WorldWideScience

Sample records for based land cover

  1. 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...

  2. 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...

  3. Land Cover

    Data.gov (United States)

    Kansas Data Access and Support Center — The Land Cover database depicts 10 general land cover classes for the State of Kansas. The database was compiled from a digital classification of Landsat Thematic...

  4. Land Cover - Minnesota Land Cover Classification System

    Data.gov (United States)

    Minnesota Department of Natural Resources — Land cover data set based on the Minnesota Land Cover Classification System (MLCCS) coding scheme. This data was produced using a combination of aerial photograph...

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

    African Journals Online (AJOL)

    Myburgh, G, Mnr

    Effect of Feature Dimensionality on Object-based Land Cover. Classification: A Comparison of Three .... Argialas, 2008), GEOBIA is generally more sensitive to the Hughes effect when statistical classifiers are used. Support .... Area, asymmetry, border length, compactness, density, length, length/width (22), main direction, ...

  6. Classification of Land Cover and Land Use Based on Convolutional Neural Networks

    Science.gov (United States)

    Yang, Chun; Rottensteiner, Franz; Heipke, Christian

    2018-04-01

    Land cover describes the physical material of the earth's surface, whereas land use describes the socio-economic function of a piece of land. Land use information is typically collected in geospatial databases. As such databases become outdated quickly, an automatic update process is required. This paper presents a new approach to determine land cover and to classify land use objects based on convolutional neural networks (CNN). The input data are aerial images and derived data such as digital surface models. Firstly, we apply a CNN to determine the land cover for each pixel of the input image. We compare different CNN structures, all of them based on an encoder-decoder structure for obtaining dense class predictions. Secondly, we propose a new CNN-based methodology for the prediction of the land use label of objects from a geospatial database. In this context, we present a strategy for generating image patches of identical size from the input data, which are classified by a CNN. Again, we compare different CNN architectures. Our experiments show that an overall accuracy of up to 85.7 % and 77.4 % can be achieved for land cover and land use, respectively. The classification of land cover has a positive contribution to the classification of the land use classification.

  7. 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...

  8. Major forest changes and land cover transitions based on plant functional types derived from the ESA CCI Land Cover product

    Science.gov (United States)

    Li, Wei; Ciais, Philippe; MacBean, Natasha; Peng, Shushi; Defourny, Pierre; Bontemps, Sophie

    2016-05-01

    Land use and land cover change are of prime concern due to their impacts on CO2 emissions, climate change and ecological services. New global land cover products at 300 m resolution from the European Space Agency (ESA) Climate Change Initiative Land Cover (CCI LC) project for epochs centered around 2000, 2005 and 2010 were analyzed to investigate forest area change and land cover transitions. Plant functional types (PFTs) fractions were derived from these land cover products according to a conversion table. The gross global forest loss between 2000 and 2010 is 172,171 km2, accounting for 0.6% of the global forest area in year 2000. The forest changes are mainly distributed in tropical areas such as Brazil and Indonesia. Forest gains were only observed between 2005 and 2010 with a global area of 9844 km2, mostly from crops in Southeast Asia and South America. The predominant PFT transition is deforestation from forest to crop, accounting for four-fifths of the total increase of cropland area between 2000 and 2010. The transitions from forest to bare soil, shrub, and grass also contributed strongly to the total areal change in PFTs. Different PFT transition matrices and composition patterns were found in different regions. The highest fractions of forest to bare soil transitions were found in the United States and Canada, reflecting forest management practices. Most of the degradation from grassland and shrubland to bare soil occurred in boreal regions. The areal percentage of forest loss and land cover transitions generally decreased from 2000-2005 to 2005-2010. Different data sources and uncertainty in the conversion factors (converting from original LC classes to PFTs) contribute to the discrepancy in the values of change in absolute forest area.

  9. Forecasting Land-Use and Land-Cover in the Great Plains Using Scenario-Based Modeling

    Science.gov (United States)

    Bouchard, M. A.; Sohl, T. L.; Sleeter, B. M.; Sayler, K.; Reker, R.; Zhu, Z.

    2011-12-01

    The U.S. Geological Survey LandCarbon project is assessing potential carbon storage under various Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES). As part of this assessment, the FORE-SCE (FOREcasting SCEnarios of future land cover) model is being used to project land use and land cover (LULC) change annually through 2050. Downscaled IPCC scenarios were used to project LULC change by Omernik Level II Ecoregions, beginning with the Great Plains. Scenarios consistent with SRES storylines A1B, A2, B1, and B2 were developed using the Integrated Model to Assess the Greenhouse Effect (IMAGE), historical land-use histories from the USGS Land Cover Trends project, and workshops of land-use experts. The FORE-SCE model was then used to create spatially explicit LULC maps at a 250-meter pixel resolution to show differences in projected land cover change between scenarios. Economically-based storylines had large increases in agriculture and a loss of natural land covers due to the high demand for agricultural commodities. Environmentally-based scenarios had stable to slight increases in wetlands and grasslands due to conservation of natural land cover. This poster will present maps and results of scenario-based LULC change for the Great Plains.

  10. Validation of Land Cover Maps in China Using a Sampling-Based Labeling Approach

    Directory of Open Access Journals (Sweden)

    Yan Bai

    2015-08-01

    Full Text Available This paper presents a rigorous validation of five widely used global land cover products, i.e., GLCC (Global Land Cover Characterization, UMd (University of Maryland land cover product, GLC2000 (Global Land Cover 2000 project data, MODIS LC (Moderate Resolution Imaging Spectro-radiometer Land Cover product and GlobCover (GLOBCOVER land cover product, and a national land cover map GLCD-2005 (Geodata Land Cover Dataset for year 2005 against an independent reference data set over China. The land cover reference data sets in three epochs (1990, 2000, and 2005 were collected on a web-based prototype system using a sampling-based labeling approach. Results show that, in China, the highest overall accuracy is observed in GLCD-2005 (72.3%, followed by MODIS LC (68.9%, GLC2000 (65.2%, GlobCover (57.7% and GLCC (57.2%, while UMd has the lowest accuracy (48.6%; all of the products performed best in representing “Trees” and “Others”, well with “Grassland” and “Cropland”, but problematic with “Water” and “Urban” across China in general. Moreover, in respect of GLCD-2005, there are significant accuracy differences across seven geographical locations of China, ranging from 46.3% in the Southwest, 77.5% in the South, 79.2% in the Northwest, 80.8% in the North, 81.8% in the Northeast, 82.6% in the Central, to 89.0% in the East. This study indicates that a regionally focused land cover map would in fact be more accurate than extracting the same region from a globally produced map.

  11. 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.

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

    Directory of Open Access Journals (Sweden)

    Jed O. Kaplan

    2017-12-01

    Full Text Available Anthropogenic land cover change (ALCC is the most important transformation of the Earth system that occurred in the preindustrial Holocene, with implications for carbon, water and sediment cycles, biodiversity and the provision of ecosystem services and regional and global climate. For example, anthropogenic deforestation in preindustrial Eurasia may have led to feedbacks to the climate system: both biogeophysical, regionally amplifying winter cold and summer warm temperatures, and biogeochemical, stabilizing atmospheric CO 2 concentrations and thus influencing global climate. Quantification of these effects is difficult, however, because scenarios of anthropogenic land cover change over the Holocene vary widely, with increasing disagreement back in time. Because land cover change had such widespread ramifications for the Earth system, it is essential to assess current ALCC scenarios in light of observations and provide guidance on which models are most realistic. Here, we perform a systematic evaluation of two widely-used ALCC scenarios (KK10 and HYDE3.1 in northern and part of central Europe using an independent, pollen-based reconstruction of Holocene land cover (REVEALS. Considering that ALCC in Europe primarily resulted in deforestation, we compare modeled land use with the cover of non-forest vegetation inferred from the pollen data. Though neither land cover change scenario matches the pollen-based reconstructions precisely, KK10 correlates well with REVEALS at the country scale, while HYDE systematically underestimates land use with increasing magnitude with time in the past. Discrepancies between modeled and reconstructed land use are caused by a number of factors, including assumptions of per-capita land use and socio-cultural factors that cannot be predicted on the basis of the characteristics of the physical environment, including dietary preferences, long-distance trade, the location of urban areas and social organization.

  13. 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.

  14. The National Land Cover Database

    Science.gov (United States)

    Homer, Collin H.; 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.

  15. Object-based land cover classification based on fusion of multifrequency SAR data and THAICHOTE optical imagery

    Science.gov (United States)

    Sukawattanavijit, Chanika; Srestasathiern, Panu

    2017-10-01

    Land Use and Land Cover (LULC) information are significant to observe and evaluate environmental change. LULC classification applying remotely sensed data is a technique popularly employed on a global and local dimension particularly, in urban areas which have diverse land cover types. These are essential components of the urban terrain and ecosystem. In the present, object-based image analysis (OBIA) is becoming widely popular for land cover classification using the high-resolution image. COSMO-SkyMed SAR data was fused with THAICHOTE (namely, THEOS: Thailand Earth Observation Satellite) optical data for land cover classification using object-based. This paper indicates a comparison between object-based and pixel-based approaches in image fusion. The per-pixel method, support vector machines (SVM) was implemented to the fused image based on Principal Component Analysis (PCA). For the objectbased classification was applied to the fused images to separate land cover classes by using nearest neighbor (NN) classifier. Finally, the accuracy assessment was employed by comparing with the classification of land cover mapping generated from fused image dataset and THAICHOTE image. The object-based data fused COSMO-SkyMed with THAICHOTE images demonstrated the best classification accuracies, well over 85%. As the results, an object-based data fusion provides higher land cover classification accuracy than per-pixel data fusion.

  16. Pollen-based land-cover change during the Holocene in temperate China for climate modelling

    Science.gov (United States)

    Li, Furong; Gaillard, Marie-José; Sugita, Shinya; Mazier, Florence; Xu, Qinghai; Cao, Xianyong; Herxschuh, Ulrike; Zhao, Yan

    2017-04-01

    Quantification of the biogeochemical and biogeophysical effects of human-induced land-cover change (land-use) on climate in the past is still a subject of debate. Progress in our understanding of the net effect of land-use change on climate greatly depends on the availability of reliable, empirical reconstructions of anthropogenic vegetation change. China is one of the key regions of the world where agricultural civilizations flourished during a large part of the Holocene. However, the role of human activity in vegetation change is not yet fully understood. As a contribution to LandCover6k, we present the first pollen-based reconstruction of land-cover change, both climate-(natural) and human-induced, over the Holocene in temperate China using the REVEALS model (Sugita, 2007). The REVEALS model requires values of pollen productivity for the major plants characteristic of the study region. We performed the first evaluation of the relative pollen productivities (RPP) available from temperate China and established a tentative standard RPP dataset for 31 plant taxa. These RPP values were used together with 95 pollen records from temperate China grouped into 35 groups for the REVEALS application. The REVEALS-based values of plant cover strongly differ from the pollen percentages. As in Europe, pollen percentages generally underestimate the cover of herbs in the vegetation, except for Artemisia that is overrepresented by pollen. As expected, human-induced deforestation is highest in eastern China with 3 major phases of decreasing woodland cover at ca. 5.5-5k, 3.5-3k and 2k calendar years BP. Disentangling human-induced from climate-induced land-cover change requires thorough comparison of the REVEALS reconstructions with historical and archaeological data. Sugita S (2007) The Holocene, 17(2): 229-241.

  17. Rank-Based Methods for Selection of Landscape Metrics for Land Cover Pattern Change Detection

    Directory of Open Access Journals (Sweden)

    Priyakant Sinha

    2016-02-01

    Full Text Available Often landscape metrics are not thoroughly evaluated with respect to remote sensing data characteristics, such as their behavior in relation to variation in spatial and temporal resolution, number of land cover classes or dominant land cover categories. In such circumstances, it may be difficult to ascertain whether a change in a metric is due to landscape pattern change or due to the inherent variability in multi-temporal data. This study builds on this important consideration and proposes a rank-based metric selection process through computation of four difference-based indices (β, γ, ξ and θ using a Max–Min/Max normalization approach. Land cover classification was carried out for two contrasting provinces, the Liverpool Range (LR and Liverpool Plains (LP, of the Brigalow Belt South Bioregion (BBSB of NSW, Australia. Landsat images, Multi Spectral Scanner (MSS of 1972–1973 and TM of 1987–1988, 1993–1994, 1999–2000 and 2009–2010 were classified using object-based image analysis methods. A total of 30 landscape metrics were computed and their sensitivities towards variation in spatial and temporal resolutions, number of land cover classes and dominant land cover categories were evaluated by computing a score based on Max–Min/Max normalization. The landscape metrics selected on the basis of the proposed methods (Diversity index (MSIDI, Area weighted mean patch fractal dimension (SHAPE_AM, Mean core area (CORE_MN, Total edge (TE, No. of patches (NP, Contagion index (CONTAG, Mean nearest neighbor index (ENN_MN and Mean patch fractal dimension (FRAC_MN were successful and effective in identifying changes over five different change periods. Major changes in land cover pattern after 1993 were observed, and though the trends were similar in both cases, the LP region became more fragmented than the LR. The proposed method was straightforward to apply, and can deal with multiple metrics when selection of an appropriate set can become

  18. LAND COVER CLASSIFICATION FROM FULL-WAVEFORM LIDAR DATA BASED ON SUPPORT VECTOR MACHINES

    Directory of Open Access Journals (Sweden)

    M. Zhou

    2016-06-01

    Full Text Available In this study, a land cover classification method based on multi-class Support Vector Machines (SVM is presented to predict the types of land cover in Miyun area. The obtained backscattered full-waveforms were processed following a workflow of waveform pre-processing, waveform decomposition and feature extraction. The extracted features, which consist of distance, intensity, Full Width at Half Maximum (FWHM and back scattering cross-section, were corrected and used as attributes for training data to generate the SVM prediction model. The SVM prediction model was applied to predict the types of land cover in Miyun area as ground, trees, buildings and farmland. The classification results of these four types of land covers were obtained based on the ground truth information according to the CCD image data of Miyun area. It showed that the proposed classification algorithm achieved an overall classification accuracy of 90.63%. In order to better explain the SVM classification results, the classification results of SVM method were compared with that of Artificial Neural Networks (ANNs method and it showed that SVM method could achieve better classification results.

  19. Analysis of potential flooding in the education Jatinangor based approach morphology, land cover, and geology

    Science.gov (United States)

    Rifai, Achmad; Hadian, Sapari Dwi; Mufti, Iqbal Jabbari; Fathoni, Azmi Rizqi; Azy, Fikri Noor; Jihadi, Lutfan Harisan

    2017-07-01

    Jatinangor formerly an agricultural area dominated by rice field. Water in Jatinangor comes from a spring located in north Jatinangor or proximal region of Manglayang mountain to flow to the south and southwest Jatinangor up to Citarum River. Jatinangor plain that was once almost all the rice fields, but now become a land settlement that grew very rapidly since its founding colleges. Flow and puddle were originally be used for agricultural land, but now turned into a disaster risks for humans. The research method using qualitative methods with the weighing factor, scoring, and overlay maps. The cause of the flood is distinguished into two: the first is the natural factors such as the condition of landform, lithology, river flow patterns, and annual rainfall. The second is non-natural factors such as land cover of settlement, irrigation, and land use. The amount of flood risks using probability Gilbert White frequency, magnitude and duration of existing events then correlated with these factors. Based on the results of the study, were divided into 3 zones Jatinangor disaster-prone (high, medium, and safe). High flood zone is located in the South Jatinangor which covers an area Cikeruh Village, Sayang Village, Cipacing village, Mekargalih village, Cintamulya village, west of Jatimukti village, and South Hegarmanah village, has a dominant causative factor is the use of solid land, poor drainage, lithology lacustrine conditions with low permeability, and flat topography. Medium flood zone was located in the central and western regions covering Cibeusi village, Cileles village, south of Cilayung village, Hegarmanah village and Padjadjaran Region, has a dominant causative factor is rather dense land use, lithology breccias and Tuffaceous Sand with moderate permeability, topography is moderately steep. Safe flood zone is located in the east Jatinangor covering Jatiroke village, Cisepur village, east Hegarmanah village, has a dominant factor in the form of a rather steep

  20. 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...

  1. Mekong Land Cover Dasboard: Regional Land Cover Mointoring Systems

    Science.gov (United States)

    Saah, D. S.; Towashiraporn, P.; Aekakkararungroj, A.; Phongsapan, K.; Triepke, J.; Maus, P.; Tenneson, K.; Cutter, P. G.; Ganz, D.; Anderson, E.

    2016-12-01

    SERVIR-Mekong, a USAID-NASA partnership, helps decision makers in the Lower Mekong Region utilize GIS and Remote Sensing information to inform climate related activities. In 2015, SERVIR-Mekong conducted a geospatial needs assessment for the Lower Mekong countries which included individual country consultations. The team found that many countries were dependent on land cover and land use maps for land resource planning, quantifying ecosystem services, including resilience to climate change, biodiversity conservation, and other critical social issues. Many of the Lower Mekong countries have developed national scale land cover maps derived in part from remote sensing products and geospatial technologies. However, updates are infrequent and classification systems do not always meet the needs of key user groups. In addition, data products stop at political boundaries and are often not accessible making the data unusable across country boundaries and with resource management partners. Many of these countries rely on global land cover products to fill the gaps of their national efforts, compromising consistency between data and policies. These gaps in national efforts can be filled by a flexible regional land cover monitoring system that is co-developed by regional partners with the specific intention of meeting national transboundary needs, for example including consistent forest definitions in transboundary watersheds. Based on these facts, key regional stakeholders identified a need for a land cover monitoring system that will produce frequent, high quality land cover maps using a consistent regional classification scheme that is compatible with national country needs. SERVIR-Mekong is currently developing a solution that leverages recent developments in remote sensing science and technology, such as Google Earth Engine (GEE), and working together with production partners to develop a system that will use a common set of input data sources to generate high

  2. 3D LAND COVER CLASSIFICATION BASED ON MULTISPECTRAL LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    X. Zou

    2016-06-01

    Full Text Available Multispectral Lidar System can emit simultaneous laser pulses at the different wavelengths. The reflected multispectral energy is captured through a receiver of the sensor, and the return signal together with the position and orientation information of sensor is recorded. These recorded data are solved with GNSS/IMU data for further post-processing, forming high density multispectral 3D point clouds. As the first commercial multispectral airborne Lidar sensor, Optech Titan system is capable of collecting point clouds data from all three channels at 532nm visible (Green, at 1064 nm near infrared (NIR and at 1550nm intermediate infrared (IR. It has become a new source of data for 3D land cover classification. The paper presents an Object Based Image Analysis (OBIA approach to only use multispectral Lidar point clouds datasets for 3D land cover classification. The approach consists of three steps. Firstly, multispectral intensity images are segmented into image objects on the basis of multi-resolution segmentation integrating different scale parameters. Secondly, intensity objects are classified into nine categories by using the customized features of classification indexes and a combination the multispectral reflectance with the vertical distribution of object features. Finally, accuracy assessment is conducted via comparing random reference samples points from google imagery tiles with the classification results. The classification results show higher overall accuracy for most of the land cover types. Over 90% of overall accuracy is achieved via using multispectral Lidar point clouds for 3D land cover classification.

  3. Land Covers Classification Based on Random Forest Method Using Features from Full-Waveform LIDAR Data

    Science.gov (United States)

    Ma, L.; Zhou, M.; Li, C.

    2017-09-01

    In this study, a Random Forest (RF) based land covers classification method is presented to predict the types of land covers in Miyun area. The returned full-waveforms which were acquired by a LiteMapper 5600 airborne LiDAR system were processed, including waveform filtering, waveform decomposition and features extraction. The commonly used features that were distance, intensity, Full Width at Half Maximum (FWHM), skewness and kurtosis were extracted. These waveform features were used as attributes of training data for generating the RF prediction model. The RF prediction model was applied to predict the types of land covers in Miyun area as trees, buildings, farmland and ground. The classification results of these four types of land covers were obtained according to the ground truth information acquired from CCD image data of the same region. The RF classification results were compared with that of SVM method and show better results. The RF classification accuracy reached 89.73% and the classification Kappa was 0.8631.

  4. Study on Land Use Cover Change (LUCC) based on remote sensing and GIS

    Science.gov (United States)

    Zhang, Hong; Zhang, Xuanbing; Shu, Ning

    2009-10-01

    As a key element for land use cover change research, change detection technique is of urgent demands and has great potential in scientific applications. Conflation is the process of combining the information from two (or more) geodata sets to make a master data set that is superior to either source data set in either spatial or attribute aspect. The objectives of conflation include increasing spatial accuracy and consistency, and updating or adding new spatial features into data sets. Based on the analysis and summarizations of researched home and aboard, the paper focused on Land Use/Cover Change detection using feature database of basic types based on vector-image data conflation, that is : Combining of Land use map and RS image, features(grey feature, texture feature and shape feature) are extracted. This methodology belongs to "Feature class" of LUCC. It should be pointed out that the researches must be focused on the land use span other then traditional methods of the pixels. Each spans of T2 will be classified according to the minimum Euclidean distance to the T2 sample span accepted, and the corresponding land use type will be assigned to the current patch, Change information are extraction automatically based on Boolean operations. The method is tested on the Quick Bird images of a district in Wuhan and the precision of the results is high as 92.6% (in urbanization).The experimental results demonstrate that the proposed method can cut down the computational costs and improve the accuracy.

  5. 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

  6. DTM generation using land cover classification based on low density lidar data

    Science.gov (United States)

    Koma, Zsófia; Zlinszky, András

    2014-05-01

    While the point density of local LIDAR surveys continues to increase, most regional or national LIDAR campaigns are carried out with medium or low density, and have the main purpose of DTM generation. Many different point selection and filtering algorithms are already established. Depending on land cover and vegetation, some perform better than others, but no algorithm exists that works perfectly for all types of land cover. Therefore, our method applies several different DTM generation and filtering algorithms for different spatial units depending on their land cover and vegetation. Land cover and vegetation are mapped based on the original raw LIDAR dataset. Two discrete echo airborne LIDAR measurements were used, one with 1 point/m2 and a larger area with 0.4 point/m2 density. The datasets were used together for DTM generation after relative georeferencing by strip adjustment. We defined several land cover categories depending on how they influence vertical distribution of LIDAR points: buildings, waterways, grasslands, crop fields, wetlands, and forests. The study area was classified to these categories based on a decision tree algorithm using parameters calculated from the original LIDAR dataset (sigmaZ, reflectance, aspect, slope, echoratio, roughness), at resolution identical to the output DTM. For the points within spatial units belonging to each of these categories, we implemented different filtering and interpolation methods to select ground points. For buildings, roof and wall points were removed and the resulting gap filled by interpolated based on the neighbouring data. In forests we calculated a first smooth approximate surface based on minimum points every 10 meter cells. We calculated a residual value for every point of this surface in this class. Then we analysed the point cloud based on residuals value and made an optimum threshold which classified the datasets for non-ground and ground points. In wetlands and croplands, the point height range

  7. Adapting observationally based metrics of biogeophysical feedbacks from land cover/land use change to climate modeling

    International Nuclear Information System (INIS)

    Chen, Liang; Dirmeyer, Paul A

    2016-01-01

    To assess the biogeophysical impacts of land cover/land use change (LCLUC) on surface temperature, two observation-based metrics and their applicability in climate modeling were explored in this study. Both metrics were developed based on the surface energy balance, and provided insight into the contribution of different aspects of land surface change (such as albedo, surface roughness, net radiation and surface heat fluxes) to changing climate. A revision of the first metric, the intrinsic biophysical mechanism, can be used to distinguish the direct and indirect effects of LCLUC on surface temperature. The other, a decomposed temperature metric, gives a straightforward depiction of separate contributions of all components of the surface energy balance. These two metrics well capture observed and model simulated surface temperature changes in response to LCLUC. Results from paired FLUXNET sites and land surface model sensitivity experiments indicate that surface roughness effects usually dominate the direct biogeophysical feedback of LCLUC, while other effects play a secondary role. However, coupled climate model experiments show that these direct effects can be attenuated by large scale atmospheric changes (indirect feedbacks). When applied to real-time transient LCLUC experiments, the metrics also demonstrate usefulness for assessing the performance of climate models and quantifying land–atmosphere interactions in response to LCLUC. (letter)

  8. Historical reconstruction of spatial distribution of land use/land cover in the early reclaimed time of Northeast China——Based on the HLURM model

    Science.gov (United States)

    Yang, Yuanyuan; Zhang, Shuwen; Liu, Yansui

    2017-04-01

    Understanding long-term human-environment interactions is essential to understanding changes in terrestrial ecosystems and this requires historical reconstruction of past land cover changes. Historical reconstruction of land use/land cover (LULC) aims to reproduce information concerning past land use, not only the quantity of land use/cover in a historical period, but also the spatial distribution. Recently, improved remote sensing technology has made feasible the continuous observation of land cover. However, remotely-sensed data have only existed for the last four decades at most, following the advent of the first land satellite, LandSat-1, launched in 1972. Prior to that, other data sources must be relied on, which may cover the global scale but often inconsistently. In this context, increasing numbers of researchers have made efforts to reconstruct historical LULC based on prime data sources and research approaches. And significant progress in gathering historical land change data has been made both at global and regional scales. However, most of the existing historical LULC reconstructions do not sufficiently meet the requirements of climate assessments due to insufficient spatial and thematic detail and the lack of consideration of various land change types. Most current studies do not thematically represent 100% of the land area, and ignore the consideration of completing land categories and land conversion types. Current research mainly focuses on arable land, wetland and forestland and it does not provide information on land categories such as settlement, water, and other land types. It is a research direction to build historical spatial land use and land cover datasets with high resolution. This paper provides a retrospective overview of historical reconstruction methods of past land-cover based on the prime data sources and research approaches. This research also explored the possibility of building a spatial-explicit modeling framework named HLURM

  9. 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

  10. A review of supervised object-based land-cover image classification

    Science.gov (United States)

    Ma, Lei; Li, Manchun; Ma, Xiaoxue; Cheng, Liang; Du, Peijun; Liu, Yongxue

    2017-08-01

    Object-based image classification for land-cover mapping purposes using remote-sensing imagery has attracted significant attention in recent years. Numerous studies conducted over the past decade have investigated a broad array of sensors, feature selection, classifiers, and other factors of interest. However, these research results have not yet been synthesized to provide coherent guidance on the effect of different supervised object-based land-cover classification processes. In this study, we first construct a database with 28 fields using qualitative and quantitative information extracted from 254 experimental cases described in 173 scientific papers. Second, the results of the meta-analysis are reported, including general characteristics of the studies (e.g., the geographic range of relevant institutes, preferred journals) and the relationships between factors of interest (e.g., spatial resolution and study area or optimal segmentation scale, accuracy and number of targeted classes), especially with respect to the classification accuracy of different sensors, segmentation scale, training set size, supervised classifiers, and land-cover types. Third, useful data on supervised object-based image classification are determined from the meta-analysis. For example, we find that supervised object-based classification is currently experiencing rapid advances, while development of the fuzzy technique is limited in the object-based framework. Furthermore, spatial resolution correlates with the optimal segmentation scale and study area, and Random Forest (RF) shows the best performance in object-based classification. The area-based accuracy assessment method can obtain stable classification performance, and indicates a strong correlation between accuracy and training set size, while the accuracy of the point-based method is likely to be unstable due to mixed objects. In addition, the overall accuracy benefits from higher spatial resolution images (e.g., unmanned aerial

  11. GAP Land Cover - Image

    Data.gov (United States)

    Minnesota Department of Natural Resources — This raster dataset is a simple image of the original detailed (1-acre minimum), hierarchically organized vegetation cover map produced by computer classification of...

  12. PIXEL-BASED CLASSIFICATION ANALYSIS OF LAND USE LAND COVER USING SENTINEL-2 AND LANDSAT-8 DATA

    Directory of Open Access Journals (Sweden)

    A. Sekertekin

    2017-11-01

    Full Text Available The aim of this study is to conduct accuracy analyses of Land Use Land Cover (LULC classifications derived from Sentinel-2 and Landsat-8 data, and to reveal which dataset present better accuracy results. Zonguldak city and its near surrounding was selected as study area for this case study. Sentinel-2 Multispectral Instrument (MSI and Landsat-8 the Operational Land Imager (OLI data, acquired on 6 April 2016 and 3 April 2016 respectively, were utilized as satellite imagery in the study. The RGB and NIR bands of Sentinel-2 and Landsat-8 were used for classification and comparison. Pan-sharpening process was carried out for Landsat-8 data before classification because the spatial resolution of Landsat-8 (30m is far from Sentinel-2 RGB and NIR bands (10m. LULC images were generated using pixel-based Maximum Likelihood (MLC supervised classification method. As a result of the accuracy assessment, kappa statistics for Sentinel-2 and Landsat-8 data were 0.78 and 0.85 respectively. The obtained results showed that Sentinel-2 MSI presents more satisfying LULC images than Landsat-8 OLI data. However, in some areas of Sea class Landsat-8 presented better results than Sentinel-2.

  13. Pixel-Based Classification Analysis of Land Use Land Cover Using SENTINEL-2 and LANDSAT-8 Data

    Science.gov (United States)

    Sekertekin, A.; Marangoz, A. M.; Akcin, H.

    2017-11-01

    The aim of this study is to conduct accuracy analyses of Land Use Land Cover (LULC) classifications derived from Sentinel-2 and Landsat-8 data, and to reveal which dataset present better accuracy results. Zonguldak city and its near surrounding was selected as study area for this case study. Sentinel-2 Multispectral Instrument (MSI) and Landsat-8 the Operational Land Imager (OLI) data, acquired on 6 April 2016 and 3 April 2016 respectively, were utilized as satellite imagery in the study. The RGB and NIR bands of Sentinel-2 and Landsat-8 were used for classification and comparison. Pan-sharpening process was carried out for Landsat-8 data before classification because the spatial resolution of Landsat-8 (30m) is far from Sentinel-2 RGB and NIR bands (10m). LULC images were generated using pixel-based Maximum Likelihood (MLC) supervised classification method. As a result of the accuracy assessment, kappa statistics for Sentinel-2 and Landsat-8 data were 0.78 and 0.85 respectively. The obtained results showed that Sentinel-2 MSI presents more satisfying LULC images than Landsat-8 OLI data. However, in some areas of Sea class Landsat-8 presented better results than Sentinel-2.

  14. 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

    Full Text Available En Colombia, desde hace algunos años, se viene trabajando en la construcción de cartografía temática de usos del suelo escala 1:100.000, utilizando la metodología desarrollada en Europa y denominada Corine Land Cover (CLC. Esto se ha logrado con el apoyo del Instituto Forestal Nacional de Francia (ONF a varios organismos nacionales, como el Instituto Geográfico Agustín Codazzi (IGAC, la Corporación Autónoma Regional Cormagdalena y el Instituto de Estudios Ambientales (IDEAM. El objetivo de la investigación fue determinar los cambios en el uso del suelo entre 1992 y 2005 para una región de los Andes colombianos, además identificar las potencialidades y limitaciones de la metodología CLC en el ámbito colombiano. Para ello se ajustó la leyenda a las condiciones de Colombia, se mejoró la unidad mínima de mapeo a 0.5 ha, y se utilizaron como fuentes de información escenas Ikonos Geo no ortorrectificadas. Con la metodología aplicada en esta investigación, se encontró entre los años 1992 y 2005, una disminución del área total en fragmentos boscosos, una disminución del área total en pastos, y un aumento en cultivos. Esta metodología puede ser utilizada en tareas de actualización de coberturas del suelo que requieran un alto nivel de detalle, sin embargo, se recomienda disminuir los errores geométricos con imágenes ortorrectificadas al trabajar en zonas de alta pendiente como es el caso de los Andes colombianos.During the last few years, the European Corine Land Cover method has been used in Colombia in order to update land use maps. Four institutes have been involved in this process: The National Forest Institute of France (ONF, El Instituto Geográfico Agustin Codazzi (IGAC, La Corporación Autonoma Regional Cormagdalena, and El instituto de Estudios Ambientales (IDEAM. The goal of this paper was to determine Land use-land cover change based on the CLC method. The study ranges between 1992 and 2005 along a transect of the

  15. The Analysis of Land Use Based on CORINE Land Cover in the Romanian Part of the Tisa Catchment Area

    Directory of Open Access Journals (Sweden)

    CIPRIAN MOLDOVAN

    2010-01-01

    Full Text Available The analysis of the land use structure of the 13 counties of the Romanian part of Tisa catchment area has been made according to the 2000 edition of CORINE Land Cover, while the 1990 edition has been used for comparative purposes. Out of the total area of 8,269,229.48 hectares, the forests cover 37.92%, the arable lands 35.02% and the grasslands 17.97%. The other types of land use have lower weights, such as the continuous and discontinuous urban fabric 4.81%, the orchards 1.10% and the vineyards 0.98%. In the category of forests, the following types of land use are included: broad-leaved forests, which form the majority (24.72%, coniferous forests (6.22%, mixed forests (3.46% and transitional woodland-shrub areas (3.52%. The forests are mainly located in the Carpathians and the hills. The non-irrigated arable lands (23.50% are predominant within the arable lands. They lie mostly in the Western Plain and in the basins and corridors of the Transylvanian Depression and the Western Hills. The analysis of the dynamics of the land use structure between 1990 and 2000 indicates a relative stability in the case of forests, a decrease of arable lands and an increase of grasslands.

  16. Comparison of land cover classification methods based on single-temporal MODIS data

    Science.gov (United States)

    Han, Tao; Xu, Xiaotao; Li, Yaohui; Xie, Yaowen

    2008-10-01

    Based on single-temporal MODIS data of Gansu province, mainly using its spectra information, three classifiers - the Maximum likelihood, BP neural network and decision tree based on data mining software See 5.0 are applied in the Land cover classification research. The validated results show that decision tree algorithm has the best performance of extraction with an overall accuracy of 82.13 percent, followed by the BP network algorithm, and that of the maximum likelihood classifier is worst; the accuracy of low vegetation area is improved with the indexes of TVA and TVD; Data mining software of See 5.0 with boosting technique can build decision tree quickly and improve the precision of miscible classes.

  17. Land Use and Land Cover Change in Guangzhou, China, from 1998 to 2003, Based on Landsat TM /ETM+ Imagery

    Directory of Open Access Journals (Sweden)

    Yunpeng Wang

    2007-07-01

    Full Text Available Land use and land cover change is a major issue in global environment change,and is especially significant in rapidly developing regions in the world. With its economicdevelopment, population growth, and urbanization, Guangzhou, a major metropolitan inSouth China, have experienced a dramatic land use and land cover (LULC change over thepast 30 years. Fast LULC change have resulted in degradation of its ecosystems andaffected adversely the environment. It is urgently needed to monitor its LULC changes andto analyses the consequences of these changes in order to provide information for policy-makers to support sustainable development. This study employed two Landsat TM/ETM images in the dry season to detect LULC patterns in 1998 and 2003, and to examine LULCchanges during the period from 1998 to 2003. The type, rate, and pattern of the changesamong five counties of Guangzhou Municipality were analyzed in details by post-classification method. LULC conversion matrix was produced for each county in order toexplore and explain the urban expansion and cropland loss, the most significant types ofLULC change. Land use conversion matrixes of five counties were discussed respectivelyin order to explore and explain the inherence of land use change. The results showed thaturban expansion in these five counties kept an even rate of increase, while substantialamount of cropland vanished during the period. It is also noted that the conversion between cropland and orchard land was intensive. Forest land became the main source of new croplands.

  18. TEXTURE BASED LAND COVER CLASSIFICATION ALGORITHM USING GABOR WAVELET AND ANFIS CLASSIFIER

    Directory of Open Access Journals (Sweden)

    S. Jenicka

    2016-05-01

    Full Text Available Texture features play a predominant role in land cover classification of remotely sensed images. In this study, for extracting texture features from data intensive remotely sensed image, Gabor wavelet has been used. Gabor wavelet transform filters frequency components of an image through decomposition and produces useful features. For classification of fuzzy land cover patterns in the remotely sensed image, Adaptive Neuro Fuzzy Inference System (ANFIS has been used. The strength of ANFIS classifier is that it combines the merits of fuzzy logic and neural network. Hence in this article, land cover classification of remotely sensed image has been performed using Gabor wavelet and ANFIS classifier. The classification accuracy of the classified image obtained is found to be 92.8%.

  19. 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.

  20. 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.

  1. 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.

  2. National-scale cropland mapping based on spectral-temporal features and outdated land cover information.

    Directory of Open Access Journals (Sweden)

    François Waldner

    Full Text Available The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring.

  3. Polsar Land Cover Classification Based on Hidden Polarimetric Features in Rotation Domain and Svm Classifier

    Science.gov (United States)

    Tao, C.-S.; Chen, S.-W.; Li, Y.-Z.; Xiao, S.-P.

    2017-09-01

    Land cover classification is an important application for polarimetric synthetic aperture radar (PolSAR) data utilization. Rollinvariant polarimetric features such as H / Ani / text-decoration: overline">α / Span are commonly adopted in PolSAR land cover classification. However, target orientation diversity effect makes PolSAR images understanding and interpretation difficult. Only using the roll-invariant polarimetric features may introduce ambiguity in the interpretation of targets' scattering mechanisms and limit the followed classification accuracy. To address this problem, this work firstly focuses on hidden polarimetric feature mining in the rotation domain along the radar line of sight using the recently reported uniform polarimetric matrix rotation theory and the visualization and characterization tool of polarimetric coherence pattern. The former rotates the acquired polarimetric matrix along the radar line of sight and fully describes the rotation characteristics of each entry of the matrix. Sets of new polarimetric features are derived to describe the hidden scattering information of the target in the rotation domain. The latter extends the traditional polarimetric coherence at a given rotation angle to the rotation domain for complete interpretation. A visualization and characterization tool is established to derive new polarimetric features for hidden information exploration. Then, a classification scheme is developed combing both the selected new hidden polarimetric features in rotation domain and the commonly used roll-invariant polarimetric features with a support vector machine (SVM) classifier. Comparison experiments based on AIRSAR and multi-temporal UAVSAR data demonstrate that compared with the conventional classification scheme which only uses the roll-invariant polarimetric features, the proposed classification scheme achieves both higher classification accuracy and better robustness. For AIRSAR data, the overall classification

  4. 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

  5. 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

  6. Remote Sensing GIS Based Spatio-temporal Land Use/ Cover Study ...

    African Journals Online (AJOL)

    Vegetations showed loss and gain changes. Forested areas were diminished greatly due to their conversion to other forms of land use/cover across the whole period. Much of the original dense forests (171.16 sq. km of the area) were lost with 5.186 sq.km average annual loss. Extreme forest loss was recorded during the ...

  7. Landscapes‘ Capacities to Provide Ecosystem Services – a Concept for Land-Cover Based Assessments

    Directory of Open Access Journals (Sweden)

    Benjamin Burkhard

    2009-12-01

    Full Text Available Landscapes differ in their capacities to provide ecosystem goods and services, which are the benefits humans obtain from nature. Structures and functions of ecosystems needed to sustain the provision of ecosystem services are altered by various human activities. In this paper, a concept for the assessment of multiple ecosystem services is proposed as a basis for discussion and further development of a respective evaluation instrument. Using quantitative and qualitative assessment data in combination with land cover and land use information originated from remote sensing and GIS, impacts of human activities can be evaluated. The results reveal typical patterns of different ecosystems‘ capacities to provide ecosystem services. The proposed approach thus delivers useful integrative information for environmental management and landscape planning, aiming at a sustainable use of services provided by nature. The research concept and methodological framework presented here for discussion have initially been applied in different case studies and shall be developed further to provide a useful tool for the quantification and spatial modelling of multiple ecosystem services in different landscapes. An exemplary application of the approach dealing with food provision in the Halle-Leipzig region in Germany is presented. It shows typical patterns of ecosystem service distribution around urban areas. As the approach is new and still rather general, there is great potential for improvement, especially with regard to a data-based quantification of the numerous hypotheses, which were formulated as base for the assessment. Moreover, the integration of more detailed landscape information on different scales will be needed in future in order to take the heterogeneous distribution of landscape properties and values into account. Therefore, the purpose of this paper is to foster critical discussions on the methodological development presented here.

  8. A Landsat-Based Assessment of Mobile Bay Land Use and Land Cover Change from 1974 to 2008

    Science.gov (United States)

    Spruce, Joseph; Ellis, Jean; Smoot, James; Swann, Roberta; Graham, William

    2009-01-01

    The Mobile Bay region has experienced noteworthy land use and land cover (LULC) change in the latter half of the 20th century. Accompanying this change has been urban expansion and a reduction of rural land uses. Much of this LULC change has reportedly occurred since the landfall of Hurricane Frederic in 1979. The Mobile Bay region provides great economic and ecologic benefits to the Nation, including important coastal habitat for a broad diversity of fisheries and wildlife. Regional urbanization threatens the estuary s water quality and aquatic-habitat dependent biota, including commercial fisheries and avian wildlife. Coastal conservation and urban land use planners require additional information on historical LULC change to support coastal habitat restoration and resiliency management efforts. This presentation discusses results of a Gulf of Mexico Application Pilot project that was conducted in 2008 to quantify and assess LULC change from 1974 to 2008. This project was led by NASA Stennis Space Center and involved multiple Gulf of Mexico Alliance (GOMA) partners, including the Mobile Bay National Estuary Program (NEP), the U.S. Army Corps of Engineers, the National Oceanic and Atmospheric Administration s (NOAA s) National Coastal Data Development Center (NCDDC), and the NOAA Coastal Services Center. Nine Landsat images were employed to compute LULC products because of their availability and suitability for the application. The project also used Landsat-based national LULC products, including coastal LULC products from NOAA s Coastal Change & Analysis Program (C-CAP), available at 5-year intervals since 1995. Our study was initiated in part because C-CAP LULC products were not available to assess the region s urbanization prior to 1995 and subsequent to post Hurricane Katrina in 2006. This project assessed LULC change across the 34-year time frame and at decadal and middecadal scales. The study area included the majority of Mobile and Baldwin counties that

  9. Optimizing land cover change detection using combined pixel-based and object-based image classification in a mountainous area in Mexico

    NARCIS (Netherlands)

    Aguirre Gutiérrez, J.; Seijmonsbergen, A.C.; Duivenvoorden, J.; Epiphanio, J.C.N.; Galvão, L.S.; dos Campos, S.J.

