Sample records for multi-scale land cover
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Land use/land cover mapping using multi-scale texture processing of high resolution data
Wong, S. N.; Sarker, M. L. R.
2014-02-01
Land use/land cover (LULC) maps are useful for many purposes, and for a long time remote sensing techniques have been used for LULC mapping using different types of data and image processing techniques. In this research, high resolution satellite data from IKONOS was used to perform land use/land cover mapping in Johor Bahru city and adjacent areas (Malaysia). Spatial image processing was carried out using the six texture algorithms (mean, variance, contrast, homogeneity, entropy, and GLDV angular second moment) with five difference window sizes (from 3×3 to 11×11). Three different classifiers i.e. Maximum Likelihood Classifier (MLC), Artificial Neural Network (ANN) and Supported Vector Machine (SVM) were used to classify the texture parameters of different spectral bands individually and all bands together using the same training and validation samples. Results indicated that texture parameters of all bands together generally showed a better performance (overall accuracy = 90.10%) for land LULC mapping, however, single spectral band could only achieve an overall accuracy of 72.67%. This research also found an improvement of the overall accuracy (OA) using single-texture multi-scales approach (OA = 89.10%) and single-scale multi-textures approach (OA = 90.10%) compared with all original bands (OA = 84.02%) because of the complementary information from different bands and different texture algorithms. On the other hand, all of the three different classifiers have showed high accuracy when using different texture approaches, but SVM generally showed higher accuracy (90.10%) compared to MLC (89.10%) and ANN (89.67%) especially for the complex classes such as urban and road.
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Land use/land cover mapping using multi-scale texture processing of high resolution data
International Nuclear Information System (INIS)
Wong, S N; Sarker, M L R
2014-01-01
Land use/land cover (LULC) maps are useful for many purposes, and for a long time remote sensing techniques have been used for LULC mapping using different types of data and image processing techniques. In this research, high resolution satellite data from IKONOS was used to perform land use/land cover mapping in Johor Bahru city and adjacent areas (Malaysia). Spatial image processing was carried out using the six texture algorithms (mean, variance, contrast, homogeneity, entropy, and GLDV angular second moment) with five difference window sizes (from 3×3 to 11×11). Three different classifiers i.e. Maximum Likelihood Classifier (MLC), Artificial Neural Network (ANN) and Supported Vector Machine (SVM) were used to classify the texture parameters of different spectral bands individually and all bands together using the same training and validation samples. Results indicated that texture parameters of all bands together generally showed a better performance (overall accuracy = 90.10%) for land LULC mapping, however, single spectral band could only achieve an overall accuracy of 72.67%. This research also found an improvement of the overall accuracy (OA) using single-texture multi-scales approach (OA = 89.10%) and single-scale multi-textures approach (OA = 90.10%) compared with all original bands (OA = 84.02%) because of the complementary information from different bands and different texture algorithms. On the other hand, all of the three different classifiers have showed high accuracy when using different texture approaches, but SVM generally showed higher accuracy (90.10%) compared to MLC (89.10%) and ANN (89.67%) especially for the complex classes such as urban and road
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Multi-temporal and Dual-polarization Interferometric SAR for Land Cover Type Classification
Directory of Open Access Journals (Sweden)
WANG Xinshuang
2015-05-01
Full Text Available In order to study SAR land cover classification method, this paper uses the multi-dimensional combination of temporal,polarization and InSAR data. The area covered by space borne data of ALOS PALSAR in Xunke County,Heilongjiang Province was chosen as test site. A land cover classification technique of SVM based on multi-temporal, multi-polarization and InSAR data had been proposed, using the sensitivity to land cover type of multi-temporal, multi-polarization SAR data and InSAR measurements, and combing time series characteristic of backscatter coefficient and correlation coefficient to identify ground objects. The results showed the problem of confusion between forest land and urban construction land can be nicely solved, using the correlation coefficient between HH and HV, and also combing the selected temporal, polarization and InSAR characteristics. The land cover classification result with higher accuracy is gotten using the classification algorithm proposed in this paper.
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National Land Cover Database (NLCD) Land Cover Collection
U.S. Geological Survey, Department of the Interior — The National Land Cover Database (NLCD) Land Cover Collection is produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC)...
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GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PROSUCTS
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K. Fukue
2016-06-01
Full Text Available The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a classification target pixel and each classification classes. The global land cover classification experiments have been conducted by applying the proposed classification method using 46 multi-temporal(in one year SR(Surface Reflectance and NBAR(Nadir BRDF-Adjusted Reflectance products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR and NBAR products showed similar classification accuracy of 99%.
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Building a Continental Scale Land Cover Monitoring Framework for Australia
Thankappan, Medhavy; Lymburner, Leo; Tan, Peter; McIntyre, Alexis; Curnow, Steven; Lewis, Adam
2012-04-01
Land cover information is critical for national reporting and decision making in Australia. A review of information requirements for reporting on national environmental indicators identified the need for consistent land cover information to be compared against a baseline. A Dynamic Land Cover Dataset (DLCD) for Australia has been developed by Geoscience Australia and the Australian Bureau of Agriculture and Resource Economics and Sciences (ABARES) recently, to provide a comprehensive and consistent land cover information baseline to enable monitoring and reporting for sustainable farming practices, water resource management, soil erosion, and forests at national and regional scales. The DLCD was produced from the analysis of Enhanced Vegetation Index (EVI) data at 250-metre resolution derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the period from 2000 to 2008. The EVI time series data for each pixel was modelled as 12 coefficients based on the statistical, phenological and seasonal characteristics. The time series were then clustered in coefficients spaces and labelled using ancillary information on vegetation and land use at the catchment scale. The accuracy of the DLCD was assessed using field survey data over 25,000 locations provided by vegetation and land management agencies in State and Territory jurisdictions, and by ABARES. The DLCD is seen as the first in a series of steps to build a framework for national land cover monitoring in Australia. A robust methodology to provide annual updates to the DLCD is currently being developed at Geoscience Australia. There is also a growing demand from the user community for land cover information at better spatial resolution than currently available through the DLCD. Global land cover mapping initiatives that rely on Earth observation data offer many opportunities for national and international programs to work in concert and deliver better outcomes by streamlining efforts on development and
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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.
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Completion of the National Land Cover Database (NLCD) 1992-2001 Land Cover Change Retrofit Product
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 betwe...
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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.
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A high accuracy land use/cover retrieval system
Directory of Open Access Journals (Sweden)
Alaa Hefnawy
2012-03-01
Full Text Available The effects of spatial resolution on the accuracy of mapping land use/cover types have received increasing attention as a large number of multi-scale earth observation data become available. Although many methods of semi automated image classification of remotely sensed data have been established for improving the accuracy of land use/cover classification during the past 40 years, most of them were employed in single-resolution image classification, which led to unsatisfactory results. In this paper, we propose a multi-resolution fast adaptive content-based retrieval system of satellite images. Through our proposed system, we apply a Super Resolution technique for the Landsat-TM images to have a high resolution dataset. The human–computer interactive system is based on modified radial basis function for retrieval of satellite database images. We apply the backpropagation supervised artificial neural network classifier for both the multi and single resolution datasets. The results show significant improved land use/cover classification accuracy for the multi-resolution approach compared with those from single-resolution approach.
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Multi-scale, multi-model assessment of projected land allocation
Vernon, C. R.; Huang, M.; Chen, M.; Calvin, K. V.; Le Page, Y.; Kraucunas, I.
2017-12-01
Effects of land use and land cover change (LULCC) on climate are generally classified into two scale-dependent processes: biophysical and biogeochemical. An extensive amount of research has been conducted related to the impact of each process under alternative climate change futures. However, these studies are generally focused on the impacts of a single process and fail to bridge the gap between sector-driven scale dependencies and any associated dynamics. Studies have been conducted to better understand the relationship of these processes but their respective scale has not adequately captured overall interdependencies between land surface changes and changes in other human-earth systems (e.g., energy, water, economic, etc.). There has also been considerable uncertainty surrounding land use land cover downscaling approaches due to scale dependencies. Demeter, a land use land cover downscaling and change detection model, was created to address this science gap. Demeter is an open-source model written in Python that downscales zonal land allocation projections to the gridded resolution of a user-selected spatial base layer (e.g., MODIS, NLCD, EIA CCI, etc.). Demeter was designed to be fully extensible to allow for module inheritance and replacement for custom research needs, such as flexible IO design to facilitate the coupling of Earth system models (e.g., the Accelerated Climate Modeling for Energy (ACME) and the Community Earth System Model (CESM)) to integrated assessment models (e.g., the Global Change Assessment Model (GCAM)). In this study, we first assessed the sensitivity of downscaled LULCC scenarios at multiple resolutions from Demeter to its parameters by comparing them to historical LULC change data. "Optimal" values of key parameters for each region were identified and used to downscale GCAM-based future scenarios consistent with those in the Land Use Model Intercomparison Project (LUMIP). Demeter-downscaled land use scenarios were then compared to the
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Morrison, Katherine D.
In the Mediterranean ecosystems of coastal California, wildfire is a common disturbance that can significantly alter vegetation in watersheds that transport sediment and nutrients to the adjacent nearshore oceanic environment. We assess the impact of two wildfires that burned in 2008 on land cover and to the nearshore environment along the Big Sur coast in central California. We created a multi-year land cover dataset to assess changes to coastal watersheds as a result of fire. This land cover dataset was then used to model changes in nonpoint source pollutants transported to the nearshore environment. Results indicate post-fire increases in percent export compared to pre-fire years and also link wildfire severity to the specific land cover changes that subsequently increase exports of pollutants and sediment to the nearshore environment. This approach is a replicable across watersheds and also provides a framework for including the nearshore environment as a value at risk terrestrial land management revolving around wildfire, including suppression, thinning, and other activities that change land cover at a landscape scale.
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Hagensieker, Ron; Roscher, Ribana; Rosentreter, Johannes; Jakimow, Benjamin; Waske, Björn
2017-12-01
Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain. The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.
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Mapping of land cover in Northern California with simulated HyspIRI images
Clark, M. L.; Kilham, N. E.
2014-12-01
Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (i.e., full range) of the spectrum have shown improved capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a full-range hyperspectral and thermal satellite being considered for development by NASA (hyspiri.jpl.nasa.gov). A hyperspectral satellite, such as HyspIRI, will provide detailed spectral and temporal information at global scales that could greatly improve our ability to map land cover with greater class detail and spatial and temporal accuracy than possible with conventional multispectral satellites. The broad goal of our research is to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping across a range of environmental and anthropogenic gradients in California. In this study, we mapped FAO Land Cover Classification System (LCCS) classes over 30,000 km2 in Northern California using multi-temporal HyspIRI imagery simulated from the AVIRIS airborne sensor. The Random Forests classification was applied to predictor variables derived from the multi-temporal hyperspectral data and accuracies were compared to that from Landsat 8 OLI. Results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different forest life-form types, such as mixed conifer and broadleaf forests and open- and closed-canopy forests.
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Modelling land change: the issue of use and cover in wide-scale applications
Bakker, M.M.; Veldkamp, A.
2008-01-01
In this article, the underlying causes for the apparent mismatch between land cover and land use in the context of wide-scale land change modelling are explored. A land use-land cover (LU/LC) ratio is proposed as a relevant landscape characteristic. The one-to-one ratio between land use and land
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EnviroAtlas - Paterson, NJ - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The Paterson, New Jersey EnviroAtlas Meter-Scale Urban Land Cover (MULC) data comprises approximately 66 km2 around the city of Paterson. The land cover data were...
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Directory of Open Access Journals (Sweden)
Marina Alberti
2009-12-01
Full Text Available Urbanization and the resulting changes in land cover have myriad impacts on ecological systems. Monitoring these changes across large spatial extents and long time spans requires synoptic remotely sensed data with an appropriate temporal sequence. We developed a multi-temporal land cover dataset for a six-county area surrounding the Seattle, Washington State, USA, metropolitan region. Land cover maps for 1986, 1991, 1995, 1999, and 2002 were developed from Landsat TM images through a combination of spectral unmixing, image segmentation, multi-season imagery, and supervised classification approaches to differentiate an initial nine land cover classes. We then used ancillary GIS layers and temporal information to define trajectories of land cover change through multiple updating and backdating rules and refined our land cover classification for each date into 14 classes. We compared the accuracy of the initial approach with the landscape trajectory modifications and determined that the use of landscape trajectory rules increased our ability to differentiate several classes including bare soil (separated into cleared for development, agriculture, and clearcut forest and three intensities of urban. Using the temporal dataset, we found that between 1986 and 2002, urban land cover increased from 8 to 18% of our study area, while lowland deciduous and mixed forests decreased from 21 to 14%, and grass and agriculture decreased from 11 to 8%. The intensity of urban land cover increased with 252 km2 in Heavy Urban in 1986 increasing to 629 km2 by 2002. The ecological systems that are present in this region were likely significantly altered by these changes in land cover. Our results suggest that multi-temporal (i.e., multiple years and multiple seasons within years Landsat data are an economical means to quantify land cover and land cover change across large and highly heterogeneous urbanizing landscapes. Our data, and similar temporal land cover change
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EnviroAtlas - Des Moines, IA - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The Des Moines, IA EnviroAtlas Meter-Scale Urban Land Cover (MULC) Data were generated from the High Resolution Land Cover (HRLC) product created by the Iowa...
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Generating local scale land use/cover change scenarios: case studies of high-risk mountain areas
Malek, Žiga; Glade, Thomas; Boerboom, Luc
2014-05-01
The relationship between land use/cover changes and consequences to human well-being is well acknowledged and has led to higher interest of both researchers and decision makers in driving forces and consequences of such changes. For example, removal of natural vegetation cover or urban expansion resulting in new elements at risk can increase hydro-meteorological risk. This is why it is necessary to study how the land use/cover could evolve in the future. Emphasis should especially be given to areas experiencing, or expecting, high rates of socio-economic change. A suitable approach to address these changes is scenario development; it offers exploring possible futures and the corresponding environmental consequences, and aids decision-making, as it enables to analyse possible options. Scenarios provide a creative methodology to depict possible futures, resulting from existing decisions, based on different assumptions of future socio-economic development. They have been used in various disciplines and on various scales, such as flood risk and soil erosion. Several studies have simulated future scenarios of land use/cover changes at a very high success rate, however usually these approaches are tailor made for specific case study areas and fit to available data. This study presents a multi-step scenario generation framework, which can be transferable to other local scale case study areas, taking into account the case study specific consequences of land use/cover changes. Through the use of experts' and decision-makers' knowledge, we aimed to develop a framework with the following characteristics: (1) it enables development of scenarios that are plausible, (2) it can overcome data inaccessibility, (3) it can address intangible and external driving forces of land use/cover change, and (4) it ensures transferability to other local scale case study areas with different land use/cover change processes and consequences. To achieve this, a set of different methods is applied
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International Nuclear Information System (INIS)
Lin, D H; Johnson, D R; Tweedie, C E; Andresen, C
2012-01-01
Analysis of time series imagery from satellite and aircraft platforms is useful for detecting land cover change at plot to regional scales. In this study, we created multi-temporal high spatial resolution land cover maps for seven locations in the Beringian Arctic and assessed the change in land cover over time. Land cover classifications were site specific and mostly aligned with a soil moisture gradient. Time series varied between 60 and 21 years. Four of the five landscapes studied in Alaska underwent an expansion of drier land cover classes while the two landscapes studies in Chukotka, Russia showed an expansion of wetter land cover types. While a range of land cover types was present across the landscapes studied, the extent of shrubs (in Chukotka) and open water (in Alaska) increased in all landscapes where these land cover types were present. The results support trends documented for regional change in NDVI (a measure of vegetation greenness and productivity) as well as a host of other long term, experimental and modeling studies. Using historic change trends for each land cover type at each landscape, we use a simple probabilistic vegetation model to establish hypotheses of future change trajectories for different land cover types at each of the landscapes investigated. This study is a contribution to the International Polar Year Back to the Future project (IPY-BTF). (letter)
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CORINE land cover and floristic variation in a Mediterranean wetland.
Giallonardo, Tommaso; Landi, Marco; Frignani, Flavio; Geri, Francesco; Lastrucci, Lorenzo; Angiolini, Claudia
2011-11-01
The aims of the present study were to: (1) investigate whether CORINE land cover classes reflect significant differences in floristic composition, using a very detailed CORINE land cover map (scale 1:5000); (2) decompose the relationships between floristic assemblages and three groups of explanatory variables (CORINE land cover classes, environmental characteristics and spatial structure) into unique and interactive components. Stratified sampling was used to select a set of 100-m(2) plots in each land cover class identified in the semi-natural wetland surrounding a lake in central Italy. The following six classes were considered: stable meadows, deciduous oak dominated woods, hygrophilous broadleaf dominated woods, heaths and shrublands, inland swamps, canals or watercourses. The relationship between land cover classes and floristic composition was tested using several statistical techniques in order to determine whether the results remained consistent with different procedures. The variation partitioning approach was applied to identify the relative importance of three groups of explanatory variables in relation to floristic variation. The most important predictor was land cover, which explained 20.7% of the variation in plant distribution, although the hypothesis that each land cover class could be associated with a particular floristic pattern was not verified. Multi Response Permutation Analysis did not indicate a strong floristic separability between land cover classes and only 9.5% of species showed a significant indicator value for a specific land cover class. We suggest that land cover classes linked with hygrophilous and herbaceous communities in a wetland may have floristic patterns that vary with fine scale and are not compatible with a land cover map.
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Image Fusion-Based Land Cover Change Detection Using Multi-Temporal High-Resolution Satellite Images
Directory of Open Access Journals (Sweden)
Biao Wang
2017-08-01
Full Text Available Change detection is usually treated as a problem of explicitly detecting land cover transitions in satellite images obtained at different times, and helps with emergency response and government management. This study presents an unsupervised change detection method based on the image fusion of multi-temporal images. The main objective of this study is to improve the accuracy of unsupervised change detection from high-resolution multi-temporal images. Our method effectively reduces change detection errors, since spatial displacement and spectral differences between multi-temporal images are evaluated. To this end, a total of four cross-fused images are generated with multi-temporal images, and the iteratively reweighted multivariate alteration detection (IR-MAD method—a measure for the spectral distortion of change information—is applied to the fused images. In this experiment, the land cover change maps were extracted using multi-temporal IKONOS-2, WorldView-3, and GF-1 satellite images. The effectiveness of the proposed method compared with other unsupervised change detection methods is demonstrated through experimentation. The proposed method achieved an overall accuracy of 80.51% and 97.87% for cases 1 and 2, respectively. Moreover, the proposed method performed better when differentiating the water area from the vegetation area compared to the existing change detection methods. Although the water area beneath moderate and sparse vegetation canopy was captured, vegetation cover and paved regions of the water body were the main sources of omission error, and commission errors occurred primarily in pixels of mixed land use and along the water body edge. Nevertheless, the proposed method, in conjunction with high-resolution satellite imagery, offers a robust and flexible approach to land cover change mapping that requires no ancillary data for rapid implementation.
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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
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Xu, Z.; Guan, K.; Peng, B.; Casler, N. P.; Wang, S. W.
2017-12-01
Landscape has complex three-dimensional features. These 3D features are difficult to extract using conventional methods. Small-footprint LiDAR provides an ideal way for capturing these features. Existing approaches, however, have been relegated to raster or metric-based (two-dimensional) feature extraction from the upper or bottom layer, and thus are not suitable for resolving morphological and intensity features that could be important to fine-scale land cover mapping. Therefore, this research combines airborne LiDAR and multi-temporal Landsat imagery to classify land cover types of Williamson County, Illinois that has diverse and mixed landscape features. Specifically, we applied a 3D convolutional neural network (CNN) method to extract features from LiDAR point clouds by (1) creating occupancy grid, intensity grid at 1-meter resolution, and then (2) normalizing and incorporating data into a 3D CNN feature extractor for many epochs of learning. The learned features (e.g., morphological features, intensity features, etc) were combined with multi-temporal spectral data to enhance the performance of land cover classification based on a Support Vector Machine classifier. We used photo interpretation for training and testing data generation. The classification results show that our approach outperforms traditional methods using LiDAR derived feature maps, and promises to serve as an effective methodology for creating high-quality land cover maps through fusion of complementary types of remote sensing data.
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International Nuclear Information System (INIS)
Tudesque, Loïc; Tisseuil, Clément; Lek, Sovan
2014-01-01
The scale dependence of ecological phenomena remains a central issue in ecology. Particularly in aquatic ecology, the consideration of the accurate spatial scale in assessing the effects of landscape factors on stream condition is critical. In this context, our study aimed at assessing the relationships between multi-spatial scale land cover patterns and a variety of water quality and diatom metrics measured at the stream reach level. This investigation was conducted in a major European river system, the Adour-Garonne river basin, characterized by a wide range of ecological conditions. Redundancy analysis (RDA) and variance partitioning techniques were used to disentangle the different relationships between land cover, water-chemistry and diatom metrics. Our results revealed a top-down “cascade effect” indirectly linking diatom metrics to land cover patterns through water physico-chemistry, which occurred at the largest spatial scales. In general, the strength of the relationships between land cover, physico-chemistry, and diatoms was shown to increase with the spatial scale, from the local to the basin scale, emphasizing the importance of continuous processes of accumulation throughout the river gradient. Unexpectedly, we established that the influence of land cover on the diatom metric was of primary importance both at the basin and local scale, as a result of discontinuous but not necessarily antagonist processes. The most detailed spatial grain of the Corine land cover classification appeared as the most relevant spatial grain to relate land cover to water chemistry and diatoms. Our findings provide suitable information to improve the implementation of effective diatom-based monitoring programs, especially within the scope of the European Water Framework Directive. - Highlights: •The spatial scale dependence of the “cascade effect” in a river system has been demonstrated. •The strength of the relationships between land cover and diatoms through
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Dewitt, Jessica D.; Chirico, Peter G.; Bergstresser, Sarah E.; Warner, Timothy A.
2017-01-01
The town of Tortiya was created in the rural northern region of Côte d′Ivoire in the late 1940s to house workers for a new diamond mine. Nearly three decades later, the closure of the industrial-scale diamond mine in 1975 did not diminish the importance of diamond profits to the region's economy, and resulted in the growth of artisanal and small-scale diamond mining (ASM) within the abandoned industrial-scale mining concession. In the early 2000s, the violent conflict that arose in Côte d′Ivoire highlighted the importance of ASM land use to the local economy, but also brought about international concerns that diamond profits were being used to fund the rebellion. In recent years, cashew plantations have expanded exponentially in the region, diversifying economic activity, but also creating the potential for conflict between diamond mining and agricultural land uses. As the government looks to address the future of Tortiya and this potential conflict, a detailed spatio-temporal understanding of the changes in these two land uses over time may assist in informing policymaking. Remotely sensed imagery presents an objective and detailed spatial record of land use/land cover (LULC), and change detection methods can provide quantitative insight regarding regional land cover trends. However, the vastly different scales of ASM and cashew orchards present a unique challenge to comprehensive understanding of land use change in the region. In this study, moderate-scale categories of LULC, including cashew orchards, uncultivated forest, urban space, mining/ bare, and mixed vegetation, were produced through supervised classification of Landsat multispectral imagery from 1984, 1991, 2000, 2007, and 2014. The fine-scale ASM land use was identified through manual interpretation of annually acquired high resolution satellite imagery. Corona imagery was also integrated into the study to extend the temporal duration of the remote sensing record back to the period of industrial-scale
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Border Lakes land-cover classification
Marvin Bauer; Brian Loeffelholz; Doug. Shinneman
2009-01-01
This document contains metadata and description of land-cover classification of approximately 5.1 million acres of land bordering Minnesota, U.S.A. and Ontario, Canada. The classification focused on the separation and identification of specific forest-cover types. Some separation of the nonforest classes also was performed. The classification was derived from multi-...
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A multi-temporal analysis approach for land cover mapping in support of nuclear incident response
Sah, Shagan; van Aardt, Jan A. N.; McKeown, Donald M.; Messinger, David W.
2012-06-01
Remote sensing can be used to rapidly generate land use maps for assisting emergency response personnel with resource deployment decisions and impact assessments. In this study we focus on constructing accurate land cover maps to map the impacted area in the case of a nuclear material release. The proposed methodology involves integration of results from two different approaches to increase classification accuracy. The data used included RapidEye scenes over Nine Mile Point Nuclear Power Station (Oswego, NY). The first step was building a coarse-scale land cover map from freely available, high temporal resolution, MODIS data using a time-series approach. In the case of a nuclear accident, high spatial resolution commercial satellites such as RapidEye or IKONOS can acquire images of the affected area. Land use maps from the two image sources were integrated using a probability-based approach. Classification results were obtained for four land classes - forest, urban, water and vegetation - using Euclidean and Mahalanobis distances as metrics. Despite the coarse resolution of MODIS pixels, acceptable accuracies were obtained using time series features. The overall accuracies using the fusion based approach were in the neighborhood of 80%, when compared with GIS data sets from New York State. The classifications were augmented using this fused approach, with few supplementary advantages such as correction for cloud cover and independence from time of year. We concluded that this method would generate highly accurate land maps, using coarse spatial resolution time series satellite imagery and a single date, high spatial resolution, multi-spectral image.
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Energy Technology Data Exchange (ETDEWEB)
Willingham, Alison N.; /Ohio State U.
2008-01-01
Statewide surveys of furbearers in Illinois indicate gray (Urocyon cinereoargenteus) and red (Vulpes vulpes) foxes have experienced substantial declines in relative abundance, whereas other species such as raccoons (Procyon lotor) and coyotes (Canis latrans) have exhibited dramatic increases during the same time period. The cause of the declines of gray and red foxes has not been identified, and the current status of gray foxes remains uncertain. Therefore, I conducted a large-scale predator survey and tracked radiocollared gray foxes from 2004 to 2007 in order to determine the distribution, survival, cause-specific mortality sources and land cover associations of gray foxes in an urbanized region of northeastern Illinois, and examined the relationships between the occurrence of gray fox and the presence other species of mesopredators, specifically coyotes and raccoons. Although generalist mesopredators are common and can reach high densities in many urban areas their urban ecology is poorly understood due to their secretive nature and wariness of humans. Understanding how mesopredators utilize urbanized landscapes can be useful in the management and control of disease outbreaks, mitigation of nuisance wildlife issues, and gaining insight into how mesopredators shape wildlife communities in highly fragmented areas. I examined habitat associations of raccoons, opossums (Didelphis virginiana), domestic cats (Felis catus), coyotes, foxes (gray and red), and striped skunks (Mephitis mephitis) at multiple spatial scales in an urban environment. Gray fox occurrence was rare and widely dispersed, and survival estimates were similar to other studies. Gray fox occurrence was negatively associated with natural and semi-natural land cover types. Fox home range size increased with increasing urban development suggesting that foxes may be negatively influenced by urbanization. Gray fox occurrence was not associated with coyote or raccoon presence. However, spatial avoidance and
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Integrated modelling of anthropogenic land-use and land-cover change on the global scale
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
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Land use/land cover and scale influences on in-stream nitrogen uptake kinetics
Covino, Tim; McGlynn, Brian; McNamara, Rebecca
2012-06-01
Land use/land cover change often leads to increased nutrient loading to streams; however, its influence on stream ecosystem nutrient transport remains poorly understood. Given the deleterious impacts elevated nutrient loading can have on aquatic ecosystems, it is imperative to improve understanding of nutrient retention capacities across stream scales and watershed development gradients. We performed 17 nutrient addition experiments on six streams across the West Fork Gallatin Watershed, Montana, USA, to quantify nitrogen uptake kinetics and retention dynamics across stream sizes (first to fourth order) and along a watershed development gradient. We observed that stream nitrogen (N) uptake kinetics and spiraling parameters varied across streams of different development intensity and scale. In more developed watersheds we observed a fertilization affect. This fertilization affect was evident as increased ash-free dry mass, chlorophylla, and ambient and maximum uptake rates in developed as compared to undeveloped streams. Ash-free dry mass, chlorophylla, and the number of structures in a subwatershed were significantly correlated to nutrient spiraling and kinetic parameters, while ambient and average annual N concentrations were not. Additionally, increased maximum uptake capacities in developed streams contributed to low in-stream nutrient concentrations during the growing season, and helped maintain watershed export at low levels during base flow. Our results indicate that land use/land cover change can enhance in-stream uptake of limiting nutrients and highlight the need for improved understanding of the watershed dynamics that control nutrient export across scales and development intensities for mitigation and protection of aquatic ecosystems.
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Land-Atmosphere Coupling in the Multi-Scale Modelling Framework
Kraus, P. M.; Denning, S.
2015-12-01
The Multi-Scale Modeling Framework (MMF), in which cloud-resolving models (CRMs) are embedded within general circulation model (GCM) gridcells to serve as the model's cloud parameterization, has offered a number of benefits to GCM simulations. The coupling of these cloud-resolving models directly to land surface model instances, rather than passing averaged atmospheric variables to a single instance of a land surface model, the logical next step in model development, has recently been accomplished. This new configuration offers conspicuous improvements to estimates of precipitation and canopy through-fall, but overall the model exhibits warm surface temperature biases and low productivity.This work presents modifications to a land-surface model that take advantage of the new multi-scale modeling framework, and accommodate the change in spatial scale from a typical GCM range of ~200 km to the CRM grid-scale of 4 km.A parameterization is introduced to apportion modeled surface radiation into direct-beam and diffuse components. The diffuse component is then distributed among the land-surface model instances within each GCM cell domain. This substantially reduces the number excessively low light values provided to the land-surface model when cloudy conditions are modeled in the CRM, associated with its 1-D radiation scheme. The small spatial scale of the CRM, ~4 km, as compared with the typical ~200 km GCM scale, provides much more realistic estimates of precipitation intensity, this permits the elimination of a model parameterization of canopy through-fall. However, runoff at such scales can no longer be considered as an immediate flow to the ocean. Allowing sub-surface water flow between land-surface instances within the GCM domain affords better realism and also reduces temperature and productivity biases.The MMF affords a number of opportunities to land-surface modelers, providing both the advantages of direct simulation at the 4 km scale and a much reduced
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Mekong Land Cover Dasboard: Regional Land Cover Mointoring Systems
Saah, D. S.; Towashiraporn, P.; Aekakkararungroj, A.; Phongsapan, K.; Triepke, J.; Maus, P.; Tenneson, K.; Cutter, P. G.; Ganz, D.; Anderson, E.
2016-12-01
SERVIR-Mekong, a USAID-NASA partnership, helps decision makers in the Lower Mekong Region utilize GIS and Remote Sensing information to inform climate related activities. In 2015, SERVIR-Mekong conducted a geospatial needs assessment for the Lower Mekong countries which included individual country consultations. The team found that many countries were dependent on land cover and land use maps for land resource planning, quantifying ecosystem services, including resilience to climate change, biodiversity conservation, and other critical social issues. Many of the Lower Mekong countries have developed national scale land cover maps derived in part from remote sensing products and geospatial technologies. However, updates are infrequent and classification systems do not always meet the needs of key user groups. In addition, data products stop at political boundaries and are often not accessible making the data unusable across country boundaries and with resource management partners. Many of these countries rely on global land cover products to fill the gaps of their national efforts, compromising consistency between data and policies. These gaps in national efforts can be filled by a flexible regional land cover monitoring system that is co-developed by regional partners with the specific intention of meeting national transboundary needs, for example including consistent forest definitions in transboundary watersheds. Based on these facts, key regional stakeholders identified a need for a land cover monitoring system that will produce frequent, high quality land cover maps using a consistent regional classification scheme that is compatible with national country needs. SERVIR-Mekong is currently developing a solution that leverages recent developments in remote sensing science and technology, such as Google Earth Engine (GEE), and working together with production partners to develop a system that will use a common set of input data sources to generate high
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The National Land Cover Database
Homer, Collin G.; Fry, Joyce A.; Barnes, Christopher A.
2012-01-01
The National Land Cover Database (NLCD) serves as the definitive Landsat-based, 30-meter resolution, land cover database for the Nation. NLCD provides spatial reference and descriptive data for characteristics of the land surface such as thematic class (for example, urban, agriculture, and forest), percent impervious surface, and percent tree canopy cover. NLCD supports a wide variety of Federal, State, local, and nongovernmental applications that seek to assess ecosystem status and health, understand the spatial patterns of biodiversity, predict effects of climate change, and develop land management policy. NLCD products are created by the Multi-Resolution Land Characteristics (MRLC) Consortium, a partnership of Federal agencies led by the U.S. Geological Survey. All NLCD data products are available for download at no charge to the public from the MRLC Web site: http://www.mrlc.gov.
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EnviroAtlas - Green Bay, WI - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The Green Bay, WI Meter-Scale Urban Land Cover (MULC) dataset comprises 936 km2 around the city of Green Bay, surrounding towns, tribal lands and rural areas in...
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Loperfido, J. V.; Noe, Gregory B.; Jarnagin, S. Taylor; Hogan, Dianna M.
2014-11-01
Urban stormwater runoff remains an important issue that causes local and regional-scale water quantity and quality issues. Stormwater best management practices (BMPs) have been widely used to mitigate runoff issues, traditionally in a centralized manner; however, problems associated with urban hydrology have remained. An emerging trend is implementation of BMPs in a distributed manner (multi-BMP treatment trains located on the landscape and integrated with urban design), but little catchment-scale performance of these systems have been reported to date. Here, stream hydrologic data (March, 2011-September, 2012) are evaluated in four catchments located in the Chesapeake Bay watershed: one utilizing distributed stormwater BMPs, two utilizing centralized stormwater BMPs, and a forested catchment serving as a reference. Among urban catchments with similar land cover, geology and BMP design standards (i.e. 100-year event), but contrasting placement of stormwater BMPs, distributed BMPs resulted in: significantly greater estimated baseflow, a higher minimum precipitation threshold for stream response and maximum discharge increases, better maximum discharge control for small precipitation events, and reduced runoff volume during an extreme (1000-year) precipitation event compared to centralized BMPs. For all catchments, greater forest land cover and less impervious cover appeared to be more important drivers than stormwater BMP spatial pattern, and caused lower total, stormflow, and baseflow runoff volume; lower maximum discharge during typical precipitation events; and lower runoff volume during an extreme precipitation event. Analysis of hydrologic field data in this study suggests that both the spatial distribution of stormwater BMPs and land cover are important for management of urban stormwater runoff. In particular, catchment-wide application of distributed BMPs improved stream hydrology compared to centralized BMPs, but not enough to fully replicate forested
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Loperfido, John V.; Noe, Gregory B.; Jarnagin, S. Taylor; Hogan, Dianna M.
2014-01-01
Urban stormwater runoff remains an important issue that causes local and regional-scale water quantity and quality issues. Stormwater best management practices (BMPs) have been widely used to mitigate runoff issues, traditionally in a centralized manner; however, problems associated with urban hydrology have remained. An emerging trend is implementation of BMPs in a distributed manner (multi-BMP treatment trains located on the landscape and integrated with urban design), but little catchment-scale performance of these systems have been reported to date. Here, stream hydrologic data (March, 2011–September, 2012) are evaluated in four catchments located in the Chesapeake Bay watershed: one utilizing distributed stormwater BMPs, two utilizing centralized stormwater BMPs, and a forested catchment serving as a reference. Among urban catchments with similar land cover, geology and BMP design standards (i.e. 100-year event), but contrasting placement of stormwater BMPs, distributed BMPs resulted in: significantly greater estimated baseflow, a higher minimum precipitation threshold for stream response and maximum discharge increases, better maximum discharge control for small precipitation events, and reduced runoff volume during an extreme (1000-year) precipitation event compared to centralized BMPs. For all catchments, greater forest land cover and less impervious cover appeared to be more important drivers than stormwater BMP spatial pattern, and caused lower total, stormflow, and baseflow runoff volume; lower maximum discharge during typical precipitation events; and lower runoff volume during an extreme precipitation event. Analysis of hydrologic field data in this study suggests that both the spatial distribution of stormwater BMPs and land cover are important for management of urban stormwater runoff. In particular, catchment-wide application of distributed BMPs improved stream hydrology compared to centralized BMPs, but not enough to fully replicate forested
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Ghosh, A.; Smith, J. C.; Hijmans, R. J.
2017-12-01
Since mid-1990s, the Cambodian government granted nearly 300 `Economic Land Concessions' (ELCs), occupying approximately 2.3 million ha to foreign and domestic organizations (primarily agribusinesses). The majority of Cambodian ELC deals have been issued in areas of both relatively low population density and low agricultural productivity, dominated by smallholder production. These regions often contain highly biodiverse areas, thereby increasing the ecological cost associated with land clearing for extractive purposes. These large-scale land transactions have also resulted in substantial and rapid changes in land-use patterns and agriculture practices by smallholder farmers. In this study, we investigated the spatio-temporal characteristics of land use change associated with large-scale land transactions across Cambodia using multi-temporal multi-reolution remote sensing data. We identified major regions of deforestation during the last two decades using Landsat archive, global forest change data (2000-2014) and georeferenced database of ELC deals. We then mapped the deforestation and land clearing within ELC boundaries as well as areas bordering or near ELCs to quantify the impact of ELCs on local communities. Using time-series from MODIS Vegetation Indices products for the study period, we also estimated the time period over which any particular ELC deal initiated its proposed activity. We found evidence of similar patterns of land use change outside the boundaries of ELC deals which may be associated with i) illegal land encroachments by ELCs and/or ii) new agricultural practices adopted by local farmers near ELC boundaries. We also detected significant time gaps between ELC deal granting dates and initiation of land clearing for ELC purposes. Interestingly, we also found that not all designated areas for ELCs were put into effect indicating the possible proliferation of speculative land deals. This study demonstrates the potential of remote sensing techniques
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Clark, M. L.; Kilham, N. E.
2015-12-01
Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Most land-cover maps at regional to global scales are produced with remote sensing techniques applied to multispectral satellite imagery with 30-500 m pixel sizes (e.g., Landsat, MODIS). Hyperspectral, or imaging spectrometer, imagery measuring the visible to shortwave infrared regions (VSWIR) of the spectrum have shown impressive capacity to map plant species and coarser land-cover associations, yet techniques have not been widely tested at regional and greater spatial scales. The Hyperspectral Infrared Imager (HyspIRI) mission is a VSWIR hyperspectral and thermal satellite being considered for development by NASA. The goal of this study was to assess multi-temporal, HyspIRI-like satellite imagery for improved land cover mapping relative to multispectral satellites. We mapped FAO Land Cover Classification System (LCCS) classes over 22,500 km2 in the San Francisco Bay Area, California using 30-m HyspIRI, Landsat 8 and Sentinel-2 imagery simulated from data acquired by NASA's AVIRIS airborne sensor. Random Forests (RF) and Multiple-Endmember Spectral Mixture Analysis (MESMA) classifiers were applied to the simulated images and accuracies were compared to those from real Landsat 8 images. The RF classifier was superior to MESMA, and multi-temporal data yielded higher accuracy than summer-only data. With RF, hyperspectral data had overall accuracy of 72.2% and 85.1% with full 20-class and reduced 12-class schemes, respectively. Multispectral imagery had lower accuracy. For example, simulated and real Landsat data had 7.5% and 4.6% lower accuracy than HyspIRI data with 12 classes, respectively. In summary, our results indicate increased mapping accuracy using HyspIRI multi-temporal imagery, particularly in discriminating different natural vegetation types, such as
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EnviroAtlas - Pittsburgh, PA - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The EnviroAtlas Pittsburgh, PA Meter-Scale Urban Land Cover (MULC) data was generated from United States Department of Agriculture (USDA) National Agricultural...
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EnviroAtlas - Austin, TX - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The Austin, TX EnviroAtlas One Meter-scale Urban Land Cover (MULC) Data were generated from United States Department of Agriculture (USDA) National Agricultural...
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Directory of Open Access Journals (Sweden)
Y. Setiawan
2012-07-01
Full Text Available Remote sensing has long been used as a means of detecting and classifying changes on the land. Analysis of multi-year time series of land surface attributes and their seasonal change indicates a complexity of land use land cover change (LULCC. This paper explores the temporal complexity of land change considering temporal vegetation dynamics, in other words, distinguishing the changes regarding to their properties in long-term image analysis. This study is based on the hypothesis that land cover might be dynamics; however, consistent land use has a typical, distinct and repeated temporal pattern of vegetation index inter-annually. Therefore, pixels represent a change when the inter-annual temporal dynamics is changed. We analysed the dynamics pattern of long-term image data of wavelet-filtered MODIS EVI from 2001 to 2007. The change of temporal vegetation dynamics was detected by differentiating distance between two successive annual EVI patterns. Moreover, we defined the type of changes using the clustering method, which were then validated by ground check points and secondary data sets.
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Green Infrastructure and Watershed-Scale Hydrology in a Mixed Land Cover System
Hoghooghi, N.; Golden, H. E.; Bledsoe, B. P.
2017-12-01
Urbanization results in replacement of pervious areas (e.g., vegetation, topsoil) with impervious surfaces such as roads, roofs, and parking lots, which cause reductions in interception, evapotranspiration, and infiltration, and increases in surface runoff (overland flow) and pollutant loads and concentrations. Research on the effectiveness of different Green Infrastructure (GI), or Low Impact Development (LID), practices to reduce these negative impacts on stream flow and water quality has been mostly focused at the local scale (e.g., plots, small catchments). However, limited research has considered the broader-scale effects of LID, such as how LID practices influence water quantity, nutrient removal, and aquatic ecosystems at watershed scales, particularly in mixed land cover and land use systems. We use the Visualizing Ecosystem Land Management Assessments (VELMA) model to evaluate the effects of different LID practices on daily and long-term watershed-scale hydrology, including infiltration surface runoff. We focus on Shayler Crossing (SHC) watershed, a mixed land cover (61% urban, 24% agriculture, 15% forest) subwatershed of the East Fork Little Miami River watershed, Ohio, United States, with a drainage area of 0.94 km2. The model was calibrated to daily stream flow at the outlet of SHC watershed from 2009 to 2010 and was applied to evaluate diverse distributions (at 25% to 100% implementation levels) and types (e.g., pervious pavement and rain gardens) of LID across the watershed. Results show reduced surface water runoff and higher rates of infiltration concomitant with increasing LID implementation levels; however, this response varies between different LID practices. The highest magnitude response in streamflow at the watershed outlet is evident when a combination of LID practices is applied. The combined scenarios elucidate that the diverse watershed-scale hydrological responses of LID practices depend primarily on the type and extent of the implemented
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EnviroAtlas - Portland, ME - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The EnviroAtlas Portland, ME Meter-Scale Urban Land Cover (MULC) data was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green,...
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EnviroAtlas - Fresno, CA - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The Fresno, CA EnviroAtlas Meter-Scale Urban Land Cover (MULC) Data were generated via supervised classification of combined aerial photography and LiDAR data. The...
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EnviroAtlas - Tampa, FL - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The EnviroAtlas Tampa, FL Meter-Scale Urban Land Cover (MULC) data was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue...
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EnviroAtlas - Portland, OR - Meter-Scale Urban Land Cover (MULC) Data (2012)
U.S. Environmental Protection Agency — The EnviroAtlas Portland, OR Meter-Scale Urban Land Cover (MULC) dataset includes data for the Portland metropolitan area plus the city of Vancouver, Washington and...
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EnviroAtlas - Woodbine, IA - Meter-Scale Urban Land Cover (MULC) Data (2011)
U.S. Environmental Protection Agency — The EnviroAtlas Woodbine, IA Meter-Scale Urban Land Cover (MULC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red,...
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EnviroAtlas - Phoenix, AZ - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The EnviroAtlas Phoenix, AZ Meter-Scale Urban Land Cover (MULC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red,...
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EnviroAtlas - Durham, NC - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The EnviroAtlas Durham, NC Meter-Scale Urban Land Cover (MULC) data was generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green, blue...
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EnviroAtlas - Memphis, TN - Meter-Scale Urban Land Cover (MULC) Data (2012)
U.S. Environmental Protection Agency — The Memphis, TN EnviroAtlas One Meter-scale Urban Land Cover (MULC) dataset comprises 2,733 km2 around the city of Memphis, surrounding towns, and rural areas. These...
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Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei
2018-06-01
Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.
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EnviroAtlas - New Bedford, MA - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The New Bedford, MA Meter-Scale Urban Land Cover (MULC) data were generated from United States Department of Agriculture (USDA) National Agricultural Imagery Program...
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GlobeLand30 as an alternative fine-scale global land cover map
DEFF Research Database (Denmark)
Jokar Arsanjani, Jamal; Tayyebi, A.; Vaz, E.
2016-01-01
land cover information such as developing countries. In this study, we look at GlobeLand30 of 2010 for Iran in order to find out the accuracy of this dataset as well as its implications. By having looked at 6 selected study sites around larger cities representing dissimilar eco-regions covering rural...
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EnviroAtlas - New York, NY - Meter-Scale Urban Land Cover (MULC) Data (2008)
U.S. Environmental Protection Agency — The New York, NY EnviroAtlas Meter-scale Urban Land Cover (MULC) Data were generated by the University of Vermont Spatial Analysis Laboratory (SAL) under the...
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Directory of Open Access Journals (Sweden)
Brian A. Johnson
2015-10-01
Full Text Available Much remote sensing (RS research focuses on fusing, i.e., combining, multi-resolution/multi-sensor imagery for land use/land cover (LULC classification. In relation to this topic, Sun and Schulz [1] recently found that a combination of visible-to-near infrared (VNIR; 30 m spatial resolution and thermal infrared (TIR; 100–120 m spatial resolution Landsat data led to more accurate LULC classification. They also found that using multi-temporal TIR data alone for classification resulted in comparable (and in some cases higher classification accuracies to the use of multi-temporal VNIR data, which contrasts with the findings of other recent research [2]. This discrepancy, and the generally very high LULC accuracies achieved by Sun and Schulz (up to 99.2% overall accuracy for a combined VNIR/TIR classification result, can likely be explained by their use of an accuracy assessment procedure which does not take into account the multi-resolution nature of the data. Sun and Schulz used 10-fold cross-validation for accuracy assessment, which is not necessarily inappropriate for RS accuracy assessment in general. However, here it is shown that the typical pixel-based cross-validation approach results in non-independent training and validation data sets when the lower spatial resolution TIR images are used for classification, which causes classification accuracy to be overestimated.
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Land Cover - Minnesota Land Cover Classification System
Minnesota Department of Natural Resources — Land cover data set based on the Minnesota Land Cover Classification System (MLCCS) coding scheme. This data was produced using a combination of aerial photograph...
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Clustering of Multi-Temporal Fully Polarimetric L-Band SAR Data for Agricultural Land Cover Mapping
Tamiminia, H.; Homayouni, S.; Safari, A.
2015-12-01
Recently, the unique capabilities of Polarimetric Synthetic Aperture Radar (PolSAR) sensors make them an important and efficient tool for natural resources and environmental applications, such as land cover and crop classification. The aim of this paper is to classify multi-temporal full polarimetric SAR data using kernel-based fuzzy C-means clustering method, over an agricultural region. This method starts with transforming input data into the higher dimensional space using kernel functions and then clustering them in the feature space. Feature space, due to its inherent properties, has the ability to take in account the nonlinear and complex nature of polarimetric data. Several SAR polarimetric features extracted using target decomposition algorithms. Features from Cloude-Pottier, Freeman-Durden and Yamaguchi algorithms used as inputs for the clustering. This method was applied to multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Canada, during June and July in 2012. The results demonstrate the efficiency of this approach with respect to the classical methods. In addition, using multi-temporal data in the clustering process helped to investigate the phenological cycle of plants and significantly improved the performance of agricultural land cover mapping.
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South African National Land-Cover Change Map
African Journals Online (AJOL)
Fritz Schoeman
monitoring land-cover change at a national scale over time using EO data. 2. .... assist with final results reporting and analysis on a sub-national level. ..... South African Land-Cover Characteristics Database: A synopsis of the landscape.
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Dar A. Robertsa; Michael Keller; Joao Vianei Soares
2003-01-01
We summarize early research on land-cover, land-use, and biophysical properties of vegetation from the Large Scale Biosphere Atmosphere (LBA) experiment in AmazoËnia. LBA is an international research program developed to evaluate regional function and to determine how land-use and climate modify biological, chemical and physical processes there. Remote sensing has...
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Energy Technology Data Exchange (ETDEWEB)
Pinho, P.; Augusto, S.; Maguas, C. [Universidade de Lisboa, Faculdade de Ciencias, Centro de Ecologia e Biologia Vegetal (CEBV), 1749-016 Lisbon (Portugal); Pereira, M.J.; Soares, A. [Universidade Tecnica de Lisboa, Instituto Superior Tecnico, Centro de Recursos Naturais e Ambiente (CERENA) Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Branquinho, C. [Universidade de Lisboa, Faculdade de Ciencias, Centro de Ecologia e Biologia Vegetal (CEBV), 1749-016 Lisbon (Portugal); Universidade Atlantica, Antiga Fabrica da Polvora de Barcarena, 2745-615 Barcarena (Portugal)], E-mail: cmbranquinho@fc.ul.pt
2008-01-15
The objective of this work was to determine the impact of neighbourhood land-cover in epiphytic lichen diversity. We used geostatistics to analyse the spatial structure of lichen-indicators (number of lichen species and Lichen Diversity Value) and correlate them to land-cover considering different distances from the observed data. The results showed that lichen diversity was influenced by different environmental factors that act in the same territory but impact lichens at different distances from the source. The differences in the distance of influence of the several land-cover types seem to be related to the size of pollutants/particles that predominantly are dispersed by each land-cover type. We also showed that a local scale of analysis gives a deeper insight into the understanding of lichen richness and abundance in the region. This work highlighted the importance of a multiple spatial scale of analysis to deeply interpret the relation between lichen diversity and the underling environmental factors. - The interpretation of lichen-biodiversity data was improved by using analysis at different scales.
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International Nuclear Information System (INIS)
Pinho, P.; Augusto, S.; Maguas, C.; Pereira, M.J.; Soares, A.; Branquinho, C.
2008-01-01
The objective of this work was to determine the impact of neighbourhood land-cover in epiphytic lichen diversity. We used geostatistics to analyse the spatial structure of lichen-indicators (number of lichen species and Lichen Diversity Value) and correlate them to land-cover considering different distances from the observed data. The results showed that lichen diversity was influenced by different environmental factors that act in the same territory but impact lichens at different distances from the source. The differences in the distance of influence of the several land-cover types seem to be related to the size of pollutants/particles that predominantly are dispersed by each land-cover type. We also showed that a local scale of analysis gives a deeper insight into the understanding of lichen richness and abundance in the region. This work highlighted the importance of a multiple spatial scale of analysis to deeply interpret the relation between lichen diversity and the underling environmental factors. - The interpretation of lichen-biodiversity data was improved by using analysis at different scales
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EnviroAtlas - Minneapolis/St. Paul, MN - Meter-Scale Urban Land Cover (MULC) Data (2010)
U.S. Environmental Protection Agency — The Minneapolis-St. Paul, MN EnviroAtlas Meter-scale Urban Land Cover (MULC) data were generated from four-band (red, green, blue, and near infrared) aerial...
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Directory of Open Access Journals (Sweden)
Prach Sangthongwattanakul
2014-03-01
Full Text Available One of important causes to climate change is land use/ land cover changes due to their important role in the amount of carbon dioxide in the atmosphere which directly relate to a solution to the problem of global warming. Analysis of land use/ land cover changes is thus very important for developing countries such as Thailand, especially to study the trend of land use/land cover changes that can be used for investigation of theirs driving forces. In addition, during these four decades, land use/cover in Nakhon Ratchasima city, a metropolitan city in Northeastern Thailand, has been rapidly changes because of rapid economical growth together with its location situated in the central of Northeastern Thailand. This study aims to determine land use/cover changes pattern of the Nakhon Ratchasima city. We employed unsupervised classification approach coupled with GIS analyses was employed to generate land use/cover maps for 1972, 2002 and 2013 with four classes; vegetated areas, settlement areas, barelands and water resoures. The results indicate that urban areas have increased based on economic and population growth as well as road network extension and consequently the urban growth affected environmental conditions. In the study, with multi-temporal Landsat data, we successfully used remote sensing techniques together with information technology as a tool for effectively monitoring urban growth.
