growth and rancher boom.
Lohr, Cheryl; Van Dongen, Ricky; Huntley, Bart; Gibson, Lesley; Morris, Keith
2014-01-01
The Montebello archipelago consists of 218 islands; 80 km from the north-west coast of Western Australia. Before 1912 the islands had a diverse terrestrial fauna. By 1952 several species were locally extinct. Between 1996 and 2011 rodents and cats were eradicated, and 5 mammal and 2 bird species were translocated to the islands. Monitoring of the broader terrestrial ecosystem over time has been limited. We used 20 dry-season Landsat images from 1988 to 2013 and estimation of green fraction cover in nadir photographs taken at 27 sites within the Montebello islands and six sites on Thevenard Island to assess change in vegetation density over time. Analysis of data averaged across the 26-year period suggests that 719 ha out of 2169 ha have increased in vegetation cover by up to 32%, 955 ha have remained stable and 0.6 ha have declined in vegetation cover. Over 492 ha (22%) had no vegetation cover at any time during the period analysed. Chronological clustering analysis identified two breakpoints in the average vegetation cover data occurring in 1997 and 2003, near the beginning and end of the rodent eradication activities. On many islands vegetation cover was declining prior to 1996 but increased after rodents were eradicated from the islands. Data for North West and Trimouille islands were analysed independently because of the potential confounding effect of native fauna being introduced to these islands. Mala (Lagorchestes hirsutus) and Shark Bay mice (Pseudomys fieldi) both appear to suppress native plant recruitment but not to the same degree as introduced rodents. Future research should assess whether the increase in vegetation cover on the Montebello islands is due to an increase in native or introduced plants. PMID:25436454
Boyte, Stephen P.; Wylie, Bruce K.; Major, Donald J.
2016-01-01
Cheatgrass (Bromus tectorum L.) is a highly invasive species in the Northern Great Basin that helps decrease fire return intervals. Fire fragments the shrub steppe and reduces its capacity to provide forage for livestock and wildlife and habitat critical to sagebrush obligates. Of particular interest is the greater sage grouse (Centrocercus urophasianus), an obligate whose populations have declined so severely due, in part, to increases in cheatgrass and fires that it was considered for inclusion as an endangered species. Remote sensing technologies and satellite archives help scientists monitor terrestrial vegetation globally, including cheatgrass in the Northern Great Basin. Along with geospatial analysis and advanced spatial modeling, these data and technologies can identify areas susceptible to increased cheatgrass cover and compare these with greater sage grouse priority areas for conservation (PAC). Future climate models forecast a warmer and wetter climate for the Northern Great Basin, which likely will force changing cheatgrass dynamics. Therefore, we examine potential climate-caused changes to cheatgrass. Our results indicate that future cheatgrass percent cover will remain stable over more than 80% of the study area when compared with recent estimates, and higher overall cheatgrass cover will occur with slightly more spatial variability. The land area projected to increase or decrease in cheatgrass cover equals 18% and 1%, respectively, making an increase in fire disturbances in greater sage grouse habitat likely. Relative susceptibility measures, created by integrating cheatgrass percent cover and temporal standard deviation datasets, show that potential increases in future cheatgrass cover match future projections. This discovery indicates that some greater sage grouse PACs for conservation could be at heightened risk of fire disturbance. Multiple factors will affect future cheatgrass cover including changes in precipitation timing and totals and increases in freeze-thaw cycles. Understanding these effects can help direct land management, guide scientific research, and influence policy.
Lowe, Phillip K; Bruno, John F; Selig, Elizabeth R; Spencer, Matthew
2011-01-01
There has been substantial recent change in coral reef communities. To date, most analyses have focussed on static patterns or changes in single variables such as coral cover. However, little is known about how community-level changes occur at large spatial scales. Here, we develop Markov models of annual changes in coral and macroalgal cover in the Caribbean and Great Barrier Reef (GBR) regions. We analyzed reef surveys from the Caribbean and GBR (1996-2006). We defined a set of reef states distinguished by coral and macroalgal cover, and obtained Bayesian estimates of the annual probabilities of transitions between these states. The Caribbean and GBR had different transition probabilities, and therefore different rates of change in reef condition. This could be due to differences in species composition, management or the nature and extent of disturbances between these regions. We then estimated equilibrium probability distributions for reef states, and coral and macroalgal cover under constant environmental conditions. In both regions, the current distributions are close to equilibrium. In the Caribbean, coral cover is much lower and macroalgal cover is higher at equilibrium than in the GBR. We found no evidence for differences in transition probabilities between the first and second halves of our survey period, or between Caribbean reefs inside and outside marine protected areas. However, our power to detect such differences may have been low. We also examined the effects of altering transition probabilities on the community state equilibrium, along a continuum from unfavourable (e.g., increased sea surface temperature) to favourable (e.g., improved management) conditions. Both regions showed similar qualitative responses, but different patterns of uncertainty. In the Caribbean, uncertainty was greatest about effects of favourable changes, while in the GBR, we are most uncertain about effects of unfavourable changes. Our approach could be extended to provide risk analysis for management decisions.
NASA Astrophysics Data System (ADS)
Putri Utami, Nadia; Ahamed, Tofael
2018-05-01
Karawang, a suburban area of Greater Jakarta, is known as the second largest rice-producing region in West Java, Indonesia. However, expansion of urban sprawl and industrial area from Greater Jakarta have created rapid agricultural land use/cover changes, especially paddy field, in Karawang. This study analyzed the land use/cover changes of paddy field from 2000 to 2016. Landsat 4-5 TM and Landsat 8 OLI/TIRS images were acquired from USGS Earth Explorer, UTM zone 48 south. Satellite image pre-processing, ground truth data collection, supervised maximum likelihood classifications, and Post-Classification Comparison (PCC) were performed in ArcGIS 10.3®. It was observed between 2000 and 2016, urban area increased 4.46% (8530 ha) from initial area of 10,004 ha. Meanwhile paddy field decreased 3.18% (6091 ha) from initial area of 115,720 ha. The spatial analysis showed that paddy field in the fringe of urban area are more susceptible for changes.
Assessing uncertainties in land cover projections.
Alexander, Peter; Prestele, Reinhard; Verburg, Peter H; Arneth, Almut; Baranzelli, Claudia; Batista E Silva, Filipe; Brown, Calum; Butler, Adam; Calvin, Katherine; Dendoncker, Nicolas; Doelman, Jonathan C; Dunford, Robert; Engström, Kerstin; Eitelberg, David; Fujimori, Shinichiro; Harrison, Paula A; Hasegawa, Tomoko; Havlik, Petr; Holzhauer, Sascha; Humpenöder, Florian; Jacobs-Crisioni, Chris; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Lavalle, Carlo; Lenton, Tim; Liu, Jiayi; Meiyappan, Prasanth; Popp, Alexander; Powell, Tom; Sands, Ronald D; Schaldach, Rüdiger; Stehfest, Elke; Steinbuks, Jevgenijs; Tabeau, Andrzej; van Meijl, Hans; Wise, Marshall A; Rounsevell, Mark D A
2017-02-01
Understanding uncertainties in land cover projections is critical to investigating land-based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro-economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover. © 2016 John Wiley & Sons Ltd.
Olang, Luke Omondi; Kundu, Peter; Bauer, Thomas; Fürst, Josef
2011-08-01
The spatio-temporal changes in the land cover states of the Nyando Basin were investigated for auxiliary hydrological impact assessment. The predominant land cover types whose conversions could influence the hydrological response of the region were selected. Six Landsat images for 1973, 1986, and 2000 were processed to discern the changes based on a methodology that employs a hybrid of supervised and unsupervised classification schemes. The accuracy of the classifications were assessed using reference datasets processed in a GIS with the help of ground-based information obtained through participatory mapping techniques. To assess the possible hydrological effect of the detected changes during storm events, a physically based lumped approach for infiltration loss estimation was employed within five selected sub-basins. The results obtained indicated that forests in the basin declined by 20% while agricultural fields expanded by 16% during the entire period of study. Apparent from the land cover conversion matrices was that the majority of the forest decline was a consequence of agricultural expansion. The model results revealed decreased infiltration amounts by between 6% and 15%. The headwater regions with the vast deforestation were noted to be more vulnerable to the land cover change effects. Despite the haphazard land use patterns and uncertainties related to poor data quality for environmental monitoring and assessment, the study exposed the vast degradation and hence the need for sustainable land use planning for enhanced catchment management purposes.
NASA Astrophysics Data System (ADS)
Saranya, K. R. L.; Reddy, C. Sudhakar
2016-04-01
The spatial changes in forest cover of Similipal biosphere reserve, Odisha, India over eight decades (1930-2012) has been quantified by using multi-temporal data from different sources. Over the period, the forest cover reduced by 970.8 km2 (23.6% of the total forest), and most significantly during the period, 1930-1975. Human-induced activities like conversion of forest land for agriculture, construction of dams and mining activities have been identified as major drivers of deforestation. Spatial analysis indicates that 399 grids (1 grid = 1 × 1 km) have undergone large-scale changes in forest cover (>75 ha) during 1930-1975, while only 3 grids have shown >75 ha loss during 1975-1990. Annual net rate of deforestation was 0.58 during 1930-1975, which has been reduced substantially during 1975-1990 (0.04). Annual gross rate of deforestation in 2006-2012 is indeed low (0.01) as compared to the national and global average. This study highlights the impact and effectiveness of conservation practices in minimizing the rate of deforestation and protecting the Similipal Biosphere Reserve.
Land cover mapping after the tsunami event over Nanggroe Aceh Darussalam (NAD) province, Indonesia
NASA Astrophysics Data System (ADS)
Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Alias, A. N.; Mohd. Saleh, N.; Wong, C. J.; Surbakti, M. S.
2008-03-01
Remote sensing offers an important means of detecting and analyzing temporal changes occurring in our landscape. This research used remote sensing to quantify land use/land cover changes at the Nanggroe Aceh Darussalam (Nad) province, Indonesia on a regional scale. The objective of this paper is to assess the changed produced from the analysis of Landsat TM data. A Landsat TM image was used to develop land cover classification map for the 27 March 2005. Four supervised classifications techniques (Maximum Likelihood, Minimum Distance-to- Mean, Parallelepiped and Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier) were performed to the satellite image. Training sites and accuracy assessment were needed for supervised classification techniques. The training sites were established using polygons based on the colour image. High detection accuracy (>80%) and overall Kappa (>0.80) were achieved by the Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier in this study. This preliminary study has produced a promising result. This indicates that land cover mapping can be carried out using remote sensing classification method of the satellite digital imagery.
Assessment of land cover changes in Lampedusa Island (Italy) using Landsat TM and OLI data
NASA Astrophysics Data System (ADS)
Mei, Alessandro; Manzo, Ciro; Fontinovo, Giuliano; Bassani, Cristiana; Allegrini, Alessia; Petracchini, Francesco
2016-10-01
The Lampedusa Island displays important socio-economic criticalities related to an intensive touristic activity, which implies an increase in electricity consumption and waste production. An adequate island conversion to a more environmental, sustainable community needs to be faced by the local Management Plans establishment. For this purpose, several thematic datasets have to be produced and evaluated. Socio-economic and bio-ecological components as well as land cover/use assessment are some of the main topics to be managed within the Decision Support Systems. Considering the lack of Land Cover (LC) and vegetation change detection maps in Lampedusa Island (Italy), this paper focuses on the retrieval of these topics by remote sensing techniques. The analysis was carried out by Landsat 5 TM and Landsat 8 OLI multispectral images from 1984 to 2014 in order to obtain spatial and temporal information of changes occurred in the island. Firstly, imagery was co-registered and atmospherically corrected; secondly, it was then classified for land cover and vegetation distribution analysis with the use of QGIS and Saga GIS open source softwares. The Maximum Likelihood Classifier (MLC) was used for LC maps production, while the Normalized Difference Vegetation Index (NDVI) was used for vegetation examination and distribution. Topographic maps, historical aerial photos, ortophotos and field data are merged in the GIS for accuracy assessment. Finally, change detection of MLC and NDVI are provided respectively by Post-Classification Comparison (PCC) and Image Differencing (ID). The provided information, combined with local socio-economic parameters, is essential for the improvement of environmental sustainability of anthropogenic activities in Lampedusa.
National housing and impervious surface scenarios for integrated climate impact assessments
Bierwagen, Britta G.; Theobald, David M.; Pyke, Christopher R.; Choate, Anne; Groth, Philip; Thomas, John V.; Morefield, Philip
2010-01-01
Understanding the impacts of climate change on people and the environment requires an understanding of the dynamics of both climate and land use/land cover changes. A range of future climate scenarios is available for the conterminous United States that have been developed based on widely used international greenhouse gas emissions storylines. Climate scenarios derived from these emissions storylines have not been matched with logically consistent land use/cover maps for the United States. This gap is a critical barrier to conducting effective integrated assessments. This study develops novel national scenarios of housing density and impervious surface cover that are logically consistent with emissions storylines. Analysis of these scenarios suggests that combinations of climate and land use/cover can be important in determining environmental conditions regulated under the Clean Air and Clean Water Acts. We found significant differences in patterns of habitat loss and the distribution of potentially impaired watersheds among scenarios, indicating that compact development patterns can reduce habitat loss and the number of impaired watersheds. These scenarios are also associated with lower global greenhouse gas emissions and, consequently, the potential to reduce both the drivers of anthropogenic climate change and the impacts of changing conditions. The residential housing and impervious surface datasets provide a substantial first step toward comprehensive national land use/land cover scenarios, which have broad applicability for integrated assessments as these data and tools are publicly available. PMID:21078956
Mihai, Bogdan; Săvulescu, Ionuț; Rujoiu-Mare, Marina; Nistor, Constantin
2017-12-01
The paper explores the dynamics of the forest cover change in the Iezer Mountains, part of Southern Carpathians, in the context of the forest ownership recovery and deforestation processes, combined with the effects of biotic and abiotic disturbances. The aim of the study is to map and evaluate the typology and the spatial extension of changes in the montane forest cover between 700 and 2462m a.s.l., sampling all the representative Carpathian ecosystems, from the European beech zone up to the spruce-fir zone and the subalpine-alpine pastures. The methodology uses a change detection analysis of satellite imagery with Landsat ETM+/OLI and Sentinel-2 MSI data. The workflow started with a complete calibration of multispectral data from 2002, before the massive forest restitution to private owners, after the Law 247/2005 empowerment, and 2015, the intensification of deforestation process. For the data classification, a Maximum Likelihood supervised classification algorithm was utilized. The forest change map was developed after combining the classifications in a unitary formula using image difference. The principal outcome of the research identifies the type of forest cover change using a quantitative formula. This information can be integrated in the future decision-making strategies for forest stand management and sustainable development. Copyright © 2017 Elsevier B.V. All rights reserved.
Projected changes to growth and mortality of Hawaiian corals over the next 100 years.
Hoeke, Ron K; Jokiel, Paul L; Buddemeier, Robert W; Brainard, Russell E
2011-03-29
Recent reviews suggest that the warming and acidification of ocean surface waters predicated by most accepted climate projections will lead to mass mortality and declining calcification rates of reef-building corals. This study investigates the use of modeling techniques to quantitatively examine rates of coral cover change due to these effects. Broad-scale probabilities of change in shallow-water scleractinian coral cover in the Hawaiian Archipelago for years 2000-2099 A.D. were calculated assuming a single middle-of-the-road greenhouse gas emissions scenario. These projections were based on ensemble calculations of a growth and mortality model that used sea surface temperature (SST), atmospheric carbon dioxide (CO(2)), observed coral growth (calcification) rates, and observed mortality linked to mass coral bleaching episodes as inputs. SST and CO(2) predictions were derived from the World Climate Research Programme (WCRP) multi-model dataset, statistically downscaled with historical data. The model calculations illustrate a practical approach to systematic evaluation of climate change effects on corals, and also show the effect of uncertainties in current climate predictions and in coral adaptation capabilities on estimated changes in coral cover. Despite these large uncertainties, this analysis quantitatively illustrates that a large decline in coral cover is highly likely in the 21(st) Century, but that there are significant spatial and temporal variances in outcomes, even under a single climate change scenario.
Projected changes to growth and mortality of Hawaiian corals over the next 100 years
Hoeke, R.K.; Jokiel, P.L.; Buddemeier, R.W.; Brainard, R.E.
2011-01-01
Background: Recent reviews suggest that the warming and acidification of ocean surface waters predicated by most accepted climate projections will lead to mass mortality and declining calcification rates of reef-building corals. This study investigates the use of modeling techniques to quantitatively examine rates of coral cover change due to these effects. Methodology/Principal Findings: Broad-scale probabilities of change in shallow-water scleractinian coral cover in the Hawaiian Archipelago for years 2000-2099 A.D. were calculated assuming a single middle-of-the-road greenhouse gas emissions scenario. These projections were based on ensemble calculations of a growth and mortality model that used sea surface temperature (SST), atmospheric carbon dioxide (CO2), observed coral growth (calcification) rates, and observed mortality linked to mass coral bleaching episodes as inputs. SST and CO2 predictions were derived from the World Climate Research Programme (WCRP) multi-model dataset, statistically downscaled with historical data. Conclusions/Significance: The model calculations illustrate a practical approach to systematic evaluation of climate change effects on corals, and also show the effect of uncertainties in current climate predictions and in coral adaptation capabilities on estimated changes in coral cover. Despite these large uncertainties, this analysis quantitatively illustrates that a large decline in coral cover is highly likely in the 21st Century, but that there are significant spatial and temporal variances in outcomes, even under a single climate change scenario.
Occidental Geothermal, Inc. , Oxy geothermal power plant No. 1. Final environmental impact report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1981-12-01
The project-specific environmental analysis covers the following: geology, soils, water resources, biology, air quality, noise, waste management, health, safety, transportation, energy and material resources, cultural resources, socioeconomics, public services, land use, and aesthetics. Other topics covered are: the cumulative envionmental analysis; unavoidable significant adverse environmental effects; irreversible environmental changes and irretrievable commitments of energy and materials; the relationship between local short-term uses of man's environment and the maintenance and enhancement of long-term productivity; growth-inducing impacts; and alternatives to the proposed action. (MHR)
Satish, K V; Saranya, K R L; Reddy, C Sudhakar; Krishna, P Hari; Jha, C S; Rao, P V V Prasada
2014-12-01
Deforestation in the biosphere reserves, which are key Protected Areas has negative impacts on biodiversity, climate, carbon fluxes and livelihoods. Comprehensive study of deforestation in biosphere reserves is required to assess the impact of the management effectiveness. This article assesses the changes in forest cover in various zones and protected areas of Nilgiri Biosphere Reserve, the first declared biosphere reserve in India which forms part of Western Ghats-a global biodiversity hotspot. In this study, we have mapped the forests from earliest available topographical maps and multi-temporal satellite data spanning from 1920's to 2012 period. Mapping of spatial extent of forest cover, vegetation types and land cover was carried out using visual interpretation technique. A grid cell of 1 km × 1 km was generated for time series change analysis to understand the patterns in spatial distribution of forest cover (1920-1973-1989-1999-2006-2012). The total forest area of biosphere reserve was found to be 5,806.5 km(2) (93.8 % of total geographical area) in 1920. Overall loss of forest cover was estimated as 1,423.6 km(2) (24.5 % of the total forest) with reference to 1920. Among the six Protected Areas, annual deforestation rate of >0.5 was found in Wayanad wildlife sanctuary during 1920-1973. The deforestation in Nilgiri Biosphere Reserve is mainly attributed to conversion of forests to plantations and agriculture along with submergence due to construction of dams during 1920 to 1989. Grid wise analysis indicates that 851 grids have undergone large-scale negative changes of >75 ha of forest loss during 1920-1973 while, only 15 grids have shown >75 ha loss during 1973-1989. Annual net rate of deforestation for the period of 1920 to 1973 was calculated as 0.5 followed by 0.1 for 1973 to 1989. Our analysis shows that there was large-scale deforestation before the declaration of area as biosphere reserve in 1986; however, the deforestation has drastically reduced after the declaration due to high degree of protection, thus indicating the secure future of reserve in the long term under the current forest management practices. The present work will stand as the most up-to-date assessment on the forest cover of the Nilgiri Biosphere Reserve with immediate applications in monitoring and management of forest biodiversity.
The Changing Nature of Work. Trend Analysis Report. TAP 17.
ERIC Educational Resources Information Center
American Council of Life Insurance, New York, NY.
This report on the changing nature of work examines developing issues and potential changes in the world of work relevant to life insurance company management. The main body of the report is divided into three sections. Topics covered in the first section are demography, women, minorities, the young worker, and blurring work roles. Challenges to…
Rafanoharana, Serge; Boissière, Manuel; Wijaya, Arief; Wardhana, Wahyu
2016-01-01
Remote sensing has been widely used for mapping land cover and is considered key to monitoring changes in forest areas in the REDD+ Measurement, Reporting and Verification (MRV) system. But Remote Sensing as a desk study cannot capture the whole picture; it also requires ground checking. Therefore, complementing remote sensing analysis using participatory mapping can help provide information for an initial forest cover assessment, gain better understanding of how local land use might affect changes, and provide a way to engage local communities in REDD+. Our study looked at the potential of participatory mapping in providing complementary information for remotely sensed maps. The research sites were located in different ecological and socio-economic contexts in the provinces of Papua, West Kalimantan and Central Java, Indonesia. Twenty-one maps of land cover and land use were drawn with local community participation during focus group discussions in seven villages. These maps, covering a total of 270,000ha, were used to add information to maps developed using remote sensing, adding 39 land covers to the eight from our initial desk assessment. They also provided additional information on drivers of land use and land cover change, resource areas, territory claims and land status, which we were able to correlate to understand changes in forest cover. Incorporating participatory mapping in the REDD+ MRV protocol would help with initial remotely sensed land classifications, stratify an area for ground checks and measurement plots, and add other valuable social data not visible at the RS scale. Ultimately, it would provide a forum for local communities to discuss REDD+ activities and develop a better understanding of REDD+. PMID:27977685
Status and trends of land change in selected U.S. ecoregions - 2000 to 2011
Sayler, Kristi L.; Acevedo, William; Taylor, Janis
2016-01-01
U.S. Geological Survey scientists developed a dataset of 2006 and 2011 land-use and land-cover (LULC) information for selected 100-km2 sample blocks within 29 U.S. Environmental Protection Agency (EPA) Level III ecoregions across the conterminous United States. The data can be used with the previously published Land Cover Trends Dataset: 1973 to 2000 to assess landuse/land-cover change across a 37-year study period. Results from analysis of these data include ecoregion-based statistical estimates of the amount of LULC change per time period, ranking of the most common types of conversions, rates of change, and percent composition. Overall estimated amount of change per ecoregion from 2001 to 2011 ranged from a low of 370 km2 in the Northern Basin and Range Ecoregion to a high of 78,782 km2 in the Southeastern Plains Ecoregion. The Southeastern Plains continues to encompass one of the most intense forest harvesting and regrowth regions in the country, with 16.6 percent of the ecoregion changing between 2001 and 2011. These LULC change statistics provide a new, valuable resource that complements other reference data and field-verified LULC data. Researchers can use this resource to independently validate other land change products or to conduct regional land change assessments.
Buddhi R. Gyawali; Rory F. Fraser; Yong Wang; Wubishet Tadesse; James Bukenya; John Schelhas
2006-01-01
Previous studies at the county level have found an increase in forest cover, urbanization, and water structures in the Black Belt counties of Alabama and have documented the connection between such increase and socioeconomic development in the region. However, such findings have limited inferences as the studies did not address the variations in demographic,...
John Rogan; Kelley O' Neal; Stephen Yool
2005-01-01
This paper examined the application of state-of-the-art remote sensing image enhancement and classification techniques for mapping land cover change in the Peloncillo Mountains of Arizona and New Mexico. Spectrally enhanced images acquired August 1985, 1991, 1996, and 2000 were combined with environmental variables such as slope and aspect to map land cover...
Sara A. Goeking; Greg C. Liknes; Erik Lindblom; John Chase; Dennis M. Jacobs; Robert. Benton
2012-01-01
Recent changes to the Forest Inventory and Analysis (FIA) Program's definition of forest land precipitated the development of a geographic information system (GIS)-based tool for efficiently estimating tree canopy cover for all FIA plots. The FIA definition of forest land has shifted from a density-related criterion based on stocking to a 10 percent tree canopy...
NASA Astrophysics Data System (ADS)
Lyons, Mitchell B.; Roelfsema, Chris M.; Phinn, Stuart R.
2013-03-01
The spatial and temporal dynamics of seagrasses have been well studied at the leaf to patch scales, however, the link to large spatial extent landscape and population dynamics is still unresolved in seagrass ecology. Traditional remote sensing approaches have lacked the temporal resolution and consistency to appropriately address this issue. This study uses two high temporal resolution time-series of thematic seagrass cover maps to examine the spatial and temporal dynamics of seagrass at both an inter- and intra-annual time scales, one of the first globally to do so at this scale. Previous work by the authors developed an object-based approach to map seagrass cover level distribution from a long term archive of Landsat TM and ETM+ images on the Eastern Banks (≈200 km2), Moreton Bay, Australia. In this work a range of trend and time-series analysis methods are demonstrated for a time-series of 23 annual maps from 1988 to 2010 and a time-series of 16 monthly maps during 2008-2010. Significant new insight was presented regarding the inter- and intra-annual dynamics of seagrass persistence over time, seagrass cover level variability, seagrass cover level trajectory, and change in area of seagrass and cover levels over time. Overall we found that there was no significant decline in total seagrass area on the Eastern Banks, but there was a significant decline in seagrass cover level condition. A case study of two smaller communities within the Eastern Banks that experienced a decline in both overall seagrass area and condition are examined in detail, highlighting possible differences in environmental and process drivers. We demonstrate how trend and time-series analysis enabled seagrass distribution to be appropriately assessed in context of its spatial and temporal history and provides the ability to not only quantify change, but also describe the type of change. We also demonstrate the potential use of time-series analysis products to investigate seagrass growth and decline as well as the processes that drive it. This study demonstrates clear benefits over traditional seagrass mapping and monitoring approaches, and provides a proof of concept for the use of trend and time-series analysis of remotely sensed seagrass products to benefit current endeavours in seagrass ecology.
Snow Cover and Vegetation-Induced Decrease in Global Albedo From 2002 to 2016
NASA Astrophysics Data System (ADS)
Li, Qiuping; Ma, Mingguo; Wu, Xiaodan; Yang, Hong
2018-01-01
Land surface albedo is an essential parameter in regional and global climate models, and it is markedly influenced by land cover change. Variations in the albedo can affect the surface radiation budget and further impact the global climate. In this study, the interannual variation of albedo from 2002 to 2016 was estimated on the global scale using Moderate Resolution Imaging Spectroradiometer (MODIS) datasets. The presence and causes of the albedo changes for each specific region were also explored. From 2002 to 2016, the MODIS-based albedo decreased globally, snow cover declined by 0.970 (percent per pixel), while the seasonally integrated normalized difference vegetation index increased by 0.175. Some obvious increases in the albedo were detected in Central Asia, northeastern China, parts of the boreal forest in Canada, and the temperate steppe in North America. In contrast, noticeable decreases in the albedo were found in the Siberian tundra, Europe, southeastern Australia, and northeastern regions of North America. In the Northern Hemisphere, the greening trend at high latitudes made more contribution to the decline in the albedo. However, the dramatic fluctuation of snow-cover at midlatitudes predominated in the change of albedo. Our analysis can help to understand the roles that vegetation and snow cover play in the variation of albedo on global and regional scales.
Zomer, Robert J; Neufeldt, Henry; Xu, Jianchu; Ahrends, Antje; Bossio, Deborah; Trabucco, Antonio; van Noordwijk, Meine; Wang, Mingcheng
2016-07-20
Agroforestry systems and tree cover on agricultural land make an important contribution to climate change mitigation, but are not systematically accounted for in either global carbon budgets or national carbon accounting. This paper assesses the role of trees on agricultural land and their significance for carbon sequestration at a global level, along with recent change trends. Remote sensing data show that in 2010, 43% of all agricultural land globally had at least 10% tree cover and that this has increased by 2% over the previous ten years. Combining geographically and bioclimatically stratified Intergovernmental Panel on Climate Change (IPCC) Tier 1 default estimates of carbon storage with this tree cover analysis, we estimated 45.3 PgC on agricultural land globally, with trees contributing >75%. Between 2000 and 2010 tree cover increased by 3.7%, resulting in an increase of >2 PgC (or 4.6%) of biomass carbon. On average, globally, biomass carbon increased from 20.4 to 21.4 tC ha(-1). Regional and country-level variation in stocks and trends were mapped and tabulated globally, and for all countries. Brazil, Indonesia, China and India had the largest increases in biomass carbon stored on agricultural land, while Argentina, Myanmar, and Sierra Leone had the largest decreases.
NASA Astrophysics Data System (ADS)
Sukawattanavijit, Chanika; Srestasathiern, Panu
2017-10-01
Land Use and Land Cover (LULC) information are significant to observe and evaluate environmental change. LULC classification applying remotely sensed data is a technique popularly employed on a global and local dimension particularly, in urban areas which have diverse land cover types. These are essential components of the urban terrain and ecosystem. In the present, object-based image analysis (OBIA) is becoming widely popular for land cover classification using the high-resolution image. COSMO-SkyMed SAR data was fused with THAICHOTE (namely, THEOS: Thailand Earth Observation Satellite) optical data for land cover classification using object-based. This paper indicates a comparison between object-based and pixel-based approaches in image fusion. The per-pixel method, support vector machines (SVM) was implemented to the fused image based on Principal Component Analysis (PCA). For the objectbased classification was applied to the fused images to separate land cover classes by using nearest neighbor (NN) classifier. Finally, the accuracy assessment was employed by comparing with the classification of land cover mapping generated from fused image dataset and THAICHOTE image. The object-based data fused COSMO-SkyMed with THAICHOTE images demonstrated the best classification accuracies, well over 85%. As the results, an object-based data fusion provides higher land cover classification accuracy than per-pixel data fusion.
NASA Astrophysics Data System (ADS)
Wang, Jie; Wang, Hao; Ning, Shaowei; Hiroshi, Ishidaira
2018-06-01
Sediment load can provide very important perspective on erosion of river basin. The changes of human-induced vegetation cover, such as deforestation or afforestation, affect sediment yield process of a catchment. We have already evaluated that climate change and land cover change changed the historical streamflow and sediment yield, and land cover change is the main factor in Red river basin. But future streamflow and sediment yield changes under potential future land cover change scenario still have not been evaluated. For this purpose, future scenario of land cover change is developed based on historical land cover changes and land change model (LCM). In addition, future leaf area index (LAI) is simulated by ecological model (Biome-BGC) based on future land cover scenario. Then future scenarios of land cover change and LAI are used to drive hydrological model and new sediment rating curve. The results of this research provide information that decision-makers need in order to promote water resources planning efforts. Besides that, this study also contributes a basic framework for assessing climate change impacts on streamflow and sediment yield that can be applied in the other basins around the world.
Asner, Gregory P; Joseph, Shijo
2015-01-01
Conservation and monitoring of tropical forests requires accurate information on their extent and change dynamics. Cloud cover, sensor errors and technical barriers associated with satellite remote sensing data continue to prevent many national and sub-national REDD+ initiatives from developing their reference deforestation and forest degradation emission levels. Here we present a framework for large-scale historical forest cover change analysis using free multispectral satellite imagery in an extremely cloudy tropical forest region. The CLASlite approach provided highly automated mapping of tropical forest cover, deforestation and degradation from Landsat satellite imagery. Critically, the fractional cover of forest photosynthetic vegetation, non-photosynthetic vegetation, and bare substrates calculated by CLASlite provided scene-invariant quantities for forest cover, allowing for systematic mosaicking of incomplete satellite data coverage. A synthesized satellite-based data set of forest cover was thereby created, reducing image incompleteness caused by clouds, shadows or sensor errors. This approach can readily be implemented by single operators with highly constrained budgets. We test this framework on tropical forests of the Colombian Pacific Coast (Chocó) – one of the cloudiest regions on Earth, with successful comparison to the Colombian government’s deforestation map and a global deforestation map. PMID:25678933
Xu, Chi; Holmgren, Milena; Van Nes, Egbert H; Hirota, Marina; Chapin, F Stuart; Scheffer, Marten
2015-01-01
Publicly available remote sensing products have boosted science in many ways. The openness of these data sources suggests high reproducibility. However, as we show here, results may be specific to versions of the data products that can become unavailable as new versions are posted. We focus on remotely-sensed tree cover. Recent studies have used this public resource to detect multi-modality in tree cover in the tropical and boreal biomes. Such patterns suggest alternative stable states separated by critical tipping points. This has important implications for the potential response of these ecosystems to global climate change. For the boreal region, four distinct ecosystem states (i.e., treeless, sparse and dense woodland, and boreal forest) were previously identified by using the Collection 3 data of MODIS Vegetation Continuous Fields (VCF). Since then, the MODIS VCF product has been updated to Collection 5; and a Landsat VCF product of global tree cover at a fine spatial resolution of 30 meters has been developed. Here we compare these different remote-sensing products of tree cover to show that identification of alternative stable states in the boreal biome partly depends on the data source used. The updated MODIS data and the newer Landsat data consistently demonstrate three distinct modes around similar tree-cover values. Our analysis suggests that the boreal region has three modes: one sparsely vegetated state (treeless), one distinct 'savanna-like' state and one forest state, which could be alternative stable states. Our analysis illustrates that qualitative outcomes of studies may change fundamentally as new versions of remote sensing products are used. Scientific reproducibility thus requires that old versions remain publicly available.
Observed climate variability over Chad using multiple observational and reanalysis datasets
NASA Astrophysics Data System (ADS)
Maharana, Pyarimohan; Abdel-Lathif, Ahmat Younous; Pattnayak, Kanhu Charan
2018-03-01
Chad is the largest of Africa's landlocked countries and one of the least studied region of the African continent. The major portion of Chad lies in the Sahel region, which is known for its rapid climate change. In this study, multiple observational datasets are analyzed from 1950 to 2014, in order to examine the trend of precipitation and temperature along with their variability over Chad to understand possible impacts of climate change over this region. Trend analysis of the climatic fields has been carried out using Mann-Kendall test. The precipitation over Chad is mostly contributed during summer by West African Monsoon, with maximum northward limit of 18° N. The Atlantic Ocean as well as the Mediterranean Sea are the major source of moisture for the summer rainfall over Chad. Based on the rainfall time series, the entire study period has been divided in to wet (1950 to 1965), dry (1966 to 1990) and recovery period (1991 to 2014). The rainfall has decreased drastically for almost 3 decades during the dry period resulted into various drought years. The temperature increases at a rate of 0.15 °C/decade during the entire period of analysis. The seasonal rainfall as well as temperature plays a major role in the change of land use/cover. The decrease of monsoon rainfall during the dry period reduces the C4 cover drastically; this reduction of C4 grass cover leads to increase of C3 grass cover. The slow revival of rainfall is still not good enough for the increase of shrub cover but it favors the gradual reduction of bare land over Chad.
Sabr, Abutaleb; Moeinaddini, Mazaher; Azarnivand, Hossein; Guinot, Benjamin
2016-12-01
In the recent years, dust storms originating from local abandoned agricultural lands have increasingly impacted Tehran and Karaj air quality. Designing and implementing mitigation plans are necessary to study land use/land cover change (LUCC). Land use/cover classification is particularly relevant in arid areas. This study aimed to map land use/cover by pixel- and object-based image classification methods, analyse landscape fragmentation and determine the effects of two different classification methods on landscape metrics. The same sets of ground data were used for both classification methods. Because accuracy of classification plays a key role in better understanding LUCC, both methods were employed. Land use/cover maps of the southwest area of Tehran city for the years 1985, 2000 and 2014 were obtained from Landsat digital images and classified into three categories: built-up, agricultural and barren lands. The results of our LUCC analysis showed that the most important changes in built-up agricultural land categories were observed in zone B (Shahriar, Robat Karim and Eslamshahr) between 1985 and 2014. The landscape metrics obtained for all categories pictured high landscape fragmentation in the study area. Despite no significant difference was evidenced between the two classification methods, the object-based classification led to an overall higher accuracy than using the pixel-based classification. In particular, the accuracy of the built-up category showed a marked increase. In addition, both methods showed similar trends in fragmentation metrics. One of the reasons is that the object-based classification is able to identify buildings, impervious surface and roads in dense urban areas, which produced more accurate maps.
A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi
Smith, Kathryn E.L.; Nayegandhi, Amar; Brock, John C.
2010-01-01
INTRODUCTION Land-use and land-cover (LULC) data provide important information for environmental management. Data pertaining to land-cover and land-management activities are a common requirement for spatial analyses, such as watershed modeling, climate change, and hazard assessment. In coastal areas, land development, storms, and shoreline modification amplify the need for frequent and detailed land-cover datasets. The northern Gulf of Mexico coastal area is no exception. The impact of severe storms, increases in urban area, dramatic changes in land cover, and loss of coastal-wetland habitat all indicate a vital need for reliable and comparable land-cover data. Four main attributes define a land-cover dataset: the date/time of data collection, the spatial resolution, the type of classification, and the source data. The source data are the foundation dataset used to generate LULC classification and are typically remotely sensed data, such as aerial photography or satellite imagery. These source data have a large influence on the final LULC data product, so much so that one can classify LULC datasets into two general groups: LULC data derived from aerial photography and LULC data derived from satellite imagery. The final LULC data can be converted from one format to another (for instance, vector LULC data can be converted into raster data for analysis purposes, and vice versa), but each subsequent dataset maintains the imprint of the source medium within its spatial accuracy and data features. The source data will also influence the spatial and temporal resolution, as well as the type of classification. The intended application of the LULC data typically defines the type of source data and methodology, with satellite imagery being selected for large landscapes (state-wide, national data products) and repeatability (environmental monitoring and change analysis). The coarse spatial scale and lack of refined land-use categories are typical drawbacks to satellite-based land-use classifications. Aerial photography is typically selected for smaller landscapes (watershed-basin scale), for greater definition of the land-use categories, and for increased spatial resolution. Disadvantages of using photography include time-consuming digitization, high costs for imagery collection, and lack of seasonal data. Recently, the availability of high-resolution satellite imagery has generated a new category of LULC data product. These new datasets have similar strengths to the aerial-photo-based LULC in that they possess the potential for refined definition of land-use categories and increased spatial resolution but also have the benefit of satellite-based classifications, such as repeatability for change analysis. LULC classification based on high-resolution satellite imagery is still in the early stages of development but merits greater attention because environmental-monitoring and landscape-modeling programs rely heavily on LULC data. This publication summarizes land-use and land-cover mapping activities for Alabama and Mississippi coastal areas within the U.S. Geological Survey (USGS) Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project boundaries. Existing LULC datasets will be described, as well as imagery data sources and ancillary data that may provide ground-truth or satellite training data for a forthcoming land-cover classification. Finally, potential areas for a high-resolution land-cover classification in the Alabama-Mississippi region will be identified.
NASA Astrophysics Data System (ADS)
Cak, A. D.
2017-12-01
The Amazon Basin has faced innumerable pressures in recent years, including logging, mining and resource extraction, agricultural expansion, road building, and urbanization. These changes have drastically altered the landscape, transforming a predominantly forested environment into a mosaic of different types of land cover. The resulting fragmentation has caused dramatic and negative impacts on its structure and function, including on biodiversity and the transfer of water and energy to and from soil, vegetation, and the atmosphere (e.g., evapotranspiration). Because evapotranspiration from forested areas, which is affected by factors including temperature and water availability, plays a significant role in water dynamics in the Amazon Basin, measuring land surface temperature (LST) across the region can provide a dynamic assessment of hydrological, vegetation, and land use and land cover changes. It can also help to identify widespread urban development, which often has a higher LST signal relative to surrounding vegetation. Here, we discuss results from work to measure and identify drivers of change in LST across the entire Amazon Basin through analysis of past and current thermal and infrared satellite imagery. We leverage cloud computing resources in new ways to allow for more efficient analysis of imagery over the Amazon Basin across multiple years and multiple sensors. We also assess potential drivers of change in LST using spatial and multivariate statistical analyses with additional data sources of land cover, urban development, and demographics.
NASA Astrophysics Data System (ADS)
Khalid, Noora; Ullah, Saleem
2016-07-01
Forests play a critical role in balancing the ecological soundness of a region and in the facilitation of essential forest resources. Depletion of forest cover is a serious environmental problem throughout the world including Pakistan where a striking degradation of forest reserves has been an ecological concern for quite some time. Remote sensing techniques have been used to monitor land use and forest cover changes. The present study aims at exploring the potential impacts of climate change in the decline of forest reserves on Margalla Hills National Park (MHNP), since it remains the primary culprit behind this depletion. Landsat images for 1992, 2000 and 2011 were manipulated for the spatial and temporal analysis, interpretation and computation of the change and shift that has occurred over the past two decades. The analysis revealed a great increase in the built-up area, barren soil and agricultural land. Though other classes such as water body, lower vegetation, scrub and conifer forest showed a diminishing trend. The rise in temperature and relative humidity, the depletion in annual precipitation, frequent wild fires and the boost in urbanization and agricultural practices are the climatic conditions and causative agents chiefly responsible for the decline shown by the vegetation of the area. The degrading condition of the forest is below par and requires conservation practices to be carried out in order to avoid ecological disturbances.
NASA Astrophysics Data System (ADS)
Teutschbein, Claudia; Grabs, Thomas; Laudon, Hjalmar; Karlsen, Reinert H.; Bishop, Kevin
2018-06-01
In this paper we explored how landscape characteristics such as topography, geology, soils and land cover influence the way catchments respond to changing climate conditions. Based on an ensemble of 15 regional climate models bias-corrected with a distribution-mapping approach, present and future streamflow in 14 neighboring and rather similar catchments in Northern Sweden was simulated with the HBV model. We established functional relationships between a range of landscape characteristics and projected changes in streamflow signatures. These were then used to analyze hydrological consequences of physical perturbations in a hypothetically ungauged basin in a climate change context. Our analysis showed a strong connection between the forest cover extent and the sensitivity of different components of a catchment's hydrological regime to changing climate conditions. This emphasizes the need to redefine forestry goals and practices in advance of climate change-related risks and uncertainties.
Rogora, M; Frate, L; Carranza, M L; Freppaz, M; Stanisci, A; Bertani, I; Bottarin, R; Brambilla, A; Canullo, R; Carbognani, M; Cerrato, C; Chelli, S; Cremonese, E; Cutini, M; Di Musciano, M; Erschbamer, B; Godone, D; Iocchi, M; Isabellon, M; Magnani, A; Mazzola, L; Morra di Cella, U; Pauli, H; Petey, M; Petriccione, B; Porro, F; Psenner, R; Rossetti, G; Scotti, A; Sommaruga, R; Tappeiner, U; Theurillat, J-P; Tomaselli, M; Viglietti, D; Viterbi, R; Vittoz, P; Winkler, M; Matteucci, G
2018-05-15
Mountain ecosystems are sensitive and reliable indicators of climate change. Long-term studies may be extremely useful in assessing the responses of high-elevation ecosystems to climate change and other anthropogenic drivers from a broad ecological perspective. Mountain research sites within the LTER (Long-Term Ecological Research) network are representative of various types of ecosystems and span a wide bioclimatic and elevational range. Here, we present a synthesis and a review of the main results from ecological studies in mountain ecosystems at 20 LTER sites in Italy, Switzerland and Austria covering in most cases more than two decades of observations. We analyzed a set of key climate parameters, such as temperature and snow cover duration, in relation to vascular plant species composition, plant traits, abundance patterns, pedoclimate, nutrient dynamics in soils and water, phenology and composition of freshwater biota. The overall results highlight the rapid response of mountain ecosystems to climate change, with site-specific characteristics and rates. As temperatures increased, vegetation cover in alpine and subalpine summits increased as well. Years with limited snow cover duration caused an increase in soil temperature and microbial biomass during the growing season. Effects on freshwater ecosystems were also observed, in terms of increases in solutes, decreases in nitrates and changes in plankton phenology and benthos communities. This work highlights the importance of comparing and integrating long-term ecological data collected in different ecosystems for a more comprehensive overview of the ecological effects of climate change. Nevertheless, there is a need for (i) adopting co-located monitoring site networks to improve our ability to obtain sound results from cross-site analysis, (ii) carrying out further studies, in particular short-term analyses with fine spatial and temporal resolutions to improve our understanding of responses to extreme events, and (iii) increasing comparability and standardizing protocols across networks to distinguish local patterns from global patterns. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Potter, Christopher
2015-01-01
Landsat image analysis over the past 20+ years showed that consistent increases in the satellite normalized difference vegetation index (NDVI) during relatively dry years were confined to large wildfire areas that burned in the late 1980s and 1990s.
