Land-cover mapping using multitemporal, dual-frequency polarimetric SAR data

DEFF Research Database (Denmark)

Skriver, Henning; Schou, Jesper; Dierking, Wolfgang

2000-01-01

during the growing season acquired a lot of data over a Danish agricultural site. The data acquisitions were co-ordinated with ground surveys to obtain a detailed land cover map. The test area contains a large number of different land cover classes, such as more than 10 different crop types, deciduous......The Danish Center for Remote Sensing (DCRS) is, in collaboration with the Danish mapping agency, conducting a study on topographic mapping using SAR data, and land cover mapping results are presented. The Danish EMISAR system (an L- and C-band, fully polarimetric, airborne SAR) have in 1994 to 1999...

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

Directory of Open Access Journals (Sweden)

Keigo Kitada

2012-05-01

Full Text Available Conventional spectral-based classification methods have significant limitations in the digital classification of urban land-use and land-cover classes from high-resolution remotely sensed data because of the lack of consideration given to the spatial properties of images. To recognize the complex distribution of urban features in high-resolution image data, texture information consisting of a group of pixels should be considered. Lacunarity is an index used to characterize different texture appearances. It is often reported that the land-use and land-cover in urban areas can be effectively classified using the lacunarity index with high-resolution images. However, the applicability of the maximum-likelihood approach for hybrid analysis has not been reported. A more effective approach that employs the original spectral data and lacunarity index can be expected to improve the accuracy of the classification. A new classification procedure referred to as “gradable classification method” is proposed in this study. This method improves the classification accuracy in incremental steps. The proposed classification approach integrates several classification maps created from original images and lacunarity maps, which consist of lacnarity values, to create a new classification map. The results of this study confirm the suitability of the gradable classification approach, which produced a higher overall accuracy (68% and kappa coefficient (0.64 than those (65% and 0.60, respectively obtained with the maximum-likelihood approach.

Geographic Information System For The Mapping Of Value Land Zone Of District Bengkong Based On AHP Analysis

Directory of Open Access Journals (Sweden)

Vera Astutik

2017-07-01

Full Text Available Information on the value of land in Indonesia is still very minimal and difficult to be known by the public, particularly in the area of Bengkong, it also results in the presence of new activity for land speculators who want to grab a great adventage in providing price and land value pricing-related information. The purpose of this research are to create the value land zone map (VLZ that illustrates the value of land is relatively the same as delivering lines and different colors on each value owned and accompanied the factors whisch affected it, as well as presenting a price comparison between the village and the land on map in the form of the web. Spatial analysis and AHP can be used for weighting for the most influential parameters and has no effect, so that the AHP can be useful to assist in decision making. VLZ obtained by observation in the field using a questionnaire and interview against the respondent. Observation and interviews done with the technique of sampling purposisive namely the selection of the sample with the groups in the number of smallest unit of score. Samples taken as many as 25 in order to achieve an accurate data. The value of the acquired land price is the current value of land prices. The result of the research in the form of web map VLZ with 6 classification of land price, the prices that Bengkong area concertrated settlement areas as Rp 3.500.000/sqm for the land prices are the highest in the village of Sadai and Rp 327.000/sqm for the lowest land price was in the village of Tanjung Buntung.

Globalland30 Mapping Capacity of Land Surface Water in Thessaly, Greece

Directory of Open Access Journals (Sweden)

Ioannis Manakos

2014-12-01

Full Text Available The National Geomatics Center of China (NGCC produced Global Land Cover (GlobalLand30 maps with 30 m spatial resolution for the years 2000 and 2009–2010, responding to the need for harmonized, accurate, and high-resolution global land cover data. This study aims to assess the mapping accuracy of the land surface water layer of GlobalLand30 for 2009–2010. A representative Mediterranean region, situated in Greece, is considered as the case study area, with 2009 as the reference year. The assessment is realized through an object-based comparison of the GlobalLand30 water layer with the ground truth and visually interpreted data from the Hellenic Cadastre fine spatial resolution (0.5 m orthophoto map layer. GlobCover 2009, GlobCorine 2009, and GLCNMO 2008 corresponding thematic layers are utilized to show and quantify the progress brought along with the increment of the spatial resolution, from 500 m to 300 m and finally to 30 m with the newly produced GlobalLand30 maps. GlobalLand30 detected land surface water areas show a 91.9% overlap with the reference data, while the coarser resolution products are restricted to lower accuracies. Validation is extended to the drainage network elements, i.e., rivers and streams, where GlobalLand30 outperforms the other global map products, as well.

Land survey map of air pollutants

International Nuclear Information System (INIS)

Hadzi-Mishev, Dimitar

1996-01-01

The first step toward finding a solution to the problems with air pollution is the realization of a land survey map of polluters and a constant acquisition of data from periodical controls of emission of harmful materials, which will be carried out with a determined dynamic. Such a land survey map is not a project which should be finished within a strict time limit, but is intended to create all conditions for a periodical monitoring of emission of harmful materials from registered polluters in order to make a periodical, exact picture of the quantity of harmful materials, which are conveyed by polluters in certain city, a part of the state or the whole country. (author). 4 ills

New GIS approaches to wild land mapping in Europe

Science.gov (United States)

Steffen Fritz; Steve Carver; Linda See

2000-01-01

This paper outlines modifications and new approaches to wild land mapping developed specifically for the United Kingdom and European areas. In particular, national level reconnaissance and local level mapping of wild land in the UK and Scotland are presented. A national level study for the UK is undertaken, and a local study focuses on the Cairngorm Mountains in...

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,...

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...... 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...... spatial configuration with rectangular parcels contained significantly more vegetation and less impervious surfaces per parcel than newer Radburn-inspired configurations with more quadratic parcels. Correlation analysis showed size of paved access ways to be positively correlated with distance from road...

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

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

Science.gov (United States)

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

2017-11-01

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

Global Land Survey Impervious Mapping Project Web Site

Science.gov (United States)

DeColstoun, Eric Brown; Phillips, Jacqueline

2014-01-01

The Global Land Survey Impervious Mapping Project (GLS-IMP) aims to produce the first global maps of impervious cover at the 30m spatial resolution of Landsat. The project uses Global Land Survey (GLS) Landsat data as its base but incorporates training data generated from very high resolution commercial satellite data and using a Hierarchical segmentation program called Hseg. The web site contains general project information, a high level description of the science, examples of input and output data, as well as links to other relevant projects.

