Mapping land cover in urban residential landscapes using fine resolution imagery and object-oriented classification

Science.gov (United States)

A knowledge of different types of land cover in urban residential landscapes is important for building social and economic city-wide policies including landscape ordinances and water conservation programs. Urban landscapes are typically heterogeneous, so classification of land cover in these areas ...

Completion of the National Land Cover Database (NLCD) 1992–2001 Land Cover Change Retrofit product

Science.gov (United States)

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.

Mapping land cover through time with the Rapid Land Cover Mapper—Documentation and user manual

Science.gov (United States)

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).

Sensitivity of selected landscape pattern metrics to land-cover misclassification and differences in land-cover composition

Science.gov (United States)

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...

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....

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 ...

Land-Cover Change in the East Central Texas Plains, 1973-2000

Science.gov (United States)

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

Land Cover/Land Use Classification and Change Detection Analysis with Astronaut Photography and Geographic Object-Based Image Analysis

Science.gov (United States)

Hollier, Andi B.; Jagge, Amy M.; Stefanov, William L.; Vanderbloemen, Lisa A.

2017-01-01

For over fifty years, NASA astronauts have taken exceptional photographs of the Earth from the unique vantage point of low Earth orbit (as well as from lunar orbit and surface of the Moon). The Crew Earth Observations (CEO) Facility is the NASA ISS payload supporting astronaut photography of the Earth surface and atmosphere. From aurora to mountain ranges, deltas, and cities, there are over two million images of the Earth's surface dating back to the Mercury missions in the early 1960s. The Gateway to Astronaut Photography of Earth website (eol.jsc.nasa.gov) provides a publically accessible platform to query and download these images at a variety of spatial resolutions and perform scientific research at no cost to the end user. As a demonstration to the science, application, and education user communities we examine astronaut photography of the Washington D.C. metropolitan area for three time steps between 1998 and 2016 using Geographic Object-Based Image Analysis (GEOBIA) to classify and quantify land cover/land use and provide a template for future change detection studies with astronaut photography.

Land cover classification using reformed fuzzy C-means

Indian Academy of Sciences (India)

This paper explains the task of land cover classification using reformed fuzzy C means. Clustering is the assignment of objects into groups called clusters so that objects from the same cluster are more similar to each other than objects from different clusters. The most basic attribute for clustering of an image is its luminance ...

Land Use and Land Cover - MO 2015 Silver Land Cover (GDB)

Data.gov (United States)

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...

Land Use and Land Cover - MO 2015 Meramec Land Cover (GDB)

Data.gov (United States)

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...

Soil chemical and physical properties that differentiate urban land-use and cover types

Science.gov (United States)

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...

Recent land cover history and nutrient retention in riparian wetlands

Science.gov (United States)

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.

CLC2000 land cover database of the Netherlands; monitoring land cover changes between 1986 and 2000

OpenAIRE

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...

Measurement of semantic similarity for land use and land cover classification systems

Science.gov (United States)

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.

Allegheny County Land Cover Areas

Data.gov (United States)

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...

Scenarios of land cover in China

Science.gov (United States)

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.

Land Use and Land Cover (LULC) Change Detection in Islamabad and its Comparison with Capital Development Authority (CDA) 2006 Master Plan

Science.gov (United States)

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.

The National Land Cover Database

Science.gov (United States)

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.

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.

The Regional Land Cover Monitoring System: Building regional capacity through innovative land cover mapping approaches

Science.gov (United States)

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

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. 

Using ASTER Imagery in Land Use/cover Classification of Eastern Mediterranean Landscapes According to CORINE Land Cover Project

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.

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.

Geovisualization of land use and land cover using bivariate maps and Sankey flow diagrams

Science.gov (United States)

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.

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...

Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods

Science.gov (United States)

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.

Border Lakes land-cover classification

Science.gov (United States)

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-...

Carbon Assessment of Hawaii Land Cover Map (CAH_LandCover)

Data.gov (United States)

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,...

Towards realistic Holocene land cover scenarios: integration of archaeological, palynological and geomorphological records and comparison to global land cover scenarios.

Science.gov (United States)

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

1990 Kansas Land Cover Patterns Update

Data.gov (United States)

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...

VT National Land Cover Dataset - 2001

Data.gov (United States)

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...

Land cover changes in central Sonora Mexico

Science.gov (United States)

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...

The Aggregate Representation of Terrestrial Land Covers Within Global Climate Models (GCM)

Science.gov (United States)

Shuttleworth, W. James; Sorooshian, Soroosh

1996-01-01

This project had four initial objectives: (1) to create a realistic coupled surface-atmosphere model to investigate the aggregate description of heterogeneous surfaces; (2) to develop a simple heuristic model of surface-atmosphere interactions; (3) using the above models, to test aggregation rules for a variety of realistic cover and meteorological conditions; and (4) to reconcile biosphere-atmosphere transfer scheme (BATS) land covers with those that can be recognized from space; Our progress in meeting these objectives can be summarized as follows. Objective 1: The first objective was achieved in the first year of the project by coupling the Biosphere-Atmosphere Transfer Scheme (BATS) with a proven two-dimensional model of the atmospheric boundary layer. The resulting model, BATS-ABL, is described in detail in a Masters thesis and reported in a paper in the Journal of Hydrology Objective 2: The potential value of the heuristic model was re-evaluated early in the project and a decision was made to focus subsequent research around modeling studies with the BATS-ABL model. The value of using such coupled surface-atmosphere models in this research area was further confirmed by the success of the Tucson Aggregation Workshop. Objective 3: There was excellent progress in using the BATS-ABL model to test aggregation rules for a variety of realistic covers. The foci of attention have been the site of the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) in Kansas and one of the study sites of the Anglo-Brazilian Amazonian Climate Observational Study (ABRACOS) near the city of Manaus, Amazonas, Brazil. These two sites were selected because of the ready availability of relevant field data to validate and initiate the BATS-ABL model. The results of these tests are given in a Masters thesis, and reported in two papers. Objective 4: Progress far exceeded original expectations not only in reconciling BATS land covers with those that can be

From land cover change to land function dynamics: A major challenge to improve land characterization

NARCIS (Netherlands)

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

LandSat-Based Land Use-Land Cover (Vector)

Data.gov (United States)

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...

LandSat-Based Land Use-Land Cover (Raster)

Data.gov (United States)

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...

Exploring dust emission responses to land cover change using an ecological land classification

Science.gov (United States)

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.

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)

A Mixed Land Cover Spatio-temporal Data Model Based on Object-oriented and Snapshot

Directory of Open Access Journals (Sweden)

LI Yinchao

2016-07-01

Full Text Available Spatio-temporal data model (STDM is one of the hot topics in the domains of spatio-temporal database and data analysis. There is a common view that a universal STDM is always of high complexity due to the various situation of spatio-temporal data. In this article, a mixed STDM is proposed based on object-oriented and snapshot models for modelling and analyzing landcover change (LCC. This model uses the object-oriented STDM to describe the spatio-temporal processes of land cover patches and organize their spatial and attributive properties. In the meantime, it uses the snapshot STDM to present the spatio-temporal distribution of LCC on the whole via snapshot images. The two types of models are spatially and temporally combined into a mixed version. In addition to presenting the spatio-temporal events themselves, this model could express the transformation events between different classes of spatio-temporal objects. It can be used to create database for historical data of LCC, do spatio-temporal statistics, simulation and data mining with the data. In this article, the LCC data in Heilongjiang province is used for case study to validate spatio-temporal data management and analysis abilities of mixed STDM, including creating database, spatio-temporal query, global evolution analysis and patches spatio-temporal process expression.

EnviroAtlas - Land Cover for the Conterminous United States

Data.gov (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...

Development of a 30 m Spatial Resolution Land Cover of Canada: Contribution to the Harmonized North America Land Cover Dataset

Science.gov (United States)

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.

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.

Object-oriented classification of land use in urban areas applying very high resolution satellite data

International Nuclear Information System (INIS)

Bauer, T.B.

2001-08-01

The availability of the new very high resolution satellite imagery will offer a wide range of new applications in the field of remote sensing. Information about actual land use is an important task for the management and planning in urban areas. High resolution satellite data will be an alternative to aerial photographs for updating and maintaining cartographic and geographic databases at reduced costs. The aim of the research is to formalize the visual interpretation procedure in order to automate the whole process. The assumption underlying this approach is that the land use functions can be distinguished on the basis of the differences in spatial distribution and pattern of land cover forms. Therefore a two-stage classification procedure is applied. In a first stage a land cover map is produced. In a second stage the morphological properties and spatial patterns of the land cover objects are analyzed with the structural analyzing and mapping system leading to a characterization and description of distinct urban land use categories. This information is then used for building a rule system that is implemented in a new commercial software tool called eCognition. An object-oriented classifier applies the rules to the land cover objects resulting in the required land use map. The potential of this method is demonstrated in a case study using IKONOS data covering a part of the metropolitan area of Vienna. (author)

Characterizing Degradation Gradients through Land Cover Change Analysis in Rural Eastern Cape, South Africa

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.

ISLSCP II Historical Land Cover and Land Use, 1700-1990

Data.gov (United States)

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...

Land cover change impact on urban flood modeling (case study: Upper Citarum watershed)

Science.gov (United States)

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.

Towards Seamless Validation of Land Cover Data

Science.gov (United States)

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.

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.

Review of Land Use and Land Cover Change research progress

Science.gov (United States)

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.

Statistical Monitoring of Changes to Land Cover

KAUST Repository

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

Assessing the Impact of Land Use and Land Cover Change on Global Water Resources

Science.gov (United States)

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

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.

Land cover mapping of Greater Mesoamerica using MODIS data

Science.gov (United States)

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.

The Land Cover Dynamics and Conversion of Agricultural Land in Northwestern Bangladesh, 1973-2003.

Science.gov (United States)

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.

Towards monitoring land-cover and land-use changes at a global scale: the global land survey 2005

Science.gov (United States)

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

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

Science.gov (United States)

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.

Statistical Monitoring of Changes to Land Cover

KAUST Repository

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.

CORINE land cover and floristic variation in a Mediterranean wetland.

Science.gov (United States)

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.

Towards automated statewide land cover mapping in Wisconsin using satellite remote sensing and GIS techniques

International Nuclear Information System (INIS)

Cosentino, B.L.; Lillesand, T.M.

1991-01-01

Attention is given to an initial research project being performed by the University of Wisconsin-Madison, Environmental Remote Sensing Center in conjunction with seven local, state, and federal agencies to implement automated statewide land cover mapping using satellite remote sensing and geographical information system (GIS) techniques. The basis, progress, and future research needs for this mapping program are presented. The research efforts are directed toward strategies that integrate satellite remote sensing and GIS techniques in the generation of land cover data for multiple users of land cover information. The project objectives are to investigate methodologies that integrate satellite data with other imagery and spatial data resident in emerging GISs in the state for particular program needs, and to develop techniques that can improve automated land cover mapping efficiency and accuracy. 10 refs

Millennium Ecosystem Assessment: MA Rapid Land Cover Change

Data.gov (United States)

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...

The causes of land-use and land-cover change : moving beyond the myths

NARCIS (Netherlands)

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

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.

Modeling Historical Land Cover and Land Use: A Review fromContemporary Modeling

Directory of Open Access Journals (Sweden)

Laura Alfonsina Chang-Martínez

2015-09-01

Full Text Available Spatially-explicit land cover land use change (LCLUC models are becoming increasingly useful tools for historians and archaeologists. Such kinds of models have been developed and used by geographers, ecologists and land managers over the last few decades to carry out prospective scenarios. In this paper, we review historical models to compare them with prospective models, with the assumption that the ample experience gained in the development of models of prospective simulation can benefit the development of models having as their objective the simulation of changes that happened in the past. The review is divided into three sections: in the first section, we explain the functioning of contemporary LCLUC models; in the second section, we analyze historical LCLUC models; in the third section, we compare the former two types of models, and finally, we discuss the contributions to historical LCLUC models of contemporary LCLUC models.

Local topographic wetness indices predict household malaria risk better than land-use and land-cover in the western Kenya highlands.

Science.gov (United States)

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

Local topographic wetness indices predict household malaria risk better than land-use and land-cover in the western Kenya highlands

Directory of Open Access Journals (Sweden)

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

Simulating feedbacks in land use and land cover change models

NARCIS (Netherlands)

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

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) .

Land use and land cover mapping: City of Palm Bay, Florida

Science.gov (United States)

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.

Deriving a per-field land use and land cover map in an agricultural mosaic catchment

Science.gov (United States)

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).

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 ...