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Land cover and topography affect the land transformation caused by wind facilities.
Directory of Open Access Journals (Sweden)
Jay E Diffendorfer
Full Text Available Land transformation (ha of surface disturbance/MW associated with wind facilities shows wide variation in its reported values. In addition, no studies have attempted to explain the variation across facilities. We digitized land transformation at 39 wind facilities using high resolution aerial imagery. We then modeled the effects of turbine size, configuration, land cover, and topography on the levels of land transformation at three spatial scales. The scales included strings (turbines with intervening roads only, sites (strings with roads connecting them, buried cables and other infrastructure, and entire facilities (sites and the roads or transmission lines connecting them to existing infrastructure. An information theoretic modeling approach indicated land cover and topography were well-supported variables affecting land transformation, but not turbine size or configuration. Tilled landscapes, despite larger distances between turbines, had lower average land transformation, while facilities in forested landscapes generally had the highest land transformation. At site and string scales, flat topographies had the lowest land transformation, while facilities on mesas had the largest. The results indicate the landscape in which the facilities are placed affects the levels of land transformation associated with wind energy. This creates opportunities for optimizing wind energy production while minimizing land cover change. In addition, the results indicate forecasting the impacts of wind energy on land transformation should include the geographic variables affecting land transformation reported here.
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Tormos, T.; Kosuth, P.; Souchon, Y.; Villeneuve, B.; Durrieu, S.; Chandesris, A.
2010-12-01
Preservation and restoration of river ecosystems require an improved understanding of the mechanisms through which they are influenced by landscape at multiple spatial scales and particularly at river corridor scale considering the role of riparian vegetation for regulating and protecting river ecological status and the relevance of this specific area for implementing efficient and realistic strategies. Assessing correctly this influence over large river networks involves accurate broad scale (i.e. at least regional) information on Land Cover within Riparian Areas (LCRA). As the structure of land cover along rivers is generally not accessible using moderate-scale satellite imagery, finer spatial resolution imagery and specific mapping techniques are needed. For this purpose we developed a generic multi-scale Object Based Image Analysis (OBIA) scheme able to produce LCRA maps in different geographic context by exploiting information available from very high spatial resolution imagery (satellite or airborne) and/or metric to decametric spatial thematic data on a given study zone thanks to fuzzy expert knowledge classification rules. A first experimentation was carried out on the Herault river watershed (southern of France), a 2650 square kilometers basin that presents a contrasted landscape (different ecoregions) and a total stream length of 1150 Km, using high and very high multispectral remotely-sensed images (10m Spot5 multispectral images and 0.5m aerial photography) and existing spatial thematic data. Application of the OBIA scheme produced a detailed (22 classes) LCRA map with an overall accuracy of 89% and a Kappa index of 83% according to a land cover pressures typology (six categories). A second experimentation (using the same data sources) was carried out on a larger test zone, a part of the Normandy river network (25 000 square kilometers basin; 6000 km long river network; 155 ecological stations). This second work aimed at elaborating a robust statistical
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National Land Cover Database (NLCD) Percent Developed Imperviousness Collection
U.S. Geological Survey, Department of the Interior — The National Land Cover Database (NLCD) Percent Developed Imperviousness Collection is produced through a cooperative project conducted by the Multi-Resolution Land...
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EnviroAtlas - Cleveland, OH - Meter-Scale Urban Land Cover (MULC) Data (2011 and 2013)
U.S. Environmental Protection Agency — The Cleveland, OH EnviroAtlas Meter-scale Urban Land Cover (MULC) dataset comprises 2,737 km2 around the city of Cleveland and portions of surrounding counties. The...
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de Souza Soler, L.; Verburg, P.H.
2010-01-01
Land cover change in the Brazilian Amazon depends on the spatial variability of political, socioeconomic and biophysical factors, as well as on the land use history and its actors. A regional scale analysis was made in Rondônia State to identify possible differences in land cover change connected to
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Nghiem, S. V.; Small, C.; Jacobson, M. Z.; Brakenridge, G. R.; Balk, D.; Sorichetta, A.; Masetti, M.; Gaughan, A. E.; Stevens, F. R.; Mathews, A.; Frazier, A. E.; Das, N. N.
2017-12-01
An innovative paradigm to observe the rural-urban transformation over the landscape using multi-sourced satellite data is formulated as a time and space continuum, extensively in space across South and Southeast Asia and in time over a decadal scale. Rather than a disparate array of individual cities and their vicinities in separated areas and in a discontinuous collection of points in time, the time-space continuum paradigm enables significant advances in addressing rural-urban change as a continuous gradient across the landscape from the wilderness to rural to urban areas to study challenging environmental and socioeconomic issues. We use satellite data including QuikSCAT scatterometer, SRTM and Sentinel-1 SAR, Landsat, WorldView, MODIS, and SMAP together with environmental and demographic data and modeling products to investigate land cover and land use change in South and Southeast Asia and associated impacts. Utilizing the new observational advances and effectively capitalizing current capabilities, we will present interdisciplinary results on urbanization in three dimensions, flood and drought, wildfire, air and water pollution, urban change, policy effects, population dynamics and vector-borne disease, agricultural assessment, and land degradation and desertification.
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The Significance of Land Cover Delineation on Soil Erosion Assessment.
Efthimiou, Nikolaos; Psomiadis, Emmanouil
2018-04-25
The study aims to evaluate the significance of land cover delineation on soil erosion assessment. To that end, RUSLE (Revised Universal Soil Loss Equation) was implemented at the Upper Acheloos River catchment, Western Central Greece, annually and multi-annually for the period 1965-92. The model estimates soil erosion as the linear product of six factors (R, K, LS, C, and P) considering the catchment's climatic, pedological, topographic, land cover, and anthropogenic characteristics, respectively. The C factor was estimated using six alternative land use delineations of different resolution, namely the CORINE Land Cover (CLC) project (2000, 2012 versions) (1:100,000), a land use map conducted by the Greek National Agricultural Research Foundation (NAGREF) (1:20,000), a land use map conducted by the Greek Payment and Control Agency for Guidance and Guarantee Community Aid (PCAGGCA) (1:5,000), and the Landsat 8 16-day Normalized Difference Vegetation Index (NDVI) dataset (30 m/pixel) (two approximations) based on remote sensing data (satellite image acquired on 07/09/2016) (1:40,000). Since all other factors remain unchanged per each RUSLE application, the differences among the yielded results are attributed to the C factor (thus the land cover pattern) variations. Validation was made considering the convergence between simulated (modeled) and observed sediment yield. The latter was estimated based on field measurements conducted by the Greek PPC (Public Power Corporation). The model performed best at both time scales using the Landsat 8 (Eq. 13) dataset, characterized by a detailed resolution and a satisfactory categorization, allowing the identification of the most susceptible to erosion areas.
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Ganguly, S.; Kumar, U.; Nemani, R. R.; Kalia, S.; Michaelis, A.
2017-12-01
In this work, we use a Fully Constrained Least Squares Subpixel Learning Algorithm to unmix global WELD (Web Enabled Landsat Data) to obtain fractions or abundances of substrate (S), vegetation (V) and dark objects (D) classes. Because of the sheer nature of data and compute needs, we leveraged the NASA Earth Exchange (NEX) high performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into 4 classes namely, forest, farmland, water and urban areas (with NPP-VIIRS - national polar orbiting partnership visible infrared imaging radiometer suite nighttime lights data) over California, USA using Random Forest classifier. Validation of these land cover maps with NLCD (National Land Cover Database) 2011 products and NAFD (North American Forest Dynamics) static forest cover maps showed that an overall classification accuracy of over 91% was achieved, which is a 6% improvement in unmixing based classification relative to per-pixel based classification. As such, abundance maps continue to offer an useful alternative to high-spatial resolution data derived classification maps for forest inventory analysis, multi-class mapping for eco-climatic models and applications, fast multi-temporal trend analysis and for societal and policy-relevant applications needed at the watershed scale.
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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.
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Kansas Data Access and Support Center — The Land Cover database depicts 10 general land cover classes for the State of Kansas. The database was compiled from a digital classification of Landsat Thematic...
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De Brue, Hanne; Verstraeten, Gert; Broothaerts, Nils; Notebaert, Bastiaan
2016-04-01
Accurate and spatially explicit landscape reconstructions for distinct time periods in human history are essential for the quantification of the effect of anthropogenic land cover changes on, e.g., global biogeochemical cycles, ecology, and geomorphic processes, and to improve our understanding of interaction between humans and the environment in general. A long-term perspective covering Mid and Late Holocene land use changes is recommended in this context, as it provides a baseline to evaluate human impact in more recent periods. Previous efforts to assess the evolution and intensity of agricultural land cover in past centuries or millennia have predominantly focused on palynological records. An increasing number of quantitative techniques has been developed during the last two decades to transfer palynological data to land cover estimates. However, these techniques have to deal with equifinality issues and, furthermore, do not sufficiently allow to reconstruct spatial patterns of past land cover. On the other hand, several continental and global databases of historical anthropogenic land cover changes based on estimates of global population and the required agricultural land per capita have been developed in the past decennium. However, at such long temporal and spatial scales, reconstruction of past anthropogenic land cover intensities and spatial patterns necessarily involves many uncertainties and assumptions as well. Here, we present a novel approach that combines archaeological, palynological and geomorphological data for the Dijle catchment in the central Belgium Loess Belt in order to arrive at more realistic Holocene land cover histories. Multiple land cover scenarios (> 60.000) are constructed using probabilistic rules and used as input into a sediment delivery model (WaTEM/SEDEM). Model outcomes are confronted with a detailed geomorphic dataset on Holocene sediment fluxes and with REVEALS based estimates of vegetation cover using palynological data from
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Schoorl, J.M.
2002-01-01
"Addressing the Multi-scale Lapsus of Landscape" with the sub-title "Multi-scale landscape process modelling to support sustainable land use: A case study for the Lower Guadalhorce valley South Spain" focuses on the role of
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The Land Cover Dynamics and Conversion of Agricultural Land in Northwestern Bangladesh, 1973-2003.
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.
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The impact of Future Land Use and Land Cover Changes on Atmospheric Chemistry-Climate Interactions
Ganzeveld, L.N.; Bouwman, L.
2010-01-01
To demonstrate potential future consequences of land cover and land use changes beyond those for physical climate and the carbon cycle, we present an analysis of large-scale impacts of land cover and land use changes on atmospheric chemistry using the chemistry-climate model EMAC (ECHAM5/MESSy
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Pairing FLUXNET sites to validate model representations of land-use/land-cover change
Chen, Liang; Dirmeyer, Paul A.; Guo, Zhichang; Schultz, Natalie M.
2018-01-01
Land surface energy and water fluxes play an important role in land-atmosphere interactions, especially for the climatic feedback effects driven by land-use/land-cover change (LULCC). These have long been documented in model-based studies, but the performance of land surface models in representing LULCC-induced responses has not been investigated well. In this study, measurements from proximate paired (open versus forest) flux tower sites are used to represent observed deforestation-induced changes in surface fluxes, which are compared with simulations from the Community Land Model (CLM) and the Noah Multi-Parameterization (Noah-MP) land model. Point-scale simulations suggest the CLM can represent the observed diurnal and seasonal changes in net radiation (Rnet) and ground heat flux (G), but difficulties remain in the energy partitioning between latent (LE) and sensible (H) heat flux. The CLM does not capture the observed decreased daytime LE, and overestimates the increased H during summer. These deficiencies are mainly associated with models' greater biases over forest land-cover types and the parameterization of soil evaporation. Global gridded simulations with the CLM show uncertainties in the estimation of LE and H at the grid level for regional and global simulations. Noah-MP exhibits a similar ability to simulate the surface flux changes, but with larger biases in H, G, and Rnet change during late winter and early spring, which are related to a deficiency in estimating albedo. Differences in meteorological conditions between paired sites is not a factor in these results. Attention needs to be devoted to improving the representation of surface heat flux processes in land models to increase confidence in LULCC simulations.
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Land cover mapping of North and Central America—Global Land Cover 2000
Latifovic, Rasim; Zhu, Zhi-Liang
2004-01-01
The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.
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A procedure to obtain a refined European land use/cover map
Batista e Silva, F.; Lavalle, C.; Koomen, E.
2013-01-01
Available land use/cover maps differ in their spatial extent and in their thematic, spatial, and temporal resolutions. Due to the costs of producing such maps, there is usually a trade-off between spatial extent and resolution. The only European-wide, consistent, and multi-temporal land use/cover
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Land-Cover Change Detection Using Multi-Temporal MODIS NDVI Imagery
Monitoring the locations and distributions of land-cover change is important for establishing linkages between policy decisions, regulatory actions and subsequent land-use activities. Past studies incorporating two-date change detection using Landsat data have tended to be perfor...
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Pouliot, D.; Latifovic, R.; Olthof, I.
2017-12-01
Land cover is needed for a large range of environmental applications regarding climate impacts and adaption, emergency response, wildlife habitat, air quality, water yield, etc. In Canada a 2008 user survey revealed that the most practical scale for provision of land cover data is 30 m, nationwide, with an update frequency of five years (Ball, 2008). In response to this need the Canada Centre for Remote Sensing has generated a 30 m land cover of Canada for the base year 2010 as part of a planned series of maps at the recommended five year update frequency. This land cover is the Canadian contribution to the North American Land Change Monitoring System initiative, which seeks to provide harmonized land cover across Canada, the United States, and Mexico. The methodology developed in this research utilized a combination of unsupervised and machine learning techniques to map land cover, blend results between mapping units, locally optimize results, and process some thematic attributes with specific features sets. Accuracy assessment with available field data shows it was on average 75% for the five study areas assessed. In this presentation an overview of the unique processing aspects, example results, and initial accuracy assessment will be discussed.
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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.
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Land use and land cover mapping: City of Palm Bay, Florida
Barile, D. D.; Pierce, R.
1977-01-01
Two different computer systems were compared for use in making land use and land cover maps. The Honeywell 635 with the LANDSAT signature development program (LSDP) produced a map depicting general patterns, but themes were difficult to classify as specific land use. Urban areas were unclassified. The General Electric Image 100 produced a map depicting eight land cover categories classifying 68 percent of the total area. Ground truth, LSDP, and Image 100 maps were all made to the same scale for comparison. LSDP agreed with the ground truth 60 percent and 64 percent within the two test areas compared and Image 100 was in agreement 70 percent and 80 percent.
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Land use and land cover change based on historical space-time model
Sun, Qiong; Zhang, Chi; Liu, Min; Zhang, Yongjing
2016-09-01
Land use and cover change is a leading edge topic in the current research field of global environmental changes and case study of typical areas is an important approach understanding global environmental changes. Taking the Qiantang River (Zhejiang, China) as an example, this study explores automatic classification of land use using remote sensing technology and analyzes historical space-time change by remote sensing monitoring. This study combines spectral angle mapping (SAM) with multi-source information and creates a convenient and efficient high-precision land use computer automatic classification method which meets the application requirements and is suitable for complex landform of the studied area. This work analyzes the histological space-time characteristics of land use and cover change in the Qiantang River basin in 2001, 2007 and 2014, in order to (i) verify the feasibility of studying land use change with remote sensing technology, (ii) accurately understand the change of land use and cover as well as historical space-time evolution trend, (iii) provide a realistic basis for the sustainable development of the Qiantang River basin and (iv) provide a strong information support and new research method for optimizing the Qiantang River land use structure and achieving optimal allocation of land resources and scientific management.
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Scrubbing Up: Multi-Scale Investigation of Woody Encroachment in a Southern African Savannah
Directory of Open Access Journals (Sweden)
Christopher G. Marston
2017-04-01
Full Text Available Changes in the extent of woody vegetation represent a major conservation question in many savannah systems around the globe. To address the problem of the current lack of broad-scale cost-effective tools for land cover monitoring in complex savannah environments, we use a multi-scale approach to quantifying vegetation change in Kruger National Park (KNP, South Africa. We test whether medium spatial resolution satellite data (Landsat, existing back to the 1970s, which have pixel sizes larger than typical vegetation patches, can nevertheless capture the thematic detail required to detect woody encroachment in savannahs. We quantify vegetation change over a 13-year period in KNP, examine the changes that have occurred, assess the drivers of these changes, and compare appropriate remote sensing data sources for monitoring change. We generate land cover maps for three areas of southern KNP using very high resolution (VHR and medium resolution satellite sensor imagery from February 2001 to 2014. Considerable land cover change has occurred, with large increases in shrubs replacing both trees and grassland. Examination of exclosure areas and potential environmental driver data suggests two mechanisms: elephant herbivory removing trees and at least one separate mechanism responsible for conversion of grassland to shrubs, theorised to be increasing atmospheric CO2. Thus, the combination of these mechanisms causes the novel two-directional shrub encroachment that we observe (tree loss and grassland conversion. Multi-scale comparison of classifications indicates that although spatial detail is lost when using medium resolution rather than VHR imagery for land cover classification (e.g., Landsat imagery cannot readily distinguish between tree and shrub classes, while VHR imagery can, the thematic detail contained within both VHR and medium resolution classifications is remarkably congruent. This suggests that medium resolution imagery contains sufficient
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Local- and landscape-scale land cover affects microclimate and water use in urban gardens.
Lin, Brenda B; Egerer, Monika H; Liere, Heidi; Jha, Shalene; Bichier, Peter; Philpott, Stacy M
2018-01-01
Urban gardens in Central California are highly vulnerable to the effects of climate change, experiencing both extended high heat periods as well as water restrictions because of severe drought conditions. This puts these critical community-based food production systems at risk as California is expected to experience increasing weather extremes. In agricultural systems, increased vegetation complexity, such as greater structure or biodiversity, can increase the resilience of food production systems from climate fluctuations. We test this theory in 15 urban gardens across California's Central Coast. Local- and landscape-scale measures of ground, vegetation, and land cover were collected in and around each garden, while climate loggers recorded temperatures in each garden in 30min increments. Multivariate analyses, using county as a random factor, show that both local- and landscape-scale factors were important. All factors were significant predictors of mean temperature. Tallest vegetation, tree/shrub species richness, grass cover, mulch cover, and landscape level agricultural cover were cooling factors; in contrast, garden size, garden age, rock cover, herbaceous species richness, and landscape level urban cover were warming factors. Results were similar for the maximum temperature analysis except that agriculture land cover and herbaceous species richness were not significant predictors of maximum temperature. Analysis of gardener watering behavior to observed temperatures shows that garden microclimate was significantly related to the number of minutes watered as well as the number of liters of water used per watering event. Thus gardeners seem to respond to garden microclimate in their watering behavior even though this behavior is most probably motivated by a range of other factors such as water regulations and time availability. This research shows that local management of ground cover and vegetation can reduce mean and maximum temperatures in gardens, and the
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Directory of Open Access Journals (Sweden)
Dong Liang
2015-11-01
Full Text Available Land cover plays an important role in the climate and biogeochemistry of the Earth system. It is of great significance to produce and evaluate the global land cover (GLC data when applying the data to the practice at a specific spatial scale. The objective of this study is to evaluate and validate the consistency of the Moderate Resolution Imaging Spectroradiometer (MODIS land cover product (MCD12Q1 at a provincial scale (Anhui Province, China based on the Chinese 30 m GLC product (GlobeLand30. A harmonization method is firstly used to reclassify the land cover types between five classification schemes (International Geosphere Biosphere Programme (IGBP global vegetation classification, University of Maryland (UMD, MODIS-derived Leaf Area Index and Fractional Photosynthetically Active Radiation (LAI/FPAR, MODIS-derived Net Primary Production (NPP, and Plant Functional Type (PFT of MCD12Q1 and ten classes of GlobeLand30, based on the knowledge rule (KR and C4.5 decision tree (DT classification algorithm. A total of five harmonized land cover types are derived including woodland, grassland, cropland, wetland and artificial surfaces, and four evaluation indicators are selected including the area consistency, spatial consistency, classification accuracy and landscape diversity in the three sub-regions of Wanbei, Wanzhong and Wannan. The results indicate that the consistency of IGBP is the best among the five schemes of MCD12Q1 according to the correlation coefficient (R. The “woodland” LAI/FPAR is the worst, with a spatial similarity (O of 58.17% due to the misclassification between “woodland” and “others”. The consistency of NPP is the worst among the five schemes as the agreement varied from 1.61% to 56.23% in the three sub-regions. Furthermore, with the biggest difference of diversity indices between LAI/FPAR and GlobeLand30, the consistency of LAI/FPAR is the weakest. This study provides a methodological reference for evaluating the
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The managed clearing: An overlooked land-cover type in urbanizing regions?
Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K.
2018-01-01
Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type–semi-natural, vegetated land surfaces with varying degrees of management practices–for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area– 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and
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Tularosa, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986
Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...
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Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)
Hansen, M.C.; Egorov, Alexey; Potapov, P.V.; Stehman, S.V.; Tyukavina, A.; Turubanova, S.A.; Roy, David P.; Goetz, S.J.; Loveland, Thomas R.; Ju, J.; Kommareddy, A.; Kovalskyy, Valeriy; Forsyth, C.; Bents, T.
2014-01-01
Forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30 m spatial resolution using Web-Enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) (http://landsat.usgs.gov/WELD.php). The approach related multi-temporal WELD metrics and expert-derived training data for forest cover loss and bare ground gain through a decision tree classification algorithm. Forest cover loss was reported at state and ecoregional scales, and the identification of core forests' absent of change was made and verified using LiDAR data from the GLAS (Geoscience Laser Altimetry System) instrument. Bare ground gain correlated with population change for large metropolitan statistical areas (MSAs) outside of desert or semi-desert environments. GoogleEarth™ time-series images were used to validate the products. Mapped forest cover loss totaled 53,084 km2 and was found to be depicted conservatively, with a user's accuracy of 78% and a producer's accuracy of 68%. Excluding errors of adjacency, user's and producer's accuracies rose to 93% and 89%, respectively. Mapped bare ground gain equaled 5974 km2 and nearly matched the estimated area from the reference (GoogleEarth™) classification; however, user's (42%) and producer's (49%) accuracies were much less than those of the forest cover loss product. Excluding errors of adjacency, user's and producer's accuracies rose to 62% and 75%, respectively. Compared to recent 2001–2006 USGS National Land Cover Database validation data for forest loss (82% and 30% for respective user's and producer's accuracies) and urban gain (72% and 18% for respective user's and producer's accuracies), results using a single CONUS-scale model with WELD data are promising and point to the potential for national-scale operational mapping of key land cover transitions. However, validation results highlighted limitations, some of which can be addressed by
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International Nuclear Information System (INIS)
Yu, Qin; Engstrom, Ryan; Shiklomanov, Nikolay; Strelestskiy, Dmitry; Epstein, Howard E
2015-01-01
Northwestern Siberia has been undergoing a range of land cover and land use changes associated with climate change, animal husbandry and development of mineral resources, particularly oil and gas. The changes caused by climate and oil/gas development Southeast of the city of Nadym were investigated using multi-temporal and multi-spatial remotely sensed images. Comparison between high spatial resolution imagery acquired in 1968 and 2006 indicates that 8.9% of the study area experienced an increase in vegetation cover (e.g. establishment of new saplings, extent of vegetated cover) in response to climate warming while 10.8% of the area showed a decrease in vegetation cover due to oil and gas development and logging activities. Waterlogging along linear structures and vehicle tracks was found near the oil and gas development site, while in natural landscapes the drying of thermokarst lakes is evident due to warming caused permafrost degradation. A Landsat time series dataset was used to document the spatial and temporal dynamics of these ecosystems in response to climate change and disturbances. The impacts of land use on surface vegetation, radiative, and hydrological properties were evaluated using Landsat image-derived biophysical indices. The spatial and temporal analyses suggest that the direct impacts associated with infrastructure development were mostly within 100 m distance from the disturbance source. While these impacts are rather localized they persist for decades despite partial recovery of vegetation after the initial disturbance and can have significant implications for changes in permafrost dynamics and surface energy budgets at landscape and regional scales. (letter)
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Use of UAV-Borne Spectrometer for Land Cover Classification
Directory of Open Access Journals (Sweden)
Sowmya Natesan
2018-04-01
Full Text Available Unmanned aerial vehicles (UAV are being used for low altitude remote sensing for thematic land classification using visible light and multi-spectral sensors. The objective of this work was to investigate the use of UAV equipped with a compact spectrometer for land cover classification. The UAV platform used was a DJI Flamewheel F550 hexacopter equipped with GPS and Inertial Measurement Unit (IMU navigation sensors, and a Raspberry Pi processor and camera module. The spectrometer used was the FLAME-NIR, a near-infrared spectrometer for hyperspectral measurements. RGB images and spectrometer data were captured simultaneously. As spectrometer data do not provide continuous terrain coverage, the locations of their ground elliptical footprints were determined from the bundle adjustment solution of the captured images. For each of the spectrometer ground ellipses, the land cover signature at the footprint location was determined to enable the characterization, identification, and classification of land cover elements. To attain a continuous land cover classification map, spatial interpolation was carried out from the irregularly distributed labeled spectrometer points. The accuracy of the classification was assessed using spatial intersection with the object-based image classification performed using the RGB images. Results show that in homogeneous land cover, like water, the accuracy of classification is 78% and in mixed classes, like grass, trees and manmade features, the average accuracy is 50%, thus, indicating the contribution of hyperspectral measurements of low altitude UAV-borne spectrometers to improve land cover classification.
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Operational monitoring of land-cover change using multitemporal remote sensing data
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
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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.
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Land cover and water yield: inference problems when comparing catchments with mixed land cover
Directory of Open Access Journals (Sweden)
A. I. J. M. van Dijk
2012-09-01
Full Text Available Controlled experiments provide strong evidence that changing land cover (e.g. deforestation or afforestation can affect mean catchment streamflow (Q. By contrast, a similarly strong influence has not been found in studies that interpret Q from multiple catchments with mixed land cover. One possible reason is that there are methodological issues with the way in which the Budyko framework was used in the latter type studies. We examined this using Q data observed in 278 Australian catchments and by making inferences from synthetic Q data simulated by a hydrological process model (the Australian Water Resources Assessment system Landscape model. The previous contrasting findings could be reproduced. In the synthetic experiment, the land cover influence was still present but not accurately detected with the Budyko- framework. Likely sources of interpretation bias demonstrated include: (i noise in land cover, precipitation and Q data; (ii additional catchment climate characteristics more important than land cover; and (iii covariance between Q and catchment attributes. These methodological issues caution against the use of a Budyko framework to quantify a land cover influence in Q data from mixed land-cover catchments. Importantly, however, our findings do not rule out that there may also be physical processes that modify the influence of land cover in mixed land-cover catchments. Process model simulations suggested that lateral water redistribution between vegetation types and recirculation of intercepted rainfall may be important.
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Land-Use and Land-Cover Change around Mobile Bay, Alabama from 1974-2008
Ellis, Jean; Spruce, Joseph P.; Swann, Roberta; Smooth, James C.
2009-01-01
), which is critical nursing ground for many Gulf fish species. A survey of Mobile Bay SAV showed widespread decreases since the 1940s. Prior to our project, coastal environmental managers in Baldwin and Mobile counties needed more understanding of the historical LULC for properly assessing the impacts of urbanization. In particular, more information on the location and extent of changing urbanization LULC patterns was needed to aid LULC planning and to assess predictions of future LULC patterns. Our products will assist the coastal environmental managers and land-use planners in making better community growth planning decisions. Our project also will help to establish a historical baseline of LULC distributions, which is a fundamental need in any stewardship plan. The primary research objective of our project was to produce historic and current geospatial LULC change products across a 34-year time frame. A multi-decadal coastal LULC change product was the major project deliverable. The geographic extent and nature of change was quantified and assessed for the upland herbaceous, barren, open water, urban, upland forest, woody wetland, and non-woody wetlanddominated land cover types. We focused on regional analyses of decadal-scale urban expansion and watershed-scaled analyses of LULC change for multiple areas of concern to the Mobile Bay NEP (Figure A). We used the following dates to derive LULC classification products from Landsat data: 1974, 1979, 1984, 1988, 1991, 1996, 2001, 2005, and 2008. We assessed the accuracy of our products using randomly sampled locations and digital geospatial reference data including field survey data, high resolution orthorectified aerial photography, high resolution multispectral and panchromatic satellite data displays (from QuickBird and Corona sensors), digital elevation model data, and National Wetlands Inventory wetland cover type data. NOAA s Coastal Change Assessment Program s (C-CAP) and National Land Cover Database (NLCD) procts
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Historical Image Registration and Land-Use Land-Cover Change Analysis
Directory of Open Access Journals (Sweden)
Fang-Ju Jao
2014-12-01
Full Text Available Historical aerial images are important to retain past ground surface information. The land-use land-cover change in the past can be identified using historical aerial images. Automatic historical image registration and stitching is essential because the historical image pose information was usually lost. In this study, the Scale Invariant Feature Transform (SIFT algorithm was used for feature extraction. Subsequently, the present study used the automatic affine transformation algorithm for historical image registration, based on SIFT features and control points. This study automatically determined image affine parameters and simultaneously transformed from an image coordinate system to a ground coordinate system. After historical aerial image registration, the land-use land-cover change was analyzed between two different years (1947 and 1975 at the Tseng Wen River estuary. Results show that sandbars and water zones were transformed into a large number of fish ponds between 1947 and 1975.
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Gallup, NM AZ 1:250,000 Quad USGS Land Use/Land Cover, 1986
Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...
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Santa Fe, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986
Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...
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Mohammad Sayemuzzaman; Manoj K. Jha
2014-01-01
State wide variant topographic features in North Carolina attract the hydro-climatologist. There is none modeling study found that predict future Land Cover Land Use (LCLU) change for whole North Carolina. In this study, satellite-derived land cover maps of year 1992, 2001 and 2006 of North Carolina were integrated within the framework of the Markov-Cellular Automata (Markov-CA) model which combines the Markov chain and Cellular Automata (CA) techniques. A Multi-Criteria Evaluation (MCE) was ...
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Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.
2017-12-01
Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in
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Louisiana Land Cover Data Set, UTM Zone 15 NAD83, USGS [landcover_la_nlcd_usgs_2001.tif
Louisiana Geographic Information Center — The National Land Cover Database 2001 land cover layer for mapping zone 37A was produced through a cooperative project conducted by the Multi-Resolution Land...
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Directory of Open Access Journals (Sweden)
Annett Bartsch
2016-11-01
Full Text Available Most applications of land cover maps that have been derived from satellite data over the Arctic require higher thematic detail than available in current global maps. A range of application studies has been reviewed, including up-scaling of carbon fluxes and pools, permafrost feature mapping and transition monitoring. Early land cover mapping studies were driven by the demand to characterize wildlife habitats. Later, in the 1990s, up-scaling of in situ measurements became central to the discipline of land cover mapping on local to regional scales at several sites across the Arctic. This includes the Kuparuk basin in Alaska, the Usa basin and the Lena Delta in Russia. All of these multi-purpose land cover maps have been derived from Landsat data. High resolution maps (from optical satellite data serve frequently as input for the characterization of periglacial features and also flux tower footprints in recent studies. The most used map to address circumpolar issues is the CAVM (Circum Arctic Vegetation Map based on AVHRR (1 km and has been manually derived. It provides the required thematic detail for many applications, but is confined to areas north of the treeline, and it is limited in spatial detail. A higher spatial resolution circumpolar land cover map with sufficient thematic content would be beneficial for a range of applications. Such a land cover classification should be compatible with existing global maps and applicable for multiple purposes. The thematic content of existing global maps has been assessed by comparison to the CAVM and regional maps. None of the maps provides the required thematic detail. Spatial resolution has been compared to used classes for local to regional applications. The required thematic detail increases with spatial resolution since coarser datasets are usually applied over larger areas covering more relevant landscape units. This is especially of concern when the entire Arctic is addressed. A spatial
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Land cover mapping of Greater Mesoamerica using MODIS data
Giri, Chandra; Jenkins, Clinton N.
2005-01-01
A new land cover database of Greater Mesoamerica has been prepared using moderate resolution imaging spectroradiometer (MODIS, 500 m resolution) satellite data. Daily surface reflectance MODIS data and a suite of ancillary data were used in preparing the database by employing a decision tree classification approach. The new land cover data are an improvement over traditional advanced very high resolution radiometer (AVHRR) based land cover data in terms of both spatial and thematic details. The dominant land cover type in Greater Mesoamerica is forest (39%), followed by shrubland (30%) and cropland (22%). Country analysis shows forest as the dominant land cover type in Belize (62%), Cost Rica (52%), Guatemala (53%), Honduras (56%), Nicaragua (53%), and Panama (48%), cropland as the dominant land cover type in El Salvador (60.5%), and shrubland as the dominant land cover type in Mexico (37%). A three-step approach was used to assess the quality of the classified land cover data: (i) qualitative assessment provided good insight in identifying and correcting gross errors; (ii) correlation analysis of MODIS- and Landsat-derived land cover data revealed strong positive association for forest (r2 = 0.88), shrubland (r2 = 0.75), and cropland (r2 = 0.97) but weak positive association for grassland (r2 = 0.26); and (iii) an error matrix generated using unseen training data provided an overall accuracy of 77.3% with a Kappa coefficient of 0.73608. Overall, MODIS 500 m data and the methodology used were found to be quite useful for broad-scale land cover mapping of Greater Mesoamerica.
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National Land Cover Database 2001 (NLCD01)
LaMotte, Andrew E.
2016-01-01
This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg). The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.
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Wingate, Vladimir; Phinn, Stuart; Kuhn, Nikolaus
2016-04-01
Woodland savannahs provide essential ecosystem functions and services to communities. On the African continent, they are widely utilized and converted to intensive land uses. This study investigates the land cover changes over 108,038 km2 in NE Namibia using multi-sensor Landsat imagery, at decadal intervals from 1975 to 2014, with a post-classification change detection method and supervised Regression Tree classifiers. We discuss likely impacts of land tenure and reforms over the past four decades on changes in land use and land cover. These included losses, gains and exchanges between predominant land cover classes. Exchanges comprised logical conversions between woodland and agricultural classes, implying woodland clearing for arable farming, cropland abandonment and vegetation succession. The dominant change was a reduction in the area of the woodland class due to the expansion of the agricultural class, specifically, small-scale cereal and pastoral production. Woodland area decreased from 90% of the study area in 1975 to 83% in 2014, while cleared land increased from 9% to 14%. We found that the main land cover changes are conversion from woodland to agricultural and urban land uses, driven by urban expansion and woodland clearing for subsistence-based agriculture and pastoralism.
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Pilant, A. N.; Baynes, J.; Dannenberg, M.; Riegel, J.; Rudder, C.; Endres, K.
2013-12-01
US EPA EnviroAtlas is an online collection of tools and resources that provides geospatial data, maps, research, and analysis on the relationships between nature, people, health, and the economy (http://www.epa.gov/research/enviroatlas/index.htm). Using EnviroAtlas, you can see and explore information related to the benefits (e.g., ecosystem services) that humans receive from nature, including clean air, clean and plentiful water, natural hazard mitigation, biodiversity conservation, food, fuel, and materials, recreational opportunities, and cultural and aesthetic value. EPA developed several urban land cover maps at very high spatial resolution (one-meter pixel size) for a portion of EnviroAtlas devoted to urban studies. This urban mapping effort supported analysis of relations among land cover, human health and demographics at the US Census Block Group level. Supervised classification of 2010 USDA NAIP (National Agricultural Imagery Program) digital aerial photos produced eight-class land cover maps for several cities, including Durham, NC, Portland, ME, Tampa, FL, New Bedford, MA, Pittsburgh, PA, Portland, OR, and Milwaukee, WI. Semi-automated feature extraction methods were used to classify the NAIP imagery: genetic algorithms/machine learning, random forest, and object-based image analysis (OBIA). In this presentation we describe the image processing and fuzzy accuracy assessment methods used, and report on some sustainability and ecosystem service metrics computed using this land cover as input (e.g., carbon sequestration from USFS iTREE model; health and demographics in relation to road buffer forest width). We also discuss the land cover classification schema (a modified Anderson Level 1 after the National Land Cover Data (NLCD)), and offer some observations on lessons learned. Meter-scale urban land cover in Portland, OR overlaid on NAIP aerial photo. Streets, buildings and individual trees are identifiable.
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Assessment of land use/land cover dynamics of Tso Moriri Lake, a Ramsar site in India.
Gupta, Sharad Kumar; Shukla, Dericks Praise
2016-12-01
Wetlands accounts for 6% area of the Earth's land cover and nearly 17% of the Hindu Kush Himalayan region. They are of utmost importance to climate dynamics and are critical links between terrestrial and aquatic ecosystems. Despite the need of high attention towards conserving and managing wetland resources, mapping them is a least practiced activity. This study shows the temporal change in land use and land cover pattern of Tso Moriri Lake, the highest altitude lake in India and designated as Ramsar site in year 2002, using multi-sensor and multi-date imagery. Due to change in hydro-meteorological conditions of the region, this lake area has been reduced. Since the lake recharge is dependent on snowmelt, hence change in climatic conditions (less snowfall in winters), to a certain extent, is also responsible for the decrease in water level and water spread of the lake. The result shows that the lake area has reduced approximately 2 km 2 in the last 15 years, and also, agriculture, grasslands, and vegetation cover have increased to a significant extent. Agricultural land and grasslands have doubled while the vegetation cover has increased more than six times, showing the coupled effect of climate change and anthropogenic activities. Trend of temperature and precipitation corroborates the effects of climate change in this region.
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Steyaert, L.T.; Hall, F.G.; Loveland, Thomas R.
1997-01-01
A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km ?? 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within
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Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale
Kreibich, Heidi; Schröter, Kai; Merz, Bruno
2016-05-01
Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB).In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.
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Impacts of Land Cover Changes on Climate over China
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.
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Lawrence, D. M.; Lombardozzi, D. L.; Lawrence, P.; Hurtt, G. C.
2017-12-01
Human land-use activities have resulted in large changes to the Earth surface, with resulting implications for climate. In the future, land-use activities are likely to intensify to meet growing demands for food, fiber, and energy. The Land Use Model Intercomparison Project (LUMIP) aims to further advance understanding of the broad question of impacts of land-use and land-cover change (LULCC) as well as more detailed science questions to get at process-level attribution, uncertainty, and data requirements in more depth and sophistication than possible in a multi-model context to date. LUMIP is multi-faceted and aims to advance our understanding of land-use change from several perspectives. In particular, LUMIP includes a factorial set of land-only simulations that differ from each other with respect to the specific treatment of land use or land management (e.g., irrigation active or not, crop fertilization active or not, wood harvest on or not), or in terms of prescribed climate. This factorial series of experiments serves several purposes and is designed to provide a detailed assessment of how the specification of land-cover change and land management affects the carbon, water, and energy cycle response to land-use change. The potential analyses that are possible through this set of experiments are vast. For example, comparing a control experiment with all land management active to an experiment with no irrigation allows a multi-model assessment of whether or not the increasing use of irrigation during the 20th century is likely to have significantly altered trends of regional water and energy fluxes (and therefore climate) and/or crop yield and carbon fluxes in agricultural regions. Here, we will present preliminary results from the factorial set of experiments utilizing the Community Land Model (CLM5). The analyses presented here will help guide multi-model analyses once the full set of LUMIP simulations are available.
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Phillips, M.; Denning, A. S.; Randall, D. A.; Branson, M.
2016-12-01
Multi-scale models of the atmosphere provide an opportunity to investigate processes that are unresolved by traditional Global Climate Models while at the same time remaining viable in terms of computational resources for climate-length time scales. The MMF represents a shift away from large horizontal grid spacing in traditional GCMs that leads to overabundant light precipitation and lack of heavy events, toward a model where precipitation intensity is allowed to vary over a much wider range of values. Resolving atmospheric motions on the scale of 4 km makes it possible to recover features of precipitation, such as intense downpours, that were previously only obtained by computationally expensive regional simulations. These heavy precipitation events may have little impact on large-scale moisture and energy budgets, but are outstanding in terms of interaction with the land surface and potential impact on human life. Three versions of the Community Earth System Model were used in this study; the standard CESM, the multi-scale `Super-Parameterized' CESM where large-scale parameterizations have been replaced with a 2D cloud-permitting model, and a multi-instance land version of the SP-CESM where each column of the 2D CRM is allowed to interact with an individual land unit. These simulations were carried out using prescribed Sea Surface Temperatures for the period from 1979-2006 with daily precipitation saved for all 28 years. Comparisons of the statistical properties of precipitation between model architectures and against observations from rain gauges were made, with specific focus on detection and evaluation of extreme precipitation events.
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Mapping land cover through time with the Rapid Land Cover Mapper—Documentation and user manual
Cotillon, Suzanne E.; Mathis, Melissa L.
2017-02-15
The Rapid Land Cover Mapper is an Esri ArcGIS® Desktop add-in, which was created as an alternative to automated or semiautomated mapping methods. Based on a manual photo interpretation technique, the tool facilitates mapping over large areas and through time, and produces time-series raster maps and associated statistics that characterize the changing landscapes. The Rapid Land Cover Mapper add-in can be used with any imagery source to map various themes (for instance, land cover, soils, or forest) at any chosen mapping resolution. The user manual contains all essential information for the user to make full use of the Rapid Land Cover Mapper add-in. This manual includes a description of the add-in functions and capabilities, and step-by-step procedures for using the add-in. The Rapid Land Cover Mapper add-in was successfully used by the U.S. Geological Survey West Africa Land Use Dynamics team to accurately map land use and land cover in 17 West African countries through time (1975, 2000, and 2013).
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PRESENTATION ON--LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA
Monitoring the locations and distributions of land-cover changes is important for establishing linkages between policy decisions, regulatory actions and subsequent landuse activities. Past efforts incorporating two-date change detection using moderate resolution data (e.g., Lands...
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LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA
Monitoring the locations and spatial distributions of land-cover changes and patterns is important for establishing links between policy decisions, regulatory actions and resulting landuse activities. The monitoring of change patterns across the landscape can also supply valuable...
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El Paso, TX NM 1:250,000 Quad USGS Land Use/Land Cover, 1986
Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...
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Las Cruces, NM TX 1:250,000 Quad USGS Land Use/Land Cover, 1986
Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...
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Saint Johns, AZ NM 1:250,000 Quad USGS Land Use/Land Cover, 1986
Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...
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Silver City, NM AZ 1:250,000 Quad USGS Land Use/Land Cover, 1986
Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...
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Temporal Land Cover Analysis for Net Ecosystem Improvement
Energy Technology Data Exchange (ETDEWEB)
Ke, Yinghai; Coleman, Andre M.; Diefenderfer, Heida L.
2013-04-09
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 analysis 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.
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Directory of Open Access Journals (Sweden)
Renke Lühken
2016-05-01
Full Text Available This study analysed Culicoides presence-absence data from 46 sampling sites in Germany, where monitoring was carried out from April 2007 until May 2008. Culicoides presence-absence data were analysed in relation to land cover data, in order to study whether the prevalence of biting midges is correlated to land cover data with respect to the trapping sites. We differentiated eight scales, i.e. buffer zones with radii of 0.5, 1, 2, 3, 4, 5, 7.5 and 10 km, around each site, and chose several land cover variables. For each species, we built eight single-scale models (i.e. predictor variables from one of the eight scales for each model based on averaged, generalised linear models and two multiscale models (i.e. predictor variables from all of the eight scales based on averaged, generalised linear models and generalised linear models with random forest variable selection. There were no significant differences between performance indicators of models built with land cover data from different buffer zones around the trapping sites. However, the overall performance of multi-scale models was higher than the alternatives. Furthermore, these models mostly achieved the best performance for the different species using the index area under the receiver operating characteristic curve. However, as also presented in this study, the relevance of the different variables could significantly differ between various scales, including the number of species affected and the positive or negative direction. This is an even more severe problem if multi-scale models are concerned, in which one model can have the same variable at different scales but with different directions, i.e. negative and positive direction of the same variable at different scales. However, multi-scale modelling is a promising approach to model the distribution of Culicoides species, accounting much more for the ecology of biting midges, which uses different resources (breeding sites, hosts, etc. at
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Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale
Directory of Open Access Journals (Sweden)
H. Kreibich
2016-05-01
Full Text Available Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB.In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.
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A Webgis Framework for Disseminating Processed Remotely Sensed on Land Cover Transformations
Caradonna, Grazia; Novelli, Antonio; Tarantino, Eufemia; Cefalo, Raffaela; Fratino, Umberto
2016-06-01
Mediterranean regions have experienced significant soil degradation over the past decades. In this context, careful land observation using satellite data is crucial for understanding the long-term usage patterns of natural resources and facilitating their sustainable management to monitor and evaluate the potential degradation. Given the environmental and political interest on this problem, there is urgent need for a centralized repository and mechanism to share geospatial data, information and maps of land change. Geospatial data collecting is one of the most important task for many users because there are significant barriers in accessing and using data. This limit could be overcome by implementing a WebGIS through a combination of existing free and open source software for geographic information systems (FOSS4G). In this paper we preliminary discuss methods for collecting raster data in a geodatabase by processing open multi-temporal and multi-scale satellite data aimed at retrieving indicators for land degradation phenomenon (i.e. land cover/land use analysis, vegetation indices, trend analysis, etc.). Then we describe a methodology for designing a WebGIS framework in order to disseminate information through maps for territory monitoring. Basic WebGIS functions were extended with the help of POSTGIS database and OpenLayers libraries. Geoserver was customized to set up and enhance the website functions developing various advanced queries using PostgreSQL and innovative tools to carry out efficiently multi-layer overlay analysis. The end-product is a simple system that provides the opportunity not only to consult interactively but also download processed remote sensing data.
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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.
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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.
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Land-use and Land-cover Change from 1974 to 2008 around Mobile Bay
Ellis, Jean; Spruce, Joseph; Smoot, James; Hilbert, Kent; Swann, Roberta
2008-01-01
This project is a Gulf of Mexico Application Pilot in which NASA Stennis Space Center (SSC) is working within a regional collaboration network of the Gulf of Mexico Alliance. NASA researchers, with support from the NASA SSC Applied Science Program Steering Committee, employed multi-temporal Landsat data to assess land-use and land-cover (LULC) changes in the coastal counties of Mobile and Baldwin, AL, between 1974 and 2008. A multi-decadal time-series, coastal LULC product unique to NASA SSC was produced. The geographic extent and nature of change was quantified for the open water, barren, upland herbaceous, non-woody wetland, upland forest, woody wetland, and urban landscapes. The National Oceanic and Atmospheric Administration (NOAA) National Coastal Development Data Center (NCDDC) will assist with the transition of the final product to the operational end user, which primarily is the Mobile Bay National Estuary Program (MBNEP). We found substantial LULC change over the 34-year study period, much more than is evident when the change occurring in the last years. Between 1974 and 2008, the upland forest landscape lost almost 6% of the total acreage, while urban land cover increased by slightly more than 3%. With exception to open water, upland forest is the dominant landscape, accounting for about 25-30% of the total area.
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Validating Remotely Sensed Land Surface Evapotranspiration Based on Multi-scale Field Measurements
Jia, Z.; Liu, S.; Ziwei, X.; Liang, S.
2012-12-01
The land surface evapotranspiration plays an important role in the surface energy balance and the water cycle. There have been significant technical and theoretical advances in our knowledge of evapotranspiration over the past two decades. Acquisition of the temporally and spatially continuous distribution of evapotranspiration using remote sensing technology has attracted the widespread attention of researchers and managers. However, remote sensing technology still has many uncertainties coming from model mechanism, model inputs, parameterization schemes, and scaling issue in the regional estimation. Achieving remotely sensed evapotranspiration (RS_ET) with confident certainty is required but difficult. As a result, it is indispensable to develop the validation methods to quantitatively assess the accuracy and error sources of the regional RS_ET estimations. This study proposes an innovative validation method based on multi-scale evapotranspiration acquired from field measurements, with the validation results including the accuracy assessment, error source analysis, and uncertainty analysis of the validation process. It is a potentially useful approach to evaluate the accuracy and analyze the spatio-temporal properties of RS_ET at both the basin and local scales, and is appropriate to validate RS_ET in diverse resolutions at different time-scales. An independent RS_ET validation using this method was presented over the Hai River Basin, China in 2002-2009 as a case study. Validation at the basin scale showed good agreements between the 1 km annual RS_ET and the validation data such as the water balanced evapotranspiration, MODIS evapotranspiration products, precipitation, and landuse types. Validation at the local scale also had good results for monthly, daily RS_ET at 30 m and 1 km resolutions, comparing to the multi-scale evapotranspiration measurements from the EC and LAS, respectively, with the footprint model over three typical landscapes. Although some
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Impacts of land use/cover classification accuracy on regional climate simulations
Ge, Jianjun; Qi, Jiaguo; Lofgren, Brent M.; Moore, Nathan; Torbick, Nathan; Olson, Jennifer M.
2007-03-01
Land use/cover change has been recognized as a key component in global change. Various land cover data sets, including historically reconstructed, recently observed, and future projected, have been used in numerous climate modeling studies at regional to global scales. However, little attention has been paid to the effect of land cover classification accuracy on climate simulations, though accuracy assessment has become a routine procedure in land cover production community. In this study, we analyzed the behavior of simulated precipitation in the Regional Atmospheric Modeling System (RAMS) over a range of simulated classification accuracies over a 3 month period. This study found that land cover accuracy under 80% had a strong effect on precipitation especially when the land surface had a greater control of the atmosphere. This effect became stronger as the accuracy decreased. As shown in three follow-on experiments, the effect was further influenced by model parameterizations such as convection schemes and interior nudging, which can mitigate the strength of surface boundary forcings. In reality, land cover accuracy rarely obtains the commonly recommended 85% target. Its effect on climate simulations should therefore be considered, especially when historically reconstructed and future projected land covers are employed.
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Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey.
Reis, Selçuk
2008-10-01
Mapping land use/land cover (LULC) changes at regional scales is essential for a wide range of applications, including landslide, erosion, land planning, global warming etc. LULC alterations (based especially on human activities), negatively effect the patterns of climate, the patterns of natural hazard and socio-economic dynamics in global and local scale. In this study, LULC changes are investigated by using of Remote Sensing and Geographic Information Systems (GIS) in Rize, North-East Turkey. For this purpose, firstly supervised classification technique is applied to Landsat images acquired in 1976 and 2000. Image Classification of six reflective bands of two Landsat images is carried out by using maximum likelihood method with the aid of ground truth data obtained from aerial images dated 1973 and 2002. The second part focused on land use land cover changes by using change detection comparison (pixel by pixel). In third part of the study, the land cover changes are analyzed according to the topographic structure (slope and altitude) by using GIS functions. The results indicate that severe land cover changes have occurred in agricultural (36.2%) (especially in tea gardens), urban (117%), pasture (-72.8%) and forestry (-12.8%) areas has been experienced in the region between 1976 and 2000. It was seen that the LULC changes were mostly occurred in coastal areas and in areas having low slope values.
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Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey
Directory of Open Access Journals (Sweden)
Selçuk Reis
2008-10-01
Full Text Available Mapping land use/land cover (LULC changes at regional scales is essential for a wide range of applications, including landslide, erosion, land planning, global warming etc. LULC alterations (based especially on human activities, negatively effect the patterns of climate, the patterns of natural hazard and socio-economic dynamics in global and local scale. In this study, LULC changes are investigated by using of Remote Sensing and Geographic Information Systems (GIS in Rize, North-East Turkey. For this purpose, firstly supervised classification technique is applied to Landsat images acquired in 1976 and 2000. Image Classification of six reflective bands of two Landsat images is carried out by using maximum likelihood method with the aid of ground truth data obtained from aerial images dated 1973 and 2002. The second part focused on land use land cover changes by using change detection comparison (pixel by pixel. In third part of the study, the land cover changes are analyzed according to the topographic structure (slope and altitude by using GIS functions. The results indicate that severe land cover changes have occurred in agricultural (36.2% (especially in tea gardens, urban (117%, pasture (-72.8% and forestry (-12.8% areas has been experienced in the region between 1976 and 2000. It was seen that the LULC changes were mostly occurred in coastal areas and in areas having low slope values.