    2011-01-01

    Inventories of past and present land cover changes form the basis for future conservation strategies and landscape management. In this study Landsat images of a mountainous area in Mexico are used in an object-based and pixel-based image classification. The land cover categories with the highest

  10. Chesapeake bay watershed land cover data series

    Science.gov (United States)

    Irani, Frederick M.; Claggett, Peter

    2010-01-01

    To better understand how the land is changing and to relate those changes to water quality trends, the USGS EGSC funded the production of a Chesapeake Bay Watershed Land Cover Data Series (CBLCD) representing four dates: 1984, 1992, 2001, and 2006. EGSC will publish land change forecasts based on observed trends in the CBLCD over the coming year. They are in the process of interpreting and publishing statistics on the extent, type and patterns of land cover change for 1984-2006 in the Bay watershed, major tributaries and counties.

  11. Image-based change estimation (ICE): monitoring land use, land cover and agent of change information for all lands

    Science.gov (United States)

    Kevin Megown; Andy Lister; Paul Patterson; Tracey Frescino; Dennis Jacobs; Jeremy Webb; Nicholas Daniels; Mark. Finco

    2015-01-01

    The Image-based Change Estimation (ICE) protocols have been designed to respond to several Agency and Department information requirements. These include provisions set forth by the 2014 Farm Bill, the Forest Service Action Plan and Strategic Plan, the 2012 Planning Rule, and the 2015 Planning Directives. ICE outputs support the information needs by providing estimates...

  12. Assessing naturalness in northern great lakes forests based on historical land-cover and vegetation changes.

    Science.gov (United States)

    Gimmi, Urs; Radeloff, Volker C

    2013-08-01

    The concept of naturalness was developed to assess to what degree landscapes represent a natural state. Protected areas are often regarded as the remnants of untouched landscapes although many landscapes commonly perceived as pristine have a long history of human impact. Here, we introduced a historical perspective into the concept of naturalness and the analysis of the effectiveness of protected areas by analyzing historical trajectories in land-cover and forest communities for the Pictured Rocks National Lakeshore on Michigan's Upper Peninsula (USA). Distribution of land-cover and forest community types was reconstructed for pre-settlement time (around 1850), the height of agricultural expansion (1928), and modern conditions (2000). Naturalness of the landscape was assessed by analyzing similarity between pre-settlement and current conditions and by assessing landscape continuity (1850-1928-2000). We compared changes in the strictly protected park core zone with those in the inland buffer zone with ongoing sustainable logging, and a not protected area adjacent to the park. Forest was the dominant land-cover type over the entire study period. We detected a gradient in land-cover continuity from the core zone (81 % continuity) to the inland buffer zone (74 %) and the area outside the park (66 %). Northern hardwood was the dominating forest type in all time points with high continuity (76 %). In contrast, pine forests show a more dynamic pattern with more than 50 % of the initial forests switching to non-forest or early succession forest types by 1928. More than half of the study area was considered as "natural virgin" (no changes in land-cover and forest community type) with a higher portion within the park than in the adjacent area. In contrast, areas with low naturalness are more abundant outside the park. Our study demonstrates the value of integrating historical information into naturalness assessments and the results provide useful information for future

  13. Land Cover Change Community-based Processing and Analysis System (LC-ComPS): Lessons Learned from Technology Infusion

    Science.gov (United States)

    Masek, J.; Rao, A.; Gao, F.; Davis, P.; Jackson, G.; Huang, C.; Weinstein, B.

    2008-12-01

    The Land Cover Change Community-based Processing and Analysis System (LC-ComPS) combines grid technology, existing science modules, and dynamic workflows to enable users to complete advanced land data processing on data available from local and distributed archives. Changes in land cover represent a direct link between human activities and the global environment, and in turn affect Earth's climate. Thus characterizing land cover change has become a major goal for Earth observation science. Many science algorithms exist to generate new products (e.g., surface reflectance, change detection) used to study land cover change. The overall objective of the LC-ComPS is to release a set of tools and services to the land science community that can be implemented as a flexible LC-ComPS to produce surface reflectance and land-cover change information with ground resolution on the order of Landsat-class instruments. This package includes software modules for pre-processing Landsat-type satellite imagery (calibration, atmospheric correction, orthorectification, precision registration, BRDF correction) for performing land-cover change analysis and includes pre-built workflow chains to automatically generate surface reflectance and land-cover change products based on user input. In order to meet the project objectives, the team created the infrastructure (i.e., client-server system with graphical and machine interfaces) to expand the use of these existing science algorithm capabilities in a community with distributed, large data archives and processing centers. Because of the distributed nature of the user community, grid technology was chosen to unite the dispersed community resources. At that time, grid computing was not used consistently and operationally within the Earth science research community. Therefore, there was a learning curve to configure and implement the underlying public key infrastructure (PKI) interfaces, required for the user authentication, secure file

  14. Land cover mapping of North and Central America—Global Land Cover 2000

    Science.gov (United States)

    Latifovic, Rasim; Zhu, Zhi-Liang

    2004-01-01

    The Land Cover Map of North and Central America for the year 2000 (GLC 2000-NCA), prepared by NRCan/CCRS and USGS/EROS Data Centre (EDC) as a regional component of the Global Land Cover 2000 project, is the subject of this paper. A new mapping approach for transforming satellite observations acquired by the SPOT4/VGTETATION (VGT) sensor into land cover information is outlined. The procedure includes: (1) conversion of daily data into 10-day composite; (2) post-seasonal correction and refinement of apparent surface reflectance in 10-day composite images; and (3) extraction of land cover information from the composite images. The pre-processing and mosaicking techniques developed and used in this study proved to be very effective in removing cloud contamination, BRDF effects, and noise in Short Wave Infra-Red (SWIR). The GLC 2000-NCA land cover map is provided as a regional product with 28 land cover classes based on modified Federal Geographic Data Committee/Vegetation Classification Standard (FGDC NVCS) classification system, and as part of a global product with 22 land cover classes based on Land Cover Classification System (LCCS) of the Food and Agriculture Organisation. The map was compared on both areal and per-pixel bases over North and Central America to the International Geosphere–Biosphere Programme (IGBP) global land cover classification, the University of Maryland global land cover classification (UMd) and the Moderate Resolution Imaging Spectroradiometer (MODIS) Global land cover classification produced by Boston University (BU). There was good agreement (79%) on the spatial distribution and areal extent of forest between GLC 2000-NCA and the other maps, however, GLC 2000-NCA provides additional information on the spatial distribution of forest types. The GLC 2000-NCA map was produced at the continental level incorporating specific needs of the region.

  15. A SEMI-AUTOMATIC RULE SET BUILDING METHOD FOR URBAN LAND COVER CLASSIFICATION BASED ON MACHINE LEARNING AND HUMAN KNOWLEDGE

    Directory of Open Access Journals (Sweden)

    H. Y. Gu

    2017-09-01

    Full Text Available Classification rule set is important for Land Cover classification, which refers to features and decision rules. The selection of features and decision are based on an iterative trial-and-error approach that is often utilized in GEOBIA, however, it is time-consuming and has a poor versatility. This study has put forward a rule set building method for Land cover classification based on human knowledge and machine learning. The use of machine learning is to build rule sets effectively which will overcome the iterative trial-and-error approach. The use of human knowledge is to solve the shortcomings of existing machine learning method on insufficient usage of prior knowledge, and improve the versatility of rule sets. A two-step workflow has been introduced, firstly, an initial rule is built based on Random Forest and CART decision tree. Secondly, the initial rule is analyzed and validated based on human knowledge, where we use statistical confidence interval to determine its threshold. The test site is located in Potsdam City. We utilised the TOP, DSM and ground truth data. The results show that the method could determine rule set for Land Cover classification semi-automatically, and there are static features for different land cover classes.

  16. a Semi-Automatic Rule Set Building Method for Urban Land Cover Classification Based on Machine Learning and Human Knowledge

    Science.gov (United States)

    Gu, H. Y.; Li, H. T.; Liu, Z. Y.; Shao, C. Y.

    2017-09-01

    Classification rule set is important for Land Cover classification, which refers to features and decision rules. The selection of features and decision are based on an iterative trial-and-error approach that is often utilized in GEOBIA, however, it is time-consuming and has a poor versatility. This study has put forward a rule set building method for Land cover classification based on human knowledge and machine learning. The use of machine learning is to build rule sets effectively which will overcome the iterative trial-and-error approach. The use of human knowledge is to solve the shortcomings of existing machine learning method on insufficient usage of prior knowledge, and improve the versatility of rule sets. A two-step workflow has been introduced, firstly, an initial rule is built based on Random Forest and CART decision tree. Secondly, the initial rule is analyzed and validated based on human knowledge, where we use statistical confidence interval to determine its threshold. The test site is located in Potsdam City. We utilised the TOP, DSM and ground truth data. The results show that the method could determine rule set for Land Cover classification semi-automatically, and there are static features for different land cover classes.

  17. Pollen-based quantitative reconstructions of Holocene regional vegetation cover (plant-functional types and land-cover types) in Europe suitable for climate modelling.

    Science.gov (United States)

    Trondman, A-K; Gaillard, M-J; Mazier, F; Sugita, S; Fyfe, R; Nielsen, A B; Twiddle, C; Barratt, P; Birks, H J B; Bjune, A E; Björkman, L; Broström, A; Caseldine, C; David, R; Dodson, J; Dörfler, W; Fischer, E; van Geel, B; Giesecke, T; Hultberg, T; Kalnina, L; Kangur, M; van der Knaap, P; Koff, T; Kuneš, P; Lagerås, P; Latałowa, M; Lechterbeck, J; Leroyer, C; Leydet, M; Lindbladh, M; Marquer, L; Mitchell, F J G; Odgaard, B V; Peglar, S M; Persson, T; Poska, A; Rösch, M; Seppä, H; Veski, S; Wick, L

    2015-02-01

    We present quantitative reconstructions of regional vegetation cover in north-western Europe, western Europe north of the Alps, and eastern Europe for five time windows in the Holocene [around 6k, 3k, 0.5k, 0.2k, and 0.05k calendar years before present (bp)] at a 1° × 1° spatial scale with the objective of producing vegetation descriptions suitable for climate modelling. The REVEALS model was applied on 636 pollen records from lakes and bogs to reconstruct the past cover of 25 plant taxa grouped into 10 plant-functional types and three land-cover types [evergreen trees, summer-green (deciduous) trees, and open land]. The model corrects for some of the biases in pollen percentages by using pollen productivity estimates and fall speeds of pollen, and by applying simple but robust models of pollen dispersal and deposition. The emerging patterns of tree migration and deforestation between 6k bp and modern time in the REVEALS estimates agree with our general understanding of the vegetation history of Europe based on pollen percentages. However, the degree of anthropogenic deforestation (i.e. cover of cultivated and grazing land) at 3k, 0.5k, and 0.2k bp is significantly higher than deduced from pollen percentages. This is also the case at 6k in some parts of Europe, in particular Britain and Ireland. Furthermore, the relationship between summer-green and evergreen trees, and between individual tree taxa, differs significantly when expressed as pollen percentages or as REVEALS estimates of tree cover. For instance, when Pinus is dominant over Picea as pollen percentages, Picea is dominant over Pinus as REVEALS estimates. These differences play a major role in the reconstruction of European landscapes and for the study of land cover-climate interactions, biodiversity and human resources. © 2014 The Authors Global Change Biology Published by John Wiley & Sons Ltd.

  18. LAND COVER CHANGE DETECTION BASED ON GENETICALLY FEATURE AELECTION AND IMAGE ALGEBRA USING HYPERION HYPERSPECTRAL IMAGERY

    Directory of Open Access Journals (Sweden)

    S. T. Seydi

    2015-12-01

    Full Text Available The Earth has always been under the influence of population growth and human activities. This process causes the changes in land use. Thus, for optimal management of the use of resources, it is necessary to be aware of these changes. Satellite remote sensing has several advantages for monitoring land use/cover resources, especially for large geographic areas. Change detection and attribution of cultivation area over time present additional challenges for correctly analyzing remote sensing imagery. In this regards, for better identifying change in multi temporal images we use hyperspectral images. Hyperspectral images due to high spectral resolution created special placed in many of field. Nevertheless, selecting suitable and adequate features/bands from this data is crucial for any analysis and especially for the change detection algorithms. This research aims to automatically feature selection for detect land use changes are introduced. In this study, the optimal band images using hyperspectral sensor using Hyperion hyperspectral images by using genetic algorithms and Ratio bands, we select the optimal band. In addition, the results reveal the superiority of the implemented method to extract change map with overall accuracy by a margin of nearly 79% using multi temporal hyperspectral imagery.

  19. Pixel-Based Land Cover Classification by Fusing Hyperspectral and LIDAR Data

    Science.gov (United States)

    Jahan, F.; Awrangjeb, M.

    2017-09-01

    Land cover classification has many applications like forest management, urban planning, land use change identification and environment change analysis. The passive sensing of hyperspectral systems can be effective in describing the phenomenology of the observed area over hundreds of (narrow) spectral bands. On the other hand, the active sensing of LiDAR (Light Detection and Ranging) systems can be exploited for characterising topographical information of the area. As a result, the joint use of hyperspectral and LiDAR data provides a source of complementary information, which can greatly assist in the classification of complex classes. In this study, we fuse hyperspectral and LiDAR data for land cover classification. We do a pixel-wise classification on a disjoint set of training and testing samples for five different classes. We propose a new feature combination by fusing features from both hyperspectral and LiDAR, which achieves competent classification accuracy with low feature dimension, while the existing method requires high dimensional feature vector to achieve similar classification result. Also, for the reduction of the dimension of the feature vector, Principal Component Analysis (PCA) is used as it captures the variance of the samples with a limited number of Principal Components (PCs). We tested our classification method using PCA applied on hyperspectral bands only and combined hyperspectral and LiDAR features. Classification with support vector machine (SVM) and decision tree shows that our feature combination achieves better classification accuracy compared to the existing feature combination, while keeping the similar number of PCs. The experimental results also show that decision tree performs better than SVM and requires less execution time.

  20. Landscape-based upstream-downstream prevalence of land-use/cover change drivers in southeastern rift escarpment of Ethiopia.

    Science.gov (United States)

    Temesgen, Habtamu; Wu, Wei; Legesse, Abiyot; Yirsaw, Eshetu; Bekele, Belew

    2018-02-23

    Characterized by high population density on a rugged topography, the Gedeo-Abaya landscape dominantly contains a multi-strata traditional agroforests showing the insight of Gedeo farmers on natural resource management practices. Currently, this area has been losing its resilience and is becoming unable to sustain its inhabitants. Based on both RS-derived and GIS-computed land-use/cover changes (LUCC) as well as socioeconomic validations, this article explored the LUCC and agroecological-based driver patterns in Gedeo-Abaya landscape from 1986 to 2015. A combination of geo-spatial technology and cross-sectional survey design were employed to detect the drivers behind these changes. The article discussed that LUCC and the prevalence of drivers are highly diverse and vary throughout agroecological zones. Except for the population, most downstream top drivers are perceived as insignificant in the upstream region and vice versa. In the downstream, land-use/cover (LUC) classes are more dynamic, diverse, and challenged by nearly all anticipated drivers than are upstream ones. Agroforestry LUC has been increasing (by 25% of its initial cover) and is becoming the predominant cover type, although socioeconomic analysis and related findings show its rapid LUC modification. A rapid reduction of woodland/shrubland (63%) occurred in the downstream, while wetland/marshy land increased threefold (158%), from 1986 to 2015 with annual change rates of - 3.7 and + 6%, respectively. Land degradation induced by changes in land use is a serious problem in Africa, especially in the densely populated sub-Saharan regions such as Ethiopia (FAO 2015). Throughout the landscape, LUCC is prominently affecting land-use system of the study landscape due to population pressure in the upstream region and drought/rainfall variability, agribusiness investment, and charcoaling in the downstream that necessitate urgent action.

  1. Holocene land-cover reconstructions for studies on land cover-climate feedbacks

    Directory of Open Access Journals (Sweden)

    M.-J. Gaillard

    2010-07-01

    Full Text Available The major objectives of this paper are: (1 to review the pros and cons of the scenarios of past anthropogenic land cover change (ALCC developed during the last ten years, (2 to discuss issues related to pollen-based reconstruction of the past land-cover and introduce a new method, REVEALS (Regional Estimates of VEgetation Abundance from Large Sites, to infer long-term records of past land-cover from pollen data, (3 to present a new project (LANDCLIM: LAND cover – CLIMate interactions in NW Europe during the Holocene currently underway, and show preliminary results of REVEALS reconstructions of the regional land-cover in the Czech Republic for five selected time windows of the Holocene, and (4 to discuss the implications and future directions in climate and vegetation/land-cover modeling, and in the assessment of the effects of human-induced changes in land-cover on the regional climate through altered feedbacks. The existing ALCC scenarios show large discrepancies between them, and few cover time periods older than AD 800. When these scenarios are used to assess the impact of human land-use on climate, contrasting results are obtained. It emphasizes the need for methods such as the REVEALS model-based land-cover reconstructions. They might help to fine-tune descriptions of past land-cover and lead to a better understanding of how long-term changes in ALCC might have influenced climate. The REVEALS model is demonstrated to provide better estimates of the regional vegetation/land-cover changes than the traditional use of pollen percentages. This will achieve a robust assessment of land cover at regional- to continental-spatial scale throughout the Holocene. We present maps of REVEALS estimates for the percentage cover of 10 plant functional types (PFTs at 200 BP and 6000 BP, and of the two open-land PFTs "grassland" and "agricultural land" at five time-windows from 6000 BP to recent time. The LANDCLIM results are expected to provide crucial data

  2. Landsat-Based Land Cover Change in the Beijing-Tianjin-Tangshan Urban Agglomeration in 1990, 2000 and 2010

    Directory of Open Access Journals (Sweden)

    Aqiang Yang

    2017-02-01

    Full Text Available Rapid urbanization dramatically changes the local environment. A hybrid classification method is designed and applied to multi-temporal Landsat images and ancillary data to obtain land cover change datasets. A support vector machine (SVM classifier is used to classify multi-temporal Landsat Enhanced Thematic Mapper Plus (ETM+ images that were collected in 2000 at the pixel level. These images are also segmented with the mean shift method. The impervious surface is refined based on a combination of the segmented objects and the SVM classification results. The changed areas in 1990 and 2010 are determined by comparing the Thematic Mapper (TM and ETM+ images via the re-weighted multivariate alteration detection transformation method. The TM images that were masked as changed areas in 1990 and 2000 are input into the SVM classifier. Land cover maps for 1990 and 2010 are produced by combining the unchanged area in 2000 with the new classes of the changed areas in 1990 and 2010. Land cover change has continuously accelerated since 1990. Remarkably, arable land decreased, while the impervious surface area significantly increased.

  3. 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...

  4. Morphometry and land cover based multi-criteria analysis for assessing the soil erosion susceptibility of the western Himalayan watershed.

    Science.gov (United States)

    Altaf, Sadaff; Meraj, Gowhar; Romshoo, Shakil Ahmad

    2014-12-01

    Complex mountainous environments such as Himalayas are highly susceptibility to natural hazards particular those that are triggered by the action of water such as floods, soil erosion, mass movements and siltation of the hydro-electric power dams. Among all the natural hazards, soil erosion is the most implicit and the devastating hazard affecting the life and property of the millions of people living in these regions. Hence to review and devise strategies to reduce the adverse impacts of soil erosion is of utmost importance to the planners of watershed management programs in these regions. This paper demonstrates the use of satellite based remote sensing data coupled with the observational field data in a multi-criteria analytical (MCA) framework to estimate the soil erosion susceptibility of the sub-watersheds of the Rembiara basin falling in the western Himalaya, using geographical information system (GIS). In this paper, watershed morphometry and land cover are used as an inputs to the MCA framework to prioritize the sub-watersheds of this basin on the basis of their different susceptibilities to soil erosion. Methodology included the derivation of a set of drainage and land cover parameters that act as the indicators of erosion susceptibility. Further the output from the MCA resulted in the categorization of the sub-watersheds into low, medium, high and very high erosion susceptibility classes. A detailed prioritization map for the susceptible sub-watersheds based on the combined role of land cover and morphometry is finally presented. Besides, maps identifying the susceptible sub-watersheds based on morphometry and land cover only are also presented. The results of this study are part of the watershed management program in the study area and are directed to instigate appropriate measures to alleviate the soil erosion in the study area.

  5. 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...

  6. Developed land cover of Puerto Rico

    Science.gov (United States)

    William A. Gould; Sebastian Martinuzzi; Olga M. Ramos Gonzalez

    2008-01-01

    This map shows the distribution of developed land cover in Puerto Rico (Martinuzzi et al. 2007). Developed land cover refers to urban, built-up and non-vegetated areas that result from human activity. These typically include built structures, concrete, asphalt, and other infrastructure. The developed land cover was estimated using Landsat 7 ETM+ satellite images pan...

  7. 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.......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....

  8. GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed, Ethiopia.

    Science.gov (United States)

    Nigatu Wondrade; Dick, Øystein B; Tveite, Havard

    2014-03-01

    Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very

  9. Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating

    Science.gov (United States)

    Matikainen, Leena; Karila, Kirsi; Hyyppä, Juha; Litkey, Paula; Puttonen, Eetu; Ahokas, Eero

    2017-06-01

    During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are

  10. An assessment of the impact of climate change effects on forest land cover based on satellite data

    Science.gov (United States)

    Zoran, Maria A.; Dida, Adrian I.

    2015-10-01

    Climate change affects forest both directly and indirectly through disturbances, that are a natural and integral part of forest ecosystems, and climate change can alter these natural interactions. Forest vegetation characteristics, including land cover and phenology, affect processes such as water cycle, absorption and re-emission of solar radiation, momentum transfer, carbon cycle, and latent and sensible heat fluxes. The climate system responds in complex ways to changes in forcing that may be natural or human-induced. Drastic climate change over the last decades has greatly increased the importance of forest land cover changes monitoring through time-series satellite data. Satellite based derived biophysical parameters for assessment of climate impacts on forest vegetation have to meet particularly high quality requirements. Forest vegetation and climate interact through a series of complex feedbacks, which are not very well understood. Satellite remote sensing is suited tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST) and GPP (Gross Primary Production), which are key biophysical variables for studying land surface processes and surface-atmosphere interactions for forested areas. The aim of this paper was to investigate their pattern dynamics due to the impact of climate variations on a periurban forest Branesti-Cernica, placed to the North-Eastern part of Bucharest city, Romania. The forest vegetation analysis was based on derived biogeophysical parameters from time-series satellite remote sensing MODIS Terra/Aqua and NOAA AVHRR data and in-situ monitoring ground data (as air temperature, aerosols distribution, relative humidity, etc.) over 2002-2014 period.

  11. 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

  12. Land Use Changes Monitoring with CORINE Land Cover Data

    Science.gov (United States)

    Cieślak, Iwona; Szuniewicz, Karol; Pawlewicz, Katarzyna; Czyża, Szymon

    2017-10-01

    The Corine Land Cover (CLC) data is a collection of information about land cover, which was created during the program that was implemented by the EU. In this article authors proposes new index of space fragmentation, which is based on the analysis of the length of the boundaries of the various forms of land use - Ex. This papers contains the procedure of designation the new index and two examples of its use for the two regions in the north – eastern part of Poland. These regions are characterized by a particularly high environmental values. Therefore, especially for these areas it is extremely important to study the fragmentation of landscapes as monitoring the increase of anthropopression. For visualization and spatial analysis authors used GIS technology.

  13. International Coalition Land Use/Land Cover

    Data.gov (United States)

    Minnesota Department of Natural Resources — This data set is a product of an effort to update Minnesota's 1969 land use inventory. The project was funded in 1989 by the State Legislature per recommendation...

  14. 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...

  15. 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...

  16. Assessing the influence of land use land cover pattern, socio economic factors and air quality status to predict morbidity on the basis of logistic based regression model

    Science.gov (United States)

    Dixit, A.; Singh, V. K.

    2017-12-01

    Recent studies conducted by World Health Organisation (WHO) estimated that 92 % of the total world population are living in places where the air quality level has exceeded the WHO standard limit for air quality. This is due to the change in Land Use Land Cover (LULC) pattern, socio economic drivers and anthropogenic heat emission caused by manmade activity. Thereby, many prevalent human respiratory diseases such as lung cancer, chronic obstructive pulmonary disease and emphysema have increased in recent times. In this study, a quantitative relationship is developed between land use (built-up land, water bodies, and vegetation), socio economic drivers and air quality parameters using logistic based regression model over 7 different cities of India for the winter season of 2012 to 2016. Different LULC, socio economic, industrial emission sources, meteorological condition and air quality level from the monitoring stations are taken to estimate the influence on morbidity of each city. Results of correlation are analyzed between land use variables and monthly concentration of pollutants. These values range from 0.63 to 0.76. Similarly, the correlation value between land use variable with socio economic and morbidity ranges from 0.57 to 0.73. The performance of model is improved from 67 % to 79 % in estimating morbidity for the year 2015 and 2016 due to the better availability of observed data.The study highlights the growing importance of incorporating socio-economic drivers with air quality data for evaluating morbidity rate for each city in comparison to just change in quantitative analysis of air quality.

  17. 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-...

  18. EASE-Grid Land Cover Classifications Derived from Boston University MODIS/Terra Land Cover Data

    Data.gov (United States)

    National Aeronautics and Space Administration — These data provide land cover classifications derived from the Boston University MOD12Q1 V004 MODIS/Terra 1 km Land Cover Product (Friedl et al. 2002). The data are...

  19. Land Use Land Cover Changes in Detection of Water Quality: A Study Based on Remote Sensing and Multivariate Statistics.

    Science.gov (United States)

    Hua, Ang Kean

    2017-01-01

    Malacca River water quality is affected due to rapid urbanization development. The present study applied LULC changes towards water quality detection in Malacca River. The method uses LULC, PCA, CCA, HCA, NHCA, and ANOVA. PCA confirmed DS, EC, salinity, turbidity, TSS, DO, BOD, COD, As, Hg, Zn, Fe, E. coli , and total coliform. CCA confirmed 14 variables into two variates; first variate involves residential and industrial activities; and second variate involves agriculture, sewage treatment plant, and animal husbandry. HCA and NHCA emphasize that cluster 1 occurs in urban area with Hg, Fe, total coliform, and DO pollution; cluster 3 occurs in suburban area with salinity, EC, and DS; and cluster 2 occurs in rural area with salinity and EC. ANOVA between LULC and water quality data indicates that built-up area significantly polluted the water quality through E. coli , total coliform, EC, BOD, COD, TSS, Hg, Zn, and Fe, while agriculture activities cause EC, TSS, salinity, E. coli , total coliform, arsenic, and iron pollution; and open space causes contamination of turbidity, salinity, EC, and TSS. Research finding provided useful information in identifying pollution sources and understanding LULC with river water quality as references to policy maker for proper management of Land Use area.

  20. Rule-based land use/land cover classification in coastal areas using seasonal remote sensing imagery: a case study from Lianyungang City, China.

    Science.gov (United States)

    Yang, Xiaoyan; Chen, Longgao; Li, Yingkui; Xi, Wenjia; Chen, Longqian

    2015-07-01

    Land use/land cover (LULC) inventory provides an important dataset in regional planning and environmental assessment. To efficiently obtain the LULC inventory, we compared the LULC classifications based on single satellite imagery with a rule-based classification based on multi-seasonal imagery in Lianyungang City, a coastal city in China, using CBERS-02 (the 2nd China-Brazil Environmental Resource Satellites) images. The overall accuracies of the classification based on single imagery are 78.9, 82.8, and 82.0% in winter, early summer, and autumn, respectively. The rule-based classification improves the accuracy to 87.9% (kappa 0.85), suggesting that combining multi-seasonal images can considerably improve the classification accuracy over any single image-based classification. This method could also be used to analyze seasonal changes of LULC types, especially for those associated with tidal changes in coastal areas. The distribution and inventory of LULC types with an overall accuracy of 87.9% and a spatial resolution of 19.5 m can assist regional planning and environmental assessment efficiently in Lianyungang City. This rule-based classification provides a guidance to improve accuracy for coastal areas with distinct LULC temporal spectral features.

  1. Object-based land cover classification and change analysis in the Baltimore metropolitan area using multitemporal high resolution remote sensing data

    Science.gov (United States)

    Weiqi Zhou; Austin Troy; Morgan Grove

    2008-01-01

    Accurate and timely information about land cover pattern and change in urban areas is crucial for urban land management decision-making, ecosystem monitoring and urban planning. This paper presents the methods and results of an object-based classification and post-classification change detection of multitemporal high-spatial resolution Emerge aerial imagery in the...

  2. Consequences of land use and land cover change

    Science.gov (United States)

    Slonecker, E. Terrence; Barnes, Christopher; Karstensen, Krista; Milheim, Lesley E.; Roig-Silva, Coral M.

    2013-01-01

    The U.S. Geological Survey (USGS) Climate and Land Use Change Mission Area is one of seven USGS mission areas that focuses on making substantial scientific "...contributions to understanding how Earth systems interact, respond to, and cause global change". Using satellite and other remotely sensed data, USGS scientists monitor patterns of land cover change over space and time at regional, national, and global scales. These data are analyzed to understand the causes and consequences of changing land cover, such as economic impacts, effects on water quality and availability, the spread of invasive species, habitats and biodiversity, carbon fluctuations, and climate variability. USGS scientists are among the leaders in the study of land cover, which is a term that generally refers to the vegetation and artificial structures that cover the land surface. Examples of land cover include forests, grasslands, wetlands, water, crops, and buildings. Land use involves human activities that take place on the land. For example, "grass" is a land cover, whereas pasture and recreational parks are land uses that produce a cover of grass.

  3. South African National Land-Cover Change Map

    African Journals Online (AJOL)

    Fritz Schoeman

    Boundary cells were clipped according to the definitive national boundary and thus are not necessarily complete 500 m x 500 m square cell structures. 4.2.2 Conversion to Standardised Land-Cover Datasets. Prior to encoding of the 500 m x 500 m national base grid, each of the individual national land- cover datasets for ...

  4. 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...

  5. 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.

  6. 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) .

  7. Land Cover Changes Detection in Polarimetric SAR Data Using Algebra, Similarity and Distance Based Methods

    Science.gov (United States)

    Najafi, A.; Hasanlou, M.; Akbari, V.

    2017-09-01

    Monitoring and surveillance changes around the world need powerful methods, so detection, visualization, and assessment of significant changes are essential for planning and management. Incorporating polarimetric SAR images due to interactions between electromagnetic waves and target and because of the high spatial resolution almost one meter can be used to study changes in the Earth's surface. Full polarized radar images comparing to single polarized radar images use amplitude and phase information of the surface in different available polarization (HH, HV, VH, and VV). This study is based on the decomposition of full polarized airborne UAVSAR images and integration of these features with algebra method involves Image Differencing (ID) and Image Ratio (IR) algorithms with the mathematical nature and distance-based method involves Canberra (CA) and Euclidean (ED) algorithms with measuring distance between corresponding vector and similarity-based method involves Taminoto (TA) and Kulczynski (KU) algorithms with dependence corresponding vector for change detecting purposes on two real PolSAR datasets. Assessment of incorporated methods is implemented using ground truth data and different criteria for evaluating such as overall accuracy (OA), area under ROC curve (AUC) and false alarms rate (FAR). The output results show that ID, IR, and CA have superiority to detect changes comparing to other implemented algorithms. Also, numerical results show that the highest performance in two datasets has OA more than 90%. In other assessment criteria, mention algorithms have low FAR and high AUC value indices to detect changes in PolSAR images.

  8. BEMD-based high resolution image fusion for land cover classification: A case study in Guilin

    Science.gov (United States)

    Li, Lei; Liu, Guang; Jin, Qingwen; He, Chengxin; Huang, Yuqing; Yao, Yuefeng

    2016-11-01

    Analysis of image texture feature can help to reduce the adverse effects of the condition that same object but different band or same band but different object. Therefore, if it can add and highlight the texture information to the remote sensing image, it will be very helpful in the classification of ground objects. In this paper we consider to add SAR image information in classification. Bidimensional empirical mode decomposition (BEMD) has been widely applied to the analysis of non-stationary and non-linear signals. This paper proposes a new method for fusing high resolution SAR and optical image in Guilin area, based on Bidimensional empirical mode decomposition (BEMD) method.

  9. Rule-based land cover classification from very high-resolution satellite image with multiresolution segmentation

    Science.gov (United States)

    Haque, Md. Enamul; Al-Ramadan, Baqer; Johnson, Brian A.

    2016-07-01

    Multiresolution segmentation and rule-based classification techniques are used to classify objects from very high-resolution satellite images of urban areas. Custom rules are developed using different spectral, geometric, and textural features with five scale parameters, which exploit varying classification accuracy. Principal component analysis is used to select the most important features out of a total of 207 different features. In particular, seven different object types are considered for classification. The overall classification accuracy achieved for the rule-based method is 95.55% and 98.95% for seven and five classes, respectively. Other classifiers that are not using rules perform at 84.17% and 97.3% accuracy for seven and five classes, respectively. The results exploit coarse segmentation for higher scale parameter and fine segmentation for lower scale parameter. The major contribution of this research is the development of rule sets and the identification of major features for satellite image classification where the rule sets are transferable and the parameters are tunable for different types of imagery. Additionally, the individual objectwise classification and principal component analysis help to identify the required object from an arbitrary number of objects within images given ground truth data for the training.

  10. Applicability of NOAA-AVHRR 1-km data for land cover based environmental monitoring in Europe; final report Part 1

    NARCIS (Netherlands)

    Mücher, C.A.; Veldkamp, J.G.; Katwijk, van V.F.; Nieuwenhuis, G.J.A.; Velde, van de R.J.

    1996-01-01

    The multispectral and multitemporal classification approach of AVHRR data on specific dates was studied for land cover mapping on a continental scale. Major conclusions are: decision keys must be developed that exploit both the use of multitemporal composites and multispectral data; the current

  11. Optimal Decision Fusion for Urban Land-Use/Land-Cover Classification Based on Adaptive Differential Evolution Using Hyperspectral and LiDAR Data

    Directory of Open Access Journals (Sweden)

    Yanfei Zhong

    2017-08-01

    Full Text Available Hyperspectral images and light detection and ranging (LiDAR data have, respectively, the high spectral resolution and accurate elevation information required for urban land-use/land-cover (LULC classification. To combine the respective advantages of hyperspectral and LiDAR data, this paper proposes an optimal decision fusion method based on adaptive differential evolution, namely ODF-ADE, for urban LULC classification. In the ODF-ADE framework the normalized difference vegetation index (NDVI, gray-level co-occurrence matrix (GLCM and digital surface model (DSM are extracted to form the feature map. The three different classifiers of the maximum likelihood classifier (MLC, support vector machine (SVM and multinomial logistic regression (MLR are used to classify the extracted features. To find the optimal weights for the different classification maps, weighted voting is used to obtain the classification result and the weights of each classification map are optimized by the differential evolution algorithm which uses a self-adaptive strategy to obtain the parameter adaptively. The final classification map is obtained after post-processing based on conditional random fields (CRF. The experimental results confirm that the proposed algorithm is very effective in urban LULC classification.

  12. 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

  13. Implication of remotely sensed data to incorporate land cover effect into a linear reservoir-based rainfall-runoff model

    Science.gov (United States)

    Nourani, Vahid; Fard, Ahmad Fakheri; Niazi, Faegheh; Gupta, Hoshin V.; Goodrich, David C.; Kamran, Khalil Valizadeh

    2015-10-01

    This study investigates the effect of land use on the Geomorphological Cascade of Unequal linear Reservoirs (GCUR) model using the Normalized Difference Vegetation Index (NDVI) derived from remotely sensed data as a measure of land use. The proposed modeling has two important aspects: it considers the effects of both watershed geomorphology and land use/cover, and it requires only one parameter to be estimated through the use of observed rainfall-runoff data. Geographic Information System (GIS) tools are employed to determine the parameters associated with watershed geomorphology, and the Vegetation Index parameter is extracted from historical Landsat images. The modeling is applied via three formulations to a watershed located in Southeastern Arizona, which consists of two gaged sub-watersheds with different land uses. The results show that while all of the formulations generate forecasts of the basin outlet hydrographs with acceptable accuracy, only the two formulations that consider the effects of land cover (using NDVI) provide acceptable results at the outlets of the sub-watersheds.

  14. Towards a Remote Sensing Based Assessment of Land Susceptibility to Degradation: Examining Seasonal Variation in Land Use-Land Cover for Modelling Land Degradation in a Semi-Arid Context

    Science.gov (United States)

    Mashame, Gofamodimo; Akinyemi, Felicia

    2016-06-01

    Land degradation (LD) is among the major environmental and anthropogenic problems driven by land use-land cover (LULC) and climate change worldwide. For example, poor LULC practises such as deforestation, livestock overstocking, overgrazing and arable land use intensification on steep slopes disturbs the soil structure leaving the land susceptible to water erosion, a type of physical land degradation. Land degradation related problems exist in Sub-Saharan African countries such as Botswana which is semi-arid in nature. LULC and LD linkage information is still missing in many semi-arid regions worldwide.Mapping seasonal LULC is therefore very important in understanding LULC and LD linkages. This study assesses the impact of seasonal LULC variation on LD utilizing Remote Sensing (RS) techniques for Palapye region in Central District, Botswana. LULC classes for the dry and rainy seasons were classified using LANDSAT 8 images at Level I according to the Food and Agriculture Organization (FAO) International Organization of Standardization (ISO) code 19144. Level I consists of 10 LULC classes. The seasonal variations in LULC are further related to LD susceptibility in the semi-arid context. The results suggest that about 985 km² (22%) of the study area is susceptible to LD by water, major LULC types affected include: cropland, paved/rocky material, bare land, built-up area, mining area, and water body. Land degradation by water susceptibility due to seasonal land use-land cover variations is highest in the east of the study area where there is high cropland to bare land conversion.

  15. TOWARDS A REMOTE SENSING BASED ASSESSMENT OF LAND SUSCEPTIBILITY TO DEGRADATION: EXAMINING SEASONAL VARIATION IN LAND USE-LAND COVER FOR MODELLING LAND DEGRADATION IN A SEMI-ARID CONTEXT

    Directory of Open Access Journals (Sweden)

    G. Mashame

    2016-06-01

    Full Text Available Land degradation (LD is among the major environmental and anthropogenic problems driven by land use-land cover (LULC and climate change worldwide. For example, poor LULC practises such as deforestation, livestock overstocking, overgrazing and arable land use intensification on steep slopes disturbs the soil structure leaving the land susceptible to water erosion, a type of physical land degradation. Land degradation related problems exist in Sub-Saharan African countries such as Botswana which is semi-arid in nature. LULC and LD linkage information is still missing in many semi-arid regions worldwide.Mapping seasonal LULC is therefore very important in understanding LULC and LD linkages. This study assesses the impact of seasonal LULC variation on LD utilizing Remote Sensing (RS techniques for Palapye region in Central District, Botswana. LULC classes for the dry and rainy seasons were classified using LANDSAT 8 images at Level I according to the Food and Agriculture Organization (FAO International Organization of Standardization (ISO code 19144. Level I consists of 10 LULC classes. The seasonal variations in LULC are further related to LD susceptibility in the semi-arid context. The results suggest that about 985 km² (22% of the study area is susceptible to LD by water, major LULC types affected include: cropland, paved/rocky material, bare land, built-up area, mining area, and water body. Land degradation by water susceptibility due to seasonal land use-land cover variations is highest in the east of the study area where there is high cropland to bare land conversion.

  16. Assessing Land Cover Change Trajectories in Olomouc, Czech Republic

    OpenAIRE

    Mukesh Singh Boori; Vít Voženílek

    2014-01-01

    Olomouc is a unique and complex landmark with widespread forestation and land use. This research work was conducted to assess important and complex land use change trajectories in Olomouc region. Multi-temporal satellite data from 1991, 2001 and 2013 were used to extract land use/cover types by object oriented classification method. To achieve the objectives, three different aspects were used: (1) Calculate the quantity of each transition; (2) Allocate location based land...

  17. 2006-2012 Land Cover and Use Changes in Romania – An Overall Assessment Based on Corine Data

    Directory of Open Access Journals (Sweden)

    Petrişor Alexandru-Ionuţ

    2017-10-01

    Full Text Available Land cover and use changes are an important component of the global changes, and in relationship with their transitional dynamics reflect the impact of socio-economic transition. This study is aimed at exploring the land cover and use changes occurred during 2006-2012 in Romania with respect to their spatial distribution over the regions of development and main transitional dynamics. The results suggest that the main drivers of change are deforestation and urbanization, accounting for 3/4 of all changes, and that the most affected regions are the northwest, southwest, center and northeast ones. Overall, the findings suggest a continuation of the trends from the previous periods, characteristic to transition economies.