Impacts of land cover transitions on surface temperature in China based on satellite observations

Science.gov (United States)

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

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

Land cover mapping and change detection in urban watersheds using QuickBird high spatial resolution satellite imagery

Science.gov (United States)

Hester, David Barry

The objective of this research was to develop methods for urban land cover analysis using QuickBird high spatial resolution satellite imagery. Such imagery has emerged as a rich commercially available remote sensing data source and has enjoyed high-profile broadcast news media and Internet applications, but methods of quantitative analysis have not been thoroughly explored. The research described here consists of three studies focused on the use of pan-sharpened 61-cm spatial resolution QuickBird imagery, the spatial resolution of which is the highest of any commercial satellite. In the first study, a per-pixel land cover classification method is developed for use with this imagery. This method utilizes a per-pixel classification approach to generate an accurate six-category high spatial resolution land cover map of a developing suburban area. The primary objective of the second study was to develop an accurate land cover change detection method for use with QuickBird land cover products. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and meaningful high spatial resolution land cover change analysis. The third study described here is an urban planning application of the high spatial resolution QuickBird-based land cover product developed in the first study. This work both meaningfully connects this exciting new data source to urban watershed management and makes an important empirical contribution to the study of suburban watersheds. Its analysis of residential roads and driveways as well as retail parking lots sheds valuable light on the impact of transportation-related land use on the suburban landscape. Broadly, these studies provide new methods for using state-of-the-art remote sensing data to inform land cover analysis and urban planning. These methods are widely adaptable and produce land cover products that are both meaningful and accurate. As additional high spatial resolution satellites are launched and the

Land-cover change in the Ozark Highlands, 1973-2000

Science.gov (United States)

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

U.S. landowner behavior, land use and land cover changes, and climate change mitigation.

Science.gov (United States)

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,...

Land-cover change and avian diversity in the conterminous United States

Science.gov (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...

Impacts of Land Cover Changes on Climate over China

Science.gov (United States)

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.

Land change monitoring, assessment, and projection (LCMAP) revolutionizes land cover and land change research

Science.gov (United States)

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.

Modeled impact of anthropogenic land cover change on climate

Science.gov (United States)

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.

Building a Continental Scale Land Cover Monitoring Framework for Australia

Science.gov (United States)

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

Land use and land cover change based on historical space-time model

Science.gov (United States)

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.

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.

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...

Use of Binary Partition Tree and energy minimization for object-based classification of urban land cover

Science.gov (United States)

Li, Mengmeng; Bijker, Wietske; Stein, Alfred

2015-04-01

Two main challenges are faced when classifying urban land cover from very high resolution satellite images: obtaining an optimal image segmentation and distinguishing buildings from other man-made objects. For optimal segmentation, this work proposes a hierarchical representation of an image by means of a Binary Partition Tree (BPT) and an unsupervised evaluation of image segmentations by energy minimization. For building extraction, we apply fuzzy sets to create a fuzzy landscape of shadows which in turn involves a two-step procedure. The first step is a preliminarily image classification at a fine segmentation level to generate vegetation and shadow information. The second step models the directional relationship between building and shadow objects to extract building information at the optimal segmentation level. We conducted the experiments on two datasets of Pléiades images from Wuhan City, China. To demonstrate its performance, the proposed classification is compared at the optimal segmentation level with Maximum Likelihood Classification and Support Vector Machine classification. The results show that the proposed classification produced the highest overall accuracies and kappa coefficients, and the smallest over-classification and under-classification geometric errors. We conclude first that integrating BPT with energy minimization offers an effective means for image segmentation. Second, we conclude that the directional relationship between building and shadow objects represented by a fuzzy landscape is important for building extraction.

Historical Land-Cover Change and Land-Use Conversions Global Dataset

Data.gov (United States)

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...

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.

Development of 2010 national land cover database for the Nepal.

Science.gov (United States)

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.

Nitrate-nitrogen losses through subsurface drainage under various agricultural land covers.

Science.gov (United States)

Qi, Zhiming; Helmers, Matthew J; Christianson, Reid D; Pederson, Carl H

2011-01-01

Nitrate-nitrogen (NO₃-N) loading to surface water bodies from subsurface drainage is an environmental concern in the midwestern United States. The objective of this study was to investigate the effect of various land covers on NO₃-N loss through subsurface drainage. Land-cover treatments included (i) conventional corn ( L.) (C) and soybean [ (L.) Merr.] (S); (ii) winter rye ( L.) cover crop before corn (rC) and before soybean (rS); (iii) kura clover ( M. Bieb.) as a living mulch for corn (kC); and (iv) perennial forage of orchardgrass ( L.) mixed with clovers (PF). In spring, total N uptake by aboveground biomass of rye in rC, rye in rS, kura clover in kC, and grasses in PF were 14.2, 31.8, 87.0, and 46.3 kg N ha, respectively. Effect of land covers on subsurface drainage was not significant. The NO₃-N loss was significantly lower for kC and PF than C and S treatments (p rye cover crop did not reduce NO₃-N loss, but NO₃-N concentration was significantly reduced in rC during March to June and in rS during July to November (p rye cover crop on NO-N loss reduction needs further investigation under conditions of different N rates, wider weather patterns, and fall tillage. by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

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 ...

Forecasting land cover change impacts on drinking water treatment costs in Minneapolis, Minnesota

Science.gov (United States)

Woznicki, S. A.; Wickham, J.

2017-12-01

Source protection is a critical aspect of drinking water treatment. The benefits of protecting source water quality in reducing drinking water treatment costs are clear. However, forecasting the impacts of environmental change on source water quality and its potential to influence future treatment processes is lacking. The drinking water treatment plant in Minneapolis, MN has recognized that land cover change threatens water quality in their source watershed, the Upper Mississippi River Basin (UMRB). Over 1,000 km2 of forests, wetlands, and grasslands in the UMRB were lost to agriculture from 2008-2013. This trend, coupled with a projected population increase of one million people in Minnesota by 2030, concerns drinking water treatment plant operators in Minneapolis with respect to meeting future demand for clean water in the UMRB. The objective of this study is to relate land cover change (forest and wetland loss, agricultural expansion, urbanization) to changes in treatment costs for the Minneapolis, MN drinking water utility. To do this, we first developed a framework to determine the relationship between land cover change and water quality in the context of recent historical changes and projected future changes in land cover. Next we coupled a watershed model, the Soil and Water Assessment Tool (SWAT) to projections of land cover change from the FOREcasting SCEnarios of Land-use Change (FORE-SCE) model for the mid-21st century. Using historical Minneapolis drinking water treatment data (chemical usage and costs), source water quality in the UMRB was linked to changes in treatment requirements as a function of projected future land cover change. These analyses will quantify the value of natural landscapes in protecting drinking water quality and future treatment processes requirements. In addition, our study provides the Minneapolis drinking water utility with information critical to their planning and capital improvement process.

The impact of Future Land Use and Land Cover Changes on Atmospheric Chemistry-Climate Interactions

NARCIS (Netherlands)

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

Next generation of global land cover characterization, mapping, and monitoring

Science.gov (United States)

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).

VT Generalized Land Cover Land Use for Champlain Basin - SAL 1992

Data.gov (United States)

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...

VT Generalized Land Cover Land Use for Champlain Basin - SAL 2001

Data.gov (United States)

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...

National Land Cover Database 2001 (NLCD01)

Science.gov (United States)

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.

Structural knowledge learning from maps for supervised land cover/use classification: Application to the monitoring of land cover/use maps in French Guiana

Science.gov (United States)

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.

A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data

Directory of Open Access Journals (Sweden)

Salman Qadri

2016-01-01

Full Text Available The main objective of this study is to find out the importance of machine vision approach for the classification of five types of land cover data such as bare land, desert rangeland, green pasture, fertile cultivated land, and Sutlej river land. A novel spectra-statistical framework is designed to classify the subjective land cover data types accurately. Multispectral data of these land covers were acquired by using a handheld device named multispectral radiometer in the form of five spectral bands (blue, green, red, near infrared, and shortwave infrared while texture data were acquired with a digital camera by the transformation of acquired images into 229 texture features for each image. The most discriminant 30 features of each image were obtained by integrating the three statistical features selection techniques such as Fisher, Probability of Error plus Average Correlation, and Mutual Information (F + PA + MI. Selected texture data clustering was verified by nonlinear discriminant analysis while linear discriminant analysis approach was applied for multispectral data. For classification, the texture and multispectral data were deployed to artificial neural network (ANN: n-class. By implementing a cross validation method (80-20, we received an accuracy of 91.332% for texture data and 96.40% for multispectral data, respectively.

Anthropogenic Influences in Land Use/Land Cover Changes in Mediterranean Forest Landscapes in Sicily

Directory of Open Access Journals (Sweden)

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.

Impact of land cover and land use change on runoff characteristics.

Science.gov (United States)

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

Impacts of land use/cover classification accuracy on regional climate simulations

Science.gov (United States)

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.

Land-cover change research at the U.S. Geological Survey-assessing our nation's dynamic land surface

Science.gov (United States)

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.

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...

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.

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.

Theorizing Land Cover and Land Use Changes: The Case of Tropical Deforestation

Science.gov (United States)

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.

The managed clearing: An overlooked land-cover type in urbanizing regions?

Science.gov (United States)

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

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.

Trajectory analysis of land use and land cover maps to improve spatial-temporal patterns, and impact assessment on groundwater recharge

Science.gov (United States)

Zomlot, Z.; Verbeiren, B.; Huysmans, M.; Batelaan, O.

2017-11-01

Land use/land cover (LULC) change is a consequence of human-induced global environmental change. It is also considered one of the major factors affecting groundwater recharge. Uncertainties and inconsistencies in LULC maps are one of the difficulties that LULC timeseries analysis face and which have a significant effect on hydrological impact analysis. Therefore, an accuracy assessment approach of LULC timeseries is needed for a more reliable hydrological analysis and prediction. The objective of this paper is to assess the impact of land use uncertainty and to improve the accuracy of a timeseries of CORINE (coordination of information on the environment) land cover maps by using a new approach of identifying spatial-temporal LULC change trajectories as a pre-processing tool. This ensures consistency of model input when dealing with land-use dynamics and as such improves the accuracy of land use maps and consequently groundwater recharge estimation. As a case study the impact of consistent land use changes from 1990 until 2013 on groundwater recharge for the Flanders-Brussels region is assessed. The change trajectory analysis successfully assigned a rational trajectory to 99% of all pixels. The methodology is shown to be powerful in correcting interpretation inconsistencies and overestimation errors in CORINE land cover maps. The overall kappa (cell-by-cell map comparison) improved from 0.6 to 0.8 and from 0.2 to 0.7 for forest and pasture land use classes respectively. The study shows that the inconsistencies in the land use maps introduce uncertainty in groundwater recharge estimation in a range of 10-30%. The analysis showed that during the period of 1990-2013 the LULC changes were mainly driven by urban expansion. The results show that the resolution at which the spatial analysis is performed is important; the recharge differences using original and corrected CORINE land cover maps increase considerably with increasing spatial resolution. This study indicates

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 ...

The effects of changing land cover on streamflow simulation in Puerto Rico

Science.gov (United States)

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.

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 ...

Comparison of two Classification methods (MLC and SVM) to extract land use and land cover in Johor Malaysia

Science.gov (United States)

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.

Comparison of two Classification methods (MLC and SVM) to extract land use and land cover in Johor Malaysia

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

LAND COVER ASSESSMENT OF INDIGENOUS COMMUNITIES IN THE BOSAWAS REGION OF NICARAGUA

Science.gov (United States)

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...

The impact of land use/land cover changes on land degradation dynamics: a Mediterranean case study.

Science.gov (United States)

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.

The Impact of Land Use/Land Cover Changes on Land Degradation Dynamics: A Mediterranean Case Study

Science.gov (United States)

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.

Land cover change detection of Hatiya Island, Bangladesh, using remote sensing techniques

Science.gov (United States)

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.

GENERATION OF 2D LAND COVER MAPS FOR URBAN AREAS USING DECISION TREE CLASSIFICATION

DEFF Research Database (Denmark)

Höhle, Joachim

2014-01-01

A 2D land cover map can automatically and efficiently be generated from high-resolution multispectral aerial images. First, a digital surface model is produced and each cell of the elevation model is then supplemented with attributes. A decision tree classification is applied to extract map objects...... of stereo-observations of false-colour stereopairs. The stratified statistical assessment of the produced land cover map with six classes and based on 91 points per class reveals a high thematic accuracy for classes ‘building’ (99%, 95% CI: 95%-100%) and ‘road and parking lot’ (90%, 95% CI: 83%-95%). Some...

Land cover mapping after the tsunami event over Nanggroe Aceh Darussalam (NAD) province, Indonesia

Science.gov (United States)

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.

Land cover change of watersheds in Southern Guam from 1973 to 2001.

Science.gov (United States)

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.

Operational monitoring of land-cover change using multitemporal remote sensing data

Science.gov (United States)

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

Error and Uncertainty in the Accuracy Assessment of Land Cover Maps

Science.gov (United States)

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

Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery

OpenAIRE

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...

Internal Migration and Land Use and Land Cover Changes in the Middle Mountains of Nepal

Directory of Open Access Journals (Sweden)

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.

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)

Tularosa, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

Data.gov (United States)

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...