Mapping Land Management Regimes in Western Ukraine Using Optical and SAR Data

Directory of Open Access Journals (Sweden)

Jan Stefanski

2014-06-01

Full Text Available The global demand for agricultural products is surging due to population growth, more meat-based diets, and the increasing role of bioenergy. Three strategies can increase agricultural production: (1 expanding agriculture into natural ecosystems; (2 intensifying existing farmland; or (3 recultivating abandoned farmland. Because agricultural expansion entails substantial environmental trade-offs, intensification and recultivation are currently gaining increasing attention. Assessing where these strategies may be pursued, however, requires improved spatial information on land use intensity, including where farmland is active and fallow. We developed a framework to integrate optical and radar data in order to advance the mapping of three farmland management regimes: (1 large-scale, mechanized agriculture; (2 small-scale, subsistence agriculture; and (3 fallow or abandoned farmland. We applied this framework to our study area in western Ukraine, a region characterized by marked spatial heterogeneity in management intensity due to the legacies from Soviet land management, the breakdown of the Soviet Union in 1991, and the recent integration of this region into world markets. We mapped land management regimes using a hierarchical, object-based framework. Image segmentation for delineating objects was performed by using the Superpixel Contour algorithm. We then applied Random Forest classification to map land management regimes and validated our map using randomly sampled in-situ data, obtained during an extensive field campaign. Our results showed that farmland management regimes were mapped reliably, resulting in a final map with an overall accuracy of 83.4%. Comparing our land management regimes map with a soil map revealed that most fallow land occurred on soils marginally suited for agriculture, but some areas within our study region contained considerable potential for recultivation. Overall, our study highlights the potential for an improved

Soil mapping and processes modelling for sustainable land management: a review

Science.gov (United States)

Pereira, Paulo; Brevik, Eric; Muñoz-Rojas, Miriam; Miller, Bradley; Smetanova, Anna; Depellegrin, Daniel; Misiune, Ieva; Novara, Agata; Cerda, Artemi

2017-04-01

Soil maps and models are fundamental for a correct and sustainable land management (Pereira et al., 2017). They are an important in the assessment of the territory and implementation of sustainable measures in urban areas, agriculture, forests, ecosystem services, among others. Soil maps represent an important basis for the evaluation and restoration of degraded areas, an important issue for our society, as consequence of climate change and the increasing pressure of humans on the ecosystems (Brevik et al. 2016; Depellegrin et al., 2016). The understanding of soil spatial variability and the phenomena that influence this dynamic is crucial to the implementation of sustainable practices that prevent degradation, and decrease the economic costs of soil restoration. In this context, soil maps and models are important to identify areas affected by degradation and optimize the resources available to restore them. Overall, soil data alone or integrated with data from other sciences, is an important part of sustainable land management. This information is extremely important land managers and decision maker's implements sustainable land management policies. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. References Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. (2016) Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274. Depellegrin, D.A., Pereira, P., Misiune, I., Egarter-Vigl, L. (2016) Mapping Ecosystem Services in Lithuania. International Journal of Sustainable Development and World Ecology, 23, 441-455. Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B., Smetanova, A., Depellegrin, D., Misiune, I., Novara, A., Cerda, A. (2017) Soil mapping and process modelling for sustainable land management. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B

Mapping Ecosystem Services for Land Use Planning, the Case of Central Kalimantan

Science.gov (United States)

Sumarga, Elham; Hein, Lars

2014-07-01

Indonesia is subject to rapid land use change. One of the main causes for the conversion of land is the rapid expansion of the oil palm sector. Land use change involves a progressive loss of forest cover, with major impacts on biodiversity and global CO2 emissions. Ecosystem services have been proposed as a concept that would facilitate the identification of sustainable land management options, however, the scale of land conversion and its spatial diversity pose particular challenges in Indonesia. The objective of this paper is to analyze how ecosystem services can be mapped at the provincial scale, focusing on Central Kalimantan, and to examine how ecosystem services maps can be used for a land use planning. Central Kalimantan is subject to rapid deforestation including the loss of peatland forests and the provincial still lacks a comprehensive land use plan. We examine how seven key ecosystem services can be mapped and modeled at the provincial scale, using a variety of models, and how large scale ecosystem services maps can support the identification of options for sustainable expansion of palm oil production.

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.

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

International Nuclear Information System (INIS)

Wong, S N; Sarker, M L R

2014-01-01

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

Using indigenous knowledge to link hyper-temporal land cover mapping with land use in the Venezuelan Amazon: "The Forest Pulse".

Science.gov (United States)

Olivero, Jesús; Ferri, Francisco; Acevedo, Pelayo; Lobo, Jorge M; Fa, John E; Farfán, Miguel Á; Romero, David; Real, Raimundo

2016-12-01

Remote sensing and traditional ecological knowledge (TEK) can be combined to advance conservation of remote tropical regions, e.g. Amazonia, where intensive in situ surveys are often not possible. Integrating TEK into monitoring and management of these areas allows for community participation, as well as for offering novel insights into sustainable resource use. In this study, we developed a 250 m resolution land-cover map of the Western Guyana Shield (Venezuela) based on remote sensing, and used TEK to validate its relevance for indigenous livelihoods and land uses. We first employed a hyper-temporal remotely sensed vegetation index to derive a land classification system. During a 1 300 km, eight day fluvial expedition in roadless areas in the Amazonas State (Venezuela), we visited six indigenous communities who provided geo-referenced data on hunting, fishing and farming activities. We overlaid these TEK data onto the land classification map, to link land classes with indigenous use. We characterized land classes using patterns of greenness temporal change and topo-hydrological information, and proposed 12 land-cover types, grouped into five main landscapes: 1) water bodies; 2) open lands/forest edges; 3) evergreen forests; 4) submontane semideciduous forests, and 5) cloud forests. Each land cover class was identified with a pulsating profile describing temporal changes in greenness, hence we labelled our map as "The Forest Pulse". These greenness profiles showed a slightly increasing trend, for the period 2000 to 2009, in the land classes representing grassland and scrubland, and a slightly decreasing trend in the classes representing forests. This finding is consistent with a gain in carbon in grassland as a consequence of climate warming, and also with some loss of vegetation in the forests. Thus, our classification shows potential to assess future effects of climate change on landscape. Several classes were significantly connected with agriculture, fishing

MAPS Appraisal Report Form

CERN Multimedia

HR Department

2005-01-01

As announced in Weekly Bulletin 48/2004, from now onwards, the paper MAPS appraisal report form has been replaced by an electronic form, which is available via EDH (on the EDH desktop under Other Tasks / HR & Training) No changes have been made to the contents of the form. Practical information will be available on the web page http://cern.ch/ais/projs/forms/maps/info.htm, and information meetings will be held on the following dates: 18 January 2005: MAIN AUDITORIUM (500-1-001) from 14:00 to 15:30. 20 January 2005: AB AUDITORIUM II (864-1-D02) from14:00 to 15:30. 24 January 2005: AT AUDITORIUM (30-7-018) from 10:00 to 11:30. Human Resources Department Tel. 73566

Image Analysis for Facility Siting: a Comparison of Lowand High-altitude Image Interpretability for Land Use/land Cover Mapping

Science.gov (United States)

Borella, H. M.; Estes, J. E.; Ezra, C. E.; Scepan, J.; Tinney, L. R.

1982-01-01

For two test sites in Pennsylvania the interpretability of commercially acquired low-altitude and existing high-altitude aerial photography are documented in terms of time, costs, and accuracy for Anderson Level II land use/land cover mapping. Information extracted from the imagery is to be used in the evaluation process for siting energy facilities. Land use/land cover maps were drawn at 1:24,000 scale using commercially flown color infrared photography obtained from the United States Geological Surveys' EROS Data Center. Detailed accuracy assessment of the maps generated by manual image analysis was accomplished employing a stratified unaligned adequate class representation. Both 'area-weighted' and 'by-class' accuracies were documented and field-verified. A discrepancy map was also drawn to illustrate differences in classifications between the two map scales. Results show that the 1:24,000 scale map set was more accurate (99% to 94% area-weighted) than the 1:62,500 scale set, especially when sampled by class (96% to 66%). The 1:24,000 scale maps were also more time-consuming and costly to produce, due mainly to higher image acquisition costs.