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Directory of Open Access Journals (Sweden)
M. W. Thompson
2017-11-01
Full Text Available For service providers developing commercial value-added data content based on remote sensing technologies, the focus is to typically create commercially appropriate geospatial information which has downstream business value. The primary aim being to link locational intelligence with business intelligence in order to better make informed decisions. From a geospatial perspective this locational information must be relevant, informative, and most importantly current; with the ability to maintain the information timeously into the future for change detection purposes. Aligned with this, GeoTerraImage has successfully embarked on the production of land-cover/land-use content over southern Africa. The ability for a private company to successfully implement and complete such an exercise has been the capability to leverage the combined advantages of cutting edge data processing technologies and methodologies, with emphasis on processing repeatability and speed, and the use of a wide range of readily available imagery. These production workflows utilise a wide range of integrated procedures including machine learning algorithms, innovative use of non-specialists for sourcing of reference data, and conventional pixel and object-based image classification routines, and experienced/expert landscape interpretation. This multi-faceted approach to data produce development demonstrates the capability for SMME level commercial entities such as GeoTerraImage to generate industry applicable large data content, in this case, wide area coverage land-cover and land-use data across the sub-continent. Within this development, the emphasis has been placed on the key land-use information, such as mining, human settlements, and agriculture, given the importance of this geo-spatial land-use information in business and socio-economic applications and decision making.
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The effects of changing land cover on streamflow simulation in Puerto Rico
Van Beusekom, Ashley; 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.
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James D. Wickham; Robert V. O' Neill; Kurt H. Riitters; Timothy G. Wade; K. Bruce Jones
1997-01-01
Calculation of landscape metrics from land-cover data is becoming increasingly common. Some studies have shown that these measurements are sensitive to differences in land-cover composition, but none are known to have tested also their a sensitivity to land-cover misclassification. An error simulation model was written to test the sensitivity of selected land-scape...
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Validation of land use / land cover changes for Denmark
DEFF Research Database (Denmark)
Levin, Gregor; Johannsen, Vivian Kvist; Caspersen, Ole Hjort
2018-01-01
This report presents applied methods and results for a validation of land use and land cover changes for 1990 and 2014-2016. Results indicate that generally, accuracies of land use and land cover. However, afforestation and particularly deforestation are significantly overestimated....
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Land Use and Land Cover Change Analysis along the Coastal ...
African Journals Online (AJOL)
Agribotix GCS 077
are carried out on the land usually effect changes in its cover. ... The FAO document on land cover classification systems, (2000) partly answers this ... over the surface land, including water, vegetation, bare soils and or artificial structures. ... diseases may occur more readily in areas exposed by Land Use and Land Cover ...
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Land use/cover classification in the Brazilian Amazon using satellite images.
Lu, Dengsheng; Batistella, Mateus; Li, Guiying; Moran, Emilio; Hetrick, Scott; Freitas, Corina da Costa; Dutra, Luciano Vieira; Sant'anna, Sidnei João Siqueira
2012-09-01
Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation-based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi-resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical-based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.
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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
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Shiprock, AZ NM CO UT 1:250,000 Quad USGS Land Use/Land Cover, 1986
Earth Data Analysis Center, University of New Mexico — This dataset contains boundaries for land use and land cover polygons in New Mexico at a scale of 1:250,000. It is in a vector digital data structure. The source...
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Next generation of global land cover characterization, mapping, and monitoring
Giri, Chandra; Pengra, Bruce; Long, J.; Loveland, Thomas R.
2013-01-01
Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).
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Directory of Open Access Journals (Sweden)
A. M. Bernales
2016-06-01
Full Text Available The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC and land surface temperature (LST. Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric “Effective mesh size” was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas and looking for common predictors between LSTs of these two different farming periods.
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International Nuclear Information System (INIS)
Dunford, Robert W.; Donoghue, Daniel N.M.; Burt, Tim P.
2012-01-01
Evidence from a multi-date regional-scale analysis of both high-flow and annual-average water quality data from Galloway, south-west Scotland, demonstrates that forest land cover continues to exacerbate freshwater acidification. This is in spite of significant reductions in airborne pollutants. The relationship between freshwater sulphate and forest cover has decreased from 1996 to 2006 indicating a decrease in pollutant scavenging. The relationship between forest cover and freshwater acidity (pH) is, however, still present over the same period, and does not show conclusive signs of having declined. Furthermore, evidence for forest cover contributing to a chlorine bias in marine ion capture suggests that forest scavenging of sea-salts may mean that the forest acidification effect may continue in the absence of anthropogenic pollutant inputs, particularly in coastal areas. - Highlights: ► Forest cover and water chemistry remain linked despite decreased sulphate emissions. ► Forest cover has significant relationships SO 4 2− , Cl − , Na + , pH, ANC and Na:Cl ratio. ► Forest cover: pH relationships shows some evidence of decline 1996–2006. ► Forest cover: freshwater sulphate relationships show evidence of decline 1996–2006. ► Natural forest-mechanisms may exacerbate acidification, particularly sea-salt scavenging. - Relationships between forest land cover and freshwater pH continue to be evident despite declines in anthropogenic pollutant sulphate deposition; sea-salt scavenging may play a role.
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Microphysics in Multi-scale Modeling System with Unified Physics
Tao, Wei-Kuo
2012-01-01
Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.
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Land Use and Land Cover - MO 2015 Silver Land Cover (GDB)
NSGIC State | GIS Inventory — MoRAP produced and integrated data to map land cover and wetlands for the Upper Silver Creek Watershed in Illinois. LiDAR elevation and vegetation height information...
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Land Use and Land Cover - MO 2015 Meramec Land Cover (GDB)
NSGIC State | GIS Inventory — MoRAP produced and integrated data to map land cover and wetlands for the Meramec River bottomland in Missouri. LiDAR elevation and vegetation height information and...
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Influence of land development on stormwater runoff from a mixed land use and land cover catchment.
Paule-Mercado, M A; Lee, B Y; Memon, S A; Umer, S R; Salim, I; Lee, C-H
2017-12-01
Mitigating for the negative impacts of stormwater runoff is becoming a concern due to increased land development. Understanding how land development influences stormwater runoff is essential for sustainably managing water resources. In recent years, aggregate low impact development-best management practices (LID-BMPs) have been implemented to reduce the negative impacts of stormwater runoff on receiving water bodies. This study used an integrated approach to determine the influence of land development and assess the ecological benefits of four aggregate LID-BMPs in stormwater runoff from a mixed land use and land cover (LULC) catchment with ongoing land development. It used data from 2011 to 2015 that monitored 41 storm events and monthly LULC, and a Personalized Computer Storm Water Management Model (PCSWMM). The four aggregate LID-BMPs are: ecological (S1), utilizing pervious covers (S2), and multi-control (S3) and (S4). These LID-BMPs were designed and distributed in the study area based on catchment characteristics, cost, and effectiveness. PCSWMM was used to simulate the monitored storm events from 2014 (calibration: R 2 and NSE>0.5; RMSE 0.5; RMSE runoff data and LULC change patterns (only 2015 for LID-BMPs) were used. Results show that the expansion of bare land and impervious cover, soil alteration, and high amount of precipitation influenced the stormwater runoff variability during different phases of land development. The four aggregate LID-BMPs reduced runoff volume (34%-61%), peak flow (6%-19%), and pollutant concentrations (53%-83%). The results of this study, in addition to supporting local LULC planning and land development activities, also could be applied to input data for empirical modeling, and designing sustainable stormwater management guidelines and monitoring strategies. Copyright © 2017 Elsevier B.V. All rights reserved.
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Extraction of land cover change information from ENVISAT-ASAR data in Chengdu Plain
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.
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Land cover/land use change in semi-arid Inner Mongolia: 1992-2004
Energy Technology Data Exchange (ETDEWEB)
John, Ranjeet; Chen Jiquan; Lu Nan; Wilske, Burkhard, E-mail: ranjeet.john@utoledo.ed [Department of Environmental Sciences, University of Toledo, Toledo, OH 43606 (United States)
2009-10-15
The semi-arid grasslands in Inner Mongolia (IM) are under increasing stress owing to climate change and rapid socio-economic development in the recent past. We investigated changes in land cover/land use and landscape structure between 1992 and 2004 through the analysis of AVHRR and MODIS derived land cover data. The scale of analysis included the regional level (i.e. the whole of IM) as well as the level of the dominant biomes (i.e. the grassland and desert). We quantified proportional change, rate of change and the changes in class-level landscape metrics using the landscape structure analysis program FRAGSTATS. The dominant land cover types, grassland and barren, 0.47 and 0.27 million km{sup 2}, respectively, have increased proportionally. Cropland and urban land use also increased to 0.15 million km{sup 2} and 2197 km{sup 2}, respectively. However, the results further indicated increases in both the homogeneity and fragmentation of the landscape. Increasing homogeneity was mainly related to the reduction in minority cover types such as savanna, forests and permanent wetlands and increasing cohesion, aggregation index and clumpy indices. Conversely, increased fragmentation of the landscape was based on the increase in patch density and the interspersion/juxtaposition index (IJI). It is important to note the socio-economic growth in this fragile ecosystem, manifested by an increasing proportion of agricultural and urban land use not just at the regional level but also at the biome level in the context of regional climate change and increasing water stress.
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Land cover/land use change in semi-arid Inner Mongolia: 1992-2004
International Nuclear Information System (INIS)
John, Ranjeet; Chen Jiquan; Lu Nan; Wilske, Burkhard
2009-01-01
The semi-arid grasslands in Inner Mongolia (IM) are under increasing stress owing to climate change and rapid socio-economic development in the recent past. We investigated changes in land cover/land use and landscape structure between 1992 and 2004 through the analysis of AVHRR and MODIS derived land cover data. The scale of analysis included the regional level (i.e. the whole of IM) as well as the level of the dominant biomes (i.e. the grassland and desert). We quantified proportional change, rate of change and the changes in class-level landscape metrics using the landscape structure analysis program FRAGSTATS. The dominant land cover types, grassland and barren, 0.47 and 0.27 million km 2 , respectively, have increased proportionally. Cropland and urban land use also increased to 0.15 million km 2 and 2197 km 2 , respectively. However, the results further indicated increases in both the homogeneity and fragmentation of the landscape. Increasing homogeneity was mainly related to the reduction in minority cover types such as savanna, forests and permanent wetlands and increasing cohesion, aggregation index and clumpy indices. Conversely, increased fragmentation of the landscape was based on the increase in patch density and the interspersion/juxtaposition index (IJI). It is important to note the socio-economic growth in this fragile ecosystem, manifested by an increasing proportion of agricultural and urban land use not just at the regional level but also at the biome level in the context of regional climate change and increasing water stress.
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A Joint Land Cover Mapping and Image Registration Algorithm Based on a Markov Random Field Model
Directory of Open Access Journals (Sweden)
Apisit Eiumnoh
2013-10-01
Full Text Available Traditionally, image registration of multi-modal and multi-temporal images is performed satisfactorily before land cover mapping. However, since multi-modal and multi-temporal images are likely to be obtained from different satellite platforms and/or acquired at different times, perfect alignment is very difficult to achieve. As a result, a proper land cover mapping algorithm must be able to correct registration errors as well as perform an accurate classification. In this paper, we propose a joint classification and registration technique based on a Markov random field (MRF model to simultaneously align two or more images and obtain a land cover map (LCM of the scene. The expectation maximization (EM algorithm is employed to solve the joint image classification and registration problem by iteratively estimating the map parameters and approximate posterior probabilities. Then, the maximum a posteriori (MAP criterion is used to produce an optimum land cover map. We conducted experiments on a set of four simulated images and one pair of remotely sensed images to investigate the effectiveness and robustness of the proposed algorithm. Our results show that, with proper selection of a critical MRF parameter, the resulting LCMs derived from an unregistered image pair can achieve an accuracy that is as high as when images are perfectly aligned. Furthermore, the registration error can be greatly reduced.
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CLC2000 land cover database of the Netherlands; monitoring land cover changes between 1986 and 2000
Hazeu, G.W.
2003-01-01
The 1986 CORINE land cover database of the Netherlands was revised and updated on basis of Landsat satellite images and ancillary data. Interpretation of satellite images from 1986 and 2000 resulted in the CLC2000, CLC1986rev and CLCchange databases. A standard European legend and production methodology was applied. Thirty land cover classes were discerned. Most extended land cover types were pastures (231), arable land (211) and complex cultivation patterns (242). Between 1986 and 2000 aroun...
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Allegheny County Land Cover Areas
Allegheny County / City of Pittsburgh / Western PA Regional Data Center — The Land Cover dataset demarcates 14 land cover types by area; such as Residential, Commercial, Industrial, Forest, Agriculture, etc. If viewing this description on...
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Directory of Open Access Journals (Sweden)
Stefan Dech
2012-09-01
Full Text Available We present a novel and innovative automated processing environment for the derivation of land cover (LC and land use (LU information. This processing framework named TWOPAC (TWinned Object and Pixel based Automated classification Chain enables the standardized, independent, user-friendly, and comparable derivation of LC and LU information, with minimized manual classification labor. TWOPAC allows classification of multi-spectral and multi-temporal remote sensing imagery from different sensor types. TWOPAC enables not only pixel-based classification, but also allows classification based on object-based characteristics. Classification is based on a Decision Tree approach (DT for which the well-known C5.0 code has been implemented, which builds decision trees based on the concept of information entropy. TWOPAC enables automatic generation of the decision tree classifier based on a C5.0-retrieved ascii-file, as well as fully automatic validation of the classification output via sample based accuracy assessment.Envisaging the automated generation of standardized land cover products, as well as area-wide classification of large amounts of data in preferably a short processing time, standardized interfaces for process control, Web Processing Services (WPS, as introduced by the Open Geospatial Consortium (OGC, are utilized. TWOPAC’s functionality to process geospatial raster or vector data via web resources (server, network enables TWOPAC’s usability independent of any commercial client or desktop software and allows for large scale data processing on servers. Furthermore, the components of TWOPAC were built-up using open source code components and are implemented as a plug-in for Quantum GIS software for easy handling of the classification process from the user’s perspective.
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Scenarios of land cover in China
Yue, Tian Xiang; Fan, Ze Meng; Liu, Ji Yuan
2007-02-01
A method for surface modeling of land cover change (SMLC) is developed on the basis of establishing transition probability matrixes between land cover types and HLZ types. SMLC is used to simulate land cover scenarios of China for the years 2039, 2069 and 2099, for which HLZ scenarios are first simulated in terms of HadCM3 climatic scenarios that are downscaled in zonal model of spatial climate change in China. This paper also analyzes spatial distribution of land cover types, area change and mean center shift of each land cover type, ecotope diversity, and patch connectivity under the land cover scenarios. The results show that cultivated land would decrease and woodland would expand greatly with climatic change, which coincides with consequences expected by implementation of Grain-for-Green policy. Nival area would shrink, and desertification area would expand at a comparatively slow rate in future 100 years. Climate change would generally cause less ecotope diversity and more patch connectivity. Ecosystems in China would have a pattern of beneficial cycle after efficient ecological conservation and restoration. However, if human activities would exceed regulation capacity of ecosystems themselves, the ecosystems in China might deteriorate more seriously.
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Comparison and assessment of coarse resolution land cover maps for Northern Eurasia
Dirk Pflugmacher; Olga N. Krankina; Warren B. Cohen; Mark A. Friedl; Damien Sulla-Menashe; Robert E. Kennedy; Peder Nelson; Tatiana V. Loboda; Tobias Kuemmerle; Egor Dyukarev; Vladimir Elsadov; Viacheslav I. Kharuk
2011-01-01
Information on land cover at global and continental scales is critical for addressing a range of ecological, socioeconomic and policy questions. Global land cover maps have evolved rapidly in the last decade, but efforts to evaluate map uncertainties have been limited, especially in remote areas like Northern Eurasia. Northern Eurasia comprises a particularly diverse...
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Carbon stock projection in North Sumatera using multi objective land allocation approach
Ichwani, S. N.; Wulandari, R.; Ramachandra, A.
2018-05-01
Nowadays, GHG emission is a critical issue for environmental management due to the large scale of land cover change, especially forest cover. This study provides a protection development strategy for North Sumatera as one way to manage the area. By using Multi Objective Land Allocation (MOLA), we evaluated two GHG emission scenarios, including a Business As Usual (BAU) scenario and Protection scenario. The result shows that the province will lose the carbon stock up to 24 million tons in the year of 2035 by using a BAU scenario. On the other hand, by implementing the Protection scenario, total carbon stock that is lost in the same period is about 5 millions tons solely. It proves that protection scenario is a good scenario and effective to reduce the carbon loss. Furthermore, this scenario can be an alternative for North Sumatera spatial plan.
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Lark, Tyler J.; Mueller, Richard M.; Johnson, David M.; Gibbs, Holly K.
2017-10-01
Monitoring agricultural land is important for understanding and managing food production, environmental conservation efforts, and climate change. The United States Department of Agriculture's Cropland Data Layer (CDL), an annual satellite imagery-derived land cover map, has been increasingly used for this application since complete coverage of the conterminous United States became available in 2008. However, the CDL is designed and produced with the intent of mapping annual land cover rather than tracking changes over time, and as a result certain precautions are needed in multi-year change analyses to minimize error and misapplication. We highlight scenarios that require special considerations, suggest solutions to key challenges, and propose a set of recommended good practices and general guidelines for CDL-based land change estimation. We also characterize a problematic issue of crop area underestimation bias within the CDL that needs to be accounted for and corrected when calculating changes to crop and cropland areas. When used appropriately and in conjunction with related information, the CDL is a valuable and effective tool for detecting diverse trends in agriculture. By explicitly discussing the methods and techniques for post-classification measurement of land-cover and land-use change using the CDL, we aim to further stimulate the discourse and continued development of suitable methodologies. Recommendations generated here are intended specifically for the CDL but may be broadly applicable to additional remotely-sensed land cover datasets including the National Land Cover Database (NLCD), Moderate Resolution Imaging Spectroradiometer (MODIS)-based land cover products, and other regional, national, and global land cover classification maps.
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Altaf, Sadaff; Meraj, Gowhar; Romshoo, Shakil Ahmad
2014-12-01
Complex mountainous environments such as Himalayas are highly susceptibility to natural hazards particular those that are triggered by the action of water such as floods, soil erosion, mass movements and siltation of the hydro-electric power dams. Among all the natural hazards, soil erosion is the most implicit and the devastating hazard affecting the life and property of the millions of people living in these regions. Hence to review and devise strategies to reduce the adverse impacts of soil erosion is of utmost importance to the planners of watershed management programs in these regions. This paper demonstrates the use of satellite based remote sensing data coupled with the observational field data in a multi-criteria analytical (MCA) framework to estimate the soil erosion susceptibility of the sub-watersheds of the Rembiara basin falling in the western Himalaya, using geographical information system (GIS). In this paper, watershed morphometry and land cover are used as an inputs to the MCA framework to prioritize the sub-watersheds of this basin on the basis of their different susceptibilities to soil erosion. Methodology included the derivation of a set of drainage and land cover parameters that act as the indicators of erosion susceptibility. Further the output from the MCA resulted in the categorization of the sub-watersheds into low, medium, high and very high erosion susceptibility classes. A detailed prioritization map for the susceptible sub-watersheds based on the combined role of land cover and morphometry is finally presented. Besides, maps identifying the susceptible sub-watersheds based on morphometry and land cover only are also presented. The results of this study are part of the watershed management program in the study area and are directed to instigate appropriate measures to alleviate the soil erosion in the study area.
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Multi-granularity synthesis segmentation for high spatial resolution Remote sensing images
International Nuclear Information System (INIS)
Yi, Lina; Liu, Pengfei; Qiao, Xiaojun; Zhang, Xiaoning; Gao, Yuan; Feng, Boyan
2014-01-01
Traditional segmentation method can only partition an image in a single granularity space, with segmentation accuracy limited to the single granularity space. This paper proposes a multi-granularity synthesis segmentation method for high spatial resolution remote sensing images based on a quotient space model. Firstly, we divide the whole image area into multiple granules (regions), each region is consisted of ground objects that have similar optimal segmentation scale, and then select and synthesize the sub-optimal segmentations of each region to get the final segmentation result. To validate this method, the land cover category map is used to guide the scale synthesis of multi-scale image segmentations for Quickbird image land use classification. Firstly, the image is coarsely divided into multiple regions, each region belongs to a certain land cover category. Then multi-scale segmentation results are generated by the Mumford-Shah function based region merging method. For each land cover category, the optimal segmentation scale is selected by the supervised segmentation accuracy assessment method. Finally, the optimal scales of segmentation results are synthesized under the guide of land cover category. Experiments show that the multi-granularity synthesis segmentation can produce more accurate segmentation than that of a single granularity space and benefit the classification
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Le, Q.; Vlek, P. L.; Park, S.
2005-12-01
Land-use and land-cover change (LUCC) is an essential environmental process that should be monitored and prognosticated to provide a basis for better land management policy. However, LUCC modeling is a challenge due to the complex nature and unexpected behavior of both human drivers and natural constraints. This paper presents a multi-agent-based model to simulate spatio-temporal land-use changes and the interdependent socio-economic dynamics emerging from the complex socio-ecological interactions at micro levels resulting from land-use policy interventions. The model provides land-use scenarios under alternative policy to support decisions on land management for improved rural livelihoods while protecting the environment. In the multi-agent simulation model, the human community is represented by household agents (heterogeneous farming households) with their profiles and decision-making mechanisms about land use. The household profile defines the five asset dimensions of household livelihood (e.g., social, human, financial, natural and physical assets). The land-use decision-making program works by taking inputs from the household profile, perceived spatial environmental attributes, and introduced policies. The decision-making program is a logical procedure that combines a land-use choice model (multi-nominal logistic choices) and anthropological rules. The landscape environment is represented by landscape agents (congruent land patches of 30mx30m) with their state variables and ecological response mechanisms to environmental changes and human interventions. State variables of landscape agents correspond to spatial GIS-raster layers of biophysical, economic, and institutional variables. Ecological mechanisms of landscape agents are represented by internal sub-models of agricultural and forest productivity dynamics, which work in response to the current state, history, and spatial neighbourhood of the landscape agents. A multi-agent based protocol coordinates the
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Land use, land cover, and drainage on the Albemarle-Pamlico Peninsula, Eastern North Carolina, 1974
Daniel, C.C.
1978-01-01
A land use, land cover, and drainage map of the 2,000-square-mile Albermarle-Pamlico peninsula of eastern North Carolina has been prepared, at a scale of 1:125,000, as part of a larger study of the effects of large-scale land clearing on regional hydrology. The peninsula includes the most extensive area of wetland in North Carolina and one of the largest in the country. In recent years the pace of land clearing on the peninsula has accelerated as land is being converted from forest, swamp, and brushland to agricultural use. Conversion of swamps to intensive farming operations requires profound changes in the landscape. Vegetation is uprooted and burned and ditches and canals are dug to remove excess water. What is the impact of these changes on ground-water supplies and on the streams and surrounding coastal waters which receive the runoff This map will aid in answering these and similar questions that have arisen about the patterns of land use and the artificial drainage system that removes excess water from the land. By showing both land use and drainage, this map can be used to identify those areas where water-related problems may occur and help assess the nature and causes of these problems. The map covers the entire area east of the Suffolk Scarp, an area of about 2,000 square miles, for the year 1974 using data from 1974-76. Land use and land cover were compiled and modified from the U.S. Geological Survey 's Rocky Mount and Manteo LUDA maps. Additional information came from U.S. Geological Survey orthophotoquads, Landsat imagery, and field checking. Drainage was mapped from orthophotoquads, some field inspection, and 7-1/2 minute topographic quadrangle maps.
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Saah, D.; Tenneson, K.; Hanh, Q. N.; Aekakkararungroj, A.; Aung, K. S.; Goldstein, J.; Cutter, P. G.; Maus, P.; Markert, K. N.; Anderson, E.; Ellenburg, W. L.; Ate, P.; Flores Cordova, A. I.; Vadrevu, K.; Potapov, P.; Phongsapan, K.; Chishtie, F.; Clinton, N.; Ganz, D.
2017-12-01
Earth observation and Geographic Information System (GIS) tools, products, and services are vital to support the environmental decision making by governmental institutions, non-governmental agencies, and the general public. At the heart of environmental decision making is the monitoring land cover and land use change (LCLUC) for land resource planning and for ecosystem services, including biodiversity conservation and resilience to climate change. A major challenge for monitoring LCLUC in developing regions, such as Southeast Asia, is inconsistent data products at inconsistent intervals that have different typologies across the region and are typically made in without stakeholder engagement or input. Here we present the Regional Land Cover Monitoring System (RLCMS), a novel land cover mapping effort for Southeast Asia, implemented by SERVIR-Mekong, a joint NASA-USAID initiative that brings Earth observations to improve environmental decision making in developing countries. The RLCMS focuses on mapping biophysical variables (e.g. canopy cover, tree height, or percent surface water) at an annual interval and in turn using those biophysical variables to develop land cover maps based on stakeholder definitions of land cover classes. This allows for flexible and consistent land cover classifications that can meet the needs of different institutions across the region. Another component of the RLCMS production is the stake-holder engagement through co-development. Institutions that directly benefit from this system have helped drive the development for regional needs leading to services for their specific uses. Examples of services for regional stakeholders include using the RLCMS to develop maps using the IPCC classification scheme for GHG emission reporting and developing custom annual maps as an input to hydrologic modeling/flood forecasting systems. In addition to the implementation of this system and the service stemming from the RLCMS in Southeast Asia, it is
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Land cover fire proneness in Europe
Directory of Open Access Journals (Sweden)
Mario Gonzalez Pereira
2014-12-01
Full Text Available Aim of study: This study aims to identify and characterize the spatial and temporal evolution of the types of vegetation that are most affected by forest fires in Europe. The characterization of the fuels is an important issue of the fire regime in each specific ecosystem while, on the other hand, fire is an important disturbance for global vegetation dynamics.Area of study: Southern European countries: Portugal, Spain, France, Italy and Greece.Material and Methods: Corine Land Cover maps for 2000 and 2006 (CLC2000, CLC2006 and burned area (BA perimeters, from 2000 to 2013 in Europe are combined to access the spatial and temporal evolution of the types of vegetation that are most affected by wild fires using descriptive statistics and Geographical Information System (GIS techniques.Main results: The spatial and temporal distribution of BA perimeters, vegetation and burnt vegetation by wild fires was performed and different statistics were obtained for Mediterranean and entire Europe, confirming the usefulness of the proposed land cover system. A fire proneness index is proposed to assess the fire selectivity of land cover classes. The index allowed to quantify and to compare the propensity of vegetation classes and countries to fire.Research highlights: The usefulness and efficiency of the land cover classification scheme and fire proneness index. The differences between northern Europe and southern Europe and among the Mediterranean region in what concerns to vegetation cover, fire incidence, area burnt in land cover classes and fire proneness between classes for the different countries.Keywords: Fire proneness; Mixed forests; Land cover/land use; Fire regime; Europe; GIS; Corine land cover.
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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
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Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.
2017-08-01
The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over
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Directory of Open Access Journals (Sweden)
Recep Gundogan
2008-02-01
Full Text Available The satellite imagery has been effectively utilized for classifying land covertypes and detecting land cover conditions. The Advanced Spaceborne Thermal Emissionand Reflection Radiometer (ASTER sensor imagery has been widely used in classificationprocess of land cover. However, atmospheric corrections have to be made by preprocessingsatellite sensor imagery since the electromagnetic radiation signals received by the satellitesensors can be scattered and absorbed by the atmospheric gases and aerosols. In this study,an ASTER sensor imagery, which was converted into top-of-atmosphere reflectance(TOA, was used to classify the land use/cover types, according to COoRdination ofINformation on the Environment (CORINE land cover nomenclature, for an arearepresenting the heterogonous characteristics of eastern Mediterranean regions inKahramanmaras, Turkey. The results indicated that using the surface reflectance data ofASTER sensor imagery can provide accurate (i.e. overall accuracy and kappa values of83.2% and 0.79, respectively and low-cost cover mapping as a part of inventory forCORINE Land Cover Project.
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Urban land use and land cover change analysis and modeling a case study area Malatya, Turkey
Baysal, Gülendam
2013-01-01
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies. This research was conducted to analyze the land use and land cover changes and to model the changes for the case study area Malatya, Turkey. The first step of the study was acquisition of multi temporal data in order to detect the changes over the time. For this purpose satellite images (Landsat 1990-2000-2010) have been used. In order to acquire data from satel...
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Scrubbing up: multi-scale investigation of woody encroachment in a southern African savannah
Marston, Christopher G.; Aplin, Paul; Wilkinson, David M.; Field, Richard; O'Regan, Hannah J.
2017-01-01
Changes in the extent of woody vegetation represent a major conservation question in many savannah systems around the globe. To address the problem of the current lack of broad-scale cost-effective tools for land cover monitoring in complex savannah environments, we use a multi-scale approach to quantifying vegetation change in Kruger National Park (KNP), South Africa. We test whether medium spatial resolution satellite data (Landsat, existing back to the 1970s), which have pixel sizes larger...
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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.
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Gao, G.; Fu, B.; Liu, Y.; Wang, Y.
2012-12-01
This study used the in-situ measurement, model simulation and radioisotope tracing methods to investigate the effects of land cover on runoff and soil erosion at plot and hillslope scales in the Loess Plateau of China. Three runoff plot groups covered by sparse young trees (Group 1), native shrubs (Group 2) and dense tussock (Group 3) with different revegetation time were established in the Yangjuangou catchment of Loess Plateau. Greater runoff was produced in plot groups (Group 2 and Group 3) with higher vegetation cover and longer restoration time as a result of soil compaction processes. Both of the runoff coefficient and soil loss rate decreased with increasing plot length in Group 2 and Group 3 plots. The runoff coefficient increased with plot length in Group 1 plots located at the early stage of revegetation, and the soil loss rates increased over an area threshold. Therefore, the effect of scale on runoff and soil erosion was dependent on restoration extent. The antecedent moisture condition (AMC) was explicitly incorporated in runoff production and initial abstraction of the SCS-CN model, and the direct effect of runoff on event soil loss was considered in the RUSLE model by adopting a rainfall-runoff erosivity factor. The modified SCS-CN and RUSLE models were coupled to link rainfall-runoff-erosion modeling. The modified SCS-CN model was accurate in predicting event runoff from the three plot groups with Nash-Sutcliffe model efficiency (EF) over 0.85, and the prediction accuracy of the modified RUSLE model was satisfactory with EF values being over 0.70. The 137Cs tracing technique was used to examine soil erosion under different land uses and land-use combinations. The results show that the order of erosion rate in different land uses increases sequentially from mature forest to grass to young forest to orchard to terrace crop. The land-use combinations of 'grass (6 years old) + mature forest (25 years old) + grass (25 years old)' and 'grass (6 years old
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Ding, Jiao; Jiang, Yuan; Liu, Qi; Hou, Zhaojiang; Liao, Jianyu; Fu, Lan; Peng, Qiuzhi
2016-05-01
Understanding the relationships between land use patterns and water quality in low-order streams is useful for effective landscape planning to protect downstream water quality. A clear understanding of these relationships remains elusive due to the heterogeneity of land use patterns and scale effects. To better assess land use influences, we developed empirical models relating land use patterns to the water quality of low-order streams at different geomorphic regions across multi-scales in the Dongjiang River basin using multivariate statistical analyses. The land use pattern was quantified in terms of the composition, configuration and hydrological distance of land use types at the reach buffer, riparian corridor and catchment scales. Water was sampled under summer base flow at 56 low-order catchments, which were classified into two homogenous geomorphic groups. The results indicated that the water quality of low-order streams was most strongly affected by the configuration metrics of land use. Poorer water quality was associated with higher patch densities of cropland, orchards and grassland in the mountain catchments, whereas it was associated with a higher value for the largest patch index of urban land use in the plain catchments. The overall water quality variation was explained better by catchment scale than by riparian- or reach-scale land use, whereas the spatial scale over which land use influenced water quality also varied across specific water parameters and the geomorphic basis. Our study suggests that watershed management should adopt better landscape planning and multi-scale measures to improve water quality. Copyright © 2016 Elsevier B.V. All rights reserved.
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Sanford, Ward E.; Selnick, David L.
2013-01-01
Evapotranspiration (ET) is an important quantity for water resource managers to know because it often represents the largest sink for precipitation (P) arriving at the land surface. In order to estimate actual ET across the conterminous United States (U.S.) in this study, a water-balance method was combined with a climate and land-cover regression equation. Precipitation and streamflow records were compiled for 838 watersheds for 1971-2000 across the U.S. to obtain long-term estimates of actual ET. A regression equation was developed that related the ratio ET/P to climate and land-cover variables within those watersheds. Precipitation and temperatures were used from the PRISM climate dataset, and land-cover data were used from the USGS National Land Cover Dataset. Results indicate that ET can be predicted relatively well at a watershed or county scale with readily available climate variables alone, and that land-cover data can also improve those predictions. Using the climate and land-cover data at an 800-m scale and then averaging to the county scale, maps were produced showing estimates of ET and ET/P for the entire conterminous U.S. Using the regression equation, such maps could also be made for more detailed state coverages, or for other areas of the world where climate and land-cover data are plentiful.
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Geovisualization of land use and land cover using bivariate maps and Sankey flow diagrams
Strode, Georgianna; Mesev, Victor; Thornton, Benjamin; Jerez, Marjorie; Tricarico, Thomas; McAlear, Tyler
2018-05-01
The terms `land use' and `land cover' typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cover tracts. We believe this is misleading, and feel we need to reiterate the well-established symbiosis of land uses as amalgams of land covers; in other words land covers are subsets of land use. Our paper addresses this spatially complex, and frequently ambiguous relationship, and posits that bivariate cartographic techniques are an ideal vehicle for representing both land use and land cover simultaneously. In more specific terms, we explore the use of nested symbology as ways to represent graphically land use and land cover, where land cover are circles nested with land use squares. We also investigate bivariate legends for representing statistical covariance as a means for visualizing the combinations of land use and cover. Lastly, we apply Sankey flow diagrams to further illustrate the complex, multifaceted relationships between land use and land cover. Our work is demonstrated on data representing land use and cover data for the US state of Florida.
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Estimating land use / land cover changes in Denmark from 1990 - 2012
DEFF Research Database (Denmark)
Levin, Gregor; Kastrup Blemmer, Morten; Gyldenkærne, Steen
According to the article 3(4) of the Kyoto Protocol, Denmark is obliged to document sequestration and emission of carbon dioxide from land use and land cover and changes in these. This report documents and describes applied data end developed methods aiming at estimating amounts and changes in land...... use and land cover for Denmark for since 1990. Estimation of land use and land cover categories and changes in these is predominantly based on existing categorical (i.e. pre-classified) geographical information. Estimations are elaborated for the period from 1990 to 2005, from 2005 to 2011 and from...... 2011 to 2012. Due to limited availability of historical spatially explicit information, estimations of change in land use and land cover from 1990 up to 2011 do, to some degree, involve decisions based on expert knowledge. Due to a significant increase in the availability of detailed spatially specific...
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Directory of Open Access Journals (Sweden)
Vladimir R. Wingate
2016-08-01
Full Text Available Woodlands and savannahs provide essential ecosystem functions and services to communities. On the African continent, they are widely utilized and converted to subsistence and intensive agriculture or urbanized. This study investigates changes in land cover over four administrative regions of North Eastern Namibia within the Kalahari woodland savannah biome, covering a total of 107,994 km2. Land cover is mapped using multi-sensor Landsat imagery at decadal intervals from 1975 to 2014, with a post-classification change detection method. The dominant change observed was a reduction in the area of woodland savannah due to the expansion of agriculture, primarily in the form of small-scale cereal and pastoral production. More specifically, woodland savannah area decreased from 90% of the study area in 1975 to 83% in 2004, and then increased to 86% in 2014, while agricultural land increased from 6% to 12% between 1975 and 2014. We assess land cover changes in relation to towns, villages, rivers and roads and find most changes occurred in proximity to these. In addition, we find that most land cover changes occur within land designated as communally held, followed by state protected land. With widespread changes occurring across the African continent, this study provides important data for understanding drivers of change in the region and their impacts on the distribution of woodland savannahs.
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Remote sensing as a source of land cover information utilized in the universal soil loss equation
Morris-Jones, D. R.; Morgan, K. M.; Kiefer, R. W.; Scarpace, F. L.
1979-01-01
In this study, methods for gathering the land use/land cover information required by the USLE were investigated with medium altitude, multi-date color and color infrared 70-mm positive transparencies using human and computer-based interpretation techniques. Successful results, which compare favorably with traditional field study methods, were obtained within the test site watershed with airphoto data sources and human airphoto interpretation techniques. Computer-based interpretation techniques were not capable of identifying soil conservation practices but were successful to varying degrees in gathering other types of desired land use/land cover information.
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Carbon Assessment of Hawaii Land Cover Map (CAH_LandCover)
Department of the Interior — While there have been many maps produced that depict vegetation for the state of Hawai‘i only a few of these display land cover for all of the main Hawaiian Islands,...
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1990 Kansas Land Cover Patterns Update
Kansas Data Access and Support Center — In 2008, an update of the 1990 Kansas Land Cover Patterns (KLCP) database was undertaken. The 1990 KLCP database depicts 10 general land cover classes for the State...
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Muñoz-Rojas, M.; Jordán, A.; Zavala, L. M.; de la Rosa, D.; Abd-Elmabod, S. K.; Anaya-Romero, M.
2012-04-01
Land use has significantly changed during the last decades at global and local scale, while the importance of ecosystems as sources/sinks of C has been highlighted, emphasizing the global impact of land use changes. The aim of this research was to improve and test methodologies to assess land use and land cover change dynamics and temporal and spatial variability in C stored in soils and vegetation at a wide scale. A Mediterranean region (Andalusia, Southern Spain) was selected for this pilot study in the period 1956-2007. Land use changes were detected by comparison of data layers, and soil information was gathered from available spatial databases. Data from land use and land cover change were reclassified according to CORINE Land Cover legend, according to land cover flows reported in Europe. Carbon vegetation stocks for 1956 and 2007 were calculated by multiplying C density for each land cover class and area. Soil carbon stocks were determined for each combination of soil and land use type at different standard depths (0-25, 25-50 and 50-75 cm). Total current carbon stocks (2007) are 156.1 Tg in vegetation and 415 Tg in soils (in the first 75 cm). Southern Spain has supported intense land cover changes affecting more than one third of the study area, with significant consequences for C stocks. Vegetation carbon increased 17.24 Mt since 1956 after afforestation practices and intensification of agriculture. Soil C stock decreased mainly in Cambisols and Regosols (above 80%) after forest areas were transformed into agricultural areas. The methodologies and information generated in this project constitute a basis for modelling of C sequestration and analysis of potential scenarios, as a new component of MicroLEIS DSS. This study highlights the importance of land cover changes for C sequestration in Mediterranean areas, highlighting possible trends for management policies in Europe in order to mitigate climate change.
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Michael C. Wimberly; Janet L. Ohmann
2004-01-01
Human modification of forest habitats is a major component of global environmental change. Even areas that remain predominantly forested may be changed considerably by human alteration of historical disturbance regimes. To better understand human influences on the abundance and pattern of forest habitats, we studied forest land cover change from 1936 to 1996 in a 25...
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Directory of Open Access Journals (Sweden)
Uttam Kumar
2017-10-01
Full Text Available Land cover (LC refers to the physical and biological cover present over the Earth’s surface in terms of the natural environment such as vegetation, water, bare soil, etc. Most LC features occur at finer spatial scales compared to the resolution of primary remote sensing satellites. Therefore, observed data are a mixture of spectral signatures of two or more LC features resulting in mixed pixels. One solution to the mixed pixel problem is the use of subpixel learning algorithms to disintegrate the pixel spectrum into its constituent spectra. Despite the popularity and existing research conducted on the topic, the most appropriate approach is still under debate. As an attempt to address this question, we compared the performance of several subpixel learning algorithms based on least squares, sparse regression, signal–subspace and geometrical methods. Analysis of the results obtained through computer-simulated and Landsat data indicated that fully constrained least squares (FCLS outperformed the other techniques. Further, FCLS was used to unmix global Web-Enabled Landsat Data to obtain abundances of substrate (S, vegetation (V and dark object (D classes. Due to the sheer nature of data and computational needs, we leveraged the NASA Earth Exchange (NEX high-performance computing architecture to optimize and scale our algorithm for large-scale processing. Subsequently, the S-V-D abundance maps were characterized into four classes, namely forest, farmland, water and urban areas (in conjunction with nighttime lights data over California, USA using a random forest classifier. Validation of these LC maps with the National Land Cover Database 2011 products and North American Forest Dynamics static forest map shows a 6% improvement in unmixing-based classification relative to per-pixel classification. As such, abundance maps continue to offer a useful alternative to high-spatial-resolution classified maps for forest inventory analysis, multi
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VT National Land Cover Dataset - 2001
Vermont Center for Geographic Information — (Link to Metadata) The NLCD2001 layer available from VCGI is a subset of the the National Land Cover Database 2001 land cover layer for mapping zone 65 was produced...
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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...
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Borella, H. M.; Estes, J. E.; Ezra, C. E.; Scepan, J.; Tinney, L. R.
1982-01-01
For two test sites in Pennsylvania the interpretability of commercially acquired low-altitude and existing high-altitude aerial photography are documented in terms of time, costs, and accuracy for Anderson Level II land use/land cover mapping. Information extracted from the imagery is to be used in the evaluation process for siting energy facilities. Land use/land cover maps were drawn at 1:24,000 scale using commercially flown color infrared photography obtained from the United States Geological Surveys' EROS Data Center. Detailed accuracy assessment of the maps generated by manual image analysis was accomplished employing a stratified unaligned adequate class representation. Both 'area-weighted' and 'by-class' accuracies were documented and field-verified. A discrepancy map was also drawn to illustrate differences in classifications between the two map scales. Results show that the 1:24,000 scale map set was more accurate (99% to 94% area-weighted) than the 1:62,500 scale set, especially when sampled by class (96% to 66%). The 1:24,000 scale maps were also more time-consuming and costly to produce, due mainly to higher image acquisition costs.
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Directory of Open Access Journals (Sweden)
Karen Ikin
Full Text Available Improving biodiversity conservation in fragmented agricultural landscapes has become an important global issue. Vegetation at the patch and landscape-scale is important for species occupancy and diversity, yet few previous studies have explored multi-scale associations between vegetation and community assemblages. Here, we investigated how patch and landscape-scale vegetation cover structure woodland bird communities. We asked: (1 How is the bird community associated with the vegetation structure of woodland patches and the amount of vegetation cover in the surrounding landscape? (2 Do species of conservation concern respond to woodland vegetation structure and surrounding vegetation cover differently to other species in the community? And (3 Can the relationships between the bird community and the woodland vegetation structure and surrounding vegetation cover be explained by the ecological traits of the species comprising the bird community? We studied 103 woodland patches (0.5 - 53.8 ha over two time periods across a large (6,800 km(2 agricultural region in southeastern Australia. We found that both patch vegetation and surrounding woody vegetation cover were important for structuring the bird community, and that these relationships were consistent over time. In particular, the occurrence of mistletoe within the patches and high values of woody vegetation cover within 1,000 ha and 10,000 ha were important, especially for bird species of conservation concern. We found that the majority of these species displayed similar, positive responses to patch and landscape vegetation attributes. We also found that these relationships were related to the foraging and nesting traits of the bird community. Our findings suggest that management strategies to increase both remnant vegetation quality and the cover of surrounding woody vegetation in fragmented agricultural landscapes may lead to improved conservation of bird communities.
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Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W
2017-01-01
Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.
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Classification of Land Cover and Land Use Based on Convolutional Neural Networks
Yang, Chun; Rottensteiner, Franz; Heipke, Christian
2018-04-01
Land cover describes the physical material of the earth's surface, whereas land use describes the socio-economic function of a piece of land. Land use information is typically collected in geospatial databases. As such databases become outdated quickly, an automatic update process is required. This paper presents a new approach to determine land cover and to classify land use objects based on convolutional neural networks (CNN). The input data are aerial images and derived data such as digital surface models. Firstly, we apply a CNN to determine the land cover for each pixel of the input image. We compare different CNN structures, all of them based on an encoder-decoder structure for obtaining dense class predictions. Secondly, we propose a new CNN-based methodology for the prediction of the land use label of objects from a geospatial database. In this context, we present a strategy for generating image patches of identical size from the input data, which are classified by a CNN. Again, we compare different CNN architectures. Our experiments show that an overall accuracy of up to 85.7 % and 77.4 % can be achieved for land cover and land use, respectively. The classification of land cover has a positive contribution to the classification of the land use classification.
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From land cover change to land function dynamics: A major challenge to improve land characterization
Verburg, P.H.; Steeg, van de J.; Veldkamp, A.; Willemen, L.
2009-01-01
Land cover change has always had a central role in land change science. This central role is largely the result of the possibilities to map and characterize land cover based on observations and remote sensing. This paper argues that more attention should be given to land use and land functions and
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CSIR Research Space (South Africa)
Salmon, BP
2015-07-01
Full Text Available In this paper the authors present a 2-tier higher order Conditional Random Field which is used for land cover classification. The Conditional Random Field is based on probabilistic messages being passed along a graph to compute efficiently...
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Introducing land-cover and land-use changes in a climate scenario of the 21. century
International Nuclear Information System (INIS)
Voldoire, A.
2005-03-01
The main objective of this work has been to run a climate simulation of the 21. century that includes not only greenhouse gases and aerosols emitted by human activity but also land-use and land-cover changes. To achieve this goal, the integrated impact model IMAGE2.2 (developed at RIVM, The Netherlands) was used, which simulates the evolution of greenhouse gases concentrations as well as land-cover changes. This model has been coupled to the general circulation model ARPEGE/OPA provided by the CNRM. Before coupling the models, sensitivity experiments with each model have been performed to test their respective sensitivity to the forcing of the other. Ultimately, a simulation with the two models coupled together has shown that interactions between climate and vegetation are not of primary importance for century scale studies. (author)
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LandSat-Based Land Use-Land Cover (Vector)
Minnesota Department of Natural Resources — Vector-based land cover data set derived from classified 30 meter resolution Thematic Mapper satellite imagery. Classification is divided into 16 classes with source...
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LandSat-Based Land Use-Land Cover (Raster)
Minnesota Department of Natural Resources — Raster-based land cover data set derived from 30 meter resolution Thematic Mapper satellite imagery. Classification is divided into 16 classes with source imagery...
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Land Cover Monitoring for Water Resources Management in Angola
Miguel, Irina; Navarro, Ana; Rolim, Joao; Catalao, Joao; Silva, Joel; Painho, Marco; Vekerdy, Zoltan
2016-08-01
The aim of this paper is to assess the impact of improved temporal resolution and multi-source satellite data (SAR and optical) on land cover mapping and monitoring for efficient water resources management. For that purpose, we developed an integrated approach based on image classification and on NDVI and SAR backscattering (VV and VH) time series for land cover mapping and crop's irrigation requirements computation. We analysed 28 SPOT-5 Take-5 images with high temporal revisiting time (5 days), 9 Sentinel-1 dual polarization GRD images and in-situ data acquired during the crop growing season. Results show that the combination of images from different sources provides the best information to map agricultural areas. The increase of the images temporal resolution allows the improvement of the estimation of the crop parameters, and then, to calculate of the crop's irrigation requirements. However, this aspect was not fully exploited due to the lack of EO data for the complete growing season.
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Exploring dust emission responses to land cover change using an ecological land classification
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.
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Foley, J. A.
2003-12-01
Over the last two hundred years, much of the Mississippi basin has been converted from forest, savanna and grassland to mosaic of agricultural and urban areas. Furthermore, technological changes -- especially those dealing with agricultural practices like fertilizer use -- have also had a widespread affect on environmental systems in the basin. Taken together, the massive transformation of land cover and agricultural land use practices have had a tremendous effect on the hydrological, biogeochemical and ecological processes occurring within the region. This transformation of the basin has a significant impact on human welfare and that other of other species, primarily through changing the distribution of ecosystem "goods and services" produced there. Here we present results that examine how large-scale changes in land use and land cover of the basin may have affected: (i) large-scale water balance and hydrology; (ii) water quality, especially nitrate concentrations; (iii) ecosystem productivity and carbon storage; and (iv) agricultural yield. In this study, we use a combination of process-based ecosystem models (for both natural ecosystems and agricultural systems), large-scale hydrological routing models, and detailed historical land use and climatic datasets. By comparing the response of different environmental processes to combinations of land use and climatic drivers, we may examine the underlying "resilience" of these ecosystems -- and how they may respond to environmental changes. Furthermore, we examine the tradeoffs between ecosystem goods and services -- such as a potential balance between increasing crop yields and decreasing water quality -- on a regional scale. Such regional-scale integrative studies are only now in their infancy. But they represent a framework for exploring the complex interactions between human societies, local landscapes, and regional environmental processes. Such "place-based" integrative studies should be compared to other regions
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Rapid Land Cover Map Updates Using Change Detection and Robust Random Forest Classifiers
Directory of Open Access Journals (Sweden)
Konrad J. Wessels
2016-10-01
Full Text Available The paper evaluated the Landsat Automated Land Cover Update Mapping (LALCUM system designed to rapidly update a land cover map to a desired nominal year using a pre-existing reference land cover map. The system uses the Iteratively Reweighted Multivariate Alteration Detection (IRMAD to identify areas of change and no change. The system then automatically generates large amounts of training samples (n > 1 million in the no-change areas as input to an optimized Random Forest classifier. Experiments were conducted in the KwaZulu-Natal Province of South Africa using a reference land cover map from 2008, a change mask between 2008 and 2011 and Landsat ETM+ data for 2011. The entire system took 9.5 h to process. We expected that the use of the change mask would improve classification accuracy by reducing the number of mislabeled training data caused by land cover change between 2008 and 2011. However, this was not the case due to exceptional robustness of Random Forest classifier to mislabeled training samples. The system achieved an overall accuracy of 65%–67% using 22 detailed classes and 72%–74% using 12 aggregated national classes. “Water”, “Plantations”, “Plantations—clearfelled”, “Orchards—trees”, “Sugarcane”, “Built-up/dense settlement”, “Cultivation—Irrigated” and “Forest (indigenous” had user’s accuracies above 70%. Other detailed classes (e.g., “Low density settlements”, “Mines and Quarries”, and “Cultivation, subsistence, drylands” which are required for operational, provincial-scale land use planning and are usually mapped using manual image interpretation, could not be mapped using Landsat spectral data alone. However, the system was able to map the 12 national classes, at a sufficiently high level of accuracy for national scale land cover monitoring. This update approach and the highly automated, scalable LALCUM system can improve the efficiency and update rate of regional land
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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
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Directory of Open Access Journals (Sweden)
C. Zhao
2015-11-01
Full Text Available Fenwei basin, China, composed by several sub-basins, has been suffering severe geo-hazards in last 60 years, including large scale land subsidence and small scale ground fissure, which caused serious infrastructure damages and property losses. In this paper, we apply different InSAR techniques with different SAR data to monitor these hazards. Firstly, combined small baseline subset (SBAS InSAR method and persistent scatterers (PS InSAR method is used to multi-track Envisat ASAR data to retrieve the large scale land subsidence covering entire Fenwei basin, from which different land subsidence magnitudes are analyzed of different sub-basins. Secondly, PS-InSAR method is used to monitor the small scale ground fissure deformation in Yuncheng basin, where different spatial deformation gradient can be clearly discovered. Lastly, different track SAR data are contributed to retrieve two-dimensional deformation in both land subsidence and ground fissure region, Xi'an, China, which can be benefitial to explain the occurrence of ground fissure and the correlation between land subsidence and ground fissure.