Carbon dioxide emissions from forestry and peat land using land-use/land-cover changes in North Sumatra, Indonesia

Science.gov (United States)

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.

Using remote sensing imagery and GIS to identify land cover and land use within Ceahlau Massif (Romania

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%

Land use, population dynamics, and land-cover change in Eastern Puerto Rico

Science.gov (United States)

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 Survey’s Water, Energy, and Biogeochemical Budgets (WEBB) program. This region occupies an area of 1,616 square kilometers, about 18 percent of the total land...

Image-based change estimation for land cover and land use monitoring

Science.gov (United States)

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...

A proposed periodic national inventory of land use land cover change

Science.gov (United States)

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...

Quantifying outdoor water consumption of urban land use/land cover: sensitivity to drought.

Science.gov (United States)

Kaplan, Shai; Myint, Soe W; Fan, Chao; Brazel, Anthony J

2014-04-01

Outdoor water use is a key component in arid city water systems for achieving sustainable water use and ensuring water security. Using evapotranspiration (ET) calculations as a proxy for outdoor water consumption, the objectives of this research are to quantify outdoor water consumption of different land use and land cover types, and compare the spatio-temporal variation in water consumption between drought and wet years. An energy balance model was applied to Landsat 5 TM time series images to estimate daily and seasonal ET for the Central Arizona Phoenix Long-Term Ecological Research region (CAP-LTER). Modeled ET estimations were correlated with water use data in 49 parks within CAP-LTER and showed good agreement (r² = 0.77), indicating model effectiveness to capture the variations across park water consumption. Seasonally, active agriculture shows high ET (>500 mm) for both wet and dry conditions, while the desert and urban land cover types experienced lower ET during drought (<300 mm). Within urban locales of CAP-LTER, xeric neighborhoods show significant differences from year to year, while mesic neighborhoods retain their ET values (400-500 mm) during drought, implying considerable use of irrigation to sustain their greenness. Considering the potentially limiting water availability of this region in the future due to large population increases and the threat of a warming and drying climate, maintaining large water-consuming, irrigated landscapes challenges sustainable practices of water conservation and the need to provide amenities of this desert area for enhancing quality of life.

Influence of land development on stormwater runoff from a mixed land use and land cover catchment.

Science.gov (United States)

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.

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.

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

High spatial resolution mapping of land cover types in a priority area for conservation in the Brazilian savanna

Science.gov (United States)

Ribeiro, F.; Roberts, D. A.; Hess, L. L.; Davis, F. W.; Caylor, K. K.; Nackoney, J.; Antunes Daldegan, G.

2017-12-01

Savannas are heterogeneous landscapes consisting of highly mixed land cover types that lack clear distinct boundaries. The Brazilian Cerrado is a Neotropical savanna considered a biodiversity hotspot for conservation due to its biodiversity richness and rapid transformation of its landscape by crop and pasture activities. The Cerrado is one of the most threatened Brazilian biomes and only 2.2% of its original extent is strictly protected. Accurate mapping and monitoring of its ecosystems and adjacent land use are important to select areas for conservation and to improve our understanding of the dynamics in this biome. Land cover mapping of savannas is difficult due to spectral similarity between land cover types resulting from similar vegetation structure, floristically similar components, generalization of land cover classes, and heterogeneity usually expressed as small patch sizes within the natural landscape. These factors are the major contributor to misclassification and low map accuracies among remote sensing studies in savannas. Specific challenges to map the Cerrado's land cover types are related to the spectral similarity between classes of land use and natural vegetation, such as natural grassland vs. cultivated pasture, and forest ecosystem vs. crops. This study seeks to classify and evaluate the land cover patterns across an area ranked as having extremely high priority for future conservation in the Cerrado. The main objective of this study is to identify the representativeness of each vegetation type across the landscape using high to moderate spatial resolution imagery using an automated scheme. A combination of pixel-based and object-based approaches were tested using RapidEye 3A imagery (5m spatial resolution) to classify the Cerrado's major land cover types. The random forest classifier was used to map the major ecosystems present across the area, and demonstrated to have an effective result with 68% of overall accuracy. Post

Quality Evaluation of Land-Cover Classification Using Convolutional Neural Network

Science.gov (United States)

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

Integrative image segmentation optimization and machine learning approach for high quality land-use and land-cover mapping using multisource remote sensing data

Science.gov (United States)

Gibril, Mohamed Barakat A.; Idrees, Mohammed Oludare; Yao, Kouame; Shafri, Helmi Zulhaidi Mohd

2018-01-01

The growing use of optimization for geographic object-based image analysis and the possibility to derive a wide range of information about the image in textual form makes machine learning (data mining) a versatile tool for information extraction from multiple data sources. This paper presents application of data mining for land-cover classification by fusing SPOT-6, RADARSAT-2, and derived dataset. First, the images and other derived indices (normalized difference vegetation index, normalized difference water index, and soil adjusted vegetation index) were combined and subjected to segmentation process with optimal segmentation parameters obtained using combination of spatial and Taguchi statistical optimization. The image objects, which carry all the attributes of the input datasets, were extracted and related to the target land-cover classes through data mining algorithms (decision tree) for classification. To evaluate the performance, the result was compared with two nonparametric classifiers: support vector machine (SVM) and random forest (RF). Furthermore, the decision tree classification result was evaluated against six unoptimized trials segmented using arbitrary parameter combinations. The result shows that the optimized process produces better land-use land-cover classification with overall classification accuracy of 91.79%, 87.25%, and 88.69% for SVM and RF, respectively, while the results of the six unoptimized classifications yield overall accuracy between 84.44% and 88.08%. Higher accuracy of the optimized data mining classification approach compared to the unoptimized results indicates that the optimization process has significant impact on the classification quality.

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

C-CAP Niihau 2005 Land Cover

Data.gov (United States)

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...

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 ...

Minnesota Land Use and Cover - A 1990's Census of the Land - Tiled

Data.gov (United States)

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...

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...

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

The GOFC-GOLD/CEOS Land Cover Harmonization and Validation Initiative: Technical Design and Implementation

Science.gov (United States)

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

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...

Land-Use and Land-Cover Change around Mobile Bay, Alabama from 1974-2008

Science.gov (United States)

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

Estimating Accuracy of Land-Cover Composition From Two-Stage Clustering Sampling

Science.gov (United States)

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), ...

The Effect of Land Cover Change on Soil Properties around Kibale National Park in South Western Uganda

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.

Identifying Generalizable Image Segmentation Parameters for Urban Land Cover Mapping through Meta-Analysis and Regression Tree Modeling

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

Analysis and Modeling of Urban Land Cover Change in Setúbal and Sesimbra, Portugal

Directory of Open Access Journals (Sweden)

Yikalo H. Araya

2010-06-01

Full Text Available The expansion of cities entails the abandonment of forest and agricultural lands, and these lands’ conversion into urban areas, which results in substantial impacts on ecosystems. Monitoring these changes and planning urban development can be successfully achieved using multitemporal remotely sensed data, spatial metrics, and modeling. In this paper, urban land use change analysis and modeling was carried out for the Concelhos of Setúbal and Sesimbra in Portugal. An existing land cover map for the year 1990, together with two derived land cover maps from multispectral satellite images for the years 2000 and 2006, were utilized using an object-oriented classification approach. Classification accuracy assessment revealed satisfactory results that fulfilled minimum standard accuracy levels. Urban land use dynamics, in terms of both patterns and quantities, were studied using selected landscape metrics and the Shannon Entropy index. Results show that urban areas increased by 91.11% between 1990 and 2006. In contrast, the change was only 6.34% between 2000 and 2006. The entropy value was 0.73 for both municipalities in 1990, indicating a high rate of urban sprawl in the area. In 2006, this value, for both Sesimbra and Setúbal, reached almost 0.90. This is demonstrative of a tendency toward intensive urban sprawl. Urban land use change for the year 2020 was modeled using a Cellular Automata based approach. The predictive power of the model was successfully validated using Kappa variations. Projected land cover changes show a growing tendency in urban land use, which might threaten areas that are currently reserved for natural parks and agricultural lands.

ISLSCP II IGBP DISCover and SiB Land Cover, 1992-1993

Data.gov (United States)

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...

NLCD - MODIS land cover- albedo dataset for the continental United States

Data.gov (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...

CLC2000 land cover database of the Netherlands; monitoring land cover changes between 1986 and 2000

NARCIS (Netherlands)

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

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...

Land-cover effects on soil organic carbon stocks in a European city.

Science.gov (United States)

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 �

LBA-ECO ND-01 Land Cover Classification, Rondonia, Brazil: 1975-2000

Data.gov (United States)

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...

Multitemporal analysis of Landsat images to detect land use land cover changes for monitoring soil sealing in the Nola area (Naples, Italy)

Science.gov (United States)

De Giglio, Michaela; Allocca, Maria; Franci, Francesca

2016-10-01

Land Use Land Cover Changes (LULCC) data provide objective information to support environmental policy, urban planning purposes and sustainable land development. Understanding of past land use/cover practices and current landscape patterns is critical to assess the effects of LULCC on the Earth system. Within the framework of soil sealing in Italy, the present study aims to assess the LULCC of the Nola area (Naples metropolitan area, Italy), relating to a thirty year period from 1984 to 2015. The urban sprawl affects this area causing the impervious surface increase, the loss in rural areas and landscape fragmentation. Located near Vesuvio volcano and crossed by artificial filled rivers, the study area is subject to landslide, hydraulic and volcanic risks. Landsat time series has been processed by means of the supervised per-pixel classification in order to produce multitemporal Land Use Land Cover maps. Then, post-classification comparison approach has been applied to quantify the changes occurring between 1984 and 2015, also analyzing the intermediate variations in 1999, namely every fifteen years. The results confirm the urban sprawl. The increase of the built-up areas mainly causes the habitat fragmentation and the agricultural land conversion of the Nola area that is already damaged by unauthorized disposal of urban waste. Moreover, considering the local risk maps, it was verified that some of the new urban areas were built over known hazardous sites. In order to limit the soil sealing, urgent measures and sustainable urban planning are required.

Effects of land use and land cover changes on water quality in the uMngeni river catchment, South Africa

Science.gov (United States)

Namugize, Jean Nepomuscene; Jewitt, Graham; Graham, Mark

2018-06-01

Land use and land cover change are major drivers of water quality deterioration in watercourses and impoundments. However, understanding of the spatial and temporal variability of land use change characteristics and their link to water quality parameters in catchments is limited. As a contribution to address this limitation, the objective of this study is to assess the linkages between biophysico-chemical water quality parameters and land use and land cover (LULC) classes in the upper reaches of the uMngeni Catchment, a rapidly developing catchment in South Africa. These were assessed using Geographic Information Systems tools and statistical analyses for the years 1994, 2000, 2008 and 2011 based on changes over time of eight LULC classes and available water quality information. Natural vegetation, forest plantations and cultivated areas occupy 85% of the catchment. Cultivated, urban/built-up and degraded areas increased by 6%, 4.5% and 3%, respectively coinciding with a decrease in natural vegetation by 17%. Variability in the concentration of water quality parameters from 1994 to 2011 and an overall decline in water quality were observed. Escherichia coli (E. coli) levels exceeding the recommended guidelines for recreation and public health protection was noted as a major issue at seven of the nine sampling points. Overall, water supply reservoirs in the catchment retained over 20% of nutrients and over 85% of E. coli entering them. A relationship between land use types and water quality variables was found. However, the degree and magnitude of the associations varies between sub-catchments and is difficult to quantify. This highlights the complexity and the site-specific nature of relationships between land use types and water quality parameters in the catchment. Thus, this study provides useful findings on the general relationship between land use and land cover and water quality degradation, but highlights the risks of applying simple relationships or adding

Four decades of land-cover, land-use and hydroclimatology changes in the Itacaiúnas River watershed, southeastern Amazon.

Science.gov (United States)

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

Gallup, NM AZ 1:250,000 Quad USGS Land Use/Land Cover, 1986

Data.gov (United States)

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...

Santa Fe, NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

Data.gov (United States)

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...

Projecting land-use and land cover change in a subtropical urban watershed

Science.gov (United States)

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...

Land use and land cover dynamics in the Brazilian Amazon: an overview

Science.gov (United States)

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...

Land use/cover classification in the Brazilian Amazon using satellite images.

Science.gov (United States)

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.

Land and Forest Management by Land Use/ Land Cover Analysis and Change Detection Using Remote Sensing and GIS

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.

Integrated modelling of anthropogenic land-use and land-cover change on the global scale

Science.gov (United States)

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

Change In Minimum Temperature As A Response To Land Cover Change In South Florida

Science.gov (United States)

Kandel, H. P.; Melesse, A. M.