Gaur, Abhishek; Eichenbaum, Markus Kalev; Simonovic, Slobodan P
2018-01-15
Surface Urban Heat Island (SUHI) is an urban climate phenomenon that is expected to respond to future climate and land-use land-cover change. It is important to further our understanding of physical mechanisms that govern SUHI phenomenon to enhance our ability to model future SUHI characteristics under changing geophysical conditions. In this study, SUHI phenomenon is quantified and modelled at 20 cities distributed across Canada. By analyzing MODerate Resolution Imaging Spectroradiometer (MODIS) sensed surface temperature at the cities over 2002-2012, it is found that 16 out of 20 selected cities have experienced a positive SUHI phenomenon while 4 cities located in the prairies region and high elevation locations have experienced a negative SUHI phenomenon in the past. A statistically significant relationship between observed SUHI magnitude and city elevation is also recorded over the observational period. A Physical Scaling downscaling model is then validated and used to downscale future surface temperature projections from 3 GCMs and 2 extreme Representative Concentration Pathways in the urban and rural areas of the cities. Future changes in SUHI magnitudes between historical (2006-2015) and future timelines: 2030s (2026-2035), 2050s (2046-2055), and 2090s (2091-2100) are estimated. Analysis of future projected changes indicate that 15 (13) out of 20 cities can be expected to experience increases in SUHI magnitudes in future under RCP 2.6 (RCP 8.5). A statistically significant relationship between projected future SUHI change and current size of the cities is also obtained. The study highlights the role of city properties (i.e. its size, elevation, and surrounding land-cover) towards shaping their current and future SUHI characteristics. The results from this analysis will help decision-makers to manage Canadian cities more efficiently under rapidly changing geophysical and demographical conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.
Carbon changes in conterminous US forests associated with growth and major disturbances: 1992-2001
Daolan Zheng; Linda S. Heath; Mark J. Ducey; James E. Smith
2011-01-01
We estimated forest area and carbon changes in the conterminous United States using a remote sensing based land cover change map, forest fire data from the Monitoring Trends in Burn Severity program, and forest growth and harvest data from the USDA Forest Service, Forest Inventory and Analysis Program. Natural and human-associated disturbances reduced the forest...
Mercury from wildfires: Global emission inventories and sensitivity to 2000-2050 global change
NASA Astrophysics Data System (ADS)
Kumar, Aditya; Wu, Shiliang; Huang, Yaoxian; Liao, Hong; Kaplan, Jed O.
2018-01-01
We estimate the global Hg wildfire emissions for the 2000s and the potential impacts from the 2000-2050 changes in climate, land use and land cover and Hg anthropogenic emissions by combining statistical analysis with global data on vegetation type and coverage as well as fire activities. Global Hg wildfire emissions are estimated to be 612 Mg year-1. Africa is the dominant source region (43.8% of global emissions), followed by Eurasia (31%) and South America (16.6%). We find significant perturbations to wildfire emissions of Hg in the context of global change, driven by the projected changes in climate, land use and land cover and Hg anthropogenic emissions. 2000-2050 climate change could increase Hg emissions by 14% globally and regionally by 18% for South America, 14% for Africa and 13% for Eurasia. Projected changes in land use by 2050 could decrease the global Hg emissions from wildfires by 13% mainly driven by a decline in African emissions due to significant agricultural land expansion. Future land cover changes could lead to significant increases in Hg emissions over some regions (+32% North America, +14% Africa, +13% Eurasia). Potential enrichment of terrestrial ecosystems in 2050 in response to changes in Hg anthropogenic emissions could increase Hg wildfire emissions globally (+28%) and regionally (+19% North America, +20% South America, +24% Africa, +41% Eurasia). Our results indicate that the future evolution of climate, land use and land cover and Hg anthropogenic emissions are all important factors affecting Hg wildfire emissions in the coming decades.
NASA Technical Reports Server (NTRS)
Potter, Christopher S.
2013-01-01
Landsat satellite imagery was analyzed to generate a detailed record of 10 years of vegetation disturbance and regrowth for Pacific coastal areas of Marin and San Francisco Counties. The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) methodology, a transformation of Tasseled-Cap data space, was applied to detected changes in perennial coastal shrubland, woodland, and forest cover from 1999 to 2009. Results showed several principal points of interest, within which extensive contiguous areas of similar LEDAPS vegetation change (either disturbed or restored) were detected. Regrowth areas were delineated as burned forest areas in the Point Reyes National Seashore (PRNS) from the 1995 Vision Fire. LEDAPS-detected disturbance patterns on Inverness Ridge, PRNS in areas observed with dieback of tanoak and bay laurel trees was consistent with defoliation by sudden oak death (Phytophthora ramorum). LEDAPS regrowth pixels were detected over much of the predominantly grassland/herbaceous cover of the Olema Valley ranchland near PRNS. Extensive restoration of perennial vegetation cover on Crissy Field, Baker Beach and Lobos Creek dunes in San Francisco was identified. Based on these examples, the LEDAPS methodology will be capable of fulfilling much of the need for continual, low-cost monitoring of emerging changes to coastal ecosystems.
Impact of land cover and land use change on runoff characteristics.
Sajikumar, N; Remya, R S
2015-09-15
Change in Land Cover and Land Use (LCLU) influences the runoff characteristics of a drainage basin to a large extent, which in turn, affects the surface and groundwater availability of the area, and hence leads to further change in LCLU. This forms a vicious circle. Hence it becomes essential to assess the effect of change in LCLU on the runoff characteristics of a region in general and of small watershed levels (sub-basin levels) in particular. Such an analysis can effectively be carried out by using watershed simulation models with integrated GIS frame work. SWAT (Soil and Water Analysis Tool) model, being one of the versatile watershed simulation models, is found to be suitable for this purpose as many GIS integration modules are available for this model (e.g. ArcSWAT, MWSWAT). Watershed simulation using SWAT requires the land use and land cover data, soil data and many other features. With the availability of repository of satellite imageries, both from Indian and foreign sources, it becomes possible to use the concurrent local land use and land cover data, thereby enabling more accurate modelling of small watersheds. Such availability will also enable us to assess the effect of LCLU on runoff characteristics and their reverse impact. The current study assesses the effect of land use and land cover on the runoff characteristics of two watersheds in Kerala, India. It also assesses how the change in land use and land cover in the last few decades affected the runoff characteristics of these watersheds. It is seen that the reduction in the forest area amounts to 60% and 32% in the analysed watersheds. However, the changes in the surface runoff for these watersheds are not comparable with the changes in the forest area but are within 20%. Similarly the maximum (peak) value of runoff has increased by an amount of 15% only. The lesser (aforementioned) effect than expected might be due to the fact that forest has been converted to agricultural purpose with major portion as plantations which have comparatively similar characteristics of the forest except for evapo-transpiration. The double sided action (increase in evapo-transpiration owing to species like rubber and increase percolation due to its plantation method by using terracing) might be the reason for relatively smaller effect of the land use change, not commensurate with the changes in the forest area amounting to 60% and 32% for Manali and Kurumali watersheds respectively. Water harvesting methods like rain harvesting ditches can be made mandatory where species with high evapo-transpiration are grown. This action shall enhance the groundwater percolation and shall counter act the effect due to high evapo-transpiration. Copyright © 2014 Elsevier Ltd. All rights reserved.
Thresholds for boreal biome transitions.
Scheffer, Marten; Hirota, Marina; Holmgren, Milena; Van Nes, Egbert H; Chapin, F Stuart
2012-12-26
Although the boreal region is warming twice as fast as the global average, the way in which the vast boreal forests and tundras may respond is poorly understood. Using satellite data, we reveal marked alternative modes in the frequency distributions of boreal tree cover. At the northern end and at the dry continental southern extremes, treeless tundra and steppe, respectively, are the only possible states. However, over a broad intermediate temperature range, these treeless states coexist with boreal forest (∼75% tree cover) and with two more open woodland states (∼20% and ∼45% tree cover). Intermediate tree covers (e.g., ∼10%, ∼30%, and ∼60% tree cover) between these distinct states are relatively rare, suggesting that they may represent unstable states where the system dwells only transiently. Mechanisms for such instabilities remain to be unraveled, but our results have important implications for the anticipated response of these ecosystems to climatic change. The data reveal that boreal forest shows no gradual decline in tree cover toward its limits. Instead, our analysis suggests that it becomes less resilient in the sense that it may more easily shift into a sparse woodland or treeless state. Similarly, the relative scarcity of the intermediate ∼10% tree cover suggests that tundra may shift relatively abruptly to a more abundant tree cover. If our inferences are correct, climate change may invoke massive nonlinear shifts in boreal biomes.
David J. Lewis; Ralph J. Alig
2014-01-01
This paper develops a plot-level spatial econometric land-use model and estimates it with U.S. Geological Survey Land Cover Trends (LCT) geographic information system panel data for the western halves of the states of Oregon and Washington. The discrete-choice framework we use models plot-scale choices of the three dominant land uses in this region: forest, agriculture...
Mallinis, Giorgos; Koutsias, Nikos; Arianoutsou, Margarita
2014-08-15
The aims of this study were to map and analyze land use/land cover transitions and landscape changes in the Parnitha and Penteli mountains, which surround the Athens metropolitan area of Attica, Greece over a period of 62 years. In order to quantify the changes between land categories through time, we computed the transition matrices for three distinct periods (1945-1960, 1960-1996, and 1996-2007), on the basis of available aerial photographs used to create multi-temporal maps. We identified systematic and stationary transitions with multi-level intensity analysis. Forest areas in Parnitha remained the dominant class of land cover throughout the 62 years studied, while transitional woodlands and shrublands were the main classes involved in LULC transitions. Conversely, in Penteli, transitional woodlands, along with shrublands, dominated the study site. The annual rate of change was faster in the first and third time intervals, compared to the second (1960-1996) time interval, in both study areas. The category level analysis results indicated that in both sites annual crops avoided to gain while discontinuous urban fabric avoided to lose areas. At the transition level of analysis, similarities as well as distinct differences existed between the two areas. In both sites the gaining pattern of permanent crops with respect to annual crops and the gain of forest with respect to transitional woodland/shrublands were stationary across the three time intervals. Overall, we identified more systematic transitions and stationary processes in Penteli. We discussed these LULC changes and associated them with human interference (activity) and other major socio-economic developments that were simultaneously occurring in the area. The different patterns of change of the areas, despite their geographical proximity, throughout the period of analysis imply that site-specific studies are needed in order to comprehensively assess the driving forces and develop models of landscape transformation in Mediterranean areas. Copyright © 2014 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Chand, Pritam; Sharma, Milap Chand
2015-12-01
A glacier inventory of the Ravi basin, north-western Himalaya has been generated for the year 2002 using Landsat ETM + and ASTER Global DEM (GDEM V2) as the baseline data for the change analysis. The Ravi basin consists of 285 glaciers (> 0.02 km2) covering an area of 164.5 ± 7.5 km2, including 71 debris-covered glaciers with an area of 36.1 ± 2.1 km2 (22% of total glacierized area) in 2002. Change analysis based on Corona KH-4B (1971), Worldview (2010) and Landsat 8 OLI/TRIS (2013) images was restricted to a subset of 157 glaciers (covering an area of 121.4 ± 5.4 km2 in 2002) due to cloud cover. Glacier area decreased from 125.8 ± 1.9 km2 (1971) to 119.9 ± 4.8 km2 (2010/13), a loss of 4.7 ± 4.1% or 0.1 ± 0.1% a- 1. The glacier recession rate has decreased, to a minimum for the recent decades (2002-2010/13). The debris-covered glacier area increased by 19.2 ± 2.2% (0.5 ± 0.05% a- 1) in the Ravi basin. However, there were significant variation in its sub-basins i.e. in Budhil and Upper Ravi sub-basin, where the debris-covered area increased by 28.6 ± 3.1% (0.7 ± 0.1% a- 1) and 14 ± 1.6% (0.3 ± 0.04% a- 1), respectively, between 1971 and 2010/13. Field investigation of selected glaciers (2010-2014) supports glacier recession trend from remote sensing data. Glacier retreat rates in the Ravi basin were lower than previously reported for selected glaciers in the similar basin and other basins (e.g. Chenab, Beas, Parbati, Baspa and Tirungkhad) of the Himachal Himalaya.
NASA Astrophysics Data System (ADS)
Pilgrim, Cassie Mechele
Soil erosion and increased sediment yields within a watershed lead to impaired water quality, decreased availability of wildlife habitat and reduced recreational opportunities. While some sedimentation occurs naturally within a water system, most erosion processes are the result of anthropogenic activities across a landscape, namely changes in land use and land cover (LULC). This study was conducted to determine temporal and spatial sedimentation trends in the Lake Issaquena watershed using sonar logging equipment, geographic information systems (GIS) and limited hydrologic data from the Soil Conservation Service (1941 and 1949). Sediment deposition was analyzed in relation to several key factors that influence erosion and sediment yields; these being dominant land cover, topography and slopes, soils and geology, rainfall and climatological aspects. Significant sedimentation has occurred in the Sixmile Creek delta, located at the northern end of Lake Issaqueena. Sedimentation rates inferred from an analysis of afore mentioned factors show considerable changes in erosion potential that correspond with substantial changes in riparian vegetation, extreme variations in rainfall events, conversion of land from agricultural to forestland and application of management practices. Water quality data, including sampling depth, water temperature, dissolved oxygen content, Fecal coliform levels, inorganic nitrogen concentrations and turbidity, were obtained from the South Carolina Department of Environmental Health and Safety (SCDHEC) for two stations and analyzed for trends as they related to land cover change. Data was available for the Sixmile Creek site for dates ranging from 1962 to 2005 and from 1999 to 2005 for the Lake Issaqueena site. From 1951 to 2009, the watershed experienced an increase of tree cover and bare ground (+17.4% evergreen, +62.3% deciduous, +9.8% bare ground) and a decrease of pasture/ grassland and cultivated (-42.6% pasture/ grassland, -57.1% cultivated). From 2005 to 2009, there was an increase of 21.5% in residential/ other development. Sampling depth ranged from 0.1 meters to 0.3 meters. Water temperature fluctuated corresponding to changing air temperatures, and dissolved oxygen content fluctuated as a factor of water temperature. Inorganic nitrogen content was higher from December to April possibly due to application of fertilizers prior to the growing season. Fecal coliform levels stayed relatively the same, there was however, a slight decrease overall, likely due to the decrease in pasture/ grassland. Turbidity remained relatively the same from 1962 to 2005, but a slight decrease in pH can be observed at both stations. Sedimentation analysis has shown that overall the lake surface area has decreased by 11.333 hectares and lake volume has decreased by 320,800 m3, while catchment area increased by 6.99 hectares. Average annual precipitation rates were shown to have no direct correlation with these bathymetric measurements, and it is hypothesized that changes in land cover, slope and extreme precipitation events are largely responsible for sedimentation in Lake Issaqueena.
A long-term perspective on deforestation rates in the Brazilian Amazon
NASA Astrophysics Data System (ADS)
Velasco Gomez, M. D.; Beuchle, R.; Shimabukuro, Y.; Grecchi, R.; Simonetti, D.; Eva, H. D.; Achard, F.
2015-04-01
Monitoring tropical forest cover is central to biodiversity preservation, terrestrial carbon stocks, essential ecosystem and climate functions, and ultimately, sustainable economic development. The Amazon forest is the Earth's largest rainforest, and despite intensive studies on current deforestation rates, relatively little is known as to how these compare to historic (pre 1985) deforestation rates. We quantified land cover change between 1975 and 2014 in the so-called Arc of Deforestation of the Brazilian Amazon, covering the southern stretch of the Amazon forest and part of the Cerrado biome. We applied a consistent method that made use of data from Landsat sensors: Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI). We acquired suitable images from the US Geological Survey (USGS) for five epochs: 1975, 1990, 2000, 2010, and 2014. We then performed land cover analysis for each epoch using a systematic sample of 156 sites, each one covering 10 km x 10 km, located at the confluence point of integer degree latitudes and longitudes. An object-based classification of the images was performed with five land cover classes: tree cover, tree cover mosaic, other wooded land, other land cover, and water. The automatic classification results were corrected by visual interpretation, and, when available, by comparison with higher resolution imagery. Our results show a decrease of forest cover of 24.2% in the last 40 years in the Brazilian Arc of Deforestation, with an average yearly net forest cover change rate of -0.71% for the 39 years considered.
Devaney, John; Barrett, Brian; Barrett, Frank; Redmond, John; O Halloran, John
2015-01-01
Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1-98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting.
Devaney, John; Barrett, Brian; Barrett, Frank; Redmond, John; O`Halloran, John
2015-01-01
Quantification of spatial and temporal changes in forest cover is an essential component of forest monitoring programs. Due to its cloud free capability, Synthetic Aperture Radar (SAR) is an ideal source of information on forest dynamics in countries with near-constant cloud-cover. However, few studies have investigated the use of SAR for forest cover estimation in landscapes with highly sparse and fragmented forest cover. In this study, the potential use of L-band SAR for forest cover estimation in two regions (Longford and Sligo) in Ireland is investigated and compared to forest cover estimates derived from three national (Forestry2010, Prime2, National Forest Inventory), one pan-European (Forest Map 2006) and one global forest cover (Global Forest Change) product. Two machine-learning approaches (Random Forests and Extremely Randomised Trees) are evaluated. Both Random Forests and Extremely Randomised Trees classification accuracies were high (98.1–98.5%), with differences between the two classifiers being minimal (<0.5%). Increasing levels of post classification filtering led to a decrease in estimated forest area and an increase in overall accuracy of SAR-derived forest cover maps. All forest cover products were evaluated using an independent validation dataset. For the Longford region, the highest overall accuracy was recorded with the Forestry2010 dataset (97.42%) whereas in Sligo, highest overall accuracy was obtained for the Prime2 dataset (97.43%), although accuracies of SAR-derived forest maps were comparable. Our findings indicate that spaceborne radar could aid inventories in regions with low levels of forest cover in fragmented landscapes. The reduced accuracies observed for the global and pan-continental forest cover maps in comparison to national and SAR-derived forest maps indicate that caution should be exercised when applying these datasets for national reporting. PMID:26262681
NASA Technical Reports Server (NTRS)
Potter, Christopher
2015-01-01
Landsat (30 meter resolution) image analysis over the past 25 years in Kings Canyon National Park was used to track changes in the normalized difference vegetation index (NDVI). Results showed that NDVI values from the wet year of 2010 were significantly lower than NDVI values from the comparatively dry year of 2013 in the majority of meadow areas in the National Park.
Status and trends of land change in the Midwest–South Central United States—1973 to 2000
Auch, Roger F.; Karstensen, Krista A.; Auch, Roger F.; Karstensen, Krista A.
2015-12-10
U.S. Geological Survey (USGS) Professional Paper 1794–C is the third in a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the Midwest–South Central United States between 1973 and 2000. Volumes A, B, and D provide similar analyses for the Western United States, the Great Plains of the United States, and the Eastern United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation.Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Midwest–South Central United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Midwest–South Central United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of ecological goods and services and also the determination of risks to, and vulnerabilities of, human communities. Results from this project also are published in peer-reviewed journals, and they are further used to produce maps of change and other tools for land management, as well as to provide inputs for carbon-cycle modeling and other climate change research.
A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011
Jin, Suming; Yang, Limin; Zhu, Zhe; Homer, Collin G.
2017-01-01
Monitoring and mapping land cover changes are important ways to support evaluation of the status and transition of ecosystems. The Alaska National Land Cover Database (NLCD) 2001 was the first 30-m resolution baseline land cover product of the entire state derived from circa 2001 Landsat imagery and geospatial ancillary data. We developed a comprehensive approach named AKUP11 to update Alaska NLCD from 2001 to 2011 and provide a 10-year cyclical update of the state's land cover and land cover changes. Our method is designed to characterize the main land cover changes associated with different drivers, including the conversion of forests to shrub and grassland primarily as a result of wildland fire and forest harvest, the vegetation successional processes after disturbance, and changes of surface water extent and glacier ice/snow associated with weather and climate changes. For natural vegetated areas, a component named AKUP11-VEG was developed for updating the land cover that involves four major steps: 1) identify the disturbed and successional areas using Landsat images and ancillary datasets; 2) update the land cover status for these areas using a SKILL model (System of Knowledge-based Integrated-trajectory Land cover Labeling); 3) perform decision tree classification; and 4) develop a final land cover and land cover change product through the postprocessing modeling. For water and ice/snow areas, another component named AKUP11-WIS was developed for initial land cover change detection, removal of the terrain shadow effects, and exclusion of ephemeral snow changes using a 3-year MODIS snow extent dataset from 2010 to 2012. The overall approach was tested in three pilot study areas in Alaska, with each area consisting of four Landsat image footprints. The results from the pilot study show that the overall accuracy in detecting change and no-change is 90% and the overall accuracy of the updated land cover label for 2011 is 86%. The method provided a robust, consistent, and efficient means for capturing major disturbance events and updating land cover for Alaska. The method has subsequently been applied to generate the land cover and land cover change products for the entire state of Alaska.
Landscape trends in Mid-Atlantic and Southeastern United States ecoregions
Griffith, J.A.; Stehman, S.V.; Loveland, Thomas R.
2003-01-01
Landscape pattern and composition metrics are potential indicators for broad-scale monitoring of change and for relating change to human and ecological processes. We used a probability sample of 20-km × 20-km sampling blocks to characterize landscape composition and pattern in five US ecoregions: the Middle Atlantic Coastal Plain, Southeastern Plains, Northern Piedmont, Piedmont, and Blue Ridge Mountains. Land use/land cover (LULC) data for five dates between 1972 and 2000 were obtained for each sample block. Analyses focused on quantifying trends in selected landscape pattern metrics by ecoregion and comparing trends in land cover proportions and pattern metrics among ecoregions. Repeated measures analysis of the landscape pattern documented a statistically significant trend in all five ecoregions towards a more fine-grained landscape from the early 1970s through 2000. The ecologically important forest cover class also became more fine-grained with time (i.e., more numerous and smaller forest patches). Trends in LULC, forest edge, and forest percent like adjacencies differed among ecoregions. These results suggest that ecoregions provide a geographically coherent way to regionalize the story of national land use and land cover change in the United States. This study provides new information on LULC change in the southeast United States. Previous studies of the region from the 1930s to the 1980s showed a decrease in landscape fragmentation and an increase in percent forest, while this study showed an increase in forest fragmentation and a loss of forest cover.
NASA Astrophysics Data System (ADS)
Barlow, J. E.; Burns, I. S.; Guertin, D. P.; Kepner, W. G.; Goodrich, D. C.
2016-12-01
Long-term land-use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology to characterize hydrologic impacts from future urban growth through time that was developed and applied on the San Pedro River Basin was expanded and utilized on the South Platte River Basin as well. Future urban growth is represented by housing density maps generated in decadal intervals from 2010 to 2100, produced by the U.S. Environmental Protection Agency (EPA) Integrated Climate and Land-Use Scenarios (ICLUS) project. ICLUS developed future housing density maps by adapting the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines to the conterminous United States. To characterize hydrologic impacts from future growth, the housing density maps were reclassified to National Land Cover Database (NLCD) 2006 land cover classes and used to parameterize the Soil and Water Assessment Tool (SWAT) using the Automated Geospatial Watershed Assessment (AGWA) tool. The objectives of this project were to 1) develop and implement a methodology for adapting the ICLUS data for use in AGWA as an approach to evaluate impacts of development on water-quantity and -quality, 2) present, evaluate, and compare results from scenarios for watersheds in two different geographic and climatic regions, 3) determine watershed specific implications of this type of future land cover change analysis.
Application of Remote Sensing for Forest Management in Nepal
NASA Astrophysics Data System (ADS)
Bajracharya, B.; Matin, M. A.
2016-12-01
Large area of the Hindu Kush Himalayan (HKH) region is covered by forest that is playing a vital role to address the challenges of climate change and livelihood options for a growing population. Effective management of forest cover needs establishment of regular monitoring system for forest. Supporting REDD assessment needs reliable baseline assessment of forest biomass and its monitoring at multiple scale. Adaptation of forest to climate change needs understanding vulnerability of forests and dependence of local communities on these forest. We present here different forest monitoring products developed under the SERVIR-Himalaya programme to address these issues. Landsat 30 meter images were used for decadal land cover change assessment and annual forest change hotspot monitoring. Methodology developed for biomass estimation at national and sub-national level biomass estimation. Decision support system was developed for analysis of forest vulnerability and dependence and selection of adaptation options based on resource availability. These products are forming the basis for development of an integrated system that will be very useful for comprehensive forest monitoring and long term strategy development for sustainable forest management.
HYDROLOGIC MODEL CALIBRATION AND UNCERTAINTY IN SCENARIO ANALYSIS
A systematic analysis of model performance during simulations based on
observed land-cover/use change is used to quantify error associated with water-yield
simulations for a series of known landscape conditions over a 24-year period with the
goal of evaluatin...
Current and historic impacts of nitrogen on water quality were evaluated and relationships between nutrients and ecosystem structure and function were developed for Narragansett Bay, RI. Land use land cover change analysis from 1985 thru 2005 resulted in a 7% increase in urban la...
Vegetation Cover Change in Yellowstone National Park Detected Using Landsat Satellite Image Analysis
NASA Technical Reports Server (NTRS)
Potter, Christopher S.
2015-01-01
Results from Landsat satellite image analysis since 1987 in all unburned areas (since the 1880s) of Yellowstone National Park (YNP) showed that consistent decreases in the normalized difference vegetation index (NDVI) have been strongly dependent on periodic variations in peak annual snow water equivalents (SWE).
SPECIAL ANALYSIS OF OPERATIONAL STORMWATER RUNOFF COVERS OVER SLIT TRENCHES
DOE Office of Scientific and Technical Information (OSTI.GOV)
Collard, L; Luther Hamm, L
2008-12-18
Solid Waste Management (SWM) commissioned this Special Analysis (SA) to determine the effects of placing operational stormwater runoff covers (referred to as covers in the remainder of this document) over slit trench (ST) disposal units ST1 through ST7 (the center set of slit trenches). Previously the United States Department of Energy (DOE) entered into an agreement with the United States Environmental Protection Agency (EPA) and the South Carolina Department of Health and Environmental Control (SCDHEC) to place covers over Slit Trenches 1 and 2 to be able to continue disposing Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) solid wastemore » (see USDOE 2008). Because the covers changed the operating conditions, DOE Order 435.1 (DOE 1999) required that an SA be performed to assess the impact. This Special Analysis has been prepared to determine the effects of placing covers over slit trenches at about years 5, 10 and 15 of the 30-year operational period. Because some slit trenches have already been operational for about 15 years, results from analyzing covers at 5 years and 10 years provide trend analysis information only. This SA also examined alternatives of covering Slit Trenches 1 and 2 with one cover and Slit Trenches 3 and 4 with a second cover versus covering them all with a single cover. Based on modeling results, minimal differences exist between covering Slit Trench groups 1-2 and 3-4 with two covers or one large cover. This SA demonstrates that placement of covers over slit trenches will slow the subsequent release and transport of radionuclides in the vadose zone in the early time periods (from time of placement until about 100 years). Release and transport of some radionuclides in the vadose zone beyond 100 years were somewhat higher than for the case without covers. The sums-of-fractions (SOFs) were examined for the current waste inventory in ST1 and ST2 and for estimated inventories at closure for ST3 through ST7. In all cases SOFs were less than one (except for one SOF for ST5 that remained at one), indicating that there should be no unacceptable impacts on operations from placing covers for the cover alternatives that were analyzed. Minimal operational limits provided in Table 4 should be used as the new set of limits for Slit Trenches 1 through 7. ST1 and ST2 are expected to be covered about 15 years after the first disposal in ST1. Because the time of actual placement of covers over the other slit trenches is unknown, this SA did not consider limit increases, only limit decreases. Thus, each minimal operational limit is the minimum of the Performance Assessment (PA) final limit and the limit calculated in this SA if covers were placed at about 5, 10 or 15 years. If other cover times are desired, further analysis will be required.« less
NASA Astrophysics Data System (ADS)
Surdu, C.; Duguay, C.; Brown, L.; Fernàndez-Prieto, D.; Samuelsson, P.
2012-12-01
Lake ice cover is highly correlated with climatic conditions and has, therefore, been demonstrated to be an essential indicator of climate variability and change. Recent studies have shown that the duration of the lake ice cover has decreased, mainly as a consequence of earlier thaw dates in many parts of the Northern Hemisphere over the last 50 years, mainly as a feedback to increased winter and spring air temperature. In response to projected air temperature and winter precipitation changes by climate models until the end of the 21st century, the timing, duration, and thickness of ice cover on Arctic lakes are expected to be impacted. This, in turn, will likely alter the energy, water, and bio-geochemical cycling in various regions of the Arctic. In the case of shallow tundra lakes, many of which are less than 3-m deep, warmer climate conditions could result in a smaller fraction of lakes that fully freeze to the bottom at the time of maximum winter ice thickness since thinner ice covers are predicted to develop. Shallow thermokarst lakes of the coastal plain of northern Alaska, and of other similar Arctic regions, have likely been experiencing changes in seasonal ice phenology and thickness over the last few decades but these have not yet been comprehensively documented. Analysis of a 20-year time series of ERS-1/2 synthetic aperture radar (SAR) data and numerical lake ice modeling were employed to determine the response of ice cover (thickness, freezing to bed, and phenology) on shallow lakes of the North Slope of Alaska (NSA) to climate conditions over the last three decades. New downscaled data specific to the Arctic domain (at a resolution of 0.44 degrees using ERA Interim Reanalysis as boundary condition) produced by the Rossby Centre Regional Atmospheric Climate Model (RCA4) was used to drive the Canadian Lake Ice Model (CLIMo) for the period 1950-2011. In order to assess and integrate the SAR-derived observed changes into a longer historical context, and to improve the simulation outputs, CLIMo was also forced with climatic data recorded at the Barrow airport meteorological station since the middle of the 20th century. ERS-1/2 data was used to map areas of the shallow lakes that freeze to bed and the rate at which this occurs during the ice season for the period 1991-2011. The results were compared to daily ice thickness results derived from CLIMo. Analysis from a sub-region of the NSA near Barrow shows that the interannual variability in ice thickness simulated with CLIMo compares favorably with the fraction of lakes that freeze to their bed in winter, thicker ice cover corresponding to a higher ratio of lakes fully frozen to the bottom, as determined from the analysis of SAR data.
NASA Astrophysics Data System (ADS)
Genet, H.; Lara, M. J.; Bolton, W. R.; McGuire, A. D.
2016-12-01
Estimation of the magnitude and consequences of permafrost degradation in high latitude is one of the most urgent research challenges related to contemporary and future climate change. In addition to widespread vertical degradation, ice-rich permafrost can thaw laterally, often triggering abrupt subsidence of the ground surface called thermokart. In this depression, permafrost plateau vegetation will transition to wetlands or lakes, while surface water of the surrounding landscape may drain towards it. These abrupt changes in land cover and hydrology can have dramatic consequences from wildlife habitat and biogeochemical cycles. Although recent studies have documented an acceleration of the rates of thermokarst formation in boreal and arctic peatlands, the importance of thermokarst at the regional level is still poorly understood. To better understand the vulnerability of the landscape to thermokarst disturbance in Alaska, we developed the Alaska Thermokarst Model (ATM), a state-and-transition model designed to simulate land cover change associated with thermokarst disturbance. In boreal regions, the model simulates transitions from permafrost plateau forest to thermokarst lake, bog or fen, as a function of climate and fire dynamics, permafrost characteristics and physiographic information. This model is designed and parameterized based on existing literature and a new repeated imagery analysis we conducted in a major wetland complex in boreal Alaska. We will present simulation and validation of thermokarst dynamic and associated land cover change in two wetland complexes in boreal Alaska, from 2000 to 2100 for six climate scenarios associating three AR5 emission scenarios and two global circulation model simulations. By 2100, ATM is predicting decrease between 3.5 and 9.1 % in the extent of permafrost plateau forest, mostly to the benefit of thermokarst fen, and lake. This analysis allowed us to assess the importance of thermokarst dynamics and landscape evolution associated with permafrost thaw in vulnerable regions of boreal Alaska during the 21st century and could be used as a baseline for managers to incorporate projected land cover changes in designing land management strategies.
EVALUATING MACROINVERTEBRATE COMMUNITY ...
Since 2010, new construction in California is required to include stormwater detention and infiltration that is designed to capture rainfall from the 85th percentile of storm events in the region, preferably through green infrastructure. This study used recent macroinvertebrate community monitoring data to determine the ecological threshold for percent impervious cover prior to large scale adoption of green infrastructure using Threshold Indicator Taxa Analysis (TITAN). TITAN uses an environmental gradient and biological community data to determine individual taxa change points with respect to changes in taxa abundance and frequency across that gradient. Individual taxa change points are then aggregated to calculate the ecological threshold. This study used impervious cover data from National Land Cover Datasets and macroinvertebrate community data from California Environmental Data Exchange Network and Southern California Coastal Water Research Project. Preliminary TITAN runs for California’s Chaparral region indicated that both increasing and decreasing taxa had ecological thresholds of <1% watershed impervious cover. Next, TITAN will be used to determine shifts in the ecological threshold after the implementation of green infrastructure on a large scale. This presentation for the Society for Freshwater Scientists will discuss initial evaluation of community and taxa-specific thresholds of impairment for macroinvertebrates in California streams along
Life cycle cost based program decisions
NASA Technical Reports Server (NTRS)
Dick, James S.
1991-01-01
The following subject areas are covered: background (space propulsion facility assessment team final report); changes (Advanced Launch System, National Aerospace Plane, and space exploration initiative); life cycle cost analysis rationale; and recommendation to panel.
Anticipating Climate Change Impacts on Army Installations
2011-10-01
13 3.2 Recent technologically derived ecological characterizations ....................................... 14 3.2.1 USGS Gap Analysis Program... GAP ) ......................................................................................... 14 3.2.2 Hargrove/Hoffman potential multivariate... GAP national land cover map .................................................................................................. 14 5 A Hargrove
Demonstrating Change with Astronaut Photography Using Object Based Image Analysis
NASA Technical Reports Server (NTRS)
Hollier, Andi; Jagge, Amy
2017-01-01
Every day, hundreds of images of Earth flood the Crew Earth Observations database as astronauts use hand held digital cameras to capture spectacular frames from the International Space Station. The variety of resolutions and perspectives provide a template for assessing land cover change over decades. We will focus on urban growth in the second fastest growing city in the nation, Houston, TX, using Object-Based Image Analysis. This research will contribute to the land change science community, integrated resource planning, and monitoring of the rapid rate of urban sprawl.
NASA Technical Reports Server (NTRS)
Peterson, Thomas C.; Barnett, Tim P.; Roeckner, Erich; Vonder Haar, Thomas H.
1992-01-01
The relationship between the sea surface temperature anomalies (SSTAs) and the anomalies of the monthly mean cloud cover (including the high-level, low-level, and total cloud cover), the outgoing longwave radiation, and the reflected solar radiation was analyzed using a least absolute deviations regression at each grid point over the open ocean for a 6-yr period. The results indicate that cloud change in association with a local 1-C increase in SSTAs cannot be used to predict clouds in a potential future world where all the oceans are 1-C warmer than at present, because much of the observed cloud changes are due to circulation changes, which in turn are related not only to changes in SSTAs but to changes in SSTA gradients. However, because SSTAs are associated with changes in the local ocean-atmosphere moisture and heat fluxes as well as significant changes in circulation (such as ENSO), SSTAs can serve as a surrogate for many aspects of global climate change.
Ankersen, Jeppe; Grogan, Kenneth; Mertz, Ole; Fensholt, Rasmus; Castella, Jean-Christophe; Lestrelin, Guillaume; Nguyen, Dinh Tien; Danielsen, Finn; Brofeldt, Søren; Rasmussen, Kjeld
2015-05-01
One of the prerequisites of the REDD+ mechanism is to effectively predict business-as-usual (BAU) scenarios for change in forest cover. This would enable estimation of how much carbon emission a project could potentially prevent and thus how much carbon credit should be rewarded. However, different factors like forest degradation and the lack of linearity in forest cover transitions challenge the accuracy of such scenarios. Here we predict and validate such BAU scenarios retrospectively based on forest cover changes at village and district level in North Central Vietnam. With the government's efforts to increase the forest cover, land use policies led to gradual abandonment of shifting cultivation since the 1990s. We analyzed Landsat images from 1973, 1989, 1998, 2000, and 2011 and found that the policies in the areas studied did lead to increased forest cover after a long period of decline, but that this increase could mainly be attributed to an increase in open forest and shrub areas. We compared Landsat classifications with participatory maps of land cover/use in 1998 and 2012 that indicated more forest degradation than was captured by the Landsat analysis. The BAU scenarios were heavily dependent on which years were chosen for the reference period. This suggests that hypothetical REDD+ activities in the past, when based on the remote sensing data available at that time, would have been unable to correctly estimate changes in carbon stocks and thus produce relevant BAU scenarios.
NASA Astrophysics Data System (ADS)
Ankersen, Jeppe; Grogan, Kenneth; Mertz, Ole; Fensholt, Rasmus; Castella, Jean-Christophe; Lestrelin, Guillaume; Nguyen, Dinh Tien; Danielsen, Finn; Brofeldt, Søren; Rasmussen, Kjeld
2015-05-01
One of the prerequisites of the REDD+ mechanism is to effectively predict business-as-usual (BAU) scenarios for change in forest cover. This would enable estimation of how much carbon emission a project could potentially prevent and thus how much carbon credit should be rewarded. However, different factors like forest degradation and the lack of linearity in forest cover transitions challenge the accuracy of such scenarios. Here we predict and validate such BAU scenarios retrospectively based on forest cover changes at village and district level in North Central Vietnam. With the government's efforts to increase the forest cover, land use policies led to gradual abandonment of shifting cultivation since the 1990s. We analyzed Landsat images from 1973, 1989, 1998, 2000, and 2011 and found that the policies in the areas studied did lead to increased forest cover after a long period of decline, but that this increase could mainly be attributed to an increase in open forest and shrub areas. We compared Landsat classifications with participatory maps of land cover/use in 1998 and 2012 that indicated more forest degradation than was captured by the Landsat analysis. The BAU scenarios were heavily dependent on which years were chosen for the reference period. This suggests that hypothetical REDD+ activities in the past, when based on the remote sensing data available at that time, would have been unable to correctly estimate changes in carbon stocks and thus produce relevant BAU scenarios.
Dominance of grain size impacts on seasonal snow albedo at open sites in New Hampshire
NASA Astrophysics Data System (ADS)
Adolph, Alden C.; Albert, Mary R.; Lazarcik, James; Dibb, Jack E.; Amante, Jacqueline M.; Price, Andrea
2017-01-01
Snow cover serves as a major control on the surface energy budget in temperate regions due to its high reflectivity compared to underlying surfaces. Winter in the northeastern United States has changed over the last several decades, resulting in shallower snowpacks, fewer days of snow cover, and increasing precipitation falling as rain in the winter. As these climatic changes occur, it is imperative that we understand current controls on the evolution of seasonal snow albedo in the region. Over three winter seasons between 2013 and 2015, snow characterization measurements were made at three open sites across New Hampshire. These near-daily measurements include spectral albedo, snow optical grain size determined through contact spectroscopy, snow depth, snow density, black carbon content, local meteorological parameters, and analysis of storm trajectories using the Hybrid Single-Particle Lagrangian Integrated Trajectory model. Using analysis of variance, we determine that land-based winter storms result in marginally higher albedo than coastal storms or storms from the Atlantic Ocean. Through multiple regression analysis, we determine that snow grain size is significantly more important in albedo reduction than black carbon content or snow density. And finally, we present a parameterization of albedo based on days since snowfall and temperature that accounts for 52% of variance in albedo over all three sites and years. Our improved understanding of current controls on snow albedo in the region will allow for better assessment of potential response of seasonal snow albedo and snow cover to changing climate.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Qin, Zhangcai; Canter, Christina E.; Dunn, Jennifer B.
Land management practices such as cover crop adoption or manure application that can increase soil organic carbon (SOC) may provide a way to counter SOC loss upon removal of stover from corn fields for use as a biofuel feedstock. This report documents the data, methodology, and assumptions behind the incorporation of land management practices into corn-soybean systems that dominate U.S. grain production using varying levels of stover removal in the GREETTM (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) model and its CCLUB (Carbon Calculator for Land Use change from Biofuels production) module. Tillage (i.e., conventional, reduced and nomore » tillage), corn stover removal (i.e., at 0, 30% and 60% removal rate), and organic matter input techniques (i.e., cover crop and manure application) are included in the analysis as major land management practices. Soil carbon changes associated with land management changes were modeled with a surrogate CENTURY model. The resulting SOC changes were incorporated into CCLUB while GREET was expanded to include energy and material consumption associated with cover crop adoption and manure application. Life-cycle greenhouse gas (GHG) emissions of stover ethanol were estimated using a marginal approach (all burdens and benefits assigned to corn stover ethanol) and an energy allocation approach (burdens and benefits divided between grain and stover ethanol). In the latter case, we considered corn grain and corn stover ethanol to be produced at an integrated facility. Life-cycle GHG emissions of corn stover ethanol are dependent upon the analysis approach selected (marginal versus allocation) and the land management techniques applied. The expansion of CCLUB and GREET to accommodate land management techniques can produce a wide range of results because users can select from multiple scenario options such as choosing tillage levels, stover removal rates, and whether crop yields increase annually or remain constant. In a scenario with conventional tillage and a 30% stover removal rate, life-cycle GHG emissions for a combined gallon of corn grain and stover ethanol without cover crop adoption or manure application are 49 g CO2eq MJ-1, in comparison with 91 g CO2eq MJ-1 for petroleum gasoline. Adopting a cover crop or applying manure reduces the former ethanol life-cycle GHG emissions by 8% and 10%, respectively. We considered two different life cycle analysis approaches to develop estimates of life-cycle GHG emissions for corn stover ethanol, marginal analysis and energy allocation. In the same scenario, this fuel has GHG emissions of 12 – 20 g CO2eq MJ-1 (for manure and cover crop application, respectively) and 45 – 48 g CO2eq MJ-1 with the marginal approach and the energy allocation approach, respectively.« less
NASA Technical Reports Server (NTRS)
Hall, Dorothy K.; Foster, James L.; DiGirolamo, Nicolo E.; Riggs, George A.
2010-01-01
MODIS-derived snow cover measured on 30 April in any given year explains approximately 89 % of the variance in stream discharge for maximum monthly streamflow in that year. Observed changes in streamflow appear to be related to increasing maximum air temperatures over the last four decades causing lower spring snow-cover extent. The majority (>70%) of the water supply in the western United States comes from snowmelt, thus analysis of the declining spring snowpack (and resulting declining stream discharge) has important implications for streamflow management in the drought-prone western U.S.
Land-cover change and avian diversity in the conterminous United States
Chadwick D. Rittenhouse; Anna M. Pidgeon; Thomas P. Albright; Patrick D. Culbert; Murray K. Clayton; Curtis H. Flather; Jeffrey G. Masek; Volker C. Radeloff
2012-01-01
Changes in land use and land cover have affected and will continue to affect biological diversity worldwide. Yet, understanding the spatially extensive effects of land-cover change has been challenging because data that are consistent over space and time are lacking. We used the U.S. National Land Cover Dataset Land Cover Change Retrofit Product and North American...
Characterization of Vegetation Change in a Sub-Arctic Mire using Remotely Sensed Imagery
NASA Astrophysics Data System (ADS)
DelGreco, J. L.; McArthur, K. J.; Palace, M. W.; Herrick, C.; Garnello, A.; Finnell, D.; McCalley, C. K.; Anderson, S. M.; Varner, R. K.
2015-12-01
Climate change is impacting northern ecosystems through the thawing of the permafrost, which has resulted in changes to plant communities and greenhouse gas emissions, such as carbon dioxide (CO2) and methane (CH4). These greenhouse gases are of concern due to their potential feedbacks which create a warmer climate, thus increasing permafrost thawing. Our study focuses on how vegetation type differs in areas that have been impacted by thawing permafrost at Stordalen Mire located in Abisko, Sweden. To estimate change in vegetation communities, field-based measurements combined with remotely sensed image data was used. 75 randomized square-meter plots were measured for vegetation composition and classified into one of five site-types, each representing a different stage of permafrost degradation. New high-resolution imagery (1 cm) was collected using Unmanned Aerial Vehicles (UAV) providing insight into the spatial patterning, characterizations, and changes of these communities. The UAV imagery was georectified using high precision GPS points collected across the mire. The imagery was then examined using a neural network analysis to estimate cover type across the mire. This 2015 cover type classification was then compared to previous UAV imagery taken on July 2014 to analyze changes in vegetation distribution as an indication of permafrost thaw. Hummock sites represent intact permafrost and have lost 21.5% coverage since 2014, while tall gramminoid sites, which indicate fully thawed sites, have increased coverage by 12.1%. A discriminate function analysis showed that site types can be differentiated based on species composition, thus showing that vegetation differs significantly across the thaw gradient. Using average flux rates of CH4 from each cover type reported previously, the percent of CH4 emitted over the mire was estimated for 2014 and 2015. Comparing both estimates, CH4 emissions increased with a flux change of 5604.5 g CH4/day. Our estimates of vegetation change may be used to parameterize simulation models and create future scenarios of how the vegetation cover will change in response to climate change. Data from this study will also help to explain how the ecology of the subarctic peatlands, now a carbon sink, may be on its way to changing into a source of carbon.
Model of land cover change prediction in West Java using cellular automata-Markov chain (CA-MC)
NASA Astrophysics Data System (ADS)
Virtriana, Riantini; Sumarto, Irawan; Deliar, Albertus; Pasaribu, Udjianna S.; Taufik, Moh.
2015-04-01
Land is a fundamental factor that closely related to economic growth and supports the needs of human life. Land-use activity is a major issue and challenge for country planners. The cause of change in land use type activity may be due to socio economic development or due to changes in the environment or may be due to both. In an effort to understand the phenomenon of land cover changes, can be approached through land cover change modelling. Based on the facts and data contained, West Java has a high economic activity that will have an impact on land cover change. CA-MC is a model that used to determine the statistical change probabilistic for each of land cover type from land cover data at different time periods. CA-MC is able to provide the output of land cover type that should occurred. Results from a CA-MC modelling in predicting land cover changes showed an accuracy rate of 95.42%.