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International Nuclear Information System (INIS)
Borella, H.M.; Estes, J.E.; Ezra, C.E.; Scepan, J.; Tinney, L.R.
1982-01-01
For two test sites in Pennsylvania the interpretability of commercially acquired low-altitude and existing high-altitude aerial photography are documented in terms of time, costs, and accuracy for Anderson Level II land use/land cover mapping. Information extracted from the imagery is to be used in the evaluation process for siting energy facilities. Land use/land cover maps were drawn at 1:24,000 scale using commercially flown color infrared photography obtained from the United States Geological Surveys' EROS Data Center. Detailed accuracy assessment of the maps generated by manual image analysis was accomplished employing a stratified unaligned adequate class representation. Both are-weighted and by-class accuracies were documented and field-verified. A discrepancy map was also drawn to illustrate differences in classifications between the two map scales. Results show that the 1:24,000 scale map set was accurate (99% to 94% area-weighted) than the 1:62,500 scale set, especially when sampled by class (96% to 66%). The 1:24,000 scale maps were also more time-consuming and costly to produce, due mainly to higher image acquisition costs
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Directory of Open Access Journals (Sweden)
Bikash Basnet
2015-05-01
Full Text Available Tracking land surface dynamics over cloud prone areas with complex mountainous terrain is an important challenge facing the Earth Science community. One such region is the Lake Kivu region in Central Africa. We developed a processing chain to systematically monitor the spatio-temporal land use/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 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 period 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. These multi-temporal datasets will be a valuable baseline for land use managers in the region interested in developing ecologically sustainable land management strategies and measuring the impacts of biodiversity conservation efforts.
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Estes, Lyndon; Chen, Peng; Debats, Stephanie; Evans, Tom; Ferreira, Stefanus; Kuemmerle, Tobias; Ragazzo, Gabrielle; Sheffield, Justin; Wolf, Adam; Wood, Eric; Caylor, Kelly
2018-01-01
Land cover maps increasingly underlie research into socioeconomic and environmental patterns and processes, including global change. It is known that map errors impact our understanding of these phenomena, but quantifying these impacts is difficult because many areas lack adequate reference data. We used a highly accurate, high-resolution map of South African cropland to assess (1) the magnitude of error in several current generation land cover maps, and (2) how these errors propagate in downstream studies. We first quantified pixel-wise errors in the cropland classes of four widely used land cover maps at resolutions ranging from 1 to 100 km, and then calculated errors in several representative "downstream" (map-based) analyses, including assessments of vegetative carbon stocks, evapotranspiration, crop production, and household food security. We also evaluated maps' spatial accuracy based on how precisely they could be used to locate specific landscape features. We found that cropland maps can have substantial biases and poor accuracy at all resolutions (e.g., at 1 km resolution, up to ∼45% underestimates of cropland (bias) and nearly 50% mean absolute error (MAE, describing accuracy); at 100 km, up to 15% underestimates and nearly 20% MAE). National-scale maps derived from higher-resolution imagery were most accurate, followed by multi-map fusion products. Constraining mapped values to match survey statistics may be effective at minimizing bias (provided the statistics are accurate). Errors in downstream analyses could be substantially amplified or muted, depending on the values ascribed to cropland-adjacent covers (e.g., with forest as adjacent cover, carbon map error was 200%-500% greater than in input cropland maps, but ∼40% less for sparse cover types). The average locational error was 6 km (600%). These findings provide deeper insight into the causes and potential consequences of land cover map error, and suggest several recommendations for land
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Quantitative reconstruction of past land cover in Denmark - The first results
DEFF Research Database (Denmark)
Nielsen, Anne Birgitte; Odgaard, Bent Vad
reflects a frequency change in the same direction of the mother plant may be unsubstantiated. Here, we present a first attempt at pollen based quantitative reconstruction of land cover around 9 Danish lake sites for the past 2500 years, based on models of pollen dispersal and -deposition (Prentice, 1985...... and local pollen signals at small sites, thus providing reconstructions of local vegetation around the sites. Results reflect rather stable land cover through the last 2500 years at the regional level but strong forest-open land dynamics at the local scale. The approach should be applicable to any...
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Quattrochi, Dale A.; Jedlovec, Gary; Meyer, Paul
2011-01-01
City growth influences the development of the urban heat island (UHI), but the effect that local meteorology has on the UHI is less well known. This paper presents some preliminary findings from a study that uses multitemporal Landsat TM and ASTER data to evaluate land cover/land use change (LULCC) over the NASA Marshall Space Flight Center (MFSC) and its Huntsville, AL metropolitan area. Landsat NLCD data for 1992 and 2001 have been used to evaluate LULCC for MSFC and the surrounding urban area. Land surface temperature (LST) and emissivity derived from NLCD data have also been analyzed to assess changes in these parameters in relation to LULCC. Additionally, LULCC, LST, and emissivity have been identified from ASTER data from 2001 and 2011 to provide a comparison with the 2001 NLCD and as a measure of current conditions within the study area. As anticipated, the multi-temporal NLCD and ASTER data show that significant changes have occurred in land covers, LST, and emissivity within and around MSFC. The patterns and arrangement of these changes, however, is significant because the juxtaposition of urban land covers within and outside of MSFC provides insight on what impacts at a local to regional scale, the inter-linkage of these changes potentially have on meteorology. To further analyze these interactions between LULCC, LST, and emissivity with the lower atmosphere, a network of eleven weather stations has been established across the MSFC property. These weather stations provide data at a 10 minute interval, and these data are uplinked for use by MSFC facilities operations and the National Weather Service. The weather data are also integrated within a larger network of meteorological stations across north Alabama. Given that the MSFC weather stations will operate for an extended period of time, they can be used to evaluate how the building of new structures, and changes in roadways, and green spaces as identified in the MSFC master plan for the future, will
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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
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Directory of Open Access Journals (Sweden)
Zahn Münch
2017-02-01
Full Text Available Land cover change analysis was performed for three catchments in the rural Eastern Cape, South Africa, for two time steps (2000 and 2014, to characterize landscape conversion trajectories for sustained landscape health. Land cover maps were derived: (1 from existing data (2000; and (2 through object-based image analysis (2014 of Landsat 8 imagery. Land cover change analysis was facilitated using land cover labels developed to identify landscape change trajectories. Land cover labels assigned to each intersection of the land cover maps at the two time steps provide a thematic representation of the spatial distribution of change. While land use patterns are characterized by high persistence (77%, the expansion of urban areas and agriculture has occurred predominantly at the expense of grassland. The persistence and intensification of natural or invaded wooded areas were identified as a degradation gradient within the landscape, which amounted to almost 10% of the study area. The challenge remains to determine significant signals in the landscape that are not artefacts of error in the underlying input data or scale of analysis. Systematic change analysis and accurate uncertainty reporting can potentially address these issues to produce authentic output for further modelling.
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Directory of Open Access Journals (Sweden)
Chandra Giri
2014-10-01
Full Text Available 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.
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Directory of Open Access Journals (Sweden)
F. Xu
2017-08-01
Full Text Available The determination of area-averaged evapotranspiration (ET at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models and general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC sites and four groups of large-aperture scintillometers (LASs, were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this
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Xu, Feinan; Wang, Weizhen; Wang, Jiemin; Xu, Ziwei; Qi, Yuan; Wu, Yueru
2017-08-01
The determination of area-averaged evapotranspiration (ET) at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models and general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC) sites and four groups of large-aperture scintillometers (LASs), were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this work will be
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EnviroAtlas - Land Cover for the Conterminous United States
U.S. Environmental Protection Agency — This dataset represents the percentage of land area that is classified as forest land cover, modified forest land cover, and natural land cover using the 2006...
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1 Integrating land cover and terrain characteristics to explain plague ...
African Journals Online (AJOL)
influence of land cover and terrain factors on the abundance and spatial distribution ... factors operating at diverse scales, including climate (Debien et al., 2009; Ben Ari .... A cloud free three-band SPOT 5 image captured on 27 February 2007, ...
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NASA Land Cover and Land Use Change (LCLUC): an interdisciplinary research program.
Justice, Chris; Gutman, Garik; Vadrevu, Krishna Prasad
2015-01-15
Understanding Land Cover/Land Use Change (LCLUC) in diverse regions of the world and at varied spatial scales is one of the important challenges in global change research. In this article, we provide a brief overview of the NASA LCLUC program, its focus areas, and the importance of satellite remote sensing observations in LCLUC research including future directions. The LCLUC Program was designed to be a cross-cutting theme within NASA's Earth Science program. The program aims to develop and use remote sensing technologies to improve understanding of human interactions with the environment. Since 1997, the NASA LCLUC program has supported nearly 280 research projects on diverse topics such as forest loss and carbon, urban expansion, land abandonment, wetland loss, agricultural land use change and land use change in mountain systems. The NASA LCLUC program emphasizes studies where land-use changes are rapid or where there are significant regional or global LCLUC implications. Over a period of years, the LCLUC program has contributed to large regional science programs such as Land Biosphere-Atmosphere (LBA), the Northern Eurasia Earth Science Partnership Initiative (NEESPI), and the Monsoon Area Integrated Regional Study (MAIRS). The primary emphasis of the program will remain on using remote sensing datasets for LCLUC research. The program will continue to emphasize integration of physical and social sciences to address regional to global scale issues of LCLUC for the benefit of society. Copyright © 2014. Published by Elsevier Ltd.
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Bourrel, Luc; Brodu, Nicolas; Frappart, Frédéric
2016-04-01
Remotely sensed images allow a frequent monitoring of land cover variations at regional and global scale. Recently launched Sentinel-1 satellite offers a global cover of land areas at an unprecedented spatial (20 m) and temporal (6 days at the Equator). We propose here to compare the performances of commonly used supervised classification techniques (i.e., k-nearest neighbors, linear and Gaussian support vector machines, naive Bayes, linear and quadratic discriminant analyzes, adaptative boosting, loggit regression, ridge regression with one-vs-one voting, random forest, extremely randomized trees) for land cover applications in the Guayas Basin, the largest river basin of the Pacific coast of Ecuator (area ~32,000 km²). The reason of this choice is the importance of this region in Ecuatorian economy as its watershed represents 13% of the total area of Ecuador where 40% of the Ecuadorian population lives. It also corresponds to the most productive region of Ecuador for agriculture and aquaculture. Fifty percents of the country shrimp farming production comes from this watershed, and represents with agriculture the largest source of revenue of the country. Similar comparisons are also performed using ENVISAT ASAR images acquired in global mode (1 km of spatial resolution). Accuracy of the results will be achieved using land cover map derived from multi-spectral images.
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Validation of Land Cover Products Using Reliability Evaluation Methods
Directory of Open Access Journals (Sweden)
Wenzhong Shi
2015-06-01
Full Text Available Validation of land cover products is a fundamental task prior to data applications. Current validation schemes and methods are, however, suited only for assessing classification accuracy and disregard the reliability of land cover products. The reliability evaluation of land cover products should be undertaken to provide reliable land cover information. In addition, the lack of high-quality reference data often constrains validation and affects the reliability results of land cover products. This study proposes a validation schema to evaluate the reliability of land cover products, including two methods, namely, result reliability evaluation and process reliability evaluation. Result reliability evaluation computes the reliability of land cover products using seven reliability indicators. Process reliability evaluation analyzes the reliability propagation in the data production process to obtain the reliability of land cover products. Fuzzy fault tree analysis is introduced and improved in the reliability analysis of a data production process. Research results show that the proposed reliability evaluation scheme is reasonable and can be applied to validate land cover products. Through the analysis of the seven indicators of result reliability evaluation, more information on land cover can be obtained for strategic decision-making and planning, compared with traditional accuracy assessment methods. Process reliability evaluation without the need for reference data can facilitate the validation and reflect the change trends of reliabilities to some extent.
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EnviroAtlas - Milwaukee, WI - Meter-Scale Urban Land Cover Data (MULC) Data (2010)
U.S. Environmental Protection Agency — The EnviroAtlas Milwaukee, WI Meter Urban Land Cover (MULC) data and map were generated from USDA NAIP (National Agricultural Imagery Program) four band (red, green,...
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Yilmaz, Rüya
2010-06-01
The objective of the present study was to assess changes in land use/land cover patterns in the coastal town of Silivri, a part of greater Istanbul administratively. In the assessment, remotely sensed data, in the form of satellite images, and geographic information systems were used. Types of land use/land cover were designated as the percentage of the total area studied. Results calculated from the satellite data for land cover classification were compared successfully with the database Coordination of Information on the Environment (CORINE). This served as a reference to appraise the reliability of the study presented here. The CORINE Program was established by the European Commission to create a harmonized Geographical Information System on the state of the environment in the European Community. Unplanned urbanization is causing land use changes mainly in developing countries such as Turkey. This situation in Turkey is frequently observed in the city of Istanbul. There are only a few studies of land use-land cover changes which provide an integrated assessment of the biophysical and societal causes and consequences of environmental degradation in Istanbul. The research area comprised greater Silivri Town which is situated by the coast of Marmara Sea, and it is located approximately 60 km west of Istanbul. The city of Istanbul is one of the largest metropolises in Europe with ca. 15 million inhabitants. Additionally, greater Silivri is located near the terminal point of the state highway connecting Istanbul with Europe. Measuring of changes occurring in land use would help control future planning of settlements; hence, it is of importance for the Greater Silivri and Silivri Town. Following our evaluations, coastal zone of Silivri was classified into the land use groups of artificial surfaces agricultural areas and forests and seminatural areas with 47.1%, 12.66%, and 22.62%, respectively.
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A Comparison of Advanced Regression Algorithms for Quantifying Urban Land Cover
Directory of Open Access Journals (Sweden)
Akpona Okujeni
2014-07-01
Full Text Available Quantitative methods for mapping sub-pixel land cover fractions are gaining increasing attention, particularly with regard to upcoming hyperspectral satellite missions. We evaluated five advanced regression algorithms combined with synthetically mixed training data for quantifying urban land cover from HyMap data at 3.6 and 9 m spatial resolution. Methods included support vector regression (SVR, kernel ridge regression (KRR, artificial neural networks (NN, random forest regression (RFR and partial least squares regression (PLSR. Our experiments demonstrate that both kernel methods SVR and KRR yield high accuracies for mapping complex urban surface types, i.e., rooftops, pavements, grass- and tree-covered areas. SVR and KRR models proved to be stable with regard to the spatial and spectral differences between both images and effectively utilized the higher complexity of the synthetic training mixtures for improving estimates for coarser resolution data. Observed deficiencies mainly relate to known problems arising from spectral similarities or shadowing. The remaining regressors either revealed erratic (NN or limited (RFR and PLSR performances when comprehensively mapping urban land cover. Our findings suggest that the combination of kernel-based regression methods, such as SVR and KRR, with synthetically mixed training data is well suited for quantifying urban land cover from imaging spectrometer data at multiple scales.
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A Synthesis of Studies on Land Use and Land Cover Dynamics during 1930–2015 in Bangladesh
Directory of Open Access Journals (Sweden)
Raju Rai
2017-10-01
Full Text Available Land use and land cover (LULC is dynamic and changes in it have important environmental and socio-economic consequences. The pathways and pace of change vary with space and time and are related to the interaction between human activities and biophysical conditions in an area. This study provides a systematic review of the changing status, patterns, and compositions of LULC in Bangladesh on national, regional, and local scales over the past 85 years. The primary LULC classes in Bangladesh are agricultural land, urban and built-up area, forest and vegetation, water bodies, and wetlands. Most of the country is covered with agricultural land, followed by urban areas; the latter has been expanding rapidly in the area surrounding the capital city, Dhaka, especially the southern capital area. Forest cover is mostly concentrated in southeast Bangladesh, the Chittagong district, and the mangrove forests are predominantly located in the southwest, with the Gangetic delta. High population growth, rapid urbanization, and infrastructure development have been directly associated with changing patterns of land use across the country. In recent decades, urban areas and water bodies have been increasing, to the detriment of both forests and agricultural land. Most of the studies reviewed here describe a general trend involving agricultural and forested land being transformed into urban areas.
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Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders
Rußwurm, Marc; Körner, Marco
2018-03-01
Earth observation (EO) sensors deliver data with daily or weekly temporal resolution. Most land use and land cover (LULC) approaches, however, expect cloud-free and mono-temporal observations. The increasing temporal capabilities of today's sensors enables the use of temporal, along with spectral and spatial features. Domains, such as speech recognition or neural machine translation, work with inherently temporal data and, today, achieve impressive results using sequential encoder-decoder structures. Inspired by these sequence-to-sequence models, we adapt an encoder structure with convolutional recurrent layers in order to approximate a phenological model for vegetation classes based on a temporal sequence of Sentinel 2 (S2) images. In our experiments, we visualize internal activations over a sequence of cloudy and non-cloudy images and find several recurrent cells, which reduce the input activity for cloudy observations. Hence, we assume that our network has learned cloud-filtering schemes solely from input data, which could alleviate the need for tedious cloud-filtering as a preprocessing step for many EO approaches. Moreover, using unfiltered temporal series of top-of-atmosphere (TOA) reflectance data, we achieved in our experiments state-of-the-art classification accuracies on a large number of crop classes with minimal preprocessing compared to other classification approaches.
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The Effect of Land use/cover change on Biomass Stock in Dryland ...
African Journals Online (AJOL)
The Effect of Land use/cover change on Biomass Stock in Dryland Areas of Eastern Uganda. ... Journal of Applied Sciences and Environmental Management ... Therefore, there is need for increased use of remote sensing and GIS to quantify change patterns at local scales for essential monitoring and assessment of land ...
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Cheng, Tao; Zhang, Jialong; Zheng, Xinyan; Yuan, Rujin
2018-03-01
The project of The First National Geographic Conditions Census developed by Chinese government has designed the data acquisition content and indexes, and has built corresponding classification system mainly based on the natural property of material. However, the unified standard for land cover classification system has not been formed; the production always needs converting to meet the actual needs. Therefore, it proposed a refined classification method based on multi source of remote sensing information fusion. It takes the third-level classes of forest land and grassland for example, and has collected the thematic data of Vegetation Map of China (1:1,000,000), attempts to develop refined classification utilizing raster spatial analysis model. Study area is selected, and refined classification is achieved by using the proposed method. The results show that land cover within study area is divided principally among 20 classes, from subtropical broad-leaved forest (31131) to grass-forb community type of low coverage grassland (41192); what's more, after 30 years in the study area, climatic factors, developmental rhythm characteristics and vegetation ecological geographical characteristics have not changed fundamentally, only part of the original vegetation types have changed in spatial distribution range or land cover types. Research shows that refined classification for the third-level classes of forest land and grassland could make the results take on both the natural attributes of the original and plant community ecology characteristics, which could meet the needs of some industry application, and has certain practical significance for promoting the product of The First National Geographic Conditions Census.
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Directory of Open Access Journals (Sweden)
Joseph St. Peter
2018-03-01
Full Text Available Land cover classification provides valuable information for prioritizing management and conservation operations across large landscapes. Current regional scale land cover geospatial products within the United States have a spatial resolution that is too coarse to provide the necessary information for operations at the local and project scales. This paper describes a methodology that uses recent advances in spatial analysis software to create a land cover classification over a large region in the southeastern United States at a fine (1 m spatial resolution. This methodology used image texture metrics and principle components derived from National Agriculture Imagery Program (NAIP aerial photographic imagery, visually classified locations, and a softmax neural network model. The model efficiently produced classification surfaces at 1 m resolution across roughly 11.6 million hectares (28.8 million acres with less than 10% average error in modeled probability. The classification surfaces consist of probability estimates of 13 visually distinct classes for each 1 m cell across the study area. This methodology and the tools used in this study constitute a highly flexible fine resolution land cover classification that can be applied across large extents using standard computer hardware, common and open source software and publicly available imagery.
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Assessing land use and cover change effects on hydrological response in the river C
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
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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...
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Land User and Land Cover Maps of Europe: a Webgis Platform
Brovelli, M. A.; Fahl, F. C.; Minghini, M.; Molinari, M. E.
2016-06-01
This paper presents the methods and implementation processes of a WebGIS platform designed to publish the available land use and land cover maps of Europe at continental scale. The system is built completely on open source infrastructure and open standards. The proposed architecture is based on a server-client model having GeoServer as the map server, Leaflet as the client-side mapping library and the Bootstrap framework at the core of the front-end user interface. The web user interface is designed to have typical features of a desktop GIS (e.g. activate/deactivate layers and order layers by drag and drop actions) and to show specific information on the activated layers (e.g. legend and simplified metadata). Users have the possibility to change the base map from a given list of map providers (e.g. OpenStreetMap and Microsoft Bing) and to control the opacity of each layer to facilitate the comparison with both other land cover layers and the underlying base map. In addition, users can add to the platform any custom layer available through a Web Map Service (WMS) and activate the visualization of photos from popular photo sharing services. This last functionality is provided in order to have a visual assessment of the available land coverages based on other user-generated contents available on the Internet. It is supposed to be a first step towards a calibration/validation service that will be made available in the future.
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Directory of Open Access Journals (Sweden)
Jed O. Kaplan
2017-12-01
Full Text Available Anthropogenic land cover change (ALCC is the most important transformation of the Earth system that occurred in the preindustrial Holocene, with implications for carbon, water and sediment cycles, biodiversity and the provision of ecosystem services and regional and global climate. For example, anthropogenic deforestation in preindustrial Eurasia may have led to feedbacks to the climate system: both biogeophysical, regionally amplifying winter cold and summer warm temperatures, and biogeochemical, stabilizing atmospheric CO 2 concentrations and thus influencing global climate. Quantification of these effects is difficult, however, because scenarios of anthropogenic land cover change over the Holocene vary widely, with increasing disagreement back in time. Because land cover change had such widespread ramifications for the Earth system, it is essential to assess current ALCC scenarios in light of observations and provide guidance on which models are most realistic. Here, we perform a systematic evaluation of two widely-used ALCC scenarios (KK10 and HYDE3.1 in northern and part of central Europe using an independent, pollen-based reconstruction of Holocene land cover (REVEALS. Considering that ALCC in Europe primarily resulted in deforestation, we compare modeled land use with the cover of non-forest vegetation inferred from the pollen data. Though neither land cover change scenario matches the pollen-based reconstructions precisely, KK10 correlates well with REVEALS at the country scale, while HYDE systematically underestimates land use with increasing magnitude with time in the past. Discrepancies between modeled and reconstructed land use are caused by a number of factors, including assumptions of per-capita land use and socio-cultural factors that cannot be predicted on the basis of the characteristics of the physical environment, including dietary preferences, long-distance trade, the location of urban areas and social organization.
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ISLSCP II Historical Land Cover and Land Use, 1700-1990
National Aeronautics and Space Administration — ABSTRACT: The Historical Land Cover and Land Use data set was developed to provide the global change community with historical land use estimates. The data set...
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TESTING OF LAND COVER CLASSIFICATION FROM MULTISPECTRAL AIRBORNE LASER SCANNING DATA
Directory of Open Access Journals (Sweden)
K. Bakuła
2016-06-01
Full Text Available Multispectral Airborne Laser Scanning provides a new opportunity for airborne data collection. It provides high-density topographic surveying and is also a useful tool for land cover mapping. Use of a minimum of three intensity images from a multiwavelength laser scanner and 3D information included in the digital surface model has the potential for land cover/use classification and a discussion about the application of this type of data in land cover/use mapping has recently begun. In the test study, three laser reflectance intensity images (orthogonalized point cloud acquired in green, near-infrared and short-wave infrared bands, together with a digital surface model, were used in land cover/use classification where six classes were distinguished: water, sand and gravel, concrete and asphalt, low vegetation, trees and buildings. In the tested methods, different approaches for classification were applied: spectral (based only on laser reflectance intensity images, spectral with elevation data as additional input data, and spectro-textural, using morphological granulometry as a method of texture analysis of both types of data: spectral images and the digital surface model. The method of generating the intensity raster was also tested in the experiment. Reference data were created based on visual interpretation of ALS data and traditional optical aerial and satellite images. The results have shown that multispectral ALS data are unlike typical multispectral optical images, and they have a major potential for land cover/use classification. An overall accuracy of classification over 90% was achieved. The fusion of multi-wavelength laser intensity images and elevation data, with the additional use of textural information derived from granulometric analysis of images, helped to improve the accuracy of classification significantly. The method of interpolation for the intensity raster was not very helpful, and using intensity rasters with both first and
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Homer, C.; Colditz, R. R.; Latifovic, R.; Llamas, R. M.; Pouliot, D.; Danielson, P.; Meneses, C.; Victoria, A.; Ressl, R.; Richardson, K.; Vulpescu, M.
2017-12-01
Land cover and land cover change information at regional and continental scales has become fundamental for studying and understanding the terrestrial environment. With recent advances in computer science and freely available image archives, continental land cover mapping has been advancing to higher spatial resolution products. The North American Land Change Monitoring System (NALCMS) remains the principal provider of seamless land cover maps of North America. Founded in 2006, this collaboration among the governments of Canada, Mexico and the United States has released two previous products based on 250m MODIS images, including a 2005 land cover and a 2005-2010 land cover change product. NALCMS has recently completed the next generation North America land cover product, based upon 30m Landsat images. This product now provides the first ever 30m land cover produced for the North American continent, providing 19 classes of seamless land cover. This presentation provides an overview of country-specific image classification processes, describes the continental map production process, provides results for the North American continent and discusses future plans. NALCMS is coordinated by the Commission for Environmental Cooperation (CEC) and all products can be obtained at their website - www.cec.org.
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Towards Seamless Validation of Land Cover Data
Chuprikova, Ekaterina; Liebel, Lukas; Meng, Liqiu
2018-05-01
This article demonstrates the ability of the Bayesian Network analysis for the recognition of uncertainty patterns associated with the fusion of various land cover data sets including GlobeLand30, CORINE (CLC2006, Germany) and land cover data derived from Volunteered Geographic Information (VGI) such as Open Street Map (OSM). The results of recognition are expressed as probability and uncertainty maps which can be regarded as a by-product of the GlobeLand30 data. The uncertainty information may guide the quality improvement of GlobeLand30 by involving the ground truth data, information with superior quality, the know-how of experts and the crowd intelligence. Such an endeavor aims to pave a way towards a seamless validation of global land cover data on the one hand and a targeted knowledge discovery in areas with higher uncertainty values on the other hand.
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Assessing the Impact of Land Use and Land Cover Change on Global Water Resources
Batra, N.; Yang, Y. E.; Choi, H. I.; Islam, A.; Charlotte, D. F.; Cai, X.; Kumar, P.
2007-12-01
Land use and land cover changes (LULCC) significantly modify the hydrological regime of the watersheds, affecting water resources and environment from regional to global scale. This study seeks to advance and integrate water and energy cycle observation, scientific understanding, and human impacts to assess future water availability. To achieve the research objective, we integrate and interpret past and current space based and in situ observations into a global hydrologic model (GHM). GHM is developed with enhanced spatial and temporal resolution, physical complexity, hydrologic theory and processes to quantify the impact of LULCC on physical variables: surface runoff, subsurface flow, groundwater, infiltration, ET, soil moisture, etc. Coupled with the common land model (CLM), a 3-dimensional volume averaged soil-moisture transport (VAST) model is expanded to incorporate the lateral flow and subgrid heterogeneity. The model consists of 11 soil-hydrology layers to predict lateral as well as vertical moisture flux transport based on Richard's equations. The primary surface boundary conditions (SBCs) include surface elevation and its derivatives, land cover category, sand and clay fraction profiles, bedrock depth and fractional vegetation cover. A consistent global GIS-based dataset is constructed for the SBCs of the model from existing observational datasets comprising of various resolutions, map projections and data formats. Global ECMWF data at 6-hour time steps for the period 1971 through 2000 is processed to get the forcing data which includes incoming longwave and shortwave radiation, precipitation, air temperature, pressure, wind components, boundary layer height and specific humidity. Land use land cover data, generated using IPCC scenarios for every 10 years from 2000 to 2100 is used for future assessment on water resources. Alterations due to LULCC on surface water balance components: ET, groundwater recharge and runoff are then addressed in the study. Land
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Review of Land Use and Land Cover Change research progress
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.
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Statistical Monitoring of Changes to Land Cover
Zerrouki, Nabil; Harrou, Fouzi; Sun, Ying
2018-01-01
Accurate detection of changes in land cover leads to better understanding of the dynamics of landscapes. This letter reports the development of a reliable approach to detecting changes in land cover based on remote sensing and radiometric data
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Usability Study to Assess the IGBP Land Cover Classification for Singapore
Directory of Open Access Journals (Sweden)
Nanki Sidhu
2017-10-01
Full Text Available Our research focuses on assessing the usability of the International Geosphere Biosphere Programme (IGBP classification scheme provided in the MODIS MCD12Q1-1 dataset for assessing the land cover of the city-state, Singapore. We conducted a user study with responses from 33 users by providing them with Google Earth images from different parts of Singapore, asking survey-takers to classify these images according to their understanding by the IGBP definitions provided. We also conducted interviews with experts from major governmental agencies working with satellite imagery, which highlighted the need for a detailed land classification for Singapore. In addition to the qualitative analysis of the IGBP land classification scheme, we carried out a validation of the MCD12Q1-1 remote sensing product against SPOT-5 imagery for our study area. The user study revealed that survey-takers were able to correctly classify urban areas, as well as densely forested areas. Misclassifications between Cropland and Mixed Forest classes were highest and were attributed by users to the broad terminology of the IGBP of the two land cover class definitions. For the accuracy assessment, we obtained validation points using weighted and unweighted stratified sampling. The overall classification accuracy for all 17 IGBP land classes is 62%. Upon selecting only the four most occurring IGBP land classes in Singapore, the classification accuracy improved to 71%. Validation of the MCD12Q1-1 against ground truth for Singapore revealed less-common land classes that may be of importance in a global context but are sources of error when the same product is applied at a smaller scale. Combining the user study with the accuracy assessment gives a comprehensive overview of the challenges associated with using global-level land cover data to derive localized land cover information specifically for smaller land masses like Singapore.
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Spatiotemporal analysis of land use and land cover change in the Brazilian Amazon.
Lu, Dengsheng; 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.
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Priem, Frederik; Okujeni, Akpona; van der Linden, Sebastian; Canters, Frank
2016-10-01
The value of characteristic reflectance features for mapping urban materials has been demonstrated in many experiments with airborne imaging spectrometry. Analysis of larger areas requires satellite-based multispectral imagery, which typically lacks the spatial and spectral detail of airborne data. Consequently the need arises to develop mapping methods that exploit the complementary strengths of both data sources. In this paper a workflow for sub-pixel quantification of Vegetation-Impervious-Soil urban land cover is presented, using medium resolution multispectral satellite imagery, hyperspectral endmember libraries and Support Vector Regression. A Landsat 8 Operational Land Imager surface reflectance image covering the greater metropolitan area of Brussels is selected for mapping. Two spectral libraries developed for the cities of Brussels and Berlin based on airborne hyperspectral APEX and HyMap data are used. First the combined endmember library is resampled to match the spectral response of the Landsat sensor. The library is then optimized to avoid spectral redundancy and confusion. Subsequently the spectra of the endmember library are synthetically mixed to produce training data for unmixing. Mapping is carried out using Support Vector Regression models trained with spectra selected through stratified sampling of the mixed library. Validation on building block level (mean size = 46.8 Landsat pixels) yields an overall good fit between reference data and estimation with Mean Absolute Errors of 0.06, 0.06 and 0.08 for vegetation, impervious and soil respectively. Findings of this work may contribute to the use of universal spectral libraries for regional scale land cover fraction mapping using regression approaches.
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Assessment of environmental responses to land use/land cover ...
African Journals Online (AJOL)
aghomotsegin
2013-12-17
Dec 17, 2013 ... 49.86% of the land cover has been converted to other land uses, ... management information system and policies that will ensure sustainable management of fragile ...... growth in agricultural output such as food and fiber.
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Goijman, Andrea Paula; Conroy, Michael. J.; Bernardos, Jaime Nicolás; Zaccagnini, María Elena
2015-01-01
Rapid expansion and intensification of agriculture create challenges for the conservation of biodiversity and associated ecosystem services. In Argentina, the total row crop planted area has increased in recent decades with the expansion of soybean cultivation, homogenizing the landscape. In 2003 we started the first long-term, large-scale bird monitoring program in agroecosystems of central Argentina, in portions of the Pampas and Espinal ecoregions. Using data from this program, we evaluated the effect of land use and cover extent on birds between 2003-2012, accounting for imperfect detection probabilities using a Bayesian hierarchical, multi-species and multi-season occupancy model. We tested predictions that species diversity is positively related to habitat heterogeneity, which in intensified agroecosystems is thought to be mediated by food availability; thus the extent of land use and cover is predicted to affect foraging guilds differently. We also infer about ecosystem services provisioning and inform management recommendations for conservation of birds. Overall our results support the predictions. Although many species within each guild responded differently to land use and native forest cover, we identified generalities for most trophic guilds. For example, granivorous gleaners, ground insectivores and omnivores responded negatively to high proportions of soybean, while insectivore gleaners and aerial foragers seemed more tolerant. Habitat heterogeneity would likely benefit most species in an intensified agroecosystem, and can be achieved with a diversity of crops, pastures, and natural areas within the landscape. Although most studied species are insectivores, potentially beneficial for pest control, some guilds such as ground insectivores are poorly represented, suggesting that agricultural intensification reduces ecological functions, which may be recovered through management. Continuation of the bird monitoring program will allow us to continue to
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Directory of Open Access Journals (Sweden)
Andrea Paula Goijman
Full Text Available Rapid expansion and intensification of agriculture create challenges for the conservation of biodiversity and associated ecosystem services. In Argentina, the total row crop planted area has increased in recent decades with the expansion of soybean cultivation, homogenizing the landscape. In 2003 we started the first long-term, large-scale bird monitoring program in agroecosystems of central Argentina, in portions of the Pampas and Espinal ecoregions. Using data from this program, we evaluated the effect of land use and cover extent on birds between 2003-2012, accounting for imperfect detection probabilities using a Bayesian hierarchical, multi-species and multi-season occupancy model. We tested predictions that species diversity is positively related to habitat heterogeneity, which in intensified agroecosystems is thought to be mediated by food availability; thus the extent of land use and cover is predicted to affect foraging guilds differently. We also infer about ecosystem services provisioning and inform management recommendations for conservation of birds. Overall our results support the predictions. Although many species within each guild responded differently to land use and native forest cover, we identified generalities for most trophic guilds. For example, granivorous gleaners, ground insectivores and omnivores responded negatively to high proportions of soybean, while insectivore gleaners and aerial foragers seemed more tolerant. Habitat heterogeneity would likely benefit most species in an intensified agroecosystem, and can be achieved with a diversity of crops, pastures, and natural areas within the landscape. Although most studied species are insectivores, potentially beneficial for pest control, some guilds such as ground insectivores are poorly represented, suggesting that agricultural intensification reduces ecological functions, which may be recovered through management. Continuation of the bird monitoring program will allow
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Li, Wei; MacBean, Natasha; Ciais, Philippe; Defourny, Pierre; Lamarche, Céline; Bontemps, Sophie; Houghton, Richard A.; Peng, Shushi
2018-01-01
Land-use and land-cover change (LULCC) impacts local energy and water balance and contributes on global scale to a net carbon emission to the atmosphere. The newly released annual ESA CCI (climate change initiative) land cover maps provide continuous land cover changes at 300 m resolution from 1992 to 2015, and can be used in land surface models (LSMs) to simulate LULCC effects on carbon stocks and on surface energy budgets. Here we investigate the absolute areas and gross and net changes in different plant functional types (PFTs) derived from ESA CCI products. The results are compared with other datasets. Global areas of forest, cropland and grassland PFTs from ESA are 30.4, 19.3 and 35.7 million km2 in the year 2000. The global forest area is lower than that from LUH2v2h (Hurtt et al., 2011), Hansen et al. (2013) or Houghton and Nassikas (2017) while cropland area is higher than LUH2v2h (Hurtt et al., 2011), in which cropland area is from HYDE 3.2 (Klein Goldewijk et al., 2016). Gross forest loss and gain during 1992-2015 are 1.5 and 0.9 million km2 respectively, resulting in a net forest loss of 0.6 million km2, mainly occurring in South and Central America. The magnitudes of gross changes in forest, cropland and grassland PFTs in the ESA CCI are smaller than those in other datasets. The magnitude of global net cropland gain for the whole period is consistent with HYDE 3.2 (Klein Goldewijk et al., 2016), but most of the increases happened before 2004 in ESA and after 2007 in HYDE 3.2. Brazil, Bolivia and Indonesia are the countries with the largest net forest loss from 1992 to 2015, and the decreased areas are generally consistent with those from Hansen et al. (2013) based on Landsat 30 m resolution images. Despite discrepancies compared to other datasets, and uncertainties in converting into PFTs, the new ESA CCI products provide the first detailed long-term time series of land-cover change and can be implemented in LSMs to characterize recent carbon dynamics
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As environmental programs within and outside the federal government continue to move away from point-based studies to larger and larger spatial (not cartographic) scale, the need for land-cover and other geographic data have become ineluctable. The national land-cover mapping pr...
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Rubber and Land-Cover Land-Use Change in Mainland Southeast Asia
Fox, J. M.; Hurni, K.
2017-12-01
Over the past half century, the five countries of Mainland Southeast Asia (MSEA) - Cambodia, Laos, Myanmar, Thailand, and Vietnam - have witnessed major shifts from predominantly subsistence agrarian economies to increasingly commercialized agriculture. Major drivers of change include policy initiatives that fostered regional economic integration and promoted among other changes rapid expansion of boom-crop plantations. Among the many types of commercial boom crops promoted and grown in MSEA are numerous tree-based products such as rubber, coffee, tree species for pulp and paper (particularly eucalyptus and acacia), cashews, and fruits such as oranges, lychees, and longans. The project proposal hypothesized that most (but not all) tree crops replaced swidden cultivation fields and hence are not necessarily accompanied by deforestation. We used MODIS EVI and SWIR time-series from 2001-2014 to classify changes in tree cover across MSEA; a total of 6849 sample points were used to train the classifier (75%) and verification (25%). The classification consists of 24 classes and 17 classes represent tree crops. Project results suggest that 4.4 m ha of rubber have been planted since 2003; 50% of rubber is planted on former evergreen forest land, 18% on deciduous forest land, and 32% on low vegetation area (former crop lands, bushes, scrub). Tree crops occupy about 8% of the landscape (half of that is rubber). Due to the differences in their political and economic histories these countries display different LCLUCs. In northern Laos, smallholder rubber plantations dominate and shifting cultivation is common in the upland. In southern Laos, large-scale plantations of rubber, coffee, eucalyptus, and sugarcane are widespread. In Thailand, vast areas are covered by annual agriculture; fruit trees and rubber are the prevailing tree crops and are mostly planted by smallholders. In Cambodia, large-scale rubber plantations have expanded in recent years on forest lands; smallholder
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Directory of Open Access Journals (Sweden)
Alfredo Fernández-Landa
2016-07-01
Full Text Available REDD+ implementation requires robust, consistent, accurate and transparent national land cover historical data and monitoring systems. Satellite imagery is the only data source with enough periodicity to provide consistent land cover information in a cost-effective way. The main aim of this paper is the creation of an operational framework for monitoring land cover dynamics based on Landsat imagery and open-source software. The methodology integrates the entire land cover and land cover change mapping processes to produce a consistent series of Land Cover maps. The consistency of the time series is achieved through the application of a single trained machine learning algorithm to radiometrically normalized imagery using iteratively re-weighted multivariate alteration detection (IR-MAD across all dates of the historical period. As a result, seven individual Land Cover maps of Costa Rica were produced from 1985/1986 to 2013/2014. Post-classification land cover change detection was performed to evaluate the land cover dynamics in Costa Rica. The validation of the land cover maps showed an overall accuracy of 87% for the 2013/2014 map, 93% for the 2000/2001 map and 89% for the 1985/1986 map. Land cover changes between forest and non-forest classes were validated for the period between 2001 and 2011, obtaining an overall accuracy of 86%. Forest age-classes were generated through a multi-temporal analysis of the maps. By linking deforestation dynamics with forest age, a more accurate discussion of the carbon emissions along the time series can be presented.
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Directory of Open Access Journals (Sweden)
C. Höpfner
2011-11-01
-annual time scale to NDVI percentiles (50 % of land cover types. Correlation results of mean daily precipitation from 16 September to 15 January and percentage of yearly classified area of each land cover type are medium up to high (max. r2=0.64. In all, an offset of nearly 1.5 months is detected between precipitation rates and NDVI values. High-productive vegetation (cropland is proved to be mainly rain-fed. We conclude that identification, understanding and knowledge about vegetation phenology, and current variability of vegetation and land cover, as well as prediction methods of land cover change, can be improved using multi-year MODIS NDVI time series data. This study enhances the comprehension of current land surface dynamics and variability of vegetation and land cover in north-western Morocco. It especially offers a quick access when estimating the extent of agricultural lands.
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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.
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Mukesh Singh Boori; Vít Voženílek; Komal Choudhary
2015-01-01
The Jeseníky Mountains tourism in Czech Republic is unique for its floristic richness. This is caused mainly by the altitude division and polymorphism of the landscape, climate and soil structure. This study assesses the impacts of tourism on the land cover in the Jeseníky Mountain region by comparing multi-temporal Landsat imageries (1991, 2001 and 2013) to describe the rate and extent of land-cover changes. This was achieved through spectral classification of different land cover classes an...
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Statistical Monitoring of Changes to Land Cover
Zerrouki, Nabil
2018-04-06
Accurate detection of changes in land cover leads to better understanding of the dynamics of landscapes. This letter reports the development of a reliable approach to detecting changes in land cover based on remote sensing and radiometric data. This approach integrates the multivariate exponentially weighted moving average (MEWMA) chart with support vector machines (SVMs) for accurate and reliable detection of changes to land cover. Here, we utilize the MEWMA scheme to identify features corresponding to changed regions. Unfortunately, MEWMA schemes cannot discriminate between real changes and false changes. If a change is detected by the MEWMA algorithm, then we execute the SVM algorithm that is based on features corresponding to detected pixels to identify the type of change. We assess the effectiveness of this approach by using the remote-sensing change detection database and the SZTAKI AirChange benchmark data set. Our results show the capacity of our approach to detect changes to land cover.
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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
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A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data
Stibig, H.-J.; Belward, A.S.; Roy, P.S.; Rosalina-Wasrin, U.; Agrawal, S.; Joshi, P.K.; ,; Beuchle, R.; Fritz, S.; Mubareka, S.; Giri, C.
2007-01-01
-tropical Asia, and it delivers reasonable thematic detail and quantitative estimates of the main land-cover proportions. The map may therefore serve for regional stratification or modelling of vegetation cover, but could also support the implementation of forest policies, watershed management or conservation strategies at regional scales.
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Ecosystem services from converted land: the importance of tree cover in Amazonian pastures
Barrett, Kirsten; Valentim, Judson; Turner, B. L.
2013-01-01
Deforestation is responsible for a substantial fraction of global carbon emissions and changes in surface energy budgets that affect climate. Deforestation losses include wildlife and human habitat, and myriad forest products on which rural and urban societies depend for food, fiber, fuel, fresh water, medicine, and recreation. Ecosystem services gained in the transition from forests to pasture and croplands, however, are often ignored in assessments of the impact of land cover change. The role of converted lands in tropical areas in terms of carbon uptake and storage is largely unknown. Pastures represent the fastest-growing form of converted land use in the tropics, even in some areas of rapid urban expansion. Tree biomass stored in these areas spans a broad range, depending on tree cover. Trees in pasture increase carbon storage, provide shade for cattle, and increase productivity of forage material. As a result, increasing fractional tree cover can provide benefits land managers as well as important ecosystem services such as reducing conversion pressure on forests adjacent to pastures. This study presents an estimation of fractional tree cover in pasture in a dynamic region on the verge of large-scale land use change. An appropriate sampling interval is established for similar studies, one that balances the need for independent samples of sufficient number to characterize a pasture in terms of fractional tree cover. This information represents a useful policy tool for government organizations and NGOs interested in encouraging ecosystem services on converted lands. Using high spatial resolution remotely sensed imagery, fractional tree cover in pasture is quantified for the municipality of Rio Branco, Brazil. A semivariogram and devolving spatial resolution are employed to determine the coarsest sampling interval that may be used, minimizing effects of spatial autocorrelation. The coarsest sampling interval that minimizes spatial dependence was about 22 m. The
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Multi-Temporal Land Cover Classification with Long Short-Term Memory Neural Networks
Rußwurm, M.; Körner, M.
2017-05-01
Land cover classification (LCC) is a central and wide field of research in earth observation and has already put forth a variety of classification techniques. Many approaches are based on classification techniques considering observation at certain points in time. However, some land cover classes, such as crops, change their spectral characteristics due to environmental influences and can thus not be monitored effectively with classical mono-temporal approaches. Nevertheless, these temporal observations should be utilized to benefit the classification process. After extensive research has been conducted on modeling temporal dynamics by spectro-temporal profiles using vegetation indices, we propose a deep learning approach to utilize these temporal characteristics for classification tasks. In this work, we show how long short-term memory (LSTM) neural networks can be employed for crop identification purposes with SENTINEL 2A observations from large study areas and label information provided by local authorities. We compare these temporal neural network models, i.e., LSTM and recurrent neural network (RNN), with a classical non-temporal convolutional neural network (CNN) model and an additional support vector machine (SVM) baseline. With our rather straightforward LSTM variant, we exceeded state-of-the-art classification performance, thus opening promising potential for further research.
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MULTI-TEMPORAL LAND COVER CLASSIFICATION WITH LONG SHORT-TERM MEMORY NEURAL NETWORKS
Directory of Open Access Journals (Sweden)
M. Rußwurm
2017-05-01
Full Text Available Land cover classification (LCC is a central and wide field of research in earth observation and has already put forth a variety of classification techniques. Many approaches are based on classification techniques considering observation at certain points in time. However, some land cover classes, such as crops, change their spectral characteristics due to environmental influences and can thus not be monitored effectively with classical mono-temporal approaches. Nevertheless, these temporal observations should be utilized to benefit the classification process. After extensive research has been conducted on modeling temporal dynamics by spectro-temporal profiles using vegetation indices, we propose a deep learning approach to utilize these temporal characteristics for classification tasks. In this work, we show how long short-term memory (LSTM neural networks can be employed for crop identification purposes with SENTINEL 2A observations from large study areas and label information provided by local authorities. We compare these temporal neural network models, i.e., LSTM and recurrent neural network (RNN, with a classical non-temporal convolutional neural network (CNN model and an additional support vector machine (SVM baseline. With our rather straightforward LSTM variant, we exceeded state-of-the-art classification performance, thus opening promising potential for further research.
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Millennium Ecosystem Assessment: MA Rapid Land Cover Change
National Aeronautics and Space Administration — The Millennium Ecosystem Assessment: MA Rapid Land Cover Change provides data and information on global and regional land cover change in raster format for...
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Land use/Land Cover Changes and Causes of Deforestation in the ...
African Journals Online (AJOL)
The objective of this paper is to provide the non-existent data on land use/land cover changes in the Wilberforce Island for the purposes of determining the causes of deforestation and changes in the vegetation cover for a 13 – year period. Accordingly, 125 questionnaires were administered in five communities to determine ...
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The causes of land-use and land-cover change : moving beyond the myths
Lambin, E.F.; Turner, B.L.; Geist, H.J.; Agbola, S.B.; Angelsen, A.; Bruce, J.W.; Coomes, O.T.; Dirzo, R.; Fischer, G.; Folke, C.; George, P.S.; Homewood, K.; Imbernon, J.; Leemans, R.; Xiubin Li,; Moran, E.F.; Mortimore, M.; Ramakrishnan, P.S.; Richards, J.F.; Skanes, H.; Steffen, W.; Stone, G.D.; Svedin, U.; Veldkamp, A.; Vogel, C.; Jianchu Xu,
2001-01-01
Common understanding of the causes of land-use and land-cover change is dominated by simplifications which, in turn, underlie many environment-development policies. This article tracks some of the major myths on driving forces of land-cover change and proposes alternative pathways of change that are
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Kimball, Heather L; Selmants, Paul C; Moreno, Alvaro; Running, Steve W; Giardina, Christian P
2017-01-01
Gross primary production (GPP) is the Earth's largest carbon flux into the terrestrial biosphere and plays a critical role in regulating atmospheric chemistry and global climate. The Moderate Resolution Imaging Spectrometer (MODIS)-MOD17 data product is a widely used remote sensing-based model that provides global estimates of spatiotemporal trends in GPP. When the MOD17 algorithm is applied to regional scale heterogeneous landscapes, input data from coarse resolution land cover and climate products may increase uncertainty in GPP estimates, especially in high productivity tropical ecosystems. We examined the influence of using locally specific land cover and high-resolution local climate input data on MOD17 estimates of GPP for the State of Hawaii, a heterogeneous and discontinuous tropical landscape. Replacing the global land cover data input product (MOD12Q1) with Hawaii-specific land cover data reduced statewide GPP estimates by ~8%, primarily because the Hawaii-specific land cover map had less vegetated land area compared to the global land cover product. Replacing coarse resolution GMAO climate data with Hawaii-specific high-resolution climate data also reduced statewide GPP estimates by ~8% because of the higher spatial variability of photosynthetically active radiation (PAR) in the Hawaii-specific climate data. The combined use of both Hawaii-specific land cover and high-resolution Hawaii climate data inputs reduced statewide GPP by ~16%, suggesting equal and independent influence on MOD17 GPP estimates. Our sensitivity analyses within a heterogeneous tropical landscape suggest that refined global land cover and climate data sets may contribute to an enhanced MOD17 product at a variety of spatial scales.
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International Nuclear Information System (INIS)
Bagan, Hasi; Yamagata, Yoshiki
2014-01-01
Global urban expansion has created incentives to convert green spaces to urban/built-up area. Therefore, understanding the distribution and dynamics of the land-cover changes in cities is essential for better understanding of the cities’ fundamental characteristics and processes, and of the impact of changing land-cover on potential carbon storage. We present a grid square approach using multi-temporal Landsat data from around 1985–2010 to monitor the spatio-temporal land-cover dynamics of 50 global cities. The maximum-likelihood classification method is applied to Landsat data to define the cities’ urbanized areas at different points in time. Subsequently, 1 km 2 grid squares with unique cell IDs are designed to link among land-cover maps for spatio-temporal land-cover change analysis. Then, we calculate land-cover category proportions for each map in 1 km 2 grid cells. Statistical comparison of the land-cover changes in grid square cells shows that urban area expansion in 50 global cities was strongly negatively correlated with forest, cropland and grassland changes. The generated land-cover proportions in 1 km 2 grid cells and the spatial relationships between the changes of land-cover classes are critical for understanding past patterns and the consequences of urban development so as to inform future urban planning, risk management and conservation strategies. (letters)
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Simulating feedbacks in land use and land cover change models
Verburg, P.H.
2006-01-01
In spite of the many advances in land use and land cover change modelling over the past decade many challenges remain. One of these challenges relates to the explicit treatment of feedback mechanisms in descriptive models of the land use system. This paper argues for model-based analysis to explore
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Evaluating The Land Use And Land Cover Dynamics In Borena ...
African Journals Online (AJOL)
The integration of satellite remote sensing and GIS was an effective approach for analyzing the direction, rate, and spatial pattern of land use change. Three land use and land cover maps were produced by analyzing remotely sensed images of Landsat satellite imageries at three time points (1972,1985,and 2003) .
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Policy makers need to understand how land cover change alters storm water regimes, yet existing methods do not fully utilize newly available datasets to quantify storm water changes at a landscape-scale. Here, we use high-resolution, remotely-sensed land cover, imperviousness, an...