  18. LAND COVER INFORMATION EXTRACTION USING LIDAR DATA

    Directory of Open Access Journals (Sweden)

    A. Shaker

    2012-07-01

    Full Text Available Light Detection and Ranging (LiDAR systems are used intensively in terrain surface modelling based on the range data determined by the LiDAR sensors. LiDAR sensors record the distance between the sensor and the targets (range data with a capability to record the strength of the backscatter energy reflected from the targets (intensity data. The LiDAR sensors use the near-infrared spectrum range which has high separability in the reflected energy from different targets. This characteristic is investigated to implement the LiDAR intensity data in land-cover classification. The goal of this paper is to investigate and evaluates the use of LiDAR data only (range and intensity data to extract land cover information. Different bands generated from the LiDAR data (Normal Heights, Intensity Texture, Surfaces Slopes, and PCA are combined with the original data to study the influence of including these layers on the classification accuracy. The Maximum likelihood classifier is used to conduct the classification process for the LiDAR Data as one of the best classification techniques from literature. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to test the different band combinations to extract four information classes: buildings, roads and parking areas, trees, and low vegetation (grass areas. The results show that an overall accuracy of more than 70% can be achieved using the intensity data, and other auxiliary data generated from the range and intensity data. Bands of the Principle Component Analysis (PCA are also created from the LiDAR original and auxiliary data. Similar overall accuracy of the results can be achieved using the four bands extracted from the Principal Component Analysis (PCA.

  19. Land Cover Information Extraction Using LIDAR Data

    Science.gov (United States)

    Shaker, A.; El-Ashmawy, N.

    2012-07-01

    Light Detection and Ranging (LiDAR) systems are used intensively in terrain surface modelling based on the range data determined by the LiDAR sensors. LiDAR sensors record the distance between the sensor and the targets (range data) with a capability to record the strength of the backscatter energy reflected from the targets (intensity data). The LiDAR sensors use the near-infrared spectrum range which has high separability in the reflected energy from different targets. This characteristic is investigated to implement the LiDAR intensity data in land-cover classification. The goal of this paper is to investigate and evaluates the use of LiDAR data only (range and intensity data) to extract land cover information. Different bands generated from the LiDAR data (Normal Heights, Intensity Texture, Surfaces Slopes, and PCA) are combined with the original data to study the influence of including these layers on the classification accuracy. The Maximum likelihood classifier is used to conduct the classification process for the LiDAR Data as one of the best classification techniques from literature. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to test the different band combinations to extract four information classes: buildings, roads and parking areas, trees, and low vegetation (grass) areas. The results show that an overall accuracy of more than 70% can be achieved using the intensity data, and other auxiliary data generated from the range and intensity data. Bands of the Principle Component Analysis (PCA) are also created from the LiDAR original and auxiliary data. Similar overall accuracy of the results can be achieved using the four bands extracted from the Principal Component Analysis (PCA).

  20. 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...

  1. 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.

  2. Land Use and Land Cover Change Analysis along the Coastal ...

    African Journals Online (AJOL)

    study area was done manually through on-screen digitization in ESRI ArcGIS 10.1. The major land use/cover types identified in the study sites were built up area, vegetation and farms. It was found that since the two study sites are both fast growing urban communities, most of the land was used for human habitation, hence, ...

  3. Assessment of environmental responses to land use/land cover ...

    African Journals Online (AJOL)

    This study investigates the pattern of land use/land cover change in the Lower Ogun River Basin between 1984 and 2012. Two sets of topographical maps, a Landsat-5 TM image of 1984, Landsat-7 ETM+ of 2000 and a Google Earth image of 2012 were used for the study. The topographical maps and satellite images were ...

  4. Land Use and Land Cover Change Analysis along the Coastal ...

    African Journals Online (AJOL)

    Agribotix GCS 077

    occur through several human activities such as lumbering, farming, mining, construction and other activities that disturb the ... diseases may occur more readily in areas exposed by Land Use and Land Cover Change (LULCC), especially in ... Then images were projected from the Accra Ghana Grid to the Ghana Meter Grid.

  5. BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

    Data.gov (United States)

    National Aeronautics and Space Administration — This regional land cover data set was developed as part of a multitemporal 1-km AVHRR land cover analysis approach that was used as the basis for regional land cover...

  6. The Land Use and Cover Change in Miombo Woodlands under Community Based Forest Management and Its Implication to Climate Change Mitigation: A Case of Southern Highlands of Tanzania

    Directory of Open Access Journals (Sweden)

    Z. J. Lupala

    2015-01-01

    Full Text Available In Tanzania, miombo woodland is the most significant forest vegetation with both ecological and socioeconomic importance. The vegetation has been threatened from land use and cover change due to unsustainable utilization. Over the past two decades, community based forest management (CBFM has been practiced to address the problem. Given the current need to mitigate global climate change, little is known on the influence of CBFM to the land use and cover change in miombo woodlands and therefore compromising climate change mitigation strategies. This study explored the dynamic of land use and covers change and biomass due to CBFM and established the implication to climate change mitigation. The study revealed increasing miombo woodland cover density with decreasing unsustainable utilization. The observed improvement in cover density and biomass provides potential for climate change mitigation strategies. CBFM also developed solidarity, cohesion, and social control of miombo woodlands illegal extraction. This further enhances permanence, reduces leakage, and increases accountability requirement for carbon credits. Collectively with these promising results, good land use plan at village level and introduction of alternative income generating activities can be among the best options to further reduce land use change and biomass loss in miombo woodlands.

  7. MODIS land cover uncertainty in regional climate simulations

    Science.gov (United States)

    Li, Xue; Messina, Joseph P.; Moore, Nathan J.; Fan, Peilei; Shortridge, Ashton M.

    2017-12-01

    MODIS land cover datasets are used extensively across the climate modeling community, but inherent uncertainties and associated propagating impacts are rarely discussed. This paper modeled uncertainties embedded within the annual MODIS Land Cover Type (MCD12Q1) products and propagated these uncertainties through the Regional Atmospheric Modeling System (RAMS). First, land cover uncertainties were modeled using pixel-based trajectory analyses from a time series of MCD12Q1 for Urumqi, China. Second, alternative land cover maps were produced based on these categorical uncertainties and passed into RAMS. Finally, simulations from RAMS were analyzed temporally and spatially to reveal impacts. Our study found that MCD12Q1 struggles to discriminate between grasslands and croplands or grasslands and barren in this study area. Such categorical uncertainties have significant impacts on regional climate model outputs. All climate variables examined demonstrated impact across the various regions, with latent heat flux affected most with a magnitude of 4.32 W/m2 in domain average. Impacted areas were spatially connected to locations of greater land cover uncertainty. Both biophysical characteristics and soil moisture settings in regard to land cover types contribute to the variations among simulations. These results indicate that formal land cover uncertainty analysis should be included in MCD12Q1-fed climate modeling as a routine procedure.

  8. 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.

  9. 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

  10. RS-land cover based environmental monitoring in Europe progress report on the applicability of NOAA-AVHRR 1-km data for small scale land cover mapping; final report part 1

    NARCIS (Netherlands)

    Mücher, C.A.; Veldkamp, J.G.; Katwijk, van V.F.; Nieuwenhuis, G.J.A.; Velde, van de R.J.

    1996-01-01

    The multispectral and multitemporal classification approach of AVHRR data on specific dates was studied for land cover mapping on a continental scale. Major conclusions are: decision keys must be developed that exploit both the use of multitemporal composites and multispectral data; the current

  11. Machine Learning Comparison between WorldView-2 and QuickBird-2-Simulated Imagery Regarding Object-Based Urban Land Cover Classification

    OpenAIRE

    Tessio Novack; Hermann Kux; Uwe Stilla; Thomas Esch

    2011-01-01

    The objective of this study is to compare WorldView-2 (WV-2) and QuickBird-2-simulated (QB-2) imagery regarding their potential for object-based urban land cover classification. Optimal segmentation parameters were automatically found for each data set and the obtained results were quantitatively compared and discussed. Four different feature selection algorithms were used in order to verify to which data set the most relevant object-based features belong to. Object-based classifications were...

  12. Use of UAV-Borne Spectrometer for Land Cover Classification

    Directory of Open Access Journals (Sweden)

    Sowmya Natesan

    2018-04-01

    Full Text Available Unmanned aerial vehicles (UAV are being used for low altitude remote sensing for thematic land classification using visible light and multi-spectral sensors. The objective of this work was to investigate the use of UAV equipped with a compact spectrometer for land cover classification. The UAV platform used was a DJI Flamewheel F550 hexacopter equipped with GPS and Inertial Measurement Unit (IMU navigation sensors, and a Raspberry Pi processor and camera module. The spectrometer used was the FLAME-NIR, a near-infrared spectrometer for hyperspectral measurements. RGB images and spectrometer data were captured simultaneously. As spectrometer data do not provide continuous terrain coverage, the locations of their ground elliptical footprints were determined from the bundle adjustment solution of the captured images. For each of the spectrometer ground ellipses, the land cover signature at the footprint location was determined to enable the characterization, identification, and classification of land cover elements. To attain a continuous land cover classification map, spatial interpolation was carried out from the irregularly distributed labeled spectrometer points. The accuracy of the classification was assessed using spatial intersection with the object-based image classification performed using the RGB images. Results show that in homogeneous land cover, like water, the accuracy of classification is 78% and in mixed classes, like grass, trees and manmade features, the average accuracy is 50%, thus, indicating the contribution of hyperspectral measurements of low altitude UAV-borne spectrometers to improve land cover classification.

  13. Modelling land cover change in the Ganga basin

    Science.gov (United States)

    Moulds, S.; Tsarouchi, G.; Mijic, A.; Buytaert, W.

    2013-12-01

    Over recent decades the green revolution in India has driven substantial environmental change. Modelling experiments have identified northern India as a 'hot spot' of land-atmosphere coupling strength during the boreal summer. However, there is a wide range of sensitivity of atmospheric variables to soil moisture between individual climate models. The lack of a comprehensive land cover change dataset to force climate models has been identified as a major contributor to model uncertainty. In this work a time series dataset of land cover change between 1970 and 2010 is constructed for northern India to improve the quantification of regional hydrometeorological feedbacks. The MODIS instrument on board the Aqua and Terra satellites provides near-continuous remotely sensed datasets from 2000 to the present day. However, the quality of satellite products before 2000 is poor. To complete the dataset MODIS images are extrapolated back in time using the Conversion of Land Use and its Effects at small regional extent (CLUE-s) modelling framework. Non-spatial estimates of land cover area from national agriculture and forest statistics, available on a state-wise, annual basis, are used as a direct model input. Land cover change is allocated spatially as a function of biophysical and socioeconomic drivers identified using logistic regression. This dataset will provide an essential input to a high resolution, physically based land surface model to generate the lower boundary condition to assess the impact of land cover change on regional climate.

  14. Land cover and water yield: inference problems when comparing catchments with mixed land cover

    Directory of Open Access Journals (Sweden)

    A. I. J. M. van Dijk

    2012-09-01

    Full Text Available Controlled experiments provide strong evidence that changing land cover (e.g. deforestation or afforestation can affect mean catchment streamflow (Q. By contrast, a similarly strong influence has not been found in studies that interpret Q from multiple catchments with mixed land cover. One possible reason is that there are methodological issues with the way in which the Budyko framework was used in the latter type studies. We examined this using Q data observed in 278 Australian catchments and by making inferences from synthetic Q data simulated by a hydrological process model (the Australian Water Resources Assessment system Landscape model. The previous contrasting findings could be reproduced. In the synthetic experiment, the land cover influence was still present but not accurately detected with the Budyko- framework. Likely sources of interpretation bias demonstrated include: (i noise in land cover, precipitation and Q data; (ii additional catchment climate characteristics more important than land cover; and (iii covariance between Q and catchment attributes. These methodological issues caution against the use of a Budyko framework to quantify a land cover influence in Q data from mixed land-cover catchments. Importantly, however, our findings do not rule out that there may also be physical processes that modify the influence of land cover in mixed land-cover catchments. Process model simulations suggested that lateral water redistribution between vegetation types and recirculation of intercepted rainfall may be important.

  15. Land cover change and soil fertility decline in tropical regions

    NARCIS (Netherlands)

    Hartemink, A.E.; Veldkamp, A.; Bai, Zhanguo

    2008-01-01

    Land cover changes influence the biogeochemistry, hydrology, and climate of the earth. Studies that assessed land cover changes at the global scale mostly focused on: deforestation, cropland expansion, dry land degradation, urbanisation, pasture expansion, and agricultural intensification. For the

  16. 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.

  17. Mekong Regional Land Cover Monitoring System Reference Methods

    Science.gov (United States)

    Saah, D.; Aekakkararungroj, A.; Phongsapan, K.; Towashiraporn, P.; Triepke, J.; Maus, P.; Tenneson, K.; Anderson, E.; Cutter, P. G.; Ganz, D.; Ate, P.; Markert, K. N.

    2016-12-01

    In 2015, SERVIR-Mekong conducted a geospatial needs assessment for the Lower Mekong countries which included individual country consultations. The assessment revealed that many countries were dependent on land cover and land use maps for land resource planning, quantifying ecosystem services including resilience to climate change, biodiversity conservation, and other critical social issues. Many of the Lower Mekong countries have developed national scale land cover maps derived in part from remote sensing products and geospatial technologies. However, updates are infrequent and classification systems and accuracy assessment do not always meet the needs of key user groups. In addition, data products stop at political boundaries and are often not accessible. Many of the Lower Mekong countries rely on global land cover products to fill the gaps of their national efforts, compromising consistency between data and policies. These gaps in national efforts can be filled by a flexible regional land cover monitoring system that is co-developed by regional partners with the specific intention of meeting national transboundary needs, for example including consistent forest definitions in transboundary watersheds. During this assessment, regional stakeholders identified a need for a land cover monitoring system that will produce frequent, high quality land cover maps using a consistent regional classification scheme that is compatible with national country needs. This system is dependent on a sustainable source of field data that insures data quality and improves potential impact. Based on this need a collaborative workshop was held to create a robust regional reference data system that integrates results from field data, national inventories and high resolution imagery. The results presented here highlights the value of collaboratively developed systems that use data convergence to improve land cover mapping results for multiple end users.

  18. Validation of Land Cover Products Using Reliability Evaluation Methods

    OpenAIRE

    Shi, Wenzhong; Zhang, Xiaokang; Hao, Ming; Shao, Pan; Cai, Liping; Lyu, Xuzhe

    2015-01-01

    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. ...

  19. Monitoring and Analysing Land Use/Cover Changes in an Arid Region Based on Multi-Satellite Data: The Kashgar Region, Northwest China

    Directory of Open Access Journals (Sweden)

    Ayisulitan Maimaitiaili

    2018-01-01

    Full Text Available In arid regions, oases ecosystems are fragile and sensitive to climate change, and water is the major limiting factor for environmental and socio-economic developments. Understanding the drivers of land use/cover change (LUCC in arid regions is important for the development of management strategies to improve or prevent environmental deterioration and loss of natural resources. The Kashgar Region is the key research area in this study; it is a typical mountain-alluvial plain-oasis-desert ecosystem in an arid region, and is one of the largest oases in Xinjiang Uyghur Autonomous Region, China. In addition, the Kashgar Region is an important cotton and grain production area. This study’s main objectives are to quantify predominant LUCCs and identify their driving forces, based on the integration of multiple remote sensors and applications of environmental and socio-economic data. Results showed that LUCCs have been significant in the Kashgar Region during the last 42 years. Cultivated land and urban/built-up lands were the most changed land cover (LC, by 3.6% and 0.4% from 1972 to 10.2% and 3% in 2014, respectively. By contrast, water and forest areas declined. Grassland and snow-covered areas have fluctuated along with climate and human activities. Bare land was changed slightly from 1972 to 2014. According to the land use transfer matrix, cultivated land replaced grass- and forestland. Urban/built-up land mainly expanded over cultivated and bare land. LUCCs were triggered by the interplay of natural and social drivers. Increasing runoff, caused by regional climate changes in seasonal variation, and snow melt water, have provided water resources for LC changes. In the same way, population growth, changes in land tenure, and socio-economic development also induced LUCCs. However, expansion of cultivated land and urban/built-up land led to increased water consumption and stressed fragile water systems during on-going climate changes. Therefore

  20. 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,...

  1. 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

  2. Change of Land Use/Cover in Tianjin City Based on the Markov and Cellular Automata Models

    Directory of Open Access Journals (Sweden)

    Ruci Wang

    2017-05-01

    Full Text Available In recent years, urban areas have been expanding rapidly in the world, especially in developing countries. With this rapid urban growth, several environmental and social problems have appeared. Better understanding of land use and land cover (LULC change will facilitate urban planning and constrain these potential problems. As one of the four municipalities in China, Tianjin has experienced rapid urbanization and such trend is expected to continue. Relying on remote sensing (RS and geographical information system (GIS tools, this study investigates LULC change in Tianjin city. First, we used RS to generate classification maps for 1995, 2005, and 2015. Then, simulation models were applied to evaluate the LULC changes. Analysis of the 1995, 2005, and 2015 LULC maps shows that more than 10% of the cropland areas were transformed into built-up areas. Finally, by employing the Markov model and cellular automata (CA model, the LULC in 2025 and 2035 were simulated and forecasted. Our analysis contributes to the understanding of the development process in the Tianjin area, which will facilitate future planning, as well as constraining the potential negative consequences brought by future LULC changes.

  3. Global land cover products tailored to the needs of the climate modeling community - Land Cover project of the ESA Climate Change Initiative

    Science.gov (United States)

    Bontemps, S.; Defourny, P.; Radoux, J.; Kalogirou, V.; Arino, O.

    2012-04-01

    Improving the systematic observation of land cover, as an Essential Climate Variable, will support the United Framework Convention on Climate Change effort to reduce the uncertainties in our understanding of the climate system and to better cope with climate change. The Land Cover project of the ESA Climate Change Initiative aims at contributing to this effort by providing new global land cover products tailored to the expectations of the climate modeling community. During the first three months of the project, consultation mechanisms were established with this community to identify its specific requirements in terms of satellite-based global land cover products. This assessment highlighted specific needs in terms of land cover characterization, accuracy of products, as well as stability and consistency, needs that are currently not met or even addressed. Based on this outcome, the project revisits the current land cover representation and mapping approaches. First, the stable and dynamic components of land cover are distinguished. The stable component refers to the set of land surface features that remains stable over time and thus defines the land cover independently of any sources of temporary or natural variability. Conversely, the dynamic component is directly related to this temporary or natural variability that can induce some variation in land observation over time but without changing the land cover state in its essence (e.g. flood, snow on forest, etc.). Second, the project focuses on the possibility to generate such stable global land cover maps. Previous projects, like GlobCover and MODIS Land Cover, have indeed shown that products' stability is a key issue. In delivering successive global products derived from the same sensor, they highlighted the existence of spurious year-to-year variability in land cover labels, which were not associated with land cover change but with phenology, disturbances or landscape heterogeneity. An innovative land cover

  4. 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...

  5. Carbon emissions from land use and land-cover change

    Directory of Open Access Journals (Sweden)

    R. A. Houghton

    2012-12-01

    Full Text Available The net flux of carbon from land use and land-cover change (LULCC accounted for 12.5% of anthropogenic carbon emissions from 1990 to 2010. This net flux is the most uncertain term in the global carbon budget, not only because of uncertainties in rates of deforestation and forestation, but also because of uncertainties in the carbon density of the lands actually undergoing change. Furthermore, there are differences in approaches used to determine the flux that introduce variability into estimates in ways that are difficult to evaluate, and not all analyses consider the same types of management activities. Thirteen recent estimates of net carbon emissions from LULCC are summarized here. In addition to deforestation, all analyses considered changes in the area of agricultural lands (croplands and pastures. Some considered, also, forest management (wood harvest, shifting cultivation. None included emissions from the degradation of tropical peatlands. Means and standard deviations across the thirteen model estimates of annual emissions for the 1980s and 1990s, respectively, are 1.14 ± 0.23 and 1.12 ± 0.25 Pg C yr−1 (1 Pg = 1015 g carbon. Four studies also considered the period 2000–2009, and the mean and standard deviations across these four for the three decades are 1.14 ± 0.39, 1.17 ± 0.32, and 1.10 ± 0.11 Pg C yr−1. For the period 1990–2009 the mean global emissions from LULCC are 1.14 ± 0.18 Pg C yr−1. The standard deviations across model means shown here are smaller than previous estimates of uncertainty as they do not account for the errors that result from data uncertainty and from an incomplete understanding of all the processes affecting the net flux of carbon from LULCC. Although these errors have not been systematically evaluated, based on partial analyses available in the literature and expert opinion, they are estimated to be on the order of ± 0.5 Pg C yr−1.

  6. Drought vulnerability drives land-use and land cover changes in the Rift Valley dry lands of Ethiopia

    NARCIS (Netherlands)

    Biazin, B.; Sterk, G.|info:eu-repo/dai/nl/157276465

    2013-01-01

    The Ethiopian Rift Valley is a dry land zone where for a long time pastoral communities have made their living from acacia-based woodlands. But many pastoralists have changed from a pastoral way of life to mixed farming over time. The aim of this study was to evaluate land-use and land cover (LULC)

  7. 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...

  8. Land Cover Analysis by Using Pixel-Based and Object-Based Image Classification Method in Bogor

    Science.gov (United States)

    Amalisana, Birohmatin; Rokhmatullah; Hernina, Revi

    2017-12-01

    The advantage of image classification is to provide earth’s surface information like landcover and time-series changes. Nowadays, pixel-based image classification technique is commonly performed with variety of algorithm such as minimum distance, parallelepiped, maximum likelihood, mahalanobis distance. On the other hand, landcover classification can also be acquired by using object-based image classification technique. In addition, object-based classification uses image segmentation from parameter such as scale, form, colour, smoothness and compactness. This research is aimed to compare the result of landcover classification and its change detection between parallelepiped pixel-based and object-based classification method. Location of this research is Bogor with 20 years range of observation from 1996 until 2016. This region is famous as urban areas which continuously change due to its rapid development, so that time-series landcover information of this region will be interesting.

  9. Applying object-based image analysis and knowledge-based classification to ADS-40 digital aerial photographs to facilitate complex forest land cover classification

    Science.gov (United States)

    Hsieh, Yi-Ta; Chen, Chaur-Tzuhn; Chen, Jan-Chang

    2017-01-01

    In general, considerable human and material resources are required for performing a forest inventory survey. Using remote sensing technologies to save forest inventory costs has thus become an important topic in forest inventory-related studies. Leica ADS-40 digital aerial photographs feature advantages such as high spatial resolution, high radiometric resolution, and a wealth of spectral information. As a result, they have been widely used to perform forest inventories. We classified ADS-40 digital aerial photographs according to the complex forest land cover types listed in the Fourth Forest Resource Survey in an effort to establish a classification method for categorizing ADS-40 digital aerial photographs. Subsequently, we classified the images using the knowledge-based classification method in combination with object-based analysis techniques, decision tree classification techniques, classification parameters such as object texture, shape, and spectral characteristics, a class-based classification method, and geographic information system mapping information. Finally, the results were compared with manually interpreted aerial photographs. Images were classified using a hierarchical classification method comprised of four classification levels (levels 1 to 4). The classification overall accuracy (OA) of levels 1 to 4 is within a range of 64.29% to 98.50%. The final result comparisons showed that the proposed classification method achieved an OA of 78.20% and a kappa coefficient of 0.7597. On the basis of the image classification results, classification errors occurred mostly in images of sunlit crowns because the image values for individual trees varied. Such a variance was caused by the crown structure and the incident angle of the sun. These errors lowered image classification accuracy and warrant further studies. This study corroborates the high feasibility for mapping complex forest land cover types using ADS-40 digital aerial photographs.

  10. Predicting land cover using GIS, Bayesian and evolutionary algorithm methods.

    Science.gov (United States)

    Aitkenhead, M J; Aalders, I H

    2009-01-01

    Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.

  11. Support Vector Data Description Model to Map Specific Land Cover with Optimal Parameters Determined from a Window-Based Validation Set.

    Science.gov (United States)

    Zhang, Jinshui; Yuan, Zhoumiqi; Shuai, Guanyuan; Pan, Yaozhong; Zhu, Xiufang

    2017-04-26

    This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD), to determine optimal parameters for support vector data description (SVDD) model to map specific land cover by integrating training and window-based validation sets. Compared to the conventional approach where the validation set included target and outlier pixels selected visually and randomly, the validation set derived from WVS-SVDD constructed a tightened hypersphere because of the compact constraint by the outlier pixels which were located neighboring to the target class in the spectral feature space. The overall accuracies for wheat and bare land achieved were as high as 89.25% and 83.65%, respectively. However, target class was underestimated because the validation set covers only a small fraction of the heterogeneous spectra of the target class. The different window sizes were then tested to acquire more wheat pixels for validation set. The results showed that classification accuracy increased with the increasing window size and the overall accuracies were higher than 88% at all window size scales. Moreover, WVS-SVDD showed much less sensitivity to the untrained classes than the multi-class support vector machine (SVM) method. Therefore, the developed method showed its merits using the optimal parameters, tradeoff coefficient ( C ) and kernel width ( s ), in mapping homogeneous specific land cover.

  12. A Texture-Based Land Cover Classification for the Delineation of a Shifting Cultivation Landscape in the Lao PDR Using Landscape Metrics

    Directory of Open Access Journals (Sweden)

    Andreas Heinimann

    2013-07-01

    Full Text Available The delineation of shifting cultivation landscapes using remote sensing in mountainous regions is challenging. On the one hand, there are difficulties related to the distinction of forest and fallow forest classes as occurring in a shifting cultivation landscape in mountainous regions. On the other hand, the dynamic nature of the shifting cultivation system poses problems to the delineation of landscapes where shifting cultivation occurs. We present a two-step approach based on an object-oriented classification of Advanced Land Observing Satellite, Advanced Visible and Near-Infrared Spectrometer (ALOS AVNIR and Panchromatic Remote-sensing Instrument for Stereo Mapping (ALOS PRISM data and landscape metrics. When including texture measures in the object-oriented classification, the accuracy of forest and fallow forest classes could be increased substantially. Based on such a classification, landscape metrics in the form of land cover class ratios enabled the identification of crop-fallow rotation characteristics of the shifting cultivation land use practice. By classifying and combining these landscape metrics, shifting cultivation landscapes could be delineated using a single land cover dataset.

  13. Land cover's refined classification based on multi source of remote sensing information fusion: a case study of national geographic conditions census in China

    Science.gov (United States)

    Cheng, Tao; Zhang, Jialong; Zheng, Xinyan; Yuan, Rujin

    2018-03-01

    The project of The First National Geographic Conditions Census developed by Chinese government has designed the data acquisition content and indexes, and has built corresponding classification system mainly based on the natural property of material. However, the unified standard for land cover classification system has not been formed; the production always needs converting to meet the actual needs. Therefore, it proposed a refined classification method based on multi source of remote sensing information fusion. It takes the third-level classes of forest land and grassland for example, and has collected the thematic data of Vegetation Map of China (1:1,000,000), attempts to develop refined classification utilizing raster spatial analysis model. Study area is selected, and refined classification is achieved by using the proposed method. The results show that land cover within study area is divided principally among 20 classes, from subtropical broad-leaved forest (31131) to grass-forb community type of low coverage grassland (41192); what's more, after 30 years in the study area, climatic factors, developmental rhythm characteristics and vegetation ecological geographical characteristics have not changed fundamentally, only part of the original vegetation types have changed in spatial distribution range or land cover types. Research shows that refined classification for the third-level classes of forest land and grassland could make the results take on both the natural attributes of the original and plant community ecology characteristics, which could meet the needs of some industry application, and has certain practical significance for promoting the product of The First National Geographic Conditions Census.

  14. 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...

  15. 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...

  16. 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...

  17. Millennium Ecosystem Assessment: MA Climate and Land Cover

    Data.gov (United States)

    National Aeronautics and Space Administration — The Millennium Ecosystem Assessment: MA Climate and Land Cover provides data and information on global gridded climatological variables, global land cover maps, and...

  18. BOREAS AFM-12 1-km AVHRR Seasonal Land Cover Classification

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This regional land cover data set was developed as part of a multitemporal 1-km AVHRR land cover analysis approach that was used as the basis for regional...

  19. 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

  20. 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 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.

  1. National Land Cover and Resource Statistics

    Science.gov (United States)

    Nilsen, A. B.; Bjørkelo, K.

    2012-08-01

    An overall societal aim is to ensure a sustainable use and management of a country's land resources. This requires continuous deliv-ery of reliable and up-to-date information to decision-makers. To be able to deliver this information the Norwegian Forest and Land-scape Institute (Skog og landskap) produces, among others, land resource statistics for all municipalities in Norway. The statistics are also produced on a county level and for the whole country. The acreage numbers are retrieved from a combination of different na-tional datasets in various scales together with interpretation of satellite images. Through a reclassification, statistics are calculated for certain land resource classes like arable land, pasture, forest based on productivity class, fresh water, snow and glacier, mountain-ous/scarcely vegetated area and built up area. Skog og landskap has for the last couple of years been using open source software. The whole statistics production line is carried out by the means of such software. The results are stored in XML-files that are published on the internet. The production requires processing of several databases with national coverage, and needs to handle geometric opera-tions efficiently and without error. The open software solution is reliable, stable and fast.

  2. land use and cover change in pastoral systems of uganda

    African Journals Online (AJOL)

    ACSS

    The current land use and cover changes have delineated mobility as a coping strategy to drought, contributed to degradation of rangelands, reduced the resilience of pastoral systems to drought and increased their vulnerability to climate change. Farm based water and forage conservation should be enhanced to sustain ...

  3. EASE-Grid Land Cover Classifications Derived from Boston University MODIS/Terra Land Cover Data, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — These data provide land cover classifications derived from the Boston University MOD12Q1 V004 MODIS/Terra 1 km Land Cover Product (Friedl et al. 2002). The data are...

  4. Land Cover Indicators for U.S. National Climate Assessments

    Science.gov (United States)

    Channan, S.; Thomson, A. M.; Collins, K. M.; Sexton, J. O.; Torrens, P.; Emanuel, W. R.

    2014-12-01

    Land is a critical resource for human habitat and for the vast majority of human activities. Many natural resources are derived from terrestrial ecosystems or otherwise extracted from the landscape. Terrestrial biodiversity depends on land attributes as do people's perceptions of the value of land, including its value for recreation or tourism. Furthermore, land surface properties and processes affect weather and climate, and land cover change and land management affect emissions of greenhouse gases. Thus, land cover with its close association with climate is so pervasive that a land cover indicator is of fundamental importance to U.S. national climate assessments and related research. Moderate resolution remote sensing products (MODIS) were used to provide systematic data on annual distributions of land cover over the period 2001-2012. Selected Landsat observations and data products further characterize land cover at higher resolution. Here we will present the prototype for a suite of land cover indicators including land cover maps as well as charts depicting attributes such as composition by land cover class, statistical indicators of landscape characteristics, and tabular data summaries indispensable for communicating the status and trends of U.S. land cover at national, regional and state levels.

  5. Evaluation of the Consistency of MODIS Land Cover Product (MCD12Q1 Based on Chinese 30 m GlobeLand30 Datasets: A Case Study in Anhui Province, China

    Directory of Open Access Journals (Sweden)

    Dong Liang

    2015-11-01

    Full Text Available Land cover plays an important role in the climate and biogeochemistry of the Earth system. It is of great significance to produce and evaluate the global land cover (GLC data when applying the data to the practice at a specific spatial scale. The objective of this study is to evaluate and validate the consistency of the Moderate Resolution Imaging Spectroradiometer (MODIS land cover product (MCD12Q1 at a provincial scale (Anhui Province, China based on the Chinese 30 m GLC product (GlobeLand30. A harmonization method is firstly used to reclassify the land cover types between five classification schemes (International Geosphere Biosphere Programme (IGBP global vegetation classification, University of Maryland (UMD, MODIS-derived Leaf Area Index and Fractional Photosynthetically Active Radiation (LAI/FPAR, MODIS-derived Net Primary Production (NPP, and Plant Functional Type (PFT of MCD12Q1 and ten classes of GlobeLand30, based on the knowledge rule (KR and C4.5 decision tree (DT classification algorithm. A total of five harmonized land cover types are derived including woodland, grassland, cropland, wetland and artificial surfaces, and four evaluation indicators are selected including the area consistency, spatial consistency, classification accuracy and landscape diversity in the three sub-regions of Wanbei, Wanzhong and Wannan. The results indicate that the consistency of IGBP is the best among the five schemes of MCD12Q1 according to the correlation coefficient (R. The “woodland” LAI/FPAR is the worst, with a spatial similarity (O of 58.17% due to the misclassification between “woodland” and “others”. The consistency of NPP is the worst among the five schemes as the agreement varied from 1.61% to 56.23% in the three sub-regions. Furthermore, with the biggest difference of diversity indices between LAI/FPAR and GlobeLand30, the consistency of LAI/FPAR is the weakest. This study provides a methodological reference for evaluating the

  6. PolSAR Land Cover Classification Based on Roll-Invariant and Selected Hidden Polarimetric Features in the Rotation Domain

    Directory of Open Access Journals (Sweden)

    Chensong Tao

    2017-07-01

    Full Text Available Land cover classification is an important application for polarimetric synthetic aperture radar (PolSAR. Target polarimetric response is strongly dependent on its orientation. Backscattering responses of the same target with different orientations to the SAR flight path may be quite different. This target orientation diversity effect hinders PolSAR image understanding and interpretation. Roll-invariant polarimetric features such as entropy, anisotropy, mean alpha angle, and total scattering power are independent of the target orientation and are commonly adopted for PolSAR image classification. On the other aspect, target orientation diversity also contains rich information which may not be sensed by roll-invariant polarimetric features. In this vein, only using the roll-invariant polarimetric features may limit the final classification accuracy. To address this problem, this work uses the recently reported uniform polarimetric matrix rotation theory and a visualization and characterization tool of polarimetric coherence pattern to investigate hidden polarimetric features in the rotation domain along the radar line of sight. Then, a feature selection scheme is established and a set of hidden polarimetric features are selected in the rotation domain. Finally, a classification method is developed using the complementary information between roll-invariant and selected hidden polarimetric features with a support vector machine (SVM/decision tree (DT classifier. Comparison experiments are carried out with NASA/JPL AIRSAR and multi-temporal UAVSAR data. For AIRSAR data, the overall classification accuracy of the proposed classification method is 95.37% (with SVM/96.38% (with DT, while that of the conventional classification method is 93.87% (with SVM/94.12% (with DT, respectively. Meanwhile, for multi-temporal UAVSAR data, the mean overall classification accuracy of the proposed method is up to 97.47% (with SVM/99.39% (with DT, which is also higher

  7. Ultra-wideband tomography of land cover

    Science.gov (United States)

    Kochetkova, Tatiana D.; Zapasnoy, Andrey S.; Klokov, Andrey V.; Shipilov, Sergey E.; Yakubov, Vladimir P.; Yurchenko, Alexey V.

    2014-11-01

    This paper describes a comprehensive approach which combines the application of OKO-2 ground penetrating radar, conventional method of cross sectioning accepted in edaphology, soil-testing parameters, mobile and laboratory research of dielectric permittivity for stratified soil cover research. Dielectric characteristics measurements of selected contact samples by the waveguide-coaxial technique showed a correlation between electrophysic characteristics of soil with soil moisture and density. Location of deep aquifers was detected and the real local topography was restored. Research was performed within the Timiryazevskoye forest district near Tomsk. Comparing the results of radar non-destructive sounding and contact measurements demonstrated high correlation of detected structural soil features. The suggested approach provides a solid basis for verifying the non-contact radiophysical methods of research in the interests of rational nature management and land utilization.

  8. Land Cover and Land Use Classification for the State of New Hampshire, 1996-2001

    Data.gov (United States)

    National Aeronautics and Space Administration — The New Hampshire Geographically Referenced Analysis and Information Transfer System (GRANIT) land cover data set provides a land cover and land use product at 30-m...

  9. Vegetated land cover near residence is associated with ...

    Science.gov (United States)

    Abstract Background: Greater exposure to urban green spaces has been linked to reduced risks of depression, cardiovascular disease, diabetes and premature death. Alleviation of chronic stress is a hypothesized pathway to improved health. Previous studies linked chronic stress with biomarker-based measures of physiological dysregulation known as allostatic load. This study aimed to assess the relationship between vegetated land cover near residences and allostatic load. Methods: This cross-sectional population-based study involved 204 adult residents of the Durham-Chapel Hill, North Carolina metropolitan area. Exposure was quantified using high-resolution metrics of trees and herbaceous vegetation within 500 m of each residence derived from the U.S. Environmental Protection Agency’s EnviroAtlas land cover dataset. Eighteen biomarkers of immune, neuroendocrine, and metabolic functions were measured in serum or saliva samples. Allostatic load was defined as a sum of biomarker values dichotomized at specific percentiles of sample distribution. Regression analysis was conducted using generalized additive models with two-dimensional spline smoothing function of geographic coordinates, weighted measures of vegetated land cover allowing decay of effects with distance, and geographic and demographic covariates. Results: An inter-quartile range increase in distance-weighted vegetated land cover was associated with 37% (46%; 27%) reduced allostatic load; significantly

  10. NASA Web-Enabled Landsat Data 5 year Land Cover Land Use Change Product V001

    Data.gov (United States)

    National Aeronautics and Space Administration — The Web-Enabled Landsat Data (WELD) 5-year Land Cover Land Use Change (LCLUC) is a composite of 30 m land use land change product for the contiguous United States...

  11. 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.

  12. 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 ...

  13. Land Cover Changes between 1974 and 2008 in Ulaanbaatar, Mongolia

    Science.gov (United States)

    Bagan, H.; Kinoshita, T.; Yamagata, Y.

    2009-12-01

    Commission VII Mid-term Symposium “Remote Sensing: From Pixels to Processes”, Enschede, the Netherlands, 8-11 May 2006. 511-516. Bagan, H., Wang, Q., Watanabe, M., Karneyarna, S., & Bao, Y. (2008). Land-cover classification using ASTER multi-band combinations based on wavelet fusion and SOM neural network. Photogrammetric Engineering and Remote Sensing, 74, 333-342. Bagan, H., Yasuoka, Y., Endo, T., Wang, X., & Feng, Z. (2008). Classification of airborne hyperspectral data based on the average learning subspace method. IEEE Geoscience and Remote Sensing Letters, 5, 368-372. Figure 1. The self-organizing map (SOM) neural network classifier (a) and the subspace classification method (b).

  14. 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

  15. 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...

  16. VT National Land Cover Dataset by Subbasin - 2011

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC)...

  17. VT National Land Cover Dataset - Impervious Only - 2001

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) The LandLandcov_IMPERV2001 layer available from VCGI is a subset of the the National Land Cover Database 2001 for mapping zone 65 was produced...

  18. RLC AVHRR-Derived Land Cover, Former Soviet Union, Far East, 1-km, 1990

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set is a 1-kilometer resolution land cover map for the land area of the Primor'ye and Southern Khabarovsk Regions, in the Russian Far East, based...

  19. RLC AVHRR-Derived Land Cover, Former Soviet Union, Far East, 1-km, 1990

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set is a 1-kilometer resolution land cover map for the land area of the Primor'ye and Southern Khabarovsk Regions, in the Russian Far East, based on 1990...

  20. 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.

  1. 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,...

  2. Remote sensing and GIS-based integrated analysis of land cover change in Duzce plain and its surroundings (north western Turkey).

    Science.gov (United States)

    Ikiel, Cercis; Ustaoglu, Beyza; Dutucu, Ayse Atalay; Kilic, Derya Evrim

    2013-02-01

    The aim of this study is to research natural land cover change caused by the permanent effects of human activities in Duzce plain and its surroundings, and to determine the current status of the land cover. For this purpose, two Landsat TM images were used in the study for the years 1987 and 2010. These images are analysed by using data image processing techniques in ERDAS Imagine©10.0 and ArcGIS©10.0 software. Land cover change nomenclature is classified according to the Coordination of Information on the Environment Level 2 Classification (1--urban fabric, 2--industrial, commercial and transport units, 3--heterogeneous agricultural areas, 4--forests, and 5--inland wetlands). Furthermore, the image analysis results are confirmed by the field research. According to the results, a decrease of 33.5 % was recorded in forest areas from 24,840.7 to 16,529.0 ha; an increase of 11.2 % was recorded in heterogeneous agricultural areas from 47,702.7 to 53,051.7 ha. Natural vegetation, which is the large part of land cover in the research area, has been changing rapidly because of rapid urbanisation and agricultural activities. As a result, it is concluded that significant changes have occurred on the natural land cover between the years 1987 and 2010 in the Duzce plain and its surroundings.

  3. Regional characterization of land cover using multiple sources of data

    Science.gov (United States)

    Vogelmann, James E.; Sohl, Terry L.; Howard, Stephen M.

    1998-01-01

    Many organizations require accurate intermediate-scale land-cover information for many applications, including modeling nutrient and pesticide runoff, understanding spatial patterns of biodiversity, land-use planning, and policy development. While many techniques have been successfully used to classify land cover in relatively small regions, there are substantial obstacles in applying these methods to large, multiscene regions. The purpose of this study was to generate and evaluate a large region land-cover classification product using a multiple-layer land-characteristics database approach. To derive land-cover information, mosaicked Landsat thematic mapper (TM) scenes were analyzed in conjunction with digital elevation data (and derived slope, aspect, and shaded relief), population census information, Defense Meteorological Satellite Program city lights data, prior land-use and land-cover data, digital line graph data, and National Wetlands Inventory data. Both leaf-on and leaf-off TM data sets were analyzed. The study area was U.S. Federal Region III, which includes the states of Pennsylvania, Virginia, Maryland, Delaware, and West Virginia. The general procedure involved (1) generating mosaics of multiple scenes of leaves-on TM data using histogram equalization methods; (2) clustering mosaics into 100 spectral classes using unsupervised classification; (3) interpreting and labeling spectral classes into approximately 15 land-cover categories (analogous to Anderson Level 1 and 2 classes) using aerial photographs; (4) developing decision-making rules and models using from one to several ancillary data layers to resolve confusion in spectral classes that represented two or more targeted land-cover categories; and (5) incorporating data from other sources (for example, leaf-off TM data and National Wetlands Inventory data) to yield a final land-cover product. Although standard accuracy assessments were not done, a series of consistency checks using available

  4. Land Cover Differences in Soil Carbon and Nitrogen at Fort Benning, Georgia

    Energy Technology Data Exchange (ETDEWEB)

    Garten Jr., C.T.