Analysis of land cover/use changes using Landsat 5 TM data and indices.
Ettehadi Osgouei, Paria; Kaya, Sinasi
2017-04-01
Urban expansion and unprecedented rural to urban transition, along with a huge population growth, are major driving forces altering land cover/use in metropolitan areas. Many of the land cover classes such as farmlands, wetlands, forests, and bare soils have been transformed during the past years into human settlements. Identification of the city growth trends and the impact of it on the vegetation cover of an area is essential for a better understanding of the sustainability of urban development processes, both planned and unplanned. Analyzing the causes and consequences of land use dynamics helps local government, urban planners, and managers for the betterment of future plans and minimizing the negative effects.This study determined temporal changes in vegetation cover and built-up area in Istanbul (Turkey) using the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and built-up area index (BUAI). The temporal data were based on Landsat 5 Thematic Mapper (TM) images acquired in June of 1984, 2002, 2007, 2009, and 2011. The NDVI was applied to all the Landsat images, and the resulting NDVI images were overlaid to generate an NDVI layer stack image. The same procedure was repeated using the SAVI and BUAI images. The layer stack images revealed those areas that had changed in terms of the different indices over the years. To determine temporal change trends, the values of 150 randomly selected control points were extracted from the same locations in the NDVI, SAVI, and BUAI layer stack images. The results obtained from these control points showed that vegetation cover decreased considerably because of a remarkable increase in the built-up area.
Cropland management dynamics as a driver of forest cover change in European Russia (Invited)
NASA Astrophysics Data System (ADS)
Tyukavina, A.; Krylov, A.; Potapov, P.; Turubanova, S.; Hansen, M.; McCarty, J. L.
2013-12-01
The European part of Russia spans over 40% of the European subcontinent and comprises most of Europe's temperate and boreal forests. The region has undergone a socio-economic transition during the last two decades that has resulted in radical changes in land management. Large-scale agriculture land abandonment caused massive afforestation in the Central and Northern parts of the region (Alcantara et al. 2012). Afforestation of former croplands is currently not included in the official forestry statistical reports (Potapov et al. 2012), but is likely to have major impacts on regional carbon budgets (Kuemmerle et al. 2009). We employed a complete archive of Landsat TM and ETM+ imagery and automatic data processing algorithm to create regional time-sequential image composites and multi-temporal metrics for 1985-2012. Spectral metrics were used as independent variables to map forest cover and change with help of supervised machine learning algorithms and trend analysis. Forest cover loss was attributed to fires, harvesting, and wind/disease dynamics, while forest cover gain was disaggregated into reforestation and afforestation using pre-1990 TM imagery as baseline data. Special attention was paid to agricultural abandonment. Fire events of the last decade have been further characterized by ignition place, time, and burning intensity using MODIS fire detection data. Change detection products have been validated using field data collected during summer 2012 and 2013 and high resolution imagery. Massive arable land abandonment caused forest area increase within Central agricultural regions. While total logging area decreased after the USSR breakdown, logging and other forms of clearing increased within the Central and Western parts of the region. Gross forest gain and loss were nearly balanced within region; however, the most populated regions of European Russia featured the highest rate of net forest cover loss during the last decade. The annual burned forest area as well as area of windstorms damage significantly increased, especially in the Central regions. Fires predominantly affected pine forests and drained peatlands prone to summer droughts. Fire date and ignition analysis showed that forest fires are not related to extensive spring-time agricultural burning. References: Alcantara, C., T. Kuemmerle, A. V. Prishchepov & V. C. Radeloff. 2012. Mapping abandoned agriculture with multi-temporal MODIS satellite data. 334-347. Remote Sensing of Environment. Kuemmerle, T., O. Chaskovskyy, J. Knorn, V. C. Radeloff, I. Kruhlov, W. S. Keeton & P. Hostert. 2009. Forest cover change and illegal logging in the Ukrainian Carpathians in the transition period from 1988 to 2007. Remote Sensing of Environment, 113, 1194-1207. Potapov, P., S. Turubanova, I. Zhuravleva, M. Hansen, A. Yaroshenko & A. Manisha. 2012. Forest Cover Change within the Russian European North after the Breakdown of Soviet Union (1990-2005) 1-11. International Journal of Forestry Research.
Improved Snow Mapping Accuracy with Revised MODIS Snow Algorithm
NASA Technical Reports Server (NTRS)
Riggs, George; Hall, Dorothy K.
2012-01-01
The MODIS snow cover products have been used in over 225 published studies. From those reports, and our ongoing analysis, we have learned about the accuracy and errors in the snow products. Revisions have been made in the algorithms to improve the accuracy of snow cover detection in Collection 6 (C6), the next processing/reprocessing of the MODIS data archive planned to start in September 2012. Our objective in the C6 revision of the MODIS snow-cover algorithms and products is to maximize the capability to detect snow cover while minimizing snow detection errors of commission and omission. While the basic snow detection algorithm will not change, new screens will be applied to alleviate snow detection commission and omission errors, and only the fractional snow cover (FSC) will be output (the binary snow cover area (SCA) map will no longer be included).
Integrated modelling of anthropogenic land-use and land-cover change on the global scale
NASA Astrophysics Data System (ADS)
Schaldach, R.; Koch, J.; Alcamo, J.
2009-04-01
In many cases land-use activities go hand in hand with substantial modifications of the physical and biological cover of the Earth's surface, resulting in direct effects on energy and matter fluxes between terrestrial ecosystems and the atmosphere. For instance, the conversion of forest to cropland is changing climate relevant surface parameters (e.g. albedo) as well as evapotranspiration processes and carbon flows. In turn, human land-use decisions are also influenced by environmental processes. Changing temperature and precipitation patterns for example are important determinants for location and intensity of agriculture. Due to these close linkages, processes of land-use and related land-cover change should be considered as important components in the construction of Earth System models. A major challenge in modelling land-use change on the global scale is the integration of socio-economic aspects and human decision making with environmental processes. One of the few global approaches that integrates functional components to represent both anthropogenic and environmental aspects of land-use change, is the LandSHIFT model. It simulates the spatial and temporal dynamics of the human land-use activities settlement, cultivation of food crops and grazing management, which compete for the available land resources. The rational of the model is to regionalize the demands for area intensive commodities (e.g. crop production) and services (e.g. space for housing) from the country-level to a global grid with the spatial resolution of 5 arc-minutes. The modelled land-use decisions within the agricultural sector are influenced by changing climate and the resulting effects on biomass productivity. Currently, this causal chain is modelled by integrating results from the process-based vegetation model LPJmL model for changing crop yields and net primary productivity of grazing land. Model output of LandSHIFT is a time series of grid maps with land-use/land-cover information that can serve as basis for further impact analysis. An exemplary simulation study with LandSHIFT is presented, based on scenario assumptions from the UNEP Global Environmental Outlook 4. Time horizon of the analysis is the year 2050. Changes of future food production on country level are computed by the agro-economy model IMPACT as a function of demography, economic development and global trade pattern. Together with scenario assumptions on climatic change and population growth, this data serves as model input to compute the changing land-use und land-cover. The continental and global scale model results are then analysed with respect to changes in the spatial pattern of natural vegetation as well as the resulting effects on evapotranspiration processes and land surface parameters. Furthermore, possible linkages of LandSHIFT to the different components of Earth System models (e.g. climate and natural vegetation) are discussed.
NASA Technical Reports Server (NTRS)
Kuan, Dana; Fahsi, A.; Steinfeld S.; Coleman, T.
1998-01-01
Two Landsat Thematic Mapper (TM) images, from July 1984 and July 1992, were used to identify land use/cover changes in the urban and suburban fringe of the city of Huntsville, Alabama. Image difference was the technique used to quantify the change between the two dates. The eight-year period showed a 16% change, mainly from agricultural lands to urban areas generated by the settlement of industrial, commercial, and residential areas. Visual analysis of the change map (i.e., difference image) supported this phenomenon by showing that most changes were occurring in the vicinity of the major roads and highways across the city.
NASA Astrophysics Data System (ADS)
Pham, Trinh Hung
Monitoring hydrological behavior of a large tropical watershed following a forest cover variation has an important role in water resource management planning as well as for forest sustainable management. Traditional methods in forest hydrology studies are Experimental watersheds, Upstream-downstream, Experimental plots, Statistical regional analysis and Watershed simulation. Those methodes have limitations for large watersheds concerning the monitoring time, the lack of input data especially about forest cover and the capacity of extrapolating results accurately in terms of large watersheds. Moreover, there is still currently a scientific debate in forest ecology on relation between water and forest. The reason of this problem comes from geographical differences in publication concerning study zones, experimental watershed size and applied methods. It gives differences in the conclusions on the influence of tropical forest cover change on the changes of outlet water and yet on the yearly runoff in terms of large watershed. In order to exceed the limitations of actual methods, to solve the difficulty of acquiring forest cover data and to have a better understanding of the relation between tropical forest cover change and hydrological behavior evolution of a large watershed, it is necessary to develop a new approach by using numeric remote sensing. We used the watershed of Dong Nai as a case study. Results show that a fusion between TM and ETM+ Landsat image series and hydro-meteorologic data allow us to observe and detect flooding trends and flooding peaks after an intensive forest cover change from 16% to 20%. Flooding frequency and flooding peaks have clearly decreased when there is an increase of the forest cover from 1983 to 1990. The influence of tropical forest cover on the hydrological behavior is varying with geographical locations of watershed. There is a significant relation between forest cover evolution and environmental facteurs as the runoff coefficient (R = 0,87) and the yearly precipitation (R = 0,93).
Assessing land use and cover change effects on hydrological response in the river C
NASA Astrophysics Data System (ADS)
Nunes, A.
2009-04-01
Assessing the impacts of land use change, especially the role of vegetation, on hydrological response from the plot to the catchment scale has become one of the widespread issues of scientific concern,in recent decades. The continuous expansion of urban areas, the dramatic changes in land-cover and land-use patterns and the climate change which have taken place on a global scale explain this increasing interest. Although scientists have long recognized that changes in land use and land cover are important factors affecting water circulation and the spatial-temporal variations in the distribution of water resources, little is known about the quantitative relation between land use/coverage characteristics and runoff generation or processes. Therefore, a better understanding of how land-use changes impact watershed hydrological processes will become a crucial issue for the planning, management, and sustainable development of water resources. In the past decades, abandonment of marginal agricultural land has been a widespread phenomenon in Portugal, as well as in many other countries of Europe, especially in the Mediterranean countries. The abandonment of arable land typically leads to natural succession and to the development of shrub and woodland. Shrubs like Cytisus spp.usually establish in study area. A Quercus pyrenaica Willd. wood generally appears after a long time, about 3 or 4 decades. The general aim of this work is to analyse the temporal evolution of water supplies in a Côa basins (located between 41°00'' N and 40°15'' N and 7°15'' W and 6°55'' W Greenwich)and relate its behaviour with changes undergone by the plant cover and by the main climatic variables (temperatures and precipitation). To achieve this goal, dynamics on the land use and land cover were estimated after the second half of the 20th century. The hydrological response under different land uses and plant covers were monitored during 2005 and 2006, using small permanently establish bounded runoff plots (8×2 m) that drain to a modified Gerlach trough. Regarding the hydrological analysis at basin scale, a study of the temporal evolution of the monthly and annual discharges (Dam3) was made at two measuring stations, between 1956 and 1999. During this period the river was not subjected to the effects of large reservoir and its data on discharges can be considered representative of the natural functioning under a natural regimen. After 2000, the Côa river functioning was submitted to the effect of a large dam. For the analysis of temperatures and precipitation, the monthly and annual series recorded between 1956 and 1999 were used. To check the degree of significance of the trend with a certain level of confidence and to detect correlations among observed variables, a non-parametric test and Pearson coefficient were applied. The obtained results show that an important increase occurred on plant covers between 1960 and 2000; scrub plant communities became the most extensive land cover and the most important vegetation type. When a permanent vegetated cover is dominant surface runoff are very well controlled at plot scale. The major part of rainfall is infiltrated. On a catchment scale, the temporal evolution of the annual discharges has been negative and statistically significant (p-value < 0.05). The correlation coefficient between rainfall and discharges was quite significant for the studied period, which means that river discharges are very sensitive to rainfall amount. Nevertheless, the relationship between the variables seems to have a significant change throughout the analysed period, which is confirmed by the observation of temporal trend in residuals, the product of the year-by-year correlation between rainfall and discharge, and time. In general, residuals behaviour are clearly positive before the 80`s and negative after this date. This temporal variability could be related with changes occurred in land use and land cover.
Zomer, Robert J.; Neufeldt, Henry; Xu, Jianchu; Ahrends, Antje; Bossio, Deborah; Trabucco, Antonio; van Noordwijk, Meine; Wang, Mingcheng
2016-01-01
Agroforestry systems and tree cover on agricultural land make an important contribution to climate change mitigation, but are not systematically accounted for in either global carbon budgets or national carbon accounting. This paper assesses the role of trees on agricultural land and their significance for carbon sequestration at a global level, along with recent change trends. Remote sensing data show that in 2010, 43% of all agricultural land globally had at least 10% tree cover and that this has increased by 2% over the previous ten years. Combining geographically and bioclimatically stratified Intergovernmental Panel on Climate Change (IPCC) Tier 1 default estimates of carbon storage with this tree cover analysis, we estimated 45.3 PgC on agricultural land globally, with trees contributing >75%. Between 2000 and 2010 tree cover increased by 3.7%, resulting in an increase of >2 PgC (or 4.6%) of biomass carbon. On average, globally, biomass carbon increased from 20.4 to 21.4 tC ha−1. Regional and country-level variation in stocks and trends were mapped and tabulated globally, and for all countries. Brazil, Indonesia, China and India had the largest increases in biomass carbon stored on agricultural land, while Argentina, Myanmar, and Sierra Leone had the largest decreases. PMID:27435095
NASA Astrophysics Data System (ADS)
Mugiraneza, T.; Haas, J.; Ban, Y.
2017-11-01
Mapping urbanization and ensuing environmental impacts using satellite data combined with landscape metrics has become a hot research topic. The objectives of the study are to analyze the spatio-temporal evolution of urbanization patterns of Kigali, Rwanda over the last three decades (from 1984 to 2015) using multitemporal Landsat data and to assess the associated environmental impact using landscape metrics. Landsat images, Normalized Difference Vegetation Index (NDVI), Grey Level Co-occurrence Matrix (GLCM) variance texture and digital elevation model (DEM) data were classified using a support vector machine (SVM). Eight landscape indices were derived from classified images for urbanization environment impact assessment. Seven land cover classes were derived with an overall accuracy exceeding 88 % with Kappa Coefficients around 0.8. As most prominent changes, cropland was reduced considerably in favour of built-up areas that increased from 2,349 ha to 11,579 ha between 1984 and 2015. During those 31 years, the increased number of patches in most land cover classes illustrated landscape fragmentation, especially for forest. The landscape configuration indices demonstrate that in general the land cover pattern remained stable for cropland but it was highly changed in built-up areas. Satellite-based analysis and quantification of urbanization and its effects using landscape metrics are found to be interesting for grassroots and provide a cost-effective method for urban information production. This information can be used for e.g. potential design and implementation of early warning systems that cater for urbanization effects.
NASA Astrophysics Data System (ADS)
Stefanov, W. L.; Stefanov, W. L.; Christensen, P. R.
2001-05-01
Land cover and land use changes associated with urbanization are important drivers of global ecologic and climatic change. Quantification and monitoring of these changes are part of the primary mission of the ASTER instrument, and comprise the fundamental research objective of the Urban Environmental Monitoring (UEM) Program. The UEM program will acquire day/night, visible through thermal infrared ASTER data twice per year for 100 global urban centers over the duration of the mission (6 years). Data are currently available for a number of these urban centers and allow for initial comparison of global city structure using spatial variance texture analysis of the 15 m/pixel visible to near infrared ASTER bands. Variance texture analysis highlights changes in pixel edge density as recorded by sharp transitions from bright to dark pixels. In human-dominated landscapes these brightness variations correlate well with urbanized vs. natural land cover and are useful for characterizing the geographic extent and internal structure of cities. Variance texture analysis was performed on twelve urban centers (Albuquerque, Baghdad, Baltimore, Chongqing, Istanbul, Johannesburg, Lisbon, Madrid, Phoenix, Puebla, Riyadh, Vancouver) for which cloud-free daytime ASTER data are available. Image transects through each urban center produce texture profiles that correspond to urban density. These profiles can be used to classify cities into centralized (ex. Baltimore), decentralized (ex. Phoenix), or intermediate (ex. Madrid) structural types. Image texture is one of the primary data inputs (with vegetation indices and visible to thermal infrared image spectra) to a knowledge-based land cover classifier currently under development for application to ASTER UEM data as it is acquired. Collaboration with local investigators is sought to both verify the accuracy of the knowledge-based system and to develop more sophisticated classification models.
Impacts of Land use change on air quality and climate of Hangzhou City, South Eastern parts of China
NASA Astrophysics Data System (ADS)
Singh, R. P.; Zheng, S.
2016-12-01
Land use and land cover change (LUCC) influence the weather and climate conditions at local, regional and global scales. It has dramatically altered the Earth's landscape, chemical fluxes and influences the Earth's climate. The rapid land use change is often related to urban sprawl, farmland displacement, and deforestation. In the last two decades, land use land cover has rapidly changed in China especially along the eastern coastal region. Earlier studies have shown frequent (160 days in a year) occurrence of haze, fog and smog during 2003-2010 in and around Hangzhou city which lies in the south east coast region of China. An analysis of ground observed air quality and trace gases from 11 stations in Hangzhou city and satellite retrieved atmospheric parameters from 2011-2015 show increasing air quality and atmospheric pollution. The pollutants show very dynamic nature especially during winter season associated with the mixing with the influx of air mass from the surrounding regions. The frequent occurrences of fog, haze and smog over Hangzhou city is associated with the land use and land cover change of 16596 km2 areas, home of 9.02 million people. The spatial-temporal characteristics of land use change and air quality in response to rapid urbanization will be presented.
Recent landscape change in California's Central Valley
NASA Astrophysics Data System (ADS)
Soulard, C. E.; Wilson, T. S.
2012-12-01
Long term monitoring of land use and land cover in California's intensively farmed Central Valley reveals several key physical and socioeconomic factors driving landscape change. As part of the USGS Land Cover Trends Project, we analyzed modern land-use/land-cover change for the California Central Valley ecoregion between 2000 and 2010, monitoring annual change between 2005 and 2010, while creating two new change intervals (2000-2005 and 2005-2010) to update the existing 27-year, interval-based analysis. Between 2000 and 2010, agricultural lands fluctuated due to changes in water allocations and emerging drought conditions, or were lost permanently to development (240 square km). Land-use pressure from agriculture and development also led to a decline in grasslands and shrublands across the region (280 square km). Overall, 400 square km of new developed lands were added in the first decade of the 21st century. From 2007 to 2010, development only expanded by 50 square km, coinciding with defaults in the banking system, the onset of historic foreclosure crisis in California and the global economic downturn. Our annual LULC change estimates capture landscape-level change in response to regional policy changes, climate, and fluctuations (e.g., growth or decline) in the national and global economy. The resulting change data provide insights into the drivers of landscape change in the California Central Valley and the combination of two consistent mapping efforts represents the first continuous, 37-year endeavor of its kind.
Beall, B F N; Twiss, M R; Smith, D E; Oyserman, B O; Rozmarynowycz, M J; Binding, C E; Bourbonniere, R A; Bullerjahn, G S; Palmer, M E; Reavie, E D; Waters, Lcdr M K; Woityra, Lcdr W C; McKay, R M L
2016-06-01
Mid-winter limnological surveys of Lake Erie captured extremes in ice extent ranging from expansive ice cover in 2010 and 2011 to nearly ice-free waters in 2012. Consistent with a warming climate, ice cover on the Great Lakes is in decline, thus the ice-free condition encountered may foreshadow the lakes future winter state. Here, we show that pronounced changes in annual ice cover are accompanied by equally important shifts in phytoplankton and bacterial community structure. Expansive ice cover supported phytoplankton blooms of filamentous diatoms. By comparison, ice free conditions promoted the growth of smaller sized cells that attained lower total biomass. We propose that isothermal mixing and elevated turbidity in the absence of ice cover resulted in light limitation of the phytoplankton during winter. Additional insights into microbial community dynamics were gleaned from short 16S rRNA tag (Itag) Illumina sequencing. UniFrac analysis of Itag sequences showed clear separation of microbial communities related to presence or absence of ice cover. Whereas the ecological implications of the changing bacterial community are unclear at this time, it is likely that the observed shift from a phytoplankton community dominated by filamentous diatoms to smaller cells will have far reaching ecosystem effects including food web disruptions. © 2015 Society for Applied Microbiology and John Wiley & Sons Ltd.
Monitoring forest dynamics with multi-scale and time series imagery.
Huang, Chunbo; Zhou, Zhixiang; Wang, Di; Dian, Yuanyong
2016-05-01
To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data. Using time series Normalized Difference Vegetation Index products derived from the Moderate Resolution Imaging Spectroradiometer images (MODIS-NDVI) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as data source, a hierarchy stepwise analysis from coarse scale to fine scale was developed for detecting the forest change area. At the coarse scale, MODIS-NDVI data with 1-km resolution were used to detect the changes in land cover types and a land cover change map was constructed using NDVI values at vegetation growing seasons. At the fine scale, based on the results at the coarse scale, Landsat TM/ETM+ data with 30-m resolution were used to precisely detect the forest change location and forest change trend by analyzing time series forest vegetation indices (IFZ). The method was tested using the data for Hubei Province, China. The MODIS-NDVI data from 2001 to 2012 were used to detect the land cover changes, and the overall accuracy was 94.02 % at the coarse scale. At the fine scale, the available TM/ETM+ images at vegetation growing seasons between 2001 and 2012 were used to locate and verify forest changes in the Three Gorges Reservoir Area, and the overall accuracy was 94.53 %. The accuracy of the two layer hierarchical monitoring results indicated that the multi-scale monitoring method is feasible and reliable.
Participative Spatial Scenario Analysis for Alpine Ecosystems
NASA Astrophysics Data System (ADS)
Kohler, Marina; Stotten, Rike; Steinbacher, Melanie; Leitinger, Georg; Tasser, Erich; Schirpke, Uta; Tappeiner, Ulrike; Schermer, Markus
2017-10-01
Land use and land cover patterns are shaped by the interplay of human and ecological processes. Thus, heterogeneous cultural landscapes have developed, delivering multiple ecosystem services. To guarantee human well-being, the development of land use types has to be evaluated. Scenario development and land use and land cover change models are well-known tools for assessing future landscape changes. However, as social and ecological systems are inextricably linked, land use-related management decisions are difficult to identify. The concept of social-ecological resilience can thereby provide a framework for understanding complex interlinkages on multiple scales and from different disciplines. In our study site (Stubai Valley, Tyrol/Austria), we applied a sequence of steps including the characterization of the social-ecological system and identification of key drivers that influence farmers' management decisions. We then developed three scenarios, i.e., "trend", "positive" and "negative" future development of farming conditions and assessed respective future land use changes. Results indicate that within the "trend" and "positive" scenarios pluri-activity (various sources of income) prevents considerable changes in land use and land cover and promotes the resilience of farming systems. Contrarily, reductions in subsidies and changes in consumer behavior are the most important key drivers in the negative scenario and lead to distinct abandonment of grassland, predominantly in the sub-alpine zone of our study site. Our conceptual approach, i.e., the combination of social and ecological methods and the integration of local stakeholders' knowledge into spatial scenario analysis, resulted in highly detailed and spatially explicit results that can provide a basis for further community development recommendations.
Participative Spatial Scenario Analysis for Alpine Ecosystems.
Kohler, Marina; Stotten, Rike; Steinbacher, Melanie; Leitinger, Georg; Tasser, Erich; Schirpke, Uta; Tappeiner, Ulrike; Schermer, Markus
2017-10-01
Land use and land cover patterns are shaped by the interplay of human and ecological processes. Thus, heterogeneous cultural landscapes have developed, delivering multiple ecosystem services. To guarantee human well-being, the development of land use types has to be evaluated. Scenario development and land use and land cover change models are well-known tools for assessing future landscape changes. However, as social and ecological systems are inextricably linked, land use-related management decisions are difficult to identify. The concept of social-ecological resilience can thereby provide a framework for understanding complex interlinkages on multiple scales and from different disciplines. In our study site (Stubai Valley, Tyrol/Austria), we applied a sequence of steps including the characterization of the social-ecological system and identification of key drivers that influence farmers' management decisions. We then developed three scenarios, i.e., "trend", "positive" and "negative" future development of farming conditions and assessed respective future land use changes. Results indicate that within the "trend" and "positive" scenarios pluri-activity (various sources of income) prevents considerable changes in land use and land cover and promotes the resilience of farming systems. Contrarily, reductions in subsidies and changes in consumer behavior are the most important key drivers in the negative scenario and lead to distinct abandonment of grassland, predominantly in the sub-alpine zone of our study site. Our conceptual approach, i.e., the combination of social and ecological methods and the integration of local stakeholders' knowledge into spatial scenario analysis, resulted in highly detailed and spatially explicit results that can provide a basis for further community development recommendations.
Effect of land use change on soil properties and functions
NASA Astrophysics Data System (ADS)
Tonutare, Tonu; Kõlli, Raimo; Köster, Tiina; Rannik, Kaire; Szajdak, Lech; Shanskiy, Merrit
2014-05-01
For good base of sustainable land management and ecologically sound protection of soils are researches on soil properties and functioning. Ecosystem approach to soil properties and functioning is equally important in both natural and cultivated land use conditions. Comparative analysis of natural and agro-ecosystems formed on similar soil types enables to elucidate principal changes caused by land use change (LUC) and to elaborate the best land use practices for local pedo-ecological conditions. Taken for actual analysis mineral soils' catena - rendzina → brown soils → pseudopodzolic soils → gley-podzols - represent ca 1/3 of total area of Estonian normal mineral soils. All soils of this catena differ substantially each from other by calcareousness, acidity, nutrition conditions, fabric and humus cover type. This catena (representative to Estonian pedo-ecological conditions) starts with drought-prone calcareous soils. Brown (distributed in northern and central Estonia) and pseudopodzolic soils (in southern Estonia) are the most broadly acknowledged for agricultural use medium-textured high-quality automorphic soils. Dispersedly distributed gley-podzols are permanently wet and strongly acid, low-productivity sandy soils. In presentation four complex functions of soils are treated: (1) being a suitable soil environment for plant cover productivity (expressed by annual increment, Mg ha-1 yr-1); (2) forming adequate conditions for decomposition, transformation and conversion of fresh falling litter (characterized by humus cover type); (3) deposition of humus, individual organic compounds, plant nutrition elements, air and water, and (4) forming (bio)chemically variegated active space for soil type specific edaphon. Capacity of soil cover as depositor (3) depends on it thickness, texture, calcareousness and moisture conditions. Biological activity of soil (4) is determined by fresh organic matter influx, quality and quantity of biochemical substances and humus, and pedo-ecological conditions. LUC from natural to arable is accompanied by different regulations: (1) regular restoration of plant available nutrition elements' stocks in soil, (2) regulation (if needed) of water regime of gleyed and gley soils, (3) optimizing of soil actual acidity by liming, and (4) forming a suitable for crops seed bed instead of natural epipedon. Principal changes are occurred in fabric and agrochemical properties of topsoil and in soil functioning. The connected with LUC changes in soil functioning are: (1) increase of openness level of chemical elements cycling and nutrition elements concentration in phytomass, and (2) decrease of total phytomass, species diversity, amount of annual falling litter and content of mortmass in soil cover. These changes lead to decreasing of biological control on soil resources, flux of energy and substances to soil processes, and volume of cycling. At the same time the intensity of organic matter decomposition and outflow of nutrition elements are increased. All these changes are resulted by alteration of food chains and exhausting of nutrition elements' stocks. The changes in soil functioning (decrease or increase of productivity) depend much on soil type. The aspects of functioning, which do not changed with LUC are chemical-textural potential of soil cover and functioning character of subsoil. The sound matching of soil and plant cover is of decisive importance for sustainable functioning of ecosystem and in attaining a good environmental status of the area.
Temesgen, Habtamu; Wu, Wei; Legesse, Abiyot; Yirsaw, Eshetu; Bekele, Belew
2018-02-23
Characterized by high population density on a rugged topography, the Gedeo-Abaya landscape dominantly contains a multi-strata traditional agroforests showing the insight of Gedeo farmers on natural resource management practices. Currently, this area has been losing its resilience and is becoming unable to sustain its inhabitants. Based on both RS-derived and GIS-computed land-use/cover changes (LUCC) as well as socioeconomic validations, this article explored the LUCC and agroecological-based driver patterns in Gedeo-Abaya landscape from 1986 to 2015. A combination of geo-spatial technology and cross-sectional survey design were employed to detect the drivers behind these changes. The article discussed that LUCC and the prevalence of drivers are highly diverse and vary throughout agroecological zones. Except for the population, most downstream top drivers are perceived as insignificant in the upstream region and vice versa. In the downstream, land-use/cover (LUC) classes are more dynamic, diverse, and challenged by nearly all anticipated drivers than are upstream ones. Agroforestry LUC has been increasing (by 25% of its initial cover) and is becoming the predominant cover type, although socioeconomic analysis and related findings show its rapid LUC modification. A rapid reduction of woodland/shrubland (63%) occurred in the downstream, while wetland/marshy land increased threefold (158%), from 1986 to 2015 with annual change rates of - 3.7 and + 6%, respectively. Land degradation induced by changes in land use is a serious problem in Africa, especially in the densely populated sub-Saharan regions such as Ethiopia (FAO 2015). Throughout the landscape, LUCC is prominently affecting land-use system of the study landscape due to population pressure in the upstream region and drought/rainfall variability, agribusiness investment, and charcoaling in the downstream that necessitate urgent action.
Extraction of land cover change information from ENVISAT-ASAR data in Chengdu Plain
NASA Astrophysics Data System (ADS)
Xu, Wenbo; Fan, Jinlong; Huang, Jianxi; Tian, Yichen; Zhang, Yong
2006-10-01
Land cover data are essential to most global change research objectives, including the assessment of current environmental conditions and the simulation of future environmental scenarios that ultimately lead to public policy development. Chinese Academy of Sciences generated a nationwide land cover database in order to carry out the quantification and spatial characterization of land use/cover changes (LUCC) in 1990s. In order to improve the reliability of the database, we will update the database anytime. But it is difficult to obtain remote sensing data to extract land cover change information in large-scale. It is hard to acquire optical remote sensing data in Chengdu plain, so the objective of this research was to evaluate multitemporal ENVISAT advanced synthetic aperture radar (ASAR) data for extracting land cover change information. Based on the fieldwork and the nationwide 1:100000 land cover database, the paper assesses several land cover changes in Chengdu plain, for example: crop to buildings, forest to buildings, and forest to bare land. The results show that ENVISAT ASAR data have great potential for the applications of extracting land cover change information.
Chen, Xuexia; Giri, Chandra; Vogelmann, James
2012-01-01
Land cover is the biophysical material on the surface of the earth. Land-cover types include grass, shrubs, trees, barren, water, and man-made features. Land cover changes continuously. The rate of change can be either dramatic and abrupt, such as the changes caused by logging, hurricanes and fire, or subtle and gradual, such as regeneration of forests and damage caused by insects (Verbesselt et al., 2001). Previous studies have shown that land cover has changed dramatically during the past sevearal centuries and that these changes have severely affected our ecosystems (Foody, 2010; Lambin et al., 2001). Lambin and Strahlers (1994b) summarized five types of cause for land-cover changes: (1) long-term natural changes in climate conditions, (2) geomorphological and ecological processes, (3) human-induced alterations of vegetation cover and landscapes, (4) interannual climate variability, and (5) human-induced greenhouse effect. Tools and techniques are needed to detect, describe, and predict these changes to facilitate sustainable management of natural resources.
Assessing the effects of land use/cover change on carbon dioxide fluxes in a semiarid shrubland
NASA Astrophysics Data System (ADS)
Gong, Tingting; Lei, Huimin; Yang, Dawen; Jiao, Yang; Yang, Hanbo
2017-04-01
Land use/cover change has been generally considered a local environmental issue. Our study focuses on the effects of land use/cover change on the carbon cycle using long-term continuous field observation data, which is measured by the eddy covariance (EC) technique. The study site is at Yulin (38.45N, 109.47E), which is a desert shrubland ecosystem in Mu Us sandland, China. Before June 2012, the vegetation in this site was covered with mixed vegetation: typical desert shrubs (e.g., Salix psammophila and Artemisia ordosica) and grass. After July 2012, a part of the land use/cover condition within the footprint was changed by the local farmers, which converted the land use/cover condition changed first from mixed vegetation to bare soil and then from bare soil to grassland resulting from the re-growing grass. Four-year carbon fluxes are selected and separated into three periods: Period I is from July 1 2011 to June 30 2012 when land use/cover condition did not change; Period II is from July 1 2012 to June 30 2014 when land use/cover condition changed from mixed vegetation (shrubs and grass) to the mix of bare soil and desert shrubs; Period III is from July 1 2014 to June 30 2015 when land use/cover condition changed from the mix of desert shrubs and bare soil to the mix of desert shrubs and re-growing grass. A linear statistical model will be used to evaluate and quantify the effects of land use/cover change on the uptake or release of carbon fluxes (net ecosystem exchange (NEE), ecosystem respiration (Reco) and gross primary production (GPP)). Moreover, this study is expected to get insights into how agricultural cultivation influences on the local carbon balance (e.g., how NEE, Reco and GPP respond to the land use/cover change; Is the annual carbon balance changed during the land use/cover change process; and the contribution of land use/cover change on these changes of carbon fluxes).
on determining land cover and land cover change around the world. Land cover is the discernible imagery. Land cover change can be assessed by comparing one area with two images taken at different dates . Determining where, when, how much and why change occurs with land cover is a crucial scientific concern. It is
Pilgrim, C M; Mikhailova, E A; Post, C J; Hains, J J
2014-11-01
Monitoring changes in land cover and the subsequent environmental responses are essential for water quality assessment, natural resource planning, management, and policies. Over the last 75 years, the Lake Issaqueena watershed has experienced a drastic shift in land use. This study was conducted to examine the changes in land cover and the implied changes in land use that have occurred and their environmental, water quality impacts. Aerial photography of the watershed (1951, 1956, 1968, 1977, 1989, 1999, 2005, 2006, and 2009) was analyzed and classified using the geographic information system (GIS) software. Seven land cover classes were defined: evergreen, deciduous, bare ground, pasture/grassland, cultivated, and residential/other development. Water quality data, including sampling depth, water temperature, dissolved oxygen content, fecal coliform levels, inorganic nitrogen concentrations, and turbidity, were obtained from the South Carolina (SC) Department of Health and Environmental Control (SCDHEC) for two stations and analyzed for trends as they relate to land cover change. From 1951 to 2009, the watershed experienced an increase of tree cover and bare ground (+17.4 % evergreen, +62.3 % deciduous, +9.8 % bare ground) and a decrease of pasture/grassland and cultivated land (-42.6 % pasture/grassland and -57.1 % cultivated). From 2005 to 2009, there was an increase of 21.5 % in residential/other development. Sampling depth ranged from 0.1 to 0.3 m. Water temperature fluctuated corresponding to changing air temperatures, and dissolved oxygen content fluctuated as a factor of water temperature. Inorganic nitrogen content was higher from December to April possibly due to application of fertilizers prior to the growing season. Turbidity and fecal coliform bacteria levels remained relatively the same from 1962 to 2005, but a slight decline in pH can be observed at both stations. Prior to 1938, the area consisted of single-crop cotton farms; after 1938, the farms were abandoned, leaving large bare areas with highly eroded soil. Starting in 1938, Clemson reforested almost 30 % of the watershed. Currently, three fourths of the watershed is forestland, with a limited coverage of small farms and residential developments. Monitoring water quality is essential in maintaining adequate freshwater supply. Water quality monitoring focuses mainly on the collection of field data, but current water quality conditions depend on the cumulative impacts of land cover change over time.
NASA Astrophysics Data System (ADS)
Sarıyılmaz, F. B.; Musaoğlu, N.; Uluğtekin, N.
2017-11-01
The Sazlidere Basin is located on the European side of Istanbul within the borders of Arnavutkoy and Basaksehir districts. The total area of the basin, which is largely located within the province of Arnavutkoy, is approximately 177 km2. The Sazlidere Basin is faced with intense urbanization pressures and land use / cover change due to the Northern Marmara Motorway, 3rd airport and Channel Istanbul Projects, which are planned to be realized in the Arnavutkoy region. Due to the mentioned projects, intense land use /cover changes occur in the basin. In this study, 2000 and 2012 dated LANDSAT images were supervised classified based on CORINE Land Cover first level to determine the land use/cover classes. As a result, four information classes were identified. These classes are water bodies, forest and semi-natural areas, agricultural areas and artificial surfaces. Accuracy analysis of the images were performed following the classification process. The supervised classified images that have the smallest mapping units 0.09 ha and 0.64 ha were generalized to be compatible with the CORINE Land Cover data. The image pixels have been rearranged by using the thematic pixel aggregation method as the smallest mapping unit is 25 ha. These results were compared with CORINE Land Cover 2000 and CORINE Land Cover 2012, which were obtained by digitizing land cover and land use classes on satellite images. It has been determined that the compared results are compatible with each other in terms of quality and quantity.
Evidence of Incipient Forest Transition in Southern Mexico
Vaca, Raúl Abel; Golicher, Duncan John; Cayuela, Luis; Hewson, Jenny; Steininger, Marc
2012-01-01
Case studies of land use change have suggested that deforestation across Southern Mexico is accelerating. However, forest transition theory predicts that trajectories of change can be modified by economic factors, leading to spatial and temporal heterogeneity in rates of change that may take the form of the Environmental Kuznets Curve (EKC). This study aimed to assess the evidence regarding potential forest transition in Southern Mexico by classifying regional forest cover change using Landsat imagery from 1990 through to 2006. Patterns of forest cover change were found to be complex and non-linear. When rates of forest loss were averaged over 342 municipalities using mixed-effects modelling the results showed a significant (p<0.001) overall reduction of the mean rate of forest loss from 0.85% per year in the 1990–2000 period to 0.67% in the 2000–2006 period. The overall regional annual rate of deforestation has fallen from 0.33% to 0.28% from the 1990s to 2000s. A high proportion of the spatial variability in forest cover change cannot be explained statistically. However analysis using spline based general additive models detected underlying relationships between forest cover and income or population density of a form consistent with the EKC. The incipient forest transition has not, as yet, resulted in widespread reforestation. Forest recovery remains below 0.20% per year. Reforestation is mostly the result of passive processes associated with reductions in the intensity of land use. Deforestation continues to occur at high rates in some focal areas. A transition could be accelerated if there were a broader recognition among policy makers that the regional rate of forest loss has now begun to fall. The changing trajectory provides an opportunity to actively restore forest cover through stimulating afforestation and stimulating more sustainable land use practices. The results have clear implications for policy aimed at carbon sequestration through reducing deforestation and enhancing forest growth. PMID:22905123
Evidence of incipient forest transition in Southern Mexico.
Vaca, Raúl Abel; Golicher, Duncan John; Cayuela, Luis; Hewson, Jenny; Steininger, Marc
2012-01-01
Case studies of land use change have suggested that deforestation across Southern Mexico is accelerating. However, forest transition theory predicts that trajectories of change can be modified by economic factors, leading to spatial and temporal heterogeneity in rates of change that may take the form of the Environmental Kuznets Curve (EKC). This study aimed to assess the evidence regarding potential forest transition in Southern Mexico by classifying regional forest cover change using Landsat imagery from 1990 through to 2006. Patterns of forest cover change were found to be complex and non-linear. When rates of forest loss were averaged over 342 municipalities using mixed-effects modelling the results showed a significant (p<0.001) overall reduction of the mean rate of forest loss from 0.85% per year in the 1990-2000 period to 0.67% in the 2000-2006 period. The overall regional annual rate of deforestation has fallen from 0.33% to 0.28% from the 1990s to 2000s. A high proportion of the spatial variability in forest cover change cannot be explained statistically. However analysis using spline based general additive models detected underlying relationships between forest cover and income or population density of a form consistent with the EKC. The incipient forest transition has not, as yet, resulted in widespread reforestation. Forest recovery remains below 0.20% per year. Reforestation is mostly the result of passive processes associated with reductions in the intensity of land use. Deforestation continues to occur at high rates in some focal areas. A transition could be accelerated if there were a broader recognition among policy makers that the regional rate of forest loss has now begun to fall. The changing trajectory provides an opportunity to actively restore forest cover through stimulating afforestation and stimulating more sustainable land use practices. The results have clear implications for policy aimed at carbon sequestration through reducing deforestation and enhancing forest growth.
Near-real-time cheatgrass percent cover in the Northern Great Basin, USA, 2015
Boyte, Stephen; Wylie, Bruce K.
2016-01-01
Cheatgrass (Bromus tectorum L.) dramatically changes shrub steppe ecosystems in the Northern Great Basin, United States.Current-season cheatgrass location and percent cover are difficult to estimate rapidly.We explain the development of a near-real-time cheatgrass percent cover dataset and map in the Northern Great Basin for the current year (2015), display the current year’s map, provide analysis of the map, and provide a website link to download the map (as a PDF) and the associated dataset.The near-real-time cheatgrass percent cover dataset and map were consistent with non-expedited, historical cheatgrass percent cover datasets and maps.Having cheatgrass maps available mid-summer can help land managers, policy makers, and Geographic Information Systems personnel as they work to protect socially relevant areas such as critical wildlife habitats.
Optimization of composite sandwich cover panels subjected to compressive loadings
NASA Technical Reports Server (NTRS)
Cruz, Juan R.
1991-01-01
An analysis and design method is presented for the design of composite sandwich cover panels that includes transverse shear effects and damage tolerance considerations. This method is incorporated into an optimization program called SANDOP (SANDwich OPtimization). SANDOP is used in the present study to design optimized composite sandwich cover panels for transport aircraft wing applications as a demonstration of its capabilities. The results of this design study indicate that optimized composite sandwich cover panels have approximately the same structural efficiency as stiffened composite cover panels designed to identical constraints. Results indicate that inplane stiffness requirements have a large effect on the weight of these composite sandwich cover panels at higher load levels. Increasing the maximum allowable strain and the upper percentage limit of the 0 degree and plus or minus 45 degree plies can yield significant weight savings. The results show that the structural efficiency of these optimized composite sandwich cover panels is relatively insensitive to changes in core density.
Factors affecting harp seal (Pagophilus groenlandicus) strandings in the Northwest Atlantic.
Soulen, Brianne K; Cammen, Kristina; Schultz, Thomas F; Johnston, David W
2013-01-01
The effects of climate change on high latitude regions are becoming increasingly evident, particularly in the rapid decline of sea ice cover in the Arctic. Many high latitude species dependent on sea ice are being forced to adapt to changing habitats. Harp seals (Pagophilus groenlandicus) are an indicator species for changing high-latitude ecosystems. This study analyzed multiple factors including ice cover, demographics, and genetic diversity, which could affect harp seal stranding rates along the eastern coast of the United States. Ice cover assessments were conducted for the month of February in the Gulf of St. Lawrence whelping region from 1991-2010 using remote sensing data, and harp seal stranding data were collected over the same time period. Genetic diversity, which may affect how quickly species can adapt to changing climates, was assessed using ten microsatellite markers to determine mean d (2) in a subset of stranded and by-caught (presumably healthy) seals sampled along the northeast U.S. coast. Our study found a strong negative correlation (R (2) = 0.49) between ice cover in the Gulf of St. Lawrence and yearling harp seal strandings, but found no relationship between sea ice conditions and adult strandings. Our analysis revealed that male seals stranded more frequently than females during the study period and that this relationship was strongest during light ice years. In contrast, we found no significant difference in mean d (2) between stranded and by-caught harp seals. The results demonstrate that sea ice cover and demographic factors have a greater influence on harp seal stranding rates than genetic diversity, with only a little of the variance in mean d (2) among stranded seals explained by ice cover. Any changes in these factors could have major implications for harp seals, and these findings should be considered in the development of future management plans for the Arctic that incorporate climate variability.
Factors Affecting Harp Seal (Pagophilus groenlandicus) Strandings in the Northwest Atlantic
Schultz, Thomas F.; Johnston, David W.