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Relating stream function and land cover in the Middle Pee Dee River Basin, SC
Directory of Open Access Journals (Sweden)
A.D. Jayakaran
2016-03-01
Full Text Available Study region: The study region comprised sixteen stream sites and associated contributing watersheds located in the Middle Pee Dee River Basin (MPDRB of South Carolina, USA. Study focus: The study was conducted between 2008 and 2010 to quantify how indices of streamflow varied with land cover characteristics analyzed at multiple spatial scales and fluvial geomorphic characteristics of sampled streams in the MPDRB. Study objectives were to relate three indices of streamflow that reflect recent temporal flow variability in a stream, with synoptic stream geomorphological measurements, and land cover type at specific spatial domains. New hydrological insights for the region: Modifications to the landscape, hydrologic regime, and alteration to channel morphology, are major threats to the functioning of riparian ecosystem functions but can rarely be linked to a single common stressor. Results from the study showed that in the MPDRB, wetland cover in the riparian corridor was an important factor, correlating significantly with stream flashiness, channel enlargement, and bed substrate character. It was also shown that a combination of stream geomorphological characteristics when combined with landscape variables at specific spatial scales were reasonable predictors of all three indices of streamflow. The study also highlights an innovative statistical methodology to relate land cover data to commonly measured metrics of streamflow and fluvial geomorphology. Keywords: Flashiness, Stream habitat, Flow indices, Land cover analysis, Wetlands, Coastal plain, Bed material, Partial least squares regression, Pee Dee River, South Carolina
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Laura E. Hoyos; Marcelo R. Cabido; Ana M. Cingolani
2018-01-01
Land-cover changes are driven by different combinations of biophysical, economic, and cultural drivers that are acting at different scales. We aimed to (1) analyze trends in land use and land cover changes (conversion, abandonment, forest persistence) in the dry Chaco in central Argentina (1979 to 2010), and (2) examine how physical and socio-economic drivers have influenced those changes. Based on Landsat data, we obtained the proportion of 16 classes of land cover changes for 81 individual ...
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Huang, Ling; McDonald-Buller, Elena; McGaughey, Gary; Kimura, Yosuke; Allen, David T
2015-10-01
the characterization of land cover in global and regional data products were examined in eastern Texas. Misclassification between trees and low-growing vegetation in central Texas resulted in substantial differences in isoprene and monoterpene emission estimates and predicted ground-level ozone concentrations. Results from this study indicate the importance of land cover validation at regional scales.
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Deriving a per-field land use and land cover map in an agricultural mosaic catchment
Seo, B.; Bogner, C.; Poppenborg, P.; Martin, E.; Hoffmeister, M.; Jun, M.; Koellner, T.; Reineking, B.; Shope, C. L.; Tenhunen, J.
2014-09-01
Detailed data on land use and land cover constitute important information for Earth system models, environmental monitoring and ecosystem services research. Global land cover products are evolving rapidly; however, there is still a lack of information particularly for heterogeneous agricultural landscapes. We censused land use and land cover field by field in the agricultural mosaic catchment Haean in South Korea. We recorded the land cover types with additional information on agricultural practice. In this paper we introduce the data, their collection and the post-processing protocol. Furthermore, because it is important to quantitatively evaluate available land use and land cover products, we compared our data with the MODIS Land Cover Type product (MCD12Q1). During the studied period, a large portion of dry fields was converted to perennial crops. Compared to our data, the forested area was underrepresented and the agricultural area overrepresented in MCD12Q1. In addition, linear landscape elements such as waterbodies were missing in the MODIS product due to its coarse spatial resolution. The data presented here can be useful for earth science and ecosystem services research. The data are available at the public repository Pangaea (doi:110.1594/PANGAEA.823677).
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Temporal change detection of land use/land cover using GIS and ...
African Journals Online (AJOL)
Satellite images for the years 1972, 1989, 1999 and 2016 were used for LULC ... built-up areas, pastures and bare land, agricultural land and water bodies. For the accuracy of assessment classifications, matrix error and KAPPA ... Keywords: land use/land cover change; change detection; classification; remote sensing; GIS ...
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LBA Regional Land Cover from AVHRR, 1-Degree, 1987 (Defries and Townshend)
National Aeronautics and Space Administration — This data set consists of a subset of a 1-degree global land cover product (DeFries and Townshend 1994). The subset was created for the study area of the Large Scale...
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Directory of Open Access Journals (Sweden)
Antonio Valera Lozano
2017-01-01
Full Text Available The aim of this study is to understand the land use-cover dynamics from the mid- 1950s to 2012 in the municipality of Valencia, eastern Spain. The study area is a very interesting example of the many land use and land cover changes in the landscape of Mediterranean alluvial plains. The analysis was based on photo interpretation of aerial photographs (1956, 1984, 2006 and 2012 and GIS based methodology. At a detailed scale (1:10,000, results show that there has been a highly dynamic process produced by the extent of land developed as urban area. In 1956 11,112 hectares were occupied by agricultural land and natural areas. During fifty five years, the sealed surface was 2,396 hectares. In 2012 the built-up extent was around 33% of the studied area. In the municipality of Valencia much of the land converted to urban use was once highly productive agricultural land.
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Wang, Yan-ying; Wang, Jin-liang; Wang, Ping; Hu, Wen-yin; Su, Shao-hua
2015-12-01
High accuracy remote sensed image classification technology is a long-term and continuous pursuit goal of remote sensing applications. In order to evaluate single classification algorithm accuracy, take Landsat TM image as data source, Northwest Yunnan as study area, seven types of land cover classification like Maximum Likelihood Classification has been tested, the results show that: (1)the overall classification accuracy of Maximum Likelihood Classification(MLC), Artificial Neural Network Classification(ANN), Minimum Distance Classification(MinDC) is higher, which is 82.81% and 82.26% and 66.41% respectively; the overall classification accuracy of Parallel Hexahedron Classification(Para), Spectral Information Divergence Classification(SID), Spectral Angle Classification(SAM) is low, which is 37.29%, 38.37, 53.73%, respectively. (2) from each category classification accuracy: although the overall accuracy of the Para is the lowest, it is much higher on grasslands, wetlands, forests, airport land, which is 89.59%, 94.14%, and 89.04%, respectively; the SAM, SID are good at forests classification with higher overall classification accuracy, which is 89.8% and 87.98%, respectively. Although the overall classification accuracy of ANN is very high, the classification accuracy of road, rural residential land and airport land is very low, which is 10.59%, 11% and 11.59% respectively. Other classification methods have their advantages and disadvantages. These results show that, under the same conditions, the same images with different classification methods to classify, there will be a classifier to some features has higher classification accuracy, a classifier to other objects has high classification accuracy, and therefore, we may select multi sub-classifier integration to improve the classification accuracy.
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Land Cover Classification Using ALOS Imagery For Penang, Malaysia
International Nuclear Information System (INIS)
Sim, C K; Abdullah, K; MatJafri, M Z; Lim, H S
2014-01-01
This paper presents the potential of integrating optical and radar remote sensing data to improve automatic land cover mapping. The analysis involved standard image processing, and consists of spectral signature extraction and application of a statistical decision rule to identify land cover categories. A maximum likelihood classifier is utilized to determine different land cover categories. Ground reference data from sites throughout the study area are collected for training and validation. The land cover information was extracted from the digital data using PCI Geomatica 10.3.2 software package. The variations in classification accuracy due to a number of radar imaging processing techniques are studied. The relationship between the processing window and the land classification is also investigated. The classification accuracies from the optical and radar feature combinations are studied. Our research finds that fusion of radar and optical significantly improved classification accuracies. This study indicates that the land cover/use can be mapped accurately by using this approach
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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,...
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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.
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Schoolmaster, Donald; Stagg, Camille L.; Sharp, Leigh Anne; McGinnis, Tommy S.; Wood, Bernard; Piazza, Sarai
2018-01-01
The loss of coastal marshes is a topic of great concern, because these habitats provide tangible ecosystem services and are at risk from sea-level rise and human activities. In recent years, significant effort has gone into understanding and modeling the relationships between the biological and physical factors that contribute to marsh stability. Simulation-based process models suggest that marsh stability is the product of a complex feedback between sediment supply, flooding regime and vegetation response, resulting in elevation gains sufficient to match the combination of relative sea-level rise and losses from erosion. However, there have been few direct, empirical tests of these models, because long-term datasets that have captured sufficient numbers of marsh loss events in the context of a rigorous monitoring program are rare. We use a multi-year data set collected by the Coastwide Reference Monitoring System (CRMS) that includes transitions of monitored vegetation plots to open water to build and test a predictive model of near-term marsh vulnerability. We found that despite the conclusions of previous process models, elevation change had no ability to predict the transition of vegetated marsh to open water. However, we found that the processes that drive elevation change were significant predictors of transitions. Specifically, vegetation cover in prior year, land area in the surrounding 1 km2 (an estimate of marsh fragmentation), and the interaction of tidal amplitude and position in tidal frame were all significant factors predicting marsh loss. This suggests that 1) elevation change is likely better a predictor of marsh loss at time scales longer than we consider in this study and 2) the significant predictive factors affect marsh vulnerability through pathways other than elevation change, such as resistance to erosion. In addition, we found that, while sensitivity of marsh vulnerability to the predictive factors varied spatially across coastal Louisiana
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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...
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Young, Steven
2017-05-02
When nature and humanity change Earth’s landscapes - through flood or fire, public policy, natural resources management, or economic development - the results are often dramatic and lasting.Wildfires can reshape ecosystems. Hurricanes with names like Sandy or Katrina will howl for days while altering the landscape for years. One growing season in the evolution of drought-resistant genetics can transform semiarid landscapes into farm fields.In the past, valuable land cover maps created for understanding the effects of those events - whether changes in wildlife habitat, water-quality impacts, or the role land use and land cover play in affecting weather and climate - came out at best every 5 to 7 years. Those high quality, high resolution maps were good, but users always craved more: even higher quality data, additional land cover and land change variables, more detailed legends, and most importantly, more frequent land change information.Now a bold new initiative called Land Change Monitoring, Assessment, and Projection (LCMAP) promises to fulfill that demand.Developed at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota, LCMAP provides definitive, timely information on how, why, and where the planet is changing. LCMAP’s continuous monitoring process can detect changes as they happen every day that Landsat satellites acquire clear observations. The result will be to place near real-time information in the hands of land and resource managers who need to understand the effects these changes have on landscapes.
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Bai, Yixin; Zhou, Rui; Cao, Jianyun; Wei, Daqing; Du, Qing; Li, Baoqiang; Wang, Yaming; Jia, Dechang; Zhou, Yu
2017-07-01
The sub-microporous microarc oxidation (MAO) coating covered Ti implant with micro-scale gouges has been fabricated via a multi-step MAO process to overcome the compromised bone-implant integration. The as-prepared implant has been further mediated by post-heat treatment to compare the effects of -OH functional group and the nano-scale orange peel-like morphology on osseointegration. The bone regeneration, bone-implant contact interface, and biomechanical push-out force of the modified Ti implant have been discussed thoroughly in this work. The greatly improved push-out force for the MAO coated Ti implants with micro-scale gouges could be attributed to the excellent mechanical interlocking effect between implants and biologically meshed bone tissues. Attributed to the -OH functional group which promotes synostosis between the biologically meshed bone and the gouge surface of implant, the multi-step MAO process could be an effective strategy to improve the osseointegration of Ti implant. Copyright © 2017 Elsevier B.V. All rights reserved.
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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.
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Agro-pastoral expansion and land use/land cover (LU/LC) change dynamics in Central-western Brazil
Sanga-Ngoie, K.; Yoshikawa, S.; Kanae, S.
2011-12-01
In Brazil, large-scale land cover changes following extensive deforestations are expected to generate big impacts onto the climate and the environment over this area, with eventually many negative feedbacks on the global scale. Mato Grosso State, located in the central western Brazil, is known to be the Brazilian state with the highest deforestation rate. Land use/land cover (LU/LC) changes have been reported to occur over large areas in this state due to the introduction of large-scale mechanized agriculture, extensive cattle ranching and uncontrolled slash-and-burn cultivation since the 1980s. In this study, we specifically aim at doing more detailed analysis for the causes of deforestation and savannization in this area, with special attention to agriculture and cattle ranching industry at the municipal district level in this state. Using GIS techniques and remotely-sensed NOAA/AVHRR data, we created 5-year Digital Vegetation Model Maps characterizing LU/LC features for every five years during the 1981-2001 periods using the PCA first components of the NOAA/AVHRR multi-spectral data. Our results make it clear that: (1) LU/LC changes among the phases are of the following 3 major types: degradation, recovery or transition; (2) The changes in LU/LC features are concomitant with the advance of cattle ranching and corn production activities toward the northern parts of the state, and with the expansion of soybean production in the central and western Mato Grosso; (3) Most of the agro-pastoral business are found in the southern Mato Grosso where about 46% of the state's deforestation during the 1981-2001 period occurred; (4) Rates of vegetation change are larger over non-inhabited areas (56%), especially in the north, than over the populated zones in the south (42%). Moreover, this work sheds some new light on the patterns of the changes in LU/LC features (deforestation and savannization) for each municipal district of Mato Grosso. In general, the following activities
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Zhou, J.; Fu, B. J.; Lü, N.; Gao, G. Y.; Lü, Y. H.; Wang, S.
2013-01-01
The Temporal stability of soil moisture (TSSM) is an important factor to evaluate the value of available water resources in a water-controlled ecosystem. In this study we used the evapotranspiration-TSSM (ET-TSSM) model and a new sampling design to examine the soil water dynamics and water balance of different land uses/cover types in a hilly landscape of the Loess Plateau under a finer spatiotemporal scale. Our primary focus is to examine the difference amo...
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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.
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Historical Land-Cover Change and Land-Use Conversions Global Dataset
National Oceanic and Atmospheric Administration, Department of Commerce — A set of three estimates of land-cover types and annual transformations of land use are provided on a global 0.5 x0.5 degree lat/lon grid at annual time steps. The...
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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.
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Monitoring land Cover Changes and Fragmentation dynamics in the ...
African Journals Online (AJOL)
Monitoring land Cover Changes and Fragmentation dynamics in the subtropical thicket of the Eastern Cape Province, South Africa. ... Baseline land use/cover maps and fragmentation analyses in a temporal framework are valuable for gaining insights into, among other things, carbon stock change trends. Keywords: Land ...
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DEFF Research Database (Denmark)
Kraemer, Roland; Prishchepov, Alexander; Müller, Daniel
2015-01-01
of Northern Kazakhstan. Further, we assessed the potential of currently idle cropland for re-cultivation. We reconstructed the cropland extent before and after the Virgin Lands Campaign using archival maps, and we mapped the agricultural land cover in the late Soviet and post-Soviet period using multi...... until 1990, as well as cropland contraction after 1990, occurred mainly in areas that were less favorable for agriculture. Cropland re-cultivation after 2000 was occurring on lands with relatively favorable agro-environmental conditions in comparison to remaining idle croplands, albeit with much lower...... agro-environmental endowment compared to stable croplands from 1990 to 2010. In sum, we found that cropland production potentials of the currently uncultivated areas are much lower than commonly believed, and further cropland expansion is only possible at the expense of marginal lands. Our results...
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Evaluating Anthropogenic Risk of Grassland and Forest Habitat Degradation using Land-Cover Data
Directory of Open Access Journals (Sweden)
Kurt Riitters
2009-09-01
Full Text Available The effects of landscape context on habitat quality are receiving increased attention in conservation biology. The objective of this research is to demonstrate a landscape-level approach to mapping and evaluating the anthropogenic risks of grassland and forest habitat degradation by examining habitat context as defined by intensive anthropogenic land uses at multiple spatial scales. A landscape mosaic model classifies a given location according to the amounts of intensive agriculture and intensive development in its surrounding landscape, providing measures of anthropogenic risks attributable to habitat isolation and edge effects at that location. The model is implemented using a land-cover map (0.09 ha/pixel of the conterminous United States and six landscape sizes (4.4, 15.2, 65.6, 591, 5300, and 47800 ha to evaluate the spatial scales of anthropogenic risk. Statistics for grassland and forest habitat are extracted by geographic overlays of the maps of land-cover and landscape mosaics. Depending on landscape size, 81 to 94 percent of all grassland and forest habitat occurs in landscapes that are dominated by natural land-cover including habitat itself. Within those natural-dominated landscapes, 50 percent of grassland and 59 percent of forest is within 590 m of intensive agriculture and/or intensive developed land which is typically a minor component of total landscape area. The conclusion is that anthropogenic risk attributable to habitat patch isolation affects a small proportion of the total grassland or forest habitat area, while the majority of habitat area is exposed to edge effects.
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LBA Regional Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)
National Aeronautics and Space Administration — This data set is a subset of an 8-km global land cover product (DeFries et al. 1998). This subset was created for the study area of the Large Scale...
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Directory of Open Access Journals (Sweden)
Muhammad Tauhidur Rahman
2016-02-01
Full Text Available While several studies examined land use and land cover changes in the central and western parts of Saudi Arabia, this study is the first to use remote sensing data to examine the decadal land cover changes in Saudi Arabia’s eastern coastal city of Al-Khobar between 1990 and 2013. Specifically, it utilized ISODATA classification method to classify Landsat TM, ETM+, and OLI data collected from 1990, 2001, and 2013 and then detected changes in the land cover within the study area. It then measured urban sprawl by calculating the relative Shannon’s entropy index values for the three years. With overall classification accuracies greater than 85%, the results show that urban built-up areas increased by 117% between 1990 and 2001 and 43.51% from 2001 to 2013. Vegetation increased by 110% from 1990 to 2001 and by 52% between 2001 and 2013. The entropy index values of 0.700 (1990, 0.779 (2001, and 0.840 (2013 indicates a high rate of urban sprawl and the city dispersing near the outskirts and towards the neighboring cities of Dhahran and Dammam. Future studies should examine the current challenges faced by the city’s residents due to urban expansion and attempt to find ways to resolve them in the near future.
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VT Generalized Land Cover Land Use for Champlain Basin - SAL 1992
Vermont Center for Geographic Information — (Link to Metadata) Circa 1992 land use - land cover (LULC) for the Lake Champlain Basin. This layer was created by performing a retrospective change detection on the...
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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.
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VT Generalized Land Cover Land Use for Champlain Basin - SAL 2001
Vermont Center for Geographic Information — (Link to Metadata) Circa 2001 land use / land cover (LULC) for the Lake Champlain Basin. The goal in creating this layer was to generate an "improved" version of...
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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
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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; Kanengieter, 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 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.
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LBA Regional Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)
National Aeronautics and Space Administration — ABSTRACT: This data set is a subset of an 8-km global land cover product (DeFries et al. 1998). This subset was created for the study area of the Large Scale...
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Directory of Open Access Journals (Sweden)
Ioannis Kamarinas
2016-10-01
Full Text Available Land cover can change frequently on intensively managed landscapes, affecting water quality across different spatiotemporal scales. Multi-resolution datasets are necessary in order to assess the extent and trends of these changes, as well as potential cross-scale interactions. In this study, both spatial and temporal analyses of land disturbance (i.e., soil exposure from vegetation removal and water quality were performed on datasets ranging from daily to yearly time scales. Time-series analyses of land disturbance were compared against the water quality variables of total suspended solids (TSS, turbidity, and visual clarity for the Hoteo River catchment on the North Island of New Zealand for the 2000–2013 period. During forest harvest and recovery phases, exotic forests were the dominant disturbance, up to five times the area of grassland disturbance; while after recovery, grasslands assumed the dominant role, for up to 16 times the area of forest disturbance. Time-series of TSS from field sampling (2000–2013 and TSS-event analyses (2012–2014 displayed distinct nonlinear patterns, suggesting that after major events, sediment that is stored in the landscape is exhausted and a period of sediment build-up follows until the next major event. Time-series analyses also showed a connection between trends in connected land disturbance and visual water clarity, with connected disturbance having the potential to be a water quality indicator. Future research should be conducted at even finer spatiotemporal scales over longer periods in order to identify effects of localized land disturbances on downstream water quality.
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Bayoudh, Meriam; Roux, Emmanuel; Richard, Gilles; Nock, Richard
2015-03-01
The number of satellites and sensors devoted to Earth observation has become increasingly elevated, delivering extensive data, especially images. At the same time, the access to such data and the tools needed to process them has considerably improved. In the presence of such data flow, we need automatic image interpretation methods, especially when it comes to the monitoring and prediction of environmental and societal changes in highly dynamic socio-environmental contexts. This could be accomplished via artificial intelligence. The concept described here relies on the induction of classification rules that explicitly take into account structural knowledge, using Aleph, an Inductive Logic Programming (ILP) system, combined with a multi-class classification procedure. This methodology was used to monitor changes in land cover/use of the French Guiana coastline. One hundred and fifty-eight classification rules were induced from 3 diachronic land cover/use maps including 38 classes. These rules were expressed in first order logic language, which makes them easily understandable by non-experts. A 10-fold cross-validation gave significant average values of 84.62%, 99.57% and 77.22% for classification accuracy, specificity and sensitivity, respectively. Our methodology could be beneficial to automatically classify new objects and to facilitate object-based classification procedures.
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Land use/land cover change geo-informative Tupu of Nujiang River in Northwest Yunnan Province
Wang, Jin-liang; Yang, Yue-yuan; Huang, You-ju; Fu, Lei; Rao, Qing
2008-10-01
Land Use/Land Cover Change (LUCC) is the core components of global change researches. It is significant for understanding regional ecological environment and LUCC mechanism of large scale to develop the study of LUCC of regional level. Nujiang River is the upper reaches of a big river in the South Asia--Salween River. Nujiang River is a typical mountainous river which is 3200 kilometer long and its basin area is 32.5 × 105 square kilometer. It locates in the core of "Three Parallel Rivers" World Natural Heritage. It is one of international biodiversity conservation center of the world, the ecological fragile zone and key ecological construction area, as well as a remote undeveloped area with high diversity ethnic. With the rapidly development of society and economy, the land use and land cover changed in a great degree. The function of ecosystem has being degraded in some areas which will not only impact on the ecological construction of local area, but also on the ecological safety of lower reaches -- Salween River. Therefore it is necessary to carry out the research of LUCC of Nujiang River. Based on the theory and methods of geo-information Tupu, the "Spatial Pattern" and "Change Process" of land use of middle reach in Nujiang River from 1974 to 2004 had been studied in quantification and integration, so as to provide a case study in local area and mesoscale in time. Supported by the remote sensing and GIS technology, LUCC Tupu of 1974-2004 had been built and the characteristics of LUCC have been analyzed quantificationally. The results showed that the built-up land (Included in this category are cities, towns, villages, strip developments along highways, transportation, power, and communications facilities, and areas such as those occupied by mills, shopping centers, industrial and commercial complexes, and institutions that may, in some instances, be isolated from urban areas), agriculture land, shrubbery land, meadow & grassland, difficultly/unused land
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Assessing land use/cover changes: a nationwide multidate spatial database for Mexico
Mas, Jean-François; Velázquez, Alejandro; Díaz-Gallegos, José Reyes; Mayorga-Saucedo, Rafael; Alcántara, Camilo; Bocco, Gerardo; Castro, Rutilio; Fernández, Tania; Pérez-Vega, Azucena
2004-10-01
A nationwide multidate GIS database was generated in order to carry out the quantification and spatial characterization of land use/cover changes (LUCC) in Mexico. Existing cartography on land use/cover at a 1:250,000 scale was revised to select compatible inputs regarding the scale, the classification scheme and the mapping method. Digital maps from three different dates (the late 1970s, 1993 and 2000) were revised, evaluated, corrected and integrated into a GIS database. In order to improve the reliability of the database, an attempt was made to assess the accuracy of the digitalisation procedure and to detect and correct unlikely changes due to thematic errors in the maps. Digital maps were overlaid in order to generate LUCC maps, transition matrices and to calculate rates of conversion. Based upon this database, rates of deforestation between 1976 and 2000 were evaluated as 0.25 and 0.76% per year for temperate and tropical forests, respectively.
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Directory of Open Access Journals (Sweden)
Jinshui Zhang
2017-04-01
Full Text Available This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD, to determine optimal parameters for support vector data description (SVDD model to map specific land cover by integrating training and window-based validation sets. Compared to the conventional approach where the validation set included target and outlier pixels selected visually and randomly, the validation set derived from WVS-SVDD constructed a tightened hypersphere because of the compact constraint by the outlier pixels which were located neighboring to the target class in the spectral feature space. The overall accuracies for wheat and bare land achieved were as high as 89.25% and 83.65%, respectively. However, target class was underestimated because the validation set covers only a small fraction of the heterogeneous spectra of the target class. The different window sizes were then tested to acquire more wheat pixels for validation set. The results showed that classification accuracy increased with the increasing window size and the overall accuracies were higher than 88% at all window size scales. Moreover, WVS-SVDD showed much less sensitivity to the untrained classes than the multi-class support vector machine (SVM method. Therefore, the developed method showed its merits using the optimal parameters, tradeoff coefficient (C and kernel width (s, in mapping homogeneous specific land cover.
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Land Use Cover Mapping of Water Melon and Cereals in Southern Italy
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Costanza Fiorentino
2010-06-01
Full Text Available The new high-resolution images from the satellites as IKONOS, SPOT5, Quickbird2 give us the opportunity to map ground features, which were not detectable in the past, by using medium resolution remote sensed data (LANDSAT. More accurate and reliable maps of land cover can then be produced. However, classification procedure with these images is more complex than with the medium resolution remote sensing data for two main reasons: firstly, because of their exiguous number of spectral bands, secondly, owing to high spatial resolution, the assumption of pixel independence does not generally hold. It is then necessary to have a multi-temporal series of images or to use classifiers taking into account also proximal information. The data in this study were (i a remote sensing image taken by SPOT5 satellite in July 2007 and used to discriminate the water melon cover class and, (ii three multi-temporal remote sensing images taken by SPOT5 satellite in May, June and July 2008 used to discriminate water melon and cereal crop cover classes. For water melon recognition, providing a single image in 2007, an object-oriented technique was applied instead of a traditional, per pixel technique obtaining an increase of overall accuracy of 15%. In 2008, since it was available a multi-temporal data set, a traditional ‘Maximum Likelihood’ technique was applied for both water melon and cereal crop cover class. The overall accuracy is greater than 95%.
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Anthropogenic Influences in Land Use/Land Cover Changes in Mediterranean Forest Landscapes in Sicily
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Donato S. La Mela Veca
2016-01-01
Full Text Available This paper analyzes and quantifies the land use/land cover changes of the main forest and semi-natural landscape types in Sicily between 1955 and 2012. We analyzed seven representative forest and shrubland landscapes in Sicily. These study areas were chosen for their importance in the Sicilian forest panorama. We carried out a diachronic survey on historical and current aerial photos; all the aerial images used to survey the land use/land cover changes were digitalized and georeferenced in the UTM WGS84 system. In order to classify land use, the Regional Forest Inventory 2010 legend was adopted for the more recent images, and the CORINE Land Cover III level used for the older, lower resolution images. This study quantifies forest landscape dynamics; our results show for almost all study areas an increase of forest cover and expansion, whereas a regressive dynamic is found in rural areas due to intensive agricultural and pasturage uses. Understanding the dynamics of forest landscapes could enhance the role of forestry policy as a tool for landscape management and regional planning.
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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
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Ghrefat, Habes A.; Goodell, Philip C.
2011-08-01
The goal of this research is to map land cover patterns and to detect changes that occurred at Alkali Flat and Lake Lucero, White Sands using multispectral Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI), and hyperspectral Hyperion and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data. The other objectives of this study were: (1) to evaluate the information dimensionality limits of Landsat 7 ETM+, ASTER, ALI, Hyperion, and AVIRIS data with respect to signal-to-noise and spectral resolution, (2) to determine the spatial distribution and fractional abundances of land cover endmembers, and (3) to check ground correspondence with satellite data. A better understanding of the spatial and spectral resolution of these sensors, optimum spectral bands and their information contents, appropriate image processing methods, spectral signatures of land cover classes, and atmospheric effects are needed to our ability to detect and map minerals from space. Image spectra were validated using samples collected from various localities across Alkali Flat and Lake Lucero. These samples were measured in the laboratory using VNIR-SWIR (0.4-2.5 μm) spectra and X-ray Diffraction (XRD) method. Dry gypsum deposits, wet gypsum deposits, standing water, green vegetation, and clastic alluvial sediments dominated by mixtures of ferric iron (ferricrete) and calcite were identified in the study area using Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and n-D Visualization. The results of MNF confirm that AVIRIS and Hyperion data have higher information dimensionality thresholds exceeding the number of available bands of Landsat 7 ETM+, ASTER, and ALI data. ASTER and ALI data can be a reasonable alternative to AVIRIS and Hyperion data for the purpose of monitoring land cover, hydrology and sedimentation in the basin. The spectral unmixing analysis and dimensionality eigen
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Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish
2010-01-01
Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of
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Directory of Open Access Journals (Sweden)
Hone-Jay Chu
2013-01-01
Full Text Available The effects on water quality of land use and land cover changes, which are associated with human activities and natural factors, are poorly identified. Fine resolution satellite imagery provides opportunities for land cover monitoring and assessment. The multiple satellite images after typhoon events collected from 2001 to 2010 covering land areas and land cover conditions are evaluated by the Normalized Difference Vegetation Index (NDVI. The relationship between land cover and observed water quality, such as suspended solids (SS and nitrate-nitrogens (NO3-N, are explored in the study area. Results show that the long-term variations in water quality are explained by NDVI data in the reservoir buffer zones. Suspended solid and nitrate concentrations are related to average NDVI values on multiple spatial scales. Annual NO3-N concentrations are positively correlated with an average NDVI with a 1 km reservoir buffer area, and the SS after typhoon events associated with landslides are negatively correlated with the average NDVI in the entire watershed. This study provides an approach for assessing the influences of land cover on variations in water quality.
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Directory of Open Access Journals (Sweden)
Brian A. Johnson
2018-01-01
Full Text Available The advent of very high resolution (VHR satellite imagery and the development of Geographic Object-Based Image Analysis (GEOBIA have led to many new opportunities for fine-scale land cover mapping, especially in urban areas. Image segmentation is an important step in the GEOBIA framework, so great time/effort is often spent to ensure that computer-generated image segments closely match real-world objects of interest. In the remote sensing community, segmentation is frequently performed using the multiresolution segmentation (MRS algorithm, which is tuned through three user-defined parameters (the scale, shape/color, and compactness/smoothness parameters. The scale parameter (SP is the most important parameter and governs the average size of generated image segments. Existing automatic methods to determine suitable SPs for segmentation are scene-specific and often computationally intensive, so an approach to estimating appropriate SPs that is generalizable (i.e., not scene-specific could speed up the GEOBIA workflow considerably. In this study, we attempted to identify generalizable SPs for five common urban land cover types (buildings, vegetation, roads, bare soil, and water through meta-analysis and nonlinear regression tree (RT modeling. First, we performed a literature search of recent studies that employed GEOBIA for urban land cover mapping and extracted the MRS parameters used, the image properties (i.e., spatial and radiometric resolutions, and the land cover classes mapped. Using this data extracted from the literature, we constructed RT models for each land cover class to predict suitable SP values based on the: image spatial resolution, image radiometric resolution, shape/color parameter, and compactness/smoothness parameter. Based on a visual and quantitative analysis of results, we found that for all land cover classes except water, relatively accurate SPs could be identified using our RT modeling results. The main advantage of our
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Directory of Open Access Journals (Sweden)
Wenyuan Zhang
2018-01-01
Full Text Available The availability of very high spatial resolution (VHR remote sensing imagery provides unique opportunities to exploit meaningful change information in detail with object-oriented image analysis. This study investigated land cover (LC changes in Shahu Lake of Wuhan using multi-temporal VHR aerial images in the years 1978, 1981, 1989, 1995, 2003, and 2011. A multi-resolution segmentation algorithm and CART (classification and regression trees classifier were employed to perform highly accurate LC classification of the individual images, while a post-classification comparison method was used to detect changes. The experiments demonstrated that significant changes in LC occurred along with the rapid urbanization during 1978–2011. The dominant changes that took place in the study area were lake and vegetation shrinking, replaced by high density buildings and roads. The total area of Shahu Lake decreased from ~7.64 km2 to ~3.60 km2 during the past 33 years, where 52.91% of its original area was lost. The presented results also indicated that urban expansion and inadequate legislative protection are the main factors in Shahu Lake’s shrinking. The object-oriented change detection schema presented in this manuscript enables us to better understand the specific spatial changes of Shahu Lake, which can be used to make reasonable decisions for lake protection and urban development.
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Land-cover change research at the U.S. Geological Survey-assessing our nation's dynamic land surface
Wilson, Tamara S.
2011-01-01
The U.S. Geological Survey (USGS) recently completed an unprecedented, 27-year assessment of land-use and land-cover change for the conterminous United States. For the period 1973 to 2000, scientists generated estimates of change in major types of land use and land cover, such as development, mining, agriculture, forest, grasslands, and wetlands. To help provide the insight that our Nation will need to make land-use decisions in coming decades, the historical trends data is now being used by the USGS to help model potential future land use/land cover under different scenarios, including climate, environmental, economic, population, public policy, and technological change.
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Land use/land cover changes around Rameshwaram Island, east coast of India
Digital Repository Service at National Institute of Oceanography (India)
Gowthaman, R.; Dwarakish, G.S.; Sanilkumar, V.
Land-use/land cover changes are studied using the Indian Remote Sensing satellite (IRS-1C, IRS-6) Linear Image Self-scan Sensor (LISS) III data of 1998 and 2010 Coastal land use categories such as sand, vegetation, coral reef and water have been...
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Directory of Open Access Journals (Sweden)
G. Billen
2012-03-01
Full Text Available Agricultural basins are the major source of N2O emissions, with arable land accounting for half of the biogenic emissions worldwide. Moreover, N2O emission strongly depends on the position of agricultural land in relation with topographical gradients, as footslope soils are often more prone to denitrification. The estimation of land surface area occupied by agricultural soils depends on the available spatial input information and resolution. Surface areas of grassland, forest and arable lands were estimated for the Orgeval sub-basin using two cover representations: the pan European CORINE Land Cover 2006 database (CLC 2006 and a combination of two databases produced by the IAU IDF (Institut d'Aménagement et d'Urbanisme de la Région d'Île-de-France, the MOS (Mode d'Occupation des Sols combined with the ECOMOS 2000 (a land-use classification. In this study, we have analyzed how different land-cover representations influence and introduce errors into the results of regional N2O emissions inventories. A further introduction of the topography concept was used to better identify the critical zones for N2O emissions, a crucial issue to better adapt the strategies of N2O emissions mitigation. Overall, we observed that a refinement of the land-cover database led to a 5 % decrease in the estimation of N2O emissions, while the integration of the topography decreased the estimation of N2O emissions up to 25 %.
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Theorizing Land Cover and Land Use Changes: The Case of Tropical Deforestation
Walker, Robert
2004-01-01
This article addresses land-cover and land-use dynamics from the perspective of regional science and economic geography. It first provides an account of the so-called spatially explicit model, which has emerged in recent years as a key empirical approach to the issue. The article uses this discussion as a springboard to evaluate the potential utility of von Thuenen to the discourse on land-cover and land-use change. After identifying shortcomings of current theoretical approaches to land use in mainly urban models, the article filters a discussion of deforestation through the lens of bid-rent and assesses its effectiveness in helping us comprehend the destruction of tropical forest in the Amazon basin. The article considers the adjustments that would have to be made to existing theory to make it more useful to the empirical issues.
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The impact of anthropogenic land use and land cover change on regional climate extremes.
Findell, Kirsten L; Berg, Alexis; Gentine, Pierre; Krasting, John P; Lintner, Benjamin R; Malyshev, Sergey; Santanello, Joseph A; Shevliakova, Elena
2017-10-20
Land surface processes modulate the severity of heat waves, droughts, and other extreme events. However, models show contrasting effects of land surface changes on extreme temperatures. Here, we use an earth system model from the Geophysical Fluid Dynamics Laboratory to investigate regional impacts of land use and land cover change on combined extremes of temperature and humidity, namely aridity and moist enthalpy, quantities central to human physiological experience of near-surface climate. The model's near-surface temperature response to deforestation is consistent with recent observations, and conversion of mid-latitude natural forests to cropland and pastures is accompanied by an increase in the occurrence of hot-dry summers from once-in-a-decade to every 2-3 years. In the tropics, long time-scale oceanic variability precludes determination of how much of a small, but significant, increase in moist enthalpy throughout the year stems from the model's novel representation of historical patterns of wood harvesting, shifting cultivation, and regrowth of secondary vegetation and how much is forced by internal variability within the tropical oceans.
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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.
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Hydrological impacts of global land cover change and human water use
Directory of Open Access Journals (Sweden)
J. H. C. Bosmans
2017-11-01
Full Text Available Human impacts on global terrestrial hydrology have been accelerating during the 20th century. These human impacts include the effects of reservoir building and human water use, as well as land cover change. To date, many global studies have focussed on human water use, but only a few focus on or include the impact of land cover change. Here we use PCR-GLOBWB, a combined global hydrological and water resources model, to assess the impacts of land cover change as well as human water use globally in different climatic zones. Our results show that land cover change has a strong effect on the global hydrological cycle, on the same order of magnitude as the effect of human water use (applying irrigation, abstracting water, for industrial use for example, including reservoirs, etc.. When globally averaged, changing the land cover from that of 1850 to that of 2000 increases discharge through reduced evapotranspiration. The effect of land cover change shows large spatial variability in magnitude and sign of change depending on, for example, the specific land cover change and climate zone. Overall, land cover effects on evapotranspiration are largest for the transition of tall natural vegetation to crops in energy-limited equatorial and warm temperate regions. In contrast, the inclusion of irrigation, water abstraction and reservoirs reduces global discharge through enhanced evaporation over irrigated areas and reservoirs as well as through water consumption. Hence, in some areas land cover change and water distribution both reduce discharge, while in other areas the effects may partly cancel out. The relative importance of both types of impacts varies spatially across climatic zones. From this study we conclude that land cover change needs to be considered when studying anthropogenic impacts on water resources.
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The Goddard multi-scale modeling system with unified physics
Directory of Open Access Journals (Sweden)
W.-K. Tao
2009-08-01
Full Text Available Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1 a cloud-resolving model (CRM, (2 a regional-scale model, the NASA unified Weather Research and Forecasting Model (WRF, and (3 a coupled CRM-GCM (general circulation model, known as the Goddard Multi-scale Modeling Framework or MMF. The same cloud-microphysical processes, long- and short-wave radiative transfer and land-surface processes are applied in all of the models to study explicit cloud-radiation and cloud-surface interactive processes in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator for comparison and validation with NASA high-resolution satellite data.
This paper reviews the development and presents some applications of the multi-scale modeling system, including results from using the multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols. In addition, use of the multi-satellite simulator to identify the strengths and weaknesses of the model-simulated precipitation processes will be discussed as well as future model developments and applications. -
Land cover mapping after the tsunami event over Nanggroe Aceh Darussalam (NAD) province, Indonesia
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.
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Tang, G.; Bartlein, P. J.
2012-01-01
Water balance models of simple structure are easier to grasp and more clearly connect cause and effect than models of complex structure. Such models are essential for studying large spatial scale land surface water balance in the context of climate and land cover change, both natural and anthropogenic. This study aims to (i) develop a large spatial scale water balance model by modifying a dynamic global vegetation model (DGVM), and (ii) test the model's performance in simulating actual evapotranspiration (ET), soil moisture and surface runoff for the coterminous United States (US). Toward these ends, we first introduced development of the "LPJ-Hydrology" (LH) model by incorporating satellite-based land covers into the Lund-Potsdam-Jena (LPJ) DGVM instead of dynamically simulating them. We then ran LH using historical (1982-2006) climate data and satellite-based land covers at 2.5 arc-min grid cells. The simulated ET, soil moisture and surface runoff were compared to existing sets of observed or simulated data for the US. The results indicated that LH captures well the variation of monthly actual ET (R2 = 0.61, p 0.46, p 0.52) with observed values over the years 1982-2006, respectively. The modeled spatial patterns of annual ET and surface runoff are in accordance with previously published data. Compared to its predecessor, LH simulates better monthly stream flow in winter and early spring by incorporating effects of solar radiation on snowmelt. Overall, this study proves the feasibility of incorporating satellite-based land-covers into a DGVM for simulating large spatial scale land surface water balance. LH developed in this study should be a useful tool for studying effects of climate and land cover change on land surface hydrology at large spatial scales.
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Land Use/Cover Changes between 1966 and 1996 in Chirokella ...
African Journals Online (AJOL)
Abstract: Keywords: Land Cover; Dynamic; Expansion; Exposed Land; ReductionTwo periods of panchromatic aerial photographs taken in 1966 and 1996 were analyzed to determine spatial and temporal land cover changes occurring in Chirokella micro-watershed, Southeastern Ethiopia. Theresults of the analysis were ...
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Impact of Land Use Land Cover Change on East Asian monsoon
Chilukoti, N.; Xue, Y.; Liu, Y.; Lee, J.
2017-12-01
Humans modify the Earth's terrestrial surface on a continental scale by removing natural vegetation for crops/grazing. The current rates, extents and intensities of Land Use and Land Cover Change (LULCC) are greater than ever in history. The earlier studies of Land-atmosphere interactions used specified land surface conditions without interannual variations. In this study using NCEP CFSv2 coupled with Simplified Simple Biosphere (SSiB) model, biogeophysical impacts of LULCC on climate variability, anomaly, and changes are investigated by using the LULCC map from the Hurtt et al. (2006, 2011), which covered 66 years from 1950-2015 with annual variability. We combined the changes in crop and pasture fractions and consider as LULCC. A methodology had been developed to convert the Hurtt LULCC change map with 1° resolution to the GCM grid points. Since the GCM has only one dominant type, when the crop and pasture frction value at one point was larger than the critical value, that grid was assigned as degraded. Comprehensive evaluation was conducted to ensure the consistence of the trend of land degradation in the Hurtt's map and in the GCM LULCC map. In the degraded point, trees were changed to low vegetation or grasses, and low vegetation to bare soil. A set of surface parameters such as leaf area index, vegetation height, roughness length, and soil parameters, associated with vegetation are changed to show the degradation effects. We integrated the model with the potential vegetation map and the map with LULCC from 1950 to 2015, and the results indicate the LULCC causes precipitation reduction globally, with the strongest signals over monsoon regions. For instance, the degradation in Mexico, West Africa, south and East Asia and South America produced significant precipitation anomalies, some of which are consistent with observed regional precipitation anomalies. Meanwhile, it has also found that the LULCC enhances the surface warming during the summer in monsoon
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Does estuarine health relate to catchment land-cover in the East ...
African Journals Online (AJOL)
Possible links between catchment and buffer zone land-cover class composition and the health of the East Kleinemonde Estuary were explored. There was a relationship between catchment land-cover and estuarine health within all assessed catchment delineations. Natural land-cover was determined to be the best ...
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Rokni Deilmai, B.; Ahmad, B. Bin; Zabihi, H.
2014-06-01
Mapping is essential for the analysis of the land use and land cover, which influence many environmental processes and properties. For the purpose of the creation of land cover maps, it is important to minimize error. These errors will propagate into later analyses based on these land cover maps. The reliability of land cover maps derived from remotely sensed data depends on an accurate classification. In this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber. Classification results indicate that SVM was more accurate than MLC. With demonstrated capability to produce reliable cover results, the SVM methods should be especially useful for land cover classification.
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International Nuclear Information System (INIS)
Deilmai, B Rokni; Ahmad, B Bin; Zabihi, H
2014-01-01
Mapping is essential for the analysis of the land use and land cover, which influence many environmental processes and properties. For the purpose of the creation of land cover maps, it is important to minimize error. These errors will propagate into later analyses based on these land cover maps. The reliability of land cover maps derived from remotely sensed data depends on an accurate classification. In this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber. Classification results indicate that SVM was more accurate than MLC. With demonstrated capability to produce reliable cover results, the SVM methods should be especially useful for land cover classification
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LAND COVER ASSESSMENT OF INDIGENOUS COMMUNITIES IN THE BOSAWAS REGION OF NICARAGUA
Data derived from remotely sensed images were utilized to conduct land cover assessments of three indigenous communities in northern Nicaragua. Historical land use, present land cover and land cover change processes were all identified through the use of a geographic informat...
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Prestele, Reinhard; Alexander, Peter; Rounsevell, Mark D A; Arneth, Almut; Calvin, Katherine; Doelman, Jonathan; Eitelberg, David A; Engström, Kerstin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Humpenöder, Florian; Jain, Atul K; Krisztin, Tamás; Kyle, Page; Meiyappan, Prasanth; Popp, Alexander; Sands, Ronald D; Schaldach, Rüdiger; Schüngel, Jan; Stehfest, Elke; Tabeau, Andrzej; Van Meijl, Hans; Van Vliet, Jasper; Verburg, Peter H
2016-12-01
Model-based global projections of future land-use and land-cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global-scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC
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Directory of Open Access Journals (Sweden)
Yongguang Zhai
2018-03-01
Full Text Available Obtaining accurate and timely land cover information is an important topic in many remote sensing applications. Using satellite image time series data should achieve high-accuracy land cover classification. However, most satellite image time-series classification methods do not fully exploit the available data for mining the effective features to identify different land cover types. Therefore, a classification method that can take full advantage of the rich information provided by time-series data to improve the accuracy of land cover classification is needed. In this paper, a novel method for time-series land cover classification using spectral, temporal, and spatial information at an annual scale was introduced. Based on all the available data from time-series remote sensing images, a refined nonlinear dimensionality reduction method was used to extract the spectral and temporal features, and a modified graph segmentation method was used to extract the spatial features. The proposed classification method was applied in three study areas with land cover complexity, including Illinois, South Dakota, and Texas. All the Landsat time series data in 2014 were used, and different study areas have different amounts of invalid data. A series of comparative experiments were conducted on the annual time-series images using training data generated from Cropland Data Layer. The results demonstrated higher overall and per-class classification accuracies and kappa index values using the proposed spectral-temporal-spatial method compared to spectral-temporal classification methods. We also discuss the implications of this study and possibilities for future applications and developments of the method.
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Directory of Open Access Journals (Sweden)
A. J. Pitman
2012-11-01
Full Text Available The impact of historical land use induced land cover change (LULCC on regional-scale climate extremes is examined using four climate models within the Land Use and Climate, IDentification of robust impacts project. To assess those impacts, multiple indices based on daily maximum and minimum temperatures and daily precipitation were used. We contrast the impact of LULCC on extremes with the impact of an increase in atmospheric CO2 from 280 ppmv to 375 ppmv. In general, consistent changes in both high and low temperature extremes are similar to the simulated change in mean temperature caused by LULCC and are restricted to regions of intense modification. The impact of LULCC on both means and on most temperature extremes is statistically significant. While the magnitude of the LULCC-induced change in the extremes can be of similar magnitude to the response to the change in CO2, the impacts of LULCC are much more geographically isolated. For most models, the impacts of LULCC oppose the impact of the increase in CO2 except for one model where the CO2-caused changes in the extremes are amplified. While we find some evidence that individual models respond consistently to LULCC in the simulation of changes in rainfall and rainfall extremes, LULCC's role in affecting rainfall is much less clear and less commonly statistically significant, with the exception of a consistent impact over South East Asia. Since the simulated response of mean and extreme temperatures to LULCC is relatively large, we conclude that unless this forcing is included, we risk erroneous conclusions regarding the drivers of temperature changes over regions of intense LULCC.
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The impact of land use/land cover changes on land degradation dynamics: a Mediterranean case study.
Bajocco, S; De Angelis, A; Perini, L; Ferrara, A; Salvati, L
2012-05-01
In the last decades, due to climate changes, soil deterioration, and Land Use/Land Cover Changes (LULCCs), land degradation risk has become one of the most important ecological issues at the global level. Land degradation involves two interlocking systems: the natural ecosystem and the socio-economic system. The complexity of land degradation processes should be addressed using a multidisciplinary approach. Therefore, the aim of this work is to assess diachronically land degradation dynamics under changing land covers. This paper analyzes LULCCs and the parallel increase in the level of land sensitivity to degradation along the coastal belt of Sardinia (Italy), a typical Mediterranean region where human pressure affects the landscape characteristics through fires, intensive agricultural practices, land abandonment, urban sprawl, and tourism concentration. Results reveal that two factors mainly affect the level of land sensitivity to degradation in the study area: (i) land abandonment and (ii) unsustainable use of rural and peri-urban areas. Taken together, these factors represent the primary cause of the LULCCs observed in coastal Sardinia. By linking the structural features of the Mediterranean landscape with its functional land degradation dynamics over time, these results contribute to orienting policies for sustainable land management in Mediterranean coastal areas.
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The Impact of Land Use/Land Cover Changes on Land Degradation Dynamics: A Mediterranean Case Study
Bajocco, S.; De Angelis, A.; Perini, L.; Ferrara, A.; Salvati, L.
2012-05-01
In the last decades, due to climate changes, soil deterioration, and Land Use/Land Cover Changes (LULCCs), land degradation risk has become one of the most important ecological issues at the global level. Land degradation involves two interlocking systems: the natural ecosystem and the socio-economic system. The complexity of land degradation processes should be addressed using a multidisciplinary approach. Therefore, the aim of this work is to assess diachronically land degradation dynamics under changing land covers. This paper analyzes LULCCs and the parallel increase in the level of land sensitivity to degradation along the coastal belt of Sardinia (Italy), a typical Mediterranean region where human pressure affects the landscape characteristics through fires, intensive agricultural practices, land abandonment, urban sprawl, and tourism concentration. Results reveal that two factors mainly affect the level of land sensitivity to degradation in the study area: (i) land abandonment and (ii) unsustainable use of rural and peri-urban areas. Taken together, these factors represent the primary cause of the LULCCs observed in coastal Sardinia. By linking the structural features of the Mediterranean landscape with its functional land degradation dynamics over time, these results contribute to orienting policies for sustainable land management in Mediterranean coastal areas.
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Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques
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.
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LeMoigne, Jacqueline; Laporte, Nadine; Netanyahuy, Nathan S.; Zukor, Dorothy (Technical Monitor)
2001-01-01
The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.
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Measurement of semantic similarity for land use and land cover classification systems
Deng, Dongpo
2008-12-01
Land use and land cover (LULC) data is essential to environmental and ecological research. However, semantic heterogeneous of land use and land cover classification are often resulted from different data resources, different cultural contexts, and different utilities. Therefore, there is need to develop a method to measure, compare and integrate between land cover categories. To understand the meaning and the use of terminology from different domains, the common ontology approach is used to acquire information regarding the meaning of terms, and to compare two terms to determine how they might be related. Ontology is a formal specification of a shared conceptualization of a domain of interest. LULC classification system is a ontology. The semantic similarity method is used to compare to entities of three LULC classification systems: CORINE (European Environmental Agency), Oregon State, USA), and Taiwan. The semantic properties and relations firstly have been extracted from their definitions of LULC classification systems. Then semantic properties and relations of categories in three LULC classification systems are mutually compared. The visualization of semantic proximity is finally presented to explore the similarity or dissimilarity of data. This study shows the semantic similarity method efficiently detect semantic distance in three LULC classification systems and find out the semantic similar objects.
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Tamara Heartsill Scalley; Tania del M. Lopez-Marrero
2014-01-01
An important element of the wise use of water-related ecosystem services provided by El Yunque National Forest, located in the Luquillo Mountains in northeastern Puerto Rico, is the facilitation of a clear understanding about the composition of land cover and its relation to water resources at different scales of analysis, management, and decision making. In this study...
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Land-Cover (LC) composition and conversions are important factors that affect ecosystem condition and function. The purpose of this research and development effort is to investigate the feasibility of using MODIS derived Normalized Difference Vegetation Index (NDVI) data to deli...