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

NARCIS (Netherlands)

Batista e Silva, F.; Lavalle, C.; Koomen, E.

2013-01-01

Available land use/cover maps differ in their spatial extent and in their thematic, spatial, and temporal resolutions. Due to the costs of producing such maps, there is usually a trade-off between spatial extent and resolution. The only European-wide, consistent, and multi-temporal land use/cover

Its4land - Challenges and Opportunities in Developing Innovative Geospatial Tools for Fit-For-Purpose Land Rights Mapping

NARCIS (Netherlands)

Koeva, M.N.; Crommelinck, S.; Stöcker, Claudia; Crompvoets, J.

2018-01-01

Mapping millions of unrecorded land rights in large parts of Sub-Saharan Africa remains a challenge. The results of many existing ICT-based approaches for recording these rights have often proven to be inappropriate; therefore, a new generation of tools needs to be developed to map land rights

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

The Interpretation of Urban Land Use Maps

Science.gov (United States)

Robinson, Roger J.

1973-01-01

Three steps in urban land use analysis, fieldwork mapping, processing of data, and classification and delimitation of zones in an urban area, are described. An appendix presents a classification of buildings by function. (KM)

Meta-Analysis of Land Use / Land Cover Change Factors in the Conterminous US and Prediction of Potential Working Timberlands in the US South from FIA Inventory Plots and NLCD Cover Maps

Science.gov (United States)

Jeuck, James A.

-analysis provides insight into the general success of econometric independent variables for future forest use or cover change research. The second part of this dissertation developed a method for predicting area estimates and spatial distribution of PWT in the US South. This technique determined land use from USFS Forest Inventory and Analysis (FIA) and land cover from the National Land Cover Database (NLCD). Three dependent variable forms (DV Forms) were derived from the FIA data: DV Form 1, timberland, other; DV Form 2, short timberland, tall timberland, agriculture, other; and DV Form 3, short hardwood (HW) timberland, tall HW timberland, short softwood (SW) timberland, tall SW timberland, agriculture, other. The prediction accuracy of each DV Form was investigated using both random forest model and logistic regression model specifications and data optimization techniques. Model verification employing a "leave-group-out" Monte Carlo simulation determined the selection of a stratified version of the random forest model using one-year NLCD observations with an overall accuracy of 0.53-0.94. The lower accuracy side of the range was when predictions were made from an aggregated NLCD land cover class "grass_shrub". The selected model specification was run using 2011 NLCD and the other predictor variables to produce three levels of timberland prediction and probability maps for the US South. Spatial masks removed areas unlikely to be working forests (protected and urbanized lands) resulting in PWT maps. The area of the resulting maps compared well with USFS area estimates and masked PWT maps and had an 8-11% reduction of the USFS timberland estimate for the US South compared to the DV Form. Change analysis of the 2011 NLCD to PWT showed (1) the majority of the short timberland came from NLCD grass_shrub; (2) the majority of NLCD grass_shrub predicted into tall timberland, and (3) NLCD grass_shrub was more strongly associated with timberland in the Coastal Plain. Resulting map products

Mapping land use changes in the carboniferous region of Santa Catarina, report 2

Science.gov (United States)

Valeriano, D. D. (Principal Investigator); Bitencourtpereira, M. D.

1983-01-01

The techniques applied to MSS-LANDSAT data in the land-use mapping of Criciuma region (Santa Catarina state, Brazil) are presented along with the results of a classification accuracy estimate tested on the resulting map. The MSS-LANDSAT data digital processing involves noise suppression, features selection and a hybrid classifier. The accuracy test is made through comparisons with aerial photographs of sampled points. The utilization of digital processing to map the classes agricultural lands, forest lands and urban areas is recommended, while the coal refuse areas should be mapped visually.

Image analysis for facility siting: a comparison of low- and high-altitude image interpretability for land use/land cover mapping

International Nuclear Information System (INIS)

Borella, H.M.; Estes, J.E.; Ezra, C.E.; Scepan, J.; Tinney, L.R.

1982-01-01

For two test sites in Pennsylvania the interpretability of commercially acquired low-altitude and existing high-altitude aerial photography are documented in terms of time, costs, and accuracy for Anderson Level II land use/land cover mapping. Information extracted from the imagery is to be used in the evaluation process for siting energy facilities. Land use/land cover maps were drawn at 1:24,000 scale using commercially flown color infrared photography obtained from the United States Geological Surveys' EROS Data Center. Detailed accuracy assessment of the maps generated by manual image analysis was accomplished employing a stratified unaligned adequate class representation. Both are-weighted and by-class accuracies were documented and field-verified. A discrepancy map was also drawn to illustrate differences in classifications between the two map scales. Results show that the 1:24,000 scale map set was accurate (99% to 94% area-weighted) than the 1:62,500 scale set, especially when sampled by class (96% to 66%). The 1:24,000 scale maps were also more time-consuming and costly to produce, due mainly to higher image acquisition costs

Rapid Land Cover Map Updates Using Change Detection and Robust Random Forest Classifiers

Directory of Open Access Journals (Sweden)

Konrad J. Wessels

2016-10-01

Full Text Available The paper evaluated the Landsat Automated Land Cover Update Mapping (LALCUM system designed to rapidly update a land cover map to a desired nominal year using a pre-existing reference land cover map. The system uses the Iteratively Reweighted Multivariate Alteration Detection (IRMAD to identify areas of change and no change. The system then automatically generates large amounts of training samples (n > 1 million in the no-change areas as input to an optimized Random Forest classifier. Experiments were conducted in the KwaZulu-Natal Province of South Africa using a reference land cover map from 2008, a change mask between 2008 and 2011 and Landsat ETM+ data for 2011. The entire system took 9.5 h to process. We expected that the use of the change mask would improve classification accuracy by reducing the number of mislabeled training data caused by land cover change between 2008 and 2011. However, this was not the case due to exceptional robustness of Random Forest classifier to mislabeled training samples. The system achieved an overall accuracy of 65%–67% using 22 detailed classes and 72%–74% using 12 aggregated national classes. “Water”, “Plantations”, “Plantations—clearfelled”, “Orchards—trees”, “Sugarcane”, “Built-up/dense settlement”, “Cultivation—Irrigated” and “Forest (indigenous” had user’s accuracies above 70%. Other detailed classes (e.g., “Low density settlements”, “Mines and Quarries”, and “Cultivation, subsistence, drylands” which are required for operational, provincial-scale land use planning and are usually mapped using manual image interpretation, could not be mapped using Landsat spectral data alone. However, the system was able to map the 12 national classes, at a sufficiently high level of accuracy for national scale land cover monitoring. This update approach and the highly automated, scalable LALCUM system can improve the efficiency and update rate of regional land

Land-use mapping for the State of Kuwait using the Geographical Information System (Gigs)

International Nuclear Information System (INIS)

Omar, S.A.S.; Misak, R.; Minkarah, H.; King, P.; Kwarting, A.; Abo-Rizq, H.; Roy, W.