2013-01-01
The effects of climate change on high latitude regions are becoming increasingly evident, particularly in the rapid decline of sea ice cover in the Arctic. Many high latitude species dependent on sea ice are being forced to adapt to changing habitats. Harp seals (Pagophilus groenlandicus) are an indicator species for changing high-latitude ecosystems. This study analyzed multiple factors including ice cover, demographics, and genetic diversity, which could affect harp seal stranding rates along the eastern coast of the United States. Ice cover assessments were conducted for the month of February in the Gulf of St. Lawrence whelping region from 1991–2010 using remote sensing data, and harp seal stranding data were collected over the same time period. Genetic diversity, which may affect how quickly species can adapt to changing climates, was assessed using ten microsatellite markers to determine mean d 2 in a subset of stranded and by-caught (presumably healthy) seals sampled along the northeast U.S. coast. Our study found a strong negative correlation (R 2 = 0.49) between ice cover in the Gulf of St. Lawrence and yearling harp seal strandings, but found no relationship between sea ice conditions and adult strandings. Our analysis revealed that male seals stranded more frequently than females during the study period and that this relationship was strongest during light ice years. In contrast, we found no significant difference in mean d 2 between stranded and by-caught harp seals. The results demonstrate that sea ice cover and demographic factors have a greater influence on harp seal stranding rates than genetic diversity, with only a little of the variance in mean d 2 among stranded seals explained by ice cover. Any changes in these factors could have major implications for harp seals, and these findings should be considered in the development of future management plans for the Arctic that incorporate climate variability. PMID:23874759
NASA Astrophysics Data System (ADS)
Saadatkhah, Nader; Mansor, Shattri; Khuzaimah, Zailani; Asmat, Arnis; Adnan, Noraizam; Adam, Siti Noradzah
2016-09-01
Changing the land cover/ land use has serious environmental impacts affecting the ecosystem in Malaysia. The impact of land cover changes on the environmental functions such as surface water, loss water, and soil moisture is considered in this paper on the Kelantan river basin. The study area at the east coast of the peninsular Malaysia has suffered significant land cover changes in the recent years. The current research tried to assess the impact of land cover changes in the study area focused on the surface water, loss water, and soil moisture from different land use classes and the potential impact of land cover changes on the ecosystem of Kelantan river basin. To simulate the impact of land cover changes on the environmental hydrology characteristics, a deterministic regional modeling were employed in this study based on five approaches, i.e. (1) Land cover classification based on Landsat images; (2) assessment of land cover changes during last three decades; (3) Calculation the rate of water Loss/ Infiltration; (4) Assessment of hydrological and mechanical effects of the land cover changes on the surface water; and (5) evaluation the impact of land cover changes on the ecosystem of the study area. Assessment of land cover impact on the environmental hydrology was computed with the improved transient rainfall infiltration and grid based regional model (Improved-TRIGRS) based on the transient infiltration, and subsequently changes in the surface water, due to precipitation events. The results showed the direct increased in surface water from development area, agricultural area, and grassland regions compared with surface water from other land covered areas in the study area. The urban areas or lower planting density areas tend to increase for surface water during the monsoon seasons, whereas the inter flow from forested and secondary jungle areas contributes to the normal surface water.
NASA Astrophysics Data System (ADS)
Bormann, K.; Rittger, K.; Painter, T. H.
2016-12-01
The continuation of large-scale snow cover records into the future is crucial for monitoring the impacts of global pressures such as climate change and weather variability on the cryosphere. With daily MODIS records since 2000 from a now ageing MODIS constellation (Terra & Aqua) and daily VIIRS records since 2012 from the Suomi-NPP platform, the consistency of information between the two optical sensors must be understood. First, we evaluated snow cover maps derived from both MODIS and VIIRS retrievals with coincident cloud-free Landsat 8 OLI maps across a range of locations. We found that both MODIS and VIIRS snow cover maps show similar errors when evaluated with Landsat OLI retrievals. Preliminary results also show a general agreement in regional snowline between the two sensors that is maintained during the spring snowline retreat where the proportion of mixed pixels is increased. The agreement between sensors supports the future use of VIIRS snow cover maps to continue the long-term record beyond the lifetime of MODIS. Second, we use snowline elevation to quantify large scale snow cover variability and to monitor potential changes in the rain/snow transition zone where climate change pressures may be enhanced. Despite the large inter-annual variability that is often observed in snow metrics, we expect that over the 16-year time series we will see a rise in seasonal elevation of the snowline and consequently an increasing rain/snow transition boundary in mountain environments. These results form the basis for global snowline elevation monitoring using optical remote sensing data and highlight regional differences in snowline elevation dynamics. The long-term variability in observed snowline elevation provides a recent climatology of mountain snowpack across several regions that will likely to be of interest to those interested in climate change impacts in mountain environments. This work will also be of interest to existing users of MODSCAG and VIIRSCAG snow cover products and those working in remote sensing of the mountain snowpack.
Analysis of the deforestation problem in tropical Latin America
Jorge Malleux
2012-01-01
The driving forces of land use changes have been analyzed and discussed for a long time with different solutions proposed and implemented. Unfortunately the reduction of natural forest cover continues in the same direction, generating an increasing alarm all around the world among scientist and politicians, related to the climate change awareness and strategies for its...
Change detection using NALC MSS triplicates to set forest planning context
D. R. Grey; P. E. Gessler; M. Hoppus; S. L. Boudreau
2000-01-01
The USDA Forest Service has purchased the North American Landscape Characterization (NALC) Landsat Multispectral Scanner (MSS) triplicates (70's, 80's, and 90's) for every national forest in the United States. To encourage analysis and use of these data for forest planning, a change-detection training course was developed. The course covers basic methods...
Development of a Unique Web2.0 Interface for Global Collaboration in Land Cover Change Research
NASA Astrophysics Data System (ADS)
Dunham, M.; Boriah, S.; Mithal, V.; Garg, A.; Steinbach, M.; Kumar, V.; Potter, C. S.; Klooster, S.; Castilla-Rubio, J.
2010-12-01
The ability to detect changes in forest cover is of critical importance for both economic and scientific reasons, e.g. using forests for economic carbon sink management and studying natural and anthropogenic impacts on ecosystems. The contribution of greenhouse gases from deforestation is one of the most uncertain elements of the global carbon cycle. In fact, changes in forests account for as much as 20% of the greenhouse gas emissions in the atmosphere, an amount second only to fossil fuel emissions. Thus, a key ingredient for effective forest management, whether for carbon trading or other purposes, is quantifiable knowledge about changes in forest cover. Rich amounts of data from remotely-sensed images are now becoming available for detecting changes in forests or more generally, land cover. However, in spite of the importance of this problem and the considerable advances made over the last few years in high-resolution satellite data acquisition, data mining, and online mapping tools and services, end users still lack practical tools to help them manage and transform this data into actionable knowledge of changes in forest ecosystems that can be used for decision making and policy planning purposes. We have developed innovations in a number of technical areas with the goal of providing actionable knowledge to end users: (i) identification of changes in global forest cover, (ii) characterization of those changes, (iii) discovery of relationships between the number, magnitude, and type of these changes with natural and anthropogenic variables, and (iv) a web-based platform that supports interactive visualization of disturbances and relationships. The focus of this abstract is on the interactive web-based platform. This key component of the project is a graphical user interface built on the Flash framework. The viewer is a groundbreaking, multi-purpose application used for everything from algorithm refinement and data analysis for the team to a demonstration platform for research partners. The team continues to develop the utility to allow for worldwide researcher and community contributions with the hopes of enhancing global understanding of environmental change.
Climate Impacts of Cover Crops
NASA Astrophysics Data System (ADS)
Lombardozzi, D.; Wieder, W. R.; Bonan, G. B.; Morris, C. K.; Grandy, S.
2016-12-01
Cover crops are planted in agricultural rotation with the intention of protecting soil rather than harvest. Cover crops have numerous environmental benefits that include preventing soil erosion, increasing soil fertility, and providing weed and pest control- among others. In addition to localized environmental benefits, cover crops can have important regional or global biogeochemical impacts by increasing soil organic carbon, changing emissions of greenhouse trace gases like nitrous oxide and methane, and reducing hydrologic nitrogen losses. Cover crops may additionally affect climate by changing biogeophysical processes, like albedo and latent heat flux, though these potential changes have not yet been evaluated. Here we use the coupled Community Atmosphere Model (CAM5) - Community Land Model (CLM4.5) to test how planting cover crops in the United States may change biogeophysical fluxes and climate. We present seasonal changes in albedo, heat fluxes, evaporative partitioning, radiation, and the resulting changes in temperature. Preliminary analyses show that during seasons when cover crops are planted, latent heat flux increases and albedo decreases, changing the evaporative fraction and surface temperatures. Understanding both the biogeophysical changes caused by planting cover crops in this study and the biogeochemical changes found in other studies will give a clearer picture of the overall impacts of cover crops on climate and atmospheric chemistry, informing how this land use strategy will impact climate in the future.
Paule, M A; Memon, S A; Lee, B-Y; Umer, S R; Lee, C-H
2014-01-01
Stormwater runoff quality is sensitive to land use and land cover (LULC) change. It is difficult to understand their relationship in predicting the pollution potential and developing watershed management practices to eliminate or reduce the pollution risk. In this study, the relationship between LULC change and stormwater runoff quality in two separate monitoring sites comprising a construction area (Site 1) and mixed land use (Site 2) was analyzed using geographic information system (GIS), event mean concentration (EMC), and correlation analysis. It was detected that bare land area increased, while other land use areas such as agriculture, commercial, forest, grassland, parking lot, residential, and road reduced. Based on the analyses performed, high maximum range and average EMCs were found in Site 2 for most of the water pollutants. Also, urban areas and increased conversion of LULC into bare land corresponded to degradation of stormwater quality. Correlation analysis between LULC and stormwater quality showed the influence of different factors such as farming practices, geographical location, and amount of precipitation, vegetation loss, and anthropogenic activities in monitoring sites. This research found that GIS application was an efficient tool for monthly monitoring, validation and statistical analysis of LULC change in the study area.
Identifying Water Insecurity Hotspots in the Lake Victoria Basin of Eastern Africa
NASA Astrophysics Data System (ADS)
Pricope, N. G.; Shukla, S.; Linard, C.; Gaughan, A.
2014-12-01
The Lake Victoria Basin (LVB), one of Africa's most populated transboundary watersheds and home to more than 30 million inhabitants, is increasingly challenged by both water quality problems and water quantity shortages against a backdrop of climate variability and change; and other environmental challenges. As a result of pollution, droughts, more erratic rainfall, heightened demand for water for both consumption and agricultural needs as well as differences in water allocation among the riverine countries of Uganda, Tanzania, Kenya, Rwanda and Burundi, many parts of this region are already experiencing water scarcity on a recurrent basis. Furthermore, given projected annual population growth rates of 2.5 to 3.5% for the next 20 years, water shortages are likely to be exacerbated in the future. Analyzing historical changes in the water resources of this region is hence important to identify "hot spots" that might be most sensitive to future changes in climate and demography. In this presentation, we report the findings of a comprehensive analysis performed to (i) examine changes in water resources of LVB in recent decades and (ii) identify overlap between regions of significant changes in water resources with land cover changes and high population centers that are also projected to grow the fastest over the coming decades. We first utilize several satellite, stations and model(s) based climatic and hydrologic datasets to assess changes in water resources in this region. We then use a quality-controlled Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product to identify areas of significant land cover changes. Simultaneously we use projections of gridded population density based on differential growth rates for rural and urban population to estimate fastest projected human population growth for 2030 and 2050 relative to 2010 data. Using the outcomes of these change analysis we identify water insecurity hotspots in the LVB.
NASA Technical Reports Server (NTRS)
Markert, Kel N.; Griffin, Robert; Limaye, Ashutosh S.; McNider, Richard T.; Anderson, Eric R.
2016-01-01
The Lower Mekong Basin (LMB) is an economically and ecologically important region that experiences hydrologic hazards such as floods and droughts, which can directly affect human well-being and limit economic growth and development. To effectively develop long-term plans for addressing hydrologic hazards, the regional hydrological response to climate variability and land cover change needs to be evaluated. This research aims to investigate how climate variability, specifically variations in the precipitation regime, and land cover change will affect hydrologic parameters both spatially and temporally within the LMB. The research goal is achieved by (1) modeling land cover change for a baseline land cover change scenario as well as changes in land cover with increases in forest or agriculture and (2) using projected climate variables and modeled land cover data as inputs into the Variable Infiltration Capacity (VIC) hydrologic model to simulate the changes to the hydrologic system. The VIC model outputs were analyzed against historic values to understand the relative contribution of climate variability and land cover to change, where these changes occur, and to what degree these changes affect the hydrology. This study found that the LMB hydrologic system is more sensitive to climate variability than land cover change. On average, climate variability was found to increase discharge and evapotranspiration (ET) while decreasing water storage. The change in land cover show that increasing forest area will slightly decrease discharge and increase ET while increasing agriculture area increases discharge and decreases ET. These findings will help the LMB by supporting individual country policy to plan for future hydrologic changes as well as policy for the basin as a whole.
Continuous Change Detection and Classification (CCDC) of Land Cover Using All Available Landsat Data
NASA Astrophysics Data System (ADS)
Zhu, Z.; Woodcock, C. E.
2012-12-01
A new algorithm for Continuous Change Detection and Classification (CCDC) of land cover using all available Landsat data is developed. This new algorithm is capable of detecting many kinds of land cover change as new images are collected and at the same time provide land cover maps for any given time. To better identify land cover change, a two step cloud, cloud shadow, and snow masking algorithm is used for eliminating "noisy" observations. Next, a time series model that has components of seasonality, trend, and break estimates the surface reflectance and temperature. The time series model is updated continuously with newly acquired observations. Due to the high variability in spectral response for different kinds of land cover change, the CCDC algorithm uses a data-driven threshold derived from all seven Landsat bands. When the difference between observed and predicted exceeds the thresholds three consecutive times, a pixel is identified as land cover change. Land cover classification is done after change detection. Coefficients from the time series models and the Root Mean Square Error (RMSE) from model fitting are used as classification inputs for the Random Forest Classifier (RFC). We applied this new algorithm for one Landsat scene (Path 12 Row 31) that includes all of Rhode Island as well as much of Eastern Massachusetts and parts of Connecticut. A total of 532 Landsat images acquired between 1982 and 2011 were processed. During this period, 619,924 pixels were detected to change once (91% of total changed pixels) and 60,199 pixels were detected to change twice (8% of total changed pixels). The most frequent land cover change category is from mixed forest to low density residential which occupies more than 8% of total land cover change pixels.
Forest land cover change (1975-2000) in the Greater Border Lakes region
Peter T. Wolter; Brian R. Sturtevant; Brian R. Miranda; Sue M. Lietz; Phillip A. Townsend; John Pastor
2012-01-01
This document and accompanying maps describe land cover classifications and change detection for a 13.8 million ha landscape straddling the border between Minnesota, and Ontario, Canada (greater Border Lakes Region). Land cover classifications focus on discerning Anderson Level II forest and nonforest cover to track spatiotemporal changes in forest cover. Multi-...
Multi-disciplinary optimization of aeroservoelastic systems
NASA Technical Reports Server (NTRS)
Karpel, Mordechay
1991-01-01
New methods were developed for efficient aeroservoelastic analysis and optimization. The main target was to develop a method for investigating large structural variations using a single set of modal coordinates. This task was accomplished by basing the structural modal coordinates on normal modes calculated with a set of fictitious masses loading the locations of anticipated structural changes. The following subject areas are covered: (1) modal coordinates for aeroelastic analysis with large local structural variations; and (2) time simulation of flutter with large stiffness changes.
Life on the Edge - Improved Forest Cover Mapping in Mixed-Use Tropical Regions
NASA Astrophysics Data System (ADS)
Anderson, C.; Mendenhall, C. D.; Daily, G.
2016-12-01
Tropical ecosystems and biodiversity are experiencing rapid change, primarily due to conversion of forest habitat to agriculture. Protected areas, while effective for conservation, only manage 15% of terrestrial area, whereas approximately 58% is privately owned. To incentivize private forest management and slow the loss of biodiversity, payments for ecosystem services (PES) programs were established in Costa Rica that pay landowners who maintain trees on their property. While this program is effective in improving livelihoods and preventing forest conversion, it is only managing payments to landowners on 1% of eligible, non-protected forested land.A major bottleneck for this program is access to accurate, national-scale tree cover maps. While the remote sensing community has made great progress in global-scale tree cover mapping, these maps are not sufficient to guide investments for PES programs. The major limitations of current global-scale tree-cover maps are that they a) do not distinguish between forest and agriculture and b) overestimate tree cover in mixed land-use areas (e.g. Global Forest Change overestimates by 20% on average in this region). This is especially problematic in biodiversity-rich Costa Rica, where small patches of forest intermix with agricultural production, and where the conservation value of tree-cover is high. To address this problem, we are developing a new forest cover mapping method that a) performs a least-squares spectral mixture analysis (SMA) using repeat Landsat imagery and canopy radiative transfer modeling: b) combines Landsat data, SMA results, and radar backscatter data using multi-sensor fusion techniques and: c) trains tree-cover classification models using high resolution data sets along a land use-intensity gradient. Our method predicted tree cover with 85% accuracy when compared to a fine-scale map of tree cover in a tropical, agricultural landscape, whereas the next-best method, the Global Forest Change map, predicted tree cover with 72% accuracy. Next steps will aim to test, improve, and apply this method globally to guide investments in nature in agricultural landscapes where forest stewardship will sustain biodiversity.
Commentary: A cautionary tale regarding use of the National Land Cover Dataset 1992
Thogmartin, Wayne E.; Gallant, Alisa L.; Knutson, Melinda G.; Fox, Timothy J.; Suarez, Manuel J.
2004-01-01
Digital land-cover data are among the most popular data sources used in ecological research and natural resource management. However, processes for accurate land-cover classification over large regions are still evolving. We identified inconsistencies in the National Land Cover Dataset 1992, the most current and available representation of land cover for the conterminous United States. We also report means to address these inconsistencies in a bird-habitat model. We used a Geographic Information System (GIS) to position a regular grid (or lattice) over the upper midwestern United States and summarized the proportion of individual land covers in each cell within the lattice. These proportions were then mapped back onto the lattice, and the resultant lattice was compared to satellite paths, state borders, and regional map classification units. We observed mapping inconsistencies at the borders between mapping regions, states, and Thematic Mapper (TM) mapping paths in the upper midwestern United States, particularly related to grass I and-herbaceous, emergent-herbaceous wetland, and small-grain land covers. We attributed these discrepancies to differences in image dates between mapping regions, suboptimal image dates for distinguishing certain land-cover types, lack of suitable ancillary data for improving discrimination for rare land covers, and possibly differences among image interpreters. To overcome these inconsistencies for the purpose of modeling regional populations of birds, we combined grassland-herbaceous and pasture-hay land-cover classes and excluded the use of emergent-herbaceous and small-grain land covers. We recommend that users of digital land-cover data conduct similar assessments for other regions before using these data for habitat evaluation. Further, caution is advised in using these data in the analysis of regional land-cover change because it is not likely that future digital land-cover maps will repeat the same problems, thus resulting in biased estimates of change.
Long-term trends in a Dimictic Lake
Robertson, Dale M.; Hsieh, Yi-Fang; Lathrop, Richard C; Wu, Chin H; Magee, Madeline; Hamilton, David P.
2016-01-01
The one-dimensional hydrodynamic ice model, DYRESM-WQ-I, was modified to simulate ice cover and thermal structure of dimictic Lake Mendota, Wisconsin, USA, over a continuous 104-year period (1911–2014). The model results were then used to examine the drivers of changes in ice cover and water temperature, focusing on the responses to shifts in air temperature, wind speed, and water clarity at multiyear timescales. Observations of the drivers include a change in the trend of warming air temperatures from 0.081 °C per decade before 1981 to 0.334 °C per decade thereafter, as well as a shift in mean wind speed from 4.44 m s−1 before 1994 to 3.74 m s−1 thereafter. Observations show that Lake Mendota has experienced significant changes in ice cover: later ice-on date(9.0 days later per century), earlier ice-off date (12.3 days per century), decreasing ice cover duration (21.3 days per century), while model simulations indicate a change in maximum ice thickness (12.7 cm decrease per century). Model simulations also show changes in the lake thermal regime of earlier stratification onset (12.3 days per century), later fall turnover (14.6 days per century), longer stratification duration (26.8 days per century), and decreasing summer hypolimnetic temperatures (−1.4 °C per century). Correlation analysis of lake variables and driving variables revealed ice cover variables, stratification onset, epilimnetic temperature, and hypolimnetic temperature were most closely correlated with air temperature, whereas freeze-over water temperature, hypolimnetic heating, and fall turnover date were more closely correlated with wind speed. Each lake variable (i.e., ice-on and ice-off dates, ice cover duration, maximum ice thickness, freeze-over water temperature, stratification onset, fall turnover date, stratification duration, epilimnion temperature, hypolimnion temperature, and hypolimnetic heating) was averaged for the three periods (1911–1980, 1981–1993, and 1994–2014) delineated by abrupt changes in air temperature and wind speed. Average summer hypolimnetic temperature and fall turnover date exhibit significant differences between the third period and the first two periods. Changes in ice cover (ice-on and ice-off dates, ice cover duration, and maximum ice thickness) exhibit an abrupt change after 1994, which was related in part to the warm El Niño winter of 1997–1998. Under-ice water temperature, freeze-over water temperature, hypolimnetic temperature, fall turnover date, and stratification duration demonstrate a significant difference in the third period (1994–2014), when air temperature was warmest and wind speeds decreased rather abruptly. The trends in ice cover and water temperature demonstrate responses to both long-term and abrupt changes in meteorological conditions that can be complemented with numerical modeling to better understand how these variables will respond in a future climate.
Exploratory analysis of environmental interactions in central California
De Cola, Lee; Falcone, Neil L.
1996-01-01
As part of its global change research program, the United States Geological Survey (USGS) has produced raster data that describe the land cover of the United States using a consistent format. The data consist of elevations, satellite measurements, computed vegetation indices, land cover classes, and ancillary political, topographic and hydrographic information. This open-file report uses some of these data to explore the environment of a (256-km)? region of central California. We present various visualizations of the data, multiscale correlations between topography and vegetation, a path analysis of more complex statistical interactions, and a map that portrays the influence of agriculture on the region's vegetation. An appendix contains C and Mathematica code used to generate the graphics and some of the analysis.
Badar, Bazigha; Romshoo, Shakil A; Khan, M A
2013-08-01
Dal Lake, a cradle of Kashmiri civilization has strong linkage with socioeconomics of the state of Jammu and Kashmir. During last few decades, anthropogenic pressures in Dal Lake Catchment have caused environmental deterioration impairing, inter-alia, sustained biotic communities and water quality. The present research was an integrated impact analysis of socioeconomic and biophysical processes at the watershed level on the current status of Dal Lake using multi-sensor and multi-temporal satellite data, simulation modelling together with field data verification. Thirteen watersheds (designated as 'W1-W13') were identified and investigated for land use/land cover change detection, quantification of erosion and sediment loads and socioeconomic analysis (total population, total households, literacy rate and economic development status). All the data for the respective watersheds was integrated into the GIS environment based upon multi-criteria analysis and knowledge-based weightage system was adopted for watershed prioritization based on its factors and after carefully observing the field situation. The land use/land cover change detection revealed significant changes with a uniform trend of decreased vegetation and increased impervious surface cover. Increased erosion and sediment loadings were recorded for the watersheds corresponding to their changing land systems, with bare and agriculture lands being the major contributors. The prioritization analysis revealed that W5 > W2 > W6 > W8 > W1 ranked highest in priority and W13 > W3 > W4 > W11 > W7 under medium priority. W12 > W9 > W10 belonged to low-priority category. The integration of the biophysical and the socioeconomic environment at the watershed level using modern geospatial tools would be of vital importance for the conservation and management strategies of Dal Lake ecosystem.
Austin, J.E.; Keough, J.R.; Pyle, W.H.
2007-01-01
Grazing and burning are commonly applied practices that can impact the diversity and biomass of wetland plant communities. We evaluated the vegetative response of wetlands and adjacent upland grasslands to four treatment regimes (continuous idle, fall prescribed burning followed by idle, annual fall cattle grazing, and rotation of summer grazing and idle) commonly used by the U.S. Fish and Wildlife Service. Our study area was Grays Lake, a large, montane wetland in southeastern Idaho that is bordered by extensive wet meadows. We identified seven plant cover types, representing the transition from dry meadow to deep wetland habitats: mixed deep marsh, spikerush slough, Baltic rush (Juncus balticus), moist meadow, alkali, mesic meadow, and dry meadow. We compared changes in community composition and total aboveground biomass of each plant cover type between 1998, when all units had been idled for three years, and 1999 (1 yr post-treatment) and 2000 (2 yr post-treatment). Analysis using non-metric multidimensional scaling indicated that compositional changes varied among cover types, treatments, and years following treatment. Treatment-related changes in community composition were greatest in mixed deep marsh, Baltic rush, and mesic meadow. In mixed deep marsh and Baltic rush, grazing and associated trampling contributed to changes in the plant community toward more open water and aquatic species and lower dominance of Baltic rush; grazing and trampling also seemed to contribute to increased cover in mesic meadow. Changing hydrological conditions, from multiple years of high water to increasing drought, was an important factor influencing community composition and may have interacted with management treatments. Biomass differed among treatments and between years within cover types. In the wettest cover types, fall burning and grazing rotation treatments had greater negative impact on biomass than the idle treatment, but in drier cover types, summer grazing stimulated biomass production. Our results illustrate the spatial and temporal complexity of the transition between dry meadow and wetland habitats, and variable interactions among plant communities, treatments, and annual wetland conditions. ?? 2007, The Society of Wetland Scientists.
Species Composition at the Sub-Meter Level in Discontinuous Permafrost in Subarctic Sweden
NASA Astrophysics Data System (ADS)
Anderson, S. M.; Palace, M. W.; Layne, M.; Varner, R. K.; Crill, P. M.
2013-12-01
Northern latitudes are experiencing rapid warming. Wetlands underlain by permafrost are particularly vulnerable to warming which results in changes in vegetative cover. Specific species have been associated with greenhouse gas emissions therefore knowledge of species compositional shift allows for the systematic change and quantification of emissions and changes in such emissions. Species composition varies on the sub-meter scale based on topography and other microsite environmental parameters. This complexity and the need to scale vegetation to the landscape level proves vital in our estimation of carbon dioxide (CO2) and methane (CH4) emissions and dynamics. Stordalen Mire (68°21'N, 18°49'E) in Abisko and is located at the edge of discontinuous permafrost zone. This provides a unique opportunity to analyze multiple vegetation communities in a close proximity. To do this, we randomly selected 25 1x1 meter plots that were representative of five major cover types: Semi-wet, wet, hummock, tall graminoid, and tall shrub. We used a quadrat with 64 sub plots and measured areal percent cover for 24 species. We collected ground based remote sensing (RS) at each plot to determine species composition using an ADC-lite (near infrared, red, green) and GoPro (red, blue, green). We normalized each image based on a Teflon white chip placed in each image. Textural analysis was conducted on each image for entropy, angular second momentum, and lacunarity. A logistic regression was developed to examine vegetation cover types and remote sensing parameters. We used a multiple linear regression using forwards stepwise variable selection. We found statistical difference in species composition and diversity indices between vegetation cover types. In addition, we were able to build regression model to significantly estimate vegetation cover type as well as percent cover for specific key vegetative species. This ground-based remote sensing allows for quick quantification of vegetation cover and species and also provides the framework for scaling to satellite image data to estimate species composition and shift on the landscape level. To determine diversity within our plots we calculated species richness and Shannon Index. We found that there were statistically different species composition within each vegetation cover type and also determined which species were indicative for cover type. Our logistical regression was able to significantly classify vegetation cover types based on RS parameters. Our multiple regression analysis indicated Betunla nana (Dwarf Birch) (r2= .48, p=<0.0001) and Sphagnum (r2=0.59, p=<0.0001) were statistically significant with respect to RS parameters. We suggest that ground based remote sensing methods may provide a unique and efficient method to quantify vegetation across the landscape in northern latitude wetlands.
Remote Sensing of Climate-Driven Range Shifts of Vegetation across North American Mountain Ranges
NASA Astrophysics Data System (ADS)
Kendrick, J. A.; Sax, D. F.; Kellner, J. R.
2015-12-01
Global climate change is driving shifts in local environmental conditions, and many organisms are projected to become poorly adapted to their current ranges. Some species may respond by gradually shifting their range limits to track environmental change. This adaptation strategy is expected to be most feasible in regions with sharp climatic gradients, such as mountain ranges. However, the extent to which this process is taking place is poorly understood, and some evidence suggests that shifts upwards in elevation might be more difficult than expected. Direct empirical evidence of range shifts in response to recent climate change could inform models and conservation strategies. Here we used Monte Carlo spectral unmixing of Landsat surface reflectance data to characterize changes in vegetation cover across major North American mountain ranges over the past 30 years. This approach allows us to observe changes in photosynthetic and nonphotosynthetic vegetation as well as absolute change in vegetation cover. We found evidence of a gradual increase in total vegetation cover at increasing elevations, but this pattern varied in its strength both within and among mountain ranges. We also observed more dramatic changes in vegetation type which differed strongly between regions with different climates. Our analysis shows that upslope range shift is a possible climate response in many cases, but that this process does not occur uniformly.
A Multitemporal, Multisensor Approach to Mapping the Canadian Boreal Forest
NASA Astrophysics Data System (ADS)
Reith, Ernest
The main anthropogenic source of CO2 emissions is the combustion of fossil fuels, while the clearing and burning of forests contribute significant amounts as well. Vegetation represents a major reservoir for terrestrial carbon stocks, and improving our ability to inventory vegetation will enhance our understanding of the impacts of land cover and climate change on carbon stocks and fluxes. These relationships may be an indication of a series of troubling biosphere-atmospheric feedback mechanisms that need to be better understood and modeled. Valuable land cover information can be provided to the global climate change modeling community using advanced remote sensing capabilities such as Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR). Individually and synergistically, data were successfully used to characterize the complex nature of the Canadian boreal forest land cover types. The multiple endmember spectral mixture analysis process was applied against seasonal AVIRIS data to produce species-level vegetated land cover maps of two study sites in the Canadian boreal forest: Old Black Spruce (OBS) and Old Jack Pine (OJP). The highest overall accuracy was assessed to be at least 66% accurate to the available reference map, providing evidence that high-quality, species-level land cover mapping of the Canadian boreal forest is achievable at accuracy levels greater than other previous research efforts in the region. Backscatter information from multichannel, polarimetric SAR utilizing a binary decision tree-based classification technique methodology was moderately successfully applied to AIRSAR to produce maps of the boreal land cover types at both sites, with overall accuracies at least 59%. A process, centered around noise whitening and principal component analysis features of the minimum noise fraction transform, was implemented to leverage synergies contained within spatially coregistered multitemporal and multisensor AVIRIS and AIRSAR data sets to successfully produce high-accuracy boreal forest land cover maps. Overall land cover map accuracies of 78% and 72% were assessed for OJP and OBS sites, respectively, for either seasonal or multitemporal data sets. High individual land cover accuracies appeared to be independent of site, season, or multisensor combination in the minimum-noise fraction-based approach.
Comprehensive data set of global land cover change for land surface model applications
NASA Astrophysics Data System (ADS)
Sterling, Shannon; Ducharne, AgnèS.
2008-09-01
To increase our understanding of how humans have altered the Earth's surface and to facilitate land surface modeling experiments aimed to elucidate the direct impact of land cover change on the Earth system, we create and analyze a database of global land use/cover change (LUCC). From a combination of sources including satellite imagery and other remote sensing, ecological modeling, and country surveys, we adapt and synthesize existing maps of potential land cover and layers of the major anthropogenic land covers, including a layer of wetland loss, that are then tailored for land surface modeling studies. Our map database shows that anthropogenic land cover totals to approximately 40% of the Earth's surface, consistent with literature estimates. Almost all (92%) of the natural grassland on the Earth has been converted to human use, mostly grazing land, and the natural temperate savanna with mixed C3/C4 is almost completely lost (˜90%), due mostly to conversion to cropland. Yet the resultant change in functioning, in terms of plant functional types, of the Earth system from land cover change is dominated by a loss of tree cover. Finally, we identify need for standardization of percent bare soil for global land covers and for a global map of tree plantations. Estimates of land cover change are inherently uncertain, and these uncertainties propagate into modeling studies of the impact of land cover change on the Earth system; to begin to address this problem, modelers need to document fully areas of land cover change used in their studies.
The use of a break-even analysis: financial analysis of a fast-track program.
Saywell, R M; Cordell, W H; Nyhuis, A W; Giles, B K; Culler, S D; Woods, J R; Chu, D K; McKinzie, J P; Rodman, G H
1995-08-01
To calculate the financial break-even point and illustrate how changes in third-party reimbursement and eligibility could affect a program's fiscal standing. Demographic, clinical, and financial data were collected retrospectively for 446 patients treated in a fast-track program during June 1993. The fast-track program is located within the confines of the emergency medicine and trauma center at a 1,050-bed tertiary care Midwestern teaching hospital and provides urgent treatment to minimally ill patients. A financial break-even analysis was performed to determine the point where the program generated enough revenue to cover its total variable and fixed costs, both direct and indirect. Given the relatively low average collection rate (62%) and high percentage of uninsured patients (31%), the analysis showed that the program's revenues covered its direct costs but not all of the indirect costs. Examining collection rates or payer class mix without examining both costs and revenues may lead to an erroneous conclusion about a program's fiscal viability. Sensitivity analysis also shows that relatively small changes in third-party coverage or eligibility (income) requirements can have a large impact on the program's financial solvency and break-even volumes.
A scale-invariant change detection method for land use/cover change research
NASA Astrophysics Data System (ADS)
Xing, Jin; Sieber, Renee; Caelli, Terrence
2018-07-01
Land Use/Cover Change (LUCC) detection relies increasingly on comparing remote sensing images with different spatial and spectral scales. Based on scale-invariant image analysis algorithms in computer vision, we propose a scale-invariant LUCC detection method to identify changes from scale heterogeneous images. This method is composed of an entropy-based spatial decomposition, two scale-invariant feature extraction methods, Maximally Stable Extremal Region (MSER) and Scale-Invariant Feature Transformation (SIFT) algorithms, a spatial regression voting method to integrate MSER and SIFT results, a Markov Random Field-based smoothing method, and a support vector machine classification method to assign LUCC labels. We test the scale invariance of our new method with a LUCC case study in Montreal, Canada, 2005-2012. We found that the scale-invariant LUCC detection method provides similar accuracy compared with the resampling-based approach but this method avoids the LUCC distortion incurred by resampling.
Modeled impact of anthropogenic land cover change on climate
Findell, K.L.; Shevliakova, E.; Milly, P.C.D.; Stouffer, R.J.
2007-01-01
Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory's climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation. ?? 2007 American Meteorological Society.
Regional assessment of trends in vegetation change dynamics using principal component analysis
NASA Astrophysics Data System (ADS)
Osunmadewa, B. A.; Csaplovics, E.; R. A., Majdaldin; Adeofun, C. O.; Aralova, D.
2016-10-01
Vegetation forms the basis for the existence of animal and human. Due to changes in climate and human perturbation, most of the natural vegetation of the world has undergone some form of transformation both in composition and structure. Increased anthropogenic activities over the last decades had pose serious threat on the natural vegetation in Nigeria, many vegetated areas are either transformed to other land use such as deforestation for agricultural purpose or completely lost due to indiscriminate removal of trees for charcoal, fuelwood and timber production. This study therefore aims at examining the rate of change in vegetation cover, the degree of change and the application of Principal Component Analysis (PCA) in the dry sub-humid region of Nigeria using Normalized Difference Vegetation Index (NDVI) data spanning from 1983-2011. The method used for the analysis is the T-mode orientation approach also known as standardized PCA, while trends are examined using ordinary least square, median trend (Theil-Sen) and monotonic trend. The result of the trend analysis shows both positive and negative trend in vegetation change dynamics over the 29 years period examined. Five components were used for the Principal Component Analysis. The results of the first component explains about 98 % of the total variance of the vegetation (NDVI) while components 2-5 have lower variance percentage (< 1%). Two ancillary land use land cover data of 2000 and 2009 from European Space Agency (ESA) were used to further explain changes observed in the Normalized Difference Vegetation Index. The result of the land use data shows changes in land use pattern which can be attributed to anthropogenic activities such as cutting of trees for charcoal production, fuelwood and agricultural practices. The result of this study shows the ability of remote sensing data for monitoring vegetation change in the dry-sub humid region of Nigeria.
Smit, Izak P J; Prins, Herbert H T
2015-01-01
With grasslands and savannas covering 20% of the world's land surface, accounting for 30-35% of worldwide Net Primary Productivity and supporting hundreds of millions of people, predicting changes in tree/grass systems is priority. Inappropriate land management and rising atmospheric CO2 levels result in increased woody cover in savannas. Although woody encroachment occurs world-wide, Africa's tourism and livestock grazing industries may be particularly vulnerable. Forecasts of responses of African wildlife and available grazing biomass to increases in woody cover are thus urgently needed. These predictions are hard to make due to non-linear responses and poorly understood feedback mechanisms between woody cover and other ecological responders, problems further amplified by the lack of long-term and large-scale datasets. We propose that a space-for-time analysis along an existing woody cover gradient overcomes some of these forecasting problems. Here we show, using an existing woody cover gradient (0-65%) across the Kruger National Park, South Africa, that increased woody cover is associated with (i) changed herbivore assemblage composition, (ii) reduced grass biomass, and (iii) reduced fire frequency. Furthermore, although increased woody cover is associated with reduced livestock production, we found indigenous herbivore biomass (excluding elephants) remains unchanged between 20-65% woody cover. This is due to a significant reorganization in the herbivore assemblage composition, mostly as a result of meso-grazers being substituted by browsers at increasing woody cover. Our results suggest that woody encroachment will have cascading consequences for Africa's grazing systems, fire regimes and iconic wildlife. These effects will pose challenges and require adaptation of livelihoods and industries dependent on conditions currently prevailing.
De Laender, F; Verschuren, D; Bindler, R; Thas, O; Janssen, C R
2012-08-21
We subjected a unique set of high-quality paleoecological data to statistical modeling to examine if the biological richness and evenness of freshwater diatom communities in the Falun area, a historical copper (Cu) mining region in central Sweden, was negatively influenced by 1000 years of metal exposure. Contrary to ecotoxicological predictions, we found no negative relation between biodiversity and the sedimentary concentrations of eight metals. Strikingly, our analysis listed metals (Co, Fe, Cu, Zn, Cd, Pb) or the fractional land cover of cultivated crops, meadow, and herbs indicating land disturbance as potentially promoting biodiversity. However, correlation between metal- and land-cover trends prevented concluding which of these two covariate types positively affected biodiversity. Because historical aqueous metal concentrations--inferred from solid-water partitioning--approached experimental toxicity thresholds for freshwater algae, positive effects of metal mining on biodiversity are unlikely. Instead, the positive relationship between biodiversity and historical land-cover change can be explained by the increasing proportion of opportunistic species when anthropogenic disturbance intensifies. Our analysis illustrates that focusing on the direct toxic effects of metals alone may yield inaccurate environmental assessments on time scales relevant for biodiversity conservation.
MODIS Vegetative Cover Conversion and Vegetation Continuous Fields
NASA Astrophysics Data System (ADS)
Carroll, Mark; Townshend, John; Hansen, Matthew; DiMiceli, Charlene; Sohlberg, Robert; Wurster, Karl
Land cover change occurs at various spatial and temporal scales. For example, large-scale mechanical removal of forests for agro-industrial activities contrasts with the small-scale clearing of subsistence farmers. Such dynamics vary in spatial extent and rate of land conversion. Such changes are attributable to both natural and anthropogenic factors. For example, lightning- or human-ignited fires burn millions of acres of land surface each year. Further, land cover conversion requires contrasting with the land cover modification. In the first instance, the dynamic represents extensive categorical change between two land cover types. Land cover modification mechanisms such as selective logging and woody encroachment depict changes within a given land cover type rather than a conversion from one land cover type to another. This chapter describes the production of two standard MODIS land products used to document changes in global land cover. The Vegetative Cover Conversion (VCC) product is designed primarily to serve as a global alarm for areas where land cover change occurs rapidly (Zhan et al. 2000). The Vegetation Continuous Fields (VCF) product is designed to continuously represent ground cover as a proportion of basic vegetation traits. Terra's launch in December 1999 afforded a new opportunity to observe the entire Earth every 1.2 days at 250-m spatial resolution. The MODIS instrument's appropriate spatial and temporal resolutions provide the opportunity to substantially improve the characterization of the land surface and changes occurring thereupon (Townshend et al. 1991).
Guerin, Greg R; Sparrow, Ben; Tokmakoff, Andrew; Smyth, Anita; Leitch, Emrys; Baruch, Zdravko; Lowe, Andrew J
2017-01-01
Australian rangelands ecosystems cover 81% of the continent but are understudied and continental-scale research has been limited in part by a lack of precise data that are standardised between jurisdictions. We present a new dataset from AusPlots Rangelands that enables integrative rangelands analysis due to its geographic scope and standardised methodology. The method provides data on vegetation and soils, enabling comparison of a suite of metrics including fractional vegetation cover, basal area, and species richness, diversity, and composition. Cover estimates are robust and repeatable, allowing comparisons among environments and detection of modest change. The 442 field plots presented here span a rainfall gradient of 129-1437 mm Mean annual precipitation with varying seasonality. Vegetation measurements include vouchered vascular plant species, growth form, basal area, height, cover and substrate type from 1010 point intercepts as well as systematically recorded absences, which are useful for predictive modelling and validation of remote sensing applications. Leaf and soil samples are sampled for downstream chemical and genomic analysis. We overview the sampling of vegetation parameters and environments, applying the data to the question of how species abundance distributions (SADs) vary over climatic gradients, a key question for the influence of environmental change on ecosystem processes. We found linear relationships between SAD shape and rainfall within grassland and shrubland communities, indicating more uneven abundance in deserts and suggesting relative abundance may shift as a consequence of climate change, resulting in altered diversity and ecosystem function. The standardised data of AusPlots enables such analyses at large spatial scales, and the testing of predictions through time with longitudinal sampling. In future, the AusPlots field program will be directed towards improving coverage of space, under-represented environments, vegetation types and fauna and, increasingly, re-sampling of established plots. Providing up-to-date data access methods to enhance re-use is also a priority.
Land Cover Change Detection using Neural Network and Grid Cells Techniques
NASA Astrophysics Data System (ADS)
Bagan, H.; Li, Z.; Tangud, T.; Yamagata, Y.
2017-12-01
In recent years, many advanced neural network methods have been applied in land cover classification, each of which has both strengths and limitations. In which, the self-organizing map (SOM) neural network method have been used to solve remote sensing data classification problems and have shown potential for efficient classification of remote sensing data. In SOM, both the distribution and the topology of features of the input layer are identified by using an unsupervised, competitive, neighborhood learning method. The high-dimensional data are then projected onto a low-dimensional map (competitive layer), usually as a two-dimensional map. The neurons (nodes) in the competitive layer are arranged by topological order in the input space. Spatio-temporal analyses of land cover change based on grid cells have demonstrated that gridded data are useful for obtaining spatial and temporal information about areas that are smaller than municipal scale and are uniform in size. Analysis based on grid cells has many advantages: grid cells all have the same size allowing for easy comparison; grids integrate easily with other scientific data; grids are stable over time and thus facilitate the modelling and analysis of very large multivariate spatial data sets. This study chose time-series MODIS and Landsat images as data sources, applied SOM neural network method to identify the land utilization in Inner Mongolia Autonomous Region of China. Then the results were integrated into grid cell to get the dynamic change maps. Land cover change using MODIS data in Inner Mongolia showed that urban area increased more than fivefold in recent 15 years, along with the growth of mining area. In terms of geographical distribution, the most obvious place of urban expansion is Ordos in southwest Inner Mongolia. The results using Landsat images from 1986 to 2014 in northeastern part of the Inner Mongolia show degradation in grassland from 1986 to 2014. Grid-cell-based spatial correlation analysis also confirmed a strong negative correlation between grassland and barren land, indicating that grassland degradation in this region is due to the urbanization and coal mining activities over the past three decades.
A decadal analysis of bioeroding sponge cover on the inshore Great Barrier Reef.
Ramsby, Blake D; Hoogenboom, Mia O; Whalan, Steve; Webster, Nicole S; Thompson, Angus
2017-06-02
Decreasing coral cover on the Great Barrier Reef (GBR) may provide opportunities for rapid growth and expansion of other taxa. The bioeroding sponges Cliona spp. are strong competitors for space and may take advantage of coral bleaching, damage, and mortality. Benthic surveys of the inshore GBR (2005-2014) revealed that the percent cover of the most abundant bioeroding sponge species, Cliona orientalis, has not increased. However, considerable variation in C. orientalis cover, and change in cover over time, was evident between survey locations. We assessed whether biotic or environmental characteristics were associated with variation in C. orientalis distribution and abundance. The proportion of fine particles in the sediments was negatively associated with the presence-absence and the percent cover of C. orientalis, indicating that the sponge requires exposed habitat. The cover of corals and other sponges explained little variation in C. orientalis cover or distribution. The fastest increases in C. orientalis cover coincided with the lowest macroalgal cover and chlorophyll a concentration, highlighting the importance of macroalgal competition and local environmental conditions for this bioeroding sponge. Given the observed distribution and habitat preferences of C. orientalis, bioeroding sponges likely represent site-specific - rather than regional - threats to corals and reef accretion.
[Cover motifs of the Tidsskrift. A 14-year cavalcade].
Nylenna, M
1998-12-10
In 1985 the Journal of the Norwegian Medical Association changed its cover policy, moving the table of contents inside the Journal and introducing cover illustrations. This article provides an analysis of all cover illustrations published over this 14-year period, 420 covers in all. There is a great variation in cover motifs and designs and a development towards more general motifs. The initial emphasis on historical and medical aspects is now less pronounced, while the use of works of art and nature motifs has increased, and the cover now more often has a direct bearing on the specific contents of the issue. Professor of medical history Oivind Larsen has photographed two thirds of the covers and contributed 95% of the inside essay-style reflections on the cover motif. Over the years, he has expanded the role of the historian of medicine disseminating knowledge to include that of the raconteur with a personal tone of voice. The Journal's covers are now one of its most characteristic features, emblematic of the Journal's ambition of standing for quality and timelessness vis-à-vis the news media, and of its aim of bridging the gap between medicine and the humanities.