    2004-02-09

    Land cover characterization might help land managers assess the impacts of management practices and land cover change on attributes linked to the maintenance and/or recovery of soil quality. However, connections between land cover and measures of soil quality are not well established. The objective of this limited investigation was to examine differences in soil carbon and nitrogen among various land cover types at Fort Benning, Georgia. Forty-one sampling sites were classified into five major land cover types: deciduous forest, mixed forest, evergreen forest or plantation, transitional herbaceous vegetation, and barren land. Key measures of soil quality (including mineral soil density, nitrogen availability, soil carbon and nitrogen stocks, as well as properties and chemistry of the O-horizon) were significantly different among the five land covers. In general, barren land had the poorest soil quality. Barren land, created through disturbance by tracked vehicles and/or erosion, had significantly greater soil density and a substantial loss of carbon and nitrogen relative to soils at less disturbed sites. We estimate that recovery of soil carbon under barren land at Fort Benning to current day levels under transitional vegetation or forests would require about 60 years following reestablishment of vegetation. Maps of soil carbon and nitrogen were produced for Fort Benning based on a 1999 land cover map and field measurements of soil carbon and nitrogen stocks under different land cover categories.

  5. Land Cover Monitoring for Water Resources Management in Angola

    Science.gov (United States)

    Miguel, Irina; Navarro, Ana; Rolim, Joao; Catalao, Joao; Silva, Joel; Painho, Marco; Vekerdy, Zoltan

    2016-08-01

    The aim of this paper is to assess the impact of improved temporal resolution and multi-source satellite data (SAR and optical) on land cover mapping and monitoring for efficient water resources management. For that purpose, we developed an integrated approach based on image classification and on NDVI and SAR backscattering (VV and VH) time series for land cover mapping and crop's irrigation requirements computation. We analysed 28 SPOT-5 Take-5 images with high temporal revisiting time (5 days), 9 Sentinel-1 dual polarization GRD images and in-situ data acquired during the crop growing season. Results show that the combination of images from different sources provides the best information to map agricultural areas. The increase of the images temporal resolution allows the improvement of the estimation of the crop parameters, and then, to calculate of the crop's irrigation requirements. However, this aspect was not fully exploited due to the lack of EO data for the complete growing season.

  6. 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.

  7. 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.

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

    Science.gov (United States)

    Giri, C.; Pengra, B.; Long, J.; Loveland, T. R.

    2013-12-01

    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).

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

    Directory of Open Access Journals (Sweden)

    Dong Jiang

    Full Text Available Land cover data represent a fundamental data source for various types of scientific research. The classification of land cover based on satellite data is a challenging task, and an efficient classification method is needed. In this study, an automatic scheme is proposed for the classification of land use using multispectral remote sensing images based on change detection and a semi-supervised classifier. The satellite image can be automatically classified using only the prior land cover map and existing images; therefore human involvement is reduced to a minimum, ensuring the operability of the method. The method was tested in the Qingpu District of Shanghai, China. Using Environment Satellite 1(HJ-1 images of 2009 with 30 m spatial resolution, the areas were classified into five main types of land cover based on previous land cover data and spectral features. The results agreed on validation of land cover maps well with a Kappa value of 0.79 and statistical area biases in proportion less than 6%. This study proposed a simple semi-automatic approach for land cover classification by using prior maps with satisfied accuracy, which integrated the accuracy of visual interpretation and performance of automatic classification methods. The method can be used for land cover mapping in areas lacking ground reference information or identifying rapid variation of land cover regions (such as rapid urbanization with convenience.

  10. 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.

  11. Using LIDAR data and airborne spectral images for urban land cover classification based on fuzzy set method

    Science.gov (United States)

    Lai, Zulong; Shen, Shaohong; Chen, Xingyi; Liang, Xinmei; Zhang, Jie

    2009-10-01

    In this paper, we propose an analysis on the combinative effect of high-resolution airborne image and light detection and ranging (LIDAR) data for the classification of complex urban areas. In greater detail, the proposed system is composed of three models briefly. Model one includes an advanced kernelized fuzzy c-means classification method for high-resolution airborne image. The characteristics of LIDAR point cloud are introduced in model two, membership degree function of buildings, vegetations and naked land have been built. In model three, high-resolution image and elevation data form LIDAR point cloud are jointed. Experiment carried out on a complex urban area provide interesting conclusions on the effectiveness and protentialities of the joint use of high-resolution image and LIDAR data. In particular, the elevation data was very effective for the separation of species with similar spectral signatures but different elevation information. Experimental results approve that elevation data can improve classification accuracy in building occupied area obviously.

  12. 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.

  13. 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...

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

    Data.gov (United States)

    National Aeronautics and Space Administration — 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 describes...

  15. 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

  16. Land use and land cover dynamics in the Brazilian Amazon: understanding human-environmental interactions

    NARCIS (Netherlands)

    Souza Soler, de L.

    2014-01-01

    Land use and land cover dynamics are a result of the interactions between human activities and the environment. The objective of this thesis is to analyze Amazonian land use and land cover pattern dynamics in order to identify the underlying system dynamics. By combining empirical statistical

  17. 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,...

  18. an assessment of the land use and land cover changes in shurugwi

    African Journals Online (AJOL)

    Dr Osondu

    with Google Earth screen to screen images to come up with the extent of the changes that have occurred. Results show that cultivation and bare land dominate land use/land cover for the district at 53.4% while degraded land covers 26.6% with the rest shared between vegetation (18.1%) and water (2%). There has.

  19. 'Cover story': a study in land management | Quadling | Southern ...

    African Journals Online (AJOL)

    'Cover story': a study in land management. ... 'Cover story': a study in land management. H Quadling, M Quadling, D Bush, C Cesario, K Spencer, Y van Grevenbroek, C Wait. Abstract. This article summarises an environmental research project undertaken by pupils of Mondeor High School, Johannesburg. The project was ...

  20. A global land cover validation dataset, I: Fundamental design principles

    NARCIS (Netherlands)

    Olofsson, P.; Stehman, S.; Woodcock, C.; Sulla-Menashe, D.; Sibley, A.; Newell, J.; Friedl, M.A.; Herold, M.

    2012-01-01

    A number of land-cover products, both global and regional, have been produced and more are forthcoming. Assessing their accuracy would be greatly facilitated by a global validation database of reference sites that allows for comparative assessments of uncertainty for multiple land-cover data sets.

  1. 1 Integrating land cover and terrain characteristics to explain plague ...

    African Journals Online (AJOL)

    Information System (GIS) can provide greater possibility to refine the analysis of land cover and terrain characteristics for ... Regression Tree (BRT) statistical method was used to clarify the relationships between land cover and terrain variables .... shapefile. The training dataset is defined as multiple polygons for each class.

  2. Applications of VIC for Climate Land Cover Change Imapacts

    Science.gov (United States)

    Markert, Kel

    2017-01-01

    Study focuses on the Lower Mekong Basin (LMB), the LMB is an economically and ecologically important region: (1) One of the largest exporters of rice and fish products, (2) Within top three most biodiverse river basins in the world. Natural climate variability plays an important role in water supply within the region: (1) Short-term climate variability (ENSO, MJO), (2) Long-term climate variability (climate change). Projections of climate change show there will be a decrease in water availability world wide which has implications for food security and ecology. Additional studies show there may be socioeconomic turmoil due to water wars and food security in developing regions such as the Mekong Basin. Southeast Asia has experienced major changes in land use and land cover from 1980 – 2000. Major economic reforms resulting in shift from subsistence farming to market-based agricultural production. Changes in land cover continue to occur which have an important role within the land surface aspect of hydrology.

  3. Seasat SAR identification of dry climate urban land cover

    Science.gov (United States)

    Henderson, F. M.; Wharton, S. W.

    1980-01-01

    Digitally processed Seasat synthetic aperture radar (SAR) imagery of the Denver, Colorado area was examined to assess its potential for mapping urban land cover and the compatibility of SAR derived classes with those described in the U.S. Geological Survey classification system. The entire scene was interpreted to generate a small-scale land cover map. In addition, six subscene enlargements representative of urban land cover categories extant in the area were used as test sites for detailed analysis of land cover types. Two distinct approaches were employed and compared in examining the imagery - a visual interpretation of black-and-white positive transparencies and an automated-machine/visual interpretation. The latter used the Image 100 interactive image analysis system to generate land cover classes by density level slicing of the image frequency histogram.

  4. Percent Agricultural Land Cover on Steep Slopes

    Data.gov (United States)

    U.S. Environmental Protection Agency — Clearing land for agriculture tends to increase soil erosion. The amount of erosion is related to the steepness of the slope, farming methods used and soil type....

  5. the implications of land use/cover dynamics on resources

    African Journals Online (AJOL)

    2017-12-04

    Dec 4, 2017 ... The analysis of static land use maps of 1983, 2000, and 2013, all pointed to the fact that, there have been significant changes observed on forest cover, farmland, grazing land and settlement land uses. ... materials, provision of shelter, food production, .... lean resources and created a variety of complex.

  6. 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...

  7. Hyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach.

    Science.gov (United States)

    Huo, Hongyuan; Guo, Jifa; Li, Zhao-Liang

    2018-01-26

    Few studies have examined hyperspectral remote-sensing image classification with type-II fuzzy sets. This paper addresses image classification based on a hyperspectral remote-sensing technique using an improved interval type-II fuzzy c-means (IT2FCM*) approach. In this study, in contrast to other traditional fuzzy c-means-based approaches, the IT2FCM* algorithm considers the ranking of interval numbers and the spectral uncertainty. The classification results based on a hyperspectral dataset using the FCM, IT2FCM, and the proposed improved IT2FCM* algorithms show that the IT2FCM* method plays the best performance according to the clustering accuracy. In this paper, in order to validate and demonstrate the separability of the IT2FCM*, four type-I fuzzy validity indexes are employed, and a comparative analysis of these fuzzy validity indexes also applied in FCM and IT2FCM methods are made. These four indexes are also applied into different spatial and spectral resolution datasets to analyze the effects of spectral and spatial scaling factors on the separability of FCM, IT2FCM, and IT2FCM* methods. The results of these validity indexes from the hyperspectral datasets show that the improved IT2FCM* algorithm have the best values among these three algorithms in general. The results demonstrate that the IT2FCM* exhibits good performance in hyperspectral remote-sensing image classification because of its ability to handle hyperspectral uncertainty.

  8. Hyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach

    Directory of Open Access Journals (Sweden)

    Hongyuan Huo

    2018-01-01

    Full Text Available Few studies have examined hyperspectral remote-sensing image classification with type-II fuzzy sets. This paper addresses image classification based on a hyperspectral remote-sensing technique using an improved interval type-II fuzzy c-means (IT2FCM* approach. In this study, in contrast to other traditional fuzzy c-means-based approaches, the IT2FCM* algorithm considers the ranking of interval numbers and the spectral uncertainty. The classification results based on a hyperspectral dataset using the FCM, IT2FCM, and the proposed improved IT2FCM* algorithms show that the IT2FCM* method plays the best performance according to the clustering accuracy. In this paper, in order to validate and demonstrate the separability of the IT2FCM*, four type-I fuzzy validity indexes are employed, and a comparative analysis of these fuzzy validity indexes also applied in FCM and IT2FCM methods are made. These four indexes are also applied into different spatial and spectral resolution datasets to analyze the effects of spectral and spatial scaling factors on the separability of FCM, IT2FCM, and IT2FCM* methods. The results of these validity indexes from the hyperspectral datasets show that the improved IT2FCM* algorithm have the best values among these three algorithms in general. The results demonstrate that the IT2FCM* exhibits good performance in hyperspectral remote-sensing image classification because of its ability to handle hyperspectral uncertainty.

  9. The Aerosol Index and Land Cover Class Based Atmospheric Correction Aerosol Optical Depth Time Series 1982–2014 for the SMAC Algorithm

    Directory of Open Access Journals (Sweden)

    Emmihenna Jääskeläinen

    2017-10-01

    Full Text Available Atmospheric effects, especially aerosols, are a significant source of uncertainty for optical remote sensing of surface parameters, such as albedo. Also to achieve a homogeneous surface albedo time series, the atmospheric correction has to be homogeneous. However, a global homogeneous aerosol optical depth (AOD time series covering several decades did not previously exist. Therefore, we have constructed an AOD time series 1982–2014 using aerosol index (AI data from the satellite measurements of the Total Ozone Mapping Spectrometer (TOMS and the Ozone Monitoring Instrument (OMI, together with the Solar zenith angle and land use classification data. It is used as input for the Simplified Method for Atmospheric Correction (SMAC algorithm when processing the surface albedo time series CLARA-A2 SAL (the Surface ALbedo from the Satellite Application Facility on Climate Monitoring project cLoud, Albedo and RAdiation data record, the second release. The surface reflectance simulations using the SMAC algorithm for different sets of satellite-based AOD data show that the aerosol-effect correction using the constructed TOMS/OMI based AOD data is comparable to using other satellite-based AOD data available for a shorter time range. Moreover, using the constructed TOMS/OMI based AOD as input for the atmospheric correction typically produces surface reflectance [-20]values closer to those obtained using in situ AOD values than when using other satellite-based AOD data.

  10. Scale-dependent effects of land cover on water physico-chemistry and diatom-based metrics in a major river system, the Adour-Garonne basin (South Western France)

    Energy Technology Data Exchange (ETDEWEB)

    Tudesque, Loïc, E-mail: loic.tudesque@univ-tlse3.fr [CNRS, Université Paul Sabatier, ENFA, UMR5174 EDB (Laboratoire Évolution and Diversité Biologique), 118 route de Narbonne, F-31062 Toulouse (France); Université Toulouse 3 Paul Sabatier, CNRS, UMR5174 EDB, F-31062 Toulouse (France); Tisseuil, Clément [CNRS, Université Paul Sabatier, ENFA, UMR5174 EDB (Laboratoire Évolution and Diversité Biologique), 118 route de Narbonne, F-31062 Toulouse (France); Université Toulouse 3 Paul Sabatier, CNRS, UMR5174 EDB, F-31062 Toulouse (France); Lek, Sovan, E-mail: sovan.lek@univ-tlse3.fr [CNRS, Université Paul Sabatier, ENFA, UMR5174 EDB (Laboratoire Évolution and Diversité Biologique), 118 route de Narbonne, F-31062 Toulouse (France); Université Toulouse 3 Paul Sabatier, CNRS, UMR5174 EDB, F-31062 Toulouse (France)

    2014-01-01

    The scale dependence of ecological phenomena remains a central issue in ecology. Particularly in aquatic ecology, the consideration of the accurate spatial scale in assessing the effects of landscape factors on stream condition is critical. In this context, our study aimed at assessing the relationships between multi-spatial scale land cover patterns and a variety of water quality and diatom metrics measured at the stream reach level. This investigation was conducted in a major European river system, the Adour-Garonne river basin, characterized by a wide range of ecological conditions. Redundancy analysis (RDA) and variance partitioning techniques were used to disentangle the different relationships between land cover, water-chemistry and diatom metrics. Our results revealed a top-down “cascade effect” indirectly linking diatom metrics to land cover patterns through water physico-chemistry, which occurred at the largest spatial scales. In general, the strength of the relationships between land cover, physico-chemistry, and diatoms was shown to increase with the spatial scale, from the local to the basin scale, emphasizing the importance of continuous processes of accumulation throughout the river gradient. Unexpectedly, we established that the influence of land cover on the diatom metric was of primary importance both at the basin and local scale, as a result of discontinuous but not necessarily antagonist processes. The most detailed spatial grain of the Corine land cover classification appeared as the most relevant spatial grain to relate land cover to water chemistry and diatoms. Our findings provide suitable information to improve the implementation of effective diatom-based monitoring programs, especially within the scope of the European Water Framework Directive. - Highlights: •The spatial scale dependence of the “cascade effect” in a river system has been demonstrated. •The strength of the relationships between land cover and diatoms through

  11. 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.

  12. Cartographic aspects of land cover change detection (over- and underestimation in the I&CORINE Land Cover 2000 project)

    NARCIS (Netherlands)

    Feranec, J.; Hazeu, G.W.; Jaffrain, G.; Cebecauer, T.

    2007-01-01

    This paper presents the results of analysis of the data obtained by the method of computer-aided visual interpretation of satellite images used for identification of changes in land cover within the framework of the Image and CORINE Land Cover 2000 (I&CLC2000) Project (jointly managed by the

  13. 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...

  14. Polarization in the land distribution, land use and land cover change in the Amazon

    Science.gov (United States)

    D'ANTONA, Alvaro; VANWEY, Leah; LUDEWIGS, Thomas

    2013-01-01

    The objective of this article is to present Polarization of Agrarian Structure as a single, more complete representation than models emphasizing rural exodus and consolidation of land into large agropastoral enterprises of the dynamics of changing land distribution, land use / cover, and thus the rural milieu of Amazonia. Data were collected in 2003 using social surveys on a sample of 587 lots randomly selected from among 5,086 lots on a cadastral map produced in the 1970s. Georeferencing of current property boundaries in the location of these previously demarcated lots allows us to relate sociodemographic and biophysical variables of the surveyed properties to the changes in boundaries that have occurred since the 1970s. As have other authors in other Amazonian regions, we found concentration of land ownership into larger properties. The approach we took, however, showed that changes in the distribution of land ownership is not limited to the appearance of larger properties, those with 200 ha or more; there also exists substantial division of earlier lots into properties with fewer than five hectares, many without any agropastoral use. These two trends are juxtaposed against the decline in establishments with between five and 200 ha. The variation across groups in land use / land cover and population distribution shows the necessity of developing conceptual models, whether from socioeconomic, demographic or environmental perspectives, look beyond a single group of people or properties. PMID:24639597

  15. Effect of land cover change on snow free surface albedo across the continental United States

    Science.gov (United States)

    Wickham, J.; Nash, M.S.; Barnes, Christopher A.

    2016-01-01

    Land cover changes (e.g., forest to grassland) affect albedo, and changes in albedo can influence radiative forcing (warming, cooling). We empirically tested albedo response to land cover change for 130 locations across the continental United States using high resolution (30 m-×-30 m) land cover change data and moderate resolution (~ 500 m-×-500 m) albedo data. The land cover change data spanned 10 years (2001 − 2011) and the albedo data included observations every eight days for 13 years (2001 − 2013). Empirical testing was based on autoregressive time series analysis of snow free albedo for verified locations of land cover change. Approximately one-third of the autoregressive analyses for woody to herbaceous or forest to shrub change classes were not significant, indicating that albedo did not change significantly as a result of land cover change at these locations. In addition, ~ 80% of mean differences in albedo arising from land cover change were less than ± 0.02, a nominal benchmark for precision of albedo measurements that is related to significant changes in radiative forcing. Under snow free conditions, we found that land cover change does not guarantee a significant albedo response, and that the differences in mean albedo response for the majority of land cover change locations were small.

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

    Directory of Open Access Journals (Sweden)

    Salman Qadri

    2017-01-01

    Full Text Available Data fusion is a powerful tool for the merging of multiple sources of information to produce a better output as compared to individual source. This study describes the data fusion of five land use/cover types, that is, bare land, fertile cultivated land, desert rangeland, green pasture, and Sutlej basin river land derived from remote sensing. A novel framework for multispectral and texture feature based data fusion is designed to identify the land use/land cover data types correctly. Multispectral data is obtained using a multispectral radiometer, while digital camera is used for image dataset. It has been observed that each image contained 229 texture features, while 30 optimized texture features data for each image has been obtained by joining together three features selection techniques, that is, Fisher, Probability of Error plus Average Correlation, and Mutual Information. This 30-optimized-texture-feature dataset is merged with five-spectral-feature dataset to build the fused dataset. A comparison is performed among texture, multispectral, and fused dataset using machine vision classifiers. It has been observed that fused dataset outperformed individually both datasets. The overall accuracy acquired using multilayer perceptron for texture data, multispectral data, and fused data was 96.67%, 97.60%, and 99.60%, respectively.

  17. Characterizing, monitoring, and simulating land cover dynamics using GlobeLand30

    DEFF Research Database (Denmark)

    Jokar Arsanjani, Jamal

    2018-01-01

    Land cover maps provide us with a unique opportunity to monitor our environmental and anthropogenic resources over space and time. Temporal land cover maps increase the efficiency of land monitoring process by providing a set of observations so that any changes in the landscape can be tracked. So...

  18. 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

  19. 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.

  20. 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).

  1. 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.

  2. 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.

  3. 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.

  4. 2005 Kansas Land Cover Patterns, Level IV, Kansas River Watershed

    Data.gov (United States)

    Kansas Data Access and Support Center — The 2005 Kansas Land Cover Patterns (KLCP) Mapping Initiative was a two-phase mapping endeavor that occurred over a three-year period (2007-2009). Note that while...

  5. SMAPVEX12 Land Cover Classification Map V001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set consists of land cover classification data derived from satellite imagery as part of the Soil Moisture Active Passive Validation Experiment 2012...

  6. The Changing Midwest Assessment: land cover, natural resources, and people

    Science.gov (United States)

    Robert Potts; Eric Gustafson; Susan I. Stewart; Frank R. Thompson; Kathleen Bergen; Daniel G. Brown; Roger Hammer; Volker Radeloff; David Bengston; John Sauer; Brian Sturtevant

    2004-01-01

    Documents changes in land cover, forests, selected natural resources, and human demographics and attitudes across the Midwest from roughly 1980 to 2000. The changing Midwest assessment: data and shapefiles are available from the Forest Service Research Data Archive....

  7. Unsupervised land cover change detection: meaningful sequential time series analysis

    CSIR Research Space (South Africa)

    Salmon, BP

    2011-06-01

    Full Text Available An automated land cover change detection method is proposed that uses coarse spatial resolution hyper-temporal earth observation satellite time series data. The study compared three different unsupervised clustering approaches that operate on short...

  8. 2005 Kansas Land Cover Patterns, Level I, Kansas River Watershed

    Data.gov (United States)

    Kansas Data Access and Support Center — The Upper Kansas River Watershed Land Cover Patterns map represents Phase 1 of a two-phase mapping initiative occurring over a three-year period as part of a...

  9. EXPLORING CLIMATE CHANGE EFFECTS ON WATERSHED SEDIMENT YIELD AND LAND COVER-BASED MITIGATION MEASURES USING SWAT MODEL, RS AND GIS: CASE OF CAGAYAN RIVER BASIN, PHILIPPINES

    Directory of Open Access Journals (Sweden)

    J. A. Principe

    2012-07-01

    Full Text Available The impact of climate change in the Philippines was examined in the country's largest basin–the Cagayan River Basin–by predicting its sediment yield for a long period of time. This was done by integrating the Soil and Water Assessment Tool (SWAT model, Remote Sensing (RS and Geographic Information System (GIS. A set of Landsat imageries were processed to include an atmospheric correction and a filling procedure for cloud and cloud-shadow infested pixels was used to maximize each downloaded scene for a subsequent land cover classification using Maximum Likelihood classifier. The Shuttle Radar Topography Mission (SRTM-DEM was used for the digital elevation model (DEM requirement of the model while ArcGIS™ provided the platform for the ArcSWAT extension, for storing data and displaying spatial data. The impact of climate change was assessed by varying air surface temperature and amount of precipitation as predicted in the Intergovernmental Panel on Climate Change (IPCC scenarios. A Nash-Sutcliff efficiency (NSE > 0.4 and coefficient of determination (R2 > 0.5 for both the calibration and validation of the model showed that SWAT model can realistically simulate the hydrological processes in the study area. The model was then utilized for land cover change and climate change analyses and their influence on sediment yield. Results showed a significant relationship exists among the changes in the climate regime, land cover distributions and sediment yield. Finally, the study suggested land cover distribution that can potentially mitigate the serious negative effects of climate change to a regional watershed's sediment yield.

  10. Land cover in single-family housing areas and how it correlates with urban form

    DEFF Research Database (Denmark)

    Nielsen, Mette Boye; Jensen, Marina Bergen

    2015-01-01

    Land cover composition is a valuable indicator of the ecological performance of a city. Single-family housing areas constitute a substantial part of most cities and may as such play an important role for sustainable urban development. From aerial photos we performed detailed GIS-based mapping...... that the urban form of neighbourhoods to some degree predicts the long term land cover composition. We conclude that strategies for maximizing the ecological performance of single-family housing areas can be informed by knowledge on urban form, and that digital mapping of land cover based on aerial photography...... of land cover in three detached single-family housing areas in Denmark of different urban form but comparable housing densities (ranging from 10.0 to 11.3 houses per hectare). The findings were subjected to statistical analysis and landscape metrics. Land cover varied with urban form: A traditional...

  11. Machine Learning Comparison between WorldView-2 and QuickBird-2-Simulated Imagery Regarding Object-Based Urban Land Cover Classification

    Directory of Open Access Journals (Sweden)

    Tessio Novack

    2011-10-01

    Full Text Available The objective of this study is to compare WorldView-2 (WV-2 and QuickBird-2-simulated (QB-2 imagery regarding their potential for object-based urban land cover classification. Optimal segmentation parameters were automatically found for each data set and the obtained results were quantitatively compared and discussed. Four different feature selection algorithms were used in order to verify to which data set the most relevant object-based features belong to. Object-based classifications were performed with four different supervised algorithms applied to each data set and the obtained accuracies and model performances indexes were compared. Segmentation experiments carried out involving bands exclusively available in the WV-2 sensor generated segments slightly more similar to our reference segments (only about 0.23 discrepancy. Fifty seven percent of the different selected features and 53% of all the 80 selections refer to features that can only be calculated with the additional bands of the WV-2 sensor. On the other hand, 57% of the most relevant features and 63% of the second most relevant features can also be calculated considering only the QB-2 bands. In 10 out of 16 classifications, higher Kappa values were achieved when features related to the additional bands of the WV-2 sensor were also considered. In most cases, classifications carried out with the 8-band-related features generated less complex and more efficient models than those generated only with QB-2 band-related features. Our results lead to the conclusion that spectrally similar classes like ceramic tile roofs and bare soil, as well as asphalt and dark asbestos roofs can be better distinguished when the additional bands of the WV-2 sensor are used throughout the object-based classification process.

  12. 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...

  13. 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...

  14. Decadal Land Use and Land Cover Classifications across India, 1985, 1995, 2005

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides land use and land cover (LULC) classification products at 100-m resolution for India at decadal intervals for 1985, 1995 and 2005. The data...

  15. Global Tree Cover and Biomass Carbon on Agricultural Land

    NARCIS (Netherlands)

    Zomer, Robert J.; Neufeldt, Henry; Xu, Jianchu; Ahrends, Antje; Bossio, Deborah; Trabucco, Antonio; Noordwijk, Van Meine; Wang, Mingcheng

    2016-01-01

    Agroforestry systems and tree cover on agricultural land make an important contribution to climate change mitigation, but are not systematically accounted for in either global carbon budgets or national carbon accounting. This paper assesses the role of trees on agricultural land and their

  16. Land cover changes and their biogeophysical effects on climate

    Science.gov (United States)

    Rezaul Mahmood; Roger A. Pielke; Kenneth G. Hubbard; Dev Niyogi; Paul A. Dirmeyer; Clive McAlpine; Andrew M. Carleton; Robert Hale; Samuel Gameda; Adriana Beltrán-Przekurat; Bruce Baker; Richard McNider; David R. Legates; Marshall Shepherd; Jinyang Du; Peter D. Blanken; Oliver W. Frauenfeld; U.S. Nair; Souleymane. Fall

    2013-01-01

    Land cover changes (LCCs) play an important role in the climate system. Research over recent decades highlights the impacts of these changes on atmospheric temperature, humidity, cloud cover, circulation, and precipitation. These impacts range from the local- and regional-scale to sub-continental and global-scale. It has been found that the impacts of regional-scale...

  17. Cost, drivers and action against land degradation through land use and cover change in Russia

    Science.gov (United States)

    Sorokin, Alexey; Strokov, Anton; Johnson, Timothy; Mirzabaev, Alisher

    2016-04-01

    The natural conditions and socio-economic factors determine the structure and the principles of land use in Russia. The increasing degradation of land resources in many parts of Russia manifested in numerous forms such as desertification, soil erosion, secondary salinization, water-logging and overgrazing. The major drivers of degradation include: climatic change, unsustainable agricultural practices, industrial and mining activities, expansion of crop production to fragile and marginal areas, inadequate maintenance of irrigation and drainage networks. Several methods for estimating Total Economic Value of land-use and land-cover change were used: 1) the cost of production per hectare (only provisional services were included); 2) the value of ecosystem services provided by Costanza et al, 1997; 3) coefficients of basic transfer and contingent approaches based on Tianhong et al, 2008 and Xie et al, 2003, who interviewed 200 ecologists to give a value of ecosystem services of different land types in China; 4) coefficients on a basic transfer and contingent approaches based on author's interview of 20 experts in Lomonosov Moscow State University. In general, the estimation of the prices for action and inaction in addressing the degradation and improvement of the land resources on a national scale (the Federal districts) with an emphasis on the period of economic reforms from 1990-2009 in Russia, where the area of arable lands decreased by 25% showed that the total land use/cover dynamic changes are about 130 mln ha, and the total annual costs of land degradation due to land-use change only, are about 189 bln USD in 2009 as compared with 2001, e.g. about 23.6 bln USD annually, or about 2% of Russia's Gross Domestic Product in 2010. The costs of action against land degradation are lower than the costs of inaction in Russia by 5-6 times over the 30 year horizon. Almost 92% of the costs of action are made up of the opportunity costs of action. The study was performed with

  18. Assessment of environmental responses to land use/land cover ...

    African Journals Online (AJOL)

    aghomotsegin

    2013-12-17

    Dec 17, 2013 ... satellite images were digitally processed using ILWIS 3.2™ software and exported to ArcGIS 9.3™ for further processing and ... annual rates of 8.26, 4.66 and 2.81%, respectively, while water bodies also decreased at an annual rate of 0.17%. ... urban land uses are direct indications of social and economic ...

  19. LAND COVER MAPPING USING SENTINEL-1 SAR DATA

    Directory of Open Access Journals (Sweden)

    S. Abdikan

    2016-06-01

    Full Text Available In this paper, the potential of using free-of-charge Sentinel-1 Synthetic Aperture Radar (SAR imagery for land cover mapping in urban areas is investigated. To this aim, we use dual-pol (VV+VH Interferometric Wide swath mode (IW data collected on September 16th 2015 along descending orbit over Istanbul megacity, Turkey. Data have been calibrated, terrain corrected, and filtered by a 5x5 kernel using gamma map approach. During terrain correction by using a 25m resolution SRTM DEM, SAR data has been resampled resulting into a pixel spacing of 20m. Support Vector Machines (SVM method has been implemented as a supervised pixel based image classification to classify the dataset. During the classification, different scenarios have been applied to find out the performance of Sentinel-1 data. The training and test data have been collected from high resolution image of Google Earth. Different combinations of VV and VH polarizations have been analysed and the resulting classified images have been assessed using overall classification accuracy and Kappa coefficient. Results demonstrate that, combining opportunely dual polarization data, the overall accuracy increases up to 93.28% against 73.85% and 70.74% of using individual polarization VV and VH, respectively. Our preliminary analysis points out that dual polarimetric Sentinel-1SAR data can be effectively exploited for producing accurate land cover maps, with relevant advantages for urban planning and management of large cities.

  20. Modelling Deforestation and Land Cover Transitions of Tropical Peatlands in Sumatra, Indonesia Using Remote Sensed Land Cover Data Sets

    Directory of Open Access Journals (Sweden)

    Ian Elz

    2015-08-01

    Full Text Available In Southeast Asia land use change associated with forest loss and degradation is a major source of greenhouse gas (GHG emissions. This is of particular concern where deforestation occurs on peat soils. A business-as-usual (BAU land change model was developed using Dinamica EGO© for a REDD+ Demonstration Activity area in south-east Jambi Province, Sumatra, Indonesia containing Berbak National Park (NP. The model output will be used as baseline land change predictions for comparison with alternative land cover management scenarios as part of a REDD+ feasibility study. The study area is approximately 376,000 ha with approximately 50% on peat soils. The model uses published 2000 and 2010 land cover maps as input and projects land cover change for thirty years until 2040. The model predicted that under a BAU scenario the forest area, 185,000 ha in 2010, will decline by 37% by 2040. In protected forest areas, approximately 50% of the study area, forest cover will reduce by 25%. Peat swamp forest will reduce by almost 37%. The greatest land cover category increases are plantation/regrowth areas (which includes oil palm and open areas which each increase by 30,000 ha. These results indicate that the site has great potential as an Indonesian REDD+ Demonstration Activity.

  1. 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.

  2. 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.

  3. Past and predicted future changes in the land cover of the Upper Mississippi River floodplain, USA

    Science.gov (United States)

    De Jager, N. R.; Rohweder, J.J.; Nelson, J.C.

    2013-01-01

    This study provides one historical and two alternative future contexts for evaluating land cover modifications within the Upper Mississippi River (UMR) floodplain. Given previously documented changes in land use, river engineering, restoration efforts and hydro-climatic changes within the UMR basin and floodplain, we wanted to know which of these changes are the most important determinants of current and projected future floodplain land cover. We used Geographic Information System data covering approximately 37% of the UMR floodplain (3232 km2) for ca 1890 (pre-lock and dam) and three contemporary periods (1975, 1989 and 2000) across which river restoration actions have increased and hydro-climatic changes have occurred. We further developed two 50-year future scenarios from the spatially dependent land cover transitions that occurred from 1975 to 1989 (scenario A) and from 1989 to 2000 (scenario B) using Markov models.Land cover composition of the UMR did not change significantly from 1975 to 2000, indicating that current land cover continues to reflect historical modifications that support agricultural production and commercial navigation despite some floodplain restoration efforts and variation in river discharge. Projected future land cover composition based on scenario A was not significantly different from the land cover for 1975, 1989 or 2000 but was different from the land cover of scenario B, which was also different from all other periods. Scenario B forecasts transition of some forest and marsh habitat to open water by the year 2050 for some portions of the northern river and projects that some agricultural lands will transition to open water in the southern portion of the river. Future floodplain management and restoration planning efforts in the UMR should consider the potential consequences of continued shifts in hydro-climatic conditions that may occur as a result of climate change and the potential effects on floodplain land cover.

  4. Space-based monitoring of land-use/land-cover in the Upper Rio Grande Basin: An opportunity for understanding urbanization trends in a water-scarce transboundary river basin.

    Science.gov (United States)

    Mubako, S. T.; Hargrove, W. L.; Heyman, J. M.; Reyes, C. S.

    2016-12-01

    Urbanization is an area of growing interest in assessing the impact of human activities on water resources in arid regions. Remote sensing techniques provide an opportunity to analyze land cover change over time, and are useful in monitoring areas undergoing rapid urban growth. This case study for the water-scarce Upper Rio Grande River Basin uses a supervised classification algorithm to quantify the rate and evaluate the pattern of urban sprawl. A focus is made on the fast growing El-Paso-Juarez metropolitan area on the US-Mexico border and the City of Las Cruces in New Mexico, areas where environmental challenges and loss of agricultural and native land to urban development are major concerns. Preliminary results show that the land cover is dominantly native with some significant agriculture along the Rio Grande River valley. Urban development across the whole study area expanded from just under 3 percent in 1990, to more than 11 percent in 2015. The urban expansion is occurring mainly around the major urban areas of El Paso, Ciudad Juarez, and Las Cruces, although there is visible growth of smaller urban settlements scattered along the Rio Grande River valley during the same analysis period. The proportion of native land cover fluctuates slightly depending on how much land is under crops each analysis year, but there is a decreasing agricultural land cover trend suggesting that land from this sector is being lost to urban development. This analysis can be useful in planning to protect the environment, preparing for growth in infrastructure such as schools, increased traffic demands, and monitoring availability of resources such as groundwater as the urban population grows.

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

    Directory of Open Access Journals (Sweden)

    Hagos Gebreslassie

    2014-12-01

    Full Text Available Land Use-Land Cover (LULC dynamic has of human kind age and is one of the phenomenons which interweave the socio economic and environmental issues in Ethiopia. Huluka watershed is one of the watersheds in Central Rift Valley of Ethiopia which drains to Lake Langano. Few decades ago the stated watershed was covered with dense acacia forest. But, nowadays like other part of Ethiopia, it is experiencing complex dynamics of LULC. The aim of this research was thus to evaluate the LULC dynamics seen in between 1973–2009. This was achieved through collecting qualitative and quantitative data using Geographic Information System (GIS and Remote Sensing (RS technique. Field observations, discussion with elders were also employed to validate results from remotely sensed data. Based on the result, eight major dynamic LULC classes were identified from the watershed. Of these LULC classes, only cultivated and open lands had shown continuous and progressive expansion mainly at the expense of grass, shrub and forest lands. The 25% and 0% of cultivated and open land of the watershed in 1973 expanded to 84% and 4% in 2009 respectively while the 29%, 18% and 22% of grass, shrub and forest land of the watershed in 1973 degraded to 3.5%, 4% and 1.5% in 2009 respectively. As a result, land units which had been used for pastoralist before 1973 were identified under mixed agricultural system after 2000. In the end, this study came with a recommendation of an intervention of concerned body to stop the rapid degradation of vegetation on the watershed.

  6. Land cover change using an energy transition paradigm in a statistical mechanics approach

    Science.gov (United States)

    Zachary, Daniel S.

    2013-10-01

    This paper explores a statistical mechanics approach as a means to better understand specific land cover changes on a continental scale. Integrated assessment models are used to calculate the impact of anthropogenic emissions via the coupling of technoeconomic and earth/atmospheric system models and they have often overlooked or oversimplified the evolution of land cover change. Different time scales and the uncertainties inherent in long term projections of land cover make their coupling to integrated assessment models difficult. The mainstream approach to land cover modelling is rule-based methodology and this necessarily implies that decision mechanisms are often removed from the physical geospatial realities, therefore a number of questions remain: How much of the predictive power of land cover change can be linked to the physical situation as opposed to social and policy realities? Can land cover change be understood using a statistical approach that includes only economic drivers and the availability of resources? In this paper, we use an energy transition paradigm as a means to predict this change. A cost function is applied to developed land covers for urban and agricultural areas. The counting of area is addressed using specific examples of a Pólya process involving Maxwell-Boltzmann and Bose-Einstein statistics. We apply an iterative counting method and compare the simulated statistics with fractional land cover data with a multi-national database. An energy level paradigm is used as a basis in a flow model for land cover change. The model is compared with tabulated land cover change in Europe for the period 1990-2000. The model post-predicts changes for each nation. When strong extraneous factors are absent, the model shows promise in reproducing data and can provide a means to test hypothesis for the standard rules-based algorithms.

  7. Understanding Land Use and Land Cover Dynamics from 1976 to 2014 in Yellow River Delta

    Directory of Open Access Journals (Sweden)

    Baolei Zhang

    2017-03-01

    Full Text Available Long-term intensive land use/cover changes (LUCCs of the Yellow River Delta (YRD have been happening since the 1960s. The land use patterns of the LUCCs are crucial for bio-diversity conservation and/or sustainable development. This study quantified patterns of the LUCCs, explored the systematic transitions, and identified wetland change trajectory for the period 1976–2014 in the YRD. Landsat imageries of 1976, 1984, 1995, 2006, and 2014 were used to derive nine land use classes. Post classification change detection analysis based on enhanced transition matrix was applied to identify land use dynamics and trajectory of wetland change. The five cartographic outputs for changes in land use underlined major decreases in natural wetland areas and increases in artificial wetland and non-wetland, especially aquafarms, salt pans and construction lands. The systematic transitions in the YRD were wetland degradation, wetland artificialization, and urbanization. Wetland change trajectory results demonstrated that the main wetland changes were wetland degradation and wetland artificialization. Coastline change is the subordinate reason for natural wetland degradation in comparison with human activities. The results of this study allowed for an improvement in the understanding of the LUCC processes and enabled researchers and planners to focus on the most important signals of systematic landscape transitions while also allowing for a better understanding of the proximate causes of changes.

  8. Modeling interactions between land cover and climate in integrated assessment models (Invited)

    Science.gov (United States)

    Calvin, K. V.

    2013-12-01

    Integrated Assessment Models (IAMs) link representations of the regionally disaggregated global economy, energy system, agriculture and land-use, terrestrial carbon cycle, oceans and climate in an internally consistent framework. These models are often used as science-based decision-support tools for evaluating the consequences of climate, energy, and other policies, and their use in this framework is likely to increase in the future. Additionally, these models are used to develop future scenarios of emissions and land cover for use in climate models (e.g., RCPs and CMIP5). Land use is strongly influenced by assumptions about population, income, diet, ecosystem productivity change, and climate policy. Population, income, and diet determine the amount of food production needed in the future. Assumptions about future changes in crop yields due to agronomic developments influence the amount of land needed to produce food crops. Climate policy has implications for land when land-based mitigation options (e.g., afforestation and bioenergy) are considered. IAM models consider each of these factors in their computation of land use in the future. As each of these factors is uncertain in the future, IAM models use scenario analysis to explore the implications of each. For example, IAMs have been used to explore the effect of different mitigation policies on land cover. These models can quantify the trade-offs in terms of land cover, energy prices, food prices, and mitigation costs of each of these policies. Furthermore, IAMs are beginning to explore the effect of climate change on land productivity, and the implications that changes in productivity have on mitigation efforts. In this talk, we describe the implications for future land use and land cover of a variety of socioeconomic, technological, and policy drivers in several IAM models. Additionally, we will discuss the effects of future land cover on climate and the effects of climate on future land cover, as simulated

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

    Science.gov (United States)

    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

  10. Land use/Land Cover Changes and Causes of Deforestation in the ...

    African Journals Online (AJOL)

    The objective of this paper is to provide the non-existent data on land use/land cover changes in the Wilberforce Island for the purposes of determining the causes of deforestation and changes in the vegetation cover for a 13 – year period. Accordingly, 125 questionnaires were administered in five communities to determine ...