2012-12-01

Replacement of higher evapotranspirative surface materials such as water and vegetation cover by other materials such as buildings, roads, and pavements increases the Bowen's ratio from about 0.5-2.0 in rural to about ≈ 5.0 in urban areas resulting in higher surface and near surface atmospheric temperatures in the urban areas (Taha, 1997). This effect is intensified by low emissivity surfaces of the urban covers storing more heat energy during day time, but emitting less during night compared to the energy emitted by rural covers causing higher night time temperatures in urban centers, an effect called Urban Heat Island (UHI). South Florida has undergone tremendous land cover change from its pre-drainage vegetated and wetlands to post drainage agricultural and urban lands, especially after late 20th century. The objective of this study was to simultaneously analyze the land use/ land cover change and the rural/ urban minimum temperatures in south Florida for the period representing pre and post drainage states. The result shows urban sprawl increased from 8% at the beginning of the analysis period to about 14% at the end. Green vegetated areas, shrubs, and forests are found to be declined. The minimum temperature is found increased as maximum as 2°F in the urbanized stations, which remained constant or shows negligible increase in rural stations. The study dictates further micro level scrutiny in order to reach a conclusion on the development of UHI in south Florida. Key words: Bowen's ratio, emissivity, urban heat island

Modelling land change: the issue of use and cover in wide-scale applications

NARCIS (Netherlands)

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

Gross and net land cover changes in the main plant functional types derived from the annual ESA CCI land cover maps (1992-2015)

Science.gov (United States)

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

Landspotting: collecting essential land cover information via an attractive internet game

Science.gov (United States)

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

C-CAP Santa Cruz 2001 era High Resolution Land Cover Metadata

Data.gov (United States)

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...

A Continental United States High Resolution NLCD Land Cover – MODIS Albedo Database to Examine Albedo and Land Cover Change Relationships

Science.gov (United States)

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...

National Land Cover Database (NLCD) Percent Developed Imperviousness Collection

Data.gov (United States)

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...

Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey.

Science.gov (United States)

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.

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.

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.

Using the FORE-SCE model to project land-cover change in the southeastern United States

Science.gov (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

Research on Land Surface Thermal-Hydrologic Exchange in Southern China under Future Climate and Land Cover Scenarios

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.

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.

LAND USE/LAND COVER CHANGES IN SEMI-ARID MOUNTAIN LANDSCAPE IN SOUTHERN INDIA: A GEOINFORMATICS BASED MARKOV CHAIN APPROACH

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.

Land Use/land Cover Changes in Semi-Arid Mountain Landscape in Southern India: a Geoinformatics Based Markov Chain Approach

Science.gov (United States)

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.

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.

A simple semi-automatic approach for land cover classification from multispectral remote sensing imagery.

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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.

Effect of land-use/land-cover change on the future of rainfed agriculture in the Jenin Governorate, Palestine

NARCIS (Netherlands)

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

Assessment of Land-Use/Land-Cover Change and Forest Fragmentation in the Garhwal Himalayan Region of India

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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.

Effect of landslides on the structural characteristics of land-cover based on complex networks

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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.

[Application of optical flow dynamic texture in land use/cover change detection].

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Yan, Li; Gong, Yi-Long; Zhang, Yi; Duan, Wei

2014-11-01

In the present study, a novel change detection approach for high resolution remote sensing images is proposed based on the optical flow dynamic texture (OFDT), which could achieve the land use & land cover change information automatically with a dynamic description of ground-object changes. This paper describes the ground-object gradual change process from the principle using optical flow theory, which breaks the ground-object sudden change hypothesis in remote sensing change detection methods in the past. As the steps of this method are simple, it could be integrated in the systems and software such as Land Resource Management and Urban Planning software that needs to find ground-object changes. This method takes into account the temporal dimension feature between remote sensing images, which provides a richer set of information for remote sensing change detection, thereby improving the status that most of the change detection methods are mainly dependent on the spatial dimension information. In this article, optical flow dynamic texture is the basic reflection of changes, and it is used in high resolution remote sensing image support vector machine post-classification change detection, combined with spectral information. The texture in the temporal dimension which is considered in this article has a smaller amount of data than most of the textures in the spatial dimensions. The highly automated texture computing has only one parameter to set, which could relax the onerous manual evaluation present status. The effectiveness of the proposed approach is evaluated with the 2011 and 2012 QuickBird datasets covering Duerbert Mongolian Autonomous County of Daqing City, China. Then, the effects of different optical flow smooth coefficient and the impact on the description of the ground-object changes in the method are deeply analyzed: The experiment result is satisfactory, with an 87.29% overall accuracy and an 0.850 7 Kappa index, and the method achieves better

Land cover change mapping using MODIS time series to improve emissions inventories

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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.

Land cover change in coastal watersheds 1996 to 2010

Science.gov (United States)

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...

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 ...

Land Cover Mapping using GEOBIA to Estimate Loss of Salacca zalacca Trees in Landslide Area of Clapar, Madukara District of Banjarnegara

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Permata, Anggi; Juniansah, Anwar; Nurcahyati, Eka; Dimas Afrizal, Mousafi; Adnan Shafry Untoro, Muhammad; Arifatha, Na'ima; Ramadhani Yudha Adiwijaya, Raden; Farda, Nur Mohammad

2016-11-01

Landslide is an unpredictable natural disaster which commonly happens in highslope area. Aerial photography in small format is one of acquisition method that can reach and obtain high resolution spatial data faster than other methods, and provide data such as orthomosaic and Digital Surface Model (DSM). The study area contained landslide area in Clapar, Madukara District of Banjarnegara. Aerial photographs of landslide area provided advantage in objects visibility. Object's characters such as shape, size, and texture were clearly seen, therefore GEOBIA (Geography Object Based Image Analysis) was compatible as method for classifying land cover in study area. Dissimilar with PPA (PerPixel Analyst) method that used spectral information as base object detection, GEOBIA could use spatial elements as classification basis to establish a land cover map with better accuracy. GEOBIA method used classification hierarchy to divide post disaster land cover into three main objects: vegetation, landslide/soil, and building. Those three were required to obtain more detailed information that can be used in estimating loss caused by landslide and establishing land cover map in landslide area. Estimating loss in landslide area related to damage in Salak (Salacca zalacca) plantations. This estimation towards quantity of Salak tree that were drifted away by landslide was calculated in assumption that every tree damaged by landslide had same age and production class with other tree that weren't damaged. Loss calculation was done by approximating quantity of damaged trees in landslide area with data of trees around area that were acquired from GEOBIA classification method.

The Significance of Land Cover Delineation on Soil Erosion Assessment.

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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.

Impact of neighbourhood land-cover in epiphytic lichen diversity: Analysis of multiple factors working at different spatial scales

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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.

Impact of neighbourhood land-cover in epiphytic lichen diversity: Analysis of multiple factors working at different spatial scales

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

Land Use-Land Cover dynamics of Huluka watershed, Central Rift Valley, Ethiopia

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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.

Multisource Data Fusion Framework for Land Use/Land Cover Classification Using Machine Vision

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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.

IRSeL-An approach to enhance continuity and accuracy of remotely sensed land cover data

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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

Measuring land-use and land-cover change using the U.S. department of agriculture's cropland data layer: Cautions and recommendations

Science.gov (United States)

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.

Constraining the Deforestation History of Europe: Evaluation of Historical Land Use Scenarios with Pollen-Based Land Cover Reconstructions

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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.

El Paso, TX NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

Data.gov (United States)

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...

Las Cruces, NM TX 1:250,000 Quad USGS Land Use/Land Cover, 1986

Data.gov (United States)

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...

Saint Johns, AZ NM 1:250,000 Quad USGS Land Use/Land Cover, 1986

Data.gov (United States)

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...

Silver City, NM AZ 1:250,000 Quad USGS Land Use/Land Cover, 1986

Data.gov (United States)

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...

Land-Use and Land-Cover Mapping Using a Gradable Classification Method

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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.

Relationship between Organic Carbon Runoff to River and Land Cover

Science.gov (United States)

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.

Generating local scale land use/cover change scenarios: case studies of high-risk mountain areas

Science.gov (United States)

Malek, Žiga; Glade, Thomas; Boerboom, Luc

2014-05-01

including: qualitative methods such as interviews, group discussions and fuzzy cognitive mapping to identify land use/cover change processes, their driving forces and possible consequences, and final scenario generation; and geospatial methods such as GIS, geostatistics and environmental modeling in an environment for geoprocessing objects (Dinamica EGO) for spatial allocation of these scenarios. The methods were applied in the Italian Alps and the Romanian Carpathians. Both are mountainous areas, however they differ in terms of past and most likely future socio-economic development, and therefore consequent land use/cover changes. Whereas we focused on urban expansion due to tourism development in the Alps, we focused on possible deforestation trajectories in the Carpathians. In both areas, the recognized most significant driving forces were either not covered by accessible data, or were characterized as intangible. With the proposed framework we were able to generate futures scenarios despite these shortcomings, and enabling the transferability of the method.

Meter-scale Urban Land Cover Mapping for EPA EnviroAtlas Using Machine Learning and OBIA Remote Sensing Techniques

Science.gov (United States)

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.

Quantifying the Effects of Historical Land Cover Conversion Uncertainty on Global Carbon and Climate Estimates

Science.gov (United States)

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.

Coastal landuse and land cover change and transformations of Kanyakumari coast, India using remote sensing and GIS

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S. Kaliraj

2017-12-01

Full Text Available The coastal landuse and land cover features in the South West coast of Kanyakumari are dynamically regulated due to marine and terrestrial processes and often controlling by natural and anthropogenic activities. The primary objective of this study is to estimate the decadal changes and their transformations of landuse and land cover (LULC features under Level II category of USGS-LULC Classification System using Landsat ETM+ and TM images using Maximum Likelihood Classifier (MLC algorithm for the period 2000–2011. The classified LULC features are categorized as beachface land cover, cultivable lands, plantation and shrub vegetation, fallow land, barren land, settlements and built-ups, water bodies, and mining area, etc. The geo-database is prepared for LULC feature class with an attributes of name, location, area and spatial distribution, etc. It shows the larger area in beachface land cover (sandy beaches, foredunes, uplands, Teri dunes (laterite and associated nearshore landforms, plantations, cultivable lands, fallows, and barren lands are converted into built-ups and it increases more than twice in the period of 10 years. Using GIS techniques, the analysis of change detection matrix reveals that the total area of 45.90 km2 in different LULC features periodically shifted or transformed from one state to another one or more states, i.e. the beachface land cover area of 1.24 km2 is encroached for built-ups and 0.63 km2 for placer mining during the decade. Meanwhile, the area of 0.21 km2 in this cover is transformed into wetlands and saltwater bodies. During the past decade, the expansion of area in the built-ups and settlements are directly proportional to the growth of population, which produces severe threat to the coastal resources. Accuracy assessment of classified images shows the overall accuracy is estimated as 81.16% and 77.52% and overall Kappa coeffient statistical values of 0.83 and 0.76 for the year 2000 and 2011 respectively

A procedure to obtain a refined European land use/cover map

NARCIS (Netherlands)

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

Land use and land cover dynamics on the campus of Federal University of Lavras from 1964 to 2009

Directory of Open Access Journals (Sweden)

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.

A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi

Science.gov (United States)

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

Land use, land cover, and drainage on the Albemarle-Pamlico Peninsula, Eastern North Carolina, 1974

Science.gov (United States)

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.

EnviroAtlas - Paterson, NJ - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

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...

The Effect Of Land Cover/Land Use On Groundwater Resources In Southern Egypt (Luxor Area): Remote Sensing And Field Studies

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

Surface erosion and hydrology of earth covers used in shallow land burial of low-level radioactive waste

International Nuclear Information System (INIS)

Bent, G.C.

1988-01-01

Shallow land burial is the current method of disposal of low-level radioactive waste in the United States. The most serious technical problems encountered in shallow land burial are water-related. Water is reported to come into contact with the waste by erosion of earth covers or through infiltration of precipitation through the earth covers. The objectives of this study were to: compare and evaluate the effects of crested wheatgrass and streambank wheatgrass on surface erosion of simulated earth covers at Idaho National Engineering Laboratory (INEL), characterize the surface hydrology, and estimate cumulative soil loss for average and extreme rainfall events and determine if the waste will become exposed during its burial life due to erosion. 30 refs., 26 figs., 21 tabs

Land Use and Land Cover - LAND_COVER_PRESETTLEMENT_IDNR_IN: Generalized Presettlement Vegetation Types of Indiana, Circa 1820 (Indiana Department of Natural Resources, Polygon Shapefile)

Data.gov (United States)

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...

Conversion of land use and cover in northwest Amazon (Brazil

Directory of Open Access Journals (Sweden)

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.

Geospatial Analysis of Land Use and Land Cover Changes for Discharge at Way Kualagaruntang Watershed in Bandar Lampung

OpenAIRE

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 ...

Global land cover mapping at 30 m resolution: A POK-based operational approach

Science.gov (United States)

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

A stochastic Forest Fire Model for future land cover scenarios assessment

Directory of Open Access Journals (Sweden)

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.

LBA-ECO LC-01 Landsat TM Land Use/Land Cover, Northern Ecuadorian Amazon: 1986-1999

Data.gov (United States)

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:...