Mapping snow cover using multi-source satellite data on big data platforms
NASA Astrophysics Data System (ADS)
Lhermitte, Stef
2017-04-01
Snowmelt is an important and dynamically changing water resource in mountainous regions around the world. In this framework, remote sensing data of snow cover data provides an essential input for hydrological models to model the water contribution from remote mountain areas and to understand how this water resource might alter as a result of climate change. Traditionally, however, many of these remote sensing products show a trade-off between spatial and temporal resolution (e.g., 16-day Landsat at 30m vs. daily MODIS at 500m resolution). With the advent of Sentinel-1 and 2 and the PROBA-V 100m products this trade-off can partially be tackled by having data that corresponds more closely to the spatial and temporal variations in snow cover typically observed over complex mountain areas. This study provides first a quantitative analysis of the trade-offs between the state-of-the-art snow cover mapping methodologies for Landsat, MODIS, PROBA-V, Sentinel-1 and 2 and applies them on big data platforms such as Google Earth Engine (GEE), RSS (ESA Research Service & Support) CloudToolbox, and the PROBA-V Mission Exploitation Platform (MEP). Second, it combines the different sensor data-cubes in one multi-sensor classification approach using newly developed spatio-temporal probability classifiers within the big data platform environments. Analysis of the spatio-temporal differences in derived snow cover areas from the different sensors reveals the importance of understanding the spatial and temporal scales at which variations occur. Moreover, it shows the importance of i) temporal resolution when monitoring highly dynamical properties such as snow cover and of ii) differences in satellite viewing angles over complex mountain areas. Finally, it highlights the potential and drawbacks of big data platforms for combining multi-source satellite data for monitoring dynamical processes such as snow cover.
López-Carr, David; Davis, Jason; Jankowska, Marta; Grant, Laura; López-Carr, Anna Carla; Clark, Matthew
2013-01-01
The relative role of space and place has long been debated in geography. Yet modeling efforts applied to coupled human-natural systems seemingly favor models assuming continuous spatial relationships. We examine the relative importance of placebased hierarchical versus spatial clustering influences in tropical land use/cover change (LUCC). Guatemala was chosen as our study site given its high rural population growth and deforestation in recent decades. We test predictors of 2009 forest cover and forest cover change from 2001-2009 across Guatemala's 331 municipalities and 22 departments using spatial and multi-level statistical models. Our results indicate the emergence of several socio-economic predictors of LUCC regardless of model choice. Hierarchical model results suggest that significant differences exist at the municipal and departmental levels but largely maintain the magnitude and direction of single-level model coefficient estimates. They are also intervention-relevant since policies tend to be applicable to distinct political units rather than to continuous space. Spatial models complement hierarchical approaches by indicating where and to what magnitude significant negative and positive clustering associations emerge. Appreciating the comparative advantages and limitations of spatial and nested models enhances a holistic approach to geographical analysis of tropical LUCC and human-environment interactions. PMID:24013908
Yalcin, Semra; Leroux, Shawn James
2018-04-14
Land-cover and climate change are two main drivers of changes in species ranges. Yet, the majority of studies investigating the impacts of global change on biodiversity focus on one global change driver and usually use simulations to project biodiversity responses to future conditions. We conduct an empirical test of the relative and combined effects of land-cover and climate change on species occurrence changes. Specifically, we examine whether observed local colonization and extinctions of North American birds between 1981-1985 and 2001-2005 are correlated with land-cover and climate change and whether bird life history and ecological traits explain interspecific variation in observed occurrence changes. We fit logistic regression models to test the impact of physical land-cover change, changes in net primary productivity, winter precipitation, mean summer temperature, and mean winter temperature on the probability of Ontario breeding bird local colonization and extinction. Models with climate change, land-cover change, and the combination of these two drivers were the top ranked models of local colonization for 30%, 27%, and 29% of species, respectively. Conversely, models with climate change, land-cover change, and the combination of these two drivers were the top ranked models of local extinction for 61%, 7%, and 9% of species, respectively. The quantitative impacts of land-cover and climate change variables also vary among bird species. We then fit linear regression models to test whether the variation in regional colonization and extinction rate could be explained by mean body mass, migratory strategy, and habitat preference of birds. Overall, species traits were weakly correlated with heterogeneity in species occurrence changes. We provide empirical evidence showing that land-cover change, climate change, and the combination of multiple global change drivers can differentially explain observed species local colonization and extinction. © 2018 John Wiley & Sons Ltd.
The Impact of Anthropogenic Land Cover Change on Continental River Flow
NASA Astrophysics Data System (ADS)
Sterling, S. M.; Ducharne, A.; Polcher, J.
2006-12-01
The 2003 World Water Forum highlighted a water crisis that forces over one billion people to drink contaminated water and leaves countless millions with insufficient supplies for agriculture industry. This crisis has spurred numerous recent calls for improved science and understanding of how we alter the water cycle. Here we investigate how this global water crisis is affected by human-caused land cover change. We examine the impact of the present extent of land cover change on the water cycle, in particular on evapotranspiration and streamflow, through numerical experiments with the ORCHIDEE land surface model. Using Geographic Information Systems, we characterise land cover change by assembling and modifying existing global-scale maps of land cover change. To see how the land cover change impacts river runoff streamflow, we input the maps into ORCHIDEE and run 50-year "potential vegetation" and "current land cover" simulations of the land surface and energy fluxes, forced by the 50-year NCC atmospheric forcing data set. We present global maps showing the "hotspot" areas with the largest change in ET and streamflow due to anthropogenic land cover change. The results of this project enhance scientific understanding of the nature of human impact on the global water cycle.
Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques
NASA Astrophysics Data System (ADS)
Kumar, Lalit; Ghosh, Manoj Kumer
2012-01-01
Land cover change is a significant issue for environmental managers for sustainable management. Remote sensing techniques have been shown to have a high probability of recognizing land cover patterns and change detection due to periodic coverage, data integrity, and provision of data in a broad range of the electromagnetic spectrum. We evaluate the applicability of remote sensing techniques for land cover pattern recognition, as well as land cover change detection of the Hatiya Island, Bangladesh, and quantify land cover changes from 1977 to 1999. A supervised classification approach was used to classify Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM), and Multispectral Scanner (MSS) images into eight major land cover categories. We detected major land cover changes over the 22-year study period. During this period, marshy land, mud, mud with small grass, and bare soil had decreased by 85%, 46%, 44%, and 24%, respectively, while agricultural land, medium forest, forest, and settlement had positive changes of 26%, 45%, 363%, and 59%, respectively. The primary drivers of such landscape change were erosion and accretion processes, human pressure, and the reforestation and land reclamation programs of the Bangladesh Government.
Changes among Israeli Youth Movements: A Structural Analysis Based on Kahane's Code of Informality
ERIC Educational Resources Information Center
Cohen, Erik H.
2015-01-01
Multi-dimensional data analysis tools are applied to Reuven Kahane's data on the informality of youth organizations, yielding a graphic portrayal of Kahane's code of informality. This structure helps address questions of the whether the eight structural components exhaustively cover the field without redundancy. Further, the structure is used to…
DOT National Transportation Integrated Search
2007-06-01
The Pipeline and Hazardous Materials Safety Administration (PHMSA) is proposing changes to the Federal pipeline safety regulations in 49 CFR Part 192, which cover the transportation of natural gas by pipeline. Specifically, PHMSA is proposing to chan...
Newman, Michelle G
2016-09-01
This is the introduction to the first of two special issues in honor of the 50th anniversary of the Association for Behavioral and Cognitive Therapies. The goal of this issue is to pay tribute to prior seminal Behavior Therapy publications on etiology and mechanisms of change, to provide an updated review of important topics covered by these papers, and to make recommendations for the future. Each invited paper highlights a particular Behavior Therapy publication's contribution to our understanding and also provides an updated review or meta-analysis on the topic of the original paper. The topics covered here include mechanisms of etiology such as preparedness, reinforcement, and control. In terms of papers on mechanisms of change, we cover mechanisms related to extinction including fear activation, within- and between-session extinction, safety behaviors, and variables related to imagery. In addition, we examine principles related to generalization of learning and optimizing the impact of homework. With the two special issues of Behavior Therapy, we hope to inspire additional research and discussion. Copyright © 2016. Published by Elsevier Ltd.
Controlling factors for infiltration on undisturbed hillslopes in unmanaged plantation forests
NASA Astrophysics Data System (ADS)
Hiraoka, Marino; Onda, Yuichi; Gomi, Takashi; Mizugaki, Shigeru; Nanko, Kazuki; Kato, Hiroaki
2017-04-01
Infiltration into the soil is a crucial factor for predicting overland flow generation. Infiltration capacity strongly relates to ground vegetation, soil characteristics, or both. For revealing controlling factors for infiltration capacity, we conducted in-situ rainfall simulation using an oscillating-nozzle type rainfall simulator at 26 plots with different ground cover conditions of unmanaged Japanese cypress (Chamaecyparis obtusa) plantations. For wide-ranging vegetation cover condition (0-100%), infiltration capacity widely varied (5-322 mm/h) and had positive correlations with indices of ground vegetation and ground litter (p < 0.01). For a limited vegetation cover condition (0-20%), the range of infiltration capacity (7-114 mm/h) was associated with ground litter thickness (p < 0.05), and difference in soil organic matter and difference in soil bulk density. Principal component analysis showed that the first and second principal components (70% of total variation) related to changes in above- and below-ground biomass and changes in pores in soil. Our findings showed that development of ground vegetation alters hydrological processes of surface soil through changes in soil characteristics via the propagation of belowground biomass development.
Valuation of climate-change effects on Mediterranean shrublands.
Riera, Pere; Peñuelas, Josep; Farreras, Verónica; Estiarte, Marc
2007-01-01
In general, the socioeconomic analysis of natural systems does not enter into the realms of natural science. This paper, however, estimates the human-welfare effects of possible physicochemical and biological impacts of climate change on Mediterranean shrublands over the coming 50 years. The contingent choice method was applied to elicit the trade-offs in perceived values for three climate-sensitive attributes of shrubland (plant cover, fire risk, and soil erosion) and for the costs of programs designed to mitigate changes. Soil erosion was found to be the attribute of shrubland that most concerned the population, followed by fire risk and then plant cover. An increase of 1% in the shrubland area affected by erosion was estimated to cost each person on average 2.9 euros per year in terms of lost welfare, a figure that is equivalent in terms of perceptions of social welfare to an increase of 0.24% in the shrub area burned annually and a decrease of 3.19% in the area of plant cover. These trade-off values may help ecologists, policy makers, and land managers to take social preferences into account.
The Analysis of Object-Based Change Detection in Mining Area: a Case Study with Pingshuo Coal Mine
NASA Astrophysics Data System (ADS)
Zhang, M.; Zhou, W.; Li, Y.
2017-09-01
Accurate information on mining land use and land cover change are crucial for monitoring and environmental change studies. In this paper, RapidEye Remote Sensing Image (Map 2012) and SPOT7 Remote Sensing Image (Map 2015) in Pingshuo Mining Area are selected to monitor changes combined with object-based classification and change vector analysis method, we also used R in highresolution remote sensing image for mining land classification, and found the feasibility and the flexibility of open source software. The results show that (1) the classification of reclaimed mining land has higher precision, the overall accuracy and kappa coefficient of the classification of the change region map were 86.67 % and 89.44 %. It's obvious that object-based classification and change vector analysis which has a great significance to improve the monitoring accuracy can be used to monitor mining land, especially reclaiming mining land; (2) the vegetation area changed from 46 % to 40 % accounted for the proportion of the total area from 2012 to 2015, and most of them were transformed into the arable land. The sum of arable land and vegetation area increased from 51 % to 70 %; meanwhile, build-up land has a certain degree of increase, part of the water area was transformed into arable land, but the extent of the two changes is not obvious. The result illustrated the transformation of reclaimed mining area, at the same time, there is still some land convert to mining land, and it shows the mine is still operating, mining land use and land cover are the dynamic procedure.
Forest canopy effects on snow accumulation and ablation: an integrative review of empirical results
Andres Varhola; Nicholas C. Coops; Markus Weiler; R. Dan Moore
2010-01-01
The past century has seen significant research comparing snow accumulation and ablation in forested and open sites. In this review we compile and standardize the results of previous empirical studies to generate statistical relations between changes in forest cover and the associated changes in snow accumulation and ablation rate. The analysis drew upon 33 articles...
Federal Register 2010, 2011, 2012, 2013, 2014
2010-07-26
...] Canola oil 2005 Diesel Fuel type biodiesel baseline Net Domestic Agriculture (w/o land 8 use change) Net... approach. 2. Models Used The proposed analysis EPA has prepared for canola oil biodiesel uses the same set... gallons) covers the range of production likely by 2022. We believe that this modeled change in canola oil...
Journal of Air Transportation, Volume 12, No. 2 (ATRS Special Edition)
NASA Technical Reports Server (NTRS)
Bowen, Brent D. (Editor); Kabashkin, Igor (Editor); Fink, Mary (Editor)
2007-01-01
Topics covered include: Competition and Change in the Long-Haul Markets from Europe; Insights into the Maintenance, Repair, and Overhaul Configurations of European Airlines; Validation of Fault Tree Analysis in Aviation Safety Management; An Investigation into Airline Service Quality Performance between U.S. Legacy Carriers and Their EU Competitors and Partners; and Climate Impact of Aircraft Technology and Design Changes.
Projected changes in wildlife habitats in Arctic natural areas of northwest Alaska
Bruce G. Marcot; M.Torre Jorgenson; James P. Lawler; Colleen M. Handel; Anthony R. DeGange
2015-01-01
We project the effects of transitional changes among 60 vegetation and other land cover types (Becotypes^) in northwest Alaska over the 21st century on habitats of 162 bird and 39 mammal species known or expected to occur regularly in the region. This analysis, encompassing a broad suite of arctic and boreal wildlife species, entailed building wildlifehabitat matrices...
Alternatives to estimate statewide changes in aspen cover type volumes
Curtis L. VanderSchaaf
2015-01-01
For Minnesota, the only data available to conduct regional or state-wide level assessments across all ownerships is the Forest Inventory and Analysis Program (FIA). Some of the many alternatives available to estimate regional changes in standing volume are referred to here as 1.) FIA alternative, 2.) a commonly applied growth and yield system referred to as Walters and...
NASA Astrophysics Data System (ADS)
Lief, Aram Parrish
In 2005, Hurricane Katrina's diverse impacts on the Greater New Orleans area included damaged and destroyed trees, and other despoiled vegetation, which also increased the exposure of artificial and bare surfaces, known factors that contribute to the climatic phenomenon known as the urban heat island (UHI). This is an investigation of UHI in the aftermath of Hurricane Katrina, which entails the analysis of pre and post-hurricane Katrina thermal imagery of the study area, including changes to surface heat patterns and vegetative cover. Imagery from Landsat TM was used to show changes to the pattern and intensity of the UHI effect, caused by an extreme weather event. Using remote sensing visualization methods, in situ data, and local knowledge, the author found there was a measurable change in the pattern and intensity of the New Orleans UHI effect, as well as concomitant changes to vegetative land cover. This finding may be relevant for urban planners and citizens, especially in the context of recovery from a large-scale disaster of a coastal city, regarding future weather events, and other natural and human impacts.
NASA Astrophysics Data System (ADS)
Szumińska, Danuta
2016-07-01
The main aim of the study is the analysis of changes in surface area of lake Böön Tsagaan (45°35‧N, 99°8‧E) and lake Orog (45°3‧N, 100°44‧E) taking place in the last 40 years in the context of climate conditions and permafrost degradation. The lakes, located in Central Mongolia, at the borderline of permafrost range are fed predominantly by river waters and groundwater from the surrounding mountain areas, characterized by continuous and discontinuous permafrost occurrence - mostly the Khangai. The analysis of the Böön Tsagaan and Orog lake surface area in 1974-2013 was conducted based on satellite images, whereas climate conditions were analysed using the NOAA climate data and CRU dataset. Principal Component Analysis (PCA) was used to study the relationship patterns between the climatic factors and changes in the surface area of the lakes. A tendency for a decrease in surface area, intermittent with short episodes of resupply, was observed in both studied lakes. Climate changes recorded in the analysed period had both direct and indirect impacts on water supply to lakes. Taking into account the results of PCA analysis, the most significant factors include: fluctuation of annual precipitation, increase in air temperature and thickness of snow cover. The extended duration of snow cover in the last decades of the 20th century may constitute a key factor in relation to permafrost degradation.
The impact of over 80 years of land cover changes on bee and wasp pollinator communities in England
Senapathi, Deepa; Carvalheiro, Luísa G.; Biesmeijer, Jacobus C.; Dodson, Cassie-Ann; Evans, Rebecca L.; McKerchar, Megan; Morton, R. Daniel; Moss, Ellen D.; Roberts, Stuart P. M.; Kunin, William E.; Potts, Simon G.
2015-01-01
Change in land cover is thought to be one of the key drivers of pollinator declines, and yet there is a dearth of studies exploring the relationships between historical changes in land cover and shifts in pollinator communities. Here, we explore, for the first time, land cover changes in England over more than 80 years, and relate them to concurrent shifts in bee and wasp species richness and community composition. Using historical data from 14 sites across four counties, we quantify the key land cover changes within and around these sites and estimate the changes in richness and composition of pollinators. Land cover changes within sites, as well as changes within a 1 km radius outside the sites, have significant effects on richness and composition of bee and wasp species, with changes in edge habitats between major land classes also having a key influence. Our results highlight not just the land cover changes that may be detrimental to pollinator communities, but also provide an insight into how increases in habitat diversity may benefit species diversity, and could thus help inform policy and practice for future land management. PMID:25833861
NASA Astrophysics Data System (ADS)
Tomczyk, Aleksandra; Ewertowski, Marek
2014-05-01
The importance of conserving the natural environment has been known for a long time. It can be fulfilled by designation of protected areas as well as proper management of broader landscapes. During past two decades, conservation has shifted from a predominantly species- and habitat-focus to a more holistic "ecosystem approach" with an emphasis on "ecosystem services", which underpin the benefits which society can obtain (directly or indirectly) from ecosystems. This study aims to investigate and compare existing land use prioritization models and to develop new GIS-based frameworks for analysis for different spatial scales. Research were carried out in several conservation areas in UK and Poland. Main focus was on regulating (including regulation of soil erosion and landslide susceptibility) and recreation services. A new GIS-based model was developed which enabled to analysis of this services. Different spatial scales, ranging from whole conservation areas to single catchments were chosen for mapping and quantifying. Based on different scenarios three sets of ecosystem services were calculated. Data contained specific land-cover/land-use resulting from the different strategy of the natural conservation for each of the study sites. Modelling was carried out based on the trends identified on the basis of past changes in land-use/land-cover (based on analysis of time-series satellite images), and the probability of a particular class of land-use/land-cover for the chosen scenario. Comparison between results revealed ecosystem service tradeoffs (when the obtaining of one service results in the reducing of another service) and synergies (when multiple services can be provides simultaneously). Results of the study shows where (and under which condition): (1) conservation areas can accommodate more visitors and in the same time provide regulation of soil erosion and protection against landslide developments, (2) further development of recreation services will lead to inevitable degradation of environment. Based on these results several further activities were proposed: from changing of conservation strategy for some part of the areas to changing of the land cover/land use.
Impacts of Land Cover Changes on Climate over China
NASA Astrophysics Data System (ADS)
Chen, L.; Frauenfeld, O. W.
2014-12-01
Land cover changes can influence regional climate through modifying the surface energy balance and water fluxes, and can also affect climate at large scales via changes in atmospheric general circulation. With rapid population growth and economic development, China has experienced significant land cover changes, such as deforestation, grassland degradation, and farmland expansion. In this study, the Community Earth System Model (CESM) is used to investigate the climate impacts of anthropogenic land cover changes over China. To isolate the climatic effects of land cover change, we focus on the CAM and CLM models, with prescribed climatological sea surface temperature and sea ice cover. Two experiments were performed, one with current vegetation and the other with potential vegetation. Current vegetation conditions were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observations, and potential vegetation over China was obtained from Ramankutty and Foley's global potential vegetation dataset. Impacts of land cover changes on surface air temperature and precipitation are assessed based on the difference of the two experiments. Results suggest that land cover changes have a cold-season cooling effect in a large region of China, but a warming effect in summer. These temperature changes can be reconciled with albedo forcing and evapotranspiration. Moreover, impacts on atmospheric circulation and the Asian Monsoon is also discussed.
Remote Sensing of the Environmental Impacts of Utility-Scale Solar Energy Plants
NASA Astrophysics Data System (ADS)
Edalat, Mohammad Masih
Solar energy has many environmental benefits compared with fossil fuels but solar farming can have environmental impacts especially during construction and development. Thus, in order to enhance environmental sustainability, it is imperative to understand the environmental impacts of utility-scale solar energy (USSE) plants. During recent decades, remote sensing techniques and geographic information systems have become standard techniques in environmental applications. In this study, the environmental impacts of USSE plants are investigated by analyzing changes to land surface characteristics using remote sensing. The surface characteristics studied include land cover, land surface temperature, and hydrological response whereas changes are mapped by comparing pre-, syn-, and post- construction conditions. In order to study the effects of USSE facilities on land cover, the changes in the land cover are measured and analyzed inside and around two USSE facilities. The principal component analysis (PCA), minimum noise fraction (MNF), and spectral mixture analysis (SMA) of remote sensing images are used to estimate the subpixel fraction of four land surface endmembers: high-albedo, low-albedo, shadow, and vegetation. The results revealed that USSE plants do not significantly impact land cover outside the plant boundary. However, land-cover radiative characteristics within the plant area are significantly affected after construction. During the construction phase, site preparation practices including shrub removal and land grading increase high-albedo and decrease low-albedo fractions. The thermal effects of USSE facilities are studied by the time series analysis of remote sensing land surface temperature (LST). A statistical trend analysis of LST, with seasonal trends removed is performed with a particular consideration of panel shadowing by analyzing sun angles for different times of year. The results revealed that the LST outside the boundary of the solar plant does not change, whereas it significantly decreases inside the plant at 10 AM after the construction. The decrease in LST mainly occurred in winters due to lower sun's altitude, which casts longer shadows on the ground. In order to study the hydrological impacts of PV plants, pre- and post-installation hydrological response over single-axis technology is compared. A theoretical reasoning is developed to explain flows under the influence of PV panels. Moreover, a distributed parametric hydrologic model is used to estimate runoff before and after the construction of PV plants. The results revealed that peak flow, peak flow time, and runoff volume alter after panel installation. After panel installation, peak flow decreases and is observed to shift in time, which depends on orientation. Likewise, runoff volume increases irrespective of panel orientation. The increase in the tilt angle of panel results in decrease in the peak flow, peak flow time, and runoff. This study provides an insight into the environmental impacts of USSE development using remote sensing. The research demonstrates that USSE plants are environmentally sustainable due to minimal impact on land cover and surface temperature in their vicinity. In addition, this research explains the role of rainfall shadowing on hydrological behavior at USSE plants.
Xian, George; Homer, Collin G.; Fry, Joyce
2009-01-01
The recent release of the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001, which represents the nation's land cover status based on a nominal date of 2001, is widely used as a baseline for national land cover conditions. To enable the updating of this land cover information in a consistent and continuous manner, a prototype method was developed to update land cover by an individual Landsat path and row. This method updates NLCD 2001 to a nominal date of 2006 by using both Landsat imagery and data from NLCD 2001 as the baseline. Pairs of Landsat scenes in the same season in 2001 and 2006 were acquired according to satellite paths and rows and normalized to allow calculation of change vectors between the two dates. Conservative thresholds based on Anderson Level I land cover classes were used to segregate the change vectors and determine areas of change and no-change. Once change areas had been identified, land cover classifications at the full NLCD resolution for 2006 areas of change were completed by sampling from NLCD 2001 in unchanged areas. Methods were developed and tested across five Landsat path/row study sites that contain several metropolitan areas including Seattle, Washington; San Diego, California; Sioux Falls, South Dakota; Jackson, Mississippi; and Manchester, New Hampshire. Results from the five study areas show that the vast majority of land cover change was captured and updated with overall land cover classification accuracies of 78.32%, 87.5%, 88.57%, 78.36%, and 83.33% for these areas. The method optimizes mapping efficiency and has the potential to provide users a flexible method to generate updated land cover at national and regional scales by using NLCD 2001 as the baseline.
Long-Term Vegetation Trends Detected In Northern Canada Using Landsat Image Stacks
NASA Astrophysics Data System (ADS)
Fraser, R.; Olthof, I.; Carrière, M.; Deschamps, A.; Pouliot, D.
2011-12-01
Evidence of recent productivity increases in arctic vegetation comes from a variety of sources. At local scales, long-term plot measurements in North America are beginning to record increases in vascular plant cover and biomass. At landscape scales, expansion and densification of shrubs has been observed using repeat oblique photographs. Finally, continental-scale increases in vegetation "greenness" have been documented based on analysis of coarse resolution (≥ 1 km) NOAA-AVHRR satellite imagery. In this study we investigated intermediate, regional-level changes occurring in tundra vegetation since 1984 using the Landsat TM and ETM+ satellite image archive. Four study areas averaging 13,619 km2 were located over widely distributed national parks in northern Canada (Ivvavik, Sirmilik, Torngat Mountains, and Wapusk). Time-series image stacks of 16-41 growing-season Landsat scenes from overlapping WRS-2 frames were acquired spanning periods of 17-25 years. Each pixel's unique temporal database of clear-sky values was then analyzed for trends in four indices (NDVI, Tasseled Cap Brightness, Greenness and Wetness) using robust linear regression. The trends were further related to changes in the fractional cover of functional vegetation types using regression tree models trained with plot data and high resolution (≤ 10 m) satellite imagery. We found all four study areas to have a larger proportion of significant (p<0.05) positive greenness trends (range 6.1-25.5%) by comparison to negative trends (range 0.3-4.1%). For the three study areas where regression tree models could be derived, consistent trends of increasing shrub or vascular fractional cover and decreasing bare cover were predicted. The Landsat-based observations were associated with warming trends in each park over the analysis periods. Many of the major changes observed could be corroborated using published studies or field observations.
A service relation model for web-based land cover change detection
NASA Astrophysics Data System (ADS)
Xing, Huaqiao; Chen, Jun; Wu, Hao; Zhang, Jun; Li, Songnian; Liu, Boyu
2017-10-01
Change detection with remotely sensed imagery is a critical step in land cover monitoring and updating. Although a variety of algorithms or models have been developed, none of them can be universal for all cases. The selection of appropriate algorithms and construction of processing workflows depend largely on the expertise of experts about the "algorithm-data" relations among change detection algorithms and the imagery data used. This paper presents a service relation model for land cover change detection by integrating the experts' knowledge about the "algorithm-data" relations into the web-based geo-processing. The "algorithm-data" relations are mapped into a set of web service relations with the analysis of functional and non-functional service semantics. These service relations are further classified into three different levels, i.e., interface, behavior and execution levels. A service relation model is then established using the Object and Relation Diagram (ORD) approach to represent the multi-granularity services and their relations for change detection. A set of semantic matching rules are built and used for deriving on-demand change detection service chains from the service relation model. A web-based prototype system is developed in .NET development environment, which encapsulates nine change detection and pre-processing algorithms and represents their service relations as an ORD. Three test areas from Shandong and Hebei provinces, China with different imagery conditions are selected for online change detection experiments, and the results indicate that on-demand service chains can be generated according to different users' demands.
NASA Astrophysics Data System (ADS)
Al-Hamdan, Mohammad Z.; Oduor, Phoebe; Flores, Africa I.; Kotikot, Susan M.; Mugo, Robinson; Ababu, Jaffer; Farah, Hussein
2017-10-01
In this study, we assessed land cover land use (LCLU) changes and their potential environmental drivers (i.e., precipitation, temperature) in five countries in Eastern & Southern (E&S) Africa (Rwanda, Botswana, Tanzania, Malawi and Namibia) between 2000 and 2010. Landsat-derived LCLU products developed by the Regional Centre for Mapping of Resources for Development (RCMRD) through the SERVIR (Spanish for ;to serve;) program, a joint initiative of NASA and USAID, and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to evaluate and quantify the LCLU changes in these five countries. Given that the original development of the MODIS land cover type standard products included limited training sites in Africa, we performed a two-level verification/validation of the MODIS land cover product in these five countries. Precipitation data from CHIRPS dataset were used to evaluate and quantify the precipitation changes in these countries and see if it was a significant driver behind some of these LCLU changes. MODIS Land Surface Temperature (LST) data were also used to see if temperature was a main driver too. Our validation analysis revealed that the overall accuracies of the regional MODIS LCLU product for this African region alone were lower than that of the global MODIS LCLU product overall accuracy (63-66% vs. 75%). However, for countries with uniform or homogenous land cover, the overall accuracy was much higher than the global accuracy and as high as 87% and 78% for Botswana and Namibia, respectively. In addition, the wetland and grassland classes had the highest user's accuracies in most of the countries (89%-99%), which are the ones with the highest number of MODIS land cover classification algorithm training sites. Our LCLU change analysis revealed that Botswana's most significant changes were the net reforestation, net grass loss and net wetland expansion. For Rwanda, although there have been significant forest, grass and crop expansions in some areas, there also have been significant forest, grass and crop loss in other areas that resulted in very minimal net changes. As for Tanzania, its most significant changes were the net deforestation and net crop expansion. Malawi's most significant changes were the net deforestation, net crop expansion, net grass expansion and net wetland loss. Finally, Namibia's most significant changes were the net deforestation and net grass expansion. The only noticeable environmental driver was in Malawi, which had a significant net wetland loss and could be due to the fact that it was the only country that had a reduction in total precipitation between the periods when the LCLU maps were developed. Not only that, but Malawi also happened to have a slight increase in temperature, which would cause more evaporation and net decrease in wetlands if the precipitation didn't increase as was the case in that country. In addition, within our studied countries, forestland expansion and loss as well as crop expansion and loss were happening in the same country almost equally in some cases. All of that implies that non-environmental factors, such as socioeconomics and governmental policies, could have been the main drivers of these LCLU changes in many of these countries in E&S Africa. It will be important to further study in the future the detailed effects of such drivers on these LCLU changes in this part of the world.
The CARIPANDA project: Climate change and water resources in the Adamello Natural Park of Italy
NASA Astrophysics Data System (ADS)
Bocchiola, D.
2009-04-01
The three years (2007-2009) CARIPANDA project funded by the Cariplo Foundation of Italy is aimed to evaluate scenarios for water resources in the Adamello natural Park of Italy in a window of 50 years or so (until 2050). The project is led by Ente Parco Adamello and involves Politecnico di Milano, Università Statale di Milano, Università di Brescia, and ARPA Lombardia as scientific partners, while ENEL hydropower Company of Italy joins the project as stake holder. The Adamello Natural Park is a noteworthy resource in the Italian Alps. The Adamello Group is made of several glacierized areas (c. 24 km2), of both debris covered and free ice types, including the widest Italian Glacier, named Adamello, spreading on an area of about c. 18 km2. Also the Adamello Natural Reserve, covering 217 km2 inside the Adamello Park and including the Adamello glaciers, hosts a number of high altitude safeguarded vegetal and animal species, the safety of which is a primary task of the Reserve. Project's activity involves analysis of local climate trend, field campaigns on glaciers, hydrological modelling and remote sensing of snow and ice covered areas, aimed to build a consistent model of the present hydrological conditions and of the areas. Then, properly tailored climate change projections for the area, obtained using local data driven downscaling of climate change projections from GCMs model, are used to infer the likely response to expected climate change conditions. With two years in the project now some preliminary findings can be highlighted and some preliminary trend analysis carried out. The proposed poster provides a resume of the main results of the project insofar, of interest as a benchmark for similar ongoing and foregoing projects about climate change impact on European mountainous natural areas.
Hernández-Clemente, Rocío; Cerrillo, R M Navarro; Hernández-Bermejo, J E; Royo, S Escuin; Kasimis, N A
2009-05-01
The present study offers an analysis of regeneration patterns and diversity dynamics after a wildfire, which occurred in 1993 and affected about 7000 ha in southern Spain. The aim of the work was to analyze the rule in the succession of shrub species after fire, relating it to the changes registered in the Normalized Difference Vegetation Index (NDVI). Fractional vegetation cover was recorded from permanent plots in 2000 and 2005. NDVI data related to each time were obtained from Landsat images. Both data sets, from fieldwork and remote sensing, were analyzed through statistical and quantitative analyses and then correlated. Results have permitted the description of the change in plant cover and species composition on a global and plot scale. It can be affirmed that, from the seventh to the twelfth year after the fire, the floristic composition within the burned area remained unchanged at a global level. However, on a smaller scale (plot level), the major shrub species, Ulex parviflorus, Rosmarinus officinalis, and Cistus clusii, underwent significant changes. The regeneration dynamics established by these species conditioned plant species composition and, consequently, diversity indexes such as Shannon (H) and Simpson (D). The changes recorded in the NDVI values corresponding to the surveyed plots were highly correlated with those found in the regrowth of the main species. Areas dominated by U. parviflorus in a senile phase were related to a decrease in NDVI values and an increase in the number of species. This result describes the successional dynamics; the dryness of the main colonizer shrub species is allowing the regrowth and re-establishment of other species. Within the study area, NDVI shows sensitivity to postfire plant cover changes and indirectly expresses the diversity dynamics.
Quantifying urban land cover change between 2001 and 2006 in the Gulf of Mexico region
Xian, George Z.; Homer, Collin G.; Bunde, Brett; Danielson, Patrick; Dewitz, Jon; Fry, Joyce; Pu, Ruiliang
2012-01-01
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 km2 with a growth rate of 5.8% between 2001 and 2006. Approximately 1110.1 km2 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.
Hirota, Marina; Nobre, Carlos; Oyama, Marcos Daisuke; Bustamante, Mercedes M C
2010-08-01
*We used a climate-vegetation-natural fire (CVNF) conceptual model to evaluate the sensitivity and vulnerability of forest, savanna, and the forest-savanna transition to environmental changes in tropical South America. *Initially, under current environmental conditions, CVNF model results suggested that, in the absence of fires, tropical forests would extend c. 200 km into the presently observed savanna domain. *Environmental changes were then imposed upon the model in temperature, precipitation and lightning strikes. These changes ranged from 2 to 6 degrees C warming, +10 to -20% precipitation change and 0 to 15% increase in lightning frequency, which, in aggregate form, represent expected future climatic changes in response to global warming and deforestation. *The most critical vegetation changes are projected to take place over the easternmost portions of the basin, with a widening of the forest-savanna transition. The transition width would increase from 150 to c. 300 km, with tree cover losses ranging from 20 to 85%. This means that c. 6% of the areas currently covered by forests could potentially turn into grass-dominated savanna landscapes. The mechanism driving tree cover reduction consists of the combination of less favorable climate conditions for trees and more fire activity. In addition, this sensitivity analysis predicts that the current dry shrubland vegetation of northeast Brazil could potentially turn into a bare soil landscape.
Tropical amphibians in shifting thermal landscapes under land-use and climate change.
Nowakowski, A Justin; Watling, James I; Whitfield, Steven M; Todd, Brian D; Kurz, David J; Donnelly, Maureen A
2017-02-01
Land-cover and climate change are both expected to alter species distributions and contribute to future biodiversity loss. However, the combined effects of land-cover and climate change on assemblages, especially at the landscape scale, remain understudied. Lowland tropical amphibians may be particularly susceptible to changes in land cover and climate warming because many species have narrow thermal safety margins resulting from air and body temperatures that are close to their critical thermal maxima (CT max ). We examined how changing thermal landscapes may alter the area of thermally suitable habitat (TSH) for tropical amphibians. We measured microclimates in 6 land-cover types and CT max of 16 frog species in lowland northeastern Costa Rica. We used a biophysical model to estimate core body temperatures of frogs exposed to habitat-specific microclimates while accounting for evaporative cooling and behavior. Thermally suitable habitat area was estimated as the portion of the landscape where species CT max exceeded their habitat-specific maximum body temperatures. We projected changes in TSH area 80 years into the future as a function of land-cover change only, climate change only, and combinations of land-cover and climate-change scenarios representing low and moderate rates of change. Projected decreases in TSH area ranged from 16% under low emissions and reduced forest loss to 30% under moderate emissions and business-as-usual land-cover change. Under a moderate emissions scenario (A1B), climate change alone contributed to 1.7- to 4.5-fold greater losses in TSH area than land-cover change only, suggesting that future decreases in TSH from climate change may outpace structural habitat loss. Forest-restricted species had lower mean CT max than species that occurred in altered habitats, indicating that thermal tolerances will likely shape assemblages in changing thermal landscapes. In the face of ongoing land-cover and climate change, it will be critical to consider changing thermal landscapes in strategies to conserve ectotherm species. © 2016 Society for Conservation Biology.
NASA Astrophysics Data System (ADS)
Yitayew, M.; Didan, K.; Barreto-munoz, A.
2013-12-01
The Nile Basin is one of the world's water resources hotspot that is home to over 437 million people in ten riparian countries with 54% or 238 millions live directly within the basin. The basin like all other basins of the world is facing water resources challenges exacerbated by climate change and increased demand. Nowadays any water resource management action in the basin has to assess the impacts of climate change to be able to predict future water supply and also to help in the negotiation process. Presently, there is a lack of basin wide weather networks to understand sensitivity of the vegetation cover to the impacts of climate change. Vegetation plays major economic and ecological functions in the basin and provides key services ranging from pastoralism, agricultural production, firewood, habitat and food sources for the rich wildlife, as well as a major role in the carbon cycle and climate regulation of the region. Under the threat of climate change and the incessant anthropogenic pressure the distribution and services of the region's ecosystems are projected to change The goal of this work is to assess and characterize how the basin vegetation productivity, distribution, and phenology have changed over the last 30+ years and what are the key climatic drivers of this change. This work makes use of a newly generated multi-sensor long-term land surface data set about vegetation and phenology. Vegetation indices derived from remotely sensed surface reflectance data are commonly used to characterize phenology or vegetation dynamics accurately and with enough spatial and temporal resolution to support change detection. We used more than 30 years of vegetation index and growing season data from AVHRR and MODIS sensors compiled by the Vegetation Index and Phenology laboratory (VIP LAB) at the University of Arizona. Available climate data about precipitation and temperature for the corresponding 30 years period is also used for this analysis. We looked at the changes in the vegetation index signal and to a lesser degree the change in land cover and land use over the last 30 years. Using the climate data record we looked at the drivers of this change. The sensitivity of the basin to climate change was assessed using the multi-linear regression analysis on the covariance of the change in key phenology parameters and the two climate drivers considered here. The overall response was very complex owing to the complicated climate regime and topography of the region. Vegetation response was mostly stable in high lands with a slightly decreasing trend over low and mid-elevations. Over the same period we also observed an intensification of agriculture production corresponding to an increase in percent cover and productivity. We also observed a decrease in forest cover associated with land use conversion. These changes were mostly driven by the precipitation regimes with little impact of the temperature. Climate models project an eventual decrease in precipitation and increase in temperature over the basin. Coupled with these results and observations these projected changes point to major challenges to the vegetation cover, productivity, and associated ecosystem services of the Nile basin.
Land cover change of watersheds in Southern Guam from 1973 to 2001.
Wen, Yuming; Khosrowpanah, Shahram; Heitz, Leroy
2011-08-01
Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.
A case study of carbon fluxes from land change in the southwest Brazilian Amazon
Barrett, K.; Rogan, J.; Eastman, J.R.
2009-01-01
Worldwide, land change is responsible for one-fifth of anthropogenic carbon emissions. In Brazil, three-quarters of carbon emissions originate from land change. This study represents a municipal-scale study of carbon fluxes from vegetation in Rio Branco, Brazil. Land-cover maps of pasture, forest, and secondary growth from 1993, 1996, 1999, and 2003 were produced using an unsupervised classification method (overall accuracy = 89%). Carbon fluxes from land change over the decade of imagery were estimated from transitions between land-cover categories for each time interval. This article presents new methods for estimating emissions reductions from carbon stored in the vegetation that replaces forests (e.g., pasture) and sequestration by new (>10-15 years) forests, which reduced gross emissions by 16, 15, and 22% for the period of 1993-1996, 1996-1999, and 1999-2003, respectively. The methods used in the analysis are broadly applicable and provide a comprehensive characterization of regional-scale carbon fluxes from land change.
Auch, Roger F.; Sayler, K. L.; Napton, D.E.; Taylor, Janis L.; Brooks, M.S.
2011-01-01
Land-cover and land-use change usually results from a combination of anthropogenic drivers and biophysical conditions found across multiple scales, ranging from parcel to regional levels. A group of four Level 111 ecoregions located in the U.S. northern Great Plains is used to demonstrate the similarities and differences in land change during nearly a 30-year period (1973-2000) using results from the U.S. Geological Survey's Land Cover Trends project. There were changes to major suites of land-cover; the transitions between agriculture and grassland/shrubland and the transitions among wetland, water, agriculture, and grassland/ shrubland were affected by different factors. Anthropogenic drivers affected the land-use tension (or land-use competition) between agriculture and grassland/shrubland land-covers, whereas changes between wetland and water land-covers, and their relationship to agriculture and grassland/shrubland land-covers, were mostly affected by regional weather cycles. More land-use tension between agriculture and grassland/shrubland landcovers occurred in ecoregions with greater amounts of economically marginal cropland. Land-cover change associated with weather variability occurred in ecoregions that had large concentrations of wetlands and water impoundments, such as the Missouri River reservoirs. The Northwestern Glaciated Plains ecoregion had the highest overall estimated percentage of change because it had both land-use tension between agriculture and grassland/shrubland land-covers and wetland-water changes.
NASA Astrophysics Data System (ADS)
Dhakal, S.; Ojha, S.
2017-12-01
Climate change and its impact of water resource have gained tremendous attention among scientific committee, governments and other stakeholders since last couple of decades, especially in Himalayan region. In this study, we purpose remotely sensed measurements to monitor snow cover, both spatially and temporal, and assess climate change impact on water resource. The snow cover data from MODIS satellite (2000-2010) have been used to analyze some climate change indicators. In particular, the variability in the maximum snow extent with elevations, its temporal variability (8-day, monthly, seasonal and annual), its variation trend and its relation with temperature have been analyzed. The snow products used in this study are the maximum snow extent and fractional snow covers, which come in 8-day temporal and 500m and 0.05 degree spatial resolutions, respectively. The results showed a tremendous potential of the MODIS snow product for studying the spatial and temporal variability of snow as well as the study of climate change impact in large and inaccessible regions like the Himalayas. The snow area extent (SAE) (%) time series exhibits similar patterns during seven hydrological years, even though there are some deviations in the accumulation and melt periods. The analysis showed relatively well inverse relation between the daily mean temperature and SAE during the melting period. Some important trends of snow fall are also observed. In particular, the decreasing trend in January and increasing trend in late winter and early spring may be interpreted as a signal of a possible seasonal shift. However, it requires more years of data to verify this conclusion.
U.S. landowner behavior, land use and land cover changes, and climate change mitigation.
Ralph J. Alig
2003-01-01
Landowner behavior is a major determinant of land use and land cover changes. an important consideration for policy analysts concerned with global change. Study of landowner behavior aids in designing more effective incentives for inducing land use and land cover changes to help mitigate climate change by reducing net greenhouse gas emissions. Afforestation,...
Geological and Inorganic Materials.
ERIC Educational Resources Information Center
Jackson, L. L.; And Others
1989-01-01
Presents a review focusing on techniques and their application to the analysis of geological and inorganic materials that offer significant changes to research and routine work. Covers geostandards, spectroscopy, plasmas, microbeam techniques, synchrotron X-ray methods, nuclear activation methods, chromatography, and electroanalytical methods.…
NASA Astrophysics Data System (ADS)
Hu, X.; Li, X.; Lu, L.
2017-12-01
Land use/cover change (LUCC) is an important subject in the research of global environmental change and sustainable development, while spatial simulation on land use/cover change is one of the key content of LUCC and is also difficult due to the complexity of the system. The cellular automata (CA) model had an irreplaceable role in simulating of land use/cover change process due to the powerful spatial computing power. However, the majority of current CA land use/cover models were binary-state model that could not provide more general information about the overall spatial pattern of land use/cover change. Here, a multi-state logistic-regression-based Markov cellular automata (MLRMCA) model and a multi-state artificial-neural-network-based Markov cellular automata (MANNMCA) model were developed and were used to simulate complex land use/cover evolutionary process in an arid region oasis city constrained by water resource and environmental policy change, the Zhangye city during the period of 1990-2010. The results indicated that the MANNMCA model was superior to MLRMCA model in simulated accuracy. These indicated that by combining the artificial neural network with CA could more effectively capture the complex relationships between the land use/cover change and a set of spatial variables. Although the MLRMCA model were also some advantages, the MANNMCA model was more appropriate for simulating complex land use/cover dynamics. The two proposed models were effective and reliable, and could reflect the spatial evolution of regional land use/cover changes. These have also potential implications for the impact assessment of water resources, ecological restoration, and the sustainable urban development in arid areas.
NASA Astrophysics Data System (ADS)
Lana-Renault, Noemí; Karssenberg, Derek; Latron, Jérôme; Serrano, Mā Pilar; Regüés, David; Bierkens, Marc F. P.