2001-01-01

A land-use survey was undertaken at a scale 1:100000 for the State of Kuwait. Land use is classified into 19 map units based on field survey and interpretation of Landsat imagery. The latest topographic map coverage for the State of Kuwait was used as a base map. The Geographic Information System (GIS) was used for the storage, analysis and presentation of spatial data. Summary statistics of total areas of each map unit are presented in nine 1:100.000map sheets and percentage areas of different land uses were identified. Land use is dominated by rangeland (75.12%) which is used primarily for grazing activities, and also recreational activities such as spring camping and hunting. Oil fields (7%) include areas of existing development of wells and associated infrastructure. Water reservoir areas represent the surficial extent of aquifers and natural water fields. Military areas (4%) are scattered throughout the country. Other significant land uses include the build-up areas of Kuwait city (3.5%), quarries, borrow pits and dumps of building debris, communication facilities, cemeteries, parkland, encampments, power stations, race tracks and unused land (7%). Land use information can be used as the basis for future land use planning applications. (author)

Well location and land-use mapping in the Columbia Plateau area

International Nuclear Information System (INIS)

Stephan, J.; Foote, H.; Coburn, V.

1979-10-01

Irrigation wells in a 41,000-square mile area located in Washington and northern Oregon were the subject of this study. Approximately 30,000 square miles of the area were mapped within the boundary of the Columbia Plateau, which covers some 48,200 square miles in the states of Washington, Oregon, and Idaho. Advanced state-of-the-art computer analysis techniques for processing Landsat digital multispectral data were used for mapping the area into ten land-use classes. Specially designed computer programs were used for mapping the locations of 1476 irrigation wells located in 13 counties. Six thematic color-encoded maps were prepared which show additional land-use types and relative areal distribution. Three maps depict the location of irrigation wells

Closed forms and multi-moment maps

DEFF Research Database (Denmark)

Madsen, Thomas Bruun; Swann, Andrew Francis

2013-01-01

We extend the notion of multi-moment map to geometries defined by closed forms of arbitrary degree. We give fundamental existence and uniqueness results and discuss a number of essential examples, including geometries related to special holonomy. For forms of degree four, multi-moment maps are gu...

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

Science.gov (United States)

Hagensieker, Ron; Roscher, Ribana; Rosentreter, Johannes; Jakimow, Benjamin; Waske, Björn

2017-12-01

Remote sensing satellite data offer the unique possibility to map land use land cover transformations by providing spatially explicit information. However, detection of short-term processes and land use patterns of high spatial-temporal variability is a challenging task. We present a novel framework using multi-temporal TerraSAR-X data and machine learning techniques, namely discriminative Markov random fields with spatio-temporal priors, and import vector machines, in order to advance the mapping of land cover characterized by short-term changes. Our study region covers a current deforestation frontier in the Brazilian state Pará with land cover dominated by primary forests, different types of pasture land and secondary vegetation, and land use dominated by short-term processes such as slash-and-burn activities. The data set comprises multi-temporal TerraSAR-X imagery acquired over the course of the 2014 dry season, as well as optical data (RapidEye, Landsat) for reference. Results show that land use land cover is reliably mapped, resulting in spatially adjusted overall accuracies of up to 79% in a five class setting, yet limitations for the differentiation of different pasture types remain. The proposed method is applicable on multi-temporal data sets, and constitutes a feasible approach to map land use land cover in regions that are affected by high-frequent temporal changes.

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.

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

Science.gov (United States)

Dirk Pflugmacher; Olga N. Krankina; Warren B. Cohen; Mark A. Friedl; Damien Sulla-Menashe; Robert E. Kennedy; Peder Nelson; Tatiana V. Loboda; Tobias Kuemmerle; Egor Dyukarev; Vladimir Elsadov; Viacheslav I. Kharuk

2011-01-01

Information on land cover at global and continental scales is critical for addressing a range of ecological, socioeconomic and policy questions. Global land cover maps have evolved rapidly in the last decade, but efforts to evaluate map uncertainties have been limited, especially in remote areas like Northern Eurasia. Northern Eurasia comprises a particularly diverse...

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

a unique method for the automatic generation of urban land cover maps. In the present paper, imagery of a new medium-format aerial camera and advanced geoprocessing software are applied to derive normalized digital surface models and vegetation maps. These two intermediate products then become input...... to a tree structured classifier, which automatically derives land cover maps in 2D or 3D. We investigate the thematic accuracy of the produced land cover map by a class-wise stratified design and provide a method for deriving necessary sample sizes. Corresponding survey adjusted accuracy measures...... 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...

Urban Land Use Mapping by Combining Remote Sensing Imagery and Mobile Phone Positioning Data

Directory of Open Access Journals (Sweden)

Yuanxin Jia

2018-03-01

Full Text Available Land use is of great importance for urban planning, environmental monitoring, and transportation management. Several methods have been proposed to obtain land use maps of urban areas, and these can be classified into two categories: remote sensing methods and social sensing methods. However, remote sensing and social sensing approaches have specific disadvantages regarding the description of social and physical features, respectively. Therefore, an appropriate fusion strategy is vital for large-area land use mapping. To address this issue, we propose an efficient land use mapping method that combines remote sensing imagery (RSI and mobile phone positioning data (MPPD for large areas. We implemented this method in two steps. First, a support vector machine was adopted to classify the RSI and MPPD. Then, the two classification results were fused using a decision fusion strategy to generate the land use map. The proposed method was applied to a case study of the central area of Beijing. The experimental results show that the proposed method improved classification accuracy compared with that achieved using MPPD alone, validating the efficacy of this new approach for identifying land use. Based on the land use map and MPPD data, activity density in key zones during daytime and nighttime was analyzed to illustrate the volume and variation of people working and living across different regions.

Map-based multicriteria analysis to support interactive land use allocation

NARCIS (Netherlands)

Arciniegas Lopez, G.A.; Janssen, R.; Omtzigt, A.Q.A.

2011-01-01

This article focuses on the use of map-based multicriteria analysis to develop a negotiation support tool for land use allocation. Spatial multicriteria analysis is used to make explicit trade-offs between objectives and to provide guidance and feedback on the land use changes negotiated by the

Land subsidence susceptibility and hazard mapping: the case of Amyntaio Basin, Greece

Science.gov (United States)

Tzampoglou, P.; Loupasakis, C.