  11. Land use/land cover and scale influences on in-stream nitrogen uptake kinetics

    Science.gov (United States)

    Covino, Tim; McGlynn, Brian; McNamara, Rebecca

    2012-06-01

    Land use/land cover change often leads to increased nutrient loading to streams; however, its influence on stream ecosystem nutrient transport remains poorly understood. Given the deleterious impacts elevated nutrient loading can have on aquatic ecosystems, it is imperative to improve understanding of nutrient retention capacities across stream scales and watershed development gradients. We performed 17 nutrient addition experiments on six streams across the West Fork Gallatin Watershed, Montana, USA, to quantify nitrogen uptake kinetics and retention dynamics across stream sizes (first to fourth order) and along a watershed development gradient. We observed that stream nitrogen (N) uptake kinetics and spiraling parameters varied across streams of different development intensity and scale. In more developed watersheds we observed a fertilization affect. This fertilization affect was evident as increased ash-free dry mass, chlorophylla, and ambient and maximum uptake rates in developed as compared to undeveloped streams. Ash-free dry mass, chlorophylla, and the number of structures in a subwatershed were significantly correlated to nutrient spiraling and kinetic parameters, while ambient and average annual N concentrations were not. Additionally, increased maximum uptake capacities in developed streams contributed to low in-stream nutrient concentrations during the growing season, and helped maintain watershed export at low levels during base flow. Our results indicate that land use/land cover change can enhance in-stream uptake of limiting nutrients and highlight the need for improved understanding of the watershed dynamics that control nutrient export across scales and development intensities for mitigation and protection of aquatic ecosystems.

  12. Modelling and optimization of land use/land cover change in a developing urban catchment.

    Science.gov (United States)

    Xu, Ping; Gao, Fei; He, Junchao; Ren, Xinxin; Xi, Weijin

    2017-06-01

    The impacts of land use/cover change (LUCC) on hydrological processes and water resources are mainly reflected in changes in runoff and pollutant variations. Low impact development (LID) technology is utilized as an effective strategy to control urban stormwater runoff and pollution in the urban catchment. In this study, the impact of LUCC on runoff and pollutants in an urbanizing catchment of Guang-Ming New District in Shenzhen, China, were quantified using a dynamic rainfall-runoff model with the EPA Storm Water Management Model (SWMM). Based on the simulations and observations, the main objectives of this study were: (1) to evaluate the catchment runoff and pollutant variations with LUCC, (2) to select and optimize the appropriate layout of LID in a planning scenario for reducing the growth of runoff and pollutants under LUCC, (3) to assess the optimal planning schemes for land use/cover. The results showed that compared to 2013, the runoff volume, peak flow and pollution load of suspended solids (SS), and chemical oxygen demand increased by 35.1%, 33.6% and 248.5%, and 54.5% respectively in a traditional planning scenario. The assessment result of optimal planning of land use showed that annual rainfall control of land use for an optimal planning scenario with LID technology was 65%, and SS pollutant load reduction efficiency 65.6%.

  13. Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed

    Data.gov (United States)

    U.S. Environmental Protection Agency — Changes in climate and land cover are among the principal variables affecting watershed hydrology. This paper uses a cell-based model to examine the hydrologic...

  14. SAFARI 2000 Land Cover from AVHRR, 1-Deg, 1987 (Defries and Townshend)

    Data.gov (United States)

    National Aeronautics and Space Administration — The UMD 1-degree Global Land Cover product was produced by researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at UMD. The product is based on...

  15. Characterizing the relationship between land use land cover change and land surface temperature

    Science.gov (United States)

    Tran, Duy X.; Pla, Filiberto; Latorre-Carmona, Pedro; Myint, Soe W.; Caetano, Mario; Kieu, Hoan V.

    2017-02-01

    Exploring changes in land use land cover (LULC) to understand the urban heat island (UHI) effect is valuable for both communities and local governments in cities in developing countries, where urbanization and industrialization often take place rapidly but where coherent planning and control policies have not been applied. This work aims at determining and analyzing the relationship between LULC change and land surface temperature (LST) patterns in the context of urbanization. We first explore the relationship between LST and vegetation, man-made features, and cropland using normalized vegetation, and built-up indices within each LULC type. Afterwards, we assess the impacts of LULC change and urbanization in UHI using hot spot analysis (Getis-Ord Gi∗ statistics) and urban landscape analysis. Finally, we propose a model applying non-parametric regression to estimate future urban climate patterns using predicted land cover and land use change. Results from this work provide an effective methodology for UHI characterization, showing that (a) LST depends on a nonlinear way of LULC types; (b) hotspot analysis using Getis Ord Gi∗ statistics allows to analyze the LST pattern change through time; (c) UHI is influenced by both urban landscape and urban development type; (d) LST pattern forecast and UHI effect examination can be done by the proposed model using nonlinear regression and simulated LULC change scenarios. We chose an inner city area of Hanoi as a case-study, a small and flat plain area where LULC change is significant due to urbanization and industrialization. The methodology presented in this paper can be broadly applied in other cities which exhibit a similar dynamic growth. Our findings can represent an useful tool for policy makers and the community awareness by providing a scientific basis for sustainable urban planning and management.

  16. Understanding Driving Forces and Implications Associated with the Land Use and Land Cover Changes in Portugal

    Directory of Open Access Journals (Sweden)

    Bruno M. Meneses

    2017-02-01

    Full Text Available Understanding the processes of land use and land cover changes (LUCC and the associated driving forces is important for achieving sustainable development. This paper presents the LUCC in Portugal at the regional level (NUTS II from 1995 to 2010 and discusses the main driving forces and implications associated with these LUCC. The main objectives of this work are: (a to quantify the land use and land cover (LUC types (level I of LUC cartography by NUT II in Portugal for the years 1995, 2007 and 2010; (b to assess the spatio-temporal LUCC; and (c to identify and discuss the main driving forces of LUCC and corresponding implications based on correlations and Principal Components Analysis. The results revealed large regional and temporal LUCC and further highlighted the different and sometimes opposite time trends between neighboring regions. By associating driving forces to LUCC, different influences at the regional level were observed, namely LUCC into agriculture land derived from the construction of dams (Alentejo region, or the conversion of coniferous forest into eucalypt forest (Centre region associated with increased gross value added (GVA and employment in industry and forestry. Temporal differentiation was also observed, particularly in the settlements that expanded between 1995 and 2007 due to the construction of large infrastructures (e.g., highways, industrial complexes, or buildings, which is reflected on employment in industry and construction and respective GVA. However, certain LUCC have implications, particularly in energy consumption, for which different behavior between regions can be highlighted in this analysis, but also on land-use sustainability.

  17. Land management and land-cover change have impacts of similar magnitude on surface temperature

    NARCIS (Netherlands)

    Luyssaert, S.; Jammet, M.; Stoy, P.C.; Estel, S.; Pongratz, J.; Ceschia, E.; Churkina, G.; Don, A.; Erb, K.; Ferlicoq, M.; Gielen, B.; Gruenwald, T.; Houghton, R.A.; Klumpp, K.; Knohl, A.; Kolb, T.; Kuemmerle, T.; Laurila, T.; Lohila, A.; Loustau, D.; McGrath, M.J.; Meyfroidt, P.; Moors, E.J.; Naudts, K.; Novick, K.; Otto, J.; Pilegaard, K.; Pio, C.A.; Rambal, S.; Rebmann, C.; Ryder, J.; Suyker, A.E.; Varlagin, A.; Wattenbach, M.; Dolman, A.J.

    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 shelter. The biophysical effects of LCC on surface climate are largely

  18. 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...

  19. Land-use and land-cover analysis of Ilorin Emirate between 1986 ...

    African Journals Online (AJOL)

    user

    Markov chain and cellular automata analysis for predicting change (Parker et al., 2003; Alejandro and Servet, 2003;. Gamerman, 1997; Gilks et al., 1996; Bucher and Culik, 1984;. Burks, 1970a). The first method was used for identifying change in the five land- use types. The comparison of the land-use / land-cover statistics.

  20. 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...

  1. 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.

  2. Locally optimized separability enhancement indices for urban land cover mapping

    DEFF Research Database (Denmark)

    Feyisa, Gudina L.; Meilby, Henrik; Darrel Jenerette, G.

    2016-01-01

    Landsat data were used to assess urbanization-induced dynamics in Land use/cover (LULC), surface thermal intensity, and its relationships with urban biophysical composition. The study was undertaken in Addis Ababa city, Ethiopia. Ground-based data and high resolution images were used as reference......–DR approach using eight Landsat images acquired between 1985 and 2010. Two approaches were applied to quantify surface heat intensity (SHIn) and to examine its spatial patterns over 25 years: thermal gradient analysis and hot spot analysis. A Simultaneous Autoregressive Spatial error model (SARerr) was used...... were statistically significant (P Heat Intensity (SHIn) analysis showed increasing contrast (1985-2010) between urban centers and the outskirt. On average, outskirts were cooler than central urban areas by up to 3.7 °C. We detected statistically significant differences in intra...

  3. A satellite based scheme for predicting the effects of land cover change on local microclimate and surface hydrology: Development of an operational regional planning tool

    Science.gov (United States)

    Arthur, Sandra Traci

    Humans have diverse goals for their use of land: mining, water supply, aesthetic enjoyment, recreation, transportation, housing, etc. Any individual living within an actively developing community can look back in time and note how, perhaps slowly but nonetheless dramatically, the total land area dedicated to human use has increased. As our society's basic functioning intensifies, the disappearance of "free" open space is apparent---today, even conservation areas are carefully designated, mapped and controlled. This transition in land use is a result of many individual decisions that occur throughout space and time, often with little concern for the potential impacts on the local environment. Two specific environmental components---the microclimate and surface hydrology---are the focus of this thesis. This study, as well as related tools and bodies of knowledge, should be used to broaden the scientific basis behind land use management decisions. It will be shown that development can induce predictable changes in measures of the local radiant surface temperature and evapotranspiration fraction---as long as certain features of the development are known. Specifically, the vegetation changes that accompany the development must be noted, as well as the initial climatic state of the land parcel. Additionally, plots of runoff vs. rainfall for gauged basins will be interpreted in terms of the proportion of the basin contributing to a storm event's runoff signal. For a particular basin, four distinct runoff responses, separated by season and antecedent moisture conditions, will be distinguished. The response for the non-summer months under typical antecedent moisture conditions will be shown to be the most representative of and responsive to a basin's land use patterns. A scheme that makes use of satellite-derived land cover patterns and other physical attributes of the basin in order to determine this particular runoff response will be presented. The Soil Conservation

  4. 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).

  5. 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...

  6. Land cover and topography affect the land transformation caused by wind facilities.

    Science.gov (United States)

    Diffendorfer, Jay E; Compton, Roger W

    2014-01-01

    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.

  7. LAND COVER CLASSIFICATION OF MULTI-SENSOR IMAGES BY DECISION FUSION USING WEIGHTS OF EVIDENCE MODEL

    Directory of Open Access Journals (Sweden)

    P. Li

    2012-07-01

    Full Text Available This paper proposed a novel method of decision fusion based on weights of evidence model (WOE. The probability rules from classification results from each separate dataset were fused using WOE to produce the posterior probability for each class. The final classification was obtained by maximum probability. The proposed method was evaluated in land cover classification using two examples. The results showed that the proposed method effectively combined multisensor data in land cover classification and obtained higher classification accuracy than the use of single source data. The weights of evidence model provides an effective decision fusion method for improved land cover classification using multi-sensor data.

  8. Simulation of regional temperature change effect of land cover change in agroforestry ecotone of Nenjiang River Basin in China

    Science.gov (United States)

    Liu, Tingxiang; Zhang, Shuwen; Yu, Lingxue; Bu, Kun; Yang, Jiuchun; Chang, Liping

    2017-05-01

    The Northeast China is one of typical regions experiencing intensive human activities within short time worldwide. Particularly, as the significant changes of agriculture land and forest, typical characteristics of pattern and process of agroforestry ecotone change formed in recent decades. The intensive land use change of agroforestry ecotone has made significant change for regional land cover, which had significant impact on the regional climate system elements and the interactions among them. This paper took agroforestry ecotone of Nenjiang River Basin in China as study region and simulated temperature change based on land cover change from 1950s to 1978 and from 1978 to 2010. The analysis of temperature difference sensitivity to land cover change based on Weather Research and Forecasting (WRF) model showed that the land cover change from 1950s to 1978 induced warming effect over all the study area, including the change of grassland to agriculture land, grassland to deciduous broad-leaved forest, and deciduous broad-leaved forest to shrub land. The land cover change from 1978 to 2010 induced cooling effect over all the study area, including the change of deciduous broad-leaved forest to agriculture land, grassland to agriculture land, shrub land to agriculture land, and deciduous broad-leaved forest to grassland. In addition, the warming and cooling effect of land cover change was more significant in the region scale than specific land cover change area.

  9. LAND USER AND LAND COVER MAPS OF EUROPE: A WEBGIS PLATFORM

    Directory of Open Access Journals (Sweden)

    M. A. Brovelli

    2016-06-01

    Full Text Available 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.

  10. 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

  11. Multi-Temporal Land Cover Classification with Sequential Recurrent Encoders

    Directory of Open Access Journals (Sweden)

    Marc Rußwurm

    2018-03-01

    Full Text Available Earth observation (EO sensors deliver data at daily or weekly intervals. Most land use and land cover classification (LULC approaches, however, are designed for cloud-free and mono-temporal observations. The increasing temporal capabilities of today’s sensors enable the use of temporal, along with spectral and spatial features.Domains such as speech recognition or neural machine translation, work with inherently temporal data and, today, achieve impressive results by using sequential encoder-decoder structures. Inspired by these sequence-to-sequence models, we adapt an encoder structure with convolutional recurrent layers in order to approximate a phenological model for vegetation classes based on a temporal sequence of Sentinel 2 (S2 images. In our experiments, we visualize internal activations over a sequence of cloudy and non-cloudy images and find several recurrent cells that reduce the input activity for cloudy observations. Hence, we assume that our network has learned cloud-filtering schemes solely from input data, which could alleviate the need for tedious cloud-filtering as a preprocessing step for many EO approaches. Moreover, using unfiltered temporal series of top-of-atmosphere (TOA reflectance data, our experiments achieved state-of-the-art classification accuracies on a large number of crop classes with minimal preprocessing, compared to other classification approaches.

  12. GlobeLand30 as an alternative fine-scale global land cover map

    DEFF Research Database (Denmark)

    Jokar Arsanjani, Jamal; Tayyebi, A.; Vaz, E.

    2016-01-01

    Global land cover maps are a vital source for mapping our globe into a set of thematic types. They have been extensively used as a basis layer for a large number of applications including ecosystem services, environmental planning, climate change, hydrological processes and policy making. While...... regional land cover maps for some areas such as Europe and North America has been greatly developed and very few temporal datasets exist, lack of such data for some regions specifically developing countries is evident. Although it seems global land cover maps such as MODIS could be a solution for mapping...... these regions, their coarse spatial resolution e.g., 500 m as well as their accuracy are very challenging. Recently, GlobeLand30 a global land cover with a relatively fine resolution at 30 m extracted from Landsat images has been released, which seems to be a potential dataset for mapping areas with limited...

  13. Has anthropogenic land-cover change been a significant climate forcing in the past? - An assessment for the Baltic Sea catchment area based on a literature review

    Science.gov (United States)

    Gaillard, Marie-Jose; Kaplan, Jed O.; Kleinen, Thomas; Brigitte Nielsen, Anne; Poska, Anneli; Samuelsson, Patrick; Strandberg, Gustav; Trondman, Anna-Kari

    2015-04-01

    We reviewed the recent published scientific literature on land cover-climate interactions at the global and regional spatial scales with the aim to assess whether it is convincingly demonstrated that anthropogenic land-cover change (ALCC) has been (over the last centuries and millennia) a significant climate forcing at the global scale, and more specifically at the scale of the Baltic Sea catchment area. The conclusions from this review are as follows: i) anthropogenic land-cover change (ALCC) is one of the few climate forcings for which the net direction of the climate response in the past is still not known. The uncertainty is due to the often counteracting temperature responses to the many biogeophysical effects, and to the biogeochemical vs biogeophysical effects; ii) there is no indication that deforestation in the Baltic Sea area since AD 1850 would have been a major cause of the recent climate warming in the region through a positive biogeochemical feedback; iii) several model studies suggest that boreal reforestation might not be an effective climate warming mitigation tool as it might lead to increased warming through biogeophysical processes; iv) palaeoecological studies indicate a major transformation of the landscape by anthropogenic activities in the southern zone of the study region occurring between 6000 and 3000/2500 calendar years before present (cal. BP) (1) ; v) the only modelling study so far of the biogeophysical effects of past ALCCs on regional climate in Europe suggests that a deforestation of the magnitude of that reconstructed for the past (between 6000 and 200 cal BP) can produce changes in winter and summer temperatures of +/- 1°, the sign of the change depending on the season and the region (2). Thus, if ALCC and their biogeophysical effects did matter in the past, they should matter today and in the future. A still prevailing idea is that planting trees will mitigate climate warming through biogeochemical effects. Therefore, there is

  14. 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

  15. Land Cover, Land Use, and Climate Change Impacts on Endemic Cichlid Habitats in Northern Tanzania

    Directory of Open Access Journals (Sweden)

    Margaret Kalacska

    2017-06-01

    Full Text Available Freshwater ecosystems are among the most threatened on Earth, facing environmental and anthropogenic pressures often surpassing their terrestrial counterparts. Land use and land cover change (LUCC such as degradation and fragmentation of the terrestrial landscape negatively impacts aquatic ecosystems. Satellite imagery allows for an impartial assessment of the past to determine habitat alterations. It can also be used as a forecasting tool in the development of species conservation strategies through models based on ecological factors extracted from imagery. In this study, we analyze Landsat time sequences (1984–2015 to quantify LUCC around three freshwater ecosystems with endemic cichlids in Tanzania. In addition, we examine population growth, agricultural expansion, and climate change as stressors that impact the habitats. We found that the natural vegetation cover surrounding Lake Chala decreased from 15.5% (1984 to 3.5% (2015. At Chemka Springs, we observed a decrease from 7.4% to 3.5% over the same period. While Lake Natron had minimal LUCC, severe climate change impacts have been forecasted for the region. Subsurface water data from the Gravity Recovery and Climate Experiment (GRACE satellite observations further show a decrease in water resources for the study areas, which could be exacerbated by increased need from a growing population and an increase in agricultural land use.

  16. Satellite images for land cover monitoring - Navigating through the maze

    Science.gov (United States)

    Künzer, Claudia; Fosnight, Gene

    2001-01-01

    Policy makers, managers, scientists and the public can view the changing environment using satellite images.  More than 60 Earth observing satellites are collecting images of the Earth's surface. Remote sensing satellite systems for land cover assessment are operated by a growing number of countries including India, the United States, Japan, France, Canada and Russia.

  17. Data mining algorithms for land cover change detection: a review

    Indian Academy of Sciences (India)

    Sangram Panigrahi

    2017-11-24

    Nov 24, 2017 ... Abstract. Land cover change detection has been a topic of active research in the remote sensing community. Due to enormous amount of data available from satellites, it has attracted the attention of data mining researchers to search a new direction for solution. The Terra Moderate Resolution Imaging ...

  18. Integrating land cover and terrain characteristics to explain plague ...

    African Journals Online (AJOL)

    Literature suggests that higher resolution remote sensing data integrated in Geographic Information System (GIS) can provide greater possibility to refine the analysis of land cover and terrain characteristics for explanation of abundance and distribution of plague hosts and vectors and hence of health risk hazards to ...

  19. Data mining algorithms for land cover change detection: a review

    Indian Academy of Sciences (India)

    Land cover change detection has been a topic of active research in the remote sensing community. Due to enormous amount of data available from satellites, it has attracted the attention of data mining researchers to search a new direction for solution. The Terra Moderate Resolution Imaging Spectrometer(MODIS) ...

  20. 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 ...

  1. Carbon emissions from land cover change in Central Vietnam

    NARCIS (Netherlands)

    Avitabile, Valerio; Schultz, Michael; Herold, Nadine; Bruin, De Sytze; Pratihast, Arun Kumar; Manh, Cuong Pham; Quang, Hien Vu; Herold, Martin

    2016-01-01

    The carbon emissions and removals due to land cover changes between 2001 and 2010 in the Vu Gia Thu Bon River Basin, Central Vietnam, were estimated using Landsat satellite images and 3083 forest inventory plots. The net emissions from above- and belowground vegetation biomass were equal to 1.76 ±

  2. 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 ...

  3. Remote Sensing-GIS Supported Land Cover Analysis of Gashaka ...

    African Journals Online (AJOL)

    This paper, using remotely acquired data and field survey analyzed land cover types, classified (supervised) and observed mean tree species distribution between the two sectors of the Gashaka-Gumti National Park (GGNP). Landsat Enhanced Thematic Mapped (ETM), 1999 imagery; Two scenes P186R054 and ...

  4. The implications of land use/cover dynamics on resources ...

    African Journals Online (AJOL)

    , ENVI 4.3, Global Mapper 15 and ArcGis 10.2. Maps were generated to show changes in land use/cover which were transposed into tables and bar graphs to show the magnitude of changes, percentage of change and the rate of change.

  5. 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.

  6. Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China

    Directory of Open Access Journals (Sweden)

    Huiran Han

    2015-04-01

    Full Text Available Land use and land cover (LULC models are essential for analyzing LULC change and predicting land use requirements and are valuable for guiding reasonable land use planning and management. However, each LULC model has its own advantages and constraints. In this paper, we explore the characteristics of LULC change and simulate future land use demand by combining a CLUE-S model with a Markov model to deal with some shortcomings of existing LULC models. Using Beijing as a case study, we describe the related driving factors from land-adaptive variables, regional spatial variables and socio-economic variables and then simulate future land use scenarios from 2010 to 2020, which include a development scenario (natural development and rapid development and protection scenarios (ecological and cultivated land protection. The results indicate good consistency between predicted results and actual land use situations according to a Kappa statistic. The conversion of cultivated land to urban built-up land will form the primary features of LULC change in the future. The prediction for land use demand shows the differences under different scenarios. At higher elevations, the geographical environment limits the expansion of urban built-up land, but the conversion of cultivated land to built-up land in mountainous areas will be more prevalent by 2020; Beijing, however, still faces the most pressure in terms of ecological and cultivated land protection.

  7. 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

  8. Land-Cover and Land-Use Change under Changing Climate in the Eurasian Arctic

    Science.gov (United States)

    Gutman, G.

    2009-04-01

    An overview of the studies conducted in the framework of the NASA Land-Cover/Land- Use Change Program focused on the Eurasian Arctic will be presented. It includes discussion of vegetation changes under climate warming and implications to carbon cycle, changes in environmental pollution, hydrologic cycle, and impacts on society. Climate change can affect land cover in the Arctic through changes in the surface reflectivity and hydrology due to changes in snow melt timing; impacts of black carbon emitted by fires and settled on bright surfaces; changes in sea ice and the consequent change in ocean circulation affecting vegetation cover patterns indirectly; and changes in the amounts of greenhouse gases emission due to permafrost melting, especially in peatlands, as warming progresses. The Arctic Eurasia is being affected by global and regional external factors that are causing its change and the positive feedbacks to this forcing may further exaggerate the situation. If the warming trend continues it will have a tremendous impact on all aspects of land cover in the Arctic region with considerable consequences at the global scale. It will cause significant changes in the natural land cover, and perhaps even greater changes in the areas where the land cover has already been considerably modified by human activities. Major changes have already taken place in how land is used in the Arctic. In many regions, there has been a clear shift from the land use practiced by indigenous people to intensive exploitation of the land for commercial and industrial uses. Results on the climate/environment - land-cover interactions will be presented.

  9. Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed

    Science.gov (United States)

    Changes in climate and land cover are among the principal variables affecting watershed hydrology.This paper uses a cell-based model to examine the hydrologic impacts of climate and land-cover changes in thesemi-arid Lower Virgin River (LVR) watershed located upstream of Lake Mead, Nevada, USA. The cell-basedmodel is developed by considering direct runoff based on the Soil Conservation Service - Curve Number (SCSCN)method and surplus runoff based on the Thornthwaite water balance theory. After calibration and validation,the model is used to predict LVR discharge under future climate and land-cover changes. The hydrologicsimulation results reveal climate change as the dominant factor and land-cover change as a secondary factor inregulating future river discharge. The combined effects of climate and land-cover changes will slightly increaseriver discharge in summer but substantially decrease discharge in winter. This impact on water resources deservesattention in climate change adaptation planning.This dataset is associated with the following publication:Chen, H., S. Tong, H. Yang, and J. Yang. Simulating the hydrologic impacts of land cover and climate changes in a semi-arid watershed. Hydrological Sciences Journal. IAHS LIMITED, Oxford, UK, 60(10): 1739-1758, (2015).

  10. EASE-Grid 2.0 Land Cover Classifications Derived from Boston University MODIS/Terra Land Cover Data, Version 1

    Data.gov (United States)

    National Aeronautics and Space Administration — These data provide land cover classifications derived from the Boston University MOD12Q1 V004 MODIS/Terra 1 km Land Cover Product (Friedl et al. 2002). The data are...

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

    Science.gov (United States)

    Stehman, S.V.; Wickham, J.D.; Fattorini, L.; Wade, T.D.; Baffetta, F.; Smith, J.H.

    2009-01-01

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

  12. 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.)

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

    Science.gov (United States)

    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.

  14. Gallup, NM 1:250,000 Quad West Half 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)...

  15. Clifton, AZ 1:250,000 Quad West Half 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)...

  16. Shiprock, NM 1:250,000 Quad East Half 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)...

  17. 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)...

  18. 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)...

  19. Roswell, NM 1:250,000 Quad West Half 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)...

  20. Gallup, NM 1:250,000 Quad East Half 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)...

  1. Socorro, NM 1:250,000 Quad West Half 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)...

  2. Carlsbad, NM 1:250,000 Quad East Half 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)...

  3. Clifton, AZ 1:250,000 Quad East Half 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)...

  4. Aztec, NM 1:250,000 Quad West Half 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)...

  5. 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)...

  6. 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)...

  7. Carlsbad, NM 1:250,000 Quad West Half 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)...

  8. Douglas, AZ 1:250,000 Quad West Half 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)...

  9. Tularosa, NM 1:250,000 Quad East Half 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)...

  10. Raton, NM 1:250,000 Quad East Half 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)...

  11. Douglas, AZ 1:250,000 Quad East Half 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)...

  12. Socorro, NM 1:250,000 Quad East Half 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)...

  13. Roswell, NM 1:250,000 Quad East Half 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)...

  14. 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)...

  15. Shiprock, NM 1:250,000 Quad West Half 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)...

  16. Raton, NM 1:250,000 Quad West Half 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)...

  17. Albuquerque, NM 1:250,000 Quad West Half 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)...

  18. Aztec, NM 1:250,000 Quad East Half 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)...

  19. Albuquerque, NM 1:250,000 Quad East Half 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)...

  20. Tularosa, NM 1:250,000 Quad West Half 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)...

  1. 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.

  2. 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.

  3. LAND COVER CLASSIFICATION USING A UAV-BORNE SPECTROMETER

    Directory of Open Access Journals (Sweden)

    S. Natesan

    2017-08-01

    Full Text Available Small fixed wing and rotor-copter unmanned aerial vehicles (UAV are being used for low altitude remote sensing for thematic land classification and precision agriculture applications. Various sensors operating in the non-visible spectrum such as multispectral, hyperspectral and thermal sensors can be used as payloads. This work presents a preliminary study on the use of unmanned aerial vehicle equipped with a compact spectrometer for land cover type characterization. When calibrated, the measured spectra by the UAV spectrometer can be processed and compared reference data to generate georeferenced reflection spectra enabling the identification, classification and characterization of land cover elements. For this case study we used a DJI Flamewheel F550 hexacopter and the FLAME-NIR spectrometer for hyperspectral measurements. The calibration of the spectrometer is described as well the approach to determine its spatial footprint. The spectrometer spectral exposure labeled ground point can be used to determine the land cover classification. Preliminary results of a case-study are presented.

  4. Land Cover Classification Using a Uav-Borne Spectrometer

    Science.gov (United States)

    Natesan, S.; Benari, G.; Armenakis, C.; Lee, R.

    2017-08-01

    Small fixed wing and rotor-copter unmanned aerial vehicles (UAV) are being used for low altitude remote sensing for thematic land classification and precision agriculture applications. Various sensors operating in the non-visible spectrum such as multispectral, hyperspectral and thermal sensors can be used as payloads. This work presents a preliminary study on the use of unmanned aerial vehicle equipped with a compact spectrometer for land cover type characterization. When calibrated, the measured spectra by the UAV spectrometer can be processed and compared reference data to generate georeferenced reflection spectra enabling the identification, classification and characterization of land cover elements. For this case study we used a DJI Flamewheel F550 hexacopter and the FLAME-NIR spectrometer for hyperspectral measurements. The calibration of the spectrometer is described as well the approach to determine its spatial footprint. The spectrometer spectral exposure labeled ground point can be used to determine the land cover classification. Preliminary results of a case-study are presented.

  5. Sensitivity of MODIS evapotranspiration algorithm (MOD16) to the acuracy of meteorological data and land use and land cover parameterization

    Science.gov (United States)

    Ruhoff, Anderson; Santini Adamatti, Daniela

    2017-04-01

    MODIS evapotranspiration (MOD16) is currently available with 1 km of spatial resolution over 109.03 Million km2 of vegetated land surface areas and this information is widely used to evaluate the linkages between hydrological, energy and carbon cycles. The algorithm is driven by meteorological reanalysis data and MODIS remotely-sensed data, which include land use and land cover classification (MCD12Q1), leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) (MOD15A2) and albedo (MOD43b3). For calibration and parameterization, the algorithm uses a Biome Property Look-up Table (BPLUT) based on MCD12Q1 land cover classification. Several studies evaluated MOD16 accuracy using evapotranspiration measurements and water balance analysis, showing that this product can reproduce global evapotranspiration effectively under a variety climate condition, from local to wide-basin scale, with uncertainties up to 25%. In this study, we evaluated the sensitivity of MOD16 algorithm to land use and land cover parameterization and to meteorological data. Considering that MCD12Q1 has an accuracy between 70 and 85% at continental scale, we changed land cover parametererization to understand the influence of land use and land cover classification on MOD16 evapotranspiration estimations. Knowing that meteorological reanalysis data also have uncertainties (mostly related to the coarse spatial resolution), we compared MOD16 evapotranspiration driven by observed meteorological data to those driven by the reanalysis data. Our analysis were carried in South America, with evapotranspiration and meteorological measurements from the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) at 8 different sites, including tropical rainforest, tropical dry forest, selective logged forest, seasonal flooded forest and pasture/agriculture. Our results indicate that land use and land cover classification has a strong influence on MOD16 algorithm. The use of

  6. Geo-spatial analysis of land use and land cover changes in the Lake ...

    African Journals Online (AJOL)

    local communities and investors in the tourism and hospitality industry in order to reduce the environmental ... 1Department of Geography and Rural Development, Kwame Nkrumah University of Science and Technology,. Kumasi .... Pandy and Nathawat (2006), in a related study on land use and land cover mapping in.

  7. An Assessment of the Land Use and Land Cover Changes in ...

    African Journals Online (AJOL)

    Most of these changes are yet to be captured and documented as essential baseline information for developmental purposes. This paper seeks to establish the current status of land use and land cover changes for Shurugwi district as well as to determine the extent of these changes using Geographic Information System ...

  8. 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...

  9. 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...

  10. 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...

  11. 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.

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. Clovis, 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...

  17. Clifton, 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...

  18. Aztec, NM CO 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...

  19. 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...

  20. Douglas, 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...

  1. Brownfield, 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...

  2. Albuquerque, 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...

  3. Tucumcari, 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...

  4. Roswell, 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...

  5. Chaco Mesa 1:100,000 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...

  6. Socorro, 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...

  7. Hobbs, 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...

  8. 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...

  9. 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...

  10. 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 ...

  11. 81 An Assessment of the land use and land cover changes in ...

    African Journals Online (AJOL)

    `123456789jkl''''#

    transformations have occurred in the land use and land cover patterns as evidenced by persistent ..... band specific maximum and minimum radiance. DN= Digital number b) At-satellite radiance was converted to surface reflectance using equation (2) ρp=π*Lλ *d2 /ESUNλ * COS (Θs) (2) where ρp = planetary reflectance ...

  12. Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments

    Science.gov (United States)

    Prestele, Reinhard; Arneth, Almut; Bondeau, Alberte; de Noblet-Ducoudré, Nathalie; Pugh, Thomas A. M.; Sitch, Stephen; Stehfest, Elke; Verburg, Peter H.

    2017-05-01

    Land-use and land-cover change (LULCC) represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in terrestrial biosphere models (TBMs). The published results of these models are used in major assessments of processes and impacts of global environmental change, such as the reports of the Intergovernmental Panel on Climate Change (IPCC). Fully coupled models of climate, land use and biogeochemical cycles to explore land use-climate interactions across spatial scales are currently not available. Instead, information on land use is provided as exogenous data from the land-use change modules of integrated assessment models (IAMs) to TBMs. In this article, we discuss, based on literature review and illustrative analysis of empirical and modeled LULCC data, three major challenges of this current LULCC representation and their implications for land use-climate interaction studies: (I) provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II) accounting for sub-grid processes and bidirectional changes (gross changes) across spatial scales, and (III) the allocation strategy of independent land-use data at the grid cell level in TBMs. We discuss the factors that hamper the development of improved land-use representation, which sufficiently accounts for uncertainties in the land-use modeling process. We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs. Moreover, we suggest concentrating on the

  13. RLC AVHRR-Derived Land Cover, Former Soviet Union, 15-km, 1984-1993

    Data.gov (United States)

    National Aeronautics and Space Administration — This dataset is a 15-kilometer resolution land cover map for the land area of the Former Soviet Union. There are sixty land cover classes distinguished in this...

  14. RLC AVHRR-Derived Land Cover, Former Soviet Union, 15-km, 1984-1993

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This dataset is a 15-kilometer resolution land cover map for the land area of the Former Soviet Union. There are sixty land cover classes distinguished in...

  15. Agricultural Land Cover from Multitemporal C-Band SAR Data

    Science.gov (United States)

    Skriver, H.

    2013-12-01

    Henning Skriver DTU Space, Technical University of Denmark Ørsteds Plads, Building 348, DK-2800 Lyngby e-mail: hs@space.dtu.dk Problem description This paper focuses on land cover type from SAR data using high revisit acquisitions, including single and dual polarisation and fully polarimetric data, at C-band. The data set were acquired during an ESA-supported campaign, AgriSAR09, with the Radarsat-2 system. Ground surveys to obtain detailed land cover maps were performed during the campaign. Classification methods using single- and dual-polarisation data, and fully polarimetric data are used with multitemporal data with short revisit time. Results for airborne campaigns have previously been reported in Skriver et al. (2011) and Skriver (2012). In this paper, the short revisit satellite SAR data will be used to assess the trade-off between polarimetric SAR data and data as single or dual polarisation SAR data. This is particularly important in relation to the future GMES Sentinel-1 SAR satellites, where two satellites with a relatively wide swath will ensure a short revisit time globally. Questions dealt with are: which accuracy can we expect from a mission like the Sentinel-1, what is the improvement of using polarimetric SAR compared to single or dual polarisation SAR, and what is the optimum number of acquisitions needed. Methodology The data have sufficient number of looks for the Gaussian assumption to be valid for the backscatter coefficients for the individual polarizations. The classification method used for these data is therefore the standard Bayesian classification method for multivariate Gaussian statistics. For the full-polarimetric cases two classification methods have been applied, the standard ML Wishart classifier, and a method based on a reversible transform of the covariance matrix into backscatter intensities. The following pre-processing steps were performed on both data sets: The scattering matrix data in the form of SLC products were

  16. 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...

  17. Effects of land cover changes induced by large physical disturbances on hydrological responses in Central Taiwan.

    Science.gov (United States)

    Hong, Nien Ming; Chu, Hone-Jay; Lin, Yu-Pin; Deng, Dung-Po

    2010-07-01

    This study analyzes the significant impacts of typhoons and earthquakes on land cover change and hydrological response. The occurrence of landslides following typhoons and earthquakes is a major indicator of natural disturbance. The hydrological response of the Chenyulan watershed to land use change was assessed from 1996 to 2005. Land use changes revealed by seven remote images corresponded to typhoons and a catastrophic earthquake in central Taiwan. Hydrological response is discussed as the change in quantities and statistical distributions of hydrological components. The land cover change results indicate that the proportion of landslide relative to total area increased to 6.1% after the Chi-Chi earthquake, representing the largest increase during the study period. The study watershed is dominated by forest land cover. Comparisons of hydrological components reveal that the disturbance significantly affects base flow and direct runoff. The hydrological modeling results demonstrate that the change in forest area correlates with the variation of base flow and direct runoff. Base flow and direct runoff are sensitive to land use in discussions of distinction. The proposed approach quantifies the effect of typhoons and earthquakes on land cover changes.

  18. 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.

  19. 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.

  20. Time series change detection: Algorithms for land cover change

    Science.gov (United States)

    Boriah, Shyam

    The climate and earth sciences have recently undergone a rapid transformation from a data-poor to a data-rich environment. In particular, climate and ecosystem related observations from remote sensors on satellites, as well as outputs of climate or earth system models from large-scale computational platforms, provide terabytes of temporal, spatial and spatio-temporal data. These massive and information-rich datasets offer huge potential for advancing the science of land cover change, climate change and anthropogenic impacts. One important area where remote sensing data can play a key role is in the study of land cover change. Specifically, the conversion of natural land cover into humandominated cover types continues to be a change of global proportions with many unknown environmental consequences. In addition, being able to assess the carbon risk of changes in forest cover is of critical importance for both economic and scientific reasons. In fact, changes in forests account for as much as 20% of the greenhouse gas emissions in the atmosphere, an amount second only to fossil fuel emissions. Thus, there is a need in the earth science domain to systematically study land cover change in order to understand its impact on local climate, radiation balance, biogeochemistry, hydrology, and the diversity and abundance of terrestrial species. Land cover conversions include tree harvests in forested regions, urbanization, and agricultural intensification in former woodland and natural grassland areas. These types of conversions also have significant public policy implications due to issues such as water supply management and atmospheric CO2 output. In spite of the importance of this problem and the considerable advances made over the last few years in high-resolution satellite data, data mining, and online mapping tools and services, end users still lack practical tools to help them manage and transform this data into actionable knowledge of changes in forest ecosystems that

  1. Land cover and rainfall interact to shape waterbird community composition.

    Directory of Open Access Journals (Sweden)

    Colin E Studds

    Full Text Available Human land cover can degrade estuaries directly through habitat loss and fragmentation or indirectly through nutrient inputs that reduce water quality. Strong precipitation events are occurring more frequently, causing greater hydrological connectivity between watersheds and estuaries. Nutrient enrichment and dissolved oxygen depletion that occur following these events are known to limit populations of benthic macroinvertebrates and commercially harvested species, but the consequences for top consumers such as birds remain largely unknown. We used non-metric multidimensional scaling (MDS and structural equation modeling (SEM to understand how land cover and annual variation in rainfall interact to shape waterbird community composition in Chesapeake Bay, USA. The MDS ordination indicated that urban subestuaries shifted from a mixed generalist-specialist community in 2002, a year of severe drought, to generalist-dominated community in 2003, of year of high rainfall. The SEM revealed that this change was concurrent with a sixfold increase in nitrate-N concentration in subestuaries. In the drought year of 2002, waterbird community composition depended only on the direct effect of urban development in watersheds. In the wet year of 2003, community composition depended both on this direct effect and on indirect effects associated with high nitrate-N inputs to northern parts of the Bay, particularly in urban subestuaries. Our findings suggest that increased runoff during periods of high rainfall can depress water quality enough to alter the composition of estuarine waterbird communities, and that this effect is compounded in subestuaries dominated by urban development. Estuarine restoration programs often chart progress by monitoring stressors and indicators, but rarely assess multivariate relationships among them. Estuarine management planning could be improved by tracking the structure of relationships among land cover, water quality, and waterbirds

  2. 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.

  3. 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.

  4. Land Cover and Land Use in Slovakia within the LUCAS 201 5 Pan-European Harmonized Survey

    Directory of Open Access Journals (Sweden)

    Vladimír Hutár

    2016-12-01

    Full Text Available The LUCAS project was launched following a decision by the European Parliament and Council of the European Union in May 2000. Eurostat started the LUCAS pilot project in close cooperation with the technical support of the Directorate General for Agriculture and Rural Development’s Joint Research Centre in 2001 . The main aim of the project is to provide a common, aligned, in situ overview of agricultural and environmental data, using GNSS and photo documentation for specific, georeferenced points. Research was carried out in Slovakia over a three-year period, starting in 2006. In 2009, an evaluation of land cover/use was carried out. This article presents the process of preparing, securing, conducting and researching the management of land cover and land use in Slovakia. The survey was launched in 201 2. The classification base consists of eight categories of land cover and land use, which are broken down into more detail. The result is a structured database of images and digital records for 2,455 selected points. The largest class mapped is forestland. The stabilization of the sampling scheme allowed the construction of a time series for monitoring land cover changes for selected types.