2010-05-01
Mediterranean mountains have been largely affected by land abandonment and subsequent vegetation recovery, with a general expansion of shrubs and forests. Such a large scale land-cover change has modified the hydrological behavior of these areas, with significant impact on runoff production. Forecasting the trend of water resources under future re-vegetation scenarios is of paramount importance in Mediterranean basins, where water management relies on runoff generated in these areas. With this purpose, a modelling experiment was designed based on the information collected in two neighbouring research catchments with a different history of land use in the central Spanish Pyrenees. One (2.84 km2) is an abandoned agricultural catchment subjected to plant colonization and at present mainly covered by shrubs. The other (0.92 km2) is a catchment covered by dense natural forest, representative of undisturbed environments. Here we present the results of the analysis of the hydrological differences between the two catchments, and a description of the approach and results of the modelling experiment. In a statistical analysis of the field data, significant differences were observed in the streamflow response of the two catchments. The forested catchment recorded fewer floods per year compared to the old agricultural catchment, and its hydrological response was characterised by a marked seasonality, with autumn and spring as the only high flow periods. Stormflow was generally higher in the old agricultural catchment, especially for low to intermediate size events; only for large events the stormflow in the forested catchment was sometimes greater. Under drier conditions, the relative differences in the stormflow between the two catchments tended to increase whereas under wet conditions they tended to be similar. The forested catchment always reacted more slowly to rainfall, with lower peakflows (generally one order of magnitude lower) and longer recession limbs. The modelling experiment aims at separating the effect of land cover from other differences (e.g. catchment area, morphology) between the two catchments. This approach allows us to make general statements on effects of land cover, required for future predictions for larger areas. In our modelling experiment, a process-based distributed hydrological model is used for the two catchments. First, we calibrate the model using data from the two catchments until a single set of parameters valid for both is found. With this set of parameters and considering a given meteorological driver (due to their proximity, it can be considered the same for both catchments), runoff at the outlet of each catchment is simulated. Land cover is then swapped between catchments and a new runoff simulation is performed for each "swapped" catchment, using the same set of parameters and the same meteorological driver. The effects of the land cover change are determined by analysing the differences between the first and the "swapped" simulations. This study is based on an analysis of the hydrological differences of two catchments with different history of land use, and a comparative modelling experiment applied to them. Following this approach, we attempt to advance our understanding of the effects of land-use/land-cover changes in catchment hydrology and, ultimately, anticipate their hydrological consequences under a future re-vegetation scenario.
NASA Astrophysics Data System (ADS)
Tyszkowski, Sebastian; Kaczmarek, Halina
2014-05-01
Changes in land cover in the catchment area are, beside climate change, some of the major factors affecting sedimentation processes in lakes. With increasing human impact, changes in land cover no longer depend primarily on climate. In relation to research on sediments of Lake Czechowskie in Pomeranian Province in North Poland, land use changes over the last 200 years were analysed, with particular reference to deforestation or afforestation. The study area was the lake catchment, which covers nearly 20 km2. The analysis was based on archival and contemporary cartographic and photogrammetric materials, georeferenced and rectified using ArcGIS software. The following materials were used: Schrötter-Engelhart, Karte von Ost-Preussen nebst Preussisch Litthauen und West-Preussen nebst dem Netzdistrict, 1:50 000, section 92, 93, 1796-1802; Map Messtishchblatt, 1:25000, sheet Czarnen, (mapping conducted in 1874), 1932; Map WIG (Military Geographical Institute - Wojskowy Instytut Geograficzny), 1:25000, sheet Osowo, (mapping conducted in 1929-31), 1933; aerial photos 1:13000, 1964, 1969; 1:25000, 1987; 1:26000, 1997; aerial ortophotomap , 1:5000, 2010. Today, over 60% of the catchment of Lake Czechowskie is covered with forests, dominated by planted Scots pine (Pinus sylvestris), while the remaining areas are used for agricultural purposes or are built up. The first cartographic materials indicate that in the late 18th c., forest covered almost 50% of the catchment surface. By the year 1870, there was a significant reduction in the forested area, as its contribution fell to 40%. Deforestation took place mainly between the main villages. In the 1920s the forest cover increased to 44%. Today, almost the entire lake is surrounded by forest and a wetland belt (at least 0.5 km wide). Deforestation in the catchment should not be attributed solely to logging because the area of Tuchola Forests (Bory Tucholskie) was repeatedly affected by natural disasters. In the 19th c. these predominantly included fires, while in the 20th c., mostly pest outbreaks were observed. Human activity in the catchment of Lake Czechowskie, shown in the cartographic materials from the late 18th and early 19th c., is also manifested by the creation of dams on the lake, which might have increased water level in the lake. The early 20th c., imaged on the map from 1933, was a period of intense change, leading to agricultural use of wetlands. They were drained by ditches, also in the Trzechowskie peatland. This study was supported by the Virtual Institute of Integrated Climate and Landscape Evolution (ICLEA) of the Helmholtz Association and the research project no. 2011/01/B/ST10/07367 Polish Ministry of Science and Higher Education
Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed
Changes in climate and land cover are among the principal variables affecting watershed hydrology.This paper uses a cell-based model to examine the hydrologic impacts of climate and land-cover changes in thesemi-arid Lower Virgin River (LVR) watershed located upstream of Lake Mead, Nevada, USA. The cell-basedmodel is developed by considering direct runoff based on the Soil Conservation Service - Curve Number (SCSCN)method and surplus runoff based on the Thornthwaite water balance theory. After calibration and validation,the model is used to predict LVR discharge under future climate and land-cover changes. The hydrologicsimulation results reveal climate change as the dominant factor and land-cover change as a secondary factor inregulating future river discharge. The combined effects of climate and land-cover changes will slightly increaseriver discharge in summer but substantially decrease discharge in winter. This impact on water resources deservesattention in climate change adaptation planning.This dataset is associated with the following publication:Chen, H., S. Tong, H. Yang, and J. Yang. Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed. Hydrological Sciences Journal. IAHS LIMITED, Oxford, UK, 60(10): 1739-1758, (2015).
NASA Astrophysics Data System (ADS)
Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero
2017-06-01
During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are no shadows on intensity images produced from the data. These are significant advantages in developing automated classification and change detection procedures.
NASA Astrophysics Data System (ADS)
Desai, A. R.; Bolstad, P. V.; Moorcroft, P. R.; Davis, K. J.
2005-12-01
The interplay between land use change, forest management and land cover variability complicates the ability to characterize regional scale (10-1000 km) exchange of carbon dioxide between the land surface and atmosphere in heterogeneous landscapes. An attempt was made to observe and model these factors and their influence on the regional carbon cycle across the upper Midwest USA. A high density of eddy-covariance carbon flux, micrometeorology, carbon dioxide mixing ratio, stand-scale biometry and canopy component flux observations have been occurring in this area as part of the Chequamegon Ecosystem-Atmosphere Study. Observations limited to sampling only dominant stands and coarse-resolution biogeochemical models limited to biome-scale parameterization neither accurately capture the variability of carbon fluxes measured by the network of eddy covariance towers nor match the regional-scale carbon flux inferred from very tall tower eddy covariance measurements and multi-site upscaling. Analysis of plot level biometric data, U.S. Forest Service Forest Inventory Analysis data and high-resolution land cover data around the tall tower revealed significant variations in vegetation type, stand age, canopy stocking and structure. Wetlands, clearcuts and recent natural disturbances occur in characteristic small non-uniformly distributed patches that aggregate to form more than 30% of the landscape. The Ecosystem Demography model, a dynamic ecosystem model that incorporates vegetation heterogeneity, canopy structure, stand age, disturbance, land use change and forest management, was parameterized with regional biometric data and meteorology, historical records of land management and high-resolution satellite land cover maps. The model will be used to examine the significance of past land use change, natural disturbance history and current forest management in explaining landscape structure and regional carbon fluxes observed in the region today.
Land cover changes in central Sonora Mexico
Diego Valdez-Zamudio; Alejandro Castellanos-Villegas; Stuart Marsh
2000-01-01
Remote sensing techniques have been demonstrated to be very effective tools to help detect, analyze, and evaluate land cover changes in natural areas of the world. Changes in land cover can generally be attributed to either natural or anthropogenic forces. Multitemporal satellite imagery and airborne videography were used to detect, analyze, and evaluate land cover...
Global land cover mapping using Earth observation satellite data: Recent progresses and challenges
NASA Astrophysics Data System (ADS)
Ban, Yifang; Gong, Peng; Giri, Chandra
2015-05-01
Land cover is an important variable for many studies involving the Earth surface, such as climate, food security, hydrology, soil erosion, atmospheric quality, conservation biology, and plant functioning. Land cover not only changes with human caused land use changes, but also changes with nature. Therefore, the state of land cover is highly dynamic. In winter snow shields underneath various other land cover types in higher latitudes. Floods may persist for a long period in a year over low land areas in the tropical and subtropical regions. Forest maybe burnt or clear cut in a few days and changes to bare land. Within several months, the coverage of crops may vary from bare land to nearly 100% crops and then back to bare land following harvest. The highly dynamic nature of land cover creates a challenge in mapping and monitoring which remains to be adequately addressed. As economic globalization continues to intensify, there is an increasing trend of land cover/land use change, environmental pollution, land degradation, biodiversity loss at the global scale, timely and reliable information on global land cover and its changes is urgently needed to mitigate the negative impact of global environment change.
Spatially explicit land-use and land-cover scenarios for the Great Plains of the United States
Sohl, Terry L.; Sleeter, Benjamin M.; Sayler, Kristi L.; Bouchard, Michelle A.; Reker, Ryan R.; Bennett, Stacie L.; Sleeter, Rachel R.; Kanengieter, Ronald L.; Zhu, Zhi-Liang
2012-01-01
The Great Plains of the United States has undergone extensive land-use and land-cover change in the past 150 years, with much of the once vast native grasslands and wetlands converted to agricultural crops, and much of the unbroken prairie now heavily grazed. Future land-use change in the region could have dramatic impacts on ecological resources and processes. A scenario-based modeling framework is needed to support the analysis of potential land-use change in an uncertain future, and to mitigate potentially negative future impacts on ecosystem processes. We developed a scenario-based modeling framework to analyze potential future land-use change in the Great Plains. A unique scenario construction process, using an integrated modeling framework, historical data, workshops, and expert knowledge, was used to develop quantitative demand for future land-use change for four IPCC scenarios at the ecoregion level. The FORE-SCE model ingested the scenario information and produced spatially explicit land-use maps for the region at relatively fine spatial and thematic resolutions. Spatial modeling of the four scenarios provided spatial patterns of land-use change consistent with underlying assumptions and processes associated with each scenario. Economically oriented scenarios were characterized by significant loss of natural land covers and expansion of agricultural and urban land uses. Environmentally oriented scenarios experienced modest declines in natural land covers to slight increases. Model results were assessed for quantity and allocation disagreement between each scenario pair. In conjunction with the U.S. Geological Survey's Biological Carbon Sequestration project, the scenario-based modeling framework used for the Great Plains is now being applied to the entire United States.
Siudek, Patrycja
2016-12-01
In the present paper, the inter-seasonal Hg variability in snow cover was examined based on multivariate statistical analysis of chemical and meteorological data. Samples of freshly fallen snow cover were collected at the semi-urban site in Poznań (central Poland), during 3-month field measurements in winter 2013. It was showed that concentrations of atmospherically deposited Hg were highly variable in snow cover, from 0.43 to 12.5 ng L -1 , with a mean value of 4.62 ng L -1 . The highest Hg concentration in snow cover coincided with local intensification of fossil fuel burning, indicating large contribution from various anthropogenic sources such as commercial and domestic heating, power generation plants, and traffic-related pollution. Moreover, the variability of Hg in collected snow samples was associated with long-range transport of pollutants, nocturnal inversion layer, low boundary layer height, and relatively low air temperature. For three snow episodes, Hg concentration in snow cover was attributed to southerly advection, suggesting significant contribution from the highly polluted region of Poland (Upper Silesia) and major European industrial hotspots. However, the peak Hg concentration was measured in samples collected during predominant N to NE advection of polluted air masses and after a relatively longer period without precipitation. Such significant contribution to the higher Hg accumulation in snow cover was associated with intensive emission from anthropogenic sources (coal combustion) and atmospheric conditions in this area. These results suggest that further measurements are needed to determine how the Hg transformation paths in snow cover change in response to longer/shorter duration of snow cover occurrence and to determine the interactions between mercury and absorbing carbonaceous aerosols in the light of climate change.
Land-use systems and resilience of tropical rain forests in the Tehuantepec Isthmus, Mexico.
García-Romero, Arturo; Oropeza-Orozco, Oralia; Galicia-Sarmiento, Leopoldo
2004-12-01
Land-cover types were analyzed for 1970, 1990 and 2000 as the bases for determining land-use systems and their influence on the resilience of tropical rain forests in the Tehuantepec Isthmus, Mexico. Deforestation (DR) and mean annual transformation rates were calculated from land-cover change data; thus, the classification of land-use change processes was determined according to their impact on resilience: a) Modification, including land-cover conservation and intensification, and b) Conversion, including disturbance and regeneration processes. Regeneration processes, from secondary vegetation under extensive use, cultivated vegetation under intensive use, and cultivated or induced vegetation under extensive use to mature or secondary vegetation, have high resilience capacity. In contrast, cattle-raising is characterized by rapid expansion, long-lasting change, and intense damages; thus, recent disturbance processes, which include the conversion to cattle-raising, provoke the downfall of the traditional agricultural system, and nullify the capacity of resilience of tropical rain forest. The land-use cover change processes reveal a) the existence of four land-use systems (forestry, extensive agriculture, extensive cattle-raising, and intensive uses) and b) a trend towards the replacement of agricultural and forestry systems by extensive cattle-raising, which was consolidated during 1990-2000 (DR of evergreen tropical rain forest = 4.6%). Only the forestry system, which is not subject to deforestation, but is affected by factors such as selective timber, extraction, firewood collection, grazing, or human-induced fire, is considered to have high resilience (2 years), compared to agriculture (2-10 years) or cattle-raising (nonresilient). It is concluded that the analysis of land-use systems is essential for understanding the implications of land-use cover dynamics on forest recovery and land degradation in tropical rain forests.
Reddy, C Sudhakar; Jha, C S; Dadhwal, V K
2013-05-01
Deforestation and fragmentation are important concerns in managing and conserving tropical forests and have global significance. In the Indian context, in the last one century, the forests have undergone significant changes due to several policies undertaken by government as well as increased population pressure. The present study has brought out spatiotemporal changes in forest cover and variation in forest type in the state of Odisha (Orissa), India, during the last 75 years period. The mapping for the period of 1924-1935, 1975, 1985, 1995 and 2010 indicates that the forest cover accounts for 81,785.6 km(2) (52.5 %), 56,661.1 km(2) (36.4 %), 51,642.3 km(2) (33.2 %), 49,773 km(2) (32 %) and 48,669.4 km(2) (31.3 %) of the study area, respectively. The study found the net forest cover decline as 40.5 % of the total forest and mean annual rate of deforestation as 0.69 % year(-1) during 1935 to 2010. There is a decline in annual rate of deforestation during 1995 to 2010 which was estimated as 0.15 %. Forest type-wise quantitative loss of forest cover reveals large scale deforestation of dry deciduous forests. The landscape analysis shows that the number of forest patches (per 1,000) are 2.463 in 1935, 10.390 in 1975, 11.899 in 1985, 12.193 in 1995 and 15.102 in 2010, which indicates high anthropogenic pressure on the forests. The mean patch size (km(2)) of forest decreased from 33.2 in 1935 to 5.5 in 1975 and reached to 3.2 by 2010. The study demonstrated that monitoring of long term forest changes, quantitative loss of forest types and landscape metrics provides critical inputs for management of forest resources.
Global Impacts of Long-Term Land Cover Changes Within China's Densely Populated Rural Regions
NASA Astrophysics Data System (ADS)
Ellis, E. C.
2006-12-01
Long-term changes in land cover are usually investigated in terms of large-scale change processes such as urban expansion, deforestation and land conversion to agriculture. Yet China's densely populated agricultural regions, which cover more than 2 million square kilometers of Monsoon Asia, have been transformed profoundly over the past fifty years by fine-scale changes in land cover caused by unprecedented changes in population, technology and social conditions. Using a regional sampling and upscaling design coupled with high-resolution landscape change measurements at five field sites, we investigated long-term changes in land cover and ecological processes, circa 1945 to 2002, within and across China's densely populated agricultural regions. As expected, the construction of buildings and roads increased impervious surface area over time, but the total net increase was surprising, being similar in magnitude to the total current extent of China's cities. Agricultural land area declined over the same period, while tree cover increased, by about 10%, driven by tree planting and regrowth around new buildings, the introduction of perennial agriculture, improved forestry, and declines in annual crop cultivation. Though changes in impervious surface areas were closely related to changes in population density, long-term changes in agricultural land and tree cover were unrelated to populated density and required explanation by more complex models with strong regional and biophysical components. Moreover, most of these changes occurred primarily at fine spatial scales (< 30 m), under the threshold for conventional global and regional land cover change measurements. Given that these changes in built structures and vegetation cover have the potential to contribute substantially to regional and global changes in biogeochemistry, hydrology, and land-atmosphere interactions, future investigations of these changes and their impacts across Monsoon Asia would benefit from models that incorporate fine-scale landscape structure and its changes over time.
NASA Astrophysics Data System (ADS)
Younger, S. E.; Jackson, C. R.
2017-12-01
In the Southeastern United States, evapotranspiration (ET) typically accounts for 60-70% of precipitation. Watershed and plot scale experiments show that evergreen forests have higher ET rates than hardwood forests and pastures. However, some plot experiments indicate that certain hardwood species have higher ET than paired evergreens. The complexity of factors influencing ET in mixed land cover watersheds makes identifying the relative influences difficult. Previous watershed scale studies have relied on regression to understand the influences or low flow analysis to indicate growing season differences among watersheds. Existing studies in the southeast investigating ET rates for watersheds with multiple forest cover types have failed to identify a significant forest type effect, but these studies acknowledge small sample sizes. Trends of decreasing streamflow have been recognized in the region and are generally attributed to five key factors, 1.) influences from multiple droughts, 2.) changes in distribution of precipitation, 3.) reforestation of agricultural land, 4.) increasing consumptive uses, or 5.) a combination of these and other factors. This study attempts to address the influence of forest type on long term average annual streamflow and on stream low flows. Long term annual ET rates were calculated as ET = P-Q for 46 USGS gaged basins with daily data for the 1982 - 2014 water years, >40% forest cover, and no large reservoirs. Land cover data was regressed against ET to describe the relationship between each of the forest types in the National Land Cover Database. Regression analysis indicates evergreen land cover has a positive relationship with ET while deciduous and total forest have a negative relationship with ET. Low flow analysis indicates low flows tend to be lower in watersheds with more evergreen cover, and that low flows increase with increasing deciduous cover, although these relationships are noisy. This work suggests considering forest cover type improves understanding of watershed scale ET at annual and seasonal levels which is consistent with historic paired watershed experiments and some plot scale data.
Aleman, Julie C; Blarquez, Olivier; Staver, Carla A
2016-09-01
Global change will likely affect savanna and forest structure and distributions, with implications for diversity within both biomes. Few studies have examined the impacts of both expected precipitation and land use changes on vegetation structure in the future, despite their likely severity. Here, we modeled tree cover in sub-Saharan Africa, as a proxy for vegetation structure and land cover change, using climatic, edaphic, and anthropic data (R(2) = 0.97). Projected tree cover for the year 2070, simulated using scenarios that include climate and land use projections, generally decreased, both in forest and savanna, although the directionality of changes varied locally. The main driver of tree cover changes was land use change; the effects of precipitation change were minor by comparison. Interestingly, carbon emissions mitigation via increasing biofuels production resulted in decreases in tree cover, more severe than scenarios with more intense precipitation change, especially within savannas. Evaluation of tree cover change against protected area extent at the WWF Ecoregion scale suggested areas of high biodiversity and ecosystem services concern. Those forests most vulnerable to large decreases in tree cover were also highly protected, potentially buffering the effects of global change. Meanwhile, savannas, especially where they immediately bordered forests (e.g. West and Central Africa), were characterized by a dearth of protected areas, making them highly vulnerable. Savanna must become an explicit policy priority in the face of climate and land use change if conservation and livelihoods are to remain viable into the next century. © 2016 John Wiley & Sons Ltd.
Consequences of land use and land cover change
Slonecker, E. Terrence; Barnes, Christopher; Karstensen, Krista; Milheim, Lesley E.; Roig-Silva, Coral M.
2013-01-01
The U.S. Geological Survey (USGS) Climate and Land Use Change Mission Area is one of seven USGS mission areas that focuses on making substantial scientific "...contributions to understanding how Earth systems interact, respond to, and cause global change". Using satellite and other remotely sensed data, USGS scientists monitor patterns of land cover change over space and time at regional, national, and global scales. These data are analyzed to understand the causes and consequences of changing land cover, such as economic impacts, effects on water quality and availability, the spread of invasive species, habitats and biodiversity, carbon fluctuations, and climate variability. USGS scientists are among the leaders in the study of land cover, which is a term that generally refers to the vegetation and artificial structures that cover the land surface. Examples of land cover include forests, grasslands, wetlands, water, crops, and buildings. Land use involves human activities that take place on the land. For example, "grass" is a land cover, whereas pasture and recreational parks are land uses that produce a cover of grass.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Treitz, P.M.; Howarth, P.J.; Gong, Peng
1992-04-01
SPOT HRV multispectral and panchromatic data were recorded and coregistered for a portion of the rural-urban fringe of Toronto, Canada. A two-stage digital analysis algorithm incorporating a spectral-class frequency-based contextual classification of eight land-cover and land-use classes resulted in an overall Kappa coefficient of 82.2 percent for training-area data and a Kappa coefficient of 70.3 percent for test-area data. A matrix-overlay analysis was then performed within the geographic information system (GIS) to combine the land-cover and land-use classes generated from the SPOT digital classification with zoning information for the area. The map that was produced has an estimated interpretation accuracymore » of 78 percent. Global Positioning System (GPS) data provided a positional reference for new road networks. These networks, in addition to the new land-cover and land-use map derived from the SPOT HRV data, provide an up-to-date synthesis of change conditions in the area. 51 refs.« less
Drummond, Mark A.; Stier, Michael P.; Coffin, Alisa W.
2015-01-01
This report summarizes baseline land-cover change information for four time intervals from between 1973 and 2000 for the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (LCC). The study used sample data from the USGS Land Cover Trends dataset to develop estimates of change for 10 land-cover classes in the LCC. The results show that an estimated 17.7 percent of the LCC land cover had a change during the 27-year period. Cyclic forest dynamics—of timber harvest and regrowth—are the most extensive types of land conversion. Agricultural land had an estimated net decline of 3.5 percent as cropland and pasture were urbanized and developed and converted to forest use. Urban and other developed land covers expanded from 2.0 percent of the LCC in 1973 to 3.1 percent in 2000. The report also highlights causes and challenges of land-cover change.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garono, Ralph; Anderson, Becci; Robinson, Rob
The Lower Columbia River Estuary Management Plan (Jerrick, 1991) recognizes the positive relationship between the conservation of fish and wildlife habitat, and sustaining their populations. An important component of fish and wildlife conservation and management is the identification of habitats, trends in habitat change, and delineation of habitat for preservation, restoration or enhancement. Alterations to the environment, such as hydropower generation, dredging, forestry, agriculture, channel alteration, diking, bank stabilization and floodplain development, have dramatically altered both the type and distribution of habitats along the Columbia River Estuary (CRE) and its floodplain. Along the Columbia River, tidally influenced habitats occur frommore » the river mouth to the Bonneville Dam, a distance of 230 km. If we are to effectively manage the natural resources of the Columbia River ecosystem, there is a need to understand how habitats have changed because fish and wildlife populations are known to respond to changes in habitat quality and distribution. The goal of this study was to measure the amount and type of change of CRE land cover from 1992 to 2000. We performed a change analysis on two spatial data sets describing land cover along the lower portion of the estuary (Fig. 1). The 1992 data set was created by the NOAA Coastal Remote Sensing, Coastal Change Analysis Program (C-CAP) in cooperation with Columbia River Estuary Study Task Force (CREST), the National Marine Fisheries Service (NMFS) Point Adams Field Station, and State of Washington Department of Natural Resources (DNR). The 2000 data set was produced by Earth Design Consultants, Inc. (EDC) and the Wetland Ecosystem Team (WET: University of Washington) as part of a larger Lower Columbia River Estuary Partnership (Estuary Partnership) habitat mapping study. Although the image classification methodologies used to create the data sets differed, both data sets were produced by classifying Landsat Thematic Mapper (TM) satellite imagery, making it feasible to assess land cover changes between 1992 and 2000.« less
NASA Technical Reports Server (NTRS)
Hollier, Andi B.; Jagge, Amy M.; Stefanov, William L.; Vanderbloemen, Lisa A.
2017-01-01
For over fifty years, NASA astronauts have taken exceptional photographs of the Earth from the unique vantage point of low Earth orbit (as well as from lunar orbit and surface of the Moon). The Crew Earth Observations (CEO) Facility is the NASA ISS payload supporting astronaut photography of the Earth surface and atmosphere. From aurora to mountain ranges, deltas, and cities, there are over two million images of the Earth's surface dating back to the Mercury missions in the early 1960s. The Gateway to Astronaut Photography of Earth website (eol.jsc.nasa.gov) provides a publically accessible platform to query and download these images at a variety of spatial resolutions and perform scientific research at no cost to the end user. As a demonstration to the science, application, and education user communities we examine astronaut photography of the Washington D.C. metropolitan area for three time steps between 1998 and 2016 using Geographic Object-Based Image Analysis (GEOBIA) to classify and quantify land cover/land use and provide a template for future change detection studies with astronaut photography.
NASA Astrophysics Data System (ADS)
Rodríguez-Carretero, María Teresa; Lorite, Ignacio J.; Ruiz-Ramos, Margarita; Dosio, Alessandro; Gómez, José A.
2013-04-01
The rainfed olive orchards in Southern Spain constitute the main socioeconomic system of the Mediterranean Spanish agriculture. These systems have an elevated level of complexity and require the accurate characterization of crop, climate and soil components for a correct management. It is common the inclusion of cover crops (usually winter cereals or natural cover) intercalated between the olive rows in order to reduce water erosion. Saving limited available water requires specific management, mowing or killing these cover crops in early spring. Thus, under the semi-arid conditions in Southern Spain the management of the cover crops in rainfed olive orchards is essential to avoid a severe impact to the olive orchards yield through depletion of soil water. In order to characterize this agricultural system, a complete water balance model has been developed, calibrated and validated for the semi-arid conditions of Southern Spain, called WABOL (Abazi et al., 2013). In this complex and fragile system, the climate change constitutes a huge threat for its sustainability, currently limited by the availability of water resources, and its forecasted reduction for Mediterranean environments in Southern Spain. The objective of this study was to simulate the impact of climate change on the different components of the water balance in these representative double cropping systems: transpiration of the olive orchard and cover crop, runoff, deep percolation and soil water content. Four climatic scenarios from the FP6 European Project ENSEMBLES were first bias corrected for temperatures and precipitation (Dosio and Paruolo, 2011; Dosio et al., 2012) and, subsequently, used as inputs for the WABOL model for five olive orchard fields located in Southern Spain under different conditions of crop, climate, soils and management, in order to consider as much as possible of the variability detected in the Spanish olive orchards. The first results indicate the significant effect of the cover crop on the transpiration of the olive orchard, indicating that a correct water and soil management is crucial for these systems especially under climate change conditions. Thus, a significant reduction of transpiration was detected when the cover crops were implanted. When the climatic conditions were more limited (reductions of around 21% for the annual precipitation and increases around 13% for reference evapotranspiration), the impact on olive orchards were critical, affecting seriously the profitability of the olive orchards. In this context, cover crops can be considered as part of adaptation strategies. Further studies will be required for the determination of optimal species and varieties to be used as cover crops to reduce the impact of climate change on olive orchards under semi-arid conditions. References Abazi U, Lorite IJ, Cárceles B, Martínez-Raya A, Durán VH, Francia JR, Gómez JA (2013) WABOL: A conceptual water balance model for analyzing rainfall water use in olive orchards under different soil and cover crop Management strategies. Computers and Electronics in Agriculture 91:35-48 Dosio A, Paruolo P (2011) Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate. Journal of Geophysical Research, V 116, D16106, doi:10.1029/2011JD015934 Dosio A, Paruolo P, Rojas R (2012) Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models: Analysis of the climate change signal. Journal of Geophysical Research, V 117, D17, doi: 10.1029/2012JD017968
Optimization of composite sandwich cover panels subjected to compressive loadings
NASA Technical Reports Server (NTRS)
Cruz, Juan R.
1991-01-01
An analysis and design method is presented for the design of composite sandwich cover panels that include the transverse shear effects and damage tolerance considerations. This method is incorporated into a sandwich optimization computer program entitled SANDOP. As a demonstration of its capabilities, SANDOP is used in the present study to design optimized composite sandwich cover panels for for transport aircraft wing applications. The results of this design study indicate that optimized composite sandwich cover panels have approximately the same structural efficiency as stiffened composite cover panels designed to satisfy individual constraints. The results also indicate that inplane stiffness requirements have a large effect on the weight of these composite sandwich cover panels at higher load levels. Increasing the maximum allowable strain and the upper percentage limit of the 0 degree and +/- 45 degree plies can yield significant weight savings. The results show that the structural efficiency of these optimized composite sandwich cover panels is relatively insensitive to changes in core density. Thus, core density should be chosen by criteria other than minimum weight (e.g., damage tolerance, ease of manufacture, etc.).
Brown, Kerry A.; Parks, Katherine E.; Bethell, Colin A.; Johnson, Steig E.; Mulligan, Mark
2015-01-01
Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future. PMID:25856241
Brown, Kerry A; Parks, Katherine E; Bethell, Colin A; Johnson, Steig E; Mulligan, Mark
2015-01-01
Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.
The effects of climate change on harp seals (Pagophilus groenlandicus).
Johnston, David W; Bowers, Matthew T; Friedlaender, Ari S; Lavigne, David M
2012-01-01
Harp seals (Pagophilus groenlandicus) have evolved life history strategies to exploit seasonal sea ice as a breeding platform. As such, individuals are prepared to deal with fluctuations in the quantity and quality of ice in their breeding areas. It remains unclear, however, how shifts in climate may affect seal populations. The present study assesses the effects of climate change on harp seals through three linked analyses. First, we tested the effects of short-term climate variability on young-of-the year harp seal mortality using a linear regression of sea ice cover in the Gulf of St. Lawrence against stranding rates of dead harp seals in the region during 1992 to 2010. A similar regression of stranding rates and North Atlantic Oscillation (NAO) index values was also conducted. These analyses revealed negative correlations between both ice cover and NAO conditions and seal mortality, indicating that lighter ice cover and lower NAO values result in higher mortality. A retrospective cross-correlation analysis of NAO conditions and sea ice cover from 1978 to 2011 revealed that NAO-related changes in sea ice may have contributed to the depletion of seals on the east coast of Canada during 1950 to 1972, and to their recovery during 1973 to 2000. This historical retrospective also reveals opposite links between neonatal mortality in harp seals in the Northeast Atlantic and NAO phase. Finally, an assessment of the long-term trends in sea ice cover in the breeding regions of harp seals across the entire North Atlantic during 1979 through 2011 using multiple linear regression models and mixed effects linear regression models revealed that sea ice cover in all harp seal breeding regions has been declining by as much as 6 percent per decade over the time series of available satellite data.
The Effects of Climate Change on Harp Seals (Pagophilus groenlandicus)
Johnston, David W.; Bowers, Matthew T.; Friedlaender, Ari S.; Lavigne, David M.
2012-01-01
Harp seals (Pagophilus groenlandicus) have evolved life history strategies to exploit seasonal sea ice as a breeding platform. As such, individuals are prepared to deal with fluctuations in the quantity and quality of ice in their breeding areas. It remains unclear, however, how shifts in climate may affect seal populations. The present study assesses the effects of climate change on harp seals through three linked analyses. First, we tested the effects of short-term climate variability on young-of-the year harp seal mortality using a linear regression of sea ice cover in the Gulf of St. Lawrence against stranding rates of dead harp seals in the region during 1992 to 2010. A similar regression of stranding rates and North Atlantic Oscillation (NAO) index values was also conducted. These analyses revealed negative correlations between both ice cover and NAO conditions and seal mortality, indicating that lighter ice cover and lower NAO values result in higher mortality. A retrospective cross-correlation analysis of NAO conditions and sea ice cover from 1978 to 2011 revealed that NAO-related changes in sea ice may have contributed to the depletion of seals on the east coast of Canada during 1950 to 1972, and to their recovery during 1973 to 2000. This historical retrospective also reveals opposite links between neonatal mortality in harp seals in the Northeast Atlantic and NAO phase. Finally, an assessment of the long-term trends in sea ice cover in the breeding regions of harp seals across the entire North Atlantic during 1979 through 2011 using multiple linear regression models and mixed effects linear regression models revealed that sea ice cover in all harp seal breeding regions has been declining by as much as 6 percent per decade over the time series of available satellite data. PMID:22238591
Development of a Landforms Model for Puerto Rico and its Application for Land Cover Change Analysis
Sebastian Martinuzzi; William A. Gould; Olga M. Ramos Gonzalez; Brook E. Edwards
2007-01-01
Comprehensive analysis of land morphology is essential to supporting a wide range environmental studies. We developed a landforms model that identifies eleven landform units for Puerto Rico based on parameters of land position and slope. The model is capable of extracting operational information in a simple way and is adaptable to different environments and objectives...
ERIC Educational Resources Information Center
Naveh, Nissan
2008-01-01
The Israeli high school sociology curriculum underwent changes during the 1980s and 1990s, the main one of which was the replacing of the 1988 academic-oriented curriculum with the "new" (1998) pedagogical-didactic curriculum. An analysis of the two reveals issues regarding the content of the two curricula. The article covers nine issues…
Long-term impacts of land cover changes on stream channel loss
Land cover change and stream channel loss are two related global environmental changes that are expanding and intensifying. Here, we examine how different types and transitions of land cover change impact stream channel loss across a large urbanizing watershed with large areas of...
Shi, Hua; Rigge, Matthew B.; Homer, Collin G.; Xian, George Z.; Meyer, Debbie; Bunde, Brett
2017-01-01
Understanding the causes and consequences of component change in sagebrush steppe is crucial for evaluating ecosystem sustainability. The sagebrush (Artemisia spp.) steppe ecosystem of the northwest USA has been impacted by the invasion of exotic grasses, increasing fire return intervals, changing land management practices, and fragmentation, often lowering the overall resilience to change. We utilized contemporary and historical Landsat imagery, field data, and regression tree models to produce fractional cover maps of rangeland components (shrub, sagebrush, herbaceous, bare ground, and litter) through the last 30 years. Our main goals were to (1) investigate rangeland component trends over 30 years, (2) evaluate the magnitude and direction of trends in components and climate drivers and their relationship, and (3) assess component trends influenced by climate. Results indicated that over the study period, shrub, sage, herbaceous, and litter cover decreased, while bare ground cover increased. Measured rates of change ranged from − 0.14% decade−1 for shrub cover to 0.05% decade−1 for bare ground, whereas herbaceous and litter cover trends were negligible. Net landscape cover changes were consistent with expectations of climate change and disturbance producing a loss of biotic cover, and converting a portion of shrub and sagebrush to herbaceous cover. Overall, fire and related successional recovery was the greatest change agent for all components in terms of area and cover change, while increasing minimum temperature, at a rate of 0.66°C decade−1, was found to be the most significant climate driver.
NASA Astrophysics Data System (ADS)
Mugo, R. M.; Limaye, A. S.; Nyaga, J. W.; Farah, H.; Wahome, A.; Flores, A.
2016-12-01
The water quality of inland lakes is largely influenced by land use and land cover changes within the lake's catchment. In Africa, some of the major land use changes are driven by a number of factors, which include urbanization, intensification of agricultural practices, unsustainable farm management practices, deforestation, land fragmentation and degradation. Often, the impacts of these factors are observable on changes in the land cover, and eventually in the hydrological systems. When the natural vegetation cover is reduced or changed, the surface water flow patterns, water and nutrient retention capacities are also changed. This can lead to high nutrient inputs into lakes, leading to eutrophication, siltation and infestation of floating aquatic vegetation. To assess the relationship between land use and land cover changes in part of the Lake Victoria Basin, a series of land cover maps were derived from Landsat imagery. Changes in land cover were identified through change maps and statistics. Further, the surface water chlorophyll-a concentration and turbidity were derived from MODIS-Aqua data for Lake Victoria. Chlrophyll-a and turbidity are good proxy indicators of nutrient inputs and siltation respectively. The trends in chlorophyll-a and turbidity concentrations were analyzed and compared to the land cover changes over time. Certain land cover changes related to agriculture and urban development were clearly identifiable. While these changes might not be solely responsible for variability in chlrophyll-a and turbidity concentrations in the lake, they are potentially contributing factors to this problem. This work illustrates the importance of addressing watershed degradation while seeking to solve water quality related problems.
RMP Guidance for Warehouses - Chapter 9: Risk Management Plan
Submit one RMP, including offsite consequence analysis, for all of your covered processes using the web-based RMP*eSubmit. Your RMP is then stored on EPA's Central Data Exchange (CDX) where you can access it and make changes or corrections.
Effect of land cover change on snow free surface albedo across the continental United States
Land cover changes (e.g., forest to grassland) affect albedo, and changes in albedo can influence radiative forcing (warming, cooling). We empirically tested albedo response to land cover change for 130 locations across the continental United States using high resolution (30 m-&t...
The National Land Cover Database (NLCD) provides nationwide data on land cover and land cover change at the native 30-m spatial resolution of the Landsat Thematic Mapper (TM). The database is designed to provide five-year cyclical updating of United States land cover and associat...
Influence of urbanization-driven land use/cover change on climate: The case of Addis Ababa, Ethiopia
NASA Astrophysics Data System (ADS)
Arsiso, Bisrat Kifle; Mengistu Tsidu, Gizaw; Stoffberg, Gerrit Hendrik; Tadesse, Tsegaye
2018-06-01
Land use change is the second most important anthropogenic influence on climate beside the emission of greenhouse gases. Urbanization is leading to significant land use changes in Africa since the continent is undergoing rapid urbanization and population growth in recent decades. Addis Ababa is one of these fast growing cities in the continent. Therefore, detection of land use change is very important to identify its impact on climate and sustainable land use management of the city. The study used Landsat images to generate land use/land cover change map for the city. The normalized difference vegetation index (NDVI) is used to detect the major changes of vegetation cover occurred between 1986 and 2011 as a result of land use and land cover change. Downscaled HadCM3 simulations under A2 and B2 emission scenarios is used to investigate future urban heat island (UHI) over the city of Addis Ababa. In the city, the analysis of Landsat images has shown that the built-up areas have increased by 121.88 km2 within the last 25 years. This finding is consistent with NDVI images taken over the same period that reveal a decline in vegetation cover. The impact of the urbanization-driven land use/cover change has resulted in notable nocturnal urban heat island (UHI) as revealed from an average increase in minimum temperature of 1.5 °C at the centre of the city relative to rural site over the 1960-2001 period. The mean of the 2006-2010 spatial minimum temperature anomaly with respect to the base period mean of 1981-2005 is consistent with the observed UHI. The temperature in the central areas (both commercial and residential sectors) of Addis Ababa is warmer than the surrounding areas. The thermal gradient increase from about 1.44 °C at the centre (Arada, Addis Ketema, Lideta and Kirkos) to 0.21 °C at the peripheral parts of the city (Gulele, Bole, Nefasilk-Lafto, Kolfe Keranio and east of Yeka sub-cities) transecting across the hot (high-density urban) to moderately warm to cool (non-built-up) areas. However, the maximum temperature and rainfall exhibit variability that follows topographic differences. Future urban climate change projections of urban heat island formation under A2 and B2 emission scenarios show that the nocturnal UHI will be intense in winter or dry season episodes in the city. The highest urban warming is from October to December (2.5 °C to 3.2 °C) during 2050s and 2080s.
Physical and Radiative Characteristic and Long-term Variability of the Okhotsk Sea Ice Cover
NASA Technical Reports Server (NTRS)
Nishio, Fumihiko; Comiso, Josefino C.; Gersten, Robert; Nakayama, Masashige; Ukita, Jinro; Gasiewski, Al; Stanko, Boba; Naoki, Kazuhiro
2008-01-01
Much of what we know about the large scale characteristics of the Okhotsk Sea ice cover has been provided by ice concentration maps derived from passive microwave data. To understand what satellite data represent in a highly divergent and rapidly changing environment like the Okhotsk Sea, we take advantage of concurrent satellite, aircraft, and ship data acquired on 7 February and characterized the sea ice cover at different scales from meters to hundreds of kilometers. Through comparative analysis of surface features using co-registered data from visible, infrared and microwave channels we evaluated the general radiative and physical characteristics of the ice cover as well as quantify the distribution of different ice types in the region. Ice concentration maps from AMSR-E using the standard sets of channels, and also only the 89 GHz channel for optimal resolution, are compared with aircraft and high resolution visible data and while the standard set provides consistent results, the 89 GHz provides the means to observe mesoscale patterns and some unique features of the ice cover. Analysis of MODIS data reveals that thick ice types represents about 37% of the ice cover indicating that young and new ice types represent a large fraction of the ice cover that averages about 90% ice concentration according to passive microwave data. These results are used to interpret historical data that indicate that the Okhotsk Sea ice extent and area are declining at a rapid rate of about -9% and -12 % per decade, respectively.
Satellite assessment of increasing tree cover 1982-2016
NASA Astrophysics Data System (ADS)
Song, X. P.; Hansen, M.
2017-12-01
The Earth's vegetation has undergone dramatic changes as we enter the Anthropocene. Recent studies have quantified global forest cover dynamics and resulting biogeochemical and biophysical impacts to the climate for the post-2000 time period. However, long-term gradual changes in undisturbed forests are less well quantified. We mapped annual tree cover using satellite data and quantified tree cover change during 1982-2016. The dataset was produced by combining optical observations from multiple satellite sensors, including the Advanced Very High Resolution Radiometer, the Moderate Resolution Imaging Spectroradiometer, the Landsat Enhanced Thematic Mapper Plus and various very high spatial resolution sensors. Contrary to current understanding of forest area change, global tree cover increased by 7%. The overall net gain in tree cover is a result of net loss in the tropics overweighed by net gain in the subtropical, temperate and boreal zones. All mountain systems, regardless of climate domain, experienced increases in tree cover. Regional patterns of tree cover gain including eastern United States, eastern Europe and southern China, indicate profound influences of socioeconomic, political or land management changes in shaping long-term environmental change. Results provide the first comprehensive record of global tree cover dynamics over the past four decades and may be used to reduce uncertainties in the quantification of the global carbon cycle.
NASA Astrophysics Data System (ADS)
Helene, G.; Lara, M. J.; McGuire, A. D.; Euskirchen, E. S.; Bolton, W. R.; Romanovsky, V. E.
2017-12-01
Our capacity to project future ecosystem trajectories in northern permafrost regions depends on our ability to characterize complex interactions between climatic and ecological processes at play in the soil, the vegetation, and the atmosphere. We present a study that uses remote sensing analyses, field observations, and data synthesis to inform models for the prediction of ecosystem responses to climate change in the boreal zone of Alaska. Recent warming, altered precipitation and fire regimes are driving permafrost degradation, threatening to mobilize vast reservoirs of ancient carbon previously protected from decomposition. Although large scale, progressive, top-down permafrost thaw have been well studied and represented in high-latitude ecosystem models, the consequences of abrupt and local thermokarst disturbances (TK) are less well understood. To fill this gap, we conducted a detection analysis characterizing 60 years of land cover change in the Tanana Flats, a wetland complex subjected to TK disturbance in Interior Alaska, using aerial and satellite images. We observed a nonlinear loss of permafrost plateau forest associated with TK and driven by precipitation and forest fragmentation. The results of this analysis were integrated into the Alaska Thermokarst Model (ATM), a state-and-transition model that simulates land cover change associated with TK disturbance. Thermokarst-related land cover change was simulated from 2000 to 2100 across the Tanana Flats. By 2100, the model predicts a mean decrease of 7.4% (sd 1.8%) in permafrost plateau forests associated with an increase in TK fens and bogs. Transitions from permafrost plateau forests to TK wetlands are accompanied with changes in physical and biogeochemical processes affecting ecosystem carbon balance. We evaluated the consequences of TK disturbances on the regional carbon balance by coupling outputs from the ATM and from a process-based biogeochemical model. We used long-term field observations of vegetation and soil physical and biogeochemical attributes to develop new parameterizations for TK wetlands and permafrost plateau forest land cover types. Preliminary simulations from 2000 to 2100 estimate that the conversion of permafrost plateau forest to young TK wetlands would result in a 7.5% (sd 3.5%) decrease in Net Ecosystem Exchange.