2017-09-01

Landslide susceptibility and hazard mapping has been applying for more than 20 years succeeding the assessment of the landslide risk and the mitigation the phenomena. On the contrary, equivalent maps aiming to study and mitigate land subsidence phenomena caused by the overexploitation of the aquifers are absent from the international literature. The current study focuses at the Amyntaio basin, located in West Macedonia at Florina prefecture. As proved by numerous studies the wider area has been severely affected by the overexploitation of the aquifers, caused by the mining and the agricultural activities. The intensive ground water level drop has triggered extensive land subsidence phenomena, especially at the perimeter of the open pit coal mine operating at the site, causing damages to settlements and infrastructure. The land subsidence susceptibility and risk maps were produced by applying the semi-quantitative WLC (Weighted Linear Combination) method, especially calibrated for this particular catastrophic event. The results were evaluated by using detailed field mapping data referring to the spatial distribution of the surface ruptures caused by the subsidence. The high correlation between the produced maps and the field mapping data, have proved the great value of the maps and of the applied technique on the management and the mitigation of the phenomena. Obviously, these maps can be safely used by decision-making authorities for the future urban safety development.

SAR China Land Mapping Project: Development, Production and Potential Applications

International Nuclear Information System (INIS)

Zhang, Lu; Guo, Huadong; Liu, Guang; Fu, Wenxue; Yan, Shiyong; Song, Rui; Ji, Peng; Wang, Xinyuan

2014-01-01

Large-area, seamless synthetic aperture radar (SAR) mosaics can reflect overall environmental conditions and highlight general trends in observed areas from a macroscopic standpoint, and effectively support research at the global scale, which is in high demand now across scientific fields. The SAR China Land Mapping Project (SCLM), supported by the Digital Earth Science Platform Project initiated and managed by the Center for Earth Observation and Digital Earth, Chinese Academy of Sciences (CEODE), is introduced in this paper. This project produced a large-area SAR mosaic dataset and generated the first complete seamless SAR map covering the entire land area of China using EnviSat-ASAR images. The value of the mosaic map is demonstrated by some potential applications in studies of urban distribution, rivers and lakes, geologic structures, geomorphology and paleoenvironmental change

A Continuously Updated, Global Land Classification Map, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — We propose to demonstrate a fully automatic capability for generating a global, high resolution (30 m) land classification map, with continuous updates from...

Risk-maps informing land-use planning processes

International Nuclear Information System (INIS)

Basta, Claudia; Neuvel, Jeroen M.M.; Zlatanova, Sisi; Ale, Ben

2007-01-01

The definition of safety distances as required by Art 12 of the Seveso II Directive on dangerous substances (96/82/EC) is necessary to minimize the consequences of potential major accidents. As they affect the land-use destinations of involved areas, safety distances can be considered as risk tolerability criteria with a territorial reflection. Recent studies explored the suitability of using Geographical Information System technologies to support their elaboration and visual rendering. In particular, the elaboration of GIS 'risk-maps' has been recognized as functional to two objectives: connecting spatial planners and safety experts during decision making processes and communicating risk to non-experts audiences. In order to elaborate on these findings and to verify their reflection on European practices, the article presents the result of a comparative study between the United Kingdom and the Netherlands recent developments. Their land-use planning practices for areas falling under Seveso II requirements are explored. The role of GIS risk-maps within decisional processes is analyzed and the reflection on the transparency and accessibility of risk-information is commented. Recommendations for further developments are given

FORMS OF DEVELOPMENT AND LAND TENURE AS IMPROVEMENT TOOLS OF land use planning IN UKRAINE

Directory of Open Access Journals (Sweden)

Tretyak A.M.

2016-05-01

Full Text Available Transformations which take place now in the the economy of Ukraine, and in particular in agriculture considerably exacerbated organizational and legal problems and organizational and territorial forms of local agricultural enterprises, protection of land ownership rights. Transformation of land relations violated the the traditional forms of organization of agricultural production, reduced the efficiency of capital investmenst in improvement of using and protection of land. Therefore, to improve the efficiency of agricultural land use in conditions of formation of market economy, general urgent of time is an in-depth analysis of the types and forms of land use which have found their consolidation at the legislative level. Land management is carried out throughout the country. It enveloped lands irrespective of unequivocal purpose, ownership and the character of using. But goals and objectives of land management, it’s content may be different. An important feature of land management are and it’s types. The current Land Code of Ukraineas the the Law of Ukraine "On Land Management" don’t contain legislative provisions on division of land management for certain types. Meanwhile, it should be noted, that normative and legal acts on land management of the Soviet period (Fundamentals of land legislation of the USSR and the United Republics 1968. Land codes 1978., 1990, 1992 there are two separate types of it - intereconomic (Modern terminology of A.M. Tretyak - territorial and internaleconomic. Modern practice of the actions in the field of land management as evidenced by about the existence of another and a third type of land management – separational. Each of them is characterized by a specific purpose, carried out at different levels. It would therefore be appropriate, hat separate species of land management und their consolidation and in legislation level. Given that the process of implementation of land management for the object of land

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).

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 ...

Terrain classification and land hazard mapping in Kalsi-Chakrata area (Garhwal Himalaya), India

Science.gov (United States)

Choubey, Vishnu D.; Litoria, Pradeep K.

Terrain classification and land system mapping of a part of the Garhwal Himalaya (India) have been used to provide a base map for land hazard evaluation, with special reference to landslides and other mass movements. The study was based on MSS images, aerial photographs and 1:50,000 scale maps, followed by detailed field-work. The area is composed of two groups of rocks: well exposed sedimentary Precambrian formations in the Himalayan Main Boundary Thrust Belt and the Tertiary molasse deposits of the Siwaliks. Major tectonic boundaries were taken as the natural boundaries of land systems. A physiographic terrain classification included slope category, forest cover, occurrence of landslides, seismicity and tectonic activity in the area.

Soil Carbon Mapping in Low Relief Areas with Combined Land Use Types and Percentages

Science.gov (United States)

Liu, Y. L.; Wu, Z. H.; Chen, Y. Y.; Wang, B. Z.

2018-05-01

Accurate mapping of soil carbon in low relief areas is of great challenge because of the defect of conventional "soil-landscape" model. Efforts have been made to integrate the land use information in the modelling and mapping of soil organic carbon (SOC), in which the spatial context was ignored. With 256 topsoil samples collected from Jianghan Plain, we aim to (i) explore the land-use dependency of SOC via one-way ANOVA; (ii) investigate the "spillover effect" of land use on SOC content; (iii) examine the feasibility of land use types and percentages (obtained with a 200-meter buffer) for soil mapping via regression Kriging (RK) models. Results showed that the SOC of paddy fields was higher than that of woodlands and irrigated lands. The land use type could explain 20.5 % variation of the SOC, and the value increased to 24.7 % when the land use percentages were considered. SOC was positively correlated with the percentage of water area and irrigation canals. Further research indicated that SOC of irrigated lands was significantly correlated with the percentage of water area and irrigation canals, while paddy fields and woodlands did not show similar trends. RK model that combined land use types and percentages outperformed the other models with the lowest values of RMSEC (5.644 g/kg) and RMSEP (6.229 g/kg), and the highest R2C (0.193) and R2P (0.197). In conclusions, land use types and percentages serve as efficient indicators for the SOC mapping in plain areas. Additionally, irrigation facilities contributed to the farmland SOC sequestration especially in irrigated lands.

Toward accountable land use mapping: Using geocomputation to improve classification accuracy and reveal uncertainty

NARCIS (Netherlands)

Beekhuizen, J.; Clarke, K.C.