LBA-ECO LC-01 Landsat TM Land Use/Land Cover, Northern Ecuadorian Amazon: 1986-1999

Data.gov (United States)

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,...

Land Cover as a Framework For Assessing the Risk of Water Pollution

Science.gov (United States)

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...

Implementación de la metodología Corine Land Cover con imágenes Ikonos The Corine Land Cover method based on Ikonos images

Directory of Open Access Journals (Sweden)

Germán Mauricio Valencia Hernández

2009-07-01

Colombian Andes. The specific objectives were: identify potentialities and limitations, adjust the CLC legend to the Colombia conditions and improve the level of detail using a Geo Ikonos product. With these methods an increase in crops and a decrease in area of forests and grasslands were found. These methods can be used to update land cover when a high level of detail is required. It is recommended to minimize geometric errors using orthorectified images were high slopes are present, like along the Colombian Andes.

Pairing FLUXNET sites to validate model representations of land-use/land-cover change

Science.gov (United States)

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.

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.

A land-cover map for South and Southeast Asia derived from SPOT-VEGETATION data

Science.gov (United States)

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

Aim  Our aim was to produce a uniform ‘regional’ land-cover map of South and Southeast Asia based on ‘sub-regional’ mapping results generated in the context of the Global Land Cover 2000 project.Location  The ‘region’ of tropical and sub-tropical South and Southeast Asia stretches from the Himalayas and the southern border of China in the north, to Sri Lanka and Indonesia in the south, and from Pakistan in the west to the islands of New Guinea in the far east.Methods  The regional land-cover map is based on sub-regional digital mapping results derived from SPOT-VEGETATION satellite data for the years 1998–2000. Image processing, digital classification and thematic mapping were performed separately for the three sub-regions of South Asia, continental Southeast Asia, and insular Southeast Asia. Landsat TM images, field data and existing national maps served as references. We used the FAO (Food and Agriculture Organization) Land Cover Classification System (LCCS) for coding the sub-regional land-cover classes and for aggregating the latter to a uniform regional legend. A validation was performed based on a systematic grid of sample points, referring to visual interpretation from high-resolution Landsat imagery. Regional land-cover area estimates were obtained and compared with FAO statistics for the categories ‘forest’ and ‘cropland’.Results  The regional map displays 26 land-cover classes. The LCCS coding provided a standardized class description, independent from local class names; it also allowed us to maintain the link to the detailed sub-regional land-cover classes. The validation of the map displayed a mapping accuracy of 72% for the dominant classes of ‘forest’ and ‘cropland’; regional area estimates for these classes correspond reasonably well to existing regional statistics.Main conclusions  The land-cover map of South and Southeast Asia provides a synoptic view of the distribution of land cover of tropical and sub

LAND COVER CHANGE MONITORING OF TYPICAL FUNCTIONAL COMMUNITIES OF SICHUAN PROVINCE BASED ON ZY-3 DATA

Directory of Open Access Journals (Sweden)

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 %.

Land Cover Change Monitoring of Typical Functional Communities of Sichuan Province Based on ZY-3 Data

Science.gov (United States)

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 %.

Land User and Land Cover Maps of Europe: a Webgis Platform

Science.gov (United States)

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.

Carbon stock projection in North Sumatera using multi objective land allocation approach

Science.gov (United States)

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.

Interrelationships between soil cover and plant cover depending on land use

Directory of Open Access Journals (Sweden)

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.

Land Cover Classification from Multispectral Data Using Computational Intelligence Tools: A Comparative Study

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.

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.

Land use/land cover change geo-informative Tupu of Nujiang River in Northwest Yunnan Province

Science.gov (United States)

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

Impact of land cover and population density on land surface temperature: case study in Wuhan, China

Science.gov (United States)

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.

Evaluation of historical land cover, land use, and land-use change emissions in the GCAM integrated assessment model

Science.gov (United States)

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.

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 ...

Combining NLCD and MODIS to create a land cover-albedo database for the continental United States

Science.gov (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.

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.

Shiprock, AZ NM CO UT 1:250,000 Quad USGS Land Use/Land Cover, 1986

Data.gov (United States)

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...

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.

Tropical land use land cover mapping in Pará (Brazil) using discriminative Markov random fields and multi-temporal TerraSAR-X data

Science.gov (United States)

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.

Brownfield, TX 1:250,000 Quad USGS Land Use/Land Cover, 2000

Data.gov (United States)

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)...

Dalhart, TX 1:250,000 Quad USGS Land Use/Land Cover, 2000

Data.gov (United States)

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)...

Hobbs, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000

Data.gov (United States)

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)...

Clovis, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000

Data.gov (United States)

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)...

Tucumcari, NM 1:250,000 Quad USGS Land Use/Land Cover, 2000

Data.gov (United States)

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)...

Tsunami exposure estimation with land-cover data: Oregon and the Cascadia subduction zone

Science.gov (United States)

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.

Analysing land cover and land use change in the Matobo National Park and surroundings in Zimbabwe

Science.gov (United States)

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

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.

LandSense: A Citizen Observatory and Innovation Marketplace for Land Use and Land Cover Monitoring

Science.gov (United States)

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

Land use/land cover and land capability data for evaluating land utilization and official land use planning in Indramayu Regency, West Java, Indonesia

Science.gov (United States)

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.

Effect of land use and land cover changes on carbon sequestration in vegetation and soils between 1956 and 2007 (southern Spain)

Science.gov (United States)

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.

Mapping of land cover in Northern California with simulated HyspIRI images

Science.gov (United States)

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.

Improving urban land use and land cover classification from high-spatial-resolution hyperspectral imagery using contextual information

Science.gov (United States)

Yang, He; Ma, Ben; Du, Qian; Yang, Chenghai

2010-08-01

In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified class pairs, such as roof and trail, road and roof. These classes may be difficult to be separated because they may have similar spectral signatures and their spatial features are not distinct enough to help their discrimination. In addition, misclassification incurred from within-class trivial spectral variation can be corrected by using pixel connectivity information in a local window so that spectrally homogeneous regions can be well preserved. Our experimental results demonstrate the efficiency of the proposed approaches in classification accuracy improvement. The overall performance is competitive to the object-based SVM classification.

Comparison of regional and global land cover products and the implications for biogenic emission modeling.

Science.gov (United States)

Huang, Ling; McDonald-Buller, Elena; McGaughey, Gary; Kimura, Yosuke; Allen, David T

2015-10-01

Accurate estimates of biogenic emissions are required for air quality models that support the development of air quality management plans and attainment demonstrations. Land cover characterization is an essential driving input for most biogenic emissions models. This work contrasted the global Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product against a regional land cover product developed for the Texas Commissions on Environmental Quality (TCEQ) over four climate regions in eastern Texas, where biogenic emissions comprise a large fraction of the total inventory of volatile organic compounds (VOCs) and land cover is highly diverse. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) was utilized to investigate the influences of land cover characterization on modeled isoprene and monoterpene emissions through changes in the standard emission potential and emission activity factor, both separately and simultaneously. In Central Texas, forest coverage was significantly lower in the MODIS land cover product relative to the TCEQ data, which resulted in substantially lower estimates of isoprene and monoterpene emissions by as much as 90%. Differences in predicted isoprene and monoterpene emissions associated with variability in land cover characterization were primarily caused by differences in the standard emission potential, which is dependent on plant functional type. Photochemical modeling was conducted to investigate the effects of differences in estimated biogenic emissions associated with land cover characterization on predicted ozone concentrations using the Comprehensive Air Quality Model with Extensions (CAMx). Mean differences in maximum daily average 8-hour (MDA8) ozone concentrations were 2 to 6 ppb with maximum differences exceeding 20 ppb. Continued focus should be on reducing uncertainties in the representation of land cover through field validation. Uncertainties in the estimation of biogenic emissions associated with

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.

Open land cover from OpenStreetMap and remote sensing

Science.gov (United States)

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.

Forests as landscapes of social inequality: tropical forest cover and land distribution among shifting cultivators

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.

EnviroAtlas - Des Moines, IA - Meter-Scale Urban Land Cover (MULC) Data (2010)

Data.gov (United States)

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...

Land-Cover Change Detection Using Multi-Temporal MODIS NDVI Imagery

Science.gov (United States)

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...

Spatial Relationships between Biomass Burning and Land Use / Land Cover Dynamics in Northern Sub-Saharan Africa

Science.gov (United States)

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

MODELING OF FUTURE LAND COVER LAND USE CHANGE IN NORTH CAROLINA USING MARKOV CHAIN AND CELLULAR AUTOMATA MODEL

OpenAIRE

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 ...

Land use/land cover in Swisher County and Deaf Smith County locations, Palo Duro Basin, Texas

International Nuclear Information System (INIS)

1984-12-01

Agriculture is the major land use/land cover in the Swisher and Deaf Smith County locations. Most of the agricultural land is irrigated. Furrow, center pivot, and lateral-wheel irrigation systems are in common use. Rangeland is the second most abundant land use/land cover; it is typically associated with stream valleys and playas. The rangeland supports cattle, which are an important source of income. The main urban areas in or near the locations are Tulia and Happy, in Swisher County, and Hereford and Vega, in Deaf Smith County. Most of the land within the locations is privately owned - corporate and government ownership is extremely limited - and large portions are currently under lease for oil exploration. County and regional agencies have no authority to regulate land-use patterns in the locations, although the Panhandle Regional Planning Commission can provide guidance to local jurisdictions. Land use within the corporate limits and extraterritorial jurisdictions of Tulia and Hereford is controlled by zoning ordinances and subdivision regulations. According to projections for the locations, agriculture will remain the major land use in the foreseeable future. Dryland farming and rangeland will become more prevalent as irrigation costs increase and marginal areas are taken out of production

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.

2005 C-CAP Land Cover of Oahu, Hawaii

Data.gov (United States)

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...

Land cover mapping and GIS processing for the Savannah River Site Database

International Nuclear Information System (INIS)

Christel, L.M.; Guber, A.L.

1994-07-01

The Savannah River Site (SRS) is owned by the U.S. Department of Energy and operated by Westinghouse Savannah River Company. Located in Barnwell, Aiken, and Allendale counties in South Carolina, SRS covers an area of approximately 77,700 hectares. Land cover information for SRS was interpreted from color and color infrared aerial photography acquired between 1980 and 1989. The data were then used as the source of the land cover data layer for the SRS sitewide Geographic Information System database. This database provides SRS managers with recent land use information and has been successfully used to support cost-effective site characterization and reclamation

Developing a New North American Land Cover Product at 30m Resolution: Methods, Results and Future Plans

Science.gov (United States)

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.

USGS Land Cover (NLCD) Overlay Map Service from The National Map - National Geospatial Data Asset (NGDA) National Land Cover Database (NLCD)

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — NLCD 1992, NLCD 2001, NLCD 2006, and NLCD 2011 are National Land Cover Database classification schemes based primarily on Landsat data along with ancillary data...

Remote Sensing Image Fusion at the Segment Level Using a Spatially-Weighted Approach: Applications for Land Cover Spectral Analysis and Mapping

Directory of Open Access Journals (Sweden)

Brian Johnson

2015-01-01

Full Text Available Segment-level image fusion involves segmenting a higher spatial resolution (HSR image to derive boundaries of land cover objects, and then extracting additional descriptors of image segments (polygons from a lower spatial resolution (LSR image. In past research, an unweighted segment-level fusion (USF approach, which extracts information from a resampled LSR image, resulted in more accurate land cover classification than the use of HSR imagery alone. However, simply fusing the LSR image with segment polygons may lead to significant errors due to the high level of noise in pixels along the segment boundaries (i.e., pixels containing multiple land cover types. To mitigate this, a spatially-weighted segment-level fusion (SWSF method was proposed for extracting descriptors (mean spectral values of segments from LSR images. SWSF reduces the weights of LSR pixels located on or near segment boundaries to reduce errors in the fusion process. Compared to the USF approach, SWSF extracted more accurate spectral properties of land cover objects when the ratio of the LSR image resolution to the HSR image resolution was greater than 2:1, and SWSF was also shown to increase classification accuracy. SWSF can be used to fuse any type of imagery at the segment level since it is insensitive to spectral differences between the LSR and HSR images (e.g., different spectral ranges of the images or different image acquisition dates.

Assessment of land use/land cover dynamics of Tso Moriri Lake, a Ramsar site in India.

Science.gov (United States)

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.

Vegetation Analysis and Land Use Land Cover Classification of Forest in Uttara Kannada District India Using Remote Sensign and GIS Techniques

Science.gov (United States)

Koppad, A. G.; Janagoudar, B. S.