  5. The Improvement of Land Cover Classification by Thermal Remote Sensing

    Directory of Open Access Journals (Sweden)

    Liya Sun

    2015-06-01

    Full Text Available Land cover classification has been widely investigated in remote sensing for agricultural, ecological and hydrological applications. Landsat images with multispectral bands are commonly used to study the numerous classification methods in order to improve the classification accuracy. Thermal remote sensing provides valuable information to investigate the effectiveness of the thermal bands in extracting land cover patterns. k-NN and Random Forest algorithms were applied to both the single Landsat 8 image and the time series Landsat 4/5 images for the Attert catchment in the Grand Duchy of Luxembourg, trained and validated by the ground-truth reference data considering the three level classification scheme from COoRdination of INformation on the Environment (CORINE using the 10-fold cross validation method. The accuracy assessment showed that compared to the visible and near infrared (VIS/NIR bands, the time series of thermal images alone can produce comparatively reliable land cover maps with the best overall accuracy of 98.7% to 99.1% for Level 1 classification and 93.9% to 96.3% for the Level 2 classification. In addition, the combination with the thermal band improves the overall accuracy by 5% and 6% for the single Landsat 8 image in Level 2 and Level 3 category and provides the best classified results with all seven bands for the time series of Landsat TM images.

  6. Assessing Hydrologic Impacts of Future Land Cover Change ...

    Science.gov (United States)

    Long‐term land‐use and land cover change and their associated impacts pose critical challenges to sustaining vital hydrological ecosystem services for future generations. In this study, a methodology was developed on the San Pedro River Basin to characterize hydrologic impacts from future urban growth through time. This methodology was then expanded and utilized to characterize the changing hydrology on the South Platte River Basin. Future urban growth is represented by housingdensity maps generated in decadal intervals from 2010 to 2100, produced by the U.S. Environmental Protection Agency (EPA) Integrated Climate and Land‐Use Scenarios (ICLUS) project. ICLUS developed future housing density maps by adapting the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines to the conterminous United States. To characterize hydrologic impacts from future growth, the housing density maps were reclassified to National Land Cover Database (NLCD) 2006 land cover classes and used to parameterize the Soil and Water Assessment Tool (SWAT) using the Automated Geospatial Watershed Assessment (AGWA) tool. The objectives of this project were to 1) develop and describe a methodology for adapting the ICLUS data for use in AGWA as anapproach to evaluate basin‐wide impacts of development on water‐quantity and ‐quality, 2) present initial results from the application of the methodology to

  7. 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.

  8. 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.

  9. 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.

  10. Plant life form based habitat monitoring in a European landscape framework for early warning of changes in land cover and biodiversity

    DEFF Research Database (Denmark)

    Brandt, Jesper; Olsen, Martin; Bloch-Petersen, Margit

    During the last 25 years different programs for detailed landscape surveys based on stratified area covering sampling in landscape grids of ¼ to 4 km2 have been carried out in a number of European countries with slightly different methodologies and perspectives, developing towards permanent...... in the preparation of a common European Field Monitoring Handbook as a user-friendly tool in support of implementing the Habitat Directive, including NATURA 2000, and linking scientific and policy-oriented European projects. The overall European monitoring role of the BioHab framework is to establish a landscape...

  11. UNCERTAINTY ASSESSMENT OF GLOBELAND30 LAND COVER DATA SET OVER CENTRAL ASIA

    Directory of Open Access Journals (Sweden)

    B. Sun

    2016-06-01

    Full Text Available GlobeLand30, the world’s first 30m-resolution global land cover data set, has recently been issued for research on global change at a fine resolution. Given the accuracy of GlobeLand30 data may show significant variation in different parts of the world and data quality at continental scale has not been validated yet, this study aims to evaluate the uncertainty of the data over Central Asia. Since it is difficult to get long-term historical ground references, GlobeLand30 data at the most recent epoch (i.e., GlobeLand30-2010 was assessed. In the test, a large sample size was adopted, and more than 25 thousand samples were selected by a random sampling scheme and interpreted manually as ground references based on higher resolution imagery at the same epoch, such as images from ZY-3 (China Resources Series satellite and Google earth. Cross validation of image interpretation by three well-trained interpreters was adopted to make the references more reliable. Error matrix and Kappa coefficient were utilized to quantify data accuracies in terms of classification accuracy. Results show that the GlobeLand30-2010 data presents an overall accuracy of 46% in the study area. As for specific land cover types, bare land illustrates a high user’s accuracy but a lower producer’s accuracy. At the same time, the accuracies of grassland and forest are significantly lower than other types. The majority of misclassification types come from bare land. It implies a difficulty of distinguishing grassland or forest from bare land in the study area. In addition, the confusion between shrub land and grassland also results in the misclassification. The results serve as a useful reference of data accuracy for further analysis of land cover change in Central Asia as well as the applications of GlobeLand30 data at a regional or continental scale.

  12. 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

  13. Integration of Fish and Wildlife Data with Geobased and Remotely Sensed Land Use/land Cover Data: a Demonstration Using Sites in Pennsylvania. [Berwick and Lancaster

    Science.gov (United States)

    Cushwa, C. T.; Laroche, G.; Dubrock, C. W.

    1982-01-01

    The U.S. Fish and Wildlife Service developed a statewide fish and wildlife data base for the Pennsylvania Game Commission that includes 125 categories of information on each of the 844 species. This species data base is integrated with geobased and remotely-sensed land use/land cover data from two sites in Pennsylvania. One site is an energy development project; the other is a high-energy use area. Analyses using the combined animal and land use data bases can be demonstrated for a variety of land use/land cover types at both sites. The ability to make "what if" analysis prior to project implementation is presented.

  14. Land Surface Phenology from MODIS: Characterization of the Collection 5 Global Land Cover Dynamics Product

    Science.gov (United States)

    Ganguly, Sangram; Friedl, Mark A.; Tan, Bin; Zhang, Xiaoyang; Verma, Manish

    2010-01-01

    Information related to land surface phenology is important for a variety of applications. For example, phenology is widely used as a diagnostic of ecosystem response to global change. In addition, phenology influences seasonal scale fluxes of water, energy, and carbon between the land surface and atmosphere. Increasingly, the importance of phenology for studies of habitat and biodiversity is also being recognized. While many data sets related to plant phenology have been collected at specific sites or in networks focused on individual plants or plant species, remote sensing provides the only way to observe and monitor phenology over large scales and at regular intervals. The MODIS Global Land Cover Dynamics Product was developed to support investigations that require regional to global scale information related to spatiotemporal dynamics in land surface phenology. Here we describe the Collection 5 version of this product, which represents a substantial refinement relative to the Collection 4 product. This new version provides information related to land surface phenology at higher spatial resolution than Collection 4 (500-m vs. 1-km), and is based on 8-day instead of 16-day input data. The paper presents a brief overview of the algorithm, followed by an assessment of the product. To this end, we present (1) a comparison of results from Collection 5 versus Collection 4 for selected MODIS tiles that span a range of climate and ecological conditions, (2) a characterization of interannual variation in Collections 4 and 5 data for North America from 2001 to 2006, and (3) a comparison of Collection 5 results against ground observations for two forest sites in the northeastern United States. Results show that the Collection 5 product is qualitatively similar to Collection 4. However, Collection 5 has fewer missing values outside of regions with persistent cloud cover and atmospheric aerosols. Interannual variability in Collection 5 is consistent with expected ranges of

  15. Rubber and Land-Cover Land-Use Change in Mainland Southeast Asia

    Science.gov (United States)

    Fox, J. M.; Hurni, K.

    2017-12-01

    Over the past half century, the five countries of Mainland Southeast Asia (MSEA) - Cambodia, Laos, Myanmar, Thailand, and Vietnam - have witnessed major shifts from predominantly subsistence agrarian economies to increasingly commercialized agriculture. Major drivers of change include policy initiatives that fostered regional economic integration and promoted among other changes rapid expansion of boom-crop plantations. Among the many types of commercial boom crops promoted and grown in MSEA are numerous tree-based products such as rubber, coffee, tree species for pulp and paper (particularly eucalyptus and acacia), cashews, and fruits such as oranges, lychees, and longans. The project proposal hypothesized that most (but not all) tree crops replaced swidden cultivation fields and hence are not necessarily accompanied by deforestation. We used MODIS EVI and SWIR time-series from 2001-2014 to classify changes in tree cover across MSEA; a total of 6849 sample points were used to train the classifier (75%) and verification (25%). The classification consists of 24 classes and 17 classes represent tree crops. Project results suggest that 4.4 m ha of rubber have been planted since 2003; 50% of rubber is planted on former evergreen forest land, 18% on deciduous forest land, and 32% on low vegetation area (former crop lands, bushes, scrub). Tree crops occupy about 8% of the landscape (half of that is rubber). Due to the differences in their political and economic histories these countries display different LCLUCs. In northern Laos, smallholder rubber plantations dominate and shifting cultivation is common in the upland. In southern Laos, large-scale plantations of rubber, coffee, eucalyptus, and sugarcane are widespread. In Thailand, vast areas are covered by annual agriculture; fruit trees and rubber are the prevailing tree crops and are mostly planted by smallholders. In Cambodia, large-scale rubber plantations have expanded in recent years on forest lands; smallholder

  16. Land cover modification geoindicator applied in a tropical coastal environment.

    Science.gov (United States)

    Palacio-Aponte, Gerardo

    2014-09-01

    Environmental changes due to natural processes and anthropic modifications can be characterized by the degree of land cover modification and its environmental implications over time. The main goal of the present study was to propose and apply a land cover modification geoindicator in order to assess the environmental condition of the territory per landscape units. It was designed to interpret diffuse information and transform it into a synthetic indicator that will be useful for environmental managers. The geoindicator evaluation was performed through a multi-temporal analysis of medium resolution Landsat satellite images and their unsupervised classification according to the direction of land use transitions. A change detection analysis between image pairs from 1973, 1991 and 2001 was made to detect unaffected areas and the areas in which positive or negative land cover changes could be observed. The proposed methodology was applied in the coastal palustrine area; specifically, in the marine-terrestrial ecotone of Campeche, Mexico. Geoindicator values during the 1974-1991 and 1991-2001 periods were low, 46.5% and 40.9%, respectively, due to the intrinsic limitations of coastal wetlands for productive activities. Urban and suburban transition areas showed high degrees of modification of about 39.5% and 32.1% for the first and the second period, respectively. Moderate modification, 4.9% in the first period and 5.7% in the second, was observed in isolated landscape units with recovering vegetation. The proposed geoindicator showed physiognomic and functional evidence of affectation levels from human activities, regeneration patterns and alteration of the landscape structure, modulated by the historical-economic process in the studied area.

  17. Land cover mapping for development planning in Eastern and Southern Africa

    Science.gov (United States)

    Oduor, P.; Flores Cordova, A. I.; Wakhayanga, J. A.; Kiema, J.; Farah, H.; Mugo, R. M.; Wahome, A.; Limaye, A. S.; Irwin, D.

    2016-12-01

    Africa continues to experience intensification of land use, driven by competition for resources and a growing population. Land cover maps are some of the fundamental datasets required by numerous stakeholders to inform a number of development decisions. For instance, they can be integrated with other datasets to create value added products such as vulnerability impact assessment maps, and natural capital accounting products. In addition, land cover maps are used as inputs into Greenhouse Gas (GHG) inventories to inform the Agriculture, Forestry and other Land Use (AFOLU) sector. However, the processes and methodologies of creating land cover maps consistent with international and national land cover classification schemes can be challenging, especially in developing countries where skills, hardware and software resources can be limiting. To meet this need, SERVIR Eastern and Southern Africa developed methodologies and stakeholder engagement processes that led to a successful initiative in which land cover maps for 9 countries (Malawi, Rwanda, Namibia, Botswana, Lesotho, Ethiopia, Uganda, Zambia and Tanzania) were developed, using 2 major classification schemes. The first sets of maps were developed based on an internationally acceptable classification system, while the second sets of maps were based on a nationally defined classification system. The mapping process benefited from reviews from national experts and also from technical advisory groups. The maps have found diverse uses, among them the definition of the Forest Reference Levels in Zambia. In Ethiopia, the maps have been endorsed by the national mapping agency as part of national data. The data for Rwanda is being used to inform the Natural Capital Accounting process, through the WAVES program, a World Bank Initiative. This work illustrates the methodologies and stakeholder engagement processes that brought success to this land cover mapping initiative.

  18. Spatially disaggregated disease transmission risk: land cover, land use and risk of dengue transmission on the island of Oahu.

    Science.gov (United States)

    Vanwambeke, Sophie O; Bennett, Shannon N; Kapan, Durrell D

    2011-02-01

    Vector-borne diseases persist in transmission systems that usually comprise heterogeneously distributed vectors and hosts leading to a highly heterogeneous case distribution. In this study, we build on principles of classical mathematical epidemiology to investigate spatial heterogeneity of disease risk for vector-borne diseases. Land cover delineates habitat suitability for vectors, and land use determines the spatial distribution of humans. We focus on the risk of exposure for dengue transmission on the Hawaiian island of Oahu, where the vector Aedes albopictus is well established and areas of dense human population exist. In Hawai'i, dengue virus is generally absent, but occasionally flares up when introduced. It is therefore relevant to investigate risk, but difficult to do based on disease incidence data. Based on publicly available data (land cover, land use, census data, surveillance mosquito trapping), we map the spatial distribution of vectors and human hosts and finally overlay them to produce a vector-to-host ratio map. The resulting high-resolution maps indicate a high spatial variability in vector-to-host ratio suggesting that risk of exposure is spatially heterogeneous and varies according to land cover and land use. © 2010 Blackwell Publishing Ltd.

  19. Meteorological Effects of Land Cover Changes in Hungary during the 20th Century

    Science.gov (United States)

    Drüszler, Á.; Vig, P.; Csirmaz, K.

    2012-04-01

    Geological, paleontological and geomorphologic studies show that the Earth's climate has always been changing since it came into existence. The climate change itself is self-evident. Therefore the far more serious question is how much does mankind strengthen or weaken these changes beyond the natural fluctuation and changes of climate. The aim of the present study was to restore the historical land cover changes and to simulate the meteorological consequences of these changes. Two different land cover maps for Hungary were created in vector data format using GIS technology. The land cover map for 1900 was reconstructed based on statistical data and two different historical maps: the derived map of the 3rd Military Mapping Survey of the Austro-Hungarian Empire and the Synoptic Forestry Map of the Kingdom of Hungary. The land cover map for 2000 was derived from the CORINE land cover database. Significant land cover changes were found in Hungary during the 20th century according to the examinations of these maps and statistical databases. The MM5 non-hydrostatic dynamic model was used to further evaluate the meteorological effects of these changes. The lower boundary conditions for this mesoscale model were generated for two selected time periods (for 1900 and 2000) based on the reconstructed maps. The dynamic model has been run with the same detailed meteorological conditions of selected days from 2006 and 2007, but with modified lower boundary conditions. The set of the 26 selected initial conditions represents the whole set of the macrosynoptic situations for Hungary. In this way, 2×26 "forecasts" were made with 48 hours of integration. The effects of land cover changes under different weather situations were further weighted by the long-term (1961-1990) mean frequency of the corresponding macrosynoptic types, to assume the climatic effects from these stratified averages. The detailed evaluation of the model results were made for three different meteorological

  20. 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.

  1. Optimum land cover products for use in a Glossina-morsitans habitat model of Kenya

    Directory of Open Access Journals (Sweden)

    Messina Joseph P

    2009-06-01

    Full Text Available Abstract Background Tsetse flies are the primary vector for African trypanosomiasis, a disease that affects both humans and livestock across the continent of Africa. In 1973 tsetse flies were estimated to inhabit 22% of Kenya; by 1996 that number had risen to roughly 34%. Efforts to control the disease were hampered by a lack of information and costs associated with the identification of infested areas. Given changing spatial and demographic factors, a model that can predict suitable tsetse fly habitat based on land cover and climate change is critical to efforts aimed at controlling the disease. In this paper we present a generalizable method, using a modified Mapcurves goodness of fit test, to evaluate the existing publicly available land cover products to determine which products perform the best at identifying suitable tsetse fly land cover. Results For single date applications, Africover was determined to be the best land use land cover (LULC product for tsetse modeling. However, for changing habitats, whether climatically or anthropogenically forced, the IGBP DISCover and MODIS type 1 products where determined to be most practical. Conclusion The method can be used to differentiate between various LULC products and be applied to any such research when there is a known relationship between a species and land cover.

  2. Statistical sampling to characterize recent United States land-cover change

    Science.gov (United States)

    Stehman, S.V.; Sohl, Terry L.; Loveland, Thomas R.

    2003-01-01

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

  3.   Quantitative reconstruction of past land cover in Denmark - The first results

    DEFF Research Database (Denmark)

    Nielsen, Anne Birgitte; Odgaard, Bent Vad

      Pollen data are traditionally used as qualitative reflections of past vegetation cover dynamics. Such uses are based on a number of assumptions which can be shown not to be universally valid. For example, the assumption that a change in percentage frequency of a pollen type between two levels...... 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...

  4. Comparing Minnesota land cover/use area estimates using NRI and FIA data

    Science.gov (United States)

    Veronica C. Lessard; Mark H. Hansen; Mark D. Nelson

    2002-01-01

    Areas for land cover/use categories on non-Federal land in Minnesota were estimated from Forest Inventory and Analysis (FIA) data and National Resources Inventory (NRI) data. Six common land cover/use categories were defined, and the NRI and FIA land cover/use categories were assigned to them. Area estimates for these categories were calculated from the FIA and NRI...

  5. 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 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.

  6. 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

  7. Land Use and Land Cover Change in Forest Frontiers: The Role of Household Life Cycles

    Science.gov (United States)

    Walker, Robert

    2002-01-01

    Tropical deforestation remains a critical issue given its present rate and a widespread consensus regarding its implications for the global carbon cycle and biodiversity. Nowhere is the problem more pronounced than in the Amazon basin, home to the world's largest intact, tropical forest. This article addresses land cover change processes at household level in the Amazon basin, and to this end adapts a concept of domestic life cycle to the current institutional environment of tropical frontiers. In particular, it poses a risk minimization model that integrates demography with market-based factors such as transportation costs and accessibility. In essence, the article merges the theory of Chayanov with the household economy framework, in which markets exist for inputs (including labor), outputs, and capital. The risk model is specified and estimated, using survey data for 261 small producers along the Transamazon Highway in the eastern sector of the Brazilian Amazon.

  8. Monitoring land use/land cover changes using CORINE land cover data: a case study of Silivri coastal zone in Metropolitan Istanbul.

    Science.gov (United States)

    Yilmaz, Rüya

    2010-06-01

    The objective of the present study was to assess changes in land use/land cover patterns in the coastal town of Silivri, a part of greater Istanbul administratively. In the assessment, remotely sensed data, in the form of satellite images, and geographic information systems were used. Types of land use/land cover were designated as the percentage of the total area studied. Results calculated from the satellite data for land cover classification were compared successfully with the database Coordination of Information on the Environment (CORINE). This served as a reference to appraise the reliability of the study presented here. The CORINE Program was established by the European Commission to create a harmonized Geographical Information System on the state of the environment in the European Community. Unplanned urbanization is causing land use changes mainly in developing countries such as Turkey. This situation in Turkey is frequently observed in the city of Istanbul. There are only a few studies of land use-land cover changes which provide an integrated assessment of the biophysical and societal causes and consequences of environmental degradation in Istanbul. The research area comprised greater Silivri Town which is situated by the coast of Marmara Sea, and it is located approximately 60 km west of Istanbul. The city of Istanbul is one of the largest metropolises in Europe with ca. 15 million inhabitants. Additionally, greater Silivri is located near the terminal point of the state highway connecting Istanbul with Europe. Measuring of changes occurring in land use would help control future planning of settlements; hence, it is of importance for the Greater Silivri and Silivri Town. Following our evaluations, coastal zone of Silivri was classified into the land use groups of artificial surfaces agricultural areas and forests and seminatural areas with 47.1%, 12.66%, and 22.62%, respectively.

  9. Consequences of Uncertainty in Global-Scale Land Cover Maps for Mapping Ecosystem Functions: An Analysis of Pollination Efficiency

    Directory of Open Access Journals (Sweden)

    Rob Alkemade

    2011-09-01

    Full Text Available Mapping ecosystem services (ESs is an important tool for providing the quantitative information necessary for the optimal use and protection of ecosystems and biodiversity. A common mapping approach is to apply established empirical relationships to ecosystem property maps. Often, ecosystem properties that provide services to humanity are strongly related to the land use and land cover, where the spatial allocation of the land cover in the landscape is especially important. Land use and land cover maps are, therefore, essential for ES mapping. However, insight into the uncertainties in land cover maps and how these propagate into ES maps is lacking. To analyze the effects of these uncertainties, we mapped pollination efficiency as an example of an ecosystem function, using two continental-scale land cover maps and two global-scale land cover maps. We compared the outputs with maps based on a detailed national-scale map. The ecosystem properties and functions could be mapped using the GLOBCOVER map with a reasonable to good accuracy. In homogeneous landscapes, an even coarser resolution map would suffice. For mapping ESs that depend on the spatial allocation of land cover in the landscape, a classification of satellite images using fractional land cover or mosaic classes is an asset.

  10. Scenario-Based Impact Assessment of Land Use/Cover and Climate Changes on Watershed Hydrology in Heihe River Basin of Northwest China

    Directory of Open Access Journals (Sweden)

    Feng Wu

    2015-01-01

    Full Text Available This study evaluated hydrological impacts of potential climate and land use changes in Heihe River Basin of Northwest China. The future climate data for the simulation with Soil and Water Assessment Tool (SWAT were prepared using a dynamical downscaling method. The future land uses were simulated with the Dynamic Land Use System (DLS model by establishing Multinomial Logistic Regression (MNL model for six land use types. In 2006–2030, land uses in the basin will experience a significant change with a prominent increase in urban areas, a moderate increase in grassland, and a great decrease in unused land. Besides, the simulation results showed that in comparison to those during 1981–2005 the temperature and precipitation during 2006–2030 will change by +0.8°C and +10.8%, respectively. The land use change and climate change will jointly make the water yield change by +8.5%, while they will separately make the water yield change by −1.8% and +9.8%, respectively. The predicted large increase in future precipitation and the corresponding decrease in unused land will have substantial impacts on the watershed hydrology, especially on the surface runoff and streamflow. Therefore, to mitigate negative hydrological impacts and utilize positive impacts, both land use and climate changes should be considered in water resource planning for the Heihe River Basin.

  11. 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-based

  12. Temporal change detection of land use/land cover using GIS and ...

    African Journals Online (AJOL)

    Temporal change detection of land use/land cover using GIS and remote sensing techniques in South Ghor Regions, Al-Karak, Jordan. M Abu Ghurah, M.K.A. Kamarudin, N.A. Wahab, R Umar, N.A.F. Nik Wan, H Juahir, M.B. Gasim, A.R. Hassan, F Lananan, A.F. Ireana Yusra, Sunardi Sunardi, Y Hidayat ...

  13. Simulating land-cover change in Montane mainland southeast Asia.

    Science.gov (United States)

    Fox, Jefferson; Vogler, John B; Sen, Omer L; Giambelluca, Thomas W; Ziegler, Alan D

    2012-05-01

    We used the conversion of land use and its effects (CLUE-s) model to simulate scenarios of land-cover change in Montane mainland southeast Asia (MMSEA), a region in the midst of transformation due to rapid intensification of agriculture and expansion of regional trade markets. Simulated changes affected approximately 10 % of the MMSEA landscape between 2001 and 2025 and 16 % between 2001 and 2050. Roughly 9 % of the current vegetation, which consists of native species of trees, shrubs, and grasses, is projected to be replaced by tree plantations, tea, and other evergreen shrubs during the 50 years period. Importantly, 4 % of this transition is expected to be due to the expansion of rubber (Hevea brasiliensis), a tree plantation crop that may have important implications for local-to-regional scale hydrology because of its potentially high water consumption in the dry season.

  14. 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

  15. 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

  16. Estimating ground water recharge from topography, hydrogeology, and land cover.

    Science.gov (United States)

    Cherkauer, Douglas S; Ansari, Sajjad A

    2005-01-01

    Proper management of ground water resources requires knowledge of the rates and spatial distribution of recharge to aquifers. This information is needed at scales ranging from that of individual communities to regional. This paper presents a methodology to calculate recharge from readily available ground surface information without long-term monitoring. The method is viewed as providing a reasonable, but conservative, first approximation of recharge, which can then be fine-tuned with other methods as time permits. Stream baseflow was measured as a surrogate for recharge in small watersheds in southeastern Wisconsin. It is equated to recharge (R) and then normalized to observed annual precipitation (P). Regression analysis was constrained by requiring that the independent and dependent variables be dimensionally consistent. It shows that R/P is controlled by three dimensionless ratios: (1) infiltrating to overland water flux, (2) vertical to lateral distance water must travel, and (3) percentage of land cover in the natural state. The individual watershed properties that comprise these ratios are now commonly available in GIS data bases. The empirical relationship for predicting R/P developed for the study watersheds is shown to be statistically viable and is then tested outside the study area and against other methods of calculating recharge. The method produces values that agree with baseflow separation from streamflow hydrographs (to within 15% to 20%), ground water budget analysis (4%), well hydrograph analysis (12%), and a distributed-parameter watershed model calibrated to total streamflow (18%). It has also reproduced the temporal variation over 5 yr observed at a well site with an average error < 12%.

  17. 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

  18. Obtaining land-use information from a remotely sensed land cover map: results from a case study in Lebanon

    Science.gov (United States)

    Jansen, Louisa J. M.; Di Gregorio, Antonio

    2004-05-01

    The availability of land-use information allows decision-makers to develop short to long-term plans for the conservation, sustainable use and development of natural resources. Spatial land-use information often does not exist, whereas land cover information is mostly present in the form of maps derived from remotely sensed data. The latter could provide a basis for obtaining land-use information but there is currently no comprehensive methodology for how to obtain such information in a standardised manner. In Lebanon, with its wide variety of land cover types due to the diversity in landforms and variability in rainfall, a case study was carried out to try to develop a set of decision rules to obtain the dominant land uses from the existing 1:50,000-scale land cover maps. The development of the decision rules to allow such a transformation brought several problems to light concerning spatial and temporal variation of land cover, the accuracy of the input materials, the limitations of the developed decision rules and the complexity of the relation between land cover and land use. The decision rules were also analysed as to their general applicability for acquisition of land-use information and the implications for field survey data collection. Furthermore, quantification of the land cover and land-use classes allowed the examination of the nature of the land cover/use relationships in Lebanon. In addition, these data were compared to the FAO Production Yearbook statistics in order to link annual production estimates with the extent of land involved in the production of commodities. This comparison underlines the complexity of deducing land-use information from land cover data, especially where the land cover/land-use relation is weak and additional data is limited. Assumptions used to identify the spatial extent of certain land uses need to be thoroughly tested in the field for their validity as this is vital in obtaining reliable land-use information.

  19. Land Use and Land Cover - Volusia County Future Land Use (FLU) 2010

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Volusia County Future Land Use 2010. This is the original land use map for 2010. It was drafted for the comprehensive plan in 1990 and contains adopted amendments.

  20. 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

  1. A land-use and land-cover modeling strategy to support a national assessment of carbon stocks and fluxes

    Science.gov (United States)

    Sohl, Terry L.; Sleeter, Benjamin M.; Zhu, Zhi-Liang; Sayler, Kristi L.; Bennett, Stacie; Bouchard, Michelle; Reker, Ryan R.; Hawbaker, Todd; Wein, Anne; Liu, Shu-Guang; Kanengieter, Ronald; Acevedo, William

    2012-01-01

    Changes in land use, land cover, disturbance regimes, and land management have considerable influence on carbon and greenhouse gas (GHG) fluxes within ecosystems. Through targeted land-use and land-management activities, ecosystems can be managed to enhance carbon sequestration and mitigate fluxes of other GHGs. National-scale, comprehensive analyses of carbon sequestration potential by ecosystem are needed, with a consistent, nationally applicable land-use and land-cover (LULC) modeling framework a key component of such analyses. The U.S. Geological Survey has initiated a project to analyze current and projected future GHG fluxes by ecosystem and quantify potential mitigation strategies. We have developed a unique LULC modeling framework to support this work. Downscaled scenarios consistent with IPCC Special Report on Emissions Scenarios (SRES) were constructed for U.S. ecoregions, and the FORE-SCE model was used to spatially map the scenarios. Results for a prototype demonstrate our ability to model LULC change and inform a biogeochemical modeling framework for analysis of subsequent GHG fluxes. The methodology was then successfully used to model LULC change for four IPCC SRES scenarios for an ecoregion in the Great Plains. The scenario-based LULC projections are now being used to analyze potential GHG impacts of LULC change across the U.S.

  2. Investigating the Impact of Land between the Lakes (LBL) and Land Use/Land Cover Change on Precipitation Patterns

    Science.gov (United States)

    Degu, A. M.; Hossain, F.

    2012-12-01

    Large dams/reservoirs as open water surface and as a mechanism of triggering land use/land cover changes in their vicinity have impacted local climate and extreme precipitation patterns as study show. Urbanization, agricultural development, and forestation are some of the Land Use/Land Cover Changes (LULCC) that are result of development of large dams/reservoirs. Thus creating heterogeneities. It is believed that such heterogeneities bring about a boundary of different air masses that triggers convection due to differential heating as well as variation in soil moisture. One such heterogeneities is of the Land Between the Lakes (LBL). LBL is an inland peninsula formed by Lake Kentucky on Tennessee River and Lake Barkley on Cumberland River in Western Kentucky. The development of the two lakes brought about an area of 680 sq.km forest cover. The LBL renders unique land use/land cover heterogeneities with in a shorter distance providing open water for evaporation and forest for evapotranspiration. Reports as well as a preliminary investigation of nearby weather radar data showed storms dying out as it approaches the inland peninsula and gaining strength east of LBL. The storm exhibits a wave like strength, attenuating before LBL and gaining strength after. The purpose of this study mainly is to investigate the impact of LBL and in general LULCC on precipitation in the area. In this study the following specific scientific question will be addressed a. Has the development of LBL modified precipitation in the region? b. Which LULCC predominately affects storm formation? Summer radar reflectivity data from Paducah, KY station along with North America Regional Reanalysis (NARR) geopotential height and wind direction data will be analyzed for identification of LBL effect precipitation and synoptic effect precipitation, respectively. A Weather Research and Forecasting Model (WRF) will be setup to investigate what land use/land cover predominately modifies precipitation in

  3. Analysis of spatial distribution of land cover maps accuracy

    Science.gov (United States)

    Khatami, R.; Mountrakis, G.; Stehman, S. V.

    2017-12-01

    Land cover maps have become one of the most important products of remote sensing science. However, classification errors will exist in any classified map and affect the reliability of subsequent map usage. Moreover, classification accuracy often varies over different regions of a classified map. These variations of accuracy will affect the reliability of subsequent analyses of different regions based on the classified maps. The traditional approach of map accuracy assessment based on an error matrix does not capture the spatial variation in classification accuracy. Here, per-pixel accuracy prediction methods are proposed based on interpolating accuracy values from a test sample to produce wall-to-wall accuracy maps. Different accuracy prediction methods were developed based on four factors: predictive domain (spatial versus spectral), interpolation function (constant, linear, Gaussian, and logistic), incorporation of class information (interpolating each class separately versus grouping them together), and sample size. Incorporation of spectral domain as explanatory feature spaces of classification accuracy interpolation was done for the first time in this research. Performance of the prediction methods was evaluated using 26 test blocks, with 10 km × 10 km dimensions, dispersed throughout the United States. The performance of the predictions was evaluated using the area under the curve (AUC) of the receiver operating characteristic. Relative to existing accuracy prediction methods, our proposed methods resulted in improvements of AUC of 0.15 or greater. Evaluation of the four factors comprising the accuracy prediction methods demonstrated that: i) interpolations should be done separately for each class instead of grouping all classes together; ii) if an all-classes approach is used, the spectral domain will result in substantially greater AUC than the spatial domain; iii) for the smaller sample size and per-class predictions, the spectral and spatial domain

  4. Monitoring Urban Land Cover/land Use Change in Algiers City Using Landsat Images (1987-2016)

    Science.gov (United States)

    Bouchachi, B.; Zhong, Y.

    2017-09-01

    Monitoring the Urban Land Cover/Land Use change detection is important as one of the main driving forces of environmental change because Urbanization is the biggest changes in form of Land, resulting in a decrease in cultivated areas. Using remote sensing ability to solve land resources problems. The purpose of this research is to map the urban areas at different times to monitor and predict possible urban changes, were studied the annual growth urban land during the last 29 years in Algiers City. Improving the productiveness of long-term training in land mapping, were have developed an approach by the following steps: 1) pre-processing for improvement of image characteristics; 2) extract training sample candidates based on the developed methods; and 3) Derive maps and analyzed of Algiers City on an annual basis from 1987 to 2016 using a Supervised Classifier Support Vector Machine (SVMs). Our result shows that the strategy of urban land followed in the region of Algiers City, developed areas mostly were extended to East, West, and South of Central Regions. The urban growth rate is linked with National Office of Statistics data. Future studies are required to understand the impact of urban rapid lands on social, economy and environmental sustainability, it will also close the gap in data of urbanism available, especially on the lack of reliable data, environmental and urban planning for each municipality in Algiers, develop experimental models to predict future land changes with statistically significant confidence.

  5. Regional Deforestation Trends within Local Realities: Land-Cover Change in Southeastern Peru 1996–2011

    Directory of Open Access Journals (Sweden)

    Andrea Chávez Michaelsen

    2013-04-01

    Full Text Available Estimating deforested areas and deforestation rates have become key steps for quantifying environmental services of tropical rain forests, particularly as linked to programs such as Reduced Emissions from Deforestation and Forest Degradation (REDD. In Southeastern Peru, reliable estimates of land-cover change (LCC are important for monitoring changes in the landscape due to agricultural expansion, pasture creation and other socio-economic influences triggered by the Inter-Oceanic Highway (IOH. Our study reports a land-use/land-cover change (LULCC analysis during a 15-year period from 1996 to 2011 in the Province of Tahuamanu, Madre de Dios. We draw on multiple years of observations of LULCC to relate changes in land cover to the use of natural resources (pasture, timber, crops and forest products and tenure types based on their distances from the highway and the Tahuamanu River. We are able to distinguish titled areas for agriculture close to the IOH from other land tenure types such as timber concessions. The findings show that LULCC varies among different types of land tenure and by distance from the highway. Agricultural areas close to transportation infrastructure within 1 km to 5 km buffers have gradually increased in non-forest areas, whereas timber concession areas away from 1 km buffer of secondary roads have maintained forest cover. Riverine settlements show a similar distance effect in forest clearance along rivers as along roads.

  6. 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.

  7. Land cover, land use changes and air pollution in Asia: a synthesis

    Science.gov (United States)

    Vadrevu, Krishna; Ohara, Toshimasa; Justice, Chris

    2017-12-01

    A better understanding of land cover/land use changes (LCLUC) and their interactions with the atmospheric environment is essential for the sustainable management of natural resources, environmental protection, air quality, agricultural planning and food security. The 15 papers published in this focus issue showcase a variety of studies relating to drivers and impacts of LCLUC and air pollution in different South/Southeast Asian (S/SEA) countries. This synthesis article, in addition to giving context to the articles in this focus issue, also reviews the broad linkages between population, LCLUC and air pollution. Additionally, we identify knowledge gaps and research priorities that are essential in addressing air pollution issues in the region. We conclude that for effective pollution mitigation in S/SEA countries, quantifying drivers, sources and impacts of pollution need a thorough data analysis through ground-based instrumentation, models and integrated research approaches. We also stress the need for the development of sustainable technologies and strengthening the scientific and resource management communities through capacity building and training activities to address air pollution issues in S/SEA countries.

  8. Land-Use and Land Cover Dynamics in South American Temperate Grasslands

    Directory of Open Access Journals (Sweden)

    Germán Baldi

    2008-12-01

    Full Text Available In the Río de la Plata grasslands (RPG biogeographical region of South America, agricultural activities have undergone important changes during the last 15-18 years because of technological improvements and new national and international market conditions. We characterized changes in the landscape structure between 1985-1989 and 2002-2004 for eight pilot areas distributed across the main regional environmental gradients. These areas incorporated approximately 35% of the 7.5 à - 105 km² of the system. Our approach involved the generation of land-use and land cover maps, the analysis of landscape metrics, and the computation of annual transition probabilities between land cover types. All of the information was summarized in 3383 cells of 8 à - 8 km. The area covered by grassland decreased from 67.4 to 61.4% between the study periods. This decrease was associated with an increase in the area of annual crops, mainly soybean, sunflower, wheat, and maize. In some subunits of the RPG, i.e., Flat Inland Pampa, the grassland-to-cropland transition probability was high (pGâ†'C = 3.7 à - 10âˆ'2, whereas in others, i.e., Flooding Pampa, this transition probability was low (pGâ†'C = 6.7 à - 10âˆ'3. Our description of the magnitude, direction, and spatial distribution of land-use and land cover changes provides a basis from which to develop spatially explicit scenarios of land cover change.

  9. Land Cover Influence on Wet Season Storm Runoff Generation and Hydrologic Flowpaths in Central Panama

    Science.gov (United States)

    Birch, A. L.; Stallard, R. F.; Barnard, H. R.

    2017-12-01

    While relationships between land use/land cover and hydrology are well studied and understood in temperate parts of the world, little research exists in the humid tropics, where hydrologic research is often decades behind. Specifically, quantitative information on how physical and biological differences across varying land covers influence runoff generation and hydrologic flowpaths in the humid tropics is scarce; frequently leading to poorly informed hydrologic modelling and water policy decision making. This research effort seeks to quantify how tropical land cover change may alter physical hydrologic processes in the economically important Panama Canal Watershed (Republic of Panama) by separating streamflow into its different runoff components using end member mixing analysis. The samples collected for this project come from small headwater catchments of four varying land covers (mature tropical forest, young secondary forest, active pasture, recently clear-cut tropical forest) within the Smithsonian Tropical Research Institute's Agua Salud Project. During the past three years, samples have been collected at the four study catchments from streamflow and from a number of water sources within hillslope transects, and have been analyzed for stable water isotopes, major cations, and major anions. Major ion analysis of these samples has shown distinct geochemical differences for the potential runoff generating end members sampled (soil moisture/ preferential flow, groundwater, overland flow, throughfall, and precipitation). Based on this finding, an effort was made from May-August 2017 to intensively sample streamflow during wet season storm events, yielding a total of 5 events of varying intensity in each land cover/catchment, with sampling intensity ranging from sub-hourly to sub-daily. The focus of this poster presentation will be to present the result of hydrograph separation's done using end member mixing analysis from this May-August 2017 storm dataset. Expected

  10. 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

    This document summarizes the major findings of a Gulf of Mexico Application Pilot project led by NASA Stennis Space Center (SSC) in conjunction with a regional collaboration network of the Gulf of Mexico Alliance (GOMA). NASA researchers processed and analyzed multi-temporal Landsat data to assess land-use and land-cover (LULC) changes in the coastal counties of Mobile and Baldwin, AL between 1974 and 2008. Our goal was to create satellite-based LULC data products using methods that could be transferable to other coastal areas of concern within the Gulf of Mexico. The Mobile Bay National Estuary Program (MBNEP) is the primary end-user, however, several other state and local groups may benefit from the project s data products that will be available through NOAA-NCDDC s Regional Ecosystem Data Management program. Mobile Bay is a critical ecologic and economic region in the Gulf of Mexico and to the entire country. Mobile Bay was designated as an estuary of national significance in 1996. This estuary receives the fourth largest freshwater inflow in the United States. It provides vital nursery habitat for commercially and recreationally important fish species. It has exceptional aquatic and terrestrial bio-diversity, however, its estuary health is influenced by changing LULC patterns, such as urbanization. Mobile and Baldwin counties have experienced a population growth of 1.1% and 20.5% from 2000-2006. Urban expansion and population growth are likely to accelerate with the construction and operation of the ThyssenKrupp steel mill in the northeast portion of Mobile County. Land-use and land-cover change can negatively impact Gulf coast water quality and ecological resources. The conversion of forest to urban cover types impacts the carbon cycle and increases the freshwater and sediment in coastal waters. Increased freshwater runoff decreases salinity and increases the turbidity of coastal waters, thus impacting the growth potential of submerged aquatic vegetation (SAV

  11. A change detection strategy for monitoring vegetative and land-use cover types using remotely-sensed, satellite-based data

    International Nuclear Information System (INIS)

    Hallum, C.