2010-01-01

The classification of satellite imagery into land use/cover maps is a major challenge in the field of remote sensing. This research aimed at improving the classification accuracy while also revealing uncertain areas by employing a geocomputational approach. We computed numerous land use maps by

Towards Innovative Geospatial Tools for Fit-For Land Rights Mapping

Science.gov (United States)

Koeva, M.; Bennett, R.; Gerke, M.; Crommelinck, S.; Stöcker, C.; Crompvoets, J.; Ho, S.; Schwering, A.; Chipofya, M.; Schultz, C.; Zein, T.; Biraro, M.; Alemie, B.; Wayumba, R.; Kundert, K.

2017-09-01

In large parts of sub Saharan Africa it remains an ongoing challenging to map millions of unrecognized land rights. Existing approaches for recognizing these rights have proven inappropriate in many cases. A new generation of tools needs to be developed to support faster, cheaper, easier, and more responsible land rights mapping. This is the main goal of its4land, an European Commission Horizon 2020 project that aims to develop innovative tools inspired by the continuum of land rights, fit-for-purpose land administration, and cadastral intelligence. its4land is using strategic collaboration between the EU and East Africa to deliver innovative, scalable, and transferrable ICT solutions. The innovation process incorporates a broad range of stakeholders and emergent geospatial technologies, including smart sketchmaps, UAVs, automated feature extraction, as well as geocloud services. The aim is to combine innovative technologies, capture the specific needs, market opportunities and readiness of end-users in the domain of land tenure information recording in Eastern Africa. The project consists of a four year work plan, € 3.9M funding, and eight consortium partners collaborating with stakeholders from six case study locations in Ethiopia, Kenya, and Rwanda. The major tasks include tool development, prototyping, and demonstration for local, national, regional, and international interest groups. The case locations cover different land uses such as: urban, peri-urban, rural smallholder, and (former) pastoralist. This paper describes the project's activities within the first 18 months and covers barriers discovered, lessons learned and results achieved.

Analytical Retrieval of Global Land Surface Emissivity Maps at AMSR-E passive microwave frequencies

Science.gov (United States)

Norouzi, H.; Temimi, M.; Khanbilvardi, R.

2009-12-01

Land emissivity is a crucial boundary condition in Numerical Weather Prediction (NWP) modeling. Land emissivity is also a key indicator of land surface and subsurface properties. The objective of this study, supported by NOAA-NESDIS, is to develop global land emissivity maps using AMSR-E passive microwave measurements along with several ancillary data. The International Satellite Cloud Climatology Project (ISCCP) database has been used to obtain several inputs for the proposed approach such as land surface temperature, cloud mask and atmosphere profile. The Community Radiative Transfer Model (CRTM) has been used to estimate upwelling and downwelling atmospheric contributions. Although it is well known that correction of the atmospheric effect on brightness temperature is required at higher frequencies (over 19 GHz), our preliminary results have shown that a correction at 10.7 GHz is also necessary over specific areas. The proposed approach is based on three main steps. First, all necessary data have been collected and processed. Second, a global cloud free composite of AMSR-E data and corresponding ancillary images is created. Finally, monthly composting of emissivity maps has been performed. AMSR-E frequencies at 6.9, 10.7, 18.7, 36.5 and 89.0 GHz have been used to retrieve the emissivity. Water vapor information obtained from ISCCP (TOVS data) was used to calculate upwelling, downwelling temperatures and atmospheric transmission in order to assess the consistency of those derived from the CRTM model. The frequent land surface temperature (LST) determination (8 times a day) in the ISCCP database has allowed us to assess the diurnal cycle effect on emissivity retrieval. Differences in magnitude and phase between thermal temperature and low frequencies microwave brightness temperature have been noticed. These differences seem to vary in space and time. They also depend on soil texture and thermal inertia. The proposed methodology accounts for these factors and

Procedure for deriving qualitative contaminant attenuation maps from land type data

CSIR Research Space (South Africa)

Sililo, OTN

2001-01-15

Full Text Available A procedure is presented for deriving qualitative contaminant attenuation maps from available soils information. Unfortunately, in South Africa, no soil map with national coverage exists at a scale larger than 1:2 500 000. However, 1:250 000 land...

Web mapping application of Roman Catholic Church administration in the Czech lands in the early modern period

Directory of Open Access Journals (Sweden)

Pavel Seemann

2017-03-01

Full Text Available Reconstruction of historical spatial relationships is still a topical issue in historical geography. In this respect, the Church history has not been well explored. The parish administration in the Czech lands is evolving since the advent of Christianity in 863, and a number of reforms have passed over the centuries. Significant changes in the administration also underwent during recatholisation of the Czech lands in the 17th and 18thcentury. From this Baroque era, there are written sources which have been preserved, so they can be utilized to reconstruct historical Church administration in the form of web mapping application. The paper briefly introduces methods which were used to build a spatial database filled with historical data. However, the main outcome of this paper is to describe the creation of the web mapping application that provides visualisation of this data. Discussed are topics like cartographic project, choice of map symbols, data generalization for different levels of detail and placement of annotations. Display of cartographic data were performed using the ArcGIS platform, through a combination of map tiles and feature services that are bundled into the application template created in Web AppBuilder.

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

NARCIS (Netherlands)

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

2013-01-01

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

Risk-maps informing land-use planning processes

Energy Technology Data Exchange (ETDEWEB)

Basta, Claudia [DIRC Sustainable Urban Areas, Section of Material Science and Sustainable Construction, Delft University of Technology, Stevinweg 1, 2600 GA, Delft (Netherlands)]. E-mail: c.basta@citg.tudelft.nl; Neuvel, Jeroen M.M. [Land Use Planning, Wageningen University, Droevendaalsesteeg 3, Postbus 47, 6700 AA Wageningen (Netherlands)]. E-mail: jeroen.neuvel@wur.nl; Zlatanova, Sisi [Section GISt, OTB Research Institute for Housing, Urban and Mobility Studies, Delft University of Technology, Jaffalaan 9, P.O. Box 5030, 2600 GA, Delft (Netherlands)]. E-mail: s.zlatanova@otb.tudelft.nl; Ale, Ben [Safety Science Group, TBM Faculty, Delft University of Technology, Jaffalaan 5, 2600 GA, Delft (Netherlands)

2007-06-25

The definition of safety distances as required by Art 12 of the Seveso II Directive on dangerous substances (96/82/EC) is necessary to minimize the consequences of potential major accidents. As they affect the land-use destinations of involved areas, safety distances can be considered as risk tolerability criteria with a territorial reflection. Recent studies explored the suitability of using Geographical Information System technologies to support their elaboration and visual rendering. In particular, the elaboration of GIS 'risk-maps' has been recognized as functional to two objectives: connecting spatial planners and safety experts during decision making processes and communicating risk to non-experts audiences. In order to elaborate on these findings and to verify their reflection on European practices, the article presents the result of a comparative study between the United Kingdom and the Netherlands recent developments. Their land-use planning practices for areas falling under Seveso II requirements are explored. The role of GIS risk-maps within decisional processes is analyzed and the reflection on the transparency and accessibility of risk-information is commented. Recommendations for further developments are given.