2017-10-01

The study was conducted in Uttara Kannada districts during the year 2012-2014. The study area lies between 13.92° N to 15.52° N latitude and 74.08° E to 75.09° E longitude with an area of 10,215 km2. The Indian satellite IRS P6 LISS-III imageries were used to classify the land use land cover classes with ground truth data collected with GPS through supervised classification in ERDAS software. The land use and land cover classes identified were dense forest, horticulture plantation, sparse forest, forest plantation, open land and agriculture land. The dense forest covered an area of 63.32 % (6468.70 sq km) followed by agriculture 12.88 % (1315.31 sq. km), sparse forest 10.59 % (1081.37 sq. km), open land 6.09 % (622.37 sq. km), horticulture plantation and least was forest plantation (1.07 %). Settlement, stony land and water body together cover about 4.26 percent of the area. The study indicated that the aspect and altitude influenced the forest types and vegetation pattern. The NDVI map was prepared which indicated that healthy vegetation is represented by high NDVI values between 0.1 and 1. The non- vegetated features such as water bodies, settlement, and stony land indicated less than 0.1 values. The decrease in forest area in some places was due to anthropogenic activities. The thematic map of land use land cover classes was prepared using Arc GIS Software.

Land Use and Land Cover Change, Urban Heat Island Phenomenon, and Health Implications: A Remote Sensing Approach

Science.gov (United States)

Lo, C. P.; Quattrochi, Dale A.

2003-01-01

Land use and land cover maps of Atlanta Metropolitan Area in Georgia were produced from Landsat MSS and TM images for 1973,1979,1983,1987,1992, and 1997, spanning a period of 25 years. Dramatic changes in land use and land cover have occurred with loss of forest and cropland to urban use. In particular, low-density urban use, which includes largely residential use, has increased by over 119% between 1973 and 1997. These land use and land cover changes have drastically altered the land surface characteristics. An analysis of Landsat images revealed an increase in surface temperature and a decline in NDVI from 1973 to 1997. These changes have forced the development of a significant urban heat island effect and an increase in ground level ozone production to such an extent, that Atlanta has violated EPA's ozone level standard in recent years. The urban heat island initiated precipitation events that were identified between 1996 and 2000 tended to occur near high-density urban areas but outside the I-285 loop that traverses around the Central Business District, i.e. not in the inner city area, but some in close proximity to the highways. The health implications were investigated by comparing the spatial patterns of volatile organic compounds (VOC) and nitrogen oxides (NOx) emissions, the two ingredients that form ozone by reacting with sunlight, with those of rates of cardiovascular and chronic lower respiratory diseases. A clear core-periphery pattern was revealed for both VOC and NOx emissions, but the spatial pattern was more random in the cases of rates of cardiovascular and chronic lower respiratory diseases. Clearly, factors other than ozone pollution were involved in explaining the rates of these diseases. Further research is therefore needed to understand the health geography and its relationship to land use and land cover change as well as urban heat island effect. This paper illustrates the usefulness of a remote sensing approach for this purpose.

Changing landscape in the Three Gorges Reservoir Area of Yangtze River from 1977 to 2005: Land use/land cover, vegetation cover changes estimated using multi-source satellite data

Science.gov (United States)

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.

The effects of changing land cover on streamflow simulation in Puerto Rico

Science.gov (United States)

A.E. Van Beusekom; L.E. Hay; R.J. Viger; W.A. Gould; J.A. Collazo; A. Henareh Khalyani

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...

Land-use poverty traps identified in shifting cultivation systems shape long-term tropical forest cover

Science.gov (United States)

Coomes, Oliver T.; Takasaki, Yoshito; Rhemtulla, Jeanine M.

2011-01-01

In this article we illustrate how fine-grained longitudinal analyses of land holding and land use among forest peasant households in an Amazonian village can enrich our understanding of the poverty/land cover nexus. We examine the dynamic links in shifting cultivation systems among asset poverty, land use, and land cover in a community where poverty is persistent and primary forests have been replaced over time—with community enclosure—by secondary forests (i.e., fallows), orchards, and crop land. Land cover change is assessed using aerial photographs/satellite imagery from 1965 to 2007. Household and plot level data are used to track land holding, portfolios, and use as well as land cover over the past 30 y, with particular attention to forest status (type and age). Our analyses find evidence for two important types of “land-use” poverty traps—a “subsistence crop” trap and a “short fallow” trap—and indicate that the initial conditions of land holding by forest peasants have long-term effects on future forest cover and household welfare. These findings suggest a new mechanism driving poverty traps: insufficient initial land holdings induce land use patterns that trap households in low agricultural productivity. Path dependency in the evolution of household land portfolios and land use strategies strongly influences not only the wellbeing of forest people but also the dynamics of tropical deforestation and secondary forest regrowth. PMID:21873179

Land cover classification using reformed fuzzy C-means

Indian Academy of Sciences (India)

This paper uses segmentation based on unsupervised clustering techniques for classification of land cover. ∗ ... and unsupervised classification can be solved by FCM. ..... They also act as input to the development and monitoring of a range of ...

Comparison and assessment of coarse resolution land cover maps for Northern Eurasia

Science.gov (United States)

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...

An Algorithm Approach for the Analysis of Urban Land-Use/Cover: Logic Filters

Directory of Open Access Journals (Sweden)

Şinasi Kaya

2014-11-01

Full Text Available Accurate classification of land-use/cover based on remotely sensed data is important for interpreters who analyze time or event-based change on certain areas. Any method that has user flexibility on area selection provides great simplicity during analysis, since the analyzer may need to work on a specific area of interest instead of dealing with the entire remotely sensed data. The objectives of the paper are to develop an automation algorithm using Matlab & Simulink on user selected areas, to filter V-I-S (Vegetation, Impervious, Soil components using the algorithm, to analyze the components according to upper and lower threshold values based on each band histogram, and finally to obtain land-use/cover map combining the V-I-S components. LANDSAT 5TM satellite data covering Istanbul and Izmit regions are utilized, and 4, 3, 2 (RGB band combination is selected to fulfill the aims of the study. These referred bands are normalized, and V-I-S components of each band are determined. This methodology that uses Matlab & Simulink program is equally successful like the unsupervised and supervised methods. Practices with these methods that lead to qualitative and quantitative assessments of selected urban areas will further provide important spatial information and data especially to the urban planners and decision-makers.

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

Modelling Spatial Compositional Data: Reconstructions of past land cover and uncertainties

DEFF Research Database (Denmark)

Pirzamanbein, Behnaz; Lindström, Johan; Poska, Anneli

2018-01-01

In this paper, we construct a hierarchical model for spatial compositional data, which is used to reconstruct past land-cover compositions (in terms of coniferous forest, broadleaved forest, and unforested/open land) for five time periods during the past $6\\,000$ years over Europe. The model...... to a fast MCMC algorithm. Reconstructions are obtained by combining pollen-based estimates of vegetation cover at a limited number of locations with scenarios of past deforestation and output from a dynamic vegetation model. To evaluate uncertainties in the predictions a novel way of constructing joint...... confidence regions for the entire composition at each prediction location is proposed. The hierarchical model's ability to reconstruct past land cover is evaluated through cross validation for all time periods, and by comparing reconstructions for the recent past to a present day European forest map...

Tracking Land Use/Land Cover Dynamics in Cloud Prone Areas Using Moderate Resolution Satellite Data: A Case Study in Central Africa

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.

Hyperspectral Sensor Data Capability for Retrieving Complex Urban Land Cover in Comparison with Multispectral Data: Venice City Case Study (Italy

Directory of Open Access Journals (Sweden)

Federico Santini

2008-05-01

Full Text Available This study aims at comparing the capability of different sensors to detect land cover materials within an historical urban center. The main objective is to evaluate the added value of hyperspectral sensors in mapping a complex urban context. In this study we used: (a the ALI and Hyperion satellite data, (b the LANDSAT ETM+ satellite data, (c MIVIS airborne data and (d the high spatial resolution IKONOS imagery as reference. The Venice city center shows a complex urban land cover and therefore was chosen for testing the spectral and spatial characteristics of different sensors in mapping the urban tissue. For this purpose, an object-oriented approach and different common classification methods were used. Moreover, spectra of the main anthropogenic surfaces (i.e. roofing and paving materials were collected during the field campaigns conducted on the study area. They were exploited for applying band-depth and sub-pixel analyses to subsets of Hyperion and MIVIS hyperspectral imagery. The results show that satellite data with a 30m spatial resolution (ALI, LANDSAT ETM+ and HYPERION are able to identify only the main urban land cover materials.

Detection and Mapping of Land Use and Land Cover Classes of a ...

African Journals Online (AJOL)

FIRST LADY

Cover Classes of a Developing City in Southeastern. Region of Nigeria .... The emergence of small and medium sized agro-husbandry industries in the peripheral, semi- ..... lack of spatial specialization a hindrance to integrated land management and development .... Journal of Applied Sciences Asian Network for Scientific ...

Global albedo change and radiative cooling from anthropogenic land cover change, 1700 to 2005 based on MODIS, land use harmonization, radiative kernels, and reanalysis

Science.gov (United States)

Ghimire, Bardan; Williams, Christopher A.; Masek, Jeffrey; Gao, Feng; Wang, Zhuosen; Schaaf, Crystal; He, Tao

2014-12-01

Widespread anthropogenic land cover change over the last five centuries has influenced the global climate system through both biogeochemical and biophysical processes. Models indicate that warming from carbon emissions associated with land cover conversion has been partially offset by cooling from elevated albedo, but considerable uncertainty remains partly because of uncertainty in model treatments of albedo. This study incorporates a new spatially and temporally explicit, land cover specific albedo product derived from Moderate Resolution Imaging Spectroradiometer with a historical land use data set (Land Use Harmonization product) to provide more precise, observationally derived estimates of albedo impacts from anthropogenic land cover change with a complete range of data set specific uncertainty. The mean annual global albedo increase due to land cover change during 1700-2005 was estimated as 0.00106 ± 0.00008 (mean ± standard deviation), mainly driven by snow exposure due to land cover transitions from natural vegetation to agriculture. This translates to a top-of-atmosphere radiative cooling of -0.15 ± 0.1 W m-2 (mean ± standard deviation). Our estimate was in the middle of the Intergovernmental Panel on Climate Change Fifth Assessment Report range of -0.05 to -0.25 W m-2 and incorporates variability in albedo within land cover classes.

Investigating the Feasibility of Geo-Tagged Photographs as Sources of Land Cover Input Data

Directory of Open Access Journals (Sweden)

Vyron Antoniou

2016-05-01

Full Text Available Geo-tagged photographs are used increasingly as a source of Volunteered Geographic Information (VGI, which could potentially be used for land use and land cover applications. The purpose of this paper is to analyze the feasibility of using this source of spatial information for three use cases related to land cover: Calibration, validation and verification. We first provide an inventory of the metadata that are collected with geo-tagged photographs and then consider what elements would be essential, desirable, or unnecessary for the aforementioned use cases. Geo-tagged photographs were then extracted from Flickr, Panoramio and Geograph for an area of London, UK, and classified based on their usefulness for land cover mapping including an analysis of the accompanying metadata. Finally, we discuss protocols for geo-tagged photographs for use of VGI in relation to land cover applications.

Central American Vegetation/Land Cover Classification and Conservation Status

Data.gov (United States)

National Aeronautics and Space Administration — The Central American Vegetation/Land Cover Classification and Conservation Status data set consists of GIS coverages of vegetation classes (forests, woodlands,...

Mapping land cover gradients through analysis of hyper-temporal NDVI imagery

NARCIS (Netherlands)

Ali, A.; de Bie, C.A.J.M.; Skidmore, A.K.; Scarrott, R.G.; Hamad, A.A.; Venus, V.; Lymberakis, P.

2013-01-01

The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but

ANALYSING THE EFFECTS OF DIFFERENT LAND COVER TYPES ON LAND SURFACE TEMPERATURE USING SATELLITE DATA

Directory of Open Access Journals (Sweden)

A. Şekertekin

2015-12-01

Full Text Available Monitoring Land Surface Temperature (LST via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

Analysing the Effects of Different Land Cover Types on Land Surface Temperature Using Satellite Data

Science.gov (United States)

Şekertekin, A.; Kutoglu, Ş. H.; Kaya, S.; Marangoz, A. M.

2015-12-01

Monitoring Land Surface Temperature (LST) via remote sensing images is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region (ÇATES and ZETES) Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.

Land Cover Characterization and Mapping of South America for the Year 2010 Using Landsat 30 m Satellite Data

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.

VEGETATION ANALYSIS AND LAND USE LAND COVER CLASSIFICATION OF FOREST IN UTTARA KANNADA DISTRICT INDIA USING REMOTE SENSIGN AND GIS TECHNIQUES

Directory of Open Access Journals (Sweden)

A. G. Koppad

2017-10-01

Full Text Available The study was conducted in Uttara Kannada districts during the year 2012–2014. The study area lies between 13.92° N to 15.52° N latitude and 74.08° E to 75.09° E longitude with an area of 10,215 km2. The Indian satellite IRS P6 LISS-III imageries were used to classify the land use land cover classes with ground truth data collected with GPS through supervised classification in ERDAS software. The land use and land cover classes identified were dense forest, horticulture plantation, sparse forest, forest plantation, open land and agriculture land. The dense forest covered an area of 63.32 % (6468.70 sq km followed by agriculture 12.88 % (1315.31 sq. km, sparse forest 10.59 % (1081.37 sq. km, open land 6.09 % (622.37 sq. km, horticulture plantation and least was forest plantation (1.07 %. Settlement, stony land and water body together cover about 4.26 percent of the area. The study indicated that the aspect and altitude influenced the forest types and vegetation pattern. The NDVI map was prepared which indicated that healthy vegetation is represented by high NDVI values between 0.1 and 1. The non- vegetated features such as water bodies, settlement, and stony land indicated less than 0.1 values. The decrease in forest area in some places was due to anthropogenic activities. The thematic map of land use land cover classes was prepared using Arc GIS Software.