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WANG Huixian
2015-05-01
Full Text Available In order to adapt different scale land cover segmentation, an optimized approach under the guidance of k-means clustering for multi-scale segmentation is proposed. At first, small scale segmentation and k-means clustering are used to process the original images; then the result of k-means clustering is used to guide objects merging procedure, in which Otsu threshold method is used to automatically select the impact factor of k-means clustering; finally we obtain the segmentation results which are applicable to different scale objects. FNEA method is taken for an example and segmentation experiments are done using a simulated image and a real remote sensing image from GeoEye-1 satellite, qualitative and quantitative evaluation demonstrates that the proposed method can obtain high quality segmentation results.
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Error and Uncertainty in the Accuracy Assessment of Land Cover Maps
Sarmento, Pedro Alexandre Reis
Traditionally the accuracy assessment of land cover maps is performed through the comparison of these maps with a reference database, which is intended to represent the "real" land cover, being this comparison reported with the thematic accuracy measures through confusion matrixes. Although, these reference databases are also a representation of reality, containing errors due to the human uncertainty in the assignment of the land cover class that best characterizes a certain area, causing bias in the thematic accuracy measures that are reported to the end users of these maps. The main goal of this dissertation is to develop a methodology that allows the integration of human uncertainty present in reference databases in the accuracy assessment of land cover maps, and analyse the impacts that uncertainty may have in the thematic accuracy measures reported to the end users of land cover maps. The utility of the inclusion of human uncertainty in the accuracy assessment of land cover maps is investigated. Specifically we studied the utility of fuzzy sets theory, more precisely of fuzzy arithmetic, for a better understanding of human uncertainty associated to the elaboration of reference databases, and their impacts in the thematic accuracy measures that are derived from confusion matrixes. For this purpose linguistic values transformed in fuzzy intervals that address the uncertainty in the elaboration of reference databases were used to compute fuzzy confusion matrixes. The proposed methodology is illustrated using a case study in which the accuracy assessment of a land cover map for Continental Portugal derived from Medium Resolution Imaging Spectrometer (MERIS) is made. The obtained results demonstrate that the inclusion of human uncertainty in reference databases provides much more information about the quality of land cover maps, when compared with the traditional approach of accuracy assessment of land cover maps. None
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A review of supervised object-based land-cover image classification
Ma, Lei; Li, Manchun; Ma, Xiaoxue; Cheng, Liang; Du, Peijun; Liu, Yongxue
2017-08-01
Object-based image classification for land-cover mapping purposes using remote-sensing imagery has attracted significant attention in recent years. Numerous studies conducted over the past decade have investigated a broad array of sensors, feature selection, classifiers, and other factors of interest. However, these research results have not yet been synthesized to provide coherent guidance on the effect of different supervised object-based land-cover classification processes. In this study, we first construct a database with 28 fields using qualitative and quantitative information extracted from 254 experimental cases described in 173 scientific papers. Second, the results of the meta-analysis are reported, including general characteristics of the studies (e.g., the geographic range of relevant institutes, preferred journals) and the relationships between factors of interest (e.g., spatial resolution and study area or optimal segmentation scale, accuracy and number of targeted classes), especially with respect to the classification accuracy of different sensors, segmentation scale, training set size, supervised classifiers, and land-cover types. Third, useful data on supervised object-based image classification are determined from the meta-analysis. For example, we find that supervised object-based classification is currently experiencing rapid advances, while development of the fuzzy technique is limited in the object-based framework. Furthermore, spatial resolution correlates with the optimal segmentation scale and study area, and Random Forest (RF) shows the best performance in object-based classification. The area-based accuracy assessment method can obtain stable classification performance, and indicates a strong correlation between accuracy and training set size, while the accuracy of the point-based method is likely to be unstable due to mixed objects. In addition, the overall accuracy benefits from higher spatial resolution images (e.g., unmanned aerial
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Recent land cover history and nutrient retention in riparian wetlands
Hogan, D.M.; Walbridge, M.R.
2009-01-01
Wetland ecosystems are profoundly affected by altered nutrient and sediment loads received from anthropogenic activity in their surrounding watersheds. Our objective was to compare a gradient of agricultural and urban land cover history during the period from 1949 to 1997, with plant and soil nutrient concentrations in, and sediment deposition to, riparian wetlands in a rapidly urbanizing landscape. We observed that recent agricultural land cover was associated with increases in Nitrogen (N) and Phosphorus (P) concentrations in a native wetland plant species. Conversely, recent urban land cover appeared to alter receiving wetland environmental conditions by increasing the relative availability of P versus N, as reflected in an invasive, but not a native, plant species. In addition, increases in surface soil Fe content suggests recent inputs of terrestrial sediments associated specifically with increasing urban land cover. The observed correlation between urban land cover and riparian wetland plant tissue and surface soil nutrient concentrations and sediment deposition, suggest that urbanization specifically enhances the suitability of riparian wetland habitats for the invasive species Japanese stiltgrass [Microstegium vimenium (Trinius) A. Camus]. ?? 2009 Springer Science+Business Media, LLC.
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Improving Land Use/Land Cover Classification by Integrating Pixel Unmixing and Decision Tree Methods
Directory of Open Access Journals (Sweden)
Chao Yang
2017-11-01
Full Text Available Decision tree classification is one of the most efficient methods for obtaining land use/land cover (LULC information from remotely sensed imageries. However, traditional decision tree classification methods cannot effectively eliminate the influence of mixed pixels. This study aimed to integrate pixel unmixing and decision tree to improve LULC classification by removing mixed pixel influence. The abundance and minimum noise fraction (MNF results that were obtained from mixed pixel decomposition were added to decision tree multi-features using a three-dimensional (3D Terrain model, which was created using an image fusion digital elevation model (DEM, to select training samples (ROIs, and improve ROI separability. A Landsat-8 OLI image of the Yunlong Reservoir Basin in Kunming was used to test this proposed method. Study results showed that the Kappa coefficient and the overall accuracy of integrated pixel unmixing and decision tree method increased by 0.093% and 10%, respectively, as compared with the original decision tree method. This proposed method could effectively eliminate the influence of mixed pixels and improve the accuracy in complex LULC classifications.
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Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery
Moran, Emilio Federico.
2010-01-01
High spatial resolution images have been increasingly used for urban land use/cover classification, but the high spectral variation within the same land cover, the spectral confusion among different land covers, and the shadow problem often lead to poor classification performance based on the traditional per-pixel spectral-based classification methods. This paper explores approaches to improve urban land cover classification with Quickbird imagery. Traditional per-pixel spectral-based supervi...
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Directory of Open Access Journals (Sweden)
Dengqiu Li
2017-12-01
Full Text Available Land cover changes significantly influence vegetation greenness in different regions. Dense Landsat time series stacks provide unique opportunity to analyze land cover change and vegetation greenness trends at finer spatial scale. In the past three decades, large reclamation activities have greatly changed land cover and vegetation growth of coastal areas. However, rarely has research investigated these frequently changed coastal areas. In this study, Landsat Normalized Difference Vegetation Index time series (1984–2016 data and the Breaks For Additive Seasonal and Trend algorithm were used to detect the intensity and dates of abrupt changes in a typical coastal area—Hangzhou Bay, China. The prior and posterior land cover categories of each change were classified using phenology information through a Random Forest model. The impacts of land cover change on vegetation greenness trends of the inland and reclaimed areas were analyzed through distinguishing gradual and abrupt changes. The results showed that the intensity and date of land cover change were detected successfully with overall accuracies of 88.7% and 86.1%, respectively. The continuous land cover dynamics were retrieved accurately with an overall accuracy of 91.0% for ten land cover classifications. Coastal reclamation did not alleviate local cropland occupation, but prompted the vegetation greenness of the reclaimed area. Most of the inland area showed a browning trend. The main contributors to the greenness and browning trends were also quantified. These findings will help the natural resource management community generate better understanding of coastal reclamation and make better management decisions.
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Internal Migration and Land Use and Land Cover Changes in the Middle Mountains of Nepal
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Bhawana KC
2017-11-01
Full Text Available The movement of rural households from remote uplands to valley floors and to semiurban and urban areas (internal migration is a common phenomenon in the middle mountain districts of Nepal. Understanding the causes and effects of internal migration is critical to the development and implementation of policies that promote land use planning and sustainable resource management. Using geospatial information technologies and social research methods, we investigated the causes and effects of internal migration on land use and land cover patterns in a western mountain district of Nepal between 1998 and 2013. The results show a decreasing number of households at high elevations (above 1400 m, where an increase in forest cover has been observed with a consequent decrease in agricultural land and shrub- or grassland. At lower elevations (below 1400 m, forest cover has remained constant over the last 25 years, and the agricultural land area has increased but has become geometrically complex to meet the diverse needs and living requirements of the growing population. Our findings indicate that internal migration plays an important role in shaping land use and land cover change in the middle mountains of Nepal and largely determines the resource management, utilization, and distribution patterns within a small geographic unit. Therefore, land use planning must take an integrated and interdisciplinary approach rather than considering social, environmental, and demographic information in isolation.
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Zhao, Yaolong; Zhang, Ke; Fu, Yingchun; Zhang, Hong
2012-10-24
Monitoring land-use/land-cover change (LULCC) and exploring its mechanisms are important processes in the environmental management of a lake watershed. The purpose of this study was to examine the spatiotemporal pattern of LULCC by using multi landscape metrics in the Lake Dianchi watershed, which is located in the Yunnan-Guizhou Plateau of Southwest China. Landsat images from the years 1974, 1988, 1998, and 2008 were analyzed using geographical information system (GIS) techniques. The results reveal that land-use/land-cover has changed greatly in the watershed since 1974. This change in land use structure was embodied in the rapid increase of developed areas with a relative change rate of up to 324.4%. The increase in developed areas mainly occurred in agricultural land, especially near the shores of Lake Dianchi. The spatial pattern and structure of the change was influenced by the urban sprawl of the city of Kunming. The urban sprawl took on the typical expansion mode of cyclic structures and a jigsaw pattern and expanded to the shore of Lake Dianchi. Agricultural land changed little with respect to the structure but changed greatly in the spatial pattern. The landscape in the watershed showed a trend of fragmentation with a complex boundary. The dynamics of land-use/land-cover in the watershed correlate with land-use policies and economic development in China.
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Land use/land cover study of urban features using spot imagery
International Nuclear Information System (INIS)
Mahmood, S.A.; Qureshi, J.; Abbas, I.
2005-01-01
This study is based on visual interpretation and classification of the urban area of Peshawar. Cloud free satellite image of the French SPOT System in panchromatic mode at 100m/pixel spatial detail was used for this purpose. The coverage area comprised nearly (7.5 x 6)sq. km. on the ground depicting the major portion of the city. Various image interpretation elements were exploited to accomplish the study, thirteen land cover classes were identified and demarcated on a tracing sheet. Having prepared the base map. Satellite image map was constructed by assigning disparate colors to the identified features. Dimensions of some of the prominent, regular and liner features were computed from the image. The results indicate that high-resolution satellite image can be effectively used for mapping and area estimation of urban land use/land cover features. (author)
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Basyuni, M.; Sulistyono, N.; Slamet, B.; Wati, R.
2018-03-01
Forestry and peat land including land-based is one of the critical sectors in the inventory of CO2 emissions and mitigation efforts of climate change. The present study analyzed the land-use and land-cover changes between 2006 and 2012 in North Sumatra, Indonesia with emphasis to CO2 emissions. The land-use/land-cover consists of twenty-one classes. Redd Abacus software version 1.1.7 was used to measure carbon emission source as well as the predicted 2carbon dioxide emissions from 2006-2024. Results showed that historical emission (2006-2012) in this province, significant increases in the intensive land use namely dry land agriculture (109.65%), paddy field (16.23%) and estate plantation (15.11%). On the other hand, land-cover for forest decreased significantly: secondary dry land forest (7.60%), secondary mangrove forest (9.03%), secondary swamp forest (33.98%), and the largest one in the mixed dry land agriculture (79.96%). The results indicated that North Sumatra province is still a CO2 emitter, and the most important driver of emissions mostly derived from agricultural lands that contributed 2carbon dioxide emissions by 48.8%, changing from forest areas into degraded lands (classified as barren land and shrub) shared 30.6% and estate plantation of 22.4%. Mitigation actions to reduce carbon emissions was proposed such as strengthening the forest land, rehabilitation of degraded area, development and plantation forest, forest protection and forest fire control, and reforestation and conservation activity. These mitigation actions have been simulated to reduce 15% for forestry and 18% for peat land, respectively. This data is likely to contribute to the low emission development in North Sumatra.
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Directory of Open Access Journals (Sweden)
GEORGE CRACU
2014-11-01
Full Text Available Using remote sensing imagery and GIS to identify land cover and land use within Ceahlău Massif (Romania. In this study we considerer land cover and land use asessment within Ceahlău Massif (Romania using satellite imagery and GIS . To achieve this goal, we used a Landsat 7 ETM + satellite image, which was processed using specialized software in analyzing satellite images and GIS software in several stages: Downloading, importing and layer stack of all spectral bands composing satellite image; Establishment of areas of interest for each category of land cover and land use, which were digitized on - screen and for which spectral signatures characteristics were established; Supervised image classification using Maximum Likelihood Method; Importing the resulting m ap (raster in GIS environment and creating the final land cover/land use map for Ceahlău Massif. In the study area we identified nine land cover/land use classes: deciduous forests, mixed forests, coniferous forests, secondary grasslands, subalpine vegeta tion, alpine meadows, agricultural land, lakes and built area. By analizing the spatial distribution of these classes, it was found that forests are the best represented class, occupying an area of 188.4 km² (56.4% of total, followed by secondary grassl and, which occupies an area of 68.2 km² (20.4% of total, lakes (26.6 km² or 7.98% of total and agricultural land (16.1 km² or 4.86%
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MANAGEMENT EFFECTS ON GROUND COVER CLUMPINESS: SCALING FROM FIELD TO SENTINEL-2 COVER ESTIMATES
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P. Scarth
2017-11-01
Full Text Available Significant progress has been made in the development of cover data and derived products based on remotely sensed fractional cover information and field data across Australia, and these cover data sets are now used for quantifying and monitoring grazing land condition. The availability of a dense time-series of nearly 30 years of cover data to describe the spatial and temporal patterns in landscape changes over time can help with monitoring the effectiveness of grazing land management practice change. With the advent of higher spatial resolution data, such as that provided by the Copernicus Sentinel 2 series of satellites, we can look beyond reporting purely on cover amount and more closely at the operational monitoring and reporting on spatial arrangement of cover and its links with land condition. We collected high spatial resolution cover transects at 20 cm intervals over the Wambiana grazing trials in the Burdekin catchment in Queensland, Australia. Spatial variance analysis was used to determine the cover autocorrelation at various support intervals. Coincident Sentinel-2 imagery was collected and processed over all the sites providing imagery to link with the field data. We show that the spatial arrangement and temporal dynamics of cover are important indicators of grazing land condition for both productivity and water quality outcomes. The metrics and products derived from this research will assist land managers to prioritize investment and practice change strategies for long term sustainability and improved water quality, particularly in the Great Barrier Reef catchments.
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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
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Directory of Open Access Journals (Sweden)
Florence Pendrill
Full Text Available 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
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Land use, population dynamics, and land-cover change in Eastern Puerto Rico
W.A. Gould; S. Martinuzzi; I.K. Páres-Ramos
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 Surveyâs Water, Energy, and Biogeochemical Budgets (WEBB) program. This region occupies an area of 1,616 square kilometers, about 18 percent of the total land...
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NSGIC Local Govt | GIS Inventory — Land Use and Land Cover dataset current as of 2000. Existing land use derived from orthoimagery. Ground-truthing from discussion with local plan commission members..
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Sustaining forest landscape connectivity under different land cover change scenarios
Energy Technology Data Exchange (ETDEWEB)
Rubio, L.; Rodriguez-Freire, M.; Mateo-Sanchez, M. C.; Estreguil, C.; Saura, S.
2012-11-01
Managing forest landscapes to sustain functional connectivity is considered one of the key strategies to counteract the negative effects of climate and human-induced changes in forest species pools. With this objective, we evaluated whether a robust network of forest connecting elements can be identified so that it remains efficient when facing different types of potential land cover changes that may affect forest habitat networks and ecological fluxes. For this purpose we considered changes both in the forested areas and in the non-forest intervening landscape matrix. We combined some of the most recent developments in graph theory with models of land cover permeability and least-cost analysis through the forest landscape. We focused on a case of study covering the habitat of a forest dwelling bird (nuthatch, Sitta europaea) in the region of Galicia (NW Spain). Seven land-use change scenarios were analysed for their effects on connecting forest elements (patches and links): one was the simplest case in which the landscape is represented as a binary forest/non-forest pattern (and where matrix heterogeneity is disregarded), four scenarios in which forest lands were converted to other cover types (to scrubland due to wildfires, to extensive and intensive agriculture, and to urban areas), and two scenarios that only involved changes in the non-forested matrix (re naturalization and intensification). Our results show that while the network of connecting elements for the species was very robust to the conversion of the forest habitat patches to different cover types, the different change scenarios in the landscape matrix could more significantly weaken its long-term validity and effectiveness. This is particularly the case when most of the key connectivity providers for the nuthatch are located outside the protected areas or public forests in Galicia, where biodiversity-friendly measures might be more easily implemented. We discuss how the methodology can be applied to
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Cloud Detection by Fusing Multi-Scale Convolutional Features
Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang
2018-04-01
Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.
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Vasenev, Ivan; Yashin, Ivan; Lukin, Sergey; Valentini, Riccardo
2015-04-01
First decades of XXI century actualized for soil researches the principal methodical problem of most modern geosciences: what spatial and temporal scale would be optimal for land quality evaluation and land-use practice optimizing? It is becoming obvious that this question cannot have one solution and have to be solved with especial attention on the features of concrete region and landscape, land-use history and practical issues, land current state and environmental functions, soil cover patterns and variability, governmental requirements and local society needs, best available technologies and their potential profitability. Central Russia is one of the most dynamical economic regions with naturally high and man-made complicated landscape and soil cover variability, long-term land-use history and self-contradictory issues, high potential of profitable farming and increased risks of land degradation. Global climate and technological changes essentially complicate the originally high and sharply increased in XX century farming land heterogeneity in the Central Russia that actualizes system analysis of its zonal, intra-zonal and azonal soil cover patterns according to their influence on land environmental functions, agroecological quality, and land-use and monitoring efficiency variability. Developed by the Laboratory of agroecological monitoring, ecosystem modeling & prediction (LAMP / RTSAU with support of RF Governmental projects #11.G34.31.0079 and #14.120.14.4266) regional systems of greenhouse gases environmental monitoring RusFluxNet (6 fixed & 1 mobile eddy covariance stations with zonal functional sets of key plots with chamber investigations in 5 Russian regions) and of agroecological monitoring (in representative key plots with different farming practice in 9 RF regions) allow to do this analysis in frame of enough representative regional multi-factorial matrix of soil cover patterns, bioclimatic conditions, landscape features, and land-use history and
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Effect of thematic map misclassification on landscape multi-metric assessment.
Kleindl, William J; Powell, Scott L; Hauer, F Richard
2015-06-01
Advancements in remote sensing and computational tools have increased our awareness of large-scale environmental problems, thereby creating a need for monitoring, assessment, and management at these scales. Over the last decade, several watershed and regional multi-metric indices have been developed to assist decision-makers with planning actions of these scales. However, these tools use remote-sensing products that are subject to land-cover misclassification, and these errors are rarely incorporated in the assessment results. Here, we examined the sensitivity of a landscape-scale multi-metric index (MMI) to error from thematic land-cover misclassification and the implications of this uncertainty for resource management decisions. Through a case study, we used a simplified floodplain MMI assessment tool, whose metrics were derived from Landsat thematic maps, to initially provide results that were naive to thematic misclassification error. Using a Monte Carlo simulation model, we then incorporated map misclassification error into our MMI, resulting in four important conclusions: (1) each metric had a different sensitivity to error; (2) within each metric, the bias between the error-naive metric scores and simulated scores that incorporate potential error varied in magnitude and direction depending on the underlying land cover at each assessment site; (3) collectively, when the metrics were combined into a multi-metric index, the effects were attenuated; and (4) the index bias indicated that our naive assessment model may overestimate floodplain condition of sites with limited human impacts and, to a lesser extent, either over- or underestimated floodplain condition of sites with mixed land use.
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Directory of Open Access Journals (Sweden)
Kerry A Brown
Full Text Available 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.
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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...
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A proposed periodic national inventory of land use land cover change
Hans T. Schreuder; Paul W. Snook; Raymond L. Czaplewski; Glenn P. Catts
1986-01-01
Three alternatives using digital thematic mapper (TM), analog TM, and a combination of either digital or analog TM data with low altitude photography are discussed for level I and level II land use/land cover classes for a proposed national inventory. Digital TM data should prove satisfactory for estimating acreage in level I classes, although estimates of precision...
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Kaya, S.; Alganci, U.; Sertel, E.; Ustundag, B.
2015-12-01
Throughout the history, agricultural activities have been performed close to urban areas. Main reason behind this phenomenon is the need of fast marketing of the agricultural production to urban residents and financial provision. Thus, using the areas nearby cities for agricultural activities brings out advantage of easy transportation of productions and fast marketing. For decades, heavy migration to cities has directly and negatively affected natural grasslands, forests and agricultural lands. This pressure has caused agricultural lands to be changed into urban areas. Dense urbanization causes increase in impervious surfaces, heat islands and many other problems in addition to destruction of agricultural lands. Considering the negative impacts of urbanization on agricultural lands and natural resources, a periodic monitoring of these changes becomes indisputably important. At this point, satellite images are known to be good data sources for land cover / use change monitoring with their fast data acquisition, large area coverages and temporal resolution properties. Classification of the satellite images provides thematic the land cover / use maps of the earth surface and changes can be determined with GIS based analysis multi-temporal maps. In this study, effects of heavy urbanization over agricultural lands in Istanbul, metropolitan city of Turkey, were investigated with use of multi-temporal Landsat TM satellite images acquired between 1984 and 2011. Images were geometrically registered to each other and classified using supervised maximum likelihood classification algorithm. Resulting thematic maps were exported to GIS environment and destructed agricultural lands by urbanization were determined using spatial analysis.
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an assessment of the land use and land cover changes in shurugwi
African Journals Online (AJOL)
Dr Osondu
Zimbabwe's fast-track land reform programme and other economic activities have caused ... Geographic Information System and remote sensing techniques. ... 1990 and 2009 Landsat images of the district were downloaded from the Global Land cover Facility as well ... Information System (GIS) are now providing new.
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Quality Evaluation of Land-Cover Classification Using Convolutional Neural Network
Dang, Y.; Zhang, J.; Zhao, Y.; Luo, F.; Ma, W.; Yu, F.
2018-04-01
Land-cover classification is one of the most important products of earth observation, which focuses mainly on profiling the physical characters of the land surface with temporal and distribution attributes and contains the information of both natural and man-made coverage elements, such as vegetation, soil, glaciers, rivers, lakes, marsh wetlands and various man-made structures. In recent years, the amount of high-resolution remote sensing data has increased sharply. Accordingly, the volume of land-cover classification products increases, as well as the need to evaluate such frequently updated products that is a big challenge. Conventionally, the automatic quality evaluation of land-cover classification is made through pixel-based classifying algorithms, which lead to a much trickier task and consequently hard to keep peace with the required updating frequency. In this paper, we propose a novel quality evaluation approach for evaluating the land-cover classification by a scene classification method Convolutional Neural Network (CNN) model. By learning from remote sensing data, those randomly generated kernels that serve as filter matrixes evolved to some operators that has similar functions to man-crafted operators, like Sobel operator or Canny operator, and there are other kernels learned by the CNN model that are much more complex and can't be understood as existing filters. The method using CNN approach as the core algorithm serves quality-evaluation tasks well since it calculates a bunch of outputs which directly represent the image's membership grade to certain classes. An automatic quality evaluation approach for the land-cover DLG-DOM coupling data (DLG for Digital Line Graphic, DOM for Digital Orthophoto Map) will be introduced in this paper. The CNN model as an robustness method for image evaluation, then brought out the idea of an automatic quality evaluation approach for land-cover classification. Based on this experiment, new ideas of quality evaluation
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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.
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International Nuclear Information System (INIS)
Majaliwa, J.G.M.; Twongyirwe, R.; Nyenje, R.; Oluka, M.; Ongom, B.; Sirike, J.; Mfitumukiza, D.; Azanga, E.; Natumanya, R.; Mwerera, R.; Barasa, B.
2010-01-01
The change from natural forest cover to tea and Eucalyptus is rampant in protected areas of western Uganda. The objectives were; to examine the trend in land-use /cover change and determine the effect of these changes on the physico-chemical properties of soils around Kibale National Park. The trend in land use/cover change was assessed by analyzing a series of Landsat images. Focused group discussions and key informant interviews were used for land-use/cover reconstruction. Three major land uses were included; wood lot (Eucalyptus grandis; 5 years old) ), tea (57 years old) and natural forest used as a control. Each of these land-uses were selected at two different North facing landscape positions and were replicated three times. A total of 36 composite soil samples were taken at 0-15 and 15-30 cm depth from natural forest, Tea plantation and eucalyptus on three ridges. Results showed that small scale farming, tea and eucalyptus plantation and built up area have increased over time, to the expense of wood lot and forest cover. Tea and Eucalyptus have induced changes in: exchangeable Mg and Ca, available P, SOM, ph, and bulk density of sub soil (P<.05). Landscape positions within land use also significantly influenced most soil properties (P<.05). Similar findings were observed by Wang et al. (2006) in commercial tea plantations in China that received nitrogen fertilizers.
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National Oceanic and Atmospheric Administration, Department of Commerce — This data set consists of land cover derived from high resolution imagery according to the Coastal Change Analysis Program (C-CAP) protocol. This data set utilized 1...
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Directory of Open Access Journals (Sweden)
Miyuki Iiyama
2018-04-01
Full Text Available Densely populated rural areas in the East African Highlands have faced significant intensification challenges under extreme population pressure on their land and ecosystems. Sustainable agricultural intensification, in the context of increasing cropping intensities, is a prerequisite for deliberate land management strategies that deliver multiple ecosystem goods (food, energy, income sources, etc. and services (especially improving soil conditions on the same land, as well as system resilience, if adopted at scale. Tree based ecosystem approaches (TBEAs are among such multi-functional land management strategies. Knowledge on the multi-functionality of TBEAs and on their scaling up, however, remains severely limited due to several methodological challenges. This study aims at offering an analytical perspective to view multi-functional TBEAs as an integral part of sustainable agricultural intensification. The study proposes a conceptual framework to guide the analysis of socio-economic data and applies it to cross-site analysis of TBEAs in extremely densely populated Rwanda. Heterogeneous TBEAs were identified across Rwanda’s different agro-ecological zones to meet locally-specific smallholders’ needs for a set of ecosystem goods and services on the same land. The sustained adoption of TBEAs would be guaranteed if farmers subjectively recognize their compatibility and synergy with sustainable intensification of existing farming systems, supported by favorable institutional conditions.
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Directory of Open Access Journals (Sweden)
E. Fundisi
2017-09-01
Full Text Available Urban areas, particularly in developing countries face immense challenges such as climate change, poverty, lack of resources poor land use management systems, and week environmental management practices. Mitigating against these challenges is often hampered by lack of data on urban expansion, urban footprint and land cover. To support the recently adopted new urban agenda 2030 there is need for the provision of information to support decision making in the urban areas. Earth observation has been identified as a tool to foster sustainable urban planning and smarter cities as recognized by the new urban agenda, because it is a solution to unavailability of data. Accordingly, this study uses high resolution EO data Pleiades satellite imagery to map and document land cover for the rapidly expanding area of Midrand in Johannesburg, South Africa. An unsupervised land cover classification of the Pleiades satellite imagery was carried out using ENVI software, whereas NDVI was derived using ArcGIS software. The land cover had an accuracy of 85% that is highly adequate to document the land cover in Midrand. The results are useful because it provides a highly accurate land cover and NDVI datasets at localised spatial scale that can be used to support land use management strategies within Midrand and the City of Johannesburg South Africa.
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Fundisi, E.; Musakwa, W.
2017-09-01
Urban areas, particularly in developing countries face immense challenges such as climate change, poverty, lack of resources poor land use management systems, and week environmental management practices. Mitigating against these challenges is often hampered by lack of data on urban expansion, urban footprint and land cover. To support the recently adopted new urban agenda 2030 there is need for the provision of information to support decision making in the urban areas. Earth observation has been identified as a tool to foster sustainable urban planning and smarter cities as recognized by the new urban agenda, because it is a solution to unavailability of data. Accordingly, this study uses high resolution EO data Pleiades satellite imagery to map and document land cover for the rapidly expanding area of Midrand in Johannesburg, South Africa. An unsupervised land cover classification of the Pleiades satellite imagery was carried out using ENVI software, whereas NDVI was derived using ArcGIS software. The land cover had an accuracy of 85% that is highly adequate to document the land cover in Midrand. The results are useful because it provides a highly accurate land cover and NDVI datasets at localised spatial scale that can be used to support land use management strategies within Midrand and the City of Johannesburg South Africa.
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Drivers and Implications of Land Use and Land Cover Change in the ...
African Journals Online (AJOL)
This study explores the major drivers of Land-use/Land-cover (LULC) dynamics and the observed environmental degradation as a response to these changes in the Modjo watershed, central Ethiopia. Data for this study were generated through household survey and supplemented with remotely sensed image interpretation ...
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Minnesota Land Use and Cover - A 1990's Census of the Land - Tiled
Minnesota Department of Natural Resources — This data set integrates six different source data sets to provide a simplified overall view of Minnesota's land use / cover. The six source data sets covered...
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Standard land-cover classification scheme for remote-sensing applications in South Africa
CSIR Research Space (South Africa)
Thompson, M
1996-01-01
Full Text Available For large areas, satellite remote-sensing techniques have now become the single most effective method for land-cover and land-use data acquisition. However, the majority of land-cover (and land-use) classification schemes used have been developed...
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Scale-dependence of land use effects on water quality of streams in agricultural catchments
International Nuclear Information System (INIS)
Buck, Oliver; Niyogi, Dev K.; Townsend, Colin R.
2004-01-01
The influence of land use on water quality in streams is scale-dependent and varies in time and space. In this study, land cover patterns and stocking rates were used as measures of agricultural development in two pasture and one native grassland catchment in New Zealand and were related to water quality in streams of various orders. The amount of pasture per subcatchment correlated well to total nitrogen and nitrate in one catchment and turbidity and total phosphorous in the other catchment. Stocking rates were only correlated to total phosphorous in one pasture catchment but showed stronger correlations to ammonium, total phosphorous and total nitrogen in the other pasture catchment. Winter and spring floods were significant sources of nutrients and faecal coliforms from one of the pasture catchments into a wetland complex. Nutrient and faecal coliform concentrations were better predicted by pastural land cover in fourth-order than in second-order streams. This suggests that upstream land use is more influential in larger streams, while local land use and other factors may be more important in smaller streams. These temporal and spatial scale effects indicate that water-monitoring schemes need to be scale-sensitive. - Land use influences water quality of streams at various spatial scales
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Scale-dependence of land use effects on water quality of streams in agricultural catchments
Energy Technology Data Exchange (ETDEWEB)
Buck, Oliver; Niyogi, Dev K.; Townsend, Colin R
2004-07-01
The influence of land use on water quality in streams is scale-dependent and varies in time and space. In this study, land cover patterns and stocking rates were used as measures of agricultural development in two pasture and one native grassland catchment in New Zealand and were related to water quality in streams of various orders. The amount of pasture per subcatchment correlated well to total nitrogen and nitrate in one catchment and turbidity and total phosphorous in the other catchment. Stocking rates were only correlated to total phosphorous in one pasture catchment but showed stronger correlations to ammonium, total phosphorous and total nitrogen in the other pasture catchment. Winter and spring floods were significant sources of nutrients and faecal coliforms from one of the pasture catchments into a wetland complex. Nutrient and faecal coliform concentrations were better predicted by pastural land cover in fourth-order than in second-order streams. This suggests that upstream land use is more influential in larger streams, while local land use and other factors may be more important in smaller streams. These temporal and spatial scale effects indicate that water-monitoring schemes need to be scale-sensitive. - Land use influences water quality of streams at various spatial scales.
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Finding pathways to national-scale land-sector sustainability
Gao, Lei; Bryan, Brett A.
2017-04-01
The 17 Sustainable Development Goals (SDGs) and 169 targets under Agenda 2030 of the United Nations map a coherent global sustainability ambition at a level of detail general enough to garner consensus amongst nations. However, achieving the global agenda will depend heavily on successful national-scale implementation, which requires the development of effective science-driven targets tailored to specific national contexts and supported by strong national governance. Here we assess the feasibility of achieving multiple SDG targets at the national scale for the Australian land-sector. We scaled targets to three levels of ambition and two timeframes, then quantitatively explored the option space for target achievement under 648 plausible future environmental, socio-economic, technological and policy pathways using the Land-Use Trade-Offs (LUTO) integrated land systems model. We show that target achievement is very sensitive to global efforts to abate emissions, domestic land-use policy, productivity growth rate, and land-use change adoption behaviour and capacity constraints. Weaker target-setting ambition resulted in higher achievement but poorer sustainability outcomes. Accelerating land-use dynamics after 2030 changed the targets achieved by 2050, warranting a longer-term view and greater flexibility in sustainability implementation. Simultaneous achievement of multiple targets is rare owing to the complexity of sustainability target implementation and the pervasive trade-offs in resource-constrained land systems. Given that hard choices are needed, the land-sector must first address the essential food/fibre production, biodiversity and land degradation components of sustainability via specific policy pathways. It may also contribute to emissions abatement, water and energy targets by capitalizing on co-benefits. However, achieving targets relevant to the land-sector will also require substantial contributions from other sectors such as clean energy, food systems
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Simulation of Land-Cover Change in Taipei Metropolitan Area under Climate Change Impact
International Nuclear Information System (INIS)
Huang, Kuo-Ching; Huang, Thomas C C
2014-01-01
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
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Directory of Open Access Journals (Sweden)
Laura E. Hoyos
2018-05-01
Full Text Available Land-cover changes are driven by different combinations of biophysical, economic, and cultural drivers that are acting at different scales. We aimed to (1 analyze trends in land use and land cover changes (conversion, abandonment, forest persistence in the dry Chaco in central Argentina (1979 to 2010, and (2 examine how physical and socio-economic drivers have influenced those changes. Based on Landsat data, we obtained the proportion of 16 classes of land cover changes for 81 individual circular samples. We performed a Principal Component Analysis (PCA to identify the main trends of change across the whole region. To explore the relationships between the changes in land cover and drivers, we developed a GIS comprising thematic maps representing the different drivers. The drivers were first correlated with the two first PCA axes, and in a second approximation were subjected to multiple regression analyses. We obtained in this way the best model to explain each PCA axis. The highest conversion, as indicated by PCA axis 1, was experienced by flat areas close to roads and with the highest annual rainfall. Besides agricultural expansion that was triggered by precipitation increase as a major driver of forest conversion, changes that were observed during the period 1979–2010, may have also been influenced by several other driving forces acting at different spatial scales and contexts.
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Herold, M.; Woodcock, C.; Stehman, S.; Nightingale, J.; Friedl, M.; Schmullius, C.
2010-12-01
A global effort to assess the accuracy of existing and future land cover products derived from a variety of satellite sensors over a range of spatial resolutions is being led by the Land Cover Implementation Team (LC-IT) of GOFC/GOLD (Global Observation of Land Cover Dynamics) in conjunction with the CEOS (Committee on Earth Observation Satellites) WGCV (Working Group on Calibration and Validation) LPV (Land Product Validation) subgroup. The first phase of this effort is complete and culminated in a publication of community consensus "best practices" for validation of global land cover datasets (2). The next phase is to implement the recommendations outlined in the "best practices" document. A "living database" of global randomized sample sites will form the basis of accuracy assessment for a host of global land cover products (GLC2000, MODIS land cover, GLOBCOVER, United Nation's Forest Resource Assessment (FRA2010), and the Mid-Decadal Global Land Survey. This "living dataset" will also be a community resource available for use in validation of regional or national mapping efforts using LCCS (UN FAO's Land Cover Classification System). Based on the known accuracy of existing land cover products, GOFC/GOLD will to develop and update a "best currently available" global land cover map. Individual geographic regions may be selected from different land cover products (global, national or regional), or they may be combined in various ways
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Land-cover mapping using multitemporal, dual-frequency polarimetric SAR data
DEFF Research Database (Denmark)
Skriver, Henning; Schou, Jesper; Dierking, Wolfgang
2000-01-01
during the growing season acquired a lot of data over a Danish agricultural site. The data acquisitions were co-ordinated with ground surveys to obtain a detailed land cover map. The test area contains a large number of different land cover classes, such as more than 10 different crop types, deciduous......The Danish Center for Remote Sensing (DCRS) is, in collaboration with the Danish mapping agency, conducting a study on topographic mapping using SAR data, and land cover mapping results are presented. The Danish EMISAR system (an L- and C-band, fully polarimetric, airborne SAR) have in 1994 to 1999...
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Estimating Accuracy of Land-Cover Composition From Two-Stage Clustering Sampling
Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), ...
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A reconstruction of global agricultural areas and land cover for the last millennium
Pongratz, J.; Reick, C.; Raddatz, T.; Claussen, M.
2008-09-01
Humans have substantially modified the Earth's land cover, especially by transforming natural ecosystems to agricultural areas. In preindustrial times, the expansion of agriculture was probably the dominant process by which humankind altered the Earth system, but little is known about its extent, timing, and spatial pattern. This study presents an approach to reconstruct spatially explicit changes in global agricultural areas (cropland and pasture) and the resulting changes in land cover over the last millennium. The reconstruction is based on published maps of agricultural areas for the last three centuries. For earlier times, a country-based method is developed that uses population data as a proxy for agricultural activity. With this approach, the extent of cropland and pasture is consistently estimated since AD 800. The resulting reconstruction of agricultural areas is combined with a map of potential vegetation to estimate the resulting historical changes in land cover. Uncertainties associated with this approach, in particular owing to technological progress in agriculture and uncertainties in population estimates, are quantified. About 5 million km2 of natural vegetation are found to be transformed to agriculture between AD 800 and 1700, slightly more to cropland (mainly at the expense of forested area) than to pasture (mainly at the expense of natural grasslands). Historical events such as the Black Death in Europe led to considerable dynamics in land cover change on a regional scale. The reconstruction can be used with global climate and ecosystem models to assess the impact of human activities on the Earth system in preindustrial times.
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ISLSCP II IGBP DISCover and SiB Land Cover, 1992-1993
National Aeronautics and Space Administration — This data set describes the geographic distributions of 17 classes of land cover based on the International Geosphere-Biosphere DISCover land cover legend (Loveland...
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NLCD - MODIS land cover- albedo dataset for the continental United States
U.S. Environmental Protection Agency — The NLCD-MODIS land cover-albedo database integrates high-quality MODIS albedo observations with areas of homogeneous land cover from NLCD. The spatial resolution...
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CLC2000 land cover database of the Netherlands; monitoring land cover changes between 1986 and 2000
Hazeu, G.W.
2003-01-01
The 1986 CORINE land cover database of the Netherlands was revised and updated on basis of Landsat satellite images and ancillary data. Interpretation of satellite images from 1986 and 2000 resulted in the CLC2000, CLC1986rev and CLCchange databases. A standard European legend and production
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International Nuclear Information System (INIS)
West, Tristram O; Le Page, Yannick; Wolf, Julie; Thomson, Allison M; Huang, Maoyi
2014-01-01
Projections of land cover change generated from integrated assessment models (IAM) and other economic-based models can be applied for analyses of environmental impacts at sub-regional and landscape scales. For those IAM and economic models that project land cover change at the continental or regional scale, these projections must be downscaled and spatially distributed prior to use in climate or ecosystem models. Downscaling efforts to date have been conducted at the national extent with relatively high spatial resolution (30 m) and at the global extent with relatively coarse spatial resolution (0.5°). We revised existing methods to downscale global land cover change projections for the US to 0.05° resolution using MODIS land cover data as the initial proxy for land class distribution. Land cover change realizations generated here represent a reference scenario and two emissions mitigation pathways (MPs) generated by the global change assessment model (GCAM). Future gridded land cover realizations are constructed for each MODIS plant functional type (PFT) from 2005 to 2095, commensurate with the community land model PFT land classes, and archived for public use. The GCAM land cover realizations provide spatially explicit estimates of potential shifts in croplands, grasslands, shrublands, and forest lands. Downscaling of the MPs indicate a net replacement of grassland by cropland in the western US and by forest in the eastern US. An evaluation of the downscaling method indicates that it is able to reproduce recent changes in cropland and grassland distributions in respective areas in the US, suggesting it could provide relevant insights into the potential impacts of socio-economic and environmental drivers on future changes in land cover. (letters)
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Land management and land-cover change have impacts of similar magnitude on surface temperature
DEFF Research Database (Denmark)
Luyssaert, Sebastiaan; Jammet, Mathilde; Stoy, Paul C.
2014-01-01
Anthropogenic changes to land cover (LCC) remain common, but continuing land scarcity promotes the widespread intensification of land management changes (LMC) to better satisfy societal demand for food, fibre, fuel and shelter1. The biophysical effects of LCC on surface climate are largely unders...
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Land-cover effects on soil organic carbon stocks in a European city.
Edmondson, Jill L; Davies, Zoe G; McCormack, Sarah A; Gaston, Kevin J; Leake, Jonathan R
2014-02-15
Soil is the vital foundation of terrestrial ecosystems storing water, nutrients, and almost three-quarters of the organic carbon stocks of the Earth's biomes. Soil organic carbon (SOC) stocks vary with land-cover and land-use change, with significant losses occurring through disturbance and cultivation. Although urbanisation is a growing contributor to land-use change globally, the effects of urban land-cover types on SOC stocks have not been studied for densely built cities. Additionally, there is a need to resolve the direction and extent to which greenspace management such as tree planting impacts on SOC concentrations. Here, we analyse the effect of land-cover (herbaceous, shrub or tree cover), on SOC stocks in domestic gardens and non-domestic greenspaces across a typical mid-sized U.K. city (Leicester, 73 km(2), 56% greenspace), and map citywide distribution of this ecosystem service. SOC was measured in topsoil and compared to surrounding extra-urban agricultural land. Average SOC storage in the city's greenspace was 9.9 kg m(-2), to 21 cm depth. SOC concentrations under trees and shrubs in domestic gardens were greater than all other land-covers, with total median storage of 13.5 kg m(-2) to 21 cm depth, more than 3 kg m(-2) greater than any other land-cover class in domestic and non-domestic greenspace and 5 kg m(-2) greater than in arable land. Land-cover did not significantly affect SOC concentrations in non-domestic greenspace, but values beneath trees were higher than under both pasture and arable land, whereas concentrations under shrub and herbaceous land-covers were only higher than arable fields. We conclude that although differences in greenspace management affect SOC stocks, trees only marginally increase these stocks in non-domestic greenspaces, but may enhance them in domestic gardens, and greenspace topsoils hold substantial SOC stores that require protection from further expansion of artificial surfaces e.g. patios and driveways. Copyright
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LBA-ECO ND-01 Land Cover Classification, Rondonia, Brazil: 1975-2000
National Aeronautics and Space Administration — This data set provides a time series of land cover classifications for Ariquemes, Ji-Parana, and Luiza, research sites in Rondonia, Brazil. The land cover...
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Towards scale-independent land-surface flux estimates in Noah-MP
Thober, Stephan; Mizukami, Naoki; Samaniego, Luis; Attinger, Sabine; Clark, Martyn; Cuntz, Matthias
2017-04-01
Land-surface models use a variety of process representations to calculate terrestrial energy, water and biogeochemical fluxes. These process descriptions are usually derived from point measurements which are, in turn, scaled to much larger resolutions ranging from 1 km in catchment hydrology to 100 km in climate modelling. Both, hydrologic and climate models are nowadays run on different spatial resolutions, using the exactly same land surface representations. A fundamental criterion for the physical consistency of land-surface simulations across scales is that a flux estimated over a given area is independent of the spatial model resolution (i.e., the flux-matching criterion). The Noah-MP land surface model considers only one soil and land cover type per model grid cell without any representation of their subgrid variability, implying a weak flux-matching. A fractional approach simulates the subgrid variability but it requires a higher computational demand than using effective parameters and it is used only for land cover in current land surface schemes. A promising approach to derive scale-independent parameters is the Multiscale Parameter Regionalization (MPR) technique, which consists of two steps: first, it applies transfer functions directly to high-resolution data (such as 100 m soil maps) to derive high-resolution model parameter fields, acknowledging the full subgrid variability. Second, it upscales these high-resolution parameter fields to the model resolution by using appropriate upscaling operators. MPR has shown to improve substantially the scalability of the mesoscale Hydrologic Models mHM (Samaniego et al., 2010 WRR). Here, we apply the MPR technique to the Noah-MP land-surface model for a large sample of basins distributed across the contiguous USA. Specifically, we evaluate the flux-matching criterion for several hydrologic fluxes such as evapotranspiration and drainage at scales ranging from 3 km to 48 km. We investigate the impact of different
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Global spatial assessment of WUI and related land cover in Portugal
Tonini, Marj; Parente, Joana; Pereira, Mário G.
2017-04-01
Forest fires as hazardous events are assuming an increasing importance all around the world, especially in relation to climate changes and to urban sprawl, which makes it difficult to outline a border between human infrastructures and wildland areas. This zone, known as the Wildland Urban Interface (WUI), is defined as the area where structures and other human development meet or intermingle with undeveloped wildland (USDA 2001). Its extension is influenced by anthropogenic features, since, as it was proved, the distance to roads and houses negatively influence the probability of forest fires ignitions, while the population density positively affects it. Land use is also a crucial feature to be considered in the analyses of the impact of forest fires, and each natural, semi-natural and artificial land cover can be affected in a different proportion. The aim of the present study is to investigate and mapping the wildland urban interface and its temporal dynamic in Portugal at global scale. Secondly, it aims at providing a quantitative characterization of forest fires occurred in the last few decades (1990 - 2012) in relation to the burned area and the land covers evolution. The National mapping burnt area dataset (by the Institute for the Conservation of Nature and Forests) provided the information allowing to precisely localize forest fires. The land cover classes were derived from the Corinne Land Cover, available for four periods (1990-2000-2006-2012). The following two classes were retained to outline the WUI: 1) artificial surfaces, as representative of the human development; 2) forest and semi-natural area, as representative of undeveloped wildland. First, we investigated the distribution of the burned areas among the different detailed land covers classes. Then, to map the WUI, we considered a buffer distance around artificial surfaces located in proximity of forests and semi-natural areas. The descriptive statistic carried out individually within each
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A hierarchical approach of hybrid image classification for land use and land cover mapping
Directory of Open Access Journals (Sweden)
Rahdari Vahid
2018-01-01
Full Text Available Remote sensing data analysis can provide thematic maps describing land-use and land-cover (LULC in a short period. Using proper image classification method in an area, is important to overcome the possible limitations of satellite imageries for producing land-use and land-cover maps. In the present study, a hierarchical hybrid image classification method was used to produce LULC maps using Landsat Thematic mapper TM for the year of 1998 and operational land imager OLI for the year of 2016. Images were classified using the proposed hybrid image classification method, vegetation cover crown percentage map from normalized difference vegetation index, Fisher supervised classification and object-based image classification methods. Accuracy assessment results showed that the hybrid classification method produced maps with total accuracy up to 84 percent with kappa statistic value 0.81. Results of this study showed that the proposed classification method worked better with OLI sensor than with TM. Although OLI has a higher radiometric resolution than TM, the produced LULC map using TM is almost accurate like OLI, which is because of LULC definitions and image classification methods used.
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Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes
Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.
2011-01-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to
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Projecting land-use and land cover change in a subtropical urban watershed
John J. Lagrosa IV; Wayne C. Zipperer; Michael G. Andreu
2018-01-01
Urban landscapes are heterogeneous mosaics that develop via significant land-use and land cover (LULC) change. Current LULC models project future landscape patterns, but generally avoid urban landscapes due to heterogeneity. To project LULC change for an urban landscape, we parameterize an established LULC model (Dyna-CLUE) under baseline conditions (continued current...
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Land use and land cover dynamics in the Brazilian Amazon: an overview
Robert Walker; Alfredo Kingo Oyama Homma
1996-01-01
This paper presents a theoretical discussion of processes linking land use decisions and land cover outcomes at household level, with an emphasis on small proceduers. Evidence from the literature substantiating the existence of domestic cycle phenomena is brought forward and interpreted for the Brazilian case. Also considered are the relative disposition of production...
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Effects of land cover change on the tropical circulation in a GCM
Jonko, Alexandra Karolina; Hense, Andreas; Feddema, Johannes Jan
2010-09-01
Multivariate statistics are used to investigate sensitivity of the tropical atmospheric circulation to scenario-based global land cover change (LCC), with the largest changes occurring in the tropics. Three simulations performed with the fully coupled Parallel Climate Model (PCM) are compared: (1) a present day control run; (2) a simulation with present day land cover and Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 greenhouse gas (GHG) projections; and (3) a simulation with SRES A2 land cover and GHG projections. Dimensionality of PCM data is reduced by projection onto a priori specified eigenvectors, consisting of Rossby and Kelvin waves produced by a linearized, reduced gravity model of the tropical circulation. A Hotelling T 2 test is performed on projection amplitudes. Effects of LCC evaluated by this method are limited to diabatic heating. A statistically significant and recurrent signal is detected for 33% of all tests performed for various combinations of parameters. Taking into account uncertainties and limitations of the present methodology, this signal can be interpreted as a Rossby wave response to prescribed LCC. The Rossby waves are shallow, large-scale motions, trapped at the equator and most pronounced in boreal summer. Differences in mass and flow fields indicate a shift of the tropical Walker circulation patterns with an anomalous subsidence over tropical South America.
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Solar energy development impacts on land cover change and protected areas.
Hernandez, Rebecca R; Hoffacker, Madison K; Murphy-Mariscal, Michelle L; Wu, Grace C; Allen, Michael F
2015-11-03
Decisions determining the use of land for energy are of exigent concern as land scarcity, the need for ecosystem services, and demands for energy generation have concomitantly increased globally. Utility-scale solar energy (USSE) [i.e., ≥ 1 megawatt (MW)] development requires large quantities of space and land; however, studies quantifying the effect of USSE on land cover change and protected areas are limited. We assessed siting impacts of >160 USSE installations by technology type [photovoltaic (PV) vs. concentrating solar power (CSP)], area (in square kilometers), and capacity (in MW) within the global solar hot spot of the state of California (United States). Additionally, we used the Carnegie Energy and Environmental Compatibility model, a multiple criteria model, to quantify each installation according to environmental and technical compatibility. Last, we evaluated installations according to their proximity to protected areas, including inventoried roadless areas, endangered and threatened species habitat, and federally protected areas. We found the plurality of USSE (6,995 MW) in California is sited in shrublands and scrublands, comprising 375 km(2) of land cover change. Twenty-eight percent of USSE installations are located in croplands and pastures, comprising 155 km(2) of change. Less than 15% of USSE installations are sited in "Compatible" areas. The majority of "Incompatible" USSE power plants are sited far from existing transmission infrastructure, and all USSE installations average at most 7 and 5 km from protected areas, for PV and CSP, respectively. Where energy, food, and conservation goals intersect, environmental compatibility can be achieved when resource opportunities, constraints, and trade-offs are integrated into siting decisions.