    1993-01-01

    Changes to the environment are of critical concern in the world today; consequently, monitoring such changes and assessing their impacts are tasks demanding considerably higher priority. The ecological impacts of the natural global cycles of gases and particulates in the earth's atmosphere are highly influenced by the extent of changes to vegetative canopy characteristics which dictates the need for capability to detect and assess the magnitude of such changes. The primary emphasis of this paper is on the determination of the size and configuration of the sampling unit that maximizes the probability of its intersection with a 'change' area. Assessment of the significance of the 'change' in a given locality is also addressed and relies on a statistical approach that compares the number of elemental units exceeding a reflectance threshold when compared to a previous point in time. Consideration is also given to a technical framework that supports quantifying the magnitude of the 'change' over large areas (i.e., the estimated area changing from forest to agricultural land-use). The latter entails a multistage approach which utilizes satellite-based and other related data sources

  12. Land cover change and plants diversity in the Sahel: A case study from northern Burkina Faso

    Directory of Open Access Journals (Sweden)

    Abel Kadeba

    2015-04-01

    Full Text Available Understanding land cover degradation patterns and the effects of geomorphological units on phytodiversity is important for guiding management decisions and restoration strategies in the Sahelian vulnerables zones. This paper describes land cover degradation by combining Landsat TM image analysis and field data measurements in the Gourouol catchment of the Sahelian zone of Burkina Faso. Erdas Imagine 9.2 and Arc-GIS.10 were applied. The change patterns were obtained by superposing land cover maps for 1992 and 2010. The field data were collected by the mean of inventories according to the Braun-Blanquet phytosociological relevés methods. Plot sizes were 50 m x 20 m for woody species and 10 m x 10 m for herbaceous species. Six land cover types were identified and mapped: cultivated lands, bared lands, lowlands, which all spatially increased; and shrub-steppes, grasslands and water bodies, which all spatially decreased. The dynamic patterns based on the geomorphological units were non-degraded lowlands, stable sand dunes and degraded glacis. High plant diversity was found in lowlands, whereas low diversity occurred in glacis. A significant dissimilarity was observed between communities. The Shannon diversity indices in plant communities were approximately close to ln(species richness. The Pielou indices were close to 1, indicating a species fairly good distribution. Our results showed a variation of land cover over time and the effects of geomorphological units on phytodiversity. Furthermore, this variation helps oppose land degradation in the Sahel.

  13. Land cover change in Colombia: surprising forest recovery trends between 2001 and 2010.

    Directory of Open Access Journals (Sweden)

    Ana María Sánchez-Cuervo

    Full Text Available BACKGROUND: Monitoring land change at multiple spatial scales is essential for identifying hotspots of change, and for developing and implementing policies for conserving biodiversity and habitats. In the high diversity country of Colombia, these types of analyses are difficult because there is no consistent wall-to-wall, multi-temporal dataset for land-use and land-cover change. METHODOLOGY/PRINCIPAL FINDINGS: To address this problem, we mapped annual land-use and land-cover from 2001 to 2010 in Colombia using MODIS (250 m products coupled with reference data from high spatial resolution imagery (QuickBird in Google Earth. We used QuickBird imagery to visually interpret percent cover of eight land cover classes used for classifier training and accuracy assessment. Based on these maps we evaluated land cover change at four spatial scales country, biome, ecoregion, and municipality. Of the 1,117 municipalities, 820 had a net gain in woody vegetation (28,092 km(2 while 264 had a net loss (11,129 km(2, which resulted in a net gain of 16,963 km(2 in woody vegetation at the national scale. Woody regrowth mainly occurred in areas previously classified as mixed woody/plantation rather than agriculture/herbaceous. The majority of this gain occurred in the Moist Forest biome, within the montane forest ecoregions, while the greatest loss of woody vegetation occurred in the Llanos and Apure-Villavicencio ecoregions. CONCLUSIONS: The unexpected forest recovery trend, particularly in the Andes, provides an opportunity to expand current protected areas and to promote habitat connectivity. Furthermore, ecoregions with intense land conversion (e.g. Northern Andean Páramo and ecoregions under-represented in the protected area network (e.g. Llanos, Apure-Villavicencio Dry forest, and Magdalena-Urabá Moist forest ecoregions should be considered for new protected areas.

  14. Data Mining Relationships Among Urban Socioeconomic, Land Cover, and Remotely Sensed Ecological Data

    Science.gov (United States)

    Mennis, J.; Wessman, C.; Golubiewski, N.

    2003-12-01

    This research investigates the relationships among socioeconomic character, land cover, and ecological function in a rapidly urbanizing region, the Front Range of Colorado. We use novel spatial geographic information systems- (GIS-) based data integration and data mining techniques to integrate and analyze diverse spatial data sets. These data include elevation data, transportation data, land cover data derived from aerial photography, block group-level U.S. Census data, and vegetation greenness (NDVI) data derived from Landsat imagery. These data are used to derive a variety of U.S. block group-level variables indicating demographic, geographic, ecological, and land cover characteristics. We employ spatial association rule mining, decision tree induction, and spatial on-line analytical processing (OLAP), in addition to more conventional multivariate statistical techniques, to investigate relationships among these variables.

  15. 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...

  16. 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...

  17. ISLSCP II MODIS (Collection 4) IGBP Land Cover, 2000-2001

    Data.gov (United States)

    National Aeronautics and Space Administration — The objective of the MODIS Land Cover Product is to provide a suite of land cover types useful to global system science modelers by exploiting the information...

  18. ISLSCP II MODIS (Collection 4) IGBP Land Cover, 2000-2001

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: The objective of the MODIS Land Cover Product is to provide a suite of land cover types useful to global system science modelers by exploiting the...

  19. 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...

  20. LBA-ECO LC-22 Land Cover from MODIS Vegetation Indices, Mato Grosso, Brazil

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set, LBA-ECO LC-22 Land Cover from MODIS Vegetation Indices, Mato Grosso, Brazil, provides land cover classifications for Mato Grosso, Brazil, for the...

  1. 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...

  2. 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...

  3. 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.

  4. A comprehensive change detection method for updating the National Land Cover Database to circa 2011

    Science.gov (United States)

    Jin, Suming; Yang, Limin; Danielson, Patrick; Homer, Collin G.; Fry, Joyce; Xian, George

    2013-01-01

    The importance of characterizing, quantifying, and monitoring land cover, land use, and their changes has been widely recognized by global and environmental change studies. Since the early 1990s, three U.S. National Land Cover Database (NLCD) products (circa 1992, 2001, and 2006) have been released as free downloads for users. The NLCD 2006 also provides land cover change products between 2001 and 2006. To continue providing updated national land cover and change datasets, a new initiative in developing NLCD 2011 is currently underway. We present a new Comprehensive Change Detection Method (CCDM) designed as a key component for the development of NLCD 2011 and the research results from two exemplar studies. The CCDM integrates spectral-based change detection algorithms including a Multi-Index Integrated Change Analysis (MIICA) model and a novel change model called Zone, which extracts change information from two Landsat image pairs. The MIICA model is the core module of the change detection strategy and uses four spectral indices (CV, RCVMAX, dNBR, and dNDVI) to obtain the changes that occurred between two image dates. The CCDM also includes a knowledge-based system, which uses critical information on historical and current land cover conditions and trends and the likelihood of land cover change, to combine the changes from MIICA and Zone. For NLCD 2011, the improved and enhanced change products obtained from the CCDM provide critical information on location, magnitude, and direction of potential change areas and serve as a basis for further characterizing land cover changes for the nation. An accuracy assessment from the two study areas show 100% agreement between CCDM mapped no-change class with reference dataset, and 18% and 82% disagreement for the change class for WRS path/row p22r39 and p33r33, respectively. The strength of the CCDM is that the method is simple, easy to operate, widely applicable, and capable of capturing a variety of natural and

  5. 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 ...

  6. 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 ...

  7. 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.

  8. An Operational Framework for Land Cover Classification in the Context of REDD+ Mechanisms. A Case Study from Costa Rica

    Directory of Open Access Journals (Sweden)

    Alfredo Fernández-Landa

    2016-07-01

    Full Text Available REDD+ implementation requires robust, consistent, accurate and transparent national land cover historical data and monitoring systems. Satellite imagery is the only data source with enough periodicity to provide consistent land cover information in a cost-effective way. The main aim of this paper is the creation of an operational framework for monitoring land cover dynamics based on Landsat imagery and open-source software. The methodology integrates the entire land cover and land cover change mapping processes to produce a consistent series of Land Cover maps. The consistency of the time series is achieved through the application of a single trained machine learning algorithm to radiometrically normalized imagery using iteratively re-weighted multivariate alteration detection (IR-MAD across all dates of the historical period. As a result, seven individual Land Cover maps of Costa Rica were produced from 1985/1986 to 2013/2014. Post-classification land cover change detection was performed to evaluate the land cover dynamics in Costa Rica. The validation of the land cover maps showed an overall accuracy of 87% for the 2013/2014 map, 93% for the 2000/2001 map and 89% for the 1985/1986 map. Land cover changes between forest and non-forest classes were validated for the period between 2001 and 2011, obtaining an overall accuracy of 86%. Forest age-classes were generated through a multi-temporal analysis of the maps. By linking deforestation dynamics with forest age, a more accurate discussion of the carbon emissions along the time series can be presented.

  9. Collect Earth: Land Use and Land Cover Assessment through Augmented Visual Interpretation

    Directory of Open Access Journals (Sweden)

    Adia Bey

    2016-09-01

    Full Text Available Collect Earth is a free and open source software for land monitoring developed by the Food and Agriculture Organization of the United Nations (FAO. Built on Google desktop and cloud computing technologies, Collect Earth facilitates access to multiple freely available archives of satellite imagery, including archives with very high spatial resolution imagery (Google Earth, Bing Maps and those with very high temporal resolution imagery (e.g., Google Earth Engine, Google Earth Engine Code Editor. Collectively, these archives offer free access to an unparalleled amount of information on current and past land dynamics for any location in the world. Collect Earth draws upon these archives and the synergies of imagery of multiple resolutions to enable an innovative method for land monitoring that we present here: augmented visual interpretation. In this study, we provide a full overview of Collect Earth’s structure and functionality, and we present the methodology used to undertake land monitoring through augmented visual interpretation. To illustrate the application of the tool and its customization potential, an example of land monitoring in Papua New Guinea (PNG is presented. The PNG example demonstrates that Collect Earth is a comprehensive and user-friendly tool for land monitoring and that it has the potential to be used to assess land use, land use change, natural disasters, sustainable management of scarce resources and ecosystem functioning. By enabling non-remote sensing experts to assess more than 100 sites per day, we believe that Collect Earth can be used to rapidly and sustainably build capacity for land monitoring and to substantively improve our collective understanding of the world’s land use and land cover.

  10. High-Precision Land-Cover-Land-Use GIS Mapping and Land Availability and Suitability Analysis for Grass Biomass Production in the Aroostook River Valley, Maine, USA

    Directory of Open Access Journals (Sweden)

    Chunzeng Wang

    2015-03-01

    Full Text Available High-precision land-cover-land-use GIS mapping was performed in four major townships in Maine’s Aroostook River Valley, using on-screen digitization and direct interpretation of very high spatial resolution satellite multispectral imagery (15–60 cm and high spatial resolution LiDAR data (2 m and the field mapping method. The project not only provides the first-ever high-precision land-use maps for northern Maine, but it also yields accurate hectarage estimates of different land-use types, in particular grassland, defined as fallow land, pasture, and hay field. This enables analysis of potential land availability and suitability for grass biomass production and other sustainable land uses. The results show that the total area of fallow land in the four towns is 7594 hectares, which accounts for 25% of total open land, and that fallow plots equal to or over four hectares in size total 4870, or 16% of open land. Union overlay analysis, using the Natural Resources Conservation Service (NRCS soil data, indicates that only a very small percentage of grassland (4.9% is on “poorly-drained” or “very-poorly-drained” soils, and that most grassland (85% falls into the “farmland of state importance” or “prime farmland” categories, as determined by NRCS. It is concluded that Maine’s Aroostook River Valley has an ample base of suitable, underutilized land for producing grass biomass.

  11. Rapid land cover map updates using change detection and robust random forest classifiers

    CSIR Research Space (South Africa)

    Wessels, Konrad J

    2016-01-01

    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...

  12. 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...

  13. 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 ...

  14. Air photo evidence of historical land cover change in the highlands ...

    African Journals Online (AJOL)

    These land covers, which are dispersed along the fine - grained dendritic stream network, are habitat for crayfish, frogs, and other fauna, yet are also prized locations in the rice - based Malagasy agricultural system. The results of this study suggest that attention be given to highland grassland, wetland and riparian forest ...

  15. HYDROLOGIC MODEL UNCERTAINTY ASSOCIATED WITH SIMULATING FUTURE LAND-COVER/USE SCENARIOS: A RETROSPECTIVE ANALYSIS

    Science.gov (United States)

    GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...

  16. Spatiotemporal Variability of Carbon Flux from Different Land Use and Land Cover Changes: A Case Study in Hubei Province, China

    Directory of Open Access Journals (Sweden)

    Li Gao

    2014-04-01

    Full Text Available Carbon sources and sinks as a result of land use and land cover changes (LUCC are significant for global climate change. This paper aims to identify and analyze the temporal and spatial changes of land use-based carbon emission in the Hubei Province in China. We use a carbon emission coefficient to calculate carbon emissions in different land use patterns in Hubei Province from 1998 to 2009. The results indicate that regional land use is facing tremendous pressure from rapid carbon emission growth. Source:sink ratios and average carbon emission intensity values of urban land are increasing, while slow-growing carbon sinks fail to offset the rapidly expanding carbon sources. Overall, urban land carbon emissions have a strong correlation with the total carbon emissions, and will continue to increase in the future mainly due to the surge of industrialization and urbanization. Furthermore, carbon emission in regions with more developed industrial structures is much higher than in regions with less advanced industrial structures. Lastly, carbon emission per unit of GDP has declined since 2004, indicating that a series of reform measures i.e., economic growth mode transformation and land-use structure optimization, has initiated the process of carbon emission reduction.

  17. 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...

  18. National climate assessment technical report on the impacts of climate and land use and land cover change

    Science.gov (United States)

    Loveland, Thomas; Mahmood, Rezaul; Patel-Weynand, Toral; Karstensen, Krista; Beckendorf, Kari; Bliss, Norman; Carleton, Andrew

    2012-01-01

    This technical report responds to the recognition by the U.S. Global Change Research Program (USGCRP) and the National Climate Assessment (NCA) of the importance of understanding how land use and land cover (LULC) affects weather and climate variability and change and how that variability and change affects LULC. Current published, peer-reviewed, scientific literature and supporting data from both existing and original sources forms the basis for this report's assessment of the current state of knowledge regarding land change and climate interactions. The synthesis presented herein documents how current and future land change may alter environment processes and in turn, how those conditions may affect both land cover and land use by specifically investigating, * The primary contemporary trends in land use and land cover, * The land-use and land-cover sectors and regions which are most affected by weather and climate variability,* How land-use practices are adapting to climate change, * How land-use and land-cover patterns and conditions are affecting weather and climate, and * The key elements of an ongoing Land Resources assessment. These findings present information that can be used to better assess land change and climate interactions in order to better assess land management and adaptation strategies for future environmental change and to assist in the development of a framework for an ongoing national assessment.

  19. Effects of Land Use/Cover Changes and Urban Forest Configuration on Urban Heat Islands in a Loess Hilly Region: Case Study Based on Yan'an City, China.

    Science.gov (United States)

    Zhang, Xinping; Wang, Dexiang; Hao, Hongke; Zhang, Fangfang; Hu, Youning

    2017-07-26

    In this study Yan'an City, a typical hilly valley city, was considered as the study area in order to explain the relationships between the surface urban heat island (SUHI) and land use/land cover (LULC) types, the landscape pattern metrics of LULC types and land surface temperature (LST) and remote sensing indexes were retrieved from Landsat data during 1990-2015, and to find factors contributed to the green space cool island intensity (GSCI) through field measurements of 34 green spaces. The results showed that during 1990-2015, because of local anthropogenic activities, SUHI was mainly located in lower vegetation cover areas. There was a significant suburban-urban gradient in the average LST, as well as its heterogeneity and fluctuations. Six landscape metrics comprising the fractal dimension index, percentage of landscape, aggregation index, division index, Shannon's diversity index, and expansion intensity of the classified LST spatiotemporal changes were paralleled to LULC changes, especially for construction land, during the past 25 years. In the urban area, an index-based built-up index was the key positive factor for explaining LST increases, whereas the normalized difference vegetation index and modified normalized difference water index were crucial factors for explaining LST decreases during the study periods. In terms of the heat mitigation performance of green spaces, mixed forest was better than pure forest, and the urban forest configuration had positive effects on GSCI. The results of this study provide insights into the importance of species choice and the spatial design of green spaces for cooling the environment.

  20. Effects of Land Use/Cover Changes and Urban Forest Configuration on Urban Heat Islands in a Loess Hilly Region: Case Study Based on Yan’an City, China

    Directory of Open Access Journals (Sweden)

    Xinping Zhang

    2017-07-01

    Full Text Available In this study Yan’an City, a typical hilly valley city, was considered as the study area in order to explain the relationships between the surface urban heat island (SUHI and land use/land cover (LULC types, the landscape pattern metrics of LULC types and land surface temperature (LST and remote sensing indexes were retrieved from Landsat data during 1990–2015, and to find factors contributed to the green space cool island intensity (GSCI through field measurements of 34 green spaces. The results showed that during 1990–2015, because of local anthropogenic activities, SUHI was mainly located in lower vegetation cover areas. There was a significant suburban-urban gradient in the average LST, as well as its heterogeneity and fluctuations. Six landscape metrics comprising the fractal dimension index, percentage of landscape, aggregation index, division index, Shannon’s diversity index, and expansion intensity of the classified LST spatiotemporal changes were paralleled to LULC changes, especially for construction land, during the past 25 years. In the urban area, an index-based built-up index was the key positive factor for explaining LST increases, whereas the normalized difference vegetation index and modified normalized difference water index were crucial factors for explaining LST decreases during the study periods. In terms of the heat mitigation performance of green spaces, mixed forest was better than pure forest, and the urban forest configuration had positive effects on GSCI. The results of this study provide insights into the importance of species choice and the spatial design of green spaces for cooling the environment.

  1. Effects of Land Use/Cover Changes and Urban Forest Configuration on Urban Heat Islands in a Loess Hilly Region: Case Study Based on Yan’an City, China

    Science.gov (United States)

    Zhang, Xinping; Hao, Hongke; Zhang, Fangfang; Hu, Youning

    2017-01-01

    In this study Yan’an City, a typical hilly valley city, was considered as the study area in order to explain the relationships between the surface urban heat island (SUHI) and land use/land cover (LULC) types, the landscape pattern metrics of LULC types and land surface temperature (LST) and remote sensing indexes were retrieved from Landsat data during 1990–2015, and to find factors contributed to the green space cool island intensity (GSCI) through field measurements of 34 green spaces. The results showed that during 1990–2015, because of local anthropogenic activities, SUHI was mainly located in lower vegetation cover areas. There was a significant suburban-urban gradient in the average LST, as well as its heterogeneity and fluctuations. Six landscape metrics comprising the fractal dimension index, percentage of landscape, aggregation index, division index, Shannon’s diversity index, and expansion intensity of the classified LST spatiotemporal changes were paralleled to LULC changes, especially for construction land, during the past 25 years. In the urban area, an index-based built-up index was the key positive factor for explaining LST increases, whereas the normalized difference vegetation index and modified normalized difference water index were crucial factors for explaining LST decreases during the study periods. In terms of the heat mitigation performance of green spaces, mixed forest was better than pure forest, and the urban forest configuration had positive effects on GSCI. The results of this study provide insights into the importance of species choice and the spatial design of green spaces for cooling the environment. PMID:28933770

  2. 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

  3. 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.

  4. Investigation of accuracy of CORINE 2006 land cover data used in watershed studies

    Directory of Open Access Journals (Sweden)

    Ayhan Ateşoğlu

    2016-01-01

    Full Text Available There have been many studies concerning the use of sustainable natural resources. The planning concerning the results of watershed-based studies is made for the future. The issue to be considered in these studies, is obtaining accurate data. The most important data of the studies in the watershed basin is obtaining land cover/use data. Land cover / land classification done by using remote sensing and GIS and monitoring the change periodically are both easy and economical. To this end, CORINE (Coordination of Information on the Environment land cover program was initiated by The European Commission (CEC. The accuracy of CORINE 2006 land cover data was evaluated using high resolution Google Earth data in two separate test areas located in the Black Sea and Central Anatolia region. Random 5000 points for each test area were assigned to classes according to the CORINE classification method using Google Earth and were compared with the CORINE 2006 data. The accuracy of first test area in Black Sea region was calculated as 51.80% the accuracy of second test area in Central Anatolia region was calculated as 55.32%. For each test area, CORINE 2006 data has not been found to be up to date and has been detected to have low accuracy.

  5. EnviroAtlas - Percent Stream Buffer Zone As Natural Land Cover for the Conterminous United States

    Science.gov (United States)

    This EnviroAtlas dataset shows the percentage of land area within a 30 meter buffer zone along the National Hydrography Dataset (NHD) high resolution stream network, and along water bodies such as lakes and ponds that are connected via flow to the streams, that is classified as forest land cover, modified forest land cover, and natural land cover using the 2006 National Land Cover Dataset (NLCD) for each Watershed Boundary Dataset (WBD) 12-digit hydrological unit (HUC) in the conterminous United States. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).

  6. [Influence of land use change on vegetation cover dynamics in Dapeng Peninsula of Shenzhen, Guangdong Province of South China].

    Science.gov (United States)

    Liang, Yao-Qin; Zeng, Hui; Li, Jing

    2012-01-01

    To study the vegetation cover dynamics under urbanization is of significance to direct regional ecological conservation. Based on the 1995-2007 remote sensing data and the investigation data of 1996 and 2007 land use change in Shenzhen, and by using NDVI index tracking and algebraic overlay calculation, this paper analyzed the vegetation types and their spatial differentiation, land use change pattern, and the relationships between land use change and vegetation cover dynamics in Dapeng Peninsula of Shenzhen. In 1995-2007, the vegetation cover in 65% of the study area changed significantly, with an overall increasing trend. Land use change was mainly caused by the development of urbanization and commercial agriculture, with 31% of the land surface changed in land use function. The land use change was one of the main causes of vegetation cover dynamics, and about 35% of the region where vegetation cover significantly degraded was related to land use change. 55% of the region where land use function changed due to mechanical disturbance caused the degradation of vegetation cover, but by the end of the study period, the vegetation cover in most of the degraded region had being improved significantly.

  7. Effects of Land Cover / Land Use, Soil Texture, and Vegetation on the Water Balance of Lake Chad Basin

    Science.gov (United States)

    Babamaaji, R. A.; Lee, J.

    2013-12-01

    Lake Chad Basin (LCB) has experienced drastic changes of land cover and poor water management practices during the last 50 years. The successive droughts in the 1970s and 1980s resulted in the shortage of surface water and groundwater resources. This problem of drought has a devastating implication on the natural resources of the Basin with great consequence on food security, poverty reduction and quality of life of the inhabitants in the LCB. Therefore, understanding the effects of land use / land cover must be a first step to find how they disturb cycle especially the groundwater in the LCB. The abundance of groundwater is affected by the climate change through the interaction with surface water, such as lakes and rivers, and disuse recharge through an infiltration process. Quantifying the impact of climate change on the groundwater resource requires reliable forecasting of changes in the major climatic variables and other spatial variations including the land use/land cover, soil texture, topographic slope, and vegetation. In this study, we employed a spatially distributed water balance model WetSpass to simulate a long-term average change of groundwater recharge in the LCB of Africa. WetSpass is a water balance-based model to estimate seasonal and spatial distribution of surface runoff, interception, evapotranspiration, and groundwater recharge. The model is especially suitable for studying the effect of land use/land cover change on the water regime in the LCB. The present study describes the concept of the model and its application to the development of recharge map of the LCB. The study shows that major role in the water balance of LCB. The mean yearly actual evapotranspiration (ET) from the basin range from 60mm - 400 mm, which is 90 % (69mm - 430) of the annual precipitation from 2003 - 2010. It is striking that about 50 - 60 % of the total runoff is produced on build-up (impervious surfaces), while much smaller contributions are obtained from vegetated

  8. Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: NLCD 2001 Land Use and Land Cover

    Science.gov (United States)

    Wieczorek, Michael; LaMotte, Andrew E.

    2010-01-01

    This data set represents the estimated area of land use and land cover from the National Land Cover Dataset 2001 (LaMotte, 2008), compiled for every catchment of NHDPlus for the conterminous United States. The source data set represents land use and land cover for the conterminous United States for 2001. 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). The NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates many of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset (NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, naming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments (drainage areas) produced using a drainage enforcement technique first widely used in New England, and thus referred to as "the New England Method." This technique involves "burning in" the 1:100,000-scale NHD and when available building "walls" using the National Watershed Boundary Dataset (WBD). The resulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree with the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey (USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method produces the best quality

  9. CHANGES IN LAND COVER AND USE AFFECT THE LOCAL AND REGIONAL CLIMATE IN PIRACICABA, BRAZIL

    Directory of Open Access Journals (Sweden)

    Priscila Pereira Coltri

    2008-12-01

    Full Text Available Land use and changes in land cover play an important role in local and regional climatic conditions, especially in tropical regions. Piracicaba, a city in southeastern Brazil, has an economy that is based primarily on sugar cane cultivation. The seasonality of this crop means that there are marked annual fluctuations in land use and cover in this municipality. In this work, we investigated the seasonal variation in urban heat-islands and local climatic variations by using remote sensing data, geographic information system (GIS and atmospheric modeling. The urban heat-islands were analyzed by using Landsat 7 (Enhanced Thematic Mapper+ images for the sugar cane crop (January to March and non-crop (August to November periods, and these images were subsequently converted to land surface brightness temperature. The average temperature in the non-crop period was 3.5°C higher than in the crop period, which suggested that heat-island intensity may be linked to the seasonality of sugar cane cultivation. In order to examine the influence of urban areas on regional temperature changes and heat fluxes, numerical simulations were done with the Brazilian Regional Atmospheric Modeling System (BRAMS. Overall, the results obtained suggested that local and regional climatic dynamics were related to land use and changes in land cover.

  10. CHANGES IN LAND COVER AND USE AFFECT THE LOCAL AND REGIONAL CLIMATE IN PIRACICABA, BRAZIL

    Directory of Open Access Journals (Sweden)

    Priscila Pereira-Coltri

    2008-01-01

    Full Text Available Land use and changes in land cover play an important role in local and regional climatic conditions, especially in tropical regions. Piracicaba, a city in southeastern Brazil, has an economy that is based primarily on sugar cane cultivation. The seasonality of this crop means that there are marked annual fluctuations in land use and cover in this municipality. In this work, we investigated the seasonal variation in urban heat-islands and local climatic variations by using remote sensing data, geographic information system (GIS and atmospheric modeling. The urban heat-islands were analyzed by using Landsat 7 (Enhanced Thematic Mapper+ images for the sugar cane crop (January to March and non-crop (August to November periods, and these images were subsequently converted to land surface brightness temperature. The average temperature in the non-crop period was 3.5°C higher than in the crop period, which suggested that heat-island intensity may be linked to the seasonality of sugar cane cultivation. In order to examine the influence of urban areas on regional temperature changes and heat fluxes, numerical simulations were done with the Brazilian Regional Atmospheric Modeling System (BRAMS. Overall, the results obtained suggested that local and regional climatic dynamics were related to land use and changes in land cover.

  11. 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.

  12. NASA Land Cover and Land Use Change (LCLUC): an interdisciplinary research program.

    Science.gov (United States)

    Justice, Chris; Gutman, Garik; Vadrevu, Krishna Prasad

    2015-01-15

    Understanding Land Cover/Land Use Change (LCLUC) in diverse regions of the world and at varied spatial scales is one of the important challenges in global change research. In this article, we provide a brief overview of the NASA LCLUC program, its focus areas, and the importance of satellite remote sensing observations in LCLUC research including future directions. The LCLUC Program was designed to be a cross-cutting theme within NASA's Earth Science program. The program aims to develop and use remote sensing technologies to improve understanding of human interactions with the environment. Since 1997, the NASA LCLUC program has supported nearly 280 research projects on diverse topics such as forest loss and carbon, urban expansion, land abandonment, wetland loss, agricultural land use change and land use change in mountain systems. The NASA LCLUC program emphasizes studies where land-use changes are rapid or where there are significant regional or global LCLUC implications. Over a period of years, the LCLUC program has contributed to large regional science programs such as Land Biosphere-Atmosphere (LBA), the Northern Eurasia Earth Science Partnership Initiative (NEESPI), and the Monsoon Area Integrated Regional Study (MAIRS). The primary emphasis of the program will remain on using remote sensing datasets for LCLUC research. The program will continue to emphasize integration of physical and social sciences to address regional to global scale issues of LCLUC for the benefit of society. Copyright © 2014. Published by Elsevier Ltd.

  13. 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.

  14. Study Of Land Cover And Condition Catchment Area Groundwater Aquifer In Tanah Merah North Samarinda District Using Resistivity Geoelectric Sounding

    Directory of Open Access Journals (Sweden)

    Djayus

    2017-06-01

    Full Text Available Land cover is a biophysical cover that maintains land conditions in water balance. The purpose of this research is to know the condition of land cover water catchment groundwater aquifer and correlation. This research begins by collecting data on land cover soil type rainfall slopes and groundwaterinformation. Field activities include observation and data collection of land cover geological conditions community wells and geoelectric sounding. Land cover data is classified according to circumstances and conditions. Geoelectric sounding data was analyzed with IP2WIN software interpretation of lithologic variation of rocks and depth based on resistivity value. Plot the position of each lithology sounding with Surfer software obtained kontour rock field boundary and 3D model of the aquifer position.The results showed that the land cover consisted of vegetated areas forests 27221 Ha 4032 and agricultural land 18336 Ha 2716 non-vegetation area 9880 Ha 1464 constructed land Open land 116.33 Ha 17.23 and water body 4.35 Ha 0.64 The condition of land cover in this water catchment area has decreased 6838 Ha 1014 from the previous condition 34059 Ha 5046 to 27221 Ha 4032. Referring to Permenhut RI No. 32 in 2009 total score catchment area 33 including the somewhat critical condition. Groundwater aquifers based on 3D sounding geolistrik modeling consist of a free aquifer for shallow groundwater depth of water level between 2-30 m with thickness 2-65 m and a distorted aquifer for groundwaterin depth of water between 75-150 m With thickness 75-125 m depth of community well 10-45 m. The transfer of land into open pit mines resulted in the destruction of the balance and water system the decreasing decreasing the discharge of the well water of the community drill the failure and the lack of new water discharge of the new wells the loss of groundwaterin several dug wells landslides and mud floods on the farmland

  15. Geodemography: Land cover, geographical information systems and population distribution

    Directory of Open Access Journals (Sweden)

    Francisco J. Goerlich Gisbert

    2013-01-01

    Full Text Available This paper examines the recent application of the Geographical Information Systems (GIS to the analysis of population distribution. We mention the efforts of the National Statistical Institutes in this direction boosted by the last census 2011.The stating point is a growing need to have available population figures for areas not related to administrative boundaries, either user defined zones or in grid format.This allows a convenient zonal system to combine demographic characteristics with environmental and pure geographic data, so the relation between the man and the environment can be analyzed in a unified way.Eventually, we offer a practical illustration of the interactions between GIS techniques and administrative population data in the study of spatial population distribution: We build a density grid for Spain by dasymetric methods from census tracts population data and Land Cover and Use Information System of Spain (SIOSE.The analysis is done within the spatial reference framework of the European Union.

  16. An assessment of support vector machines for land cover classification

    Science.gov (United States)

    Huang, C.; Davis, L.S.; Townshend, J.R.G.

    2002-01-01

    The support vector machine (SVM) is a group of theoretically superior machine learning algorithms. It was found competitive with the best available machine learning algorithms in classifying high-dimensional data sets. This paper gives an introduction to the theoretical development of the SVM and an experimental evaluation of its accuracy, stability and training speed in deriving land cover classifications from satellite images. The SVM was compared to three other popular classifiers, including the maximum likelihood classifier (MLC), neural network classifiers (NNC) and decision tree classifiers (DTC). The impacts of kernel configuration on the performance of the SVM and of the selection of training data and input variables on the four classifiers were also evaluated in this experiment.

  17. Land use and land cover change in the North Central Appalachians ecoregion

    Science.gov (United States)

    Napton, D.E.; Sohl, Terry L.; Auch, Roger F.; Loveland, Thomas R.

    2003-01-01

    The North Central Appalachians ecoregion, spanning northern Pennsylvania and southern New York, has a long history of land use and land cover change. Turn-of-the-century logging dramatically altered the natural landscape of the ecoregion, but subsequent regeneration returned the ecoregion to a forest dominated condition. To understand contemporary land use and land cover changes, the U.S. Geological Survey with NASA and the U.S. Environmental Protection Agency used a random sample of satellite remotely sensed data for 1973, 1980, 1986, 1992, and 2000 to estimate the rates and assess the primary drivers of change in the North Central Appalachians. The overall change was 6.2%. The 1973-1980 period had the lowest rate of change (1.5%); the highest rate (2.9%) occurred during the 1992-2000 period. The primary conversions were deforestation through harvesting and natural disturbance (i.e., tornados) followed by regeneration, and conversion of forests to mining and urban lands. The primary drivers of the change included changes in access, energy and forest prices, and attitudes toward the environment.

  18. Integration of land use and land cover inventories for landscape management and planning in Italy.

    Science.gov (United States)

    Sallustio, Lorenzo; Munafò, Michele; Riitano, Nicola; Lasserre, Bruno; Fattorini, Lorenzo; Marchetti, Marco

    2016-01-01

    There are both semantic and technical differences between land use (LU) and land cover (LC) measurements. In cartographic approaches, these differences are often neglected, giving rise to a hybrid classification. The aim of this paper is to provide a better understanding and characterization of the two classification schemes using a comparison that allows maximization of the informative power of both. The analysis was carried out in the Molise region (Central Italy) using sample information from the Italian Land Use Inventory (IUTI). The sampling points were classified with a visual interpretation of aerial photographs for both LU and LC in order to estimate surfaces and assess the changes that occurred between 2000 and 2012. The results underscore the polarization of land use and land cover changes resulting from the following: (a) recolonization of natural surfaces, (b) strong dynamisms between the LC classes in the natural and semi-natural domain and (c) urban sprawl on the lower hills and plains. Most of the observed transitions are attributable to decreases in croplands, natural grasslands and pastures, owing to agricultural abandonment. The results demonstrate that a comparison between LU and LC estimates and their changes provides an understanding of the causes of misalignment between the two criteria. Such information may be useful for planning policies in both natural and semi-natural contexts as well as in urban areas.

  19. Impacts of changes in climate, land use and land cover on atmospheric mercury

    Science.gov (United States)

    Zhang, H.; Holmes, C. D.; Wu, S.

    2016-09-01

    Mercury is an important pollutant that can be transported globally due to its long lifetime in the atmosphere. Atmosphere-surface exchange is a major process affecting the cycling of mercury in the global environment and its impacts on food webs. We investigate the sensitivities of the air-surface exchange, atmospheric transport, and budget of mercury to projected 2000-2050 changes in climate and land use/land cover with a global chemical transport model (GEOS-Chem). We find that annual mean Hg(0) dry deposition flux over land could increase by up to 20% in northern mid-latitudes by 2050 due to increased vegetation and foliage density. Climate change can significantly affect both the wet deposition and atmospheric chemistry of mercury. In response to the projected climate change, the annual mean wet deposition flux increases over most continental regions and decreases over most of the mid-latitude and tropical oceans. The annual mean mercury wet deposition flux over northern and southern high latitudes increases by 7% and 8% respectively, largely driven by increases in precipitation there. Surface Hg(0) is predicted to increase generally, because high temperatures decrease Hg(0) oxidation by bromine and high moisture increases aqueous Hg(II) photo reduction. The combined effects of projected changes in climate, land use and land cover increase mercury deposition to the continental biosphere and decrease mercury deposition to the marine biosphere.

  20. Land Cover Mapping in Southwestern China Using the HC-MMK Approach

    Directory of Open Access Journals (Sweden)

    Guangbin Lei

    2016-04-01

    Full Text Available Land cover mapping in mountainous areas is a notoriously challenging task due to the rugged terrain and high spatial heterogeneity of land surfaces as well as the frequent cloud contamination of satellite imagery. Taking Southwestern China (a typical mountainous region as an example, this paper established a new HC-MMK approach (Hierarchical Classification based on Multi-source and Multi-temporal data and geo-Knowledge, which was especially designed for land cover mapping in mountainous areas. This approach was taken in order to generate a 30 m-resolution land cover product in Southwestern China in 2010 (hereinafter referred to as CLC-SW2010. The multi-temporal native HJ (HuanJing, small satellite constellation for disaster and environmental monitoring CCD (Charge-Coupled Device images, Landsat TM (Thematic Mapper images and topographical data (including elevation, aspect, slope, etc. were taken as the main input data sources. Hierarchical classification tree construction and a five-step knowledge-based interactive quality control were the major components of this proposed approach. The CLC-SW2010 product contained six primary categories and 38 secondary categories, which covered about 2.33 million km2 (accounting for about a quarter of the land area of China. The accuracies of primary and secondary categories for CLC-SW2010 reached 95.09% and 87.14%, respectively, which were assessed independently by a third-party group. This product has so far been used to estimate the terrestrial carbon stocks and assess the quality of the ecological environments. The proposed HC-MMK approach could be used not only in mountainous areas, but also for plains, hills and other regions. Meanwhile, this study could also be used as a reference for other land cover mapping projects over large areas or even the entire globe.

  1. Effect of surface BRDF of various land cover types on geostationary observations of tropospheric NO2

    Science.gov (United States)

    Noguchi, K.; Richter, A.; Rozanov, V.; Rozanov, A.; Burrows, J. P.; Irie, H.; Kita, K.

    2014-10-01

    We investigated the effect of surface reflectance anisotropy, bidirectional reflectance distribution function (BRDF), on satellite retrievals of tropospheric NO2. We assume the geometry of geostationary measurements over Tokyo, which is one of the worst air-polluted regions in East Asia. We calculated air mass factors (AMF) and box AMFs (BAMF) for tropospheric NO2 to evaluate the effect of BRDF by using the radiative transfer model SCIATRAN. To model the BRDF effect, we utilized the Moderate Resolution Imaging Spectroradiometer (MODIS) products (MOD43B1 and MOD43B2), which provide three coefficients to express the RossThick-LiSparse reciprocal model, a semi-empirical and kernel-based model of BRDF. Because BRDF depends on the land cover type, we also utilized the High Resolution Land-Use and Land-Cover Map of the Advanced Land Observing Satellite (ALOS)/Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2), which classifies the ground pixels over Tokyo into six main types: water, urban, paddy, crop, deciduous forest, and evergreen forest. We first develop an empirical model of the three BRDF coefficients for each land cover type over Tokyo and then apply the model to the calculation of land-cover-type-dependent AMFs and BAMFs. Results show that the variability of AMF among the land types is up to several tens of percent, and if we neglect the reflectance anisotropy, the difference with AMFs based on BRDF reaches 10% or more. The evaluation of the BAMFs calculated shows that not considering BRDF will cause large errors if the concentration of NO2 is high close to the surface, although the importance of BRDF for AMFs decreases for large aerosol optical depth (AOD).

  2. 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.

  3. Reconstructing Historical Land Cover Type and Complexity by Synergistic Use of Landsat Multispectral Scanner and CORONA

    Directory of Open Access Journals (Sweden)

    Amir Reza Shahtahmassebi

    2017-07-01

    Full Text Available Survey data describing land cover information such as type and diversity over several decades are scarce. Therefore, our capacity to reconstruct historical land cover using field data and archived remotely sensed data over large areas and long periods of time is somewhat limited. This study explores the relationship between CORONA texture—a surrogate for actual land cover type and complexity—with spectral vegetation indices and texture variables derived from Landsat MSS under the Spectral Variation Hypothesis (SVH such as to reconstruct historical continuous land cover type and complexity. Image texture of CORONA was calculated using a mean occurrence measure while image textures of Landsat MSS were calculated by occurrence and co-occurrence measures. The relationship between these variables was evaluated using correlation and regression techniques. The reconstruction procedure was undertaken through regression kriging. The results showed that, as expected, texture based on the visible bands and corresponding indices indicated larger correlation with CORONA texture, a surrogate of land cover (correlation >0.65. In terms of prediction, the combination of the first-order mean of band green, second-order measure of tasseled cap brightness, second-order mean of Normalized Visible Index (NVI and second-order entropy of NIR yielded the best model with respect to Akaike’s Information Criterion (AIC, r-square, and variance inflation factors (VIF. The regression model was then used in regression kriging to map historical continuous land cover. The resultant maps indicated the type and degree of complexity in land cover. Moreover, the proposed methodology minimized the impacts of topographic shadow in the region. The performance of this approach was compared with two conventional classification methods: hard classifiers and continuous classifiers. In contrast to conventional techniques, the technique could clearly quantify land cover complexity and

  4. Urban land use and land cover change analysis and modeling a case study area Malatya, Turkey

    OpenAIRE

    Baysal, Gülendam

    2013-01-01

    Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies. This research was conducted to analyze the land use and land cover changes and to model the changes for the case study area Malatya, Turkey. The first step of the study was acquisition of multi temporal data in order to detect the changes over the time. For this purpose satellite images (Landsat 1990-2000-2010) have been used. In order to acquire data from satel...