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

Generation of Land Cover Maps Using High-Resolution Multispectral Aerial Cameras

DEFF Research Database (Denmark)

Höhle, Joachim

2013-01-01

. The classification had an overall accuracy of 79%. Suggestions for the improvements in the applied methodology are made. The potential of land cover maps lies in updating of topographic databases, quality control of maps, studies of town development, and other geo-spatial domain applications. The automatic...... for classification of land cover. A high degree of automation can be achieved. The obtained results of a practical example are checked with reference values derived from ortho-images in natural colour and from colour images using stereo-vision. An error matrix is applied in the evaluation of the results...

Open land cover from OpenStreetMap and remote sensing

Science.gov (United States)

Schultz, Michael; Voss, Janek; Auer, Michael; Carter, Sarah; Zipf, Alexander

2017-12-01

OpenStreetMap (OSM) tags were used to produce a global Open Land Cover (OLC) product with fractional data gaps available at osmlanduse.org. Data gaps in the global OLC map were filled for a case study in Heidelberg, Germany using free remote sensing data, which resulted in a land cover (LC) prototype with complete coverage in this area. Sixty tags in the OSM were used to allocate a Corine Land Cover (CLC) level 2 land use classification to 91.8% of the study area, and the remaining gaps were filled with remote sensing data. For this case study, complete are coverage OLC overall accuracy was estimated 87%, which performed better than the CLC product (81% overall accuracy) of 2012. Spatial thematic overlap for the two products was 84%. OLC was in large parts found to be more detailed than CLC, particularly when LC patterns were heterogeneous, and outperformed CLC in the classification of 12 of the 14 classes. Our OLC product represented data created in different periods; 53% of the area was 2011-2016, and 46% of the area was representative of 2016-2017.

A Study on remote sensing method for drawing up and utilizing ecological and natural map - concentrated on drawing up of Land Cover Classification Map

Energy Technology Data Exchange (ETDEWEB)

Jun, Sung Woo; Chung, Sung Moon [Korea Environment Institute, Seoul (Korea)

1998-12-01

The drawing up of ecological and natural map, which is highly efficient using remote exploration method, was promoted in this study. As the first step of drawing up of ecological and natural map, this study is working on the drawing up of Land Cover using as a base map. Through the detailed and sufficient consideration on GAP analysis of USA, CORINE project of EU, and examples in Korea, it studied and proposed the Land Cover Classification system and method suitable for Korea. It will be helpful to draw up ecological and natural map by providing two strategies and principles for land cover classification. 26 refs., 33 figs., 9 tabs.

A multi-temporal analysis approach for land cover mapping in support of nuclear incident response

Science.gov (United States)

Sah, Shagan; van Aardt, Jan A. N.; McKeown, Donald M.; Messinger, David W.

2012-06-01

Remote sensing can be used to rapidly generate land use maps for assisting emergency response personnel with resource deployment decisions and impact assessments. In this study we focus on constructing accurate land cover maps to map the impacted area in the case of a nuclear material release. The proposed methodology involves integration of results from two different approaches to increase classification accuracy. The data used included RapidEye scenes over Nine Mile Point Nuclear Power Station (Oswego, NY). The first step was building a coarse-scale land cover map from freely available, high temporal resolution, MODIS data using a time-series approach. In the case of a nuclear accident, high spatial resolution commercial satellites such as RapidEye or IKONOS can acquire images of the affected area. Land use maps from the two image sources were integrated using a probability-based approach. Classification results were obtained for four land classes - forest, urban, water and vegetation - using Euclidean and Mahalanobis distances as metrics. Despite the coarse resolution of MODIS pixels, acceptable accuracies were obtained using time series features. The overall accuracies using the fusion based approach were in the neighborhood of 80%, when compared with GIS data sets from New York State. The classifications were augmented using this fused approach, with few supplementary advantages such as correction for cloud cover and independence from time of year. We concluded that this method would generate highly accurate land maps, using coarse spatial resolution time series satellite imagery and a single date, high spatial resolution, multi-spectral image.

Updating the Geologic Maps of the Apollo 15, 16, and 17 Landing Sites

Science.gov (United States)

Garry, W. B.; Mest, S. C.; Yingst, R. A.; Ostrach, L. R.; Petro, N. E.; Cohen, B. A.

2018-06-01

Our team is funded through NASA's Planetary Data Archiving, Restoration, and Tools (PDART) program to produce two new USGS Special Investigation Maps (SIM) for the Apollo 15, 16, and 17 missions: a regional map (1:200K) and a landing-site map (1:24K).

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

International Nuclear Information System (INIS)

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

1991-01-01

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

Application of Google Maps API service for creating web map of information retrieved from CORINE land cover databases

Directory of Open Access Journals (Sweden)

Kilibarda Milan

2010-01-01

Full Text Available Today, Google Maps API application based on Ajax technology as standard web service; facilitate users with publication interactive web maps, thus opening new possibilities in relation to the classical analogue maps. CORINE land cover databases are recognized as the fundamental reference data sets for numerious spatial analysis. The theoretical and applicable aspects of Google Maps API cartographic service are considered on the case of creating web map of change in urban areas in Belgrade and surround from 2000. to 2006. year, obtained from CORINE databases.

TOWARDS INNOVATIVE GEOSPATIAL TOOLS FOR FIT-FOR-PURPOSE LAND RIGHTS MAPPING

Directory of Open Access Journals (Sweden)

M. Koeva

2017-09-01

Full Text Available In large parts of sub Saharan Africa it remains an ongoing challenging to map millions of unrecognized land rights. Existing approaches for recognizing these rights have proven inappropriate in many cases. A new generation of tools needs to be developed to support faster, cheaper, easier, and more responsible land rights mapping. This is the main goal of its4land, an European Commission Horizon 2020 project that aims to develop innovative tools inspired by the continuum of land rights, fit-for-purpose land administration, and cadastral intelligence. its4land is using strategic collaboration between the EU and East Africa to deliver innovative, scalable, and transferrable ICT solutions. The innovation process incorporates a broad range of stakeholders and emergent geospatial technologies, including smart sketchmaps, UAVs, automated feature extraction, as well as geocloud services. The aim is to combine innovative technologies, capture the specific needs, market opportunities and readiness of end-users in the domain of land tenure information recording in Eastern Africa. The project consists of a four year work plan, € 3.9M funding, and eight consortium partners collaborating with stakeholders from six case study locations in Ethiopia, Kenya, and Rwanda. The major tasks include tool development, prototyping, and demonstration for local, national, regional, and international interest groups. The case locations cover different land uses such as: urban, peri-urban, rural smallholder, and (former pastoralist. This paper describes the project’s activities within the first 18 months and covers barriers discovered, lessons learned and results achieved.

Mapping the global land surface using 1 km AVHRR data

Science.gov (United States)

Lauer, D.T.; Eidenshink, J.C.