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Directory of Open Access Journals (Sweden)
Ankana
2016-01-01
Full Text Available Remote sensing and Geographical Information System (GIS are the most effective tools in spatial data analysis. Natural resources like land, forest and water, these techniques have proved a valuable source of information generation as well as in the management and planning purposes. This study aims to suggest possible land and forest management strategies in Chakia tahsil based on land use and land cover analysis and the changing pattern observed during the last ten years. The population of Chakia tahsil is mainly rural in nature. The study has revealed that the northern part of the region, which offers for the settlement and all the agricultural practices constitutes nearly 23.48% and is a dead level plain, whereas the southern part, which constitute nearly 76.6% of the region is characterized by plateau and is covered with forest. The southern plateau rises abruptly from the northern alluvial plain with a number of escarpments. The contour line of 100 m mainly demarcates the boundary between plateau and plain. The plateau zone is deeply dissected and highly rugged terrain. The resultant topography comprises of a number of mesas and isolated hillocks showing elevation differences from 150 m to 385 m above mean sea level. Being rugged terrain in the southern part, nowadays human encroachment are taking place for more land for the cultivation. The changes were well observed in the land use and land cover in the study region. A large part of fallow land and open forest were converted into cultivated land.
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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
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Song, Kaishan; Wu, Junjie; Li, Lin; Wang, Zongming; Lu, Dongmei; Du, Jia; Zhang, Bai
2010-08-01
Atmospheric water vapor (AWV) content is closely related to precipitation that in turn has effects on the productivity of agricultural, forestry and range land. MODIS images have been used for AWV retrieval, and the method uses either two (0.841-0.876 μm and 0.915-0.965 μm) or three (0.841-0.876, 0.915-0.965 and 1.230-0-1.250 μm) MODIS channel ratios. We applied both methods to the MODIS data over Northeast China acquired from June to August, 2008 to retrieve AWV content, and the results were validated on ground observed data from 10 radio sonde stations characterized by various land cover. The bulk results indicate that the two-channel ratio outperformed the three-channel ratio based on the coefficient of determination R2 = 0.81 vs. 0.78. The validation results for individual land cover types also support this observation with R2 = 0.92 vs. 0.84 for woodland, 0.82 vs. 0.79 for cropland, 0.90 vs. 0.86 for grassland and 0.673 vs. 0.669 for urban areas. The spatial distribution of AWV derived using the two-channel ratio method was correlated to land-use classification data, and a high correlation was evident when other conditions were similar. With the exception of dry cropland, the amount of average water vapor content over different land use types demonstrates a consistent order: water-body > paddy-field > woodland > grassland > barren for the analyzed multi-temporal MODIS data. This order partially matches the evapotranspiration pattern of underlying surface, and future work is required for analyzing the association of the landscape pattern with AWV in the region.
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Landspotting: collecting essential land cover information via an attractive internet game
Fritz, Steffen; McCallum, Ian; Perger, Christoph; Christian, Schill; Florian, Kraxner; Erik, Lindquist; Michael, Obersteiner
2010-05-01
Based on the geo-wiki.org concept of collecting land cover information via crowdsourcing, we present a novel approach on how to get the crowd involved. Internet games as well as social networks are becoming increasingly popular and the full potential is yet to be exploited. However, thus far, few if any games provide anything other than entertainment. Can an attractive philanthropic game be created which uses the crowd to collect essential information needed to help to acquire better data to improve the understanding of the earth system? Since accurate and up to date information on global land cover plays a very important role in a number of different research fields such as climate change, monitoring of tropical deforestation, land use monitoring and land-use modelling, but still shows high levels of disagreement, the game will focus on how this essential land cover calibration and validation data can be collected in areas where uncertainty is currently highest. In the current version of the land spotting game, we combine uncertainty hotspot information from three global land cover datasets (GLC, MODIS and GlobCover). With an ever increasing amount of high resolution images available on Google Earth, it is becoming increasingly possible to distinguish land cover features with a high degree of accuracy. We first direct the landspotting game community to certain hotspots of land cover uncertainty and then ask them to enter/record the type of land cover they see (for this they will be able to acquire a certain number of points), possibly uploading pictures at that location (additional points will be received). Even though the development of the game "landspotting.org" is still underway, we illustrate what the functionality will be and what features are envisaged for the near future. Landspotting.org will be designed in such a way as to challenge users to help map out the remaining areas of confusion over the globe - possibly in the form of an adventure game. Users
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C-CAP Santa Cruz 2001 era High Resolution Land Cover Metadata
National Oceanic and Atmospheric Administration, Department of Commerce — This dataset represents land cover for the San Lorenzo River basin in Santa Cruz County, California derived from high resolution imagery. The land cover features in...
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Surface albedo influences climate by affecting the amount of solar radiation that is reflected at the Earth’s surface, and surface albedo is, in turn, affected by land cover. General Circulation Models typically use modeled or prescribed albedo to assess the influence of land co...
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Directory of Open Access Journals (Sweden)
Ayisulitan Maimaitiaili
2018-01-01
Full Text Available In arid regions, oases ecosystems are fragile and sensitive to climate change, and water is the major limiting factor for environmental and socio-economic developments. Understanding the drivers of land use/cover change (LUCC in arid regions is important for the development of management strategies to improve or prevent environmental deterioration and loss of natural resources. The Kashgar Region is the key research area in this study; it is a typical mountain-alluvial plain-oasis-desert ecosystem in an arid region, and is one of the largest oases in Xinjiang Uyghur Autonomous Region, China. In addition, the Kashgar Region is an important cotton and grain production area. This study’s main objectives are to quantify predominant LUCCs and identify their driving forces, based on the integration of multiple remote sensors and applications of environmental and socio-economic data. Results showed that LUCCs have been significant in the Kashgar Region during the last 42 years. Cultivated land and urban/built-up lands were the most changed land cover (LC, by 3.6% and 0.4% from 1972 to 10.2% and 3% in 2014, respectively. By contrast, water and forest areas declined. Grassland and snow-covered areas have fluctuated along with climate and human activities. Bare land was changed slightly from 1972 to 2014. According to the land use transfer matrix, cultivated land replaced grass- and forestland. Urban/built-up land mainly expanded over cultivated and bare land. LUCCs were triggered by the interplay of natural and social drivers. Increasing runoff, caused by regional climate changes in seasonal variation, and snow melt water, have provided water resources for LC changes. In the same way, population growth, changes in land tenure, and socio-economic development also induced LUCCs. However, expansion of cultivated land and urban/built-up land led to increased water consumption and stressed fragile water systems during on-going climate changes. Therefore
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Gaydos, Leonard
1978-01-01
Computer-aided techniques for interpreting multispectral data acquired by Landsat offer economies in the mapping of land cover. Even so, the actual establishment of the statistical classes, or "signatures," is one of the relatively more costly operations involved. Analysts have therefore been seeking cost-saving signature extension techniques that would accept training data acquired for one time or place and apply them to another. Opportunities to extend signatures occur in preprocessing steps and in the classification steps that follow. In the present example, land cover classes were derived by the simplest and most direct form of signature extension: Classes statistically derived from a Landsat scene for the Puget Sound area, Wash., were applied to the Portland area, Oreg., using data for the next Landsat scene acquired less than 25 seconds down orbit. Many features can be recognized on the reduced-scale version of the Portland land cover map shown in this report, although no statistical assessment of its accuracy is available.
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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
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Directory of Open Access Journals (Sweden)
Jianwu Yan
2013-01-01
Full Text Available Climate change inevitably leads to changes in hydrothermal circulation. However, thermal-hydrologic exchanging caused by land cover change has also undergone ineligible changes. Therefore, studying the comprehensive effects of climate and land cover changes on land surface water and heat exchanges enables us to well understand the formation mechanism of regional climate and predict climate change with fewer uncertainties. This study investigated the land surface thermal-hydrologic exchange across southern China for the next 40 years using a land surface model (ecosystem-atmosphere simulation scheme (EASS. Our findings are summarized as follows. (i Spatiotemporal variation patterns of sensible heat flux (H and evapotranspiration (ET under the land cover scenarios (A2a or B2a and climate change scenario (A1B are unanimous. (ii Both H and ET take on a single peak pattern, and the peak occurs in June or July. (iii Based on the regional interannual variability analysis, H displays a downward trend (10% and ET presents an increasing trend (15%. (iv The annual average H and ET would, respectively, increase and decrease by about 10% when woodland converts to the cultivated land. Through this study, we recognize that land surface water and heat exchanges are affected greatly by the future climate change as well as land cover change.
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the implications of land use/cover dynamics on resources
African Journals Online (AJOL)
2017-12-04
Dec 4, 2017 ... Land use maps were produced using the GIS software packages of ... Keywords: Land use/cover, Dynamics, Remote Sensing Techniques, Geographic Information System, .... sporadic floods and landslides in Bambui which.
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Directory of Open Access Journals (Sweden)
S. A. Rahaman
2017-05-01
Full Text Available 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.
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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.
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A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes
Tao, W. K.
2017-12-01
In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.
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Directory of Open Access Journals (Sweden)
Dong Jiang
Full Text Available Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1 images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization with convenience.
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Buruli Ulcer Disease and Its Association with Land Cover in Southwestern Ghana.
Directory of Open Access Journals (Sweden)
Jianyong Wu
2015-06-01
Full Text Available Buruli ulcer (BU, one of 17 neglected tropical diseases, is a debilitating skin and soft tissue infection caused by Mycobacterium ulcerans. In tropical Africa, changes in land use and proximity to water have been associated with the disease. This study presents the first analysis of BU at the village level in southwestern Ghana, where prevalence rates are among the highest globally, and explores fine and medium-scale associations with land cover by comparing patterns both within BU clusters and surrounding landscapes.We obtained 339 hospital-confirmed BU cases in southwestern Ghana between 2007 and 2010. The clusters of BU were identified using spatial scan statistics and the percentages of six land cover classes were calculated based on Landsat and Rapid Eye imagery for each of 154 villages/towns. The association between BU prevalence and each land cover class was calculated using negative binomial regression models. We found that older people had a significantly higher risk for BU after considering population age structure. BU cases were positively associated with the higher percentage of water and grassland surrounding each village, but negatively associated with the percent of urban. The results also showed that BU was clustered in areas with high percentage of mining activity, suggesting that water and mining play an important and potentially interactive role in BU occurrence.Our study highlights the importance of multiple land use changes along the Offin River, particularly mining and agriculture, which might be associated with BU disease in southwestern Ghana. Our study is the first to use both medium- and high-resolution imagery to assess these changes. We also show that older populations (≥ 60 y appear to be at higher risk of BU disease than children, once BU data were weighted by population age structures.
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Directory of Open Access Journals (Sweden)
Enrico Paringit
2011-05-01
Full Text Available Landsat MSS and ETM+ images were analyzed to detect 25-year land-cover change (1976–2001 in the critical Taguibo Watershed in Mindanao Island, Southern Philippines. This watershed has experienced historical modifications of its land-cover due to the presence of logging industries in the 1950s, and continuous deforestation due to illegal logging and slash-and-burn agriculture in the present time. To estimate the impacts of land-cover change on watershed runoff, land-cover information derived from the Landsat images was utilized to parameterize a GIS-based hydrologic model. The model was then calibrated with field-measured discharge data and used to simulate the responses of the watershed in its year 2001 and year 1976 land-cover conditions. The availability of land-cover information on the most recent state of the watershed from the Landsat ETM+ image made it possible to locate areas for rehabilitation such as barren and logged-over areas. We then created a “rehabilitated” land-cover condition map of the watershed (re-forestation of logged-over areas and agro-forestation of barren areas and used it to parameterize the model and predict the runoff responses of the watershed. Model results showed that changes in land-cover from 1976 to 2001 were directly related to the significant increase in surface runoff. Runoff predictions showed that a full rehabilitation of the watershed, especially in barren and logged-over areas, will be likely to reduce the generation of a huge volume of runoff during rainfall events. The results of this study have demonstrated the usefulness of multi-temporal Landsat images in detecting land-cover change, in identifying areas for rehabilitation, and in evaluating rehabilitation strategies for management of tropical watersheds through its use in hydrologic modeling.
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Thawaba, Salem; Abu-Madi, Maher; Özerol, Gül
2017-01-01
Land cover has been changed by humans throughout history. At the global level, population growth and socio-economic development have a significant impact on land resources. Recently, scholars added climate change as one of the major factors affecting land-cover transformation. In the West Bank of
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Wang, J.; Xue, Y.; Forman, B. A.; Girotto, M.; Reichle, R. H.
2017-12-01
The Gravity and Recovery Climate Experiment (GRACE) has revolutionized large-scale remote sensing of the Earth's terrestrial hydrologic cycle and has provided an unprecedented observational constraint for global land surface models. However, the coarse-scale (in space and time), vertically-integrated measure of terrestrial water storage (TWS) limits GRACE's applicability to smaller scale hydrologic applications. In order to enhance model-based estimates of TWS while effectively adding resolution (in space and time) to the coarse-scale TWS retrievals, a multi-variate, multi-sensor data assimilation framework is presented here that simultaneously assimilates gravimetric retrievals of TWS in conjunction with passive microwave (PMW) brightness temperature (Tb) observations over snow-covered terrain. The framework uses the NASA Catchment Land Surface Model (Catchment) and an ensemble Kalman filter (EnKF). A synthetic assimilation experiment is presented for the Volga river basin in Russia. The skill of the output from the assimilation of synthetic observations is compared with that of model estimates generated without the benefit of assimilating the synthetic observations. It is shown that the EnKF framework improves modeled estimates of TWS, snow depth, and snow mass (a.k.a. snow water equivalent). The data assimilation routine produces a conditioned (updated) estimate that is more accurate and contains less uncertainty during both the snow accumulation phase of the snow season as well as during the snow ablation season.
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Directory of Open Access Journals (Sweden)
Mohammad Mehedy Hassan
2017-12-01
Full Text Available Accurate information on, and human interpretation of, urban land cover using satellite-derived sensor imagery is critical given the intricate nature and niches of socioeconomic, demographic, and environmental factors occurring at multiple temporal and spatial scales. Detailed knowledge of urban land and their changing pattern over time periods associated with ecological risk is, however, required for the best use of critical land and its environmental resources. Interest in this topic has increased recently, driven by a surge in the use of open-source computing software, satellite-derived imagery, and improved classification algorithms. Using the machine learning algorithm Random Forest, combined with multi-date Landsat imagery, we classified eight periods of land cover maps with up-to-date spatial and temporal information of urban land between the period of 1972 and 2015 for the mega-urban region of greater Dhaka in Bangladesh. Random Forest—a non-parametric ensemble classifier—has shown a quantum increase in satellite-derived image classification accuracy due to its outperformance over traditional approaches, e.g., Maximum Likelihood. Employing Random Forest as an image classification approach for this study with independent cross-validation techniques, we obtained high classification accuracy, user and producer accuracy. Our overall classification accuracy ranges were between 85% and 97% with kappa values between 0.81 and 0.94. The area statistics derived from the thematic land cover map show that the built-up area in the 43-year study period expanded quickly, from 35 km2 in 1972 to 378 km2 in 2015, with a net increase rate of approximately 980% and an average annual growth rate of 6%. This growth rate, however, was higher in peripheral areas, with a 2903% increase and an annual expansion rate of 8%, compared to a 460% increase with an annual growth rate of 4% in the core city area (Dhaka City Corporation. This huge urban expansion took
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Directory of Open Access Journals (Sweden)
Amit Kumar Batar
2017-04-01
Full Text Available The Garhwal Himalaya has experienced extensive deforestation and forest fragmentation, but data and documentation detailing this transformation of the Himalaya are limited. The aim of this study is to analyse the observed changes in land cover and forest fragmentation that occurred between 1976 and 2014 in the Garhwal Himalayan region in India. Three images from Landsat 2 Multispectral Scanner System (MSS, Landsat 5 Thematic Mapper (TM, and Landsat 8 Operational Land Imager (OLI were used to extract the land cover maps. A cross-tabulation detection method in the geographic information system (GIS module was used to detect land cover changes during the 1st period (1976–1998 and 2nd period (1998–2014. The landscape fragmentation tool LFT v2.0 was used to construct a forest fragmentation map and analyse the forest fragmentation pattern and change during the 1st period (1976–1998 and 2nd period (1998–2014. The overall annual rate of change in the forest cover was observed to be 0.22% and 0.27% in the 1st period (1976–1998 and 2nd period (1998–2014, respectively. The forest fragmentation analysis shows that a large core forest has decreased throughout the study period. The total area of forest patches also increased from 1976 to 2014, which are completely degraded forests. The results indicate that anthropogenic activities are the main causes of the loss of forest cover and forest fragmentation, but that natural factors also contributed. An increase in the area of scrub and barren land also contributed to the accumulation of wasteland or non-forest land in this region. Determining the trend and the rate of land cover conversion is necessary for development planners to establish a rational land use policy.
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Effect of landslides on the structural characteristics of land-cover based on complex networks
He, Jing; Tang, Chuan; Liu, Gang; Li, Weile
2017-09-01
Landslides have been widely studied by geologists. However, previous studies mainly focused on the formation of landslides and never considered the effect of landslides on the structural characteristics of land-cover. Here we define the modeling of the graph topology for the land-cover, using the satellite images of the earth’s surface before and after the earthquake. We find that the land-cover network satisfies the power-law distribution, whether the land-cover contains landslides or not. However, landslides may change some parameters or measures of the structural characteristics of land-cover. The results show that the linear coefficient, modularity and area distribution are all changed after the occurence of landslides, which means the structural characteristics of the land-cover are changed.
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Pilant, A. N.; Baynes, J.; Dannenberg, M.
2012-12-01
The US EPA National Atlas for Sustainability is a web-based, easy-to-use, mapping application that allows users to view and analyze multiple ecosystem services in a specific region. The Atlas provides users with a visual method for interpreting ecosystem services and understanding how they can be conserved and enhanced for a sustainable future. The Urban Atlas component of the National Atlas will provide fine-scale information linking human health and well-being to environmental conditions such as urban heat islands, near-road pollution, resource use, access to recreation, drinking water quality and other quality of life indicators. The National Land Cover Data (NLCD) derived from 30 m scale 2006 Landsat imagery provides the land cover base for the Atlas. However, urban features and phenomena occur at finer spatial scales, so higher spatial resolution and more current LC maps are required. We used 4 band USDA NAIP imagery (1 m pixel size) and various classification approaches to produce urban land cover maps with these classes: impervious surface, grass and herbaceous, trees and forest, soil and barren, and water. Here we present the remote sensing methods used and results from four pilot cities in this effort, highlighting the pros and cons of the approach, and the benefits to sustainability and ecosystem services analysis. Example of high resolution land cover map derived from USDA NAIP aerial photo. Compare 30 m and 1 m resolution land cover maps of downtown Durham, NC.
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Land cover change mapping using MODIS time series to improve emissions inventories
López-Saldaña, Gerardo; Quaife, Tristan; Clifford, Debbie
2016-04-01
MELODIES is an FP7 funded project to develop innovative and sustainable services, based upon Open Data, for users in research, government, industry and the general public in a broad range of societal and environmental benefit areas. Understanding and quantifying land surface changes is necessary for estimating greenhouse gas and ammonia emissions, and for meeting air quality limits and targets. More sophisticated inventories methodologies for at least key emission source are needed due to policy-driven air quality directives. Quantifying land cover changes on an annual basis requires greater spatial and temporal disaggregation of input data. The main aim of this study is to develop a methodology for using Earth Observations (EO) to identify annual land surface changes that will improve emissions inventories from agriculture and land use/land use change and forestry (LULUCF) in the UK. First goal is to find the best sets of input features that describe accurately the surface dynamics. In order to identify annual and inter-annual land surface changes, a times series of surface reflectance was used to capture seasonal variability. Daily surface reflectance images from the Moderate Resolution Imaging Spectroradiometer (MODIS) at 500m resolution were used to invert a Bidirectional Reflectance Distribution Function (BRDF) model to create the seamless time series. Given the limited number of cloud-free observations, a BRDF climatology was used to constrain the model inversion and where no high-scientific quality observations were available at all, as a gap filler. The Land Cover Map 2007 (LC2007) produced by the Centre for Ecology & Hydrology (CEH) was used for training and testing purposes. A land cover product was created for 2003 to 2015 and a bayesian approach was created to identified land cover changes. We will present the results of the time series development and the first exercises when creating the land cover and land cover changes products.
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Land cover change in coastal watersheds 1996 to 2010
Nate Herold
2016-01-01
Land use and land cover play a significant role as drivers of environmental change. Information on what is changing and where those changes are occurring is essential if we are to improve our understanding of...
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Detecting and quantifying land use/land cover dynamics in Wadla ...
African Journals Online (AJOL)
A study was conducted in Wadla Delanta Massif to investigate land use/cover dynamics over the last four decades (1973-2014) using satellite images (1973 MSS, 1995 TM and 2014 ETM+). Global positioning system ... in the study area. Keywords: GIS, Image classification, Remote sensing, Supervised classification ...
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Villarreal, Miguel L.; Norman, Laura M.; Webb, Robert H.; Boyer, Diane E.; Turner, Raymond M.
2011-01-01
A significant amount of research conducted in the Sonoran Desert of North America has documented, both anecdotally and empirically, major vegetation changes over the past century due to human land use activities. However, many studies lack coincidental landscape-scale data characterizing the spatial and temporal manifestation of these changes. Vegetation changes in a binational (USA and Mexico) watershed were documented using a series of four land cover maps (1979-2009) derived from multispectral satellite imagery. Cover changes are compared to georeferenced, repeat oblique photographs dating from the late 19th century to present. Results indicate the expansion of grassland over the past 20 years following nearly a century of decline. Historical repeat photography documents early-mid 20th century mesquite invasions, but recent land cover data and rephotography demonstrate declines in xeroriparian/riparian mesquite communities in recent decades. These vegetation changes are variable over the landscape and influenced by topography and land management.
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Peters-Lidard, Christa D.
2011-01-01
Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins". LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling be enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation, who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs.LIS has also recently been demonstrated for multi-model data assimilation using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature.Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation.Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeorological modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems
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Directory of Open Access Journals (Sweden)
Lina Zhong
2014-04-01
Full Text Available In this study, statistical data on the national economic and social development, including the year-end actual area of arable land, the crop yield per unit area and 10 factors, were obtained for the period between 1980 and 2010 and used to analyze the factors driving changes in the arable land of the Loess Plateau in northern Shaanxi, China. The following areas of arable land, which represent different spatial scales, were investigated: the Baota District, the city of Yan’an, and the Northern Shaanxi region. The scale effects of the factors driving the changes to the arable land were analyzed using a canonical correlation analysis and a principal component analysis. Because it was difficult to quantify the impact of the national government policies on the arable land changes, the contributions of the national government policies to the changes in arable land were analyzed qualitatively. The primary conclusions of the study were as follows: between 1980 and 2010, the arable land area decreased. The trends of the year-end actual arable land proportion of the total area in the northern Shaanxi region and Yan’an City were broadly consistent, whereas the proportion in the Baota District had no obvious similarity with the northern Shaanxi region and Yan’an City. Remarkably different factors were shown to influence the changes in the arable land at different scales. Environmental factors exerted a greater effect for smaller scale arable land areas (the Baota District. The effect of socio-economic development was a major driving factor for the changes in the arable land area at the city and regional scales. At smaller scales, population change, urbanization and socio-economic development affected the crop yield per unit area either directly or indirectly. Socio-economic development and the modernization of agricultural technology had a greater effect on the crop yield per unit area at the large-scales. Furthermore, the qualitative analysis
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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.
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Land Use-Land Cover dynamics of Huluka watershed, Central Rift Valley, Ethiopia
Directory of Open Access Journals (Sweden)
Hagos Gebreslassie
2014-12-01
Full Text Available Land Use-Land Cover (LULC dynamic has of human kind age and is one of the phenomenons which interweave the socio economic and environmental issues in Ethiopia. Huluka watershed is one of the watersheds in Central Rift Valley of Ethiopia which drains to Lake Langano. Few decades ago the stated watershed was covered with dense acacia forest. But, nowadays like other part of Ethiopia, it is experiencing complex dynamics of LULC. The aim of this research was thus to evaluate the LULC dynamics seen in between 1973–2009. This was achieved through collecting qualitative and quantitative data using Geographic Information System (GIS and Remote Sensing (RS technique. Field observations, discussion with elders were also employed to validate results from remotely sensed data. Based on the result, eight major dynamic LULC classes were identified from the watershed. Of these LULC classes, only cultivated and open lands had shown continuous and progressive expansion mainly at the expense of grass, shrub and forest lands. The 25% and 0% of cultivated and open land of the watershed in 1973 expanded to 84% and 4% in 2009 respectively while the 29%, 18% and 22% of grass, shrub and forest land of the watershed in 1973 degraded to 3.5%, 4% and 1.5% in 2009 respectively. As a result, land units which had been used for pastoralist before 1973 were identified under mixed agricultural system after 2000. In the end, this study came with a recommendation of an intervention of concerned body to stop the rapid degradation of vegetation on the watershed.
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van Asselen, S.; Verburg, P.H.
2013-01-01
Land-use change is both a cause and consequence of many biophysical and socioeconomic changes. The CLUMondo model provides an innovative approach for global land-use change modeling to support integrated assessments. Demands for goods and services are, in the model, supplied by a variety of land
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Multisource Data Fusion Framework for Land Use/Land Cover Classification Using Machine Vision
Directory of Open Access Journals (Sweden)
Salman Qadri
2017-01-01
Full Text Available Data fusion is a powerful tool for the merging of multiple sources of information to produce a better output as compared to individual source. This study describes the data fusion of five land use/cover types, that is, bare land, fertile cultivated land, desert rangeland, green pasture, and Sutlej basin river land derived from remote sensing. A novel framework for multispectral and texture feature based data fusion is designed to identify the land use/land cover data types correctly. Multispectral data is obtained using a multispectral radiometer, while digital camera is used for image dataset. It has been observed that each image contained 229 texture features, while 30 optimized texture features data for each image has been obtained by joining together three features selection techniques, that is, Fisher, Probability of Error plus Average Correlation, and Mutual Information. This 30-optimized-texture-feature dataset is merged with five-spectral-feature dataset to build the fused dataset. A comparison is performed among texture, multispectral, and fused dataset using machine vision classifiers. It has been observed that fused dataset outperformed individually both datasets. The overall accuracy acquired using multilayer perceptron for texture data, multispectral data, and fused data was 96.67%, 97.60%, and 99.60%, respectively.
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Energy Technology Data Exchange (ETDEWEB)
Lu, Xiaoliang [The Ecosystems Center, Marine Biological Laboratory, Woods Hole MA USA; Zhou, Yuyu [Departments of Geological and Atmospheric Sciences, Iowa State University, Ames IA USA; Liu, Yaling [Pacific Northwest National Laboratory, Joint Global Change Research Institute, College Park MD USA; Le Page, Yannick [Department Tapada da Ajuda, Centro de Estudos Florestais, Instituto Superior de Agronomia, Universidade de Lisboa, Lisbon Portugal
2017-08-08
Protected areas (PAs) cover about 22% of the conterminous United States. Understanding their role on historical land use and land cover change (LULCC) and on the carbon cycle is essential to provide guidance for environmental policies. In this study, we compiled historical LULCC and PAs data to explore these interactions within the terrestrial ecosystem model (TEM). We found that intensive LULCC occurred in the conterminous United States from 1700 to 2005. More than 3 million km2 of forest, grassland and shrublands were converted into agricultural lands, which caused 10,607 Tg C release from land ecosystems to atmosphere. PAs had experienced little LULCC as they were generally established in the 20th century after most of the agricultural expansion had occurred. PAs initially acted as a carbon source due to land use legacies, but their accumulated carbon budget switched to a carbon sink in the 1960s, sequestering an estimated 1,642 Tg C over 1700–2005, or 13.4% of carbon losses in non-PAs. We also find that PAs maintain larger carbon stocks and continue sequestering carbon in recent years (2001–2005), but at a lower rate due to increased heterotrophic respiration as well as lower productivity associated to aging ecosystems. It is essential to continue efforts to maintain resilient, biodiverse ecosystems and avoid large-scale disturbances that would release large amounts of carbon in PAs.
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IRSeL-An approach to enhance continuity and accuracy of remotely sensed land cover data
Rathjens, H.; Dörnhöfer, K.; Oppelt, N.
2014-09-01
Land cover data gives the opportunity to study interactions between land cover status and environmental issues such as hydrologic processes, soil properties, or biodiversity. Land cover data often are based on classification of remote sensing data that seldom provides the requisite accuracy, spatial availability and temporal observational frequency for environmental studies. Thus, there is a high demand for accurate and spatio-temporal complete time series of land cover. In the past considerable research was undertaken to increase land cover classification accuracy, while less effort was spent on interpolation techniques. The purpose of this article is to present a space-time interpolation and revision approach for remotely sensed land cover data. The approach leverages special properties known for agricultural areas such as crop rotations or temporally static land cover classes. The newly developed IRSeL-tool (Interpolation and improvement of Remotely Sensed Land cover) corrects classification errors and interpolates missing land cover pixels. The easy-to-use tool solely requires an initial land cover data set. The IRSeL specific interpolation and revision technique, the data input requirements and data output structure are described in detail. A case study in an area around the city of Neumünster in Northern Germany from 2006 to 2012 was performed for IRSeL validation with initial land cover data sets (Landsat TM image classifications) for the years 2006, 2007, 2009, 2010 and 2011. The results of the case study showed that IRSeL performs well; including years with no classification data overall accuracy values for IRSeL interpolated pixels range from 0.63 to 0.81. IRSeL application significantly increases the accuracy of the land cover data; overall accuracy values rise 0.08 in average resulting in overall accuracy values of at least 0.86. Considering estimated reliabilities, the IRSeL tool provides a temporally and spatially completed and revised land cover
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Martin, K. L.; Emanuel, R. E.; Vose, J. M.
2016-12-01
The number of concentrated animal feeding operations (CAFOs) has increased rapidly in recent decades. Although important to food supplies, CAFOs may present significant risks to human health and environmental quality. The National land cover database (NLCD) is a publically available database of land cover whose purpose is to provide assessment of ecosystem health, facilitate nutrient modeling, land use planning, and developing land management practices. However, CAFOs do not align with any existing NLCD land cover classes. This is especially concerning due to their distinct nutrient loading characteristics, potential for other environmental impacts, and given that individual CAFOs may occupy several NLCD pixels worth of ground area. Using 2011 NLCD data, we examined the land cover classification of CAFO sites in North Carolina (USA). Federal regulations require CAFOs with a liquid waste disposal system to obtain a water quality permit. In North Carolina, there were 2679 permitted sites as of 2015, primarily in the southeastern part of the state. As poultry operations most frequently use dry waste disposal systems, they are not required to obtain a permit and thus, their locations are undocumented. For each permitted CAFO, we determined the mode of the NLCD land uses within a 50m buffer surrounding point coordinates. We found permitted CAFOS were most likely to be classified as hay/pasture (58%). An additional 13% were identified as row crops, leaving 29% as a non-agricultural land cover class, including wetlands (12%). This misclassification of CAFOs can have implications for environmental management and public policy. Scientists and land managers need access to better spatial data on the distribution of these operations to monitor the environmental impacts and identify the best landscape scale mitigation strategies. We recommend adding a new land cover class (concentrated animal operations) to the NLCD database.
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Global land cover mapping at 30 m resolution: A POK-based operational approach
Chen, Jun; Chen, Jin; Liao, Anping; Cao, Xin; Chen, Lijun; Chen, Xuehong; He, Chaoying; Han, Gang; Peng, Shu; Lu, Miao; Zhang, Weiwei; Tong, Xiaohua; Mills, Jon
2015-05-01
Global Land Cover (GLC) information is fundamental for environmental change studies, land resource management, sustainable development, and many other societal benefits. Although GLC data exists at spatial resolutions of 300 m and 1000 m, a 30 m resolution mapping approach is now a feasible option for the next generation of GLC products. Since most significant human impacts on the land system can be captured at this scale, a number of researchers are focusing on such products. This paper reports the operational approach used in such a project, which aims to deliver reliable data products. Over 10,000 Landsat-like satellite images are required to cover the entire Earth at 30 m resolution. To derive a GLC map from such a large volume of data necessitates the development of effective, efficient, economic and operational approaches. Automated approaches usually provide higher efficiency and thus more economic solutions, yet existing automated classification has been deemed ineffective because of the low classification accuracy achievable (typically below 65%) at global scale at 30 m resolution. As a result, an approach based on the integration of pixel- and object-based methods with knowledge (POK-based) has been developed. To handle the classification process of 10 land cover types, a split-and-merge strategy was employed, i.e. firstly each class identified in a prioritized sequence and then results are merged together. For the identification of each class, a robust integration of pixel-and object-based classification was developed. To improve the quality of the classification results, a knowledge-based interactive verification procedure was developed with the support of web service technology. The performance of the POK-based approach was tested using eight selected areas with differing landscapes from five different continents. An overall classification accuracy of over 80% was achieved. This indicates that the developed POK-based approach is effective and feasible
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Land-Use and Land-Cover Mapping Using a Gradable Classification Method
Directory of Open Access Journals (Sweden)
Keigo Kitada
2012-05-01
Full Text Available Conventional spectral-based classification methods have significant limitations in the digital classification of urban land-use and land-cover classes from high-resolution remotely sensed data because of the lack of consideration given to the spatial properties of images. To recognize the complex distribution of urban features in high-resolution image data, texture information consisting of a group of pixels should be considered. Lacunarity is an index used to characterize different texture appearances. It is often reported that the land-use and land-cover in urban areas can be effectively classified using the lacunarity index with high-resolution images. However, the applicability of the maximum-likelihood approach for hybrid analysis has not been reported. A more effective approach that employs the original spectral data and lacunarity index can be expected to improve the accuracy of the classification. A new classification procedure referred to as “gradable classification method” is proposed in this study. This method improves the classification accuracy in incremental steps. The proposed classification approach integrates several classification maps created from original images and lacunarity maps, which consist of lacnarity values, to create a new classification map. The results of this study confirm the suitability of the gradable classification approach, which produced a higher overall accuracy (68% and kappa coefficient (0.64 than those (65% and 0.60, respectively obtained with the maximum-likelihood approach.
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Relationship between Organic Carbon Runoff to River and Land Cover
Kim, G. S.; Lee, S. G.; Lim, C. H.; Lee, W.; Yoo, S.; Kim, S. J.; Heo, S.; Lee, W. K.
2017-12-01
Carbon is an important unit in understanding the ecosystem and energy circulation. Each ecosystem, land, water, and atmosphere, is interconnected through the exchange of energy and organic carbon. In the rivers, primary producers utilize the organic carbon from the land. Understanding the organic carbon uptake into the river is important for understanding the mechanism of river ecosystems. The main organic carbon source of the river is land. However, it is difficult to observe the amount of organic carbon runoff to the river. Therefore, an indirect method should be used to estimate the amount of organic carbon runoff to the river. The organic carbon inflow is caused by the runoff of organic carbon dissolved in water or the inflow of organic carbon particles by soil loss. Therefore, the hydrological model was used to estimate organic carbon runoff through the flow of water. The land cover correlates with soil respiration, soil loss, and so on, and the organic carbon runoff coefficient will be estimated to the river by land cover. Using the organic carbon concentration from water quality data observed at each point in the river, we estimate the amount of organic carbon released from the land. The reason is that the runoff from the watershed converges into the rivers in the watershed, the watershed simulation is conducted based on the water quality data observation point. This defines a watershed that affects organic carbon observation sites. The flow rate of each watershed is calculated by the SWAT (Soil and Water Assessment Tool), and the total organic carbon runoff is calculated by using flow rate and organic carbon concentration. This is compared with the factors related to the amount of organic carbon such as land cover, soil loss, and soil organic carbon, and spatial analysis is carried out to estimate the organic carbon runoff coefficient per land cover.
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International Nuclear Information System (INIS)
Hofmann, Lorenz; Stemmler, Irene; Lammel, Gerhard
2012-01-01
Global fate and transport of γ-HCH and DDT was studied using a global multicompartment chemistry-transport model, MPI-MCTM, with and without inclusion of land ice (in Antarctica and Greenland) or snow cover (dynamic). MPI-MCTM is based on coupled ocean and atmosphere general circulation models. After a decade of simulation 4.2% γ-HCH and 2.3% DDT are stored in land ice and snow. Neglection of land ice and snow in modelling would underestimate the total environmental residence time, τ ov , of γ-HCH and overestimate τ ov for DDT, both on the order of 1% and depending on actual compartmental distribution. Volatilisation of DDT from boreal, seasonally snow covered land is enhanced throughout the year, while volatilisation of γ-HCH is only enhanced during the snow-free season. Including land ice and snow cover in modelling matters in particular for the Arctic, where higher burdens are predicted to be stored. - Highlights: ► Land ice and snow hosts 2–4% of the global environmental burden of γ-HCH and DDT. ► Inclusion of land ice and snow cover matters for global environmental residence time. ► Including of land ice and snow cover matters in particular for the Arctic. - The inclusion of cycling in temporary snow cover and land ice in the model is found relevant for predicted POPs multicompartmental distribution and fate in the Arctic and on the global scale.
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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
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Di Vittorio, A. V.; Mao, J.; Shi, X.; Chini, L.; Hurtt, G.; Collins, W. D.
2018-01-01
Previous studies have examined land use change as a driver of global change, but the translation of land use change into land cover conversion has been largely unconstrained. Here we quantify the effects of land cover conversion uncertainty on the global carbon and climate system using the integrated Earth System Model. Our experiments use identical land use change data and vary land cover conversions to quantify associated uncertainty in carbon and climate estimates. Land cover conversion uncertainty is large, constitutes a 5 ppmv range in estimated atmospheric CO2 in 2004, and generates carbon uncertainty that is equivalent to 80% of the net effects of CO2 and climate and 124% of the effects of nitrogen deposition during 1850-2004. Additionally, land cover uncertainty generates differences in local surface temperature of over 1°C. We conclude that future studies addressing land use, carbon, and climate need to constrain and reduce land cover conversion uncertainties.
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Hasaan, Zahra
2016-07-01
Remote sensing is very useful for the production of land use and land cover statistics which can be beneficial to determine the distribution of land uses. Using remote sensing techniques to develop land use classification mapping is a convenient and detailed way to improve the selection of areas designed to agricultural, urban and/or industrial areas of a region. In Islamabad city and surrounding the land use has been changing, every day new developments (urban, industrial, commercial and agricultural) are emerging leading to decrease in vegetation cover. The purpose of this work was to develop the land use of Islamabad and its surrounding area that is an important natural resource. For this work the eCognition Developer 64 computer software was used to develop a land use classification using SPOT 5 image of year 2012. For image processing object-based classification technique was used and important land use features i.e. Vegetation cover, barren land, impervious surface, built up area and water bodies were extracted on the basis of object variation and compared the results with the CDA Master Plan. The great increase was found in built-up area and impervious surface area. On the other hand vegetation cover and barren area followed a declining trend. Accuracy assessment of classification yielded 92% accuracies of the final land cover land use maps. In addition these improved land cover/land use maps which are produced by remote sensing technique of class definition, meet the growing need of legend standardization.
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Cohen, Justin M; Ernst, Kacey C; Lindblade, Kim A; Vulule, John M; John, Chandy C; Wilson, Mark L
2010-11-16
Identification of high-risk malaria foci can help enhance surveillance or control activities in regions where they are most needed. Associations between malaria risk and land-use/land-cover are well-recognized, but these environmental characteristics are closely interrelated with the land's topography (e.g., hills, valleys, elevation), which also influences malaria risk strongly. Parsing the individual contributions of land-cover/land-use variables to malaria risk requires examining these associations in the context of their topographic landscape. This study examined whether environmental factors like land-cover, land-use, and urban density improved malaria risk prediction based solely on the topographically-determined context, as measured by the topographic wetness index. The topographic wetness index, an estimate of predicted water accumulation in a defined area, was generated from a digital terrain model of the landscape surrounding households in two neighbouring western Kenyan highland communities. Variables determined to best encompass the variance in this topographic wetness surface were calculated at a household level. Land-cover/land-use information was extracted from a high-resolution satellite image using an object-based classification method. Topographic and land-cover variables were used individually and in combination to predict household-level malaria in the communities through an iterative split-sample model fitting and testing procedure. Models with only topographic variables were compared to those with additional predictive factors related to land-cover/land-use to investigate whether these environmental factors improved prediction of malaria based on the shape of the land alone. Variables related to topographic wetness proved most useful in predicting the households of individuals contracting malaria in this region of rugged terrain. Other variables related to human modification of the environment also demonstrated clear associations with
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Vulule John M
2010-11-01
Full Text Available Abstract Background Identification of high-risk malaria foci can help enhance surveillance or control activities in regions where they are most needed. Associations between malaria risk and land-use/land-cover are well-recognized, but these environmental characteristics are closely interrelated with the land's topography (e.g., hills, valleys, elevation, which also influences malaria risk strongly. Parsing the individual contributions of land-cover/land-use variables to malaria risk requires examining these associations in the context of their topographic landscape. This study examined whether environmental factors like land-cover, land-use, and urban density improved malaria risk prediction based solely on the topographically-determined context, as measured by the topographic wetness index. Methods The topographic wetness index, an estimate of predicted water accumulation in a defined area, was generated from a digital terrain model of the landscape surrounding households in two neighbouring western Kenyan highland communities. Variables determined to best encompass the variance in this topographic wetness surface were calculated at a household level. Land-cover/land-use information was extracted from a high-resolution satellite image using an object-based classification method. Topographic and land-cover variables were used individually and in combination to predict household-level malaria in the communities through an iterative split-sample model fitting and testing procedure. Models with only topographic variables were compared to those with additional predictive factors related to land-cover/land-use to investigate whether these environmental factors improved prediction of malaria based on the shape of the land alone. Results Variables related to topographic wetness proved most useful in predicting the households of individuals contracting malaria in this region of rugged terrain. Other variables related to human modification of the
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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.
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Land use and land cover dynamics on the campus of Federal University of Lavras from 1964 to 2009
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Elizabeth Ferreira
2013-03-01
Full Text Available This study identified, quantified and analyzed changes in land use and cover on the campus of Federal University of Lavras campus, located in Lavras city (Minas Gerais State. The 2009 QuickBird satellite imagery and 1985, 1979, 1971, 1964 vertical aerial photographs were used to produce a set of land use and land cover maps. The work started with the orthorectification of the QuickBird satellite imagery and vertical aerial photographs. The identification and definition of land cover and land use classes were obtained from field surveys in 2009. First, the land cover and land use maps were made from that information. Finally, the quantification and analysis of changes were performed at the imagery time range. The results showed that in 2009 the "urbanized area class" of the campus reached 65.79 ha and that the most significant increase of this class occurred between the years 1964 (6.24 ha and 1971 (24.4 ha. The smallest area of "forest land class" found on the campus was 38.38 ha in 1971, and from 1979 on this situation has been improved reaching 113.18 ha of "forest land class" in 2009. For the "water class" there was not any dam constructed yet in the campus before 1971. Most of the campus area, previously used for "agricultural land class" had a significant reduction within this category, from 384.19 ha in 1964 to 271.16 ha in 2009.
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Soil chemical and physical properties that differentiate urban land-use and cover types
R.V. Pouyat; I.D. Yesilonis; J. Russell-Anelli; N.K. Neerchal
2007-01-01
We investigated the effects of land use and cover and surface geology on soil properties in Baltimore, MD, with the objectives to: (i) measure the physical and chemical properties of surface soils (0?10 cm) by land use and cover; and (ii) ascertain whether land use and cover explain differences in these properties relative to surface geology. Mean and median values of...
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Litt, Guy Finley
As the Panama Canal Authority faces sensitivity to water shortages, managing water resources becomes crucial for the global shipping industry's security. These studies address knowledge gaps in tropical water resources to aid hydrological model development and validation. Field-based hydrological investigations in the Agua Salud Project within the Panama Canal Watershed employed multiple tools across a variety of land covers to investigate hydrological processes. Geochemical tracers informed where storm runoff in a stream comes from and identified electrical conductivity (EC) as an economical, high sample frequency tracer during small storms. EC-based hydrograph separation coupled with hydrograph recession rate analyses identified shallow and deep groundwater storage-discharge relationships that varied by season and land cover. A series of plot-scale electrical resistivity imaging geophysical experiments coupled with rainfall simulation characterized subsurface flow pathway behavior and quantified respectively increasing infiltration rates across pasture, 10 year old secondary succession forest, teak (tectona grandis), and 30 year old secondary succession forest land covers. Additional soil water, groundwater, and geochemical studies informed conceptual model development in subsurface flow pathways and groundwater, and identified future research needs.
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Generation of multi annual land use and crop rotation data for regional agro-ecosystem modeling
Waldhoff, G.; Lussem, U.; Sulis, M.; Bareth, G.
2017-12-01
For agro-ecosystem modeling on a regional scale with systems like the Community Land Model (CLM), detailed crop type and crop rotation information on the parcel-level is of key importance. Only with this, accurate assessments of the fluxes associated with the succession of crops and their management are possible. However, sophisticated agro-ecosystem modeling for large regions is only feasible at grid resolutions, which are much coarser than the spatial resolution of modern land use maps (usually ca. 30 m). As a result, much of the original information content of the maps has to be dismissed during resampling. Here we present our mapping approach for the Rur catchment (located in the west of Germany), which was developed to address these demands and issues. We integrated remote sensing and geographic information system (GIS) methods to classify multi temporal images of (e.g.) Landsat, RapidEye and Sentinel-2 to generate annual crop maps for the years 2008-2017 at 15 m spatial resolution (accuracy always ca. 90 %). A key aspect of our method is the consideration of crop phenology for the data selection and the analysis. In a GIS, the annul crop maps were integrated to a crop sequence dataset from which the major crop rotations were derived (based on the 10-years). To retain the multi annual crop succession and crop area information at coarser grid resolutions, cell-based land use fractions, including other land use classes were calculated for each year and for various target cell sizes (1-32 arc seconds). The resulting datasets contain the contribution (in percent) of every land use class to each cell. Our results show that parcels with the major crop types can be differentiated with a high accuracy and on an annual basis. The analysis of the crop sequence data revealed a very large number of different crop rotations, but only relatively few crop rotations cover larger areas. This strong diversity emphasizes the importance of information on crop rotations to reduce
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Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh
2017-09-01
Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates
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International Nuclear Information System (INIS)
Faid, A.M.; Hinz, E.A.; Montgomery, H.
2003-01-01
The impact of land cover/land use on groundwater can be critical. Land cover / land use maps give an early warning for planners and developers to protect groundwater resources from depletion and preserve its sustain ability. These land cover / land use maps can be used for the planning of groundwater development to prevent the deterioration of the aquifer. The Research Institute for Groundwater of Egypt (RIGW) has carried out hydrogeological studies in 1990 to evaluate the potentiality of groundwater in Luxor area in southern Egypt close to the Nile valley. The region is characterized by a rapid and continuous increase in land reclamation and development on the fringes which surround the already heavily cultivated land within the Nile valley. This presented a need for continuous monitoring and information updating over a vast region in a short time and at a reasonable cost. This study illustrates how remote sensing techniques can be effectively used for monitoring changes in land cover / land use in an effort to aid groundwater management. Landsat Thematic Mapper (TM) data collected in 1984 and 2000 were processed and analyzed over the study area to produce land cover/land use maps. The Normalized Difference Vegetation Index (NDVI) technique is used for Landsat TM images of to quantify areas which are covered by vegetation. Results indicated significant increase in cultivated areas. Remote sensing results are compared with iso-piezo metric maps and iso-salinity maps that were produced in 1984 and 2000. Comparison of these maps indicates groundwater depletion and salinity increase from 1984 to 2000. We relate this to the increase of the area being cultivated
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NSGIC State | GIS Inventory — LAND_COVER_PRESETTLEMENT_IDNR_IN.SHP is a polygon shapefile showing generalized presettlement vegetation types of Indiana, circa 1820. The work was based on original...
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Conversion of land use and cover in northwest Amazon (Brazil
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Carlos Antonio da Silva Junior
2014-09-01
Full Text Available The increasing use of natural resources in a disorderly way has been demanding constant monitoring and ecological-economic zoning. The knowledge on land use and cover allows that measures that guarantee the preservation, maintenance of the environment and space management be appropriate to the reality, since through these factors it is possible to follow the probable environmental impacts and the socioeconomic development of a place in several contexts. The Geographical Information System (GIS and remote sensing techniques have been applied to land use and land cover mapping. This study aimed to analyze the conversion of land use from different perspectives, concerning geoprocessing techniques, in the southeastern of Roraima State, Brazil, in two distinct periods. In order to verify the land use and cover, two analyses were conducted, using the Spring and TerraView softwares. Great part of the cultivated areas was converted into capoeira, what probably denotes an ending of profitable agriculture, as well as its abandonment caused by the nutritional deficiency of the soil, that became inappropriate for cultivation in the subsequent years. A fuzzy logic would possibly fit well to the types of data analyzed, because the attribute query is overly complex.
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Yuniarti, Fieni; K, Dyah Indriana; Winarno, Dwi Joko
2013-01-01
Land use and land cover change in a watershed might drive some impacts, such as high amounts of discharge fluctuations. Way Kuala Garuntang Watersheed is one of watershed in Bandar Lampung that has changed significantly. This study analyzed land use and land cover change to determine how much its influence on discharce fluctuations based on Geographics Information System. The method used in this study comprised of hidrology, spatial and sensitivity analysis. Hidrology analysis based on daily ...
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A stochastic Forest Fire Model for future land cover scenarios assessment
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M. D'Andrea
2010-10-01
Full Text Available Land cover is affected by many factors including economic development, climate and natural disturbances such as wildfires. The ability to evaluate how fire regimes may alter future vegetation, and how future vegetation may alter fire regimes, would assist forest managers in planning management actions to be carried out in the face of anticipated socio-economic and climatic change. In this paper, we present a method for calibrating a cellular automata wildfire regime simulation model with actual data on land cover and wildfire size-frequency. The method is based on the observation that many forest fire regimes, in different forest types and regions, exhibit power law frequency-area distributions. The standard Drossel-Schwabl cellular automata Forest Fire Model (DS-FFM produces simulations which reproduce this observed pattern. However, the standard model is simplistic in that it considers land cover to be binary – each cell either contains a tree or it is empty – and the model overestimates the frequency of large fires relative to actual landscapes. Our new model, the Modified Forest Fire Model (MFFM, addresses this limitation by incorporating information on actual land use and differentiating among various types of flammable vegetation. The MFFM simulation model was tested on forest types with Mediterranean and sub-tropical fire regimes. The results showed that the MFFM was able to reproduce structural fire regime parameters for these two regions. Further, the model was used to forecast future land cover. Future research will extend this model to refine the forecasts of future land cover and fire regime scenarios under climate, land use and socio-economic change.
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LBA-ECO LC-01 Landsat TM Land Use/Land Cover, Northern Ecuadorian Amazon: 1986-1999
National Aeronautics and Space Administration — ABSTRACT: This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes:...
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LBA-ECO LC-01 Landsat TM Land Use/Land Cover, Northern Ecuadorian Amazon: 1986-1999
National Aeronautics and Space Administration — This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes: Forest,...
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Land Cover as a Framework For Assessing the Risk of Water Pollution
James D. Wickham; Kurt H. Riitters; Robert V. O' Neill; Kenneth H. Reckhow; Timothy G. Wade; K. Bruce Jones
2000-01-01
A survey of numerous field studies shows that nitrogen and phosphorous export coefficients are significantly different across forest, agriculture, and urban land-cover types. We used simulations to estimate the land-cover composition at which there was a significant risk of nutrient loads representative of watersheds without forest cover. The results suggest that at...