  5. Global land-cover and land-use change of the last 6000 years for climate modelling studies: the PAGES LandCover6k initiative and its first achievements

    Science.gov (United States)

    Gaillard, Marie-Jose; Morrison, Kathleen; Madella, Marco; Whitehouse, Nicki J.; Pages Landcover6k Sub-Coordinators

    2016-04-01

    The goal of the PAGES LandCover6k initiative is to provide relevant, empirical data on past anthropogenic land-cover change (land-use change) to climate modellers (e.g. the CMIP5 initiative). Land-use change is one of many climate forcings and its effect on climate is still badly understood. Among the effects of land-cover change on climate, the best known are the biogeochemical effects, and in particular the influence on the exchange of CO2 between the land surface and the atmosphere. The biogeophysical effects are less well understood, i.e. the net effect of changes in the albedo and evapotranspiration is complex. Moreover, the net effect of both biogeochemical and biogeophysical processes due to land-use change is still a matter of debate. The LandCover6k working group infers land-use data from fossil pollen records from lake sediments and peat deposits, and from historical archives and archaeological records (including pollen and other palaeoecological records such as wood and plant micro/macroremains). The working group is divided into two activities, i) pollen-based reconstructions of past land cover using pollen-vegetation modelling approaches, and mapping of pollen-based land-cover change using spatial statistics (e.g. Trondman et al., 2015; Pirzimanbein et al., 2014), and ii) upscaling and summarizing historical and archaeological data into maps of major land-use categories linked to quantitative attributes. Studies on pollen productivity of major plant taxa are an essential part of activity i). Pollen productivity estimates are available for a large number of the northern hemisphere, major plant taxa, but are still missing for large parts of the tropics for which research is currently in progress. The results of both activities are then used to revise existing Anthropogenic Land-Cover Change (ALCC) scenarios, the HYDE database (Klein-Goldewijk et al.,) and KK (Kaplan et al.,). Climate modellers (e.g. the CMIP5 initiative) can use the LandCover6k products

  6. Land cover classification and economic assessment of citrus groves using remote sensing

    Science.gov (United States)

    Shrivastava, Rahul J.; Gebelein, Jennifer L.

    The citrus industry has the second largest impact on Florida's economy, following tourism. Estimation of citrus area coverage and annual forecasts of Florida's citrus production are currently dependent on labor-intensive interpretation of aerial photographs. Remotely sensed data from satellites has been widely applied in agricultural yield estimation and cropland management. Satellite data can potentially be obtained throughout the year, making it especially suitable for the detection of land cover change in agriculture and horticulture, plant health status, soil and moisture conditions, and effects of crop management practices. In this study, we analyzed land cover of citrus crops in Florida using Landsat Enhanced Thematic Mapper Plus (ETM+) imagery from the University of Maryland Global Land Cover Facility (GLCF). We hypothesized that an interdisciplinary approach combining citrus production (economic) data with citrus land cover area per county would yield a correlation between observable spectral reflectance throughout the year, and the fiscal impact of citrus on local economies. While the data from official sources based on aerial photography were positively correlated, there were serious discrepancies between agriculture census data and satellite-derived cropland area using medium-resolution satellite imagery. If these discrepancies can be resolved by using imagery of higher spatial resolution, a stronger correlation would be observed for citrus production based on satellite data. This would allow us to predict the economic impact of citrus from satellite-derived spectral data analysis to determine final crop harvests.

  7. A reconstruction of global agricultural areas and land cover for the last millennium

    Science.gov (United States)

    Pongratz, J.; Reick, C.; Raddatz, T.; Claussen, M.

    2008-09-01

    Humans have substantially modified the Earth's land cover, especially by transforming natural ecosystems to agricultural areas. In preindustrial times, the expansion of agriculture was probably the dominant process by which humankind altered the Earth system, but little is known about its extent, timing, and spatial pattern. This study presents an approach to reconstruct spatially explicit changes in global agricultural areas (cropland and pasture) and the resulting changes in land cover over the last millennium. The reconstruction is based on published maps of agricultural areas for the last three centuries. For earlier times, a country-based method is developed that uses population data as a proxy for agricultural activity. With this approach, the extent of cropland and pasture is consistently estimated since AD 800. The resulting reconstruction of agricultural areas is combined with a map of potential vegetation to estimate the resulting historical changes in land cover. Uncertainties associated with this approach, in particular owing to technological progress in agriculture and uncertainties in population estimates, are quantified. About 5 million km2 of natural vegetation are found to be transformed to agriculture between AD 800 and 1700, slightly more to cropland (mainly at the expense of forested area) than to pasture (mainly at the expense of natural grasslands). Historical events such as the Black Death in Europe led to considerable dynamics in land cover change on a regional scale. The reconstruction can be used with global climate and ecosystem models to assess the impact of human activities on the Earth system in preindustrial times.

  8. LBA-ECO CD-06 Land Use/Land Cover Time Series, Ji-Parana Basin, Brazil: 1986-2001

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains four land use/land cover maps (1986, 1992, 1996 and 2001) for the Ji-Parana River Basin, derived from the digital classification of 8 Landsat...

  9. LBA-ECO CD-06 Ji-Parana River Basin Land Use and Land Cover Map, Brazil: 1999

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set provides a land use/land cover map of the Ji-Parana River Basin in the state of Rondonia, Brazil produced from the digital classification of...

  10. LBA-ECO CD-06 Ji-Parana River Basin Land Use and Land Cover Map, Brazil: 1999

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set provides a land use/land cover map of the Ji-Parana River Basin in the state of Rondonia, Brazil produced from the digital classification of eight...

  11. LBA-ECO CD-06 Land Use/Land Cover Time Series, Ji-Parana Basin, Brazil: 1986-2001

    Data.gov (United States)

    National Aeronautics and Space Administration — ABSTRACT: This data set contains four land use/land cover maps (1986, 1992, 1996 and 2001) for the Ji-Parana River Basin, derived from the digital classification of...

  12. EnviroAtlas - Percent Land Cover with Potentially Restorable Wetlands on Agricultural Land per 12-Digit HUC - Contiguous United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas dataset shows the percent land cover with potentially restorable wetlands on agricultural land for each 12-digit Hydrologic Unit (HUC) watershed in...

  13. 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:...

  14. 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,...

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

    Directory of Open Access Journals (Sweden)

    W. Li

    2018-01-01

    Full Text Available 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

  16. 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

  17. Agricultural land cover mapping in the context of a geographically referenced digital information system. [Carroll, Macon, and Gentry Counties, Missouri

    Science.gov (United States)

    Stoner, E. R.

    1982-01-01

    The introduction of soil map information to the land cover mapping process can improve discrimination of land cover types and reduce confusion among crop types that may be caused by soil-specific management practices and background reflectance characteristics. Multiple dates of LANDSAT MSS digital were analyzed for three study areas in northern Missouri to produce cover types for major agricultural land cover classes. Digital data bases were then developed by adding ancillary data such as digitized soil and transportation network information to the LANDSAT-derived cover type map. Procedures were developed to manipulate the data base parameters to extract information applicable to user requirements. An agricultural information system combining such data can be used to determine the productive capacity of land to grow crops, fertilizer needs, chemical weed control rates, irrigation suitability, and trafficability of soil for planting.

  18. Predicting plant diversity patterns in Madagascar: understanding the effects of climate and land cover change in a biodiversity hotspot.

    Directory of Open Access Journals (Sweden)

    Kerry A Brown

    Full Text Available Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.

  19. Predicting plant diversity patterns in Madagascar: understanding the effects of climate and land cover change in a biodiversity hotspot.

    Science.gov (United States)

    Brown, Kerry A; Parks, Katherine E; Bethell, Colin A; Johnson, Steig E; Mulligan, Mark

    2015-01-01

    Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.

  20. Rapid Detection of Land Cover Changes Using Crowdsourced Geographic Information: A Case Study of Beijing, China

    Directory of Open Access Journals (Sweden)

    Yuan Meng

    2017-08-01

    Full Text Available Land cover change (LCC detection is a significant component of sustainability research including ecological economics and climate change. Due to the rapid variability of natural environment, effective LCC detection is required to capture sufficient change-related information. Although such information has been available through remotely sensed images, the complicated image processing and classification make it time consuming and labour intensive. In contrast, the freely available crowdsourced geographic information (CGI contains easily interpreted textual information, and thus has the potential to be applied for capturing effective change-related information. Therefore, this paper presents and evaluates a method using CGI for rapid LCC detection. As a case study, Beijing is chosen as the study area, and CGI is applied to monitor LCC information. As one kind of CGI which is generated from commercial Internet maps, points of interest (POIs with detailed textual information are utilised to detect land cover in 2016. Those POIs are first classified into land cover nomenclature based on their textual information. Then, a kernel density approach is proposed to effectively generate land cover regions in 2016. Finally, with GlobeLand30 in 2010 as baseline map, LCC is detected using the post-classification method in the period of 2010–2016 in Beijing. The result shows that an accuracy of 89.20% is achieved with land cover regions generated by POIs, indicating that POIs are reliable for rapid LCC detection. Additionally, an LCC detection comparison is proposed between remotely sensed images and CGI, revealing the advantages of POIs in terms of LCC efficiency. However, due to the uneven distribution, remotely sensed images are still required in areas with few POIs.

  1. Land Use and Land Cover Change in the Bale Mountain Eco-Region of Ethiopia during 1985 to 2015

    Directory of Open Access Journals (Sweden)

    Sisay Nune Hailemariam

    2016-11-01

    Full Text Available Anthropogenic factors are responsible for major land use and land cover changes (LULCC. Bale Mountain Eco-Region in Ethiopia is a biodiversity-rich ecosystem where such LULCC have occurred. The specific objectives of this study were to: (i determine which LULC types gained or lost most as a result of the observed LULCC; (ii identify the major drivers of the LULCC/deforestation; and (iii assess the approximate amount of carbon stock removed as a result of deforestation during the study period. Remote sensing and GIS were used to analyze LULCC. Landsat images acquired in 1985, 1995, 2005, and 2015 were used. Additionally, data from the Central Statistics Agency on cropland expansion, and human and livestock population growth were analyzed and correlations were made. The results showed that forest lost 123,751 ha while farmland gained 292,294 ha. Farmland and urban settlement expansion were found to be major drivers of LULCC. Aboveground carbon stock removed from forest and shrubland was more than 24 million tons. In the future, allocation of land to different uses must be based on appropriate land use policies. Integrating biodiversity and ecosystem values for each land cover as per the UN Sustainable Development Goal (UN-SDG 15.9 may be one of the mechanisms to limit unplanned expansion or invasion of one sector at the expense of another.

  2. 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

  3. 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

  4. Effect of land use land cover change on soil erosion potential in an agricultural watershed.

    Science.gov (United States)

    Sharma, Arabinda; Tiwari, Kamlesh N; Bhadoria, P B S

    2011-02-01

    Universal soil loss equation (USLE) was used in conjunction with a geographic information system to determine the influence of land use and land cover change (LUCC) on soil erosion potential of a reservoir catchment during the period 1989 to 2004. Results showed that the mean soil erosion potential of the watershed was increased slightly from 12.11 t ha(-1) year(-1) in the year 1989 to 13.21 t ha(-1) year(-1) in the year 2004. Spatial analysis revealed that the disappearance of forest patches from relatively flat areas, increased in wasteland in steep slope, and intensification of cultivation practice in relatively more erosion-prone soil were the main factors contributing toward the increased soil erosion potential of the watershed during the study period. Results indicated that transition of other land use land cover (LUC) categories to cropland was the most detrimental to watershed in terms of soil loss while forest acted as the most effective barrier to soil loss. A p value of 0.5503 obtained for two-tailed paired t test between the mean erosion potential of microwatersheds in 1989 and 2004 also indicated towards a moderate change in soil erosion potential of the watershed over the studied period. This study revealed that the spatial location of LUC parcels with respect to terrain and associated soil properties should be an important consideration in soil erosion assessment process.

  5. Land Cover Mapping in Northern High Latitude Permafrost Regions with Satellite Data: Achievements and Remaining Challenges

    Directory of Open Access Journals (Sweden)

    Annett Bartsch

    2016-11-01

    Full Text Available Most applications of land cover maps that have been derived from satellite data over the Arctic require higher thematic detail than available in current global maps. A range of application studies has been reviewed, including up-scaling of carbon fluxes and pools, permafrost feature mapping and transition monitoring. Early land cover mapping studies were driven by the demand to characterize wildlife habitats. Later, in the 1990s, up-scaling of in situ measurements became central to the discipline of land cover mapping on local to regional scales at several sites across the Arctic. This includes the Kuparuk basin in Alaska, the Usa basin and the Lena Delta in Russia. All of these multi-purpose land cover maps have been derived from Landsat data. High resolution maps (from optical satellite data serve frequently as input for the characterization of periglacial features and also flux tower footprints in recent studies. The most used map to address circumpolar issues is the CAVM (Circum Arctic Vegetation Map based on AVHRR (1 km and has been manually derived. It provides the required thematic detail for many applications, but is confined to areas north of the treeline, and it is limited in spatial detail. A higher spatial resolution circumpolar land cover map with sufficient thematic content would be beneficial for a range of applications. Such a land cover classification should be compatible with existing global maps and applicable for multiple purposes. The thematic content of existing global maps has been assessed by comparison to the CAVM and regional maps. None of the maps provides the required thematic detail. Spatial resolution has been compared to used classes for local to regional applications. The required thematic detail increases with spatial resolution since coarser datasets are usually applied over larger areas covering more relevant landscape units. This is especially of concern when the entire Arctic is addressed. A spatial

  6. Selection of LiDAR geometric features with adaptive neighborhood size for urban land cover classification

    Science.gov (United States)

    Dong, Weihua; Lan, Jianhang; Liang, Shunlin; Yao, Wei; Zhan, Zhicheng

    2017-08-01

    LiDAR has been an effective technology for acquiring urban land cover data in recent decades. Previous studies indicate that geometric features have a strong impact on land cover classification. Here, we analyzed an urban LiDAR dataset to explore the optimal feature subset from 25 geometric features incorporating 25 scales under 6 definitions for urban land cover classification. We performed a feature selection strategy to remove irrelevant or redundant features based on the correlation coefficient between features and classification accuracy of each features. The neighborhood scales were divided into small (0.5-1.5 m), medium (1.5-6 m) and large (>6 m) scale. Combining features with lower correlation coefficient and better classification performance would improve classification accuracy. The feature depicting homogeneity or heterogeneity of points would be calculated at a small scale, and the features to smooth points at a medium scale and the features of height different at large scale. As to the neighborhood definition, cuboid and cylinder were recommended. This study can guide the selection of optimal geometric features with adaptive neighborhood scale for urban land cover classification.

  7. 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

  8. From forest to farmland: pollen-inferred land cover change across Europe using the pseudobiomization approach.

    Science.gov (United States)

    Fyfe, Ralph M; Woodbridge, Jessie; Roberts, Neil

    2015-03-01

    Maps of continental-scale land cover are utilized by a range of diverse users but whilst a range of products exist that describe present and recent land cover in Europe, there are currently no datasets that describe past variations over long time-scales. User groups with an interest in past land cover include the climate modelling community, socio-ecological historians and earth system scientists. Europe is one of the continents with the longest histories of land conversion from forest to farmland, thus understanding land cover change in this area is globally significant. This study applies the pseudobiomization method (PBM) to 982 pollen records from across Europe, taken from the European Pollen Database (EPD) to produce a first synthesis of pan-European land cover change for the period 9000 bp to present, in contiguous 200 year time intervals. The PBM transforms pollen proportions from each site to one of eight land cover classes (LCCs) that are directly comparable to the CORINE land cover classification. The proportion of LCCs represented in each time window provides a spatially aggregated record of land cover change for temperate and northern Europe, and for a series of case study regions (western France, the western Alps, and the Czech Republic and Slovakia). At the European scale, the impact of Neolithic food producing economies appear to be detectable from 6000 bp through reduction in broad-leaf forests resulting from human land use activities such as forest clearance. Total forest cover at a pan-European scale moved outside the range of previous background variability from 4000 bp onwards. From 2200 bp land cover change intensified, and the broad pattern of land cover for preindustrial Europe was established by 1000 bp. Recognizing the timing of anthropogenic land cover change in Europe will further the understanding of land cover-climate interactions, and the origins of the modern cultural landscape. © 2014 John Wiley & Sons Ltd.

  9. Agricultural land cover mapping with the aid of digital soil survey data

    Science.gov (United States)

    Stoner, E. R.

    1982-01-01

    A study is recounted which assessed the effect of stratifying multidate Landsat MSS data on land cover classification accuracy. The study area covered 49,184 ha (121,534 acres) in Gentry County in northwestern Missouri. A pixel-by-pixel comparison of the two land cover classifications with field-verified land cover indicated improvements in identification of all cover types when land areas were stratified by soils. The introduction of soil map information to the land cover mapping process can improve discrimination of land cover types and reduce confusion among crop types that may be caused by soil-specific management practices, soil-induced crop development differences, and background reflectance characteristics.

  10. 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 ...

  11. 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...

  12. Determining the Impacts of Land Cover/use Categories on Land Surface Temperature Using LANDSAT8-OLI

    Science.gov (United States)

    Bektas Balcik, F.; Ergene, E. M.

    2016-06-01

    Due to unplanned and uncontrolled expansion of urban areas, rural land cover types have been replaced with artificial materials. As a result of these replacements, a wide range of negative environmental impacts seriously impacting human health, natural areas, ecosystems, climate, energy efficiency, and quality of living in town center. In this study, the impact of land surface temperature with respect to land cover and land use categories is investigated and evaluated for Istanbul, Turkey. Land surface temperature data was extracted from 21 October 2014 dated Landsat 8 OLI data using mono-window algorithm. In order to extract land use/cover information from remotely sensed data wetness, greenness and brightness components were derived using Tasseled Cap Transformation. The statistical relationship between land surface temperature and Tasseled Cap Transformation components in Istanbul was analyzed using the regression methods. Correlation between Land Surface Temperature and Meteorological Stations Temperature calculated %74.49.

  13. DETERMINING THE IMPACTS OF LAND COVER/USE CATEGORIES ON LAND SURFACE TEMPERATURE USING LANDSAT8-OLI

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    F. Bektas Balcik

    2016-06-01

    Full Text Available Due to unplanned and uncontrolled expansion of urban areas, rural land cover types have been replaced with artificial materials. As a result of these replacements, a wide range of negative environmental impacts seriously impacting human health, natural areas, ecosystems, climate, energy efficiency, and quality of living in town center. In this study, the impact of land surface temperature with respect to land cover and land use categories is investigated and evaluated for Istanbul, Turkey. Land surface temperature data was extracted from 21 October 2014 dated Landsat 8 OLI data using mono-window algorithm. In order to extract land use/cover information from remotely sensed data wetness, greenness and brightness components were derived using Tasseled Cap Transformation. The statistical relationship between land surface temperature and Tasseled Cap Transformation components in Istanbul was analyzed using the regression methods. Correlation between Land Surface Temperature and Meteorological Stations Temperature calculated %74.49.

  14. Development of Decadal (1985–1995–2005 Land Use and Land Cover Database for India

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    Parth S. Roy

    2015-02-01

    Full Text Available India has experienced significant Land-Use and Land-Cover Change (LULCC over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP to ensure compatibility with other global/regional LULC datasets for comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS, it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study.

  15. Land use/land cover mapping using multi-scale texture processing of high resolution data

    Science.gov (United States)

    Wong, S. N.; Sarker, M. L. R.

    2014-02-01

    Land use/land cover (LULC) maps are useful for many purposes, and for a long time remote sensing techniques have been used for LULC mapping using different types of data and image processing techniques. In this research, high resolution satellite data from IKONOS was used to perform land use/land cover mapping in Johor Bahru city and adjacent areas (Malaysia). Spatial image processing was carried out using the six texture algorithms (mean, variance, contrast, homogeneity, entropy, and GLDV angular second moment) with five difference window sizes (from 3×3 to 11×11). Three different classifiers i.e. Maximum Likelihood Classifier (MLC), Artificial Neural Network (ANN) and Supported Vector Machine (SVM) were used to classify the texture parameters of different spectral bands individually and all bands together using the same training and validation samples. Results indicated that texture parameters of all bands together generally showed a better performance (overall accuracy = 90.10%) for land LULC mapping, however, single spectral band could only achieve an overall accuracy of 72.67%. This research also found an improvement of the overall accuracy (OA) using single-texture multi-scales approach (OA = 89.10%) and single-scale multi-textures approach (OA = 90.10%) compared with all original bands (OA = 84.02%) because of the complementary information from different bands and different texture algorithms. On the other hand, all of the three different classifiers have showed high accuracy when using different texture approaches, but SVM generally showed higher accuracy (90.10%) compared to MLC (89.10%) and ANN (89.67%) especially for the complex classes such as urban and road.

  16. Sensitivity of summer climate to anthropogenic land-cover change over the Greater Phoenix, AZ, region

    Science.gov (United States)

    Georgescu, M.; Miguez-Macho, G.; Steyaert, L.T.; Weaver, C.P.

    2008-01-01

    This work evaluates the first-order effect of land-use/land-cover change (LULCC) on the summer climate of one of the nation's most rapidly expanding metropolitan complexes, the Greater Phoenix, AZ, region. High-resolution-2-km grid spacing-Regional Atmospheric Modeling System (RAMS) simulations of three "wet" and three "dry" summers were carried out for two different land-cover reconstructions for the region: a circa 1992 representation based on satellite observations, and a hypothetical land-cover scenario where the anthropogenic landscape of irrigated agriculture and urban pixels was replaced with current semi-natural vegetation. Model output is evaluated with respect to observed air temperature, dew point, and precipitation. Our results suggest that development of extensive irrigated agriculture adjacent to the urban area has dampened any regional-mean warming due to urbanization. Consistent with previous observationally based work, LULCC produces a systematic increase in precipitation to the north and east of the city, though only under dry conditions. This is due to a change in background atmospheric stability resulting from the advection of both warmth from the urban core and moisture from the irrigated area. ?? 2008 Elsevier Ltd. All rights reserved.

  17. Evaluating relationships between urban land cover composition and evapotranspiration in semi-arid regions

    Science.gov (United States)

    Manago, K. F.; Hogue, T. S.; Litvak, E.; Pataki, D. E.

    2016-12-01

    California experienced its most severe drought on record in 2013 and 2014, forcing the governor to call for the first statewide reductions in urban water use. This led to numerous water conservation efforts including turf removal and restrictions on outdoor irrigation. The decrease in irrigation across the city of Los Angeles has had major effects on regional hydrologic fluxes. Previous studies have found that conservation efforts have decreased streamflow but little work has been done on the impact of reduced irrigation on Evapotranspiration (ET). ET is one of the most difficult variables to measure as a result of its heterogeneity both spatially and temporally; yet, it is imperative in characterizing energy and hydrologic processes and in aiding water management decisions. Estimating ET is further complicated in urban regions where land cover composition is extremely variable, even at small scales. Irrigated landscape and impervious surfaces are two of the most common land cover types associated with urbanization, but they have opposite effects on ET. While numerous studies have evaluated changes in ET caused by urbanization, they have all produced varying results. This is expected as changes to ET are highly dependent on land cover composition. In this study, we modeled the relationship between ET and urban land cover change in Los Angeles. We utilized empirical equations derived from in situ measurements to calculate tree and irrigated turfgrass ET and compared the results to estimates based on remote-sensing and California Irrigation Management Information System (CIMIS) network of weather stations. We found that unshaded turfgrass largely increased ET compared to impervious surfaces, which reveals lavish irrigation practices. Trees also increased ET, but they provided shade that decreased ET from turf grass. With much of the western United States facing drought and water supply uncertainty due to climate change, understanding and predicting how land cover

  18. Management Effectiveness and Land Cover Change in Dynamic Cultural Landscapes - Assessing a Central European Biosphere Reserve

    Directory of Open Access Journals (Sweden)

    Bettina Ohnesorge

    2013-12-01

    Full Text Available Protected areas are a central pillar of efforts to safeguard biodiversity and ecosystem services, but their contribution to the conservation and management of European cultural landscapes that have complex spatial-temporal dynamics is unclear. The conservation strategy of biosphere reserves aims at integrating biodiversity and ecosystem service conservation with economic development by designating zones of differing protection and use intensities. It is applied worldwide to protect and manage valuable cultural landscapes. Using the example of a German biosphere reserve, we developed a framework to assess the effectiveness of Central European reserves in meeting their land cover related management goals. Based on digital biotope maps, we defined and assessed land cover change processes that were relevant to the reserve management's goals over a period of 13 years. We then compared these changes in the reserve's core, buffer, and transition zones and in a surrounding reference area by means of a geographical information system. (Un-desirable key processes related to management aims were defined and compared for the various zones. We found that - despite an overall land cover persistence of approximately 85% across all zones - differences in land cover changes can be more prominent across zones inside the reserve than between the areas inside and outside of it. The reserve as a whole performed better than the surrounding reference area when using land cover related management goals as a benchmark. However, some highly desirable targets, such as the conversion of coniferous plantations into seminatural forests or the gain of valuable biotope types, affected larger areas in the nonprotected reference area than in the transition zone.

  19. LACO-Wiki: A land cover validation tool and a new, innovative teaching resource for remote sensing and the geosciences

    Science.gov (United States)

    See, Linda; Perger, Christoph; Dresel, Christopher; Hofer, Martin; Weichselbaum, Juergen; Mondel, Thomas; Steffen, Fritz

    2016-04-01

    The validation of land cover products is an important step in the workflow of generating a land cover map from remotely-sensed imagery. Many students of remote sensing will be given exercises on classifying a land cover map followed by the validation process. Many algorithms exist for classification, embedded within proprietary image processing software or increasingly as open source tools. However, there is little standardization for land cover validation, nor a set of open tools available for implementing this process. The LACO-Wiki tool was developed as a way of filling this gap, bringing together standardized land cover validation methods and workflows into a single portal. This includes the storage and management of land cover maps and validation data; step-by-step instructions to guide users through the validation process; sound sampling designs; an easy-to-use environment for validation sample interpretation; and the generation of accuracy reports based on the validation process. The tool was developed for a range of users including producers of land cover maps, researchers, teachers and students. The use of such a tool could be embedded within the curriculum of remote sensing courses at a university level but is simple enough for use by students aged 13-18. A beta version of the tool is available for testing at: http://www.laco-wiki.net.

  20. 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.

  1. Snow cover as an indicator of cumulative land pollution

    Directory of Open Access Journals (Sweden)

    V. R. Alekseev

    2013-01-01

    Full Text Available A reliable technique has been devised for a simultaneous total and serial retrospective assessment of the ever increasing pollution of lands from aerospace images and from benchmark ground-based observations which permit calculations of the negative human impact on the environment for the particular regions, river drainage basins, states, and for the planet Earth as a whole. Use is made of the glacio-indication approach to the study of polluted territories around cities and transport routes that has come to be known as the «ProcUsmethod». An assessment of the land pollution across the globe was made for 221 administrative entities. Calculations were done for 193 states and 41 trust territories. The total area of polluted lands on the continents was estimated at 13 606 thousand km2 (10% of the Earth’s land surface. The heaviest pollution corresponds to West Europe (44.5% of its area, Micronesia (33.3%, and to the countries within the Caribbean basin (31.1%; the worst levels of land pollution correspond to Australia with New Zealand (2.1%, Melanesia (3.1%, and to Central Africa (3.8%. The most heavily polluted states are China (with the polluted area of 2400 thou km2, India (1460 thou km2, the USA (1156 thou km2, Russia (683 thou km2 and Brazil (657 thou km2.The findings, obtained by the Russian scientists V.G. Prokacheva and V.F. Usachev over the course of the last 30 years, are recognized as a fundamental contribution to glaciology and geoecology. The ProcUs method, suggested by Russian scientists, offers strong possibilities of obtaining quantitative indicators and studying spatiotemporal variability of pollutants. It is recommended that the method should be expanded and sophisticated on the basis of special-purpose ground-truth pilot observations to be used in implementing the Earth’s global ecological monitoring program.

  2. 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...

  3. Livelihood profiling and sensitivity of livelihood strategies to land cover dynamics and agricultural variability

    Science.gov (United States)

    Berchoux, Tristan; Hutton, Craig; Watmough, Gary; Amoako Johnson, Fiifi; Atkinson, Peter

    2017-04-01

    With population increase and the urbanisation of rural areas, land scarcity is one of the biggest challenges now faced by communities in agrarian societies. At the household level, loss of land can be due to physical processes such as erosion, to social constraints such as inheritance, or to financial constraints such as loan reimbursement or the need of cash. For rural households, whose livelihoods are mainly based on agriculture, a decrease in the area of land cultivated can have significant consequences on their livelihood strategies, thus on their livelihood outcomes. However, it is still unclear how changes in cultivated area and agricultural productivity influence households' livelihood systems, including community capitals and households' livelihood strategies. This study aims to answer this gap by combining together earth observation from space, national census and participatory qualitative data into a community-wise analysis of the relationships between land cover dynamics, variability in agricultural production and livelihood activities. Its overarching aim is to investigate how land cover dynamics relates to changes in livelihood strategies and livelihood capitals. The study demonstrates that a change in land cover influences livelihood activities differently depending on the community capitals that households have access to. One significant aspect of integrating land dynamics with livelihood activities is its capacity to provide insights on the relationships between climate, agriculture, livelihood dynamics and rural development. More broadly, it gives policymakers new methods to characterise livelihood dynamics, thus to monitor some of the key Sustainable Development Goals: food security (SDG2), employment dynamics (SDG8), inequalities (SDG10) and sustainability of communities (SDG11).

  4. 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 (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.

  5. Land-use and Land-cover Change from 1974 to 2008 around Mobile Bay

    Science.gov (United States)

    Ellis, Jean; Spruce, Joseph; Smoot, James; Hilbert, Kent; Swann, Roberta

    2008-01-01

    This project is a Gulf of Mexico Application Pilot in which NASA Stennis Space Center (SSC) is working within a regional collaboration network of the Gulf of Mexico Alliance. NASA researchers, with support from the NASA SSC Applied Science Program Steering Committee, employed multi-temporal Landsat data to assess land-use and land-cover (LULC) changes in the coastal counties of Mobile and Baldwin, AL, between 1974 and 2008. A multi-decadal time-series, coastal LULC product unique to NASA SSC was produced. The geographic extent and nature of change was quantified for the open water, barren, upland herbaceous, non-woody wetland, upland forest, woody wetland, and urban landscapes. The National Oceanic and Atmospheric Administration (NOAA) National Coastal Development Data Center (NCDDC) will assist with the transition of the final product to the operational end user, which primarily is the Mobile Bay National Estuary Program (MBNEP). We found substantial LULC change over the 34-year study period, much more than is evident when the change occurring in the last years. Between 1974 and 2008, the upland forest landscape lost almost 6% of the total acreage, while urban land cover increased by slightly more than 3%. With exception to open water, upland forest is the dominant landscape, accounting for about 25-30% of the total area.

  6. Assessing implications of land use and land cover changes in forest ecosystems of NE Turkey.

    Science.gov (United States)

    Kadıoğulları, Ali Ihsan

    2013-03-01

    Monitoring land use and land cover change (LUCC) and understanding forest cover dynamics is extremely important in sustainable development and management of forest ecosystems. This study analyzed the spatial and temporal pattern of LUCC in the Yalnızçam and Uğurlu forest planning units which are located in the northeast corner of Turkey. The investigation also evaluates the temporal changes of the spatial structure of forest conditions through the spatial analysis of forest-cover type maps from 1972 and 2005 using geographical information systems and FRAGSTATS(TM). As an overall change between 1972 and 2005, there was a net increase of 1,823 ha in forested areas, and cumulative forest improvement accounted for 2.06 %. In terms of spatial configuration, the landscape structure in the study area changed substantially over the 33-year study period, resulting in fragmentation of the landscape as indicated by large patch numbers and smaller mean patch sizes, owing to heavy grazing, illegal cutting, and uncontrolled stand treatments.

  7. Object-based method outperforms per-pixel method for land cover classification in a protected area of the Brazilian Atlantic rainforest region

    NARCIS (Netherlands)

    Francischinelli Rittl, T.; Cooper, M.; Heck, R.J.; Ballester, V.R.

    2013-01-01

    Conventional image classification based on pixels hinders the possibilities to obtain information contained in images, while modern object-based classification methods increase the acquisition of information about the object and the context in which it is inserted in the image. The objective of this

  8. A Detailed and High-Resolution Land Use and Land Cover Change Analysis over the Past 16 Years in the Horqin Sandy Land, Inner Mongolia

    Directory of Open Access Journals (Sweden)

    Xiulian Bai

    2017-01-01

    Full Text Available Land use and land cover (LULC change plays a key role in the process of land degradation and desertification in the Horqin Sandy Land, Inner Mongolia. This research presents a detailed and high-resolution (30 m LULC change analysis over the past 16 years in Ongniud Banner, western part of the Horqin Sandy Land. The LULC classification was performed by combining multiple features calculated from the Landsat Archive products using the Support Vector Machine (SVM based supervised classification approach. LULC maps with 17 secondary classes were produced for the year of 2000, 2009, and 2015 in the study area. The results showed that the multifeatures combination approach is crucial for improving the accuracy of the secondary-level LULC classification. The LULC change analyses over three different periods, 2000–2009, 2009–2015, and 2000–2015, identified significant changes as well as different trends of the secondary-level LULC in study area. Over the past 16 years, irrigated farming lands and salinized areas were expanded, whereas the waterbodies and sandy lands decreased. This implies increasing demand of water and indicates that the conservation of water resources is crucial for protecting the sensitive ecological zones in the Horqin Sandy Land.

  9. ACCURACY EVALUATION OF TWO GLOBAL LAND COVER DATA SETS OVER WETLANDS OF CHINA

    Directory of Open Access Journals (Sweden)

    Z. G. Niu

    2012-07-01

    Full Text Available Although wetlands are well known as one of the most important ecosystems in the world, there are still few global wetland mapping efforts at present. To evaluate the wetland-related types of data accurately for both the Global Land Cover 2000 (GLC2000 data set and MODIS land cover data set (MOD12Q1, we used the China wetland map of 2000, which was interpreted manually based on Landsat TM images, to examine the precision of these global land cover data sets from two aspects (class area accuracy, and spatial agreement across China. The results show that the area consistency coefficients of wetland-related types between the two global data sets and the reference data are 77.27% and 56.85%, respectively. However, the overall accuracy of relevant wetland types from GLC2000 is only 19.81% based on results of confusion matrix of spatial consistency, and similarly, MOD12Q1 is merely 18.91%. Furthermore, the accuracy of the peatlands is much lower than that of the water bodies according to the results of per-pixel comparison. The categories where errors occurred frequently mainly include grasslands, croplands, bare lands and part of woodland (deciduous coniferous forest, deciduous broadleaf forest and open shrubland. The possible reasons for the low precision of wetland-related land cover types include (1the different aims of various products and therefore the inconsistent wetland definitions in their systems; (2 the coarse spatial resolution of satellite images used in global data; (3 Discrepancies in dates when images were acquired between the global data set and the reference data. Overall, the unsatisfactory results highlight that more attention should be paid to the application of these two global data products, especially in wetland-relevant types across China.

  10. Evaluation of the 2010 MODIS Collection 5.1 Land Cover Type Product over China

    Directory of Open Access Journals (Sweden)

    Tian Zeng

    2015-02-01

    Full Text Available Although the MODIS Collection 5.1 Land Cover Type (MODIS v5.1 LCT product is one of the most recent global land cover datasets and has the shortest updating cycle, evaluations regarding this collection have not been reported. Given the importance of evaluating global land cover data for producers and potential users, the 2010 MODIS v5.1 LCT product IGBP (International Geosphere-Biosphere Programme layer was evaluated based on two grid maps at scales of 100-m and 500-m,which were derived by rasterizing the 2010 data from the national land use/cover database of China (NLUD-C. This comparison was conducted based on a new legend consisting of nine classes constructed based on the definitions of classes in the IGBP and NLUD-C legends. The overall accuracies of the aggregated classification data were 64.62% and 66.42% at the sub-pixel and pixel scales, respectively. These accuracies differed significantly in different regions. Specifically, high-quality data were obtained more easily for regions with a single land cover type, such as Xinjiang province and the northeast plain of China. The lowest accuracies were obtained for the middle of China, including Ningxia, Shaanxi, Chongqing, Yunnan and Guizhou. At the sub-pixel scale, relatively high producer and user accuracies were obtained for cropland, grass and barren regions; the highest producer accuracy was obtained for forests, and the highest user accuracy was obtained for water bodies. Shrublands and wetlands were associated with low producer and user accuracies at the sub-pixel and pixel scales, of less than 10%. Based on dominant-type reference data, the errors were classified as mixed-pixel errors and labeling errors. Labeling errors primarily originated from misclassification between grassland and barren lands. Mixed pixel errors increased as the pixel diversity increased and as the percentage of dominant-type sub-pixels decreased. Overall, mixed pixels were sources of error for most land cover

  11. Generation and Assessment of Urban Land Cover Maps Using High-Resolution Multispectral Aerial Images

    DEFF Research Database (Denmark)

    Höhle, Joachim; Höhle, Michael

    2013-01-01

    and their associated confidence intervals are used to adequately reflect uncertainty in the assessment based on the chosen sample size. Proof of concept for the method is given for an urban area in Switzerland. Here, the produced land cover map with six classes (building, wall and carport, road and parking lot, hedge...... and bush, grass) has an overall accuracy of 86% (95% confidence interval: 83-88%) and a kappa coefficient of 0.82 (95% confidence interval: 0.78-0.85). The classification of buildings is correct with 99% and of road and parking lot with 95%. To possibly improve the classification further, classification...... tree learning based on recursive partitioning is investigated. We conclude that the open source software “R” provides all the tools needed for performing statistical prudent classification and accuracy evaluations of urban land cover maps....

  12. PRESENTATION ON--LAND-COVER CHANGE DETECTION USING MULTI-TEMPORAL MODIS NDVI DATA

    Science.gov (United States)

    Monitoring the locations and distributions of land-cover changes is important for establishing linkages between policy decisions, regulatory actions and subsequent landuse activities. Past efforts incorporating two-date change detection using moderate resolution data (e.g., Lands...

  13. EnviroAtlas - 2011 Agricultural Land Cover on Steep Slopes for the Conterminous United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas dataset represents the percentage land area that is classified as agricultural land cover that occurs on slopes above a given threshold for each...

  14. Scenarios of land cover change and landslide susceptibility : An example from the buzau subcarpathians, romania

    NARCIS (Netherlands)

    Malek, Žiga; Zumpano, Veronica; Schröter, Dagmar; Glade, Thomas; Balteanu, Dan; Micu, Mihai

    2015-01-01

    Since 1990 the Subcarpathians in Buzau County, Romania have witnessed substantial socioeconomic changes and resulting changes in the land cover. Influenced by the interplay of poor economic conditions, land ownership reforms, and institutional difficulties, these changes have been difficult to

  15. EnviroAtlas - Green Bay, WI - Meter-Scale Urban Land Cover (MULC) Data (2010)

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Green Bay, WI Meter-Scale Urban Land Cover (MULC) dataset comprises 936 km2 around the city of Green Bay, surrounding towns, tribal lands and rural areas in...

  16. EnviroAtlas - 2011 Land Cover by 12-digit HUC for the Conterminous United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas dataset represents the percentage of land area that is classified as natural, forest, wetland, agricultural, natural, and developed land cover using...

  17. Complex land use and cover trajectories in the northern Choco bioregion of Colombia

    Science.gov (United States)

    Santos, Carolina

    The Choco bioregion in Northwestern Colombia is a lowland rain forest and hotspot of biodiversity. Significant land use and cover change (LUCC) is occurring throughout the region driven by global markets, illicit drug production, and civil unrest. The dominant land cover conversion is from primary forest to African Palm plantations, mediated and modified by complex combinations of social and biophysical drivers. This research combined a remote sensing based methodology to monitor LUCC in the region with an analytical approach for evaluating the possible trajectories of LUCC in a complex biological, socio-economical, and political environment. Synoptic LUCC models were developed using textural classification derived from Synthetic Aperture Radar (SAR) images for the period 1995 to 2010. LUCC models along with empirical social and spatial biophysical drivers were used to project historical land use trajectories. DINAMICA EGO a complex systems based spatial analytical framework was adopted as the platform to model land use change. The RADAR backscatter was able to capture areas were forest has been converted to African Oil Palm Plantations. However, an in depth characterization of the LUC dynamics was problematic given the spectral and spatial limitations of the sensor combined with the lack of ground data. The results of the LUC model suggest that under the current socio-political conditions African oil palm plantations will continue to expand toward forested areas into the territories traditionally inhabited by Afro-Colombians and Indigenous populations. Insecure land tenure appears as a main driver of the transformation in close association with the conditions created by the armed conflict, and the drug traffic. The rate of the transformation appears to slow down in the period after 2007. However, according to the model by 2020 most of the area inhabited by ethnic groups will be transform to AOP. This study contributes towards the understanding of land use change

  18. Anthropogenical Drivers on Land Use/Cover Change and their ...

    African Journals Online (AJOL)

    The study recommended to the government to facilitate participatory land use planning at village level, agro-forestry, provision of extensions services, and modern family planning services to check overpopulation for sustainable land use and improvement of rural livelihoods in and beyond the study area. Keywords: Land ...

  19. Recent land cover and use changes in Miombo woodlands of ...

    African Journals Online (AJOL)

    Forest and wood land ecosystems in Tanzania occupy more than 45% of the land area, more than two thirds of which made up of the Miombo woodland. The main form of land use in the Miombo region has long been shifting and small-scale sedentary cultivation. The lack of infrastructure and prevalence of deadly diseases ...

  20. Attribution of surface temperature anomalies induced by land use and land cover changes

    Science.gov (United States)

    Rigden, Angela J.; Li, Dan

    2017-07-01

    Land use/land cover changes (LULCC) directly impact the surface temperature by modifying the radiative, physiological, and aerodynamic properties controlling the surface energy and water balances. In this study, we propose a new method to attribute changes in the surface temperature induced by LULCC to changes in radiative and turbulent heat fluxes, with the partition of turbulent fluxes controlled by aerodynamic and surface resistances. We demonstrate that previous attribution studies have overestimated the contribution of aerodynamic resistance by assuming independence between the aerodynamic resistance and the Bowen ratio. Our results further demonstrate that acceptable agreement between modeled and observed temperature anomalies does not guarantee correct attribution by the model. When performing an attribution analysis, the covariance among attributing variables needs to be taken into consideration in order to accurately interpret the results.