Habitat Evaluation Procedures (HEP) Report Wanaket Wildlife Area, Techical Report 2005-2006.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ashley, Paul
2006-02-01
The Regional HEP Team (RHT) and Confederated Tribes of the Umatilla Indian Reservation (CTUIR) Wildlife Program staff conducted a follow-up habitat evaluation procedures (HEP) analysis on the Wanaket Wildlife Management Area in June 2005. The 2005 HEP investigation generated 3,084.48 habitat units (HUs) for a net increase of 752.18 HUs above 1990/1995 baseline survey results. The HU to acre ratio also increased from 0.84:1.0 to 1.16:1.0. The largest increase in habitat units occurred in the shrubsteppe/grassland cover type (California quail and western meadowlark models), which increased from 1,544 HUs to 2,777 HUs (+43%), while agriculture cover type HUs were eliminatedmore » because agricultural lands (managed pasture) were converted to shrubsteppe/grassland. In addition to the agriculture cover type, major changes in habitat structure occurred in the shrubsteppe/grassland cover type due to the 2001 wildfire which removed the shrub component from well over 95% of its former range. The number of acres of all other cover types remained relatively stable; however, habitat quality improved in the riparian herb and riparian shrub cover types. The number and type of HEP species models used during the 2005 HEP analysis were identical to those used in the 1990/1995 baseline HEP surveys. The number of species models employed to evaluate the shrubsteppe/grassland, sand/gravel/mud/cobble, and riparian herb cover types, however, were fewer than reported in the McNary Dam Loss Assessment (Rassmussen and Wright 1989) for the same cover types.« less
NASA Astrophysics Data System (ADS)
Dennison, P. E.; Kokaly, R. F.; Daughtry, C. S. T.; Roberts, D. A.; Thompson, D. R.; Chambers, J. Q.; Nagler, P. L.; Okin, G. S.; Scarth, P.
2016-12-01
Terrestrial vegetation is dynamic, expressing seasonal, annual, and long-term changes in response to climate and disturbance. Phenology and disturbance (e.g. drought, insect attack, and wildfire) can result in a transition from photosynthesizing "green" vegetation to non-photosynthetic vegetation (NPV). NPV cover can include dead and senescent vegetation, plant litter, agricultural residues, and non-photosynthesizing stem tissue. NPV cover is poorly captured by conventional remote sensing vegetation indices, but it is readily separable from substrate cover based on spectral absorption features in the shortwave infrared. We will present past research motivating the need for global NPV measurements, establishing that mapping seasonal NPV cover is critical for improving our understanding of ecosystem function and carbon dynamics. We will also present new research that helps determine a best achievable accuracy for NPV cover estimation. To test the sensitivity of different NPV cover estimation methods, we simulated satellite imaging spectrometer data using field spectra collected over mixtures of NPV, green vegetation, and soil substrate. We incorporated atmospheric transmittance and modeled sensor noise to create simulated spectra with spectral resolutions ranging from 10 to 30 nm. We applied multiple methods of NPV estimation to the simulated spectra, including spectral indices, spectral feature analysis, multiple endmember spectral mixture analysis, and partial least squares regression, and compared the accuracy and bias of each method. These results prescribe sensor characteristics for an imaging spectrometer mission with NPV measurement capabilities, as well as a "Quantified Earth Science Objective" for global measurement of NPV cover. Copyright 2016, all rights reserved.
Seasonal snow cover regime and historical change in Central Asia from 1986 to 2008
NASA Astrophysics Data System (ADS)
Zhou, Hang; Aizen, Elena; Aizen, Vladimir
2017-01-01
A series of statistics describing seasonal Snow Cover Extent and timing in Central Asia (CA) have been derived from AVHRR satellite images for the time period from 1986 to 2008. Analysis of long term mean snow cover statistics shows that the area weighted mean of long term Snow Covering Days (SCD) for the whole CA is 95.2 ± 65.7 days. High elevation mountainous areas above 3000 m in Altai, Tien Shan and Pamir, which account for about 2.8% of total area in CA, have SCD > 240 days. Deserts (Karakorum Desert, Taklamakan Desert, Kumtag Desert) and rain shadow areas of major mountains, accounting for 27.0% of total area in CA, have SCD in the range of 0-30 days. Factors affecting snow cover distribution have been analyzed using simple linear regression and segmented regression. For plain regions and windward regions, the SCD rate is + 5.9 days/100 m, while for leeward regions, the rate jumps from + 0.7 days/100 m to + 10.0 days/100 m at about 2335 m. Latitude affects the SCD, especially in plain regions with insignificant change of elevation, with rates of 9-10 days/degree from south to north. The Mann-Kendal test and the Theil-Sen regression methods have been applied to analyze the spatial heterogeneous trends of change of SCD, Snow Cover Onset Date (SCOD), and Snow Cover Melt Date (SCMD). Area weighed mean SCD in the whole CA does not exhibit significant trend of change from 1986 to 2008. Increase of SCD was observed in the northeastern Kazakh Steppe. Low elevation areas below 2000 m in Central Tien Shan and Eastern Tien Shan, as well as mid-elevation areas from 1000 m to 3000 m in Western Tien Shan, Pamiro-Alai and Western Pamir, also experienced increase of SCD, associated with both earlier SCOD and later SCMD. Decrease of SCD was observed in mountainous areas of Altai, Tien Shan and Pamir, and vast areas in plains surrounding the Aral Sea.
The Use of Cover Crops as Climate-Smart Management in Midwest Cropping Systems
NASA Astrophysics Data System (ADS)
Basche, A.; Miguez, F.; Archontoulis, S.; Kaspar, T.
2014-12-01
The observed trends in the Midwestern United States of increasing rainfall variability will likely continue into the future. Events such as individual days of heavy rain as well as seasons of floods and droughts have large impacts on agricultural productivity and the natural resource base that underpins it. Such events lead to increased soil erosion, decreased water quality and reduced corn and soybean yields. Winter cover crops offer the potential to buffer many of these impacts because they essentially double the time for a living plant to protect and improve the soil. However, at present, cover crops are infrequently utilized in the Midwest (representing 1-2% of row cropped land cover) in particular due to producer concerns over higher costs and management, limited time and winter growing conditions as well as the potential harm to corn yields. In order to expand their use, there is a need to quantify how cover crops impact Midwest cropping systems in the long term and namely to understand how to optimize the benefits of cover crops while minimizing their impacts on cash crops. We are working with APSIM, a cropping systems platform, to specifically quantify the long term future impacts of cover crop incorporation in corn-based cropping systems. In general, our regional analysis showed only minor changes to corn and soybean yields (<1% differences) when a cover crop was or was not included in the simulation. Further, a "bad spring" scenario (where every third year had an abnormally wet/cold spring and cover crop termination and planting cash crop were within one day) did not result in any major changes to cash crop yields. Through simulations we estimate an average increase of 4-9% organic matter improvement in the topsoil and an average decrease in soil erosion of 14-32% depending on cover crop planting date and growth. Our work is part of the Climate and Corn-based Cropping Systems Coordinated Agriculture Project (CSCAP), a collaboration of eleven Midwestern institutions established to evaluate how conservation practices, including cover crops, improve the resilience of Midwest agriculture to future change. Such collaborations can help better quantify long term impacts of conservation practices on the landscape that ultimately lead to more climate-smart management of such agricultural systems.
Lee, Tae Hoon; Jang, Bong Seok; Jung, Min Kyo; Pack, Chan Gi; Choi, Jun-Ho; Park, Do Hyun
2016-01-01
To reduce tissue or tumor ingrowth, covered self-expandable metal stents (SEMSs) have been developed. The effectiveness of covered SEMSs may be attenuated by sludge or stone formation or by stent clogging due to the formation of biofilm on the covering membrane. In this study, we tested the hypothesis that a silicone membrane containing silver particles (Ag-P) would prevent sludge and biofilm formation on the covered SEMS. In vitro, the Ag-P-integrated silicone polymer-covered membrane exhibited sustained antibacterial activity, and there was no definite release of silver ions from the Ag-P-integrated silicone polymer membrane at any time point. Using a porcine stent model, in vivo analysis demonstrated that the Ag-P-integrated silicone polymer-covered SEMS reduced the thickness of the biofilm and the quantity of sludge formed, compared with a conventional silicone-covered SEMS. In vivo, the release of silver ions from an Ag-P-integrated silicone polymer-covered SEMS was not detected in porcine serum. The Ag-P-integrated silicone polymer-covered SEMS also resulted in significantly less stent-related bile duct and subepithelium tissue inflammation than a conventional silicone polymer-covered SEMS. Therefore, the Ag-P-integrated silicone polymer-covered SEMS reduced sludge and biofilm formation and stent-induced pathological changes in tissue. This novel SEMS may prolong the stent patency in clinical application. PMID:27739486
Lee, Tae Hoon; Jang, Bong Seok; Jung, Min Kyo; Pack, Chan Gi; Choi, Jun-Ho; Park, Do Hyun
2016-10-14
To reduce tissue or tumor ingrowth, covered self-expandable metal stents (SEMSs) have been developed. The effectiveness of covered SEMSs may be attenuated by sludge or stone formation or by stent clogging due to the formation of biofilm on the covering membrane. In this study, we tested the hypothesis that a silicone membrane containing silver particles (Ag-P) would prevent sludge and biofilm formation on the covered SEMS. In vitro, the Ag-P-integrated silicone polymer-covered membrane exhibited sustained antibacterial activity, and there was no definite release of silver ions from the Ag-P-integrated silicone polymer membrane at any time point. Using a porcine stent model, in vivo analysis demonstrated that the Ag-P-integrated silicone polymer-covered SEMS reduced the thickness of the biofilm and the quantity of sludge formed, compared with a conventional silicone-covered SEMS. In vivo, the release of silver ions from an Ag-P-integrated silicone polymer-covered SEMS was not detected in porcine serum. The Ag-P-integrated silicone polymer-covered SEMS also resulted in significantly less stent-related bile duct and subepithelium tissue inflammation than a conventional silicone polymer-covered SEMS. Therefore, the Ag-P-integrated silicone polymer-covered SEMS reduced sludge and biofilm formation and stent-induced pathological changes in tissue. This novel SEMS may prolong the stent patency in clinical application.
NASA Technical Reports Server (NTRS)
Lo, C. P.; Quattrochi, Dale A.
2003-01-01
Land use and land cover maps of Atlanta Metropolitan Area in Georgia were produced from Landsat MSS and TM images for 1973,1979,1983,1987,1992, and 1997, spanning a period of 25 years. Dramatic changes in land use and land cover have occurred with loss of forest and cropland to urban use. In particular, low-density urban use, which includes largely residential use, has increased by over 119% between 1973 and 1997. These land use and land cover changes have drastically altered the land surface characteristics. An analysis of Landsat images revealed an increase in surface temperature and a decline in NDVI from 1973 to 1997. These changes have forced the development of a significant urban heat island effect and an increase in ground level ozone production to such an extent, that Atlanta has violated EPA's ozone level standard in recent years. The urban heat island initiated precipitation events that were identified between 1996 and 2000 tended to occur near high-density urban areas but outside the I-285 loop that traverses around the Central Business District, i.e. not in the inner city area, but some in close proximity to the highways. The health implications were investigated by comparing the spatial patterns of volatile organic compounds (VOC) and nitrogen oxides (NOx) emissions, the two ingredients that form ozone by reacting with sunlight, with those of rates of cardiovascular and chronic lower respiratory diseases. A clear core-periphery pattern was revealed for both VOC and NOx emissions, but the spatial pattern was more random in the cases of rates of cardiovascular and chronic lower respiratory diseases. Clearly, factors other than ozone pollution were involved in explaining the rates of these diseases. Further research is therefore needed to understand the health geography and its relationship to land use and land cover change as well as urban heat island effect. This paper illustrates the usefulness of a remote sensing approach for this purpose.
Nam, Kijun; Lee, Woo-Kyun; Kim, Moonil; Kwak, Doo-Ahn; Byun, Woo-Hyuk; Yu, Hangnan; Kwak, Hanbin; Kwon, Taesung; Sung, Joohan; Chung, Dong-Jun; Lee, Seung-Ho
2015-07-01
This study analyzes change in carbon storage by applying forest growth models and final cutting age to actual and potential forest cover for six major tree species in South Korea. Using National Forest Inventory data, the growth models were developed to estimate mean diameter at breast height, tree height, and number of trees for Pinus densiflora, Pinus koraiensis, Pinus rigida, Larix kaempferi, Castanea crenata and Quercus spp. stands. We assumed that actual forest cover in a forest type map will change into potential forest covers according to the Hydrological and Thermal Analogy Groups model. When actual forest cover reaches the final cutting age, forest volume and carbon storage are estimated by changed forest cover and its growth model. Forest volume between 2010 and 2110 would increase from 126.73 to 157.33 m(3) hm(-2). Our results also show that forest cover, volume, and carbon storage could abruptly change by 2060. This is attributed to the fact that most forests are presumed to reach final cutting age. To avoid such dramatic change, a regeneration and yield control scheme should be prepared and implemented in a way that ensures balance in forest practice and yield.
Exploring dust emission responses to land cover change using an ecological land classification
NASA Astrophysics Data System (ADS)
Galloza, Magda S.; Webb, Nicholas P.; Bleiweiss, Max P.; Winters, Craig; Herrick, Jeffrey E.; Ayers, Eldon
2018-06-01
Despite efforts to quantify the impacts of land cover change on wind erosion, assessment uncertainty remains large. We address this uncertainty by evaluating the application of ecological site concepts and state-and-transition models (STMs) for detecting and quantitatively describing the impacts of land cover change on wind erosion. We apply a dust emission model over a rangeland study area in the northern Chihuahuan Desert, New Mexico, USA, and evaluate spatiotemporal patterns of modelled horizontal sediment mass flux and dust emission in the context of ecological sites and their vegetation states; representing a diversity of land cover types. Our results demonstrate how the impacts of land cover change on dust emission can be quantified, compared across land cover classes, and interpreted in the context of an ecological model that encapsulates land management intensity and change. Results also reveal the importance of established weaknesses in the dust model soil characterisation and drag partition scheme, which appeared generally insensitive to the impacts of land cover change. New models that address these weaknesses, coupled with ecological site concepts and field measurements across land cover types, could significantly reduce assessment uncertainties and provide opportunities for identifying land management options.
Dieye, A.M.; Roy, David P.; Hanan, N.P.; Liu, S.; Hansen, M.; Toure, A.
2012-01-01
Spatially explicit land cover land use (LCLU) change information is needed to drive biogeochemical models that simulate soil organic carbon (SOC) dynamics. Such information is increasingly being mapped using remotely sensed satellite data with classification schemes and uncertainties constrained by the sensing system, classification algorithms and land cover schemes. In this study, automated LCLU classification of multi-temporal Landsat satellite data were used to assess the sensitivity of SOC modeled by the Global Ensemble Biogeochemical Modeling System (GEMS). The GEMS was run for an area of 1560 km2 in Senegal under three climate change scenarios with LCLU maps generated using different Landsat classification approaches. This research provides a method to estimate the variability of SOC, specifically the SOC uncertainty due to satellite classification errors, which we show is dependent not only on the LCLU classification errors but also on where the LCLU classes occur relative to the other GEMS model inputs.
NASA Astrophysics Data System (ADS)
Li, S.; Zhang, S.; Yang, D.
2017-09-01
Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.
Changing drivers of deforestation and new opportunities for conservation.
Rudel, Thomas K; Defries, Ruth; Asner, Gregory P; Laurance, William F
2009-12-01
Over the past 50 years, human agents of deforestation have changed in ways that have potentially important implications for conservation efforts. We characterized these changes through a meta-analysis of case studies of land-cover change in the tropics. From the 1960s to the 1980s, small-scale farmers, with state assistance, deforested large areas of tropical forest in Southeast Asia and Latin America. As globalization and urbanization increased during the 1980s, the agents of deforestation changed in two important parts of the tropical biome, the lowland rainforests in Brazil and Indonesia. Well-capitalized ranchers, farmers, and loggers producing for consumers in distant markets became more prominent in these places and this globalization weakened the historically strong relationship between local population growth and forest cover. At the same time, forests have begun to regrow in some tropical uplands. These changing circumstances, we believe, suggest two new and differing strategies for biodiversity conservation in the tropics, one focused on conserving uplands and the other on promoting environmental stewardship in lowlands and other areas conducive to industrial agriculture.
Wollan, David; Pham, Duc-Truc; Wilkinson, Kerry Leigh
2016-10-12
The relative proportion of water and ethanol present in alcoholic beverages can significantly influence the perception of wine sensory attributes. This study therefore investigated changes in wine ethanol concentration due to evaporation from wine glasses. The ethanol content of commercial wines exposed to ambient conditions while in wine glasses was monitored over time. No change in wine ethanol content was observed where glasses were covered with plastic lids, but where glasses were not covered, evaporation had a significant impact on wine ethanol content, with losses from 0.9 to 1.9% alcohol by volume observed for wines that received direct exposure to airflow for 2 h. Evaporation also resulted in decreases in the concentration of some fermentation volatiles (determined by gas chromatography-mass spectrometry) and a perceptible change in wine aroma. The rate of ethanol loss was strongly influenced by exposure to airflow (i.e., from the laboratory air-conditioning unit), together with certain glass shape and wine parameters; glass headspace in particular. This is the first study to demonstrate the significant potential for ethanol evaporation from wine in wine glasses. Research findings have important implications for the technical evaluation of wine sensory properties; in particular, informal sensory trials and wine show judging, where the use of covers on wine glasses is not standard practice.
Sohl, Terry L.; Sleeter, Benjamin M.; Zhu, Zhiliang; Sayler, Kristi L.; Bennett, Stacie; Bouchard, Michelle; Reker, Ryan R.; Hawbaker, Todd J.; Wein, Anne M.; Liu, Shuguang; Kanengieter, Ronald L.; Acevedo, William
2012-01-01
Changes in land use, land cover, disturbance regimes, and land management have considerable influence on carbon and greenhouse gas (GHG) fluxes within ecosystems. Through targeted land-use and land-management activities, ecosystems can be managed to enhance carbon sequestration and mitigate fluxes of other GHGs. National-scale, comprehensive analyses of carbon sequestration potential by ecosystem are needed, with a consistent, nationally applicable land-use and land-cover (LULC) modeling framework a key component of such analyses. The U.S. Geological Survey has initiated a project to analyze current and projected future GHG fluxes by ecosystem and quantify potential mitigation strategies. We have developed a unique LULC modeling framework to support this work. Downscaled scenarios consistent with IPCC Special Report on Emissions Scenarios (SRES) were constructed for U.S. ecoregions, and the FORE-SCE model was used to spatially map the scenarios. Results for a prototype demonstrate our ability to model LULC change and inform a biogeochemical modeling framework for analysis of subsequent GHG fluxes. The methodology was then successfully used to model LULC change for four IPCC SRES scenarios for an ecoregion in the Great Plains. The scenario-based LULC projections are now being used to analyze potential GHG impacts of LULC change across the U.S.
Sohl, Terry L.; Sleeter, Benjamin M.; Zhu, Zhi-Liang; Sayler, Kristi L.; Bennett, Stacie; Bouchard, Michelle; Reker, Ryan R.; Hawbaker, Todd; Wein, Anne; Liu, Shu-Guang; Kanengleter, Ronald; Acevedo, William
2012-01-01
Changes in land use, land cover, disturbance regimes, and land management have considerable influence on carbon and greenhouse gas (GHG) fluxes within ecosystems. Through targeted land-use and landmanagement activities, ecosystems can be managed to enhance carbon sequestration and mitigate fluxes of other GHGs. National-scale, comprehensive analyses of carbon sequestration potential by ecosystem are needed, with a consistent, nationally applicable land-use and land-cover (LULC) modeling framework a key component of such analyses. The U.S. Geological Survey has initiated a project to analyze current and projected future GHG fluxes by ecosystem and quantify potential mitigation strategies. We have developed a unique LULC modeling framework to support this work. Downscaled scenarios consistent with IPCC Special Report on Emissions Scenarios (SRES) were constructed for U.S. ecoregions, and the FORE-SCE model was used to spatially map the scenarios. Results for a prototype demonstrate our ability to model LULC change and inform a biogeochemical modeling framework for analysis of subsequent GHG fluxes. The methodology was then successfully used to model LULC change for four IPCC SRES scenarios for an ecoregion in the Great Plains. The scenario-based LULC projections are now being used to analyze potential GHG impacts of LULC change across the U.S.
NASA Astrophysics Data System (ADS)
Osunmadewa, Babatunde Adeniyi; Gebrehiwot, Worku Zewdie; Csaplovics, Elmar; Adeofun, Olabinjo Clement
2018-03-01
Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.
John F. Caratti
2006-01-01
The FIREMON Cover/Frequency (CF) method is used to assess changes in plant species cover and frequency for a macroplot. This method uses multiple quadrats to sample within-plot variation and quantify statistically valid changes in plant species cover, height, and frequency over time. Because it is difficult to estimate cover in quadrats for larger plants, this method...
Trends in landscape and vegetation change and implications for the Santa Cruz Watershed
Villarreal, Miguel; Norman, Laura M.; Webb, Robert H.; Turner, Raymond M.
2013-01-01
Monitoring and characterizing the interactive effects of land use and climate on land surface processes is a primary focus of land change science, and of particular concern in arid Wells Distribution in Shallow Groundwater Areas Pumping Trends Increase Streamflow Extent Declines 27 environments where both landscapes and livelihoods can be impacted by short-term climate variability. Using a multi-observational approach to land-change analysis that included landownership data as a proxy for land-use practices, multitemporal land-cover maps, and repeat photography dating to the late 19th century, we examine changing spatial and temporal distributions of two vegetation types with high conservation value in the southwestern United States: grasslands and riparian vegetation. Our study area is the bi-national Santa Cruz Watershed, a topographically complex watershed that straddles the Sonoran Desert and the Madrean Archipelago Ecoregions. In this presentation we focus on historical changes in vegetation and land use in grasslands and riparian areas of the Madrean Ecoregion (San Raphael Valley, Cienega Creek, Sonoita), and compare changes in these areas to changes in the warmer and drier Sonoran Ecoregion. Analysis of historical photography confirms major 20th century vegetation shifts documented in other research: woody plant encroachment, desertification of grasslands, and changing riparian and xeroriparian vegetation occurred in both ecoregions following human settlement. However, vegetation changes over the past decade appear to be more subtle and some of the past trajectories appear to be reversing; most notable are recent mesquite declines in xeroriparian and upland areas, and changes from shrubland to grassland area in the Madrean ecoregion. Land cover changes were temporally variable, reflecting broad climate changes. The most dynamic cover changes occurred during the period from 1989 to 1999, a period with two intense droughts. The degree of vegetation change driven by climate was related to topographic setting: vegetation declines were greater per unit area in the lower elevation Sonoran ecoregion where temperatures are higher and precipitation lower than in the Madrean. Fine-scale changes within these broad climate patterns were likely the result of land use practices: declines were highest on state lands (grazing) and increases highest on private ranches and some federal lands (active mesquite removal and watershed restoration).
Hu, Tangao; Liu, Jiahong; Zheng, Gang; Li, Yao; Xie, Bin
2018-05-09
Accurate and timely information describing urban wetland resources and their changes over time, especially in rapidly urbanizing areas, is becoming more important. We applied an object-based image analysis and nearest neighbour classifier to map and monitor changes in land use/cover using multi-temporal high spatial resolution satellite imagery in an urban wetland area (Hangzhou Xixi Wetland) from 2000, 2005, 2007, 2009 and 2013. The overall eight-class classification accuracies averaged 84.47% for the five years. The maps showed that between 2000 and 2013 the amount of non-wetland (urban) area increased by approximately 100%. Herbaceous (32.22%), forest (29.57%) and pond (23.85%) are the main land-cover types that changed to non-wetland, followed by cropland (6.97%), marsh (4.04%) and river (3.35%). In addition, the maps of change patterns showed that urban wetland loss is mainly distributed west and southeast of the study area due to real estate development, and the greatest loss of urban wetlands occurred from 2007 to 2013. The results demonstrate the advantages of using multi-temporal high spatial resolution satellite imagery to provide an accurate, economical means to map and analyse changes in land use/cover over time and the ability to use the results as inputs to urban wetland management and policy decisions.
Changes in Andes snow cover from MODIS data, 2000-2016
NASA Astrophysics Data System (ADS)
Saavedra, Freddy A.; Kampf, Stephanie K.; Fassnacht, Steven R.; Sibold, Jason S.
2018-03-01
The Andes span a length of 7000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP) as the fraction of time with snow cover for each year between 2000 and 2016 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors (500 m, 8-day maximum snow cover extent). This analysis is conducted between 8 and 36° S due to high frequency of cloud (> 30 % of the time) south and north of this range. We ran Mann-Kendall and Theil-Sens analyses to identify areas with significant changes in SP and snowline (the line at lower elevation where SP = 20 %). We evaluated how these trends relate to temperature and precipitation from Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) and University of Delaware datasets and climate indices as El Niño-Southern Oscillation (ENSO), Southern Annular Mode (SAM), and Pacific Decadal Oscillation (PDO). Areas north of 29° S have limited snow cover, and few trends in snow persistence were detected. A large area (34 370 km2) with persistent snow cover between 29 and 36° S experienced a significant loss of snow cover (2-5 fewer days of snow year-1). Snow loss was more pronounced (62 % of the area with significant trends) on the east side of the Andes. We also found a significant increase in the elevation of the snowline at 10-30 m year-1 south of 29-30° S. Decreasing SP correlates with decreasing precipitation and increasing temperature, and the magnitudes of these correlations vary with latitude and elevation. ENSO climate indices better predicted SP conditions north of 31° S, whereas the SAM better predicted SP south of 31° S.
NASA Astrophysics Data System (ADS)
Kancírová, M.; Kudela, K.; Erlykin, A. D.; Wolfendale, A. W.
2016-10-01
A detailed analysis has been made based on annual meteorological and cosmic ray data from the Lomnicky stit mountain observatory (LS, 2634 masl; 49.40°N, 20.22°E; vertical cut-off rigidity 3.85 GV), from the standpoint of looking for possible solar cycle (including cosmic ray) manifestations. A comparison of the mountain data with the Global average for the cloud cover in general shows no correlation but there is a possible small correlation for low clouds (LCC in the Global satellite data). However, whereas it cannot be claimed that cloud cover observed at Lomnicky stit (LSCC) can be used directly as a proxy for the Global LCC, its examination has value because it is an independent estimate of cloud cover and one that has a different altitude weighting to that adopted in the satellite-derived LCC. This statement is derived from satellite data (http://isccp.giss.nasa.gov/climanal7.html) which shows the time series for the period 1983-2010 for 9 cloud regimes. There is a significant correlation only between cosmic ray (CR) intensity (and sunspot number (SSN)) and the cloud cover of the types cirrus and stratus. This effect is mainly confined to the CR intensity minimum during the epoch around 1990, when the SSN was at its maximum. This fact, together with the present study of the correlation of LSCC with our measured CR intensity, shows that there is no firm evidence for a significant contribution of CR induced ionization to the local (or, indeed, Global) cloud cover. Pressure effects are the preferred cause of the cloud cover changes. A consequence is that there is no evidence favouring a contribution of CR to the Global Warming problem. Our analysis shows that the LS data are consistent with the Gas Laws for a stable mass of atmosphere.
Behavioral Marital Bibliotherapy: An Initial Investigation of Therapeutic Efficacy.
ERIC Educational Resources Information Center
Bornstein, Philip H.; And Others
1984-01-01
Reports an attempt to validate a self-help behavioral marital bibliotherapy program. Evaluated five clinical distressed couples via a multiple baseline analysis. Treatment involved reading and exercises covering communications, problem solving, and sexual dysfunction. Results were highly variable and reflected minimal change. (BH)
NASA Astrophysics Data System (ADS)
Taghadosi, M. M.; Hasanlou, M.
2017-09-01
Soil salinity is one of the main causes of desertification and land degradation which has negative impacts on soil fertility and crop productivity. Monitoring salt affected areas and assessing land cover changes, which caused by salinization, can be an effective approach to rehabilitate saline soils and prevent further salinization of agricultural fields. Using potential of satellite imagery taken over time along with remote sensing techniques, makes it possible to determine salinity changes at regional scales. This study deals with monitoring salinity changes and trend of the expansion in different land cover types of Bakhtegan Salt Lake district during the last two decades using multi-temporal Landsat images. For this purpose, per-pixel trend analysis of soil salinity during years 2000 to 2016 was performed and slope index maps of the best salinity indicators were generated for each pixel in the scene. The results of this study revealed that vegetation indices (GDVI and EVI) and also salinity indices (SI-1 and SI-3) have great potential to assess soil salinity trends in vegetation and bare soil lands respectively due to more sensitivity to salt features over years of study. In addition, images of May had the best performance to highlight changes in pixels among different months of the year. A comparative analysis of different slope index maps shows that more than 76% of vegetated areas have experienced negative trends during 17 years, of which about 34% are moderately and highly saline. This percent is increased to 92% for bare soil lands and 29% of salt affected soils had severe salinization. It can be concluded that the areas, which are close to the lake, are more affected by salinity and salts from the lake were brought into the soil which will lead to loss of soil productivity ultimately.
Mathematics and mallard management
Cowardin, L.M.; Johnson, D.H.
1979-01-01
Waterfowl managers can effectively use simple population models to aid in making management decisions. We present a basic model of the change in population size as related to survival and recruitment. A management technique designed to increase survival of mallards (Anas platyrhynchos) by limiting harvest on the Chippewa National Forest, Minnesota, is used to illustrate the application of models in decision making. The analysis suggests that the management technique would be of limited effectiveness. In a 2nd example, the change in mallard population in central North Dakota is related to implementing programs to create dense nesting cover with or without supplementary predator control. The analysis suggests that large tracts of land would be required to achieve a hypothetical management objective of increasing harvest by 50% while maintaining a stable population. Less land would be required if predator reduction were used in combination with cover management, but questions about effectiveness and ecological implications of large scale predator reduction remain unresolved. The use of models as a guide to planning research responsive to the needs of management is illustrated.
Braided river flow and invasive vegetation dynamics in the Southern Alps, New Zealand.
Caruso, Brian S; Edmondson, Laura; Pithie, Callum
2013-07-01
In mountain braided rivers, extreme flow variability, floods and high flow pulses are fundamental elements of natural flow regimes and drivers of floodplain processes, understanding of which is essential for management and restoration. This study evaluated flow dynamics and invasive vegetation characteristics and changes in the Ahuriri River, a free-flowing braided, gravel-bed river in the Southern Alps of New Zealand's South Island. Sixty-seven flow metrics based on indicators of hydrologic alteration and environmental flow components (extreme low flows, low flows, high flow pulses, small floods and large floods) were analyzed using a 48-year flow record. Changes in the areal cover of floodplain and invasive vegetation classes and patch characteristics over 20 years (1991-2011) were quantified using five sets of aerial photographs, and the correlation between flow metrics and cover changes were evaluated. The river exhibits considerable hydrologic variability characteristic of mountain braided rivers, with large variation in floods and other flow regime metrics. The flow regime, including flood and high flow pulses, has variable effects on floodplain invasive vegetation, and creates dynamic patch mosaics that demonstrate the concepts of a shifting mosaic steady state and biogeomorphic succession. As much as 25 % of the vegetation cover was removed by the largest flood on record (570 m(3)/s, ~50-year return period), with preferential removal of lupin and less removal of willow. However, most of the vegetation regenerated and spread relatively quickly after floods. Some flow metrics analyzed were highly correlated with vegetation cover, and key metrics included the peak magnitude of the largest flood, flood frequency, and time since the last flood in the interval between photos. These metrics provided a simple multiple regression model of invasive vegetation cover in the aerial photos evaluated. Our analysis of relationships among flow regimes and invasive vegetation cover has implications for braided rivers impacted by hydroelectric power production, where increases in invasive vegetation cover are typically greater than in unimpacted rivers.
Assessing cover crop management under actual and climate change conditions.
Alonso-Ayuso, María; Quemada, Miguel; Vanclooster, Marnik; Ruiz-Ramos, Margarita; Rodriguez, Alfredo; Gabriel, José Luis
2018-04-15
The termination date is recognized as a key management factor to enhance cover crops for multiple benefits and to avoid competition with the following cash crop. However, the optimum date depends on annual meteorological conditions, and climate variability induces uncertainty in a decision that needs to be taken every year. One of the most important cover crop benefits is reducing nitrate leaching, a major concern for irrigated agricultural systems and highly affected by the termination date. This study aimed to determine the effects of cover crops and their termination date on the water and N balances of an irrigated Mediterranean agroecosystem under present and future climate conditions. For that purpose, two field experiments were used for inverse calibration and validation of the WAVE model (Water and Agrochemicals in the soil and Vadose Environment), based on continuous soil water content data, soil nitrogen content and crop measurements. The calibrated and validated model was subsequently used in advanced scenario analysis under present and climate change conditions. Under present conditions, a late termination date increased cover crop biomass and subsequently soil water and N depletion. Hence, preemptive competition risk with the main crop was enhanced, but a reduction of nitrate leaching also occurred. The hypothetical planting date of the following cash crop was also an important tool to reduce preemptive competition. Under climate change conditions, the simulations showed that the termination date will be even more important to reduce preemptive competition and nitrate leaching. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.
Spatio-Temporal Assessment of Margalla Hills Forest by Using Landsat Imagery for Year 2000 and 2018
NASA Astrophysics Data System (ADS)
Batool, R.; Javaid, K.
2018-04-01
Environmental imbalance due to human activities has shown serious threat to ecosystem and produced negative impacts. The main goal of this study is to identify, monitor and classify temporal changes of forest cover, build up and open spaces in Margalla Hills National Park, Islamabad. Geographic Information Sciences (GISc) and Remote Sensing (RS) techniques has been used for the assessment of analysis. LANDSAT-7 Enhanced Thematic Mapper (ETM+) and LANDSAT-8 Operational Land Imager (OLI) were utilized for obtaining data of year 2000 and 2018. Temporal changes were evaluated after applying supervised classification and discrimination was analyzed by Per-Pixel based change detection. Results depicts forest cover decrease from 87 % to 74 % whereas build up has increased from 5 % to 7 % over the span. Consequences also justify the presence of open land in study area that has been increased from 2 % to 7 % respectively.
NASA Technical Reports Server (NTRS)
Bender, Frida A-M.; Rananathan, V.; Tselioudis, G.
2012-01-01
Climate model simulations suggest that the extratropical storm tracks will shift poleward as a consequence of global warming. In this study the northern and southern hemisphere storm tracks over the Pacific and Atlantic ocean basins are studied using observational data, primarily from the International Satellite Cloud Climatology Project, ISCCP. Potential shifts in the storm tracks are examined using the observed cloud structures as proxies for cyclone activity. Different data analysis methods are employed, with the objective to address difficulties and uncertainties in using ISCCP data for regional trend analysis. In particular, three data filtering techniques are explored; excluding specific problematic regions from the analysis, regressing out a spurious viewing geometry effect, and excluding specific cloud types from the analysis. These adjustments all, to varying degree, moderate the cloud trends in the original data but leave the qualitative aspects of those trends largely unaffected. Therefore, our analysis suggests that ISCCP data can be used to interpret regional trends in cloudiness, provided that data and instrumental artefacts are recognized and accounted for. The variation in magnitude between trends emerging from application of different data correction methods, allows us to estimate possible ranges for the observational changes. It is found that the storm tracks, here represented by the extent of the midlatitude-centered band of maximum cloud cover over the studied ocean basins, experience a poleward shift as well as a narrowing over the 25 year period covered by ISCCP. The observed magnitudes of these effects are larger than in current generation climate models (CMIP3). The magnitude of the shift is particularly large in the northern hemisphere Atlantic. This is also the one of the four regions in which imperfect data primarily prevents us from drawing firm conclusions. The shifted path and reduced extent of the storm track cloudiness is accompanied by a regional reduction in total cloud cover. This decrease in cloudiness can primarily be ascribed to low level clouds, whereas the upper level cloud fraction actually increases, according to ISCCP. Independent satellite observations of radiative fluxes at the top of the atmosphere are consistent with the changes in total cloud cover. The shift in cloudiness is also supported by a shift in central position of the mid-troposphere meridional temperature gradient. We do not find support for aerosols playing a significant role in the satellite observed changes in cloudiness. The observed changes in storm track cloudiness can be related to local cloud-induced changes in radiative forcing, using ERBE and CERES radiative fluxes. The shortwave and the longwave components are found to act together, leading to a positive (warming) net radiative effect in response to the cloud changes in the storm track regions, indicative of positive cloud feedback. Among the CMIP3 models that simulate poleward shifts in all four storm track areas, all but one show decreasing cloud amount on a global mean scale in response to increased CO2 forcing, further consistent with positive cloud feedback. Models with low equilibrium climate sensitivity to a lesser extent than higher-sensitivity models simulate a poleward shift of the storm tracks.
Analysing land cover and land use change in the Matobo National Park and surroundings in Zimbabwe
NASA Astrophysics Data System (ADS)
Scharsich, Valeska; Mtata, Kupakwashe; Hauhs, Michael; Lange, Holger; Bogner, Christina
2016-04-01
Natural forests are threatened worldwide, therefore their protection in National Parks is essential. Here, we investigate how this protection status affects the land cover. To answer this question, we analyse the surface reflectance of three Landsat images of Matobo National Park and surrounding in Zimbabwe from 1989, 1998 and 2014 to detect changes in land cover in this region. To account for the rolling countryside and the resulting prominent shadows, a topographical correction of the surface reflectance was required. To infer land cover changes it is not only necessary to have some ground data for the current satellite images but also for the old ones. In particular for the older images no recent field study could help to reconstruct these data reliably. In our study we follow the idea that land cover classes of pixels in current images can be transferred to the equivalent pixels of older ones if no changes occurred meanwhile. Therefore we combine unsupervised clustering with supervised classification as follows. At first, we produce a land cover map for 2014. Secondly, we cluster the images with clara, which is similar to k-means, but suitable for large data sets. Whereby the best number of classes were determined to be 4. Thirdly, we locate unchanged pixels with change vector analysis in the images of 1989 and 1998. For these pixels we transfer the corresponding cluster label from 2014 to 1989 and 1998. Subsequently, the classified pixels serve as training data for supervised classification with random forest, which is carried out for each image separately. Finally, we derive land cover classes from the Landsat image in 2014, photographs and Google Earth and transfer them to the other two images. The resulting classes are shrub land; forest/shallow waters; bare soils/fields with some trees/shrubs; and bare light soils/rocks, fields and settlements. Subsequently the three different classifications are compared and land changes are mapped. The main changes are observable in the surroundings of the National Park, especially the common lands have lost their clear boundaries with time. In the National Park, the area of forest increases from 1989 to 2014 from 58% to 61% whereas the area of shrub land decreases by the same amount. The amount of each of the other two classes remains constant. These changes indicate an actual effect of the protection status of the National Park. In our study remote sensing data are the main source to evaluate the effects and the benefits of a protected area without on-side studies. This could be important for regions, where field studies are not possible because of insecure political conditions and only remote sensing data are available.
LANDSAT data for coastal zone management. [New Jersey
NASA Technical Reports Server (NTRS)
Mckenzie, S.
1981-01-01
The lack of adequate, current data on land and water surface conditions in New Jersey led to the search for better data collections and analysis techniques. Four-channel MSS data of Cape May County and access to the OSER computer interpretation system were provided by NASA. The spectral resolution of the data was tested and a surface cover map was produced by going through the steps of supervised classification. Topics covered include classification; change detection and improvement of spectral and spatial resolution; merging LANDSAT and map data; and potential applications for New Jersey.
Kathleen M. Bergen; Daniel G. Brown; James F. Rutherford; Eric J. Gustafson
2005-01-01
A ca. 1980 national-scale land-cover classification based on aerial photo interpretation was combined with 2000 AVHRR satellite imagery to derive land cover and land-cover change information for forest, urban, and agriculture categories over a seven-state region in the U.S. To derive useful land-cover change data using a heterogeneous dataset and to validate our...
Coastal regime shifts: rapid responses of coastal wetlands to changes in mangrove cover.
Guo, Hongyu; Weaver, Carolyn; Charles, Sean P; Whitt, Ashley; Dastidar, Sayantani; D'Odorico, Paolo; Fuentes, Jose D; Kominoski, John S; Armitage, Anna R; Pennings, Steven C
2017-03-01
Global changes are causing broad-scale shifts in vegetation communities worldwide, including coastal habitats where the borders between mangroves and salt marsh are in flux. Coastal habitats provide numerous ecosystem services of high economic value, but the consequences of variation in mangrove cover are poorly known. We experimentally manipulated mangrove cover in large plots to test a set of linked hypotheses regarding the effects of changes in mangrove cover. We found that changes in mangrove cover had strong effects on microclimate, plant community, sediment accretion, soil organic content, and bird abundance within 2 yr. At higher mangrove cover, wind speed declined and light interception by vegetation increased. Air and soil temperatures had hump-shaped relationships with mangrove cover. The cover of salt marsh plants decreased at higher mangrove cover. Wrack cover, the distance that wrack was distributed from the water's edge, and sediment accretion decreased at higher mangrove cover. Soil organic content increased with mangrove cover. Wading bird abundance decreased at higher mangrove cover. Many of these relationships were non-linear, with the greatest effects when mangrove cover varied from zero to intermediate values, and lesser effects when mangrove cover varied from intermediate to high values. Temporal and spatial variation in measured variables often peaked at intermediate mangrove cover, with ecological consequences that are largely unexplored. Because different processes varied in different ways with mangrove cover, the "optimum" cover of mangroves from a societal point of view will depend on which ecosystem services are most desired. © 2016 by the Ecological Society of America.
Environmental change pattern in central Japan as revealed by LANDSAT data
NASA Technical Reports Server (NTRS)
Maruyasu, T. (Principal Investigator); Tsuchiya, K.; Ochiai, H.
1977-01-01
The author has identified the following significant results. A patched cirrus reported by weather stations was hardly recognizable by the eye in LANDSAT MSS data of a three year time lapse. The cloud cover affected radiance values significantly in band 4, while its effect was minimal in bands 6 and 7 (near infrared spectra). The cross correlation coefficient analysis between the two images indicated that the highest value obtained in central Japan was 0.963 for the area where little change occurred in land use over the three period. An analysis of land use in Nagoya showed little change in the metropolitan area while a fairly large change occurred in the northern periphery of the city where large scale housing projects are located.
NASA Astrophysics Data System (ADS)
Hawtree, D.; Nunes, J. P.; Keizer, J. J.; Jacinto, R.; Santos, J.; Rial-Rivas, M. E.; Boulet, A.-K.; Tavares-Wahren, F.; Feger, K.-H.
2015-07-01
The north-central region of Portugal has undergone significant land cover change since the early 1900s, with large-scale replacement of natural vegetation types with plantation forests. This transition consisted of an initial conversion primarily to Pinus pinaster, followed by a secondary transition to Eucalyptus globulus. This land cover change is likely to have altered the hydrologic functioning of this region; however, these potential impacts are not fully understood. To contribute to a better understanding of the potential hydrologic impacts of this land cover change, this study examines the temporal trends in 75 years of data from the Águeda watershed (part of the Vouga Basin) over the period of 1936-2010. A number of hydrometeorological variables were analyzed using a combined Thiel-Sen/Mann-Kendall trend-testing approach, to assess the magnitude and significance of patterns in the observed data. These trend tests indicated that there have been no significant reductions in streamflow over either the entire test period, or during sub-record periods, despite the large-scale afforestation which has occurred. This lack of change in streamflow is attributed to the specific characteristics of the watershed and land cover change. By contrast, a number of significant trends were found for baseflow index, with positive trends in the early data record (primarily during Pinus pinaster afforestation), followed by negative trends later in the data record (primarily during Eucalyptus globulus afforestation). These trends are attributed to land use and vegetation impacts on streamflow generating processes, both due to species differences and to alterations in soil properties (i.e., infiltration capacity, soil water repellency). These results highlight the importance of considering both vegetation types/dynamics and watershed characteristic when assessing hydrologic impacts, in particular with respect to soil properties.
NASA Astrophysics Data System (ADS)
Tromboni, F.; Feijó de Lima, R.; Silva-Júnior, E. F.; Lourenço-Amorim, C.; Zandoná, E.; Moulton, T. P.; Da Silva, B. S.; Silva-Araújo, M.; Thomas, S. A.
2015-12-01
Riparian land-cover change (LCC) causes a cascade of subsequent hierarchical effects that propagate through abiotic compartments until reaching the biota, altering stream ecosystem functioning. Due to the movement of water downstream, these lateral effects co-occur with longitudinal influences. We investigated both the lateral and longitudinal effects of deforestation in four streams in the Atlantic tropical rainforest of Brazil. We collected physical-chemical, geomorphic, hydrological data and samples of macroinvertebrates assemblages. We then categorized land cover at different scales (from different riparian and reach buffer sizes to sub and total watershed) using a SPOT-5 satellite image and ArcGIS. We also carried out a series of experiments along the streams to understand: 1) the mechanisms by which LCC affects periphyton and how these changes alter metabolism and nutrient uptake rates; 2) the downstream distance at which periphyton and the associated variables change in the transitions from one riparian category to the other. We used (i) a path analysis to test if our hypothesized land-cover cascade model described our data and (ii) non-linear models to describe the longitudinal effect on each variable. Our results showed that deforestation produced a range of physical changes at different spatial scale, longitudinally altering periphyton taxonomic composition (taxa depending on light), stoichiometry (nutritionally richer with increasing deforestation) and growth rates (greater in deforested). Macroinvertebrate assemblages behaved similarly to chlorophyll a in response to forest loss. Respiration rate increased with deforestation probably due to higher nutrient concentrations but primary production did not increase. Models were used to upscale LCC impacts on ecosystem processes from local scale experiments to landscape and our work has important implications for socio-economic decisions concerning ecosystem management and conservation.