Simulation of the influence of historical land cover changes on the global climate

Energy Technology Data Exchange (ETDEWEB)

Wang, Y. [Nanjing Univ. of Aeronautics and Astronautics (China). College of Civil Aviation; Chinese Academy of Sciences, Beijing (China). Key Lab. of Regional Climate-Environment for East Asia; Yan, X. [Chinese Academy of Sciences, Beijing (China). Key Lab. of Regional Climate-Environment for East Asia; Beijing Normal Univ. (China). State Key Lab. of Earth Surface Processes and Resource Ecology (ESPRE); Wang, Z. [British Antarctic Survey, Cambridge (United Kingdom)

2013-09-01

In order to estimate biogeophysical effects of historical land cover change on climate during last three centuries, a set of experiments with a climate system model of intermediate complexity (MPM-2) is performed. In response to historical deforestation, the model simulates a decrease in annual mean global temperature in the range of 0.07-0.14 C based on different grassland albedos. The effect of land cover changes is most pronounced in the middle northern latitudes with maximum cooling reaching approximately 0.6 C during northern summer. The cooling reaches 0.57 C during northern spring owing to the large effects of land surface albedo. These results suggest that land cover forcing is important for study on historical climate change and that more research is necessary in the assessment of land management options for climate change mitigation. (orig.)

Effect of land cover change on runoff curve number estimation in Iowa, 1832-2001

Science.gov (United States)

Wehmeyer, Loren L.; Weirich, Frank H.; Cuffney, Thomas F.

2011-01-01

Within the first few decades of European-descended settlers arriving in Iowa, much of the land cover across the state was transformed from prairie and forest to farmland, patches of forest, and urbanized areas. Land cover change over the subsequent 126 years was minor in comparison. Between 1832 and 1859, the General Land Office conducted a survey of the State of Iowa to aid in the disbursement of land. In 1875, an illustrated atlas of the State of Iowa was published, and in 2001, the US Geological Survey National Land Cover Dataset was compiled. Using these three data resources for classifying land cover, the hydrologic impact of the land cover change at three points in time over a period of 132+ years is presented in terms of the effect on the area-weighted average curve number, a term commonly used to predict peak runoff from rainstorms. In the four watersheds studied, the area-weighted average curve number associated with the first 30 years of settlement increased from 61·4 to 77·8. State-wide mapped forest area over this same period decreased 19%. Over the next 126 years, the area-weighted average curve number decreased to 76·7, despite an additional forest area reduction of 60%. This suggests that degradation of aquatic resources (plants, fish, invertebrates, and habitat) arising from hydrologic alteration was likely to have been much higher during the 30 years of initial settlement than in the subsequent period of 126 years in which land cover changes resulted primarily from deforestation and urbanization. 

Agricultural land cover changes in metropolitan areas of Poland for the period 1990–2012

Directory of Open Access Journals (Sweden)

Nalej Marta

2016-06-01

Full Text Available Agricultural land covers more than half the area of metropolitan areas in Poland, and is therefore particularly prone to the influences of the processes associated with their development. The aim of the study was to analyse changes in agricultural land cover within the metropolitan areas of Poland for the years 1990–2012; and to capture their dynamics, types and directions. The percentage share of the total study area, for each of the forms of agricultural land cover and their changes were traced, with the spatial distribution of the changes also being determined. The results of the study show that in metropolitan areas, agricultural land cover is undergoing transformations that do not result in the loss of agricultural lands, or that involve a decrease in surface area due to their change into anthropogenic forms of land cover. The greatest transitions occurred between 2000 and 2006 and were observed in the outer zones of metropolitan areas.

The Multi-Resolution Land Characteristics (MRLC) Consortium: 20 years of development and integration of USA national land cover data

Science.gov (United States)

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.

Using Urban Landscape Trajectories to Develop a Multi-Temporal Land Cover Database to Support Ecological Modeling

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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

Land cover characterization and mapping of South America for the year 2010 using Landsat 30 m satellite data

Science.gov (United States)

Giri, Chandra; Long, Jordan

2014-01-01

Detailed and accurate land cover and land cover change information is needed for South America because the continent is in constant flux, experiencing some of the highest rates of land cover change and forest loss in the world. The land cover data available for the entire continent are too coarse (250 m to 1 km) for resource managers, government and non-government organizations, and Earth scientists to develop conservation strategies, formulate resource management options, and monitor land cover dynamics. We used Landsat 30 m satellite data of 2010 and prepared the land cover database of South America using state-of-the-science remote sensing techniques. We produced regionally consistent and locally relevant land cover information by processing a large volume of data covering the entire continent. Our analysis revealed that in 2010, 50% of South America was covered by forests, 2.5% was covered by water, and 0.02% was covered by snow and ice. The percent forest area of South America varies from 9.5% in Uruguay to 96.5% in French Guiana. We used very high resolution (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.

Land cover change interacts with drought severity to change fire regimes in Western Amazonia.

Science.gov (United States)

Gutiérrez-Vélez, Víctor H; Uriarte, María; DeFries, Ruth; Pinedo-Vásquez, Miguel; Fernandes, Katia; Ceccato, Pietro; Baethgen, Walter; Padoch, Christine

Fire is becoming a pervasive driver of environmental change in Amazonia and is expected to intensify, given projected reductions in precipitation and forest cover. Understanding of the influence of post-deforestation land cover change on fires in Amazonia is limited, even though fires in cleared lands constitute a threat for ecosystems, agriculture, and human health. We used MODIS satellite data to map burned areas annually between 2001 and 2010. We then combined these maps with land cover and climate information to understand the influence of land cover change in cleared lands and dry-season severity on fire occurrence and spread in a focus area in the Peruvian Amazon. Fire occurrence, quantified as the probability of burning of individual 232-m spatial resolution MODIS pixels, was modeled as a function of the area of land cover types within each pixel, drought severity, and distance to roads. Fire spread, quantified as the number of pixels burned in 3 × 3 pixel windows around each focal burned pixel, was modeled as a function of land cover configuration and area, dry-season severity, and distance to roads. We found that vegetation regrowth and oil palm expansion are significantly correlated with fire occurrence, but that the magnitude and sign of the correlation depend on drought severity, successional stage of regrowing vegetation, and oil palm age. Burning probability increased with the area of nondegraded pastures, fallow, and young oil palm and decreased with larger extents of degraded pastures, secondary forests, and adult oil palm plantations. Drought severity had the strongest influence on fire occurrence, overriding the effectiveness of secondary forests, but not of adult plantations, to reduce fire occurrence in severely dry years. Overall, irregular and scattered land cover patches reduced fire spread but irregular and dispersed fallows and secondary forests increased fire spread during dry years. Results underscore the importance of land cover

Impacts of land use/cover change on ecosystem services for Xiamen

Science.gov (United States)

Shi, L.; Cui, S.

2009-12-01

Based on remote sensing images of Xiamen in 1987, 1997 and 2007, the process of ecosystem service alteration resulting from land use/cover change was quantitatively analyzed through RS and GIS techniques. Consulting relative researches, an integrated assessment model was built to evaluating regional ecosystem services of Xiamen. The results showed that the total ecosystem service value of Xiamen was increased by 14.67%, from 3271.5 million to 3751.39 RMB. The relative change rate of supplying service, regulation service, cultural service and supporting service were 97.8%, -25.1%, 165.0% and -44.7% respectively, which indicated that land use/ cover change had positive effects on supplying and cultural service, whereas it had negatively affected both regulation service and supporting service. Land use/cover types of Xiamen in 1987, 1997 and 2007 Ecosystem values of Xiamen in 1987, 1997 and 2007 10 thousand RMB

South African National Land-Cover Change Map | Schoeman ...

African Journals Online (AJOL)

Globally, countries face a changing environment due to population growth, increase in agricultural production, increasing demand on natural resources, climate change and resultant degradation of the natural environment. One means of monitoring this changing scenario is through land-cover change mapping. Modern ...

TESTING OF LAND COVER CLASSIFICATION FROM MULTISPECTRAL AIRBORNE LASER SCANNING DATA

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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

Land use and land cover change in the Western Cape Province: quantification of changes & understanding of driving factors

CSIR Research Space (South Africa)

Tizora, P

2016-07-01

Full Text Available changes in land use and land cover (LULC) and incited issues such as urban sprawl, marginalization of the poor, limited public access to resources, land degradation and climate change. This paper seeks to understand the most significant drivers of LULC...

Land use/cover change and perceived watershed status in Eastern ...

African Journals Online (AJOL)

ROBERT

Five land use/cover types were identified namely; (1) ... The focus group discussion findings indicated a negative trend in land ... Awoja watershed in Kyoga Water Management Zone of eastern ... as compared to the national average of 11% (MWE, 2013). ... This was acquired from USGS Earth ... The unit of analysis was the.

Development of deforestation and land cover database for Bhutan (1930-2014).

Science.gov (United States)

Reddy, C Sudhakar; Satish, K V; Jha, C S; Diwakar, P G; Murthy, Y V N Krishna; Dadhwal, V K

2016-12-01

Bhutan is a mountainous country located in the Himalayan biodiversity hotspot. This study has quantified the total area under land cover types, estimated the rate of forest cover change, analyzed the changes across forest types, and modeled forest cover change hotpots in Bhutan. The topographical maps and satellite remote sensing images were analyzed to get the spatial patterns of forest and associated land cover changes over the past eight decades (1930-1977-1987-1995-2005-2014). Forest is the largest land cover in Bhutan and constitutes 68.3% of the total geographical area in 2014. Subtropical broad leaved hill forest is predominant type occupies 34.1% of forest area in Bhutan, followed by montane dry temperate (20.9%), montane wet temperate (18.9%), Himalayan moist temperate (10%), and tropical moist sal (8.1%) in 2014. The major forest cover loss is observed in subtropical broad leaved hill forest (64.5 km 2 ) and moist sal forest (9.9 km 2 ) from 1977 to 2014. The deforested areas have mainly been converted into agriculture and contributed for 60.9% of forest loss from 1930 to 2014. In spite of major decline of forest cover in time interval of 1930-1977, there is no net rate of deforestation is recorded in Bhutan since 1995. Forest cover change analysis has been carried out to evaluate the conservation effectiveness in "Protected Areas" of Bhutan. Hotspots that have undergone high transformation in forest cover for afforestation and deforestation were highlighted in the study for conservation prioritisation. Forest conservation policies in Bhutan are highly effective in controlling deforestation as compared to neighboring Asian countries and such service would help in mitigating climate change.

ASSESSING LAND COVER CHANGES CAUSED BY GRANITE QUARRYING USING REMOTE SENSING

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R. S. Moeletsi

2017-11-01

Full Text Available Dimension stone quarrying in the area between Rustenburg and Brits in the North West Province of South Africa has been in existence for over 70 decades. The unique characteristics of the granite deposits in South Africa resulted in making the country a global producer of the granite rocks. This led to intensified quarrying activities between Rustenburg and Brits town. However, this surface mining method, has a potential to impact the environment in a negative way causing loss in vegetation, depletion of natural resources, loss of scenic beauty and contamination of surface water resources. To assess the land cover changes caused by granite quarrying activities, remotely sensed data in the form of Landsat images between 1998 and 2015 were used. Supervised classification was used to create maps. Accuracy assessment using Google EarthTM as a reference data yielded an overall accuracy of 78 %. The post classification change detection method was used to assess land cover changes within the granite quarries. Granite quarries increased by 1174.86 ha while formation of quarry lakes increased to 5.3 ha over the 17-year period. Vegetation cover decreased by 1308 ha in area while 18.3 ha bare land was lost during the same period. This study demonstrated the utility of remote sensing to detect changes in land cover within granite quarries.

Impacts of land use and land cover on surface and air temperature in urban landscapes

Science.gov (United States)

Crum, S.; Jenerette, D.