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Mukesh Singh Boori
2015-06-01
Full Text Available The Jeseníky Mountains tourism in Czech Republic is unique for its floristic richness. This is caused mainly by the altitude division and polymorphism of the landscape, climate and soil structure. This study assesses the impacts of tourism on the land cover in the Jeseníky Mountain region by comparing multi-temporal Landsat imageries (1991, 2001 and 2013 to describe the rate and extent of land-cover changes. This was achieved through spectral classification of different land cover classes and by assessing the change in forest; settlements; pasture and agriculture in relation to increasing distances (5, 10 and 15 km from three tourism sites with the help of ArcGIS software. The results indicate that the area was deforested (11.13% from 1991 to 2001 than experienced forest regrowth (6.71% from 2001 to 2013. In the first decade pasture and agriculture areas increased and then in next decade decreased. The influence of tourism facilities on land cover is also variable. Around each of the tourism site sampled, there was a general trend of forest removal decreasing as the distance from each village increased, which indicates tourism does have a negative impact on forests. However there was an opposite trend from 2001 to 2013 that indicates conservation area. The interplay among global (tourism, climate, regional (national policies, large-river management and local (construction and agriculture, energy and water sources to support the tourism industry factors drives a distinctive but complex pattern of land-use and land-cover disturbance.
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S. T. Seydi
2015-12-01
Full Text Available The Earth has always been under the influence of population growth and human activities. This process causes the changes in land use. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes. Satellite remote sensing has several advantages for monitoring land use/cover resources, especially for large geographic areas. Change detection and attribution of cultivation area over time present additional challenges for correctly analyzing remote sensing imagery. In this regards, for better identifying change in multi temporal images we use hyperspectral images. Hyperspectral images due to high spectral resolution created special placed in many of field. Nevertheless, selecting suitable and adequate features/bands from this data is crucial for any analysis and especially for the change detection algorithms. This research aims to automatically feature selection for detect land use changes are introduced. In this study, the optimal band images using hyperspectral sensor using Hyperion hyperspectral images by using genetic algorithms and Ratio bands, we select the optimal band. In addition, the results reveal the superiority of the implemented method to extract change map with overall accuracy by a margin of nearly 79% using multi temporal hyperspectral imagery.
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G. M. Li
2018-04-01
Full Text Available According to the function, land space types are divided into key development areas, restricted development areas and forbidden development areas in Sichuan Province. This paper monitors and analyses the changes of land cover in different typical functional areas from 2010 to 2017, which based on ZY-3 high-score images data and combined with statistical yearbook and thematic data of Sichuan Province. The results show that: The land cover types of typical key development zones are mainly composed of cultivated land, forest land, garden land, and housing construction land, which accounts for the total area of land cover 87 %. The land cover types of typical restricted development zone mainly consists of forest land and grassland, which occupy 97.71 % of the total area of the surface coverage. The land cover types of the typical prohibition development zone mainly consist of forest land, grassland, desert and bared earth, which accounts for the total area of land cover 99.31 %.
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Li, G. M.; Li, S.; Ying, G. W.; Wu, X. P.
2018-04-01
According to the function, land space types are divided into key development areas, restricted development areas and forbidden development areas in Sichuan Province. This paper monitors and analyses the changes of land cover in different typical functional areas from 2010 to 2017, which based on ZY-3 high-score images data and combined with statistical yearbook and thematic data of Sichuan Province. The results show that: The land cover types of typical key development zones are mainly composed of cultivated land, forest land, garden land, and housing construction land, which accounts for the total area of land cover 87 %. The land cover types of typical restricted development zone mainly consists of forest land and grassland, which occupy 97.71 % of the total area of the surface coverage. The land cover types of the typical prohibition development zone mainly consist of forest land, grassland, desert and bared earth, which accounts for the total area of land cover 99.31 %.
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Assessing the sensitivity of avian species abundance to land cover and climate
LeBrun, Jaymi J.; Thogmartin, Wayne E.; Thompson, Frank R.; Dijak, William D.; Millspaugh, Joshua J.
2016-01-01
Climate projections for the Midwestern United States predict southerly climates to shift northward. These shifts in climate could alter distributions of species across North America through changes in climate (i.e., temperature and precipitation), or through climate-induced changes on land cover. Our objective was to determine the relative impacts of land cover and climate on the abundance of five bird species in the Central United States that have habitat requirements ranging from grassland and shrubland to forest. We substituted space for time to examine potential impacts of a changing climate by assessing climate and land cover relationships over a broad latitudinal gradient. We found positive and negative relationships of climate and land cover factors with avian abundances. Habitat variables drove patterns of abundance in migratory and resident species, although climate was also influential in predicting abundance for some species occupying more open habitat (i.e., prairie warbler, blue-winged warbler, and northern bobwhite). Abundance of northern bobwhite increased with winter temperature and was the species exhibiting the most significant effect of climate. Models for birds primarily occupying early successional habitats performed better with a combination of habitat and climate variables whereas models of species found in contiguous forest performed best with land cover alone. These varied species-specific responses present unique challenges to land managers trying to balance species conservation over a variety of land covers. Management activities focused on increasing forest cover may play a role in mitigating effects of future climate by providing habitat refugia to species vulnerable to projected changes. Conservation efforts would be best served focusing on areas with high species abundances and an array of habitats. Future work managing forests for resilience and resistance to climate change could benefit species already susceptible to climate impacts.
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Investigating the Effects of Land Cover Change on the Hydrology of the Mississippi River Basin
Twine, T. E.; Coe, M. T.; Lenters, J. D.; Kucharik, C. J.; Donner, S.; Foley, J. A.
2001-12-01
Humans have greatly altered the Earth's landscape since the beginning of sedentary agriculture. Through the conversion of forests and grasslands to croplands and pasture, human land use activities have changed biogeochemical cycles including the water cycle. Using IBIS, a global land surface model with 0.5-degree resolution (Foley et al., 1996; Kucharik et al., 2000), and HYDRA, a runoff-routing algorithm with 5-minute resolution (Coe, 2000), we have studied how land cover change may affect the hydrology of the Mississippi River Basin. The IBIS model describes physical, physiological, and ecological processes occurring in vegetative canopies and soils. Through forcing from climate data and vegetation and soil properties, IBIS simulates energy, water, and biogeochemical cycles at small time-steps (30-60 minutes). Lenters et al. (2000) have validated the IBIS-modeled water budget over the Mississippi River Basin at several scales and HYDRA-modeled discharge has been compared favorably to United States Geological Survey stream gauge data (Donner et al., 2001). This work extends those studies through use of an improved version of IBIS. The IBIS model has been calibrated for use over the continental United States through an improved phenology routine and the inclusion of corn and soybeans as land cover types. Results from a comparison of a control run of natural vegetation with experimental runs of corn and soybean cover will be shown.
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Interrelationships between soil cover and plant cover depending on land use
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Tiina Köster
2013-05-01
Full Text Available Interrelationships between soil cover and plant cover of normally developed (or postlithogenic mineral soils are analysed on the basis of four sampling soil groups. The four-link pedo-ecological sequence of analysed soils, rendzinas → brown soils → pseudopodzolic soils → gley-podzols, forms a representative cross section in relation to the normal mineral soils of Estonia. All groups differ substantially from each other in terms of soil properties (calcareousness, acidity, nutrition conditions, profile fabric and humus cover. The primary tasks of the research were (1 to elucidate the main pedo-ecological characteristics of the four soil groups and their suitability for plant cover, (2 to evaluate comparatively soils in terms of productivity, sustainability, biodiversity and environmental protection ability and (3 to analyse possibilities for ecologically sound matching of soil cover with suitable plant cover. On the basis of the same material, the influence of land-use change on humus cover (epipedon fabric, properties of the entire soil cover and soil–plant interrelationship were also analysed. An ecosystem approach enables us to observe particularities caused by specific properties of a soil type (species, variety in biological turnover and in the formation of biodiversity.
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M. Aquilino
2014-01-01
The historical archive of LANDSAT imagery dating back to the launch of ERTS in 1972 provides a comprehensive and permanent data source for tracking change on the planet‟s land surface. In this study case the imagery acquisition dates of 1987, 2002 and 2011 were selected to cover a time trend of 24 years. Land cover categories were based on classes outlined by the Curve Number method with the aim of characterizing land use according to the level of surface imperviousness. After comparing two land use classification methods, i.e. Maximum Likelihood Classifier (MLC and Multi-Layer Perceptron (MLP neural network, the Artificial Neural Networks (ANN approach was found the best reliable and efficient method in the absence of ground reference data. The ANN approach has a distinct advantage over statistical classification methods in that it is non-parametric and requires little or no a priori knowledge on the distribution model of input data. The results quantify land cover change patterns in the river basin area under study and demonstrate the potential of multitemporal LANDSAT data to provide an accurate and cost-effective means to map and analyse land cover changes over time that can be used as input in land management and policy decision-making.
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Peters-Lidard, Christa D.; Kumar, Sujay V.; Santanello, Joseph A., Jr.; Reichle, Rolf H.
2009-01-01
NOAA's National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center (EMC) for their land data assimilation systems to support weather and climate modeling. LIS not only consolidates the capabilities of these two systems, but also enables a much larger variety of configurations with respect to horizontal spatial resolution, input datasets and choice of land surface model through "plugins,". As described in Kumar et al., 2007, and demonstrated in Case et al., 2008, and Santanello et al., 2009, LIS has been coupled to the Weather Research and Forecasting (WRF) model to support studies of land-atmosphere coupling the enabling ensembles of land surface states to be tested against multiple representations of the atmospheric boundary layer. LIS has also been demonstrated for parameter estimation as described in Peters-Lidard et al. (2008) and Santanello et al. (2007), who showed that the use of sequential remotely sensed soil moisture products can be used to derive soil hydraulic and texture properties given a sufficient dynamic range in the soil moisture retrievals and accurate precipitation inputs. LIS has also recently been demonstrated for multi-model data assimilation (Kumar et al., 2008) using an Ensemble Kalman Filter for sequential assimilation of soil moisture, snow, and temperature. Ongoing work has demonstrated the value of bias correction as part of the filter, and also that of joint calibration and assimilation. Examples and case studies demonstrating the capabilities and impacts of LIS for hydrometeoroogical modeling, assimilation and parameter estimation will be presented as advancements towards the next generation of integrated observation and modeling systems.
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SPOT-Based Sub-Field Level Monitoring of Vegetation Cover Dynamics: A Case of Irrigated Croplands
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Olena Dubovyk
2015-05-01
Full Text Available Acquiring multi-temporal spatial information on vegetation condition at scales appropriate for site-specific agricultural management is often complicated by the need for meticulous field measurements. Understanding spatial/temporal crop cover heterogeneity within irrigated croplands may support sustainable land use, specifically in areas affected by land degradation due to secondary soil salinization. This study demonstrates the use of multi-temporal, high spatial resolution (10 m SPOT-4/5 image data in an integrated change vector analysis and spectral mixture analysis (CVA-SMA procedure. This procedure was implemented with the principal objective of mapping sub-field vegetation cover dynamics in irrigated lowland areas within the lowerlands of the Amu Darya River. CVA intensity and direction were calculated separately for the periods of 1998–2006 and 2006–2010. Cumulative change intensity and the overall directional trend were also derived for the entire observation period of 1998–2010. Results show that most of the vector changes were observed between 1998 and 2006; persistent conditions were seen within the study region during the 2006–2010 period. A decreasing vegetation cover trend was identified within 38% of arable land. Areas of decreasing vegetation cover were located principally in the irrigation system periphery where deficient water supply and low soil quality lead to substandard crop development. During the 2006–2010 timeframe, degraded crop cover conditions persisted in 37% of arable land. Vegetation cover increased in 25% of the arable land where irrigation water supply was adequate. This high sub-field crop performance spatial heterogeneity clearly indicates that current land management practices are inefficient. Such information can provide the basis for implementing and adapting irrigation applications and salt leaching techniques to site-specific conditions and thereby make a significant contribution to sustainable
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Directory of Open Access Journals (Sweden)
André Mora
2017-11-01
Full Text Available This article discusses how computational intelligence techniques are applied to fuse spectral images into a higher level image of land cover distribution for remote sensing, specifically for satellite image classification. We compare a fuzzy-inference method with two other computational intelligence methods, decision trees and neural networks, using a case study of land cover classification from satellite images. Further, an unsupervised approach based on k-means clustering has been also taken into consideration for comparison. The fuzzy-inference method includes training the classifier with a fuzzy-fusion technique and then performing land cover classification using reinforcement aggregation operators. To assess the robustness of the four methods, a comparative study including three years of land cover maps for the district of Mandimba, Niassa province, Mozambique, was undertaken. Our results show that the fuzzy-fusion method performs similarly to decision trees, achieving reliable classifications; neural networks suffer from overfitting; while k-means clustering constitutes a promising technique to identify land cover types from unknown areas.
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Aldrich, Stephen P.; Walker, Robert T.; Arima, Eugenio Y.; Caldas, Marcellus M.; Browder, John O.; Perz, Stephen
2006-01-01
Tropical deforestation is a significant driver of global environmental change, given its impacts on the carbon cycle and biodiversity. Loss of the Amazon forest, the focus of this article, is of particular concern because of the size and the rapid rate at which the forest is being converted to agricultural use. In this article, we identify what has been the most important driver of deforestation in a specific colonization frontier in the Brazilian Amazon. To this end, we consider (1) the land-use dynamics of smallholder households, (2) the formation of pasture by large-scale ranchers, and (3) structural processes of land aggregation by ranchers. Much has been written about relations between smallholders and ranchers in the Brazilian Amazon, particularly those involving conflict over land, and this article explicates the implications of such social processes for land cover. Toward this end, we draw on panel data (1996-2002) and satellite imagery (1986-1999) to show the deforestation that is attributable to small- and largeholders, and the deforestation that is attributable to aggregations of property arising from a process that we refer to as frontier stratification. Evidently, most of the recent deforestation in the study area has resulted from the household processes of smallholders, not from conversions to pasture pursuant to the appropriations of smallholders' property by well-capitalized ranchers or speculators.
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Land Cover Change Detection using Neural Network and Grid Cells Techniques
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
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International Nuclear Information System (INIS)
Chen, Liang; Dirmeyer, Paul A
2016-01-01
To assess the biogeophysical impacts of land cover/land use change (LCLUC) on surface temperature, two observation-based metrics and their applicability in climate modeling were explored in this study. Both metrics were developed based on the surface energy balance, and provided insight into the contribution of different aspects of land surface change (such as albedo, surface roughness, net radiation and surface heat fluxes) to changing climate. A revision of the first metric, the intrinsic biophysical mechanism, can be used to distinguish the direct and indirect effects of LCLUC on surface temperature. The other, a decomposed temperature metric, gives a straightforward depiction of separate contributions of all components of the surface energy balance. These two metrics well capture observed and model simulated surface temperature changes in response to LCLUC. Results from paired FLUXNET sites and land surface model sensitivity experiments indicate that surface roughness effects usually dominate the direct biogeophysical feedback of LCLUC, while other effects play a secondary role. However, coupled climate model experiments show that these direct effects can be attenuated by large scale atmospheric changes (indirect feedbacks). When applied to real-time transient LCLUC experiments, the metrics also demonstrate usefulness for assessing the performance of climate models and quantifying land–atmosphere interactions in response to LCLUC. (letter)
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Long-term effects of climate and land cover change on freshwater provision in the tropical Andes
Molina, A.; Vanacker, V.; Brisson, E.; Mora, D.; Balthazar, V.
2015-06-01
Andean headwater catchments play a pivotal role to supply fresh water for downstream water users. However, few long-term studies exist on the relative importance of climate change and direct anthropogenic perturbations on flow regimes. In this paper, we assess multi-decadal change in freshwater provision based on long time series (1974-2008) of hydrometeorological data and land cover reconstructions for a 282 km2 catchment located in the tropical Andes. Three main land cover change trajectories can be distinguished: (1) rapid decline of native vegetation in montane forest and páramo ecosystems in ~1/5 or 20% of the catchment area, (2) expansion of agricultural land by 14% of the catchment area, (3) afforestation of 12% of native páramo grasslands with exotic tree species in recent years. Given the strong temporal variability of precipitation and streamflow data related to El Niño-Southern Oscillation, we use empirical mode decomposition techniques to detrend the time series. The long-term increasing trend in rainfall is remarkably different from the observed changes in streamflow that exhibit a decreasing trend. Hence, observed changes in streamflow are not the result of long-term climate change but very likely result from direct anthropogenic disturbances after land cover change. Partial water budgets for montane cloud forest and páramo ecosystems suggest that the strongest changes in evaporative water losses are observed in páramo ecosystems, where progressive colonization and afforestation of high alpine grasslands leads to a strong increase in transpiration losses.
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Highlighting continued uncertainty in global land cover maps for the user community
International Nuclear Information System (INIS)
Fritz, Steffen; See, Linda; McCallum, Ian; Schill, Christian; Obersteiner, Michael; Van der Velde, Marijn; Boettcher, Hannes; Havlík, Petr; Achard, Frédéric
2011-01-01
In the last 10 years a number of new global datasets have been created and new, more sophisticated algorithms have been designed to classify land cover. GlobCover and MODIS v.5 are the most recent global land cover products available, where GlobCover (300 m) has the finest spatial resolution of other comparable products such as MODIS v.5 (500 m) and GLC-2000 (1 km). This letter shows that the thematic accuracy in the cropland domain has decreased when comparing these two latest products. This disagreement is also evident spatially when examining maps of cropland and forest disagreement between GLC-2000, MODIS and GlobCover. The analysis highlights the continued uncertainty surrounding these products, with a combined forest and cropland disagreement of 893 Mha (GlobCover versus MODIS v.5). This letter suggests that data sharing efforts and the provision of more in situ data for training, calibration and validation are very important conditions for improving future global land cover products.
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Impact of land cover and population density on land surface temperature: case study in Wuhan, China
Li, Lin; Tan, Yongbin; Ying, Shen; Yu, Zhonghai; Li, Zhen; Lan, Honghao
2014-01-01
With the rapid development of urbanization, the standard of living has improved, but changes to the city thermal environment have become more serious. Population urbanization is a driving force of residential expansion, which predominantly influences the land surface temperature (LST). We obtained the land covers and LST maps of Wuhan from Landsat-5 images in 2000, 2002, 2005, and 2009, and discussed the distribution of land use/cover change and LST variation, and we analyzed the correlation between population distribution and LST values in residential regions. The results indicated massive variation of land cover types, which was shown as a reduction in cultivatable land and the expansion of building regions. High-LST regions concentrated on the residential and industrial areas with low vegetation coverage. In the residential region, the population density (PD) had effects on the LST values. Although the area or variation of residential regions was close, lower PD was associated with lower mean LST or LST variation. Thus, decreasing the high-LST regions concentration by reducing the PD may alleviate the urban heat island effect on the residential area. Taken together, these results can provide supports for urban planning projects and studies on city ecological environments.
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A Multi-Scalar Approach to Theorizing Socio-Ecological Dynamics of Urban Residential Landscapes
Directory of Open Access Journals (Sweden)
Rinku Roy Chowdhury
2011-01-01
Full Text Available Urban residential expansion increasingly drives land use, land cover and ecological changes worldwide, yet social science theories explaining such change remain under-developed. Existing theories often focus on processes occurring at one scale, while ignoring other scales. Emerging evidence from four linked U.S. research sites suggests it is essential to examine processes at multiple scales simultaneously when explaining the evolution of urban residential landscapes. Additionally, focusing on urbanization dynamics across multiple sites with a shared research design may yield fruitful comparative insights. The following processes and social-hierarchical scales significantly influence the spatial configurations of residential landscapes: household-level characteristics and environmental attitudes; formal and informal institutions at the neighborhood scale; and municipal-scale land-use governance. While adopting a multi-scale and multi-site approach produces research challenges, doing so is critical to advancing understanding of coupled socio-ecological systems and associated vulnerabilities in a dynamic and environmentally important setting: residential landscapes.
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Calvin, K. V.; Wise, M.; Kyle, P.; Janetos, A. C.; Zhou, Y.
2012-12-01
Integrated Assessment Models (IAMs) are often used as science-based decision-support tools for evaluating the consequences of climate and energy policies, and their use in this framework is likely to increase in the future. However, quantitative evaluation of these models has been somewhat limited for a variety of reasons, including data availability, data quality, and the inherent challenges in projections of societal values and decision-making. In this analysis, we identify and confront methodological challenges involved in evaluating the agriculture and land use component of the Global Change Assessment Model (GCAM). GCAM is a global integrated assessment model, linking submodules of the regionally disaggregated global economy, energy system, agriculture and land-use, terrestrial carbon cycle, oceans and climate. GCAM simulates supply, demand, and prices for energy and agricultural goods from 2005 to 2100 in 5-year increments. In each time period, the model computes the allocation of land across a variety of land cover types in 151 different regions, assuming that farmers maximize profits and that food demand is relatively inelastic. GCAM then calculates both emissions from land-use practices, and long-term changes in carbon stocks in different land uses, thus providing simulation information that can be compared to observed historical data. In this work, we compare GCAM results, both in recent historic and future time periods, to historical data sets. We focus on land use, land cover, land-use change emissions, and albedo.
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Land Use Land Cover Change in the fringe of eThekwini ...
African Journals Online (AJOL)
Concerns on urban environmental quality, increasing knowledge on impacts of climate change and pursuit for sustainable development have increased the need for past, current and future knowledge on the transformation of remnant urban fringe green ecosystems. Using land-cover change modeler and a Markov chain ...
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O'Donnell, Michael S.; Aldridge, Cameron L.; Doherty, Kevin E.; Fedy, Bradley C.
2015-01-01
With rapidly changing landscape conditions within Wyoming and the potential effects of landscape changes on sage-grouse habitat, land managers and conservation planners, among others, need procedures to assess the location and juxtaposition of important habitats, land-cover, and land-use patterns to balance wildlife requirements with multiple human land uses. Biologists frequently develop habitat-selection studies to identify prioritization efforts for species of conservation concern to increase understanding and help guide habitat-conservation efforts. Recently, the authors undertook a large-scale collaborative effort that developed habitat-selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes in Wyoming, USA and for multiple life-stages (nesting, late brood-rearing, and winter). We developed these habitat models using resource selection functions, based upon sage-grouse telemetry data collected for localized studies and within each life-stage. The models allowed us to characterize and spatially predict seasonal sage-grouse habitat use in Wyoming. Due to the quantity of models, the diversity of model predictors (in the form of geographic information system data) produced by analyses, and the variety of potential applications for these data, we present here a resource that complements our published modeling effort, which will further support land managers.
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Combining NLCD and MODIS to create a land cover-albedo database for the continental United States
Wickham, J.; Barnes, Christopher A.; Nash, M.S.; Wade, T.G.
2015-01-01
Land surface albedo is an essential climate variable that is tightly linked to land cover, such that specific land cover classes (e.g., deciduous broadleaf forest, cropland) have characteristic albedos. Despite the normative of land-cover class specific albedos, there is considerable variability in albedo within a land cover class. The National Land Cover Database (NLCD) and the Moderate Resolution Imaging Spectroradiometer (MODIS) albedo product were combined to produce a long-term (14 years) integrated land cover-albedo database for the continental United States that can be used to examine the temporal behavior of albedo as a function of land cover. The integration identifies areas of homogeneous land cover at the nominal spatial resolution of the MODIS (MCD43A) albedo product (500 m × 500 m) from the NLCD product (30 m × 30 m), and provides an albedo data record per 500 m × 500 m pixel for 14 of the 16 NLCD land cover classes. Individual homogeneous land cover pixels have up to 605 albedo observations, and 75% of the pixels have at least 319 MODIS albedo observations (≥ 50% of the maximum possible number of observations) for the study period (2000–2013). We demonstrated the utility of the database by conducting a multivariate analysis of variance of albedo for each NLCD land cover class, showing that locational (pixel-to-pixel) and inter-annual variability were significant factors in addition to expected seasonal (intra-annual) and geographic (latitudinal) effects.
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Khalifa, Muhammad; Elagib, Nadir Ahmed; Ribbe, Lars; Schneider, Karl
2018-05-15
The impact of climate variability on the Net Primary Productivity (NPP) of different land cover types and the reaction of NPP to drought conditions are still unclear, especially in Sub-Saharan Africa. This research utilizes public-domain data for the period 2000 through 2013 to analyze these aspects for several land cover types in Sudan and Ethiopia, as examples of data-scarce countries. Spatio-temporal variation in NPP, water use efficiency (WUE) and carbon use efficiency (CUE) for several land covers were correlated with variations in precipitation, temperature and drought at different time scales, i.e. 1, 3, 6 and 12months using Standardized Precipitation Evapotranspiration Index (SPEI) datasets. WUE and CUE were estimated as the ratios of NPP to actual evapotranspiration and NPP to Gross Primary Productivity (GPP), respectively. Results of this study revealed that NPP, WUE and CUE of the different land cover types in Ethiopia have higher magnitudes than their counterparts in Sudan. Moreover, they exhibit higher sensitivity to drought and variation in precipitation. Whereas savannah represents the most sensitive land cover to drought, croplands and permanent wetlands are the least sensitive ones. The inter-annual variation in NPP, WUE and CUE in Ethiopia is likely to be driven by a drought of time scale of three months. No statistically significant correlation was found for Sudan between the inter-annual variations in these indicators with drought at any of the time scales considered in the study. Our findings are useful from the view point of both food security for a growing population and mitigation to climate change as discussed in the present study. Copyright © 2017 Elsevier B.V. All rights reserved.
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Hacker, Kathryn P; Seto, Karen C; Costa, Federico; Corburn, Jason; Reis, Mitermayer G; Ko, Albert I; Diuk-Wasser, Maria A
2013-10-20
The expansion of urban slums is a key challenge for public and social policy in the 21st century. The heterogeneous and dynamic nature of slum communities limits the use of rigid slum definitions. A systematic and flexible approach to characterize, delineate and model urban slum structure at an operational resolution is essential to plan, deploy, and monitor interventions at the local and national level. We modeled the multi-dimensional structure of urban slums in the city of Salvador, a city of 3 million inhabitants in Brazil, by integrating census-derived socioeconomic variables and remotely-sensed land cover variables. We assessed the correlation between the two sets of variables using canonical correlation analysis, identified land cover proxies for the socioeconomic variables, and produced an integrated map of deprivation in Salvador at 30 m × 30 m resolution. The canonical analysis identified three significant ordination axes that described the structure of Salvador census tracts according to land cover and socioeconomic features. The first canonical axis captured a gradient from crowded, low-income communities with corrugated roof housing to higher-income communities. The second canonical axis discriminated among socioeconomic variables characterizing the most marginalized census tracts, those without access to sanitation or piped water. The third canonical axis accounted for the least amount of variation, but discriminated between high-income areas with white-painted or tiled roofs from lower-income areas. Our approach captures the socioeconomic and land cover heterogeneity within and between slum settlements and identifies the most marginalized communities in a large, complex urban setting. These findings indicate that changes in the canonical scores for slum areas can be used to track their evolution and to monitor the impact of development programs such as slum upgrading.
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Effect of land cover, stream discharge, and precipitation on water quality in Puerto Rico
Hall, J. S.; Uriarte, M.
2017-12-01
In 2015, Puerto Rico experienced one of the worst droughts in its history, causing widespread water rationing and sparking concerns for future resources. The drought represents precipitation extremes that provide valuable insight into the effects of land cover (LC), on modulating discharge and water quality indices at varying spatial scales. We used data collected from 38 water quality and 55 precipitation monitoring stations in Puerto Rico from 2005 to 2016, paired with a 2010 land cover map to (1) determine whether temporal variability in discharge, precipitation, or antecedent precipitation was a better predictor of water quality, (2) find the spatial scale where LC has the greatest impact on water quality, and (3) quantify impacts of LC on water quality indices, including dissolved oxygen (mg/L), total nitrogen (mg/L), phosphorous (mg/L), turbidity (NTRU), fecal coliforms (colony units/100mL) and instantaneous discharge (ft3/s). The resulting linear mixed effects models account for between 36-68% of the variance in water quality. Preliminary results indicate that phosphorous and nitrogen were best predicted from instantaneous stream discharge, the log of discharge was the better predictor for turbidity and fecal coliforms, and summed 2 and 14-day antecedent precipitation indices were better predictors for dissolved oxygen and discharge, respectively. Increased urban and pasture area reliably decreased water quality in relation to forest cover, while agriculture and wetlands had little or mixed effects. Turbidity and nitrogen responded to a watershed level LC, while phosphorous, fecal coliforms, and discharge responded to LC in 60 m riparian buffers at the watershed scale. Our results indicate that LC modulates changing precipitation regimes and the ensuing impacts on water quality at a range of spatial scales.
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Directory of Open Access Journals (Sweden)
Sunarto Sunarto
Full Text Available The critically endangered Sumatran tiger (Panthera tigris sumatrae Pocock, 1929 is generally known as a forest-dependent animal. With large-scale conversion of forests into plantations, however, it is crucial for restoration efforts to understand to what extent tigers use modified habitats. We investigated tiger-habitat relationships at 2 spatial scales: occupancy across the landscape and habitat use within the home range. Across major landcover types in central Sumatra, we conducted systematic detection, non-detection sign surveys in 47, 17×17 km grid cells. Within each cell, we surveyed 40, 1-km transects and recorded tiger detections and habitat variables in 100 m segments totaling 1,857 km surveyed. We found that tigers strongly preferred forest and used plantations of acacia and oilpalm, far less than their availability. Tiger probability of occupancy covaried positively and strongly with altitude, positively with forest area, and negatively with distance-to-forest centroids. At the fine scale, probability of habitat use by tigers across landcover types covaried positively and strongly with understory cover and altitude, and negatively and strongly with human settlement. Within forest areas, tigers strongly preferred sites that are farther from water bodies, higher in altitude, farther from edge, and closer to centroid of large forest block; and strongly preferred sites with thicker understory cover, lower level of disturbance, higher altitude, and steeper slope. These results indicate that to thrive, tigers depend on the existence of large contiguous forest blocks, and that with adjustments in plantation management, tigers could use mosaics of plantations (as additional roaming zones, riparian forests (as corridors and smaller forest patches (as stepping stones, potentially maintaining a metapopulation structure in fragmented landscapes. This study highlights the importance of a multi-spatial scale analysis and provides crucial
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Directory of Open Access Journals (Sweden)
Regina Gabriela Medina
2016-11-01
Full Text Available Subtropical dry forests are among the most vulnerable biomes to land transformation at a global scale. Among them, the Dry Chaco suffers an accelerated change due to agriculture expansion and intensification. The Dry Chaco ecoregion is characterized by high levels of endemisms and species diversity, which are the result of a variety of climates and reliefs, allowing a wide variety of environments. The amphibian group exhibits a high richness in the Dry Chaco, which has been barely studied in relation to land cover changes. We used ecological niche models (ENMs to assess the potential geographic distribution of 10 Leptodactylus species (Anura, Leptodactylidae, which are mainly distributed within the Dry Chaco. We characterized these distributions environmentally, analyzed their overlap with land cover classes, and assessed their diversity of ecoregions. Also, we evaluated how these species potential distribution is affected by the transformation of land, and quantified the proportional area of the potential distribution in protected areas. We found that temperature seasonality is the main constraint to the occurrence of the species studied, whose main habitats are savannas, grasslands and croplands. The main threats to these species are the effects of climate change over spatial patterns of seasonality, which could affect their breeding and reproduction mode; the loss of their natural habitat; the exposure to contaminants used by intensive agriculture and their underrepresentation in protected areas.
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Land cover change impact on urban flood modeling (case study: Upper Citarum watershed)
Siregar, R. I.
2018-03-01
The upper Citarum River watershed utilizes remote sensing technology in Geographic Information System to provide information on land coverage by interpretation of objects in the image. Rivers that pass through urban areas will cause flooding problems causing disadvantages, and it disrupts community activities in the urban area. Increased development in a city is related to an increase in the number of population growth that added by increasing quality and quantity of life necessities. Improved urban lifestyle changes have an impact on land cover. The impact in over time will be difficult to control. This study aims to analyze the condition of flooding in urban areas caused by upper Citarum watershed land-use change in 2001 with the land cover change in 2010. This modeling analyzes with the help of HEC-RAS to describe flooded inundation urban areas. Land cover change in upper Citarum watershed is not very significant; it based on the results of data processing of land cover has the difference of area that changed is not enormous. Land cover changes for the floods increased dramatically to a flow coefficient for 2001 is 0.65 and in 2010 at 0.69. In 2001, the inundation area about 105,468 hectares and it were about 92,289 hectares in 2010.
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Brownfield, TX 1:250,000 Quad USGS Land Use/Land Cover, 2000
Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...
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Dalhart, TX 1:250,000 Quad USGS Land Use/Land Cover, 2000
Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...
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Hobbs, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000
Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...
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Clovis, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000
Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...
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Tucumcari, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000
Earth Data Analysis Center, University of New Mexico — This land cover data set was produced as part of a cooperative project between the U.S. Geological Survey (USGS) and the U.S. Environmental Protection Agency (USEPA)...
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Tsunami exposure estimation with land-cover data: Oregon and the Cascadia subduction zone
Wood, N.
2009-01-01
A Cascadia subduction-zone earthquake has the potential to generate tsunami waves which would impact more than 1000 km of coastline on the west coast of the United States and Canada. Although the predictable extent of tsunami inundation is similar for low-lying land throughout the region, human use of tsunami-prone land varies, creating variations in community exposure and potential impacts. To better understand such variations, land-cover information derived from midresolution remotely-sensed imagery (e.g., 30-m-resolution Landsat Thematic Mapper imagery) was coupled with tsunami-hazard information to describe tsunami-prone land along the Oregon coast. Land-cover data suggest that 95% of the tsunami-prone land in Oregon is undeveloped and is primarily wetlands and unconsolidated shores. Based on Spearman rank correlation coefficients (rs), correlative relationships are strong and statistically significant (p < 0.05) between city-level estimates of the amount of land-cover pixels classified as developed (impervious cover greater than 20%) and the amount of various societal assets, including residential and employee populations, homes, businesses, and tax-parcel values. Community exposure to tsunami hazards, described here by the amount and relative percentage of developed land in tsunami-prone areas, varies considerably among the 26 communities of the study area, and these variations relate to city size. Correlative relationships are strong and significant (p < 0.05) for community exposure rankings based on land-cover data and those based on aggregated socioeconomic data. In the absence of socioeconomic data or community-based knowledge, the integration of hazards information and land-cover information derived from midresolution remotely-sensed imagery to estimate community exposure may be a useful first step in understanding variations in community vulnerability to regional hazards.
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Analysing land cover and land use change in the Matobo National Park and surroundings in Zimbabwe
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
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Simulated impacts of land cover change on summer climate in the Tibetan Plateau
International Nuclear Information System (INIS)
Li Qian; Xue Yongkang
2010-01-01
The Tibetan Plateau (TP) is a key region of land-atmosphere interactions with severe eco-environment degradation. This study uses an atmospheric general circulation model, NCEP GCM/SSiB, to present the major TP summer climate features for six selected ENSO years and preliminarily assess the possible impact of land cover change on the summer circulation over the TP. Compared to Reanalysis II data, the GCM using satellite derived vegetation properties generally reproduces the main 6-year-mean TP summer circulation features despite some discrepancies in intensity and geographic locations of some climate features. Two existing vegetation maps with very different land cover conditions over the TP, one with bare ground and one with vegetation cover, derived from satellite derived data, are tested and produce clearer climate signals due to land cover change. It shows that land cover change from vegetated land to bare ground decreases the radiation absorbed by the surface and results in weaker surface thermal effects, which lead to lower atmospheric temperature, as well as weaker vertical ascending motion, low-layer cyclonic, upper level anticyclonic, and summer monsoon circulation. These changes in circulation cause a decrease in the precipitation in the southeastern TP.
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Impacts of land cover transitions on surface temperature in China based on satellite observations
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
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LandSense: A Citizen Observatory and Innovation Marketplace for Land Use and Land Cover Monitoring
Moorthy, Inian; Fritz, Steffen; See, Linda; McCallum, Ian
2017-04-01
Currently within the EU's Earth Observation (EO) monitoring framework, there is a need for low-cost methods for acquiring high quality in-situ data to create accurate and well-validated environmental monitoring products. To help address this need, a new four year Horizon 2020 project entitled LandSense will link remote sensing data with modern participatory data collection methods that involve citizen scientists. This paper will describe the citizen science activities within the LandSense Observatory that aim to deliver concrete, measurable and quality-assured ground-based data that will complement existing satellite monitoring systems. LandSense will deploy advanced tools, services and resources to mobilize and engage citizens to collect in-situ observations (i.e. ground-based data and visual interpretations of EO imagery). Integrating these citizen-driven in-situ data collections with established authoritative and open access data sources will help reduce costs, extend GEOSS and Copernicus capacities, and support comprehensive environmental monitoring systems. Policy-relevant campaigns will be implemented in close collaboration with multiple stakeholders to ensure that citizen observations address user requirements and contribute to EU-wide environmental governance and decision-making. Campaigns for addressing local and regional Land Use and Land Cover (LULC) issues are planned for select areas in Austria, France, Germany, Spain, Slovenia and Serbia. Novel LandSense services (LandSense Campaigner, FarmLand Support, Change Detector and Quality Assurance & Control) will be deployed and tested in these areas to address critical LULC issues (i.e. urbanization, agricultural land use and forest/habitat monitoring). For example, local residents in the cities of Vienna, Tulln, and Heidelberg will help cooperatively detect and map changes in land cover and green space to address key issues of urban sprawl, land take and flooding. Such campaigns are facilitated through
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Ambarwulan, W.; Widiatmaka; Nahib, I.
2018-05-01
Land utilization in Indonesia is regulated in an official spatial land use planning (OSLUP), stipulated by government regulations. However in fact, land utilizations are often develops inconsistent with regulations. OSLUP itself is also not usually compatible with sustainable land utilizations. This study aims to evaluate current land utilizations and OSLUP in Indramayu Regency, West Java. The methodology used is the integrated analysis using land use and land cover (LU/LC) data, land capability data and spatial pattern in OSLUP. Actual LU/LC are interpreted using SPOT-6 imagery of 2014. The spatial data of land capabilities are derived from land capability classification using field data and laboratory analysis. The confrontation between these spatial data is interpreted in terms of future direction for sustainable land use planning. The results shows that Indramayu regency consists of 8 types of LU/LC. Land capability in research area range from class II to VIII. Only a small portion of the land in Indramayu has been used in accordance with land capability, but most of the land is used exceeding its land capability.
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International Nuclear Information System (INIS)
Issa, S.M.
2009-01-01
The main objective of this study is to apply the most appropriate change detection techniques to assess land development achievements on Al Sammalyah Island, off the coast of Abu Dhabi, United Arab Emirates capital city. This was accomplished by mapping trajectory of land cover change of the whole island between 1999 and 2005. Another objective was to assess the level of development that occurred on the island and the level of change in the local environment. Available historical large scale aerial photographs from the late nineties to the most recent 2005 were used for the multi temporal study. Geographic information systems (GIS) layers were created by on-screen digitizing of corrected and co-registered images. A GIS overlay analysis combined with post classification change detection method analysis schema was adopted. Results of the current study demonstrate intense land development occurring on the Al Sammalyah Island; vegetation cover extent has increased from 3.742 km/sup 2/ (1.44 miles/sup 2/) in 1999 to 5.101 km/sup 2/ (1.97 miles/sup 2/) in 2005 that corresponds to 36.3% increase over this period. The study also shows that this increase in vegetation extent is mostly attributed to the increase in mangrove planted areas alone with an aerial increase from 2.256 km/sup 2/ (0.87 miles/sup 2/) in 1999 to 3.568 km/sup 2/ (1.38 miles/sup 2/) in 2005, an increase of 58.2% in seven years. (author)
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Stapanian, Martin A.; Gara, Brian; Schumacher, William
2018-01-01
The loss of wetland habitats and their often-unique biological communities is a major environmental concern. We examined vegetation data obtained from 380 wetlands sampled in a statistical survey of wetlands in the USA. Our goal was to identify which surrounding land cover types best predict two indices of vegetation quality in wetlands at the regional scale. We considered palustrine wetlands in four regions (Coastal Plains, North Central East, Interior Plains, and West) in which the dominant vegetation was emergent, forested, or scrub-shrub. For each wetland, we calculated weighted proportions of eight land cover types surrounding the area in which vegetation was assessed, in four zones radiating from the edge of the assessment area to 2 km. Using Akaike's Information Criterion, we determined the best 1-, 2- and 3-predictor models of the two indices, using the weighted proportions of the land cover types as potential predictors. Mean values of the two indices were generally higher in the North Central East and Coastal Plains than the other regions for forested and emergent wetlands. In nearly all cases, the best predictors of the indices were not the dominant surrounding land cover types. Overall, proportions of forest (positive effect) and agriculture (negative effect) surrounding the assessment area were the best predictors of the two indices. One or both of these variables were included as predictors in 65 of the 72 models supported by the data. Wetlands surrounding the assessment area had a positive effect on the indices, and ranked third (33%) among the predictors included in supported models. Development had a negative effect on the indices and was included in only 28% of supported models. These results can be used to develop regional management plans for wetlands, such as creating forest buffers around wetlands, or to conserve zones between wetlands to increase habitat connectivity.
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Spruce, J. P.; Smoot, James; Ellis, Jean; Hilbert, Kent; Swann, Roberta
2012-01-01
This paper discusses the development and implementation of a geospatial data processing method and multi-decadal Landsat time series for computing general coastal U.S. land-use and land-cover (LULC) classifications and change products consisting of seven classes (water, barren, upland herbaceous, non-woody wetland, woody upland, woody wetland, and urban). Use of this approach extends the observational period of the NOAA-generated Coastal Change and Analysis Program (C-CAP) products by almost two decades, assuming the availability of one cloud free Landsat scene from any season for each targeted year. The Mobile Bay region in Alabama was used as a study area to develop, demonstrate, and validate the method that was applied to derive LULC products for nine dates at approximate five year intervals across a 34-year time span, using single dates of data for each classification in which forests were either leaf-on, leaf-off, or mixed senescent conditions. Classifications were computed and refined using decision rules in conjunction with unsupervised classification of Landsat data and C-CAP value-added products. Each classification's overall accuracy was assessed by comparing stratified random locations to available reference data, including higher spatial resolution satellite and aerial imagery, field survey data, and raw Landsat RGBs. Overall classification accuracies ranged from 83 to 91% with overall Kappa statistics ranging from 0.78 to 0.89. The accuracies are comparable to those from similar, generalized LULC products derived from C-CAP data. The Landsat MSS-based LULC product accuracies are similar to those from Landsat TM or ETM+ data. Accurate classifications were computed for all nine dates, yielding effective results regardless of season. This classification method yielded products that were used to compute LULC change products via additive GIS overlay techniques.
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Impact of land cover changes on the South African climate
International Nuclear Information System (INIS)
Ngwana, T I; Demory, M-E; Vidale, P L; Plant, R S; Mbedzi, M P
2010-01-01
The Joint UK Land Environmental Simulator (JULES) was run offline to investigate the sensitivity of land surface type changes over South Africa. Sensitivity tests were made in idealised experiments where the actual land surface cover is replaced by a single homogeneous surface type. The vegetation surface types on which some of the experiments were made are static. Experimental tests were evaluated against the control. The model results show among others that the change of the surface cover results in changes of other variables such as soil moisture, albedo, net radiation and etc. These changes are also visible in the spin up process. The model shows different surfaces spinning up at different cycles. Because JULES is the land surface model of Unified Model, the results could be more physically meaningful if it is coupled to the Unified Model.
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Effects of Land Cover on the Movement of Frugivorous Birds in a Heterogeneous Landscape.
Da Silveira, Natalia Stefanini; Niebuhr, Bernardo Brandão S; Muylaert, Renata de Lara; Ribeiro, Milton Cezar; Pizo, Marco Aurélio
2016-01-01
Movement is a key spatiotemporal process that enables interactions between animals and other elements of nature. The understanding of animal trajectories and the mechanisms that influence them at the landscape level can yield insight into ecological processes and potential solutions to specific ecological problems. Based upon optimal foraging models and empirical evidence, we hypothesized that movement by thrushes is highly tortuous (low average movement speeds and homogeneous distribution of turning angles) inside forests, moderately tortuous in urban areas, which present intermediary levels of resources, and minimally tortuous (high movement speeds and turning angles next to 0 radians) in open matrix types (e.g., crops and pasture). We used data on the trajectories of two common thrush species (Turdus rufiventris and Turdus leucomelas) collected by radio telemetry in a fragmented region in Brazil. Using a maximum likelihood model selection approach we fit four probability distribution models to average speed data, considering short-tailed, long-tailed, and scale-free distributions (to represent different regimes of movement variation), and one distribution to relative angle data. Models included land cover type and distance from forest-matrix edges as explanatory variables. Speed was greater farther away from forest edges and increased faster inside forest habitat compared to urban and open matrices. However, turning angle was not influenced by land cover. Thrushes presented a very tortuous trajectory, with many displacements followed by turns near 180 degrees. Thrush trajectories resembled habitat and edge dependent, tortuous random walks, with a well-defined movement scale inside each land cover type. Although thrushes are habitat generalists, they showed a greater preference for forest edges, and thus may be considered edge specialists. Our results reinforce the importance of studying animal movement patterns in order to understand ecological processes such as
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Effects of Land Cover on the Movement of Frugivorous Birds in a Heterogeneous Landscape.
Directory of Open Access Journals (Sweden)
Natalia Stefanini Da Silveira
Full Text Available Movement is a key spatiotemporal process that enables interactions between animals and other elements of nature. The understanding of animal trajectories and the mechanisms that influence them at the landscape level can yield insight into ecological processes and potential solutions to specific ecological problems. Based upon optimal foraging models and empirical evidence, we hypothesized that movement by thrushes is highly tortuous (low average movement speeds and homogeneous distribution of turning angles inside forests, moderately tortuous in urban areas, which present intermediary levels of resources, and minimally tortuous (high movement speeds and turning angles next to 0 radians in open matrix types (e.g., crops and pasture. We used data on the trajectories of two common thrush species (Turdus rufiventris and Turdus leucomelas collected by radio telemetry in a fragmented region in Brazil. Using a maximum likelihood model selection approach we fit four probability distribution models to average speed data, considering short-tailed, long-tailed, and scale-free distributions (to represent different regimes of movement variation, and one distribution to relative angle data. Models included land cover type and distance from forest-matrix edges as explanatory variables. Speed was greater farther away from forest edges and increased faster inside forest habitat compared to urban and open matrices. However, turning angle was not influenced by land cover. Thrushes presented a very tortuous trajectory, with many displacements followed by turns near 180 degrees. Thrush trajectories resembled habitat and edge dependent, tortuous random walks, with a well-defined movement scale inside each land cover type. Although thrushes are habitat generalists, they showed a greater preference for forest edges, and thus may be considered edge specialists. Our results reinforce the importance of studying animal movement patterns in order to understand ecological
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Open land cover from OpenStreetMap and remote sensing
Schultz, Michael; Voss, Janek; Auer, Michael; Carter, Sarah; Zipf, Alexander
2017-12-01
OpenStreetMap (OSM) tags were used to produce a global Open Land Cover (OLC) product with fractional data gaps available at osmlanduse.org. Data gaps in the global OLC map were filled for a case study in Heidelberg, Germany using free remote sensing data, which resulted in a land cover (LC) prototype with complete coverage in this area. Sixty tags in the OSM were used to allocate a Corine Land Cover (CLC) level 2 land use classification to 91.8% of the study area, and the remaining gaps were filled with remote sensing data. For this case study, complete are coverage OLC overall accuracy was estimated 87%, which performed better than the CLC product (81% overall accuracy) of 2012. Spatial thematic overlap for the two products was 84%. OLC was in large parts found to be more detailed than CLC, particularly when LC patterns were heterogeneous, and outperformed CLC in the classification of 12 of the 14 classes. Our OLC product represented data created in different periods; 53% of the area was 2011-2016, and 46% of the area was representative of 2016-2017.
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Directory of Open Access Journals (Sweden)
Oliver T. Coomes
2016-09-01
Full Text Available Can social inequality be seen imprinted in a forest landscape? We studied the relationship between land holding, land use, and inequality in a peasant community in the Peruvian Amazon where farmers practice swidden-fallow cultivation. Longitudinal data on land holding, land use, and land cover were gathered through field-level surveys (n = 316 and household interviews (n = 51 in 1994/1995 and 2007. Forest cover change between 1965 and 2007 was documented through interpretation of air photos and satellite imagery. We introduce the concept of "land use inequality" to capture differences across households in the distribution of forest fallowing and orchard raising as key land uses that affect household welfare and the sustainability of swidden-fallow agriculture. We find that land holding, land use, and forest cover distribution are correlated and that the forest today reflects social inequality a decade prior. Although initially land-poor households may catch up in terms of land holdings, their use and land cover remain impoverished. Differential land use investment through time links social inequality and forest cover. Implications are discussed for the study of forests as landscapes of inequality, the relationship between social inequality and forest composition, and the forest-poverty nexus.
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Wang, Hailong; Tetzlaff, Doerthe; Soulsby, Chris
2018-03-01
Climate and land cover are two major factors affecting the water fluxes and balance across spatiotemporal scales. These two factors and their impacts on hydrology are often interlinked. The quantification and differentiation of such impacts is important for developing sustainable land and water management strategies. Here, we calibrated the well-known Hydrus-1D model in a data-rich boreal headwater catchment in Scotland to assess the role of two dominant vegetation types (shrubs vs. trees) in regulating the soil water partitioning and balance. We also applied previously established climate projections for the area and replaced shrubs with trees to imitate current land use change proposals in the region, so as to quantify the potential impacts of climate and land cover changes on soil hydrology. Under tree cover, evapotranspiration and deep percolation to recharge groundwater was about 44% and 57% of annual precipitation, whilst they were about 10% lower and 9% higher respectively under shrub cover in this humid, low energy environment. Meanwhile, tree canopies intercepted 39% of annual precipitation in comparison to 23% by shrubs. Soils with shrub cover stored more water than tree cover. Land cover change was shown to have stronger impacts than projected climate change. With a complete replacement of shrubs with trees under future climate projections at this site, evapotranspiration is expected to increase by ∼39% while percolation to decrease by 21% relative to the current level, more pronounced than the modest changes in the two components (seasons, which may result in water stress experienced by the vegetation. The findings provide an important evidence base for adaptive management strategies of future changes in low-energy humid environments, where vegetation growth is usually restricted by radiative energy and not water availability while few studies that quantify soil water partitioning exist.
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Ellison, L.; Ichoku, C. M.
2016-12-01
Biomass burning (BB) is an extensive and persistent phenomenon across the world, and is a result of either natural (via lightning strikes) or anthropogenic processes, depending on the location. In Northern Sub-Saharan Africa (NSSA), where access to affordable modern farming equipment is extremely limited, agricultural practices dominate and BB is completely anthropogenic for all practical purposes, resulting in NSSA consistently contributing 15-20% of the total global annual emission of particulate matter from fires, according to estimates from version 1.0 of the Fire Energetics and Emissions Research BB emissions inventory (FEERv1.0, http://feer.gsfc.nasa.gov/data/emissions/). The FEERv1.0 algorithm uses a land cover type (LCT) product at either 0.5° or 0.1° resolutions for the conversion of total particulate matter estimates to various other smoke constituents. Due to the fact that fires are closely associated with land cover types, it became apparent that a fire-prone land cover type product at those spatial resolutions were needed, resulting in the FEERv1 BB-LCT product (http://feer.gsfc.nasa.gov/data/landcover/). In version 2 of the product, it was found that 6% of all grid cells with partial or full land cover in the original 0.5° LCT product is reclassified when considering BB practices. In NSSA, we see that the differences fall mainly along the borders between major regions of different LCT. Roughly speaking, fires along the cropland/savanna and savanna/forest borders in NSSA are mostly from from savanna burning. An in-depth analysis of the spatial extent and variability of fires and land cover in NSSA reveals that within the last one-and-a-half decades, the maximum fire activity occurred in the 2006/07 fire season and has been decreasing ever since. Interestingly, despite this decrease in fire activity, we observe a continuing increase in land cover conversion to cropland over the same time period at a rate of 0.3%/yr, which is equal to ≈37,500 km2/yr