1998-01-01

The scientific requirements for mapping the global land surface using 1 km advanced very high resolution radiometer (AVHRR) data have been set forth by the U.S. Global Change Research Program; the International Geosphere Biosphere Programme (IGBP); The United Nations; the National Oceanic and Atmospheric Administration (NOAA); the Committee on Earth Observations Satellites; and the National Aeronautics and Space Administration (NASA) mission to planet Earth (MTPE) program. Mapping the global land surface using 1 km AVHRR data is an international effort to acquire, archive, process, and distribute 1 km AVHRR data to meet the needs of the international science community. A network of AVHRR receiving stations, along with data recorded by NOAA, has been acquiring daily global land coverage since April 1, 1992. A data set of over 70,000 AVHRR images is archived and distributed by the United States Geological Survey (USGS) EROS Data Center, and the European Space Agency. Under the guidance of the IGBP, processing standards have been developed for calibration, atmospheric correction, geometric registration, and the production of global 10-day maximum normalized difference vegetation index (NDVI) composites. The major uses of the composites are for the study of surface vegetation condition, mapping land cover, and deriving biophysical characteristics of terrestrial ecosystems. A time-series of 54 10-day global vegetation index composites for the period of April 1, 1992 through September 1993 has been produced. The production of a time-series of 33 10-day global vegetation index composites using NOAA-14 data for the period of February 1, 1995 through December 31, 1995 is underway. The data products are available from the USGS, in cooperation with NASA's MTPE program and other international organizations.

Mapping Urban Land Use at Street Block Level Using OpenStreetMap, Remote Sensing Data, and Spatial Metrics

Directory of Open Access Journals (Sweden)

Taïs Grippa

2018-06-01

Full Text Available Up-to-date and reliable land-use information is essential for a variety of applications such as planning or monitoring of the urban environment. This research presents a workflow for mapping urban land use at the street block level, with a focus on residential use, using very-high resolution satellite imagery and derived land-cover maps as input. We develop a processing chain for the automated creation of street block polygons from OpenStreetMap and ancillary data. Spatial metrics and other street block features are computed, followed by feature selection that reduces the initial datasets by more than 80%, providing a parsimonious, discriminative, and redundancy-free set of features. A random forest (RF classifier is used for the classification of street blocks, which results in accuracies of 84% and 79% for five and six land-use classes, respectively. We exploit the probabilistic output of RF to identify and relabel blocks that have a high degree of uncertainty. Finally, the thematic precision of the residential blocks is refined according to the proportion of the built-up area. The output data and processing chains are made freely available. The proposed framework is able to process large datasets, given that the cities in the case studies, Dakar and Ouagadougou, cover more than 1000 km2 in total, with a spatial resolution of 0.5 m.

Creation and cessation of the land ownership right - legal forms

OpenAIRE

Celerýn, Jakub

2009-01-01

I chose for my diploma thesis the theme which is called "Creation and cessation of the land ownership right - legal forms". The aim of the work is to give complex and complete description of basic legal forms of acquiring ownership right to land. The presented work is divided into ten chapters. The first part (second chapter) of the diploma thesis determines the concepts of "ownership", "real estate", "land", "plot" etc. According to Czech law concept of "real estate" means mainly under groun...

Techniques for the creation of land use maps and tabulations from Landsat imagery

Science.gov (United States)

Angelici, G. L.; Bryant, N. A.

1977-01-01

Methods for creating color thematic maps and land use tabulations, employing both Landsat imagery and computer image processing, are discussed. The system, the Multiple Input Land Use System (MILUS) has been tested in the metropolitan section of Dayton, Ohio. Training areas for land use were first digitized by coordinates and then transformed onto an image of white lines on a black background. This image was added to a Landsat image of the same area. Then multispectral classification was performed. A tape of digitized census tract boundaries was computer interfaced to yield an image of tract boundaries on a background registered to the thematic land-use map. Using a data management system, the data were then used to produce figures for the area and percent of land use in each tract. Future work is expected to convert most of the steps into interactive processing. This would greatly reduce the time needed to edit and register the data sets.

Digital soil mapping in assessment of land suitability for organic farming

Science.gov (United States)

Ghambashidze, Giorgi; Kentchiashvili, Naira; Tarkhnishvili, Maia; Jolokhava, Tamar; Meskhi, Tea

2017-04-01

Digital soil mapping (DSM) is a fast-developing sub discipline of soil science which gets more importance along with increased availability of spatial data. DSM is based on three main components: the input in the form of field and laboratory observational methods, the process used in terms of spatial and non-spatial soil inference systems, and the output in the form of spatial soil information systems, which includes outputs in the form of rasters of prediction along with the uncertainty of prediction. Georgia is one of the countries who are under the way of spatial data infrastructure development, which includes soil related spatial data also. Therefore, it is important to demonstrate the capacity of DSM technics for planning and decision making process, in which assessment of land suitability is a major interest for those willing to grow agricultural crops. In that term land suitability assessment for establishing organic farms is in high demand as market for organically produced commodities is still increasing. It is the first attempt in Georgia to use DSM to predict areas with potential for organic farming development. Current approach is based on risk assessment of soil pollution with toxic elements (As, Hg, Pb, Cd, Cr) and prediction of bio-availability of those elements to plants on example of the region of Western Georgia, where detailed soil survey was conducted and spatial database of soil was created. The results of the study show the advantages of DSM at early stage assessment and depending on availability and quality of the input data, it can achieve acceptable accuracy.

Using IKONOS and Aerial Videography to Validate Landsat Land Cover Maps of Central African Tropical Rain Forests

Science.gov (United States)

Lin, T.; Laporte, N. T.

2003-12-01

Compared to the traditional validation methods, aerial videography is a relatively inexpensive and time-efficient approach to collect "field" data for validating satellite-derived land cover map over large areas. In particular, this approach is valuable in remote and inaccessible locations. In the Sangha Tri-National Park region of Central Africa, where road access is limited to industrial logging sites, we are using IKONOS imagery and aerial videography to assess the accuracy of Landsat-derived land cover maps. As part of a NASA Land Cover Land Use Change project (INFORMS) and in collaboration with the Wildlife Conservation Society in the Republic of Congo, over 1500km of aerial video transects were collected in the Spring of 2001. The use of MediaMapper software combined with a VMS 200 video mapping system enabled the collection of aerial transects to be registered with geographic locations from a Geographic Positioning System. Video frame were extracted, visually interpreted, and compared to land cover types mapped by Landsat. We addressed the limitations of accuracy assessment using aerial-base data and its potential for improving vegetation mapping in tropical rain forests. The results of the videography and IKONOS image analysis demonstrate the utility of very high resolution imagery for map validation and forest resource assessment.

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

DEFF Research Database (Denmark)

Höhle, Joachim

2014-01-01

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

A large-area, spatially continuous assessment of land cover map error and its impact on downstream analyses.

Science.gov (United States)

Estes, Lyndon; Chen, Peng; Debats, Stephanie; Evans, Tom; Ferreira, Stefanus; Kuemmerle, Tobias; Ragazzo, Gabrielle; Sheffield, Justin; Wolf, Adam; Wood, Eric; Caylor, Kelly

2018-01-01

Land cover maps increasingly underlie research into socioeconomic and environmental patterns and processes, including global change. It is known that map errors impact our understanding of these phenomena, but quantifying these impacts is difficult because many areas lack adequate reference data. We used a highly accurate, high-