2015-12-01

Accelerating urbanization affects regional climate as the result of changing land cover and land use (LCLU). Urban land cover composition may provide valuable insight into relationships among urbanization, air, and land-surface temperature (Ta and LST, respectively). Climate may alter these relationships, where hotter climates experience larger LULC effects. To address these hypotheses we examined links between Ta, LST, LCLU, and vegetation across an urban coastal to desert climate gradient in southern California, USA. Using surface temperature radiometers, continuously measuring LST on standardized asphalt, concrete, and turf grass surfaces across the climate gradient, we found a 7.2°C and 4.6°C temperature decrease from asphalt to vegetated cover in the coast and desert, respectively. There is 131% more temporal variation in asphalt than turf grass surfaces, but 37% less temporal variation in concrete than turf grass. For concrete and turf grass surfaces, temporal variation in temperature increased from coast to desert. Using ground-based thermal imagery, measuring LST for 24 h sequences over citrus orchard and industrial use locations, we found a 14.5°C temperature decrease from industrial to orchard land use types (38.4°C and 23.9°C, respectively). Additionally, industrial land use types have 209% more spatial variation than orchard (CV=0.20 and 0.09, respectively). Using a network of 300 Ta (iButton) sensors mounted in city street trees throughout the region and hyperspectral imagery data we found urban vegetation greenness, measured using the normalized difference vegetation index (NDVI), was negatively correlated to Ta at night across the climate gradient. Contrasting previous findings, the closest coupling between NDVI and Ta is at the coast from 0000 h to 0800 h (highest r2 = 0.6, P urbanized regions of southern California, USA decrease Ta and LST and spatial variation in LST, while built surfaces and land uses have the opposite effect. Furthermore

Use of AMSR-E microwave satellite data for land surface characteristics and snow cover variation

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Mukesh Singh Boori

2016-12-01

Full Text Available This data article contains data related to the research article entitled “Global land cover classification based on microwave polarization and gradient ratio (MPGR” [1] and “Microwave polarization and gradient ratio (MPGR for global land surface phenology” [2]. This data article presents land surface characteristics and snow cover variation information from sensors like EOS Advanced Microwave Scanning Radiometer (AMSR-E. This data article use the HDF Explorer, Matlab, and ArcGIS software to process the pixel latitude, longitude, snow water equivalent (SWE, digital elevation model (DEM and Brightness Temperature (BT information from AMSR-E satellite data to provide land surface characteristics and snow cover variation data in all-weather condition at any time. This data information is useful to discriminate different land surface cover types and snow cover variation, which is turn, will help to improve monitoring of weather, climate and natural disasters.

Effect of Feature Dimensionality on Object-based Land Cover ...

African Journals Online (AJOL)

Geographic object-based image analysis (GEOBIA) allows the easy integration of such additional features into the classification process. This paper compares the performance of three supervised classifiers in a GEOBIA environment as an increasing number of object features are included as classification input.

Estimation and comparision of curve numbers based on dynamic land use land cover change, observed rainfall-runoff data and land slope

Science.gov (United States)

Deshmukh, Dhananjay Suresh; Chaube, Umesh Chandra; Ekube Hailu, Ambaye; Aberra Gudeta, Dida; Tegene Kassa, Melaku

2013-06-01

The CN represents runoff potential is estimated using three different methods for three watersheds namely Barureva, Sher and Umar watershed located in Narmada basin. Among three watersheds, Sher watershed has gauging site for the runoff measurements. The CN computed from the observed rainfall-runoff events is termed as CN(PQ), land use and land cover (LULC) is termed as CN(LU) and the CN based on land slope is termed as SACN2. The estimated annual CN(PQ) varies from 69 to 87 over the 26 years data period with median 74 and average 75. The range of CN(PQ) from 70 to 79 are most significant values and these truly represent the AMC II condition for the Sher watershed. The annual CN(LU) was computed for all three watersheds using GIS and the years are 1973, 1989 and 2000. Satellite imagery of MSS, TM and ETM+ sensors are available for these years and obtained from the Global Land Cover Facility Data Center of Maryland University USA. The computed CN(LU) values show rising trend with the time and this trend is attributed to expansion of agriculture area in all watersheds. The predicted values of CN(LU) with time (year) can be used to predict runoff potential under the effect of change in LULC. Comparison of CN(LU) and CN(PQ) values shows close agreement and it also validates the classification of LULC. The estimation of slope adjusted SA-CN2 shows the significant difference over conventional CN for the hilly forest lands. For the micro watershed planning, SCS-CN method should be modified to incorporate the effect of change in land use and land cover along with effect of land slope.

81 An Assessment of the land use and land cover changes in ...

African Journals Online (AJOL)

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Three satellite images for three different years (1991, 2000 and 2009) were used to come up with a ... land cover change maps among other data resources that are .... in agro-ecological region 3 that receives an average rainfall of .... After field observation and collection of .... the image along with statistical comparison of.

Spatial and temporal land cover changes in Terminos Lagoon Reserve, Mexico.

Science.gov (United States)

Soto-Galera, Ernesto; Piera, Jaume; López, Pilar

2010-06-01

Terminos Lagoon ecosystem is the largest fluvial-lagoon estuarine system in the country and one of the most important reserves of coastal flora and fauna in Mexico. Since the seventies, part of the main infrastructure for country's oil extraction is located in this area. Its high biodiversity has motivated different type of studies including deforestation processes and land use planning. In this work we used satellite image analysis to determine land cover changes in the area from 1974 to 2001. Our results indicate that tropical forest and mangroves presented the most extensive losses in its coverage. In contrast, urban areas and induced grassland increased considerably. In 2001 more than half of the ecosystem area showed changes from its original land cover, and a third part of it was deteriorated. The main causes of deforestation were both the increase in grassland and the growth of urban areas. However, deforestation was attenuated by natural reforestation and plant canopy recovery. We conclude that the introduction of cattle and urban development were the main causes for the land cover changes; however, the oil industry activity located in the ecosystem, has promoted indirectly to urban growth and rancher boom.

Potential Role of Land Use and Land Cover Information in Powerplant Siting: Example of Three Mile Island

Science.gov (United States)

Wray, J. R.

1982-01-01

Selecting a site for a nuclear powerplant can be helped by digitizing land use and land cover data, population data, and other pertinent data sets, and then placing them in a geographic information system. Such a system begins with a set of standardized maps for location reference and then provides for retrieval and analysis of spatial data keyed to the maps. This makes possible thematic mapping by computer, or interactive visual display for decisionmaking. It also permits correlating land use area measurements with census and other data (such as fallout dosages), and the updating of all data sets. The system is thus a tool for dealing with resource management problems and for analyzing the interaction between people and their environment. An explanation of a computer-plotted map of land use and cover for Three Mile Island and vicinity is given.

Water Resources Response to Climate and Land-Cover Changes in a Semi-Arid Watershed, New Mexico, USA

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Joonghyeok Heo

2015-01-01

Full Text Available This research evaluates a climate-land cover-water resources interconnected system in a semi-arid watershed with minimal human impact from 1970 - 2009. We found _ increase in temperature and 10.9% decrease in precipitation. The temperature exhibited a lower increase trend and precipitation showed a similar decrease trend compared to previous studies. The dominant land-cover change trend was grass and forest conversion into bush/shrub and developed land and crop land into barren and grass land. These alterations indicate that changes in temperature and precipitation in the study area may be linked to changes in land cover, although human intervention is recognized as the major land-cover change contributor for the short term. These alterations also suggest that decreasing human activity in the study area leads to developed land and crop land conversion into barren and grass land. Hydrological responses to climate and land-cover changes for surface runoff, groundwater discharge, soil water content and evapotranspiration decreased by 10.2, 10.0, 4.1, and 10.5%, respectively. Hydrological parameters generally follow similar trends to that of precipitation in semi-arid watersheds with minimal human development. Soil water content is sensitive to land-cover change and offset relatively by the changes in precipitation.

Assessing Wetland Health Using a Newly Developed Land Cover ...

African Journals Online (AJOL)

Citizen science combines environmental research with environmental education .... health of the wetland using land cover type impacts. Once the impact is ... to interpret the findings of the quantitative method using the qualitative findings.

"Land-Cover Conversion in Amazonia, The Role of ENV" Ironment and Substrate composition in Modifying SOI

Science.gov (United States)

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.

Introducing land-cover and land-use changes in a climate scenario of the 21. century; Prise en compte des changements de vegetation dans un scenario climatique du 21. siecle

Energy Technology Data Exchange (ETDEWEB)

Voldoire, A

2005-03-15

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)

Optimal land use/land cover classification using remote sensing imagery for hydrological modeling in a Himalayan watersched

NARCIS (Netherlands)

Saran, S.; Sterk, G.; Kumar, S.

2009-01-01

Land use/land cover is an important watershed surface characteristic that affects surface runoff and erosion. Many of the available hydrological models divide the watershed into Hydrological Response Units (HRU), which are spatial units with expected similar hydrological behaviours. The division

CHANGE DETECTION IN LAND-USE AND LAND-COVER DYNAMICS AT A REGIONAL SCALE FROM MODIS TIME-SERIES IMAGERY

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.

Object-oriented image analysis and change detection of land-use on Tenerife related to socio-economic conditions

Science.gov (United States)

Naumann, Simone; Siegmund, Alexander

2004-10-01

The island Tenerife is characterized by an increasing tourism, which causes an enormous change of the socio-economic situation and a rural exodus. This development leads - beside for example sociocultural issues - to fallow land, decreasing settlements, land wasting etc., as well as to an economic and ecological problem. This causes to a growing interest in geoecological aspects and to an increasing demand for an adequate monitoring database. In order to study the change of land use and land cover, the technology of remote sensing (LANDSAT 3 MSS and 7 ETM+, orthophotos) and geographical information systems were used to analyze the spatial pattern and its spatial temporal changes of land use from end of the 70s to the present in different scales. Because of the heterogeneous landscape and the unsatisfactory experience with pixel-based classification of the same area, object-oriented image analysis techniques have been applied to classify the remote sensed data. A post-classification application was implemented to detect spatial and categorical land use and land cover changes, which have been clipped with the socio-economic data within GIS to derive the driving forces of the changes and their variability in time and space.

Land-cover impacts on streamflow: a change-detection modelling approach that incorporates parameter uncertainty

Science.gov (United States)

Jan Seibert; Jeffrey J. McDonnell

2010-01-01

The effect of land-use or land-cover change on stream runoff dynamics is not fully understood. In many parts of the world, forest management is the major land-cover change agent. While the paired catchment approach has been the primary methodology used to quantify such effects, it is only possible for small headwater catchments where there is uniformity in...

USGS National Land Cover Dataset (NLCD) Downloadable Data Collection

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — NLCD 1992, NLCD 2001, NLCD 2006, and NLCD 2011 are National Land Cover Database classification schemes based primarily on Landsat data along with ancillary data...

Perubahan Lingkungan Mikro pada Berbagai Penutupan Lahan Hasil Revegetasi (Micro Environmental Change in Various Form Land Cover Revegetation

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Dadan Mulyana

2011-07-01

Full Text Available Evaluation of land rehabilitation (revegetation activities is necessary for measuring the extent of success of the ongoing activities in rehabilitating and recovering degraded lands. One way for evaluating the success of land rehabilitation (revegetation is by determining the changes of micro enviroment.  The objective of this research was to study the changes of micro environment in  various types of revegetated land cover, including scrub/bush land (SB, agricultural land (TP, monoculture teak (JM and mixed crops (TC in Ciliwung upper watershed. Research results showed that the highest air temperature and soil temperature were  obtained at SB, respectively at 32.8 0C and 26.5 0C, and the lowest at TC, respectively at 28.1 0C and 20.7 0C. Relative humidity and soil moisture were highest at TC (72.3% and 96% and lowest at SB (60.8%, and the lowest soil moisture occurred at JM (45%.  The highest infiltration rate occurred on TP (475.5 mm h-1, very rapid, followed by JM (117 mmh-1, fast and TC (80 mm h-1, and the lowest at SB (17.65 mm h-1, medium slow.  Erosion reductions occurred after 6 years of the revegetation activities with the following  results:TC  (96,676.1 ton year-1 ha-1, JM (10,790 ton year-1 ha-1, TP and SB (52,867.9 ton year-1 ha-1 and 24,612.6 ton year-1 ha-1.  The micro environments for all land cover types were better after revegetation activities.Keywords: micro environment, land cover, erosion, infiltration, upper watershed

  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...

Linear Subpixel Learning Algorithm for Land Cover Classification from WELD using High Performance Computing

Science.gov (United States)

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.

Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis

Science.gov (United States)

Sharpe, Jennifer B.; Soong, David T.

2015-01-01

The U.S. Army Corps of Engineers (USACE), Chicago District, is responsible for monitoring and computation of the quantity of Lake Michigan water diverted by the State of Illinois. As part of this effort, the USACE uses the Hydrological Simulation Program–FORTRAN (HSPF) with measured meteorological data inputs to estimate runoff from the Lake Michigan diversion special contributing areas (SCAs), the North Branch Chicago River above Niles and the Little Calumet River above South Holland gaged basins, and the Lower Des Plaines and the Calumet ungaged that historically drained to Lake Michigan. These simulated runoffs are used for estimating the total runoff component from the diverted Lake Michigan watershed, which is accountable to the total diversion by the State of Illinois. The runoff is simulated from three interpreted land cover types in the HSPF models: impervious, grass, and forest. The three land cover data types currently in use were derived from aerial photographs acquired in the early 1990s.