Research in nonlinear structural and solid mechanics
NASA Technical Reports Server (NTRS)
Mccomb, H. G., Jr. (Compiler); Noor, A. K. (Compiler)
1981-01-01
Recent and projected advances in applied mechanics, numerical analysis, computer hardware and engineering software, and their impact on modeling and solution techniques in nonlinear structural and solid mechanics are discussed. The fields covered are rapidly changing and are strongly impacted by current and projected advances in computer hardware. To foster effective development of the technology perceptions on computing systems and nonlinear analysis software systems are presented.
Estimation of Fractional Plant Lifeform Cover Using Landsat and Airborne LiDAR/hyperspectral Data
NASA Astrophysics Data System (ADS)
Parra, A. S.; Xu, Q.; Dilts, T.; Weisberg, P.; Greenberg, J. A.
2017-12-01
Land-cover change has generally been understood as the result of local, landscape or regional-scale processes with most studies focusing on case-study landscapes or smaller regions. However, as we observe similar types of land-cover change occurring across different biomes worldwide, it becomes clear that global-scale processes such as climate change and CO2 fertilization, in interaction with local influences, are underlying drivers in land-cover change patterns. Prior studies on global land-cover change may not have had a suitable spatial, temporal and thematic resolution for allowing the identification of such patterns. Furthermore, the lack of globally consistent spatial data products also constitutes a limiting factor in evaluating both proximate and ultimate causes of land-cover change. In this study, we derived a global model for broadleaf tree, needleleaf tree, shrub, herbaceous, and "other" fractional cover using Landsat imagery. Combined LiDAR/hyperspectral data sets were used for calibration and validation of the Landsat-derived products. Spatially explicit uncertainties were also created as part of the data products. Our results highlight the potential for large-scale studies that model local and global influences on land-cover transition types and rates at fine thematic, spatial, and temporal resolutions. These spatial data products are relevant for identifying patterns in land-cover change due to underlying global-scale processes and can provide valuable insights into climatic and land-use factors determining vegetation distributions.
Satellite geological and geophysical remote sensing of Iceland
NASA Technical Reports Server (NTRS)
Williams, R. S., Jr. (Principal Investigator)
1974-01-01
The author has identified the following significant results. ERTS-1 imagery provides sufficient resolution to discern two effects of geothermal activity at the Namafjall geothermal area: snowmelt anomalies and delineation of altered ground. The fallout pattern of tephra from Hekla's 1970 volcanic eruption can be mapped where sufficient depth of deposition destroyed the vegetation. Lava flows from the volcanic eruptions at Askja and Hekla can be delineated. Low sun-angle imagery of snow-covered terrain has permitted the mapping of new structural and volcanic features beneath the icecaps. Coastline changes on the islands of Surtsey and Heimaey can be mapped. Variations of sediment plumes from glacial rivers on the south coast give a qualitative indication of seasonal changes in melting rates of glaciers. ERTS-1 imagery has been shown to be especially amenable to portrayal of changing glaciological phenomena: surging glaciers, collapse features in icecaps caused by subglacial volcanic (?) and geothermal activity and resulting jokulhlaups, and variations in size of glacier-margin lakes. A fifth vegetation class has now been added: lichen-covered bedrock. The high latitude permits more precise analysis of landforms, vegetation distribution, occurrence of snow cover, glaciers, and geologic structure.
NASA Astrophysics Data System (ADS)
Hashiba, Hideki; Nakayama, Yasunori; Sugimura, Toshiro
The growth of major cities in Asia, as a consequence of economic development, is feared to have adverse influences on the natural environment of the surrounding areas. Comparison of land cover changes in major cities from the viewpoints of both spatial and time series is necessary to fully understand the characteristics of urban development in Asia. To accomplish this, multiple satellite remote sensing data were analyzed across a wide range and over a long term in this study. The process of transition of a major Asian city in Tokyo, Osaka, Beijing, Shanghai, and Hong Kong was analyzed from the characteristic changes of the vegetation index value and the land cover over about 40 years, from 1972 to 2010. Image data for LANDSAT/MSS, LAND-SAT/TM, ALOS/AVNIR-2, and ALOS/PRISM were obtained using a tandem time series. The ratio and state of detailed distribution of land cover were clarified by the classification processing. The time series clearly showed different change characteristics for each city and its surrounding natural environment of vegetation and forest etc. as a result of development processes.
NASA Astrophysics Data System (ADS)
Chakraborty, S.; Banerjee, A.; Gupta, S. K. S.; Christensen, P. R.; Papandreou-Suppappola, A.
2017-12-01
Multitemporal observations acquired frequently by satellites with short revisit periods such as the Moderate Resolution Imaging Spectroradiometer (MODIS), is an important source for modeling land cover. Due to the inherent seasonality of the land cover, harmonic modeling reveals hidden state parameters characteristic to it, which is used in classifying different land cover types and in detecting changes due to natural or anthropogenic factors. In this work, we use an eight day MODIS composite to create a Normalized Difference Vegetation Index (NDVI) time-series of ten years. Improved hidden parameter estimates of the nonlinear harmonic NDVI model are obtained using the Particle Filter (PF), a sequential Monte Carlo estimator. The nonlinear estimation based on PF is shown to improve parameter estimation for different land cover types compared to existing techniques that use the Extended Kalman Filter (EKF), due to linearization of the harmonic model. As these parameters are representative of a given land cover, its applicability in near real-time detection of land cover change is also studied by formulating a metric that captures parameter deviation due to change. The detection methodology is evaluated by considering change as a rare class problem. This approach is shown to detect change with minimum delay. Additionally, the degree of change within the change perimeter is non-uniform. By clustering the deviation in parameters due to change, this spatial variation in change severity is effectively mapped and validated with high spatial resolution change maps of the given regions.
ERIC Educational Resources Information Center
Caron, Jean; Julien, Marie; Huang, Jean Hua
2008-01-01
This study presents the changes in the overall and firearm suicide rates for Quebec (Canada) before and after Bill C-17, which was implemented to secure safe storage of firearms. It covers 20,009 suicide cases reported to the coroner's office. Interrupted time series analysis is used to compare suicide rates in the two periods. Firearm suicide…
Hansen, Matt; Stehman, Steve; Loveland, Tom; Vogelmann, Jim; Cochrane, Mark
2009-01-01
Quantifying rates of forest-cover change is important for improved carbon accounting and climate change modeling, management of forestry and agricultural resources, and biodiversity monitoring. A practical solution to examining trends in forest cover change at global scale is to employ remotely sensed data. Satellite-based monitoring of forest cover can be implemented consistently across large regions at annual and inter-annual intervals. This research extends previous research on global forest-cover dynamics and land-cover change estimation to establish a robust, operational forest monitoring and assessment system. The approach integrates both MODIS and Landsat data to provide timely biome-scale forest change estimation. This is achieved by using annual MODIS change indicator maps to stratify biomes into low, medium and high change categories. Landsat image pairs can then be sampled within these strata and analyzed for estimating area of forest cleared.
Tracking Trends in Fractional Forest Cover Change using Long Term Data from AVHRR and MODIS
NASA Astrophysics Data System (ADS)
Kim, D. H.; DiMiceli, C.; Sohlberg, R. A.; Hansen, M.; Carroll, M.; Kelly, M.; Townshend, J. R.
2014-12-01
Tree cover affects terrestrial energy and water exchanges, photosynthesis and transpiration, net primary production, and carbon and nutrient fluxes. Accurate and long-term continuous observation of tree cover change is critical for the study of the gradual ecosystem change. Tree cover is most commonly inferred from categorical maps which may inadequately represent within-class heterogeneity for many analyses. Alternatively, Vegetation Continuous Fields data measures fractions or proportions of pixel area. Recent development in remote sensing data processing and cross sensor calibration techniques enabled the continuous, long-term observations such as Land Long-Term Data Records. Such data products and their surface reflectance data have enhanced the possibilities for long term Vegetation Continuous Fields data, thus enabling the estimation of long term trend of fractional forest cover change. In this presentation, we will summarize the progress in algorithm development including automation of training selection for deciduous and evergreen forest, the preliminary results, and its future applications to relate trends in fractional forest cover change and environmental change.
NASA Astrophysics Data System (ADS)
Leon-Perez, M.; Hernandez, W. J.; Armstrong, R.
2016-02-01
Reported cases of seagrass loss have increased over the last 40 years, increasing the awareness of the need for assessing seagrass health. In situ monitoring has been the main method to assess spatial and temporal changes in seagrass ecosystem. Although remote sensing techniques with multispectral imagery have been recently used for these purposes, long-term analysis is limited to the sensor's mission life. The objective of this project is to determine long-term changes in seagrass habitat cover at Caja de Muertos Island Nature Reserve, by combining in situ data with a satellite image and historical aerial photography. A current satellite imagery of the WorldView-2 sensor was used to generate a 2014 benthic habitat map for the study area. The multispectral image was pre-processed using: conversion of digital numbers to radiance, and atmospheric and water column corrections. Object-based image analysis was used to segment the image into polygons representing different benthic habitats and to classify those habitats according to the classification scheme developed for this project. The scheme include the following benthic habitat categories: seagrass (sparse, dense and very dense), colonized hard bottom (sparse, dense and very dense), sand and mix algae on unconsolidated sediments. Field work was used to calibrate the satellite-derived benthic maps and to asses accuracy of the final products. In addition, a time series of satellite imagery and historic aerial photography from 1950 to 2014 provided data to assess long-term changes in seagrass habitat cover within the Reserve. Preliminary results show an increase in seagrass habitat cover, contrasting with the worldwide declining trend. The results of this study will provide valuable information for the conservation and management of seagrass habitat in the Caja de Muertos Island Nature Reserve.
ONLY Deforestation data -- displays changes in land cover MODIS (2001-2005) available globally Forest (1981-2000) available globally Land Cover Classification -- useful for identifying changes in land cover
Milestones in Rotorcraft Aeromechanics
NASA Technical Reports Server (NTRS)
Johnson, Wayne
2011-01-01
The subject of this paper is milestones in rotorcraft aeromechanics. Aeromechanics covers much of what the engineer needs: performance, loads, vibration, stability, flight dynamics, noise. These topics cover many of the key performance attributes, and many of the often-encountered problems in rotorcraft designs. A milestone is a critical achievement, a turning point, an event marking a significant change or stage in development. The milestones identified and discussed include the beginnings of aeromechanics with autogyro analysis, ground resonance, aeromechanics books, unsteady aerodynamics and airloads, nonuniform inflow and wakes, beams and dynamics, comprehensive analysis, computational fluid dynamics, and rotor airloads tests. The focus on milestones limits the scope of the history, but allows the author to acknowledge his choices for key steps in the development of the science and engineering of rotorcraft.
Land-cover trends in the Mojave basin and range ecoregion
Sleeter, Benjamin M.; Raumann, Christian G.
2006-01-01
The U.S. Geological Survey's Land-Cover Trends Project aims to estimate the rates of contemporary land-cover change within the conterminous United States between 1972 and 2000. A random sampling approach was used to select a representative sample of 10-km by 10-km sample blocks and to estimate change within +/- 1 percent at an 85-percent confidence interval. Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus data were used, and each 60-m pixel was assigned to one of 11 distinct land-cover classes based upon a modified Anderson classification system. Upon completion of land-cover change mapping for five dates, land-cover change statistics were generated and analyzed. This paper presents estimates for the Mojave Basin and Range ecoregion located in the southwestern United States. Our research suggests land-cover change within the Mojave to be relatively rare and highly localized. The primary shift in land cover is unidirectional, with natural desert grass/shrubland being converted to development. We estimate that more than 1,300 km2 have been converted since 1973 and that the conversion is being largely driven by economic and recreational opportunities provided by the Mojave ecoregion. The time interval with the highest rate of change was 1986 to 1992, in which the rate was 0.21 percent (321.9 km2) per year total change.
Löw, F; Navratil, P; Kotte, K; Schöler, H F; Bubenzer, O
2013-10-01
With the recession of the Aral Sea in Central Asia, once the world's fourth largest lake, a huge new saline desert emerged which is nowadays called the Aralkum. Saline soils in the Aralkum are a major source for dust and salt storms in the region. The aim of this study was to analyze the spatio-temporal land cover change dynamics in the Aralkum and discuss potential implications for the recent and future dust and salt storm activity in the region. MODIS satellite time series were classified from 2000-2008 and change of land cover was quantified. The Aral Sea desiccation accelerated between 2004 and 2008. The area of sandy surfaces and salt soils, which bear the greatest dust and salt storm generation potential increased by more than 36 %. In parts of the Aralkum desalinization of soils was found to take place within 4-8 years. The implication of the ongoing regression of the Aral Sea is that the expansion of saline surfaces will continue. Knowing the spatio-temporal dynamics of both the location and the surface characteristics of the source areas for dust and salt storms allows drawing conclusions about the potential hazard degree of the dust load. The remote-sensing-based land cover assessment presented in this study could be coupled with existing knowledge on the location of source areas for an early estimation of trends in shifting dust composition. Opportunities, limits, and requirements of satellite-based land cover classification and change detection in the Aralkum are discussed.
NASA Astrophysics Data System (ADS)
Jeuck, James A.
This dissertation consists of research projects related to forest land use / land cover (LULC): (1) factors predicting LULC change and (2) methodology to predict particular forest use, or "potential working timberland" (PWT), from current forms of land data. The first project resulted in a published paper, a meta-analysis of 64 econometric models from 47 studies predicting forest land use changes. The response variables, representing some form of forest land change, were organized into four groups: forest conversion to agriculture (F2A), forestland to development (F2D), forestland to non-forested (F2NF) and undeveloped (including forestland) to developed (U2D) land. Over 250 independent econometric variables were identified, from 21 F2A models, 21 F2D models, 12 F2NF models, and 10 U2D models. These variables were organized into a hierarchy of 119 independent variable groups, 15 categories, and 4 econometric drivers suitable for conducting simple vote count statistics. Vote counts were summarized at the independent variable group level and formed into ratios estimating the predictive success of each variable group. Two ratio estimates were developed based on (1) proportion of times independent variables successfully achieved statistical significance (p ≤0.10), and (2) proportion of times independent variables successfully met the original researchers'expectations. In F2D models, popular independent variables such as population, income, and urban proximity often achieved statistical significance. In F2A models, popular independent variables such as forest and agricultural rents and costs, governmental programs, and site quality often achieved statistical significance. In U2D models, successful independent variables included urban rents and costs, zoning issues concerning forestland loss, site quality, urban proximity, population, and income. F2NF models high success variables were found to be agricultural rents, site quality, population, and income. This meta-analysis provides insight into the general success of econometric independent variables for future forest use or cover change research. The second part of this dissertation developed a method for predicting area estimates and spatial distribution of PWT in the US South. This technique determined land use from USFS Forest Inventory and Analysis (FIA) and land cover from the National Land Cover Database (NLCD). Three dependent variable forms (DV Forms) were derived from the FIA data: DV Form 1, timberland, other; DV Form 2, short timberland, tall timberland, agriculture, other; and DV Form 3, short hardwood (HW) timberland, tall HW timberland, short softwood (SW) timberland, tall SW timberland, agriculture, other. The prediction accuracy of each DV Form was investigated using both random forest model and logistic regression model specifications and data optimization techniques. Model verification employing a "leave-group-out" Monte Carlo simulation determined the selection of a stratified version of the random forest model using one-year NLCD observations with an overall accuracy of 0.53-0.94. The lower accuracy side of the range was when predictions were made from an aggregated NLCD land cover class "grass_shrub". The selected model specification was run using 2011 NLCD and the other predictor variables to produce three levels of timberland prediction and probability maps for the US South. Spatial masks removed areas unlikely to be working forests (protected and urbanized lands) resulting in PWT maps. The area of the resulting maps compared well with USFS area estimates and masked PWT maps and had an 8-11% reduction of the USFS timberland estimate for the US South compared to the DV Form. Change analysis of the 2011 NLCD to PWT showed (1) the majority of the short timberland came from NLCD grass_shrub; (2) the majority of NLCD grass_shrub predicted into tall timberland, and (3) NLCD grass_shrub was more strongly associated with timberland in the Coastal Plain. Resulting map products provide practical analytical tools for those interested in studying the area and distribution of PWT in the US South.
Office for Analysis and Evaluation of Operational Data. Annual report, 1994-FY 95
DOE Office of Scientific and Technical Information (OSTI.GOV)
None
1996-07-01
The United States Nuclear Regulatory Commission`s Office for Analysis and Evaluation of Operational Data (AEOD) has published reports of its activities since 1984. The first report covered January through June of 1984, and the second report covered July through December 1984. Since those first two semiannual reports, AEOD has published annual reports of its activities from 1985 through 1993. Beginning with the report for 1986, AEOD Annual Reports have been published as NUREG-1272. Beginning with the report for 1987, NUREG-1272 has been published in two parts, No. 1 covering power reactors and No. 2 covering nonreactors (changed to {open_quotes}nuclear materials{close_quotes}more » with the 1993 report). The 1993 AEOD Annual Report was NUREG-1272, Volume 8. AEOD has changed its annual report from a calendar year to a fiscal year report to be consistent with the NRC Annual Report and to conserve staff resources. NUREG-1272, Volume 9, No. 1 and No. 2, therefore, are combined calendar year 1994 (1994) and fiscal year 1995 (FY 95) reports which describe activities conducted between January 1, 1994, and September 30, 1995. Certain data which have historically been reported on a calendar year basis, however, are complete through calendar year 1995. Throughout this report, whenever information is presented for fiscal year 1995, it is designated as FY 95 data. Calendar year information is always designated by the four digits of the calendar year. This report, NUREG-1272, Volume 9, No. 1, covers power reactors and presents an overview of the operating experience of the nuclear power industry from the NRC perspective. NUREG-1272, Vol. 9, No. 2, covers nuclear materials and presents a review of the events and concerns associated with the use of licensed material in non-power reactor applications. A new part has been added, NUREG-1272, Volume 9, No. 3, which covers technical training and presents the activities of the Technical Training Center in FY 95 in support of the NRC`s mission.« less
Persson, U. Martin
2017-01-01
While we know that deforestation in the tropics is increasingly driven by commercial agriculture, most tropical countries still lack recent and spatially-explicit assessments of the relative importance of pasture and cropland expansion in causing forest loss. Here we present a spatially explicit quantification of the extent to which cultivated land and grassland expanded at the expense of forests across Latin America in 2001–2011, by combining two “state-of-the-art” global datasets (Global Forest Change forest loss and GlobeLand30-2010 land cover). We further evaluate some of the limitations and challenges in doing this. We find that this approach does capture some of the major patterns of land cover following deforestation, with GlobeLand30-2010’s Grassland class (which we interpret as pasture) being the most common land cover replacing forests across Latin America. However, our analysis also reveals some major limitations to combining these land cover datasets for quantifying pasture and cropland expansion into forest. First, a simple one-to-one translation between GlobeLand30-2010’s Cultivated land and Grassland classes into cropland and pasture respectively, should not be made without caution, as GlobeLand30-2010 defines its Cultivated land to include some pastures. Comparisons with the TerraClass dataset over the Brazilian Amazon and with previous literature indicates that Cultivated land in GlobeLand30-2010 includes notable amounts of pasture and other vegetation (e.g. in Paraguay and the Brazilian Amazon). This further suggests that the approach taken here generally leads to an underestimation (of up to ~60%) of the role of pasture in replacing forest. Second, a large share (~33%) of the Global Forest Change forest loss is found to still be forest according to GlobeLand30-2010 and our analysis suggests that the accuracy of the combined datasets, especially for areas with heterogeneous land cover and/or small-scale forest loss, is still too poor for deriving accurate quantifications of land cover following forest loss. PMID:28704510
Pendrill, Florence; Persson, U Martin
2017-01-01
While we know that deforestation in the tropics is increasingly driven by commercial agriculture, most tropical countries still lack recent and spatially-explicit assessments of the relative importance of pasture and cropland expansion in causing forest loss. Here we present a spatially explicit quantification of the extent to which cultivated land and grassland expanded at the expense of forests across Latin America in 2001-2011, by combining two "state-of-the-art" global datasets (Global Forest Change forest loss and GlobeLand30-2010 land cover). We further evaluate some of the limitations and challenges in doing this. We find that this approach does capture some of the major patterns of land cover following deforestation, with GlobeLand30-2010's Grassland class (which we interpret as pasture) being the most common land cover replacing forests across Latin America. However, our analysis also reveals some major limitations to combining these land cover datasets for quantifying pasture and cropland expansion into forest. First, a simple one-to-one translation between GlobeLand30-2010's Cultivated land and Grassland classes into cropland and pasture respectively, should not be made without caution, as GlobeLand30-2010 defines its Cultivated land to include some pastures. Comparisons with the TerraClass dataset over the Brazilian Amazon and with previous literature indicates that Cultivated land in GlobeLand30-2010 includes notable amounts of pasture and other vegetation (e.g. in Paraguay and the Brazilian Amazon). This further suggests that the approach taken here generally leads to an underestimation (of up to ~60%) of the role of pasture in replacing forest. Second, a large share (~33%) of the Global Forest Change forest loss is found to still be forest according to GlobeLand30-2010 and our analysis suggests that the accuracy of the combined datasets, especially for areas with heterogeneous land cover and/or small-scale forest loss, is still too poor for deriving accurate quantifications of land cover following forest loss.
NASA Astrophysics Data System (ADS)
Arias, P.; Fu, R.; Li, W.
2007-12-01
Tropical forests play a key role in determining the global carbon-climate feedback in the 21st century. Changes in rainforest growth and mortality rates, especially in the deep and least perturbed forest areas, have been consistently observed across global tropics in recent years. Understanding the underlying causes of these changes, especially their links to the global climate change, is especially important in determining the future of the tropical rainforests in the 21st century. Previous studies have mostly focus on the potential influences from elevated atmospheric CO2 and increasing surface temperature. Because the rainforests in wet tropical region is often light limited, we explore whether cloudiness have changed, if so, whether it is consistent with that expected from changes in forest growth rate. We will report our observational analysis examining the trends in annual average shortwave (SW) downwelling radiation, total cloud cover, and cumulus cover over the tropical land regions and to link them with trends in convective available potencial energy (CAPE). ISCCP data and radiosonde records available from the Department of Atmospheric Sciences of the University of Wyoming (http://www.weather.uwyo.edu/upperair/sounding.html) are used to study the trends. The period for the trend analysis is 1984-2004 for the ISCCP data and 1980-2006 for the radiosondes. The results for the Amazon rainforest region suggest a decreasing trend in total cloud and convective cloud covers, which results in an increase in downwelling SW radiation at the surface. These changes of total and convective clouds are consistent with a trend of decreasing CAPE and an elevated Level of Free Convection (LFC) height, as obtained from the radiosondes. All the above mentioned trends are statistically significant based on the Mann-Kendall test with 95% of confidence. These results consistently suggest the downward surface solar radiation has been increasing since 1984, result from a decrease of convective and total cloudiness over the Southern Amazon basin, due to an increase of LFC and atmospheric thermodynamic stability. Such an increase of surface SW radiation probably has contributed to the increasing in growth rate for the forests in the Amazon forests. Currently, the same analysis is being applied using radiosonde data from the Comprehensive Aerological Reference Data Set (CARDS) over the Amazon and Congo basins and the Southeast Asia. Our objective is to identify changes in cloudiness over tropical land and identify its underlying causes, especially the link to changes in surface temperature and humidity.
NASA Astrophysics Data System (ADS)
Mugo, R. M.; Korme, T.; Farah, H.; Nyaga, J. W.; Irwin, D.; Flores, A.; Limaye, A. S.; Artis, G.
2014-12-01
Lake Victoria (LV) is an important freshwater resource in East Africa, covering 68,800 km2, and a catchment that spans 193,000km2. It is an important source of food, energy, drinking and irrigation water, transport and a repository for agricultural, human and industrial wastes generated from its catchment. For such a lake, and a catchment transcending 5 international boundaries, collecting data to guide informed decision making is a hard task. Remote sensing is currently the only tool capable of providing information on environmental changes at high spatio-temporal scales. To address the problem of information availability for LV, we tackled two objectives; (1) we analyzed water quality parameters retrieved from MODIS data, and (2) assessed land cover changes in the catchment area using Landsat data. We used L1A MODIS-Aqua data to retrieve lake surface temperature (LST), total suspended matter (TSM), chlorophyll-a (CHLa) and diffuse attenuation coefficient (KD490) in four temporal periods i.e. daily, weekly, monthly and seasonal scales. An Empirical Orthogonal Function (EOF) analysis was done on monthly data. An analysis of land cover change was done using Landsat data for 3 epochs in order to assess if land degradation contributes to water quality changes. Our results indicate that MODIS-Aqua data provides synoptic views of water quality changes in LV at different temporal scales. The Winam Gulf in Kenya, the shores of Jinja town in Uganda, as well as the Mwanza region in Tanzania represent water quality hotspots due to their relatively high TSM and CHLa concentrations. High levels of KD490 in these areas would also indicate high turbidity and thus low light penetration due to the presence of suspended matter, algal blooms, and/or submerged vegetation. The EOF analysis underscores the areas where LST and water color variability are more significant. The changes can be associated with corresponding land use changes in the catchment, where for instance wetlands are converted to croplands. On-going dissemination of our findings together with capacity building efforts with the three main fishery and research institutions working in the lake, will enable informed decision making for the water management of LV. Enhanced capacity in trans-boundary water resources research is critical for successful decision making.
Trends in annual minimum exposed snow and ice cover in High Mountain Asia from MODIS
NASA Astrophysics Data System (ADS)
Rittger, Karl; Brodzik, Mary J.; Painter, Thomas H.; Racoviteanu, Adina; Armstrong, Richard; Dozier, Jeff
2016-04-01
Though a relatively short record on climatological scales, data from the Moderate Resolution Imaging Spectroradiometer (MODIS) from 2000-2014 can be used to evaluate changes in the cryosphere and provide a robust baseline for future observations from space. We use the MODIS Snow Covered Area and Grain size (MODSCAG) algorithm, based on spectral mixture analysis, to estimate daily fractional snow and ice cover and the MODICE Persistent Ice (MODICE) algorithm to estimate the annual minimum snow and ice fraction (fSCA) for each year from 2000 to 2014 in High Mountain Asia. We have found that MODSCAG performs better than other algorithms, such as the Normalized Difference Index (NDSI), at detecting snow. We use MODICE because it minimizes false positives (compared to maximum extents), for example, when bright soils or clouds are incorrectly classified as snow, a common problem with optical satellite snow mapping. We analyze changes in area using the annual MODICE maps of minimum snow and ice cover for over 15,000 individual glaciers as defined by the Randolph Glacier Inventory (RGI) Version 5, focusing on the Amu Darya, Syr Darya, Upper Indus, Ganges, and Brahmaputra River basins. For each glacier with an area of at least 1 km2 as defined by RGI, we sum the total minimum snow and ice covered area for each year from 2000 to 2014 and estimate the trends in area loss or gain. We find the largest loss in annual minimum snow and ice extent for 2000-2014 in the Brahmaputra and Ganges with 57% and 40%, respectively, of analyzed glaciers with significant losses (p-value<0.05). In the Upper Indus River basin, we see both gains and losses in minimum snow and ice extent, but more glaciers with losses than gains. Our analysis shows that a smaller proportion of glaciers in the Amu Darya and Syr Darya are experiencing significant changes in minimum snow and ice extent (3.5% and 12.2%), possibly because more of the glaciers in this region are smaller than 1 km2 than in the Indus, Ganges, and Brahmaputra making analysis from MODIS (pixel area ~0.25 km2) difficult. Overall, we see 23% of the glaciers in the 5 river basins with significant trends (in either direction). We relate these changes in area to topography and climate to understand the driving processes related to these changes. In addition to annual minimum snow and ice cover, the MODICE algorithm also provides the date of minimum fSCA for each pixel. To determine whether the surface was snow or ice we use the date of minimum fSCA from MODICE to index daily maps of snow on ice (SOI), or exposed glacier ice (EGI) and systematically derive an equilibrium line altitude (ELA) for each year from 2000-2014. We test this new algorithm in the Upper Indus basin and produce annual estimates of ELA. For the Upper Indus basin we are deriving annual ELAs that range from 5350 m to 5450 m which is slightly higher than published values of 5200 m for this region.
Sohl, Terry L.; Sayler, Kristi L.; Drummond, Mark A.; Loveland, Thomas R.
2007-01-01
A wide variety of ecological applications require spatially explicit, historic, current, and projected land use and land cover data. The U.S. Land Cover Trends project is analyzing contemporary (1973–2000) land-cover change in the conterminous United States. The newly developed FORE-SCE model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land cover change through 2020 for multiple plausible scenarios. Projected proportions of future land use were initially developed, and then sited on the lands with the highest potential for supporting that land use and land cover using a statistically based stochastic allocation procedure. Three scenarios of 2020 land cover were mapped for the western Great Plains in the US. The model provided realistic, high-resolution, scenario-based land-cover products suitable for multiple applications, including studies of climate and weather variability, carbon dynamics, and regional hydrology.
NASA Astrophysics Data System (ADS)
Elmore, Andrew James
The conversion of large natural basins to managed watersheds for the purpose of providing water to urban centers has had a negative impact on semiarid ecosystems, worldwide. We view semiarid plant communities as being adapted to short, regular periods of drought. However, human induced changes in the water balance often remove these systems from the range of natural variability that has been historically established. This thesis explores vegetation changes over a 13-yr period for Owens Valley, in eastern California. Using remotely sensed measurements of vegetation cover, an extensive vegetation survey, field data and observations, precipitation records, and data on water table depth, I identify the key modes of response of xeric, phreatophytic, and exotic Great Basin plant communities. Three specific advancements were reached as a result of this work. (1) A change classification technique was developed that was used to separate regions of land-cover that were dependent on precipitation from regions dependent on groundwater. This technique utilized Spectral Mixture Analysis of annually acquired Landsat Thematic Mapper remote sensing data, to retrieve regional estimates of percent vegetation cover. (2) A threshold response related to depth-to-water dependence was identified for phreatophytic Alkali Meadow communities. Plant communities that were subject to groundwater depths below this threshold exhibited greater invasion by precipitation sensitive plants. (3) The floristic differences between previously cultivated and uncultivated land were found to account for an increased sensitivity of plant communities to precipitation variability. Through (2) and (3), two human influences (groundwater decline and previous land cultivation) were shown to alter land cover such that the land became more sensitive to precipitation change. Climate change predictions include a component of increased climate variability for the western United States; therefore, these results place serious doubt on the sustainability of human activities in this region. The results from this work broadly cover topics from remote sensing techniques to the ecology of Great Basin plant communities and are applicable wherever large regions of land are being managed in an era of changing environmental conditions.
NASA Astrophysics Data System (ADS)
Thompson, S. E.; Levy, M. C.
2016-12-01
Quantifying regional water cycle changes resulting from the physical transformation of the earth's surface is essential for water security. Although hydrology has a rich legacy of "paired basin" experiments that identify water cycle responses to imposed land use or land cover change (i) there is a deficit of such studies across many representative biomes worldwide, including the tropics, and (ii) the paired basins generally do not provide a representative sample of regional river systems in a way that can inform policy. Larger sample, empirical analyses are needed for such policy-relevant understanding - and these analyses must be supported by regional data. Northern Brazil is a global agricultural and biodiversity center, where regional climate and hydrology are projected (through modeling) to have strong sensitivities to land cover change. Dramatic land cover change has and continues to occur in this region. We used a causal statistical anlaysis framework to explore the effects of deforestation and land cover conversion on regional hydrology. Firstly, we used a comparative approach to address the `data selection uncertainty' problem associated with rainfall datasets covering this sparsely monitored region. We compared 9 remotely-sensed (RS) and in-situ (IS) rainfall datasets, demonstrating that rainfall characterization and trends were sensitive to the selected data sources and identifying which of these datasets had the strongest fidelity to independently measured streamflow occurrence. Next, we employed a "differences-in-differences" regression technique to evaluate the effects of land use change on the quantiles of the flow duration curve between populations of basins experiencing different levels of land conversion. Regionally, controlling for climate and other variables, deforestation significantly increased flow in the lowest third of the flow duration curve. Addressing this problem required harmonizing 9 separate spatial datasets (in addition to the 9 rainfall datasets originally considered), and relied extensively on the use of newly developed data acquisition and analysis platforms such as Google Earth Engine and Columbia IRI/LDEO. The datasets developed in this project have been made discoverable through collaboration with CUAHSI.
Economic Development and Forest Cover: Evidence from Satellite Data
Crespo Cuaresma, Jesús; Danylo, Olha; Fritz, Steffen; McCallum, Ian; Obersteiner, Michael; See, Linda; Walsh, Brian
2017-01-01
Ongoing deforestation is a pressing, global environmental issue with direct impacts on climate change, carbon emissions, and biodiversity. There is an intuitive link between economic development and overexploitation of natural resources including forests, but this relationship has proven difficult to establish empirically due to both inadequate data and convoluting geo-climactic factors. In this analysis, we use satellite data on forest cover along national borders in order to study the determinants of deforestation differences across countries. Controlling for trans-border geo-climactic differences, we find that income per capita is the most robust determinant of differences in cross-border forest cover. We show that the marginal effect of per capita income growth on forest cover is strongest at the earliest stages of economic development, and weakens in more advanced economies, presenting some of the strongest evidence to date for the existence of at least half of an environmental Kuznets curve for deforestation. PMID:28091593
Economic Development and Forest Cover: Evidence from Satellite Data.
Crespo Cuaresma, Jesús; Danylo, Olha; Fritz, Steffen; McCallum, Ian; Obersteiner, Michael; See, Linda; Walsh, Brian
2017-01-16
Ongoing deforestation is a pressing, global environmental issue with direct impacts on climate change, carbon emissions, and biodiversity. There is an intuitive link between economic development and overexploitation of natural resources including forests, but this relationship has proven difficult to establish empirically due to both inadequate data and convoluting geo-climactic factors. In this analysis, we use satellite data on forest cover along national borders in order to study the determinants of deforestation differences across countries. Controlling for trans-border geo-climactic differences, we find that income per capita is the most robust determinant of differences in cross-border forest cover. We show that the marginal effect of per capita income growth on forest cover is strongest at the earliest stages of economic development, and weakens in more advanced economies, presenting some of the strongest evidence to date for the existence of at least half of an environmental Kuznets curve for deforestation.
Economic Development and Forest Cover: Evidence from Satellite Data
NASA Astrophysics Data System (ADS)
Crespo Cuaresma, Jesús; Danylo, Olha; Fritz, Steffen; McCallum, Ian; Obersteiner, Michael; See, Linda; Walsh, Brian
2017-01-01
Ongoing deforestation is a pressing, global environmental issue with direct impacts on climate change, carbon emissions, and biodiversity. There is an intuitive link between economic development and overexploitation of natural resources including forests, but this relationship has proven difficult to establish empirically due to both inadequate data and convoluting geo-climactic factors. In this analysis, we use satellite data on forest cover along national borders in order to study the determinants of deforestation differences across countries. Controlling for trans-border geo-climactic differences, we find that income per capita is the most robust determinant of differences in cross-border forest cover. We show that the marginal effect of per capita income growth on forest cover is strongest at the earliest stages of economic development, and weakens in more advanced economies, presenting some of the strongest evidence to date for the existence of at least half of an environmental Kuznets curve for deforestation.
NASA Astrophysics Data System (ADS)
Gantumur, Byambakhuu; Wu, Falin; Zhao, Yan; Vandansambuu, Battsengel; Dalaibaatar, Enkhjargal; Itiritiphan, Fareda; Shaimurat, Dauryenbyek
2017-10-01
Urban growth can profoundly alter the urban landscape structure, ecosystem processes, and local climates. Timely and accurate information on the status and trends of urban ecosystems is critical to develop strategies for sustainable development and to improve the urban residential environment and living quality. Ulaanbaatar city was urbanized very rapidly caused by herders and farmers, many of them migrating from rural places, have played a big role in this urban expansion (sprawl). Today, 1.3 million residents for about 40% of total population are living in the Ulaanbaatar region. Those human activities influenced stronger to green environments. Therefore, the aim of this study is determined to change detection of land use/land cover (LULC) and estimating their areas for the trend of future by remote sensing and statistical methods. The implications of analysis were provided by change detection methods of LULC, remote sensing spectral indices including normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and normalized difference built-up index (NDBI). In addition, it can relate to urban heat island (UHI) provided by Land surface temperature (LST) with local climate issues. Statistical methods for image processing used to define relations between those spectral indices and change detection images and regression analysis for time series trend in future. Remote sensing data are used by Landsat (TM/ETM+/OLI) satellite images over the period between 1990 and 2016 by 5 years. The advantages of this study are very useful remote sensing approaches with statistical analysis and important to detecting changes of LULC. The experimental results show that the LULC changes can image on the present and after few years and determined relations between impacts of environmental conditions.
NASA Astrophysics Data System (ADS)
Peneva-Reed, Elitsa I.
This study was designed to gain an understanding of the linkage between development and sustainability of mangrove forest conversion in three coastal communities in Thailand. It presents a methodology that could potentially aid coastal communities in determining sustainable land use conversion approaches by considering the viewpoint of villagers. A remote sensing analysis of Landsat satellite images from 1989, 2001 and 2007 showed the results of a moderate, but sustained shrimp farming industry that only partially exploited mangrove forests. The three villages experienced a range of changes in mangrove forest area. The villagers' perceptions (collected through field surveys) did not match the results from the remote sensing analysis and varied significantly. A logit multiple regression model was utilized to study the factors influencing whether villagers' estimates agreed or disagreed with the remote sensing analysis. Results showed that the only variables statistically significant at the 0.10 level were age, occupation, and proximity to the mangrove resource. There is a widespread belief that one of the main negative effects of the development of shrimp farms is the pollution of water and, as a consequence, the reduction of wild catch. In this study, a majority of fishing households reported a reduction in wild catch, with nearly all attributing it to shrimp farms. A relatively small number of households noted positive effects from shrimp farming and listed these as an increase of income as a result of working at shrimp farms. The most common negative effects identified by the locals were water pollution, followed by a decrease in wild catch, and an increase in the number of mosquitoes. Although shrimp farm developers promised many benefits from this enterprise, very few were realized by the villagers. Integrating information from household surveys with data on land-cover change derived from remote sensing improves our understanding of the causes and processes of land cover change, and the perceptions of such changes. Integrating these two data sources illustrated that while shrimp farms did not have very many positive effects on the villagers, they were not as directly harmful to the mangrove forests as many believed.
Late twentieth century land-cover change in the basin and range ecoregions of the United States
Soulard, Christopher E.; Sleeter, Benjamin M.
2012-01-01
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 km2). 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 km2) in 1973 to 82.6% (578,242 km2) 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.
NASA Astrophysics Data System (ADS)
Tölle, Merja H.; Gutjahr, Oliver; Busch, Gerald; Thiele, Jan C.
2014-03-01
The extent and magnitude of land cover change effect on local and regional future climate during the vegetation period due to different forms of bioenergy plants are quantified for extreme temperatures and energy fluxes. Furthermore, we vary the spatial extent of plant allocation on arable land and simulate alternative availability of transpiration water to mimic both rainfed agriculture and irrigation. We perform climate simulations down to 1 km scale for 1970-1975 C20 and 2070-2075 A1B over Germany with Consortium for Small-Scale Modeling in Climate Mode. Here an impact analysis indicates a strong local influence due to land cover changes. The regional effect is decreased by two thirds of the magnitude of the local-scale impact. The changes are largest locally for irrigated poplar with decreasing maximum temperatures by 1°C in summer months and increasing specific humidity by 0.15 g kg-1. The increased evapotranspiration may result in more precipitation. The increase of surface radiative fluxes Rnet due to changes in latent and sensible heat is estimated by 5 W m-2locally. Moreover, increases in the surface latent heat flux cause strong local evaporative cooling in the summer months, whereas the associated regional cooling effect is pronounced by increases in cloud cover. The changes on a regional scale are marginal and not significant. Increasing bioenergy production on arable land may result in local temperature changes but not in substantial regional climate change in Germany. We show the effect of agricultural practices during climate transitions in spring and fall.
NASA Astrophysics Data System (ADS)
Vatle, S. S.
2015-12-01
Frequent and up-to-date glacier outlines are needed for many applications of glaciology, not only glacier area change analysis, but also for masks in volume or velocity analysis, for the estimation of water resources and as model input data. Remote sensing offers a good option for creating glacier outlines over large areas, but manual correction is frequently necessary, especially in areas containing supraglacial debris. We show three different workflows for mapping clean ice and debris-covered ice within Object Based Image Analysis (OBIA). By working at the object level as opposed to the pixel level, OBIA facilitates using contextual, spatial and hierarchical information when assigning classes, and additionally permits the handling of multiple data sources. Our first example shows mapping debris-covered ice in the Manaslu Himalaya, Nepal. SAR Coherence data is used in combination with optical and topographic data to classify debris-covered ice, obtaining an accuracy of 91%. Our second example shows using a high-resolution LiDAR derived DEM over the Hohe Tauern National Park in Austria. Breaks in surface morphology are used in creating image objects; debris-covered ice is then classified using a combination of spectral, thermal and topographic properties. Lastly, we show a completely automated workflow for mapping glacier ice in Norway. The NDSI and NIR/SWIR band ratio are used to map clean ice over the entire country but the thresholds are calculated automatically based on a histogram of each image subset. This means that in theory any Landsat scene can be inputted and the clean ice can be automatically extracted. Debris-covered ice can be included semi-automatically using contextual and morphological information.
Kweka, Eliningaya J; Kimaro, Epiphania E; Munga, Stephen
2016-01-01
African highlands were known to be free of malaria for the past 50 years. However, the ever growing human population in the highlands of Africa has led to the deforestation and land coverage changes to create space for more land for cultivation, grazing, and house construction materials needs. This has lead to the creation of suitable breeding habitats, which are in open places. Decrease of canopy and forest cover has led to increased temperature both in outdoors and indoors in deforested areas. This increased temperature has resulted in the shortening of developmental stages of aquatic stages of mosquitoes and sporogony development in adult mosquitoes. Assessment of the effects of deforestation and land coverage changes (decrease), which leads to temperature changes and subsequently increases survivorship of adults and sporogony development in adult mosquitoes' body was gathered from previous data collected from 2003 to 2012 using different analysis techniques. Habitats productivity, species dynamics and abundance, mosquitoes feeding rates, and sporogony development are presented in relation to temperature changes. The effects of temperature rise due to land cover changes in highlands of western Kenya on larval developmental rates, adult sporogony developments, and malaria risk in human population were derived. Vector species dynamics and abundance in relation to land use changes have been found to change with time. This study found that, land cover changes is a key driver for the temperature rise in African highlands and increases the rate of malaria vectors Anopheles gambiae ssp., An. Funestus , and An. arabiensis colonizing the highlands. It has also significantly enhanced sporogony development rate and adult vector survival and therefore the risk of malaria transmission in the highlands.
Plant communities on infertile soils are less sensitive to climate change.
Harrison, Susan; Damschen, Ellen; Fernandez-Going, Barbara; Eskelinen, Anu; Copeland, Stella
2015-11-01
Much evidence suggests that plant communities on infertile soils are relatively insensitive to increased water deficit caused by increasing temperature and/or decreasing precipitation. However, a multi-decadal study of community change in the western USA does not support this conclusion. This paper tests explanations related to macroclimatic differences, overstorey effects on microclimate, variation in soil texture and plant functional traits. A re-analysis was undertaken of the changes in the multi-decadal study, which concerned forest understorey communities on infertile (serpentine) and fertile soils in an aridifying climate (southern Oregan) from 1949-1951 to 2007-2008. Macroclimatic variables, overstorey cover and soil texture were used as new covariates. As an alternative measure of climate-related change, the community mean value of specific leaf area was used, a functional trait measuring drought tolerance. We investigated whether these revised analyses supported the prediction of lesser sensitivity to climate change in understorey communities on infertile serpentine soils. Overstorey cover, but not macroclimate or soil texture, was a significant covariate of community change over time. It strongly buffered understorey temperatures, was correlated with less change and averaged >50 % lower on serpentine soils, thereby counteracting the lower climate sensitivity of understorey herbs on these soils. Community mean specific leaf area showed the predicted pattern of less change over time in serpentine than non-serpentine communities. Based on the current balance of evidence, plant communities on infertile serpentine soils are less sensitive to changes in the climatic water balance than communities on more fertile soils. However, this advantage may in some cases be lessened by their sparser overstorey cover. © The Author 2014. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Aleman, Julie C; Blarquez, Olivier; Gourlet-Fleury, Sylvie; Bremond, Laurent; Favier, Charly
2017-01-30
Tree cover is a key variable for ecosystem functioning, and is widely used to study tropical ecosystems. But its determinants and their relative importance are still a matter of debate, especially because most regional and global analyses have not considered the influence of agricultural practices. More information is urgently needed regarding how human practices influence vegetation structure. Here we focused in Central Africa, a region still subjected to traditional agricultural practices with a clear vegetation gradient. Using remote sensing data and global databases, we calibrated a Random Forest model to correlatively link tree cover with climatic, edaphic, fire and agricultural practices data. We showed that annual rainfall and accumulated water deficit were the main drivers of the distribution of tree cover and vegetation classes (defined by the modes of tree cover density), but agricultural practices, especially pastoralism, were also important in determining tree cover. We simulated future tree cover with our model using different scenarios of climate and land-use (agriculture and population) changes. Our simulations suggest that tree cover may respond differently regarding the type of scenarios, but land-use change was an important driver of vegetation change even able to counterbalance the effect of climate change in Central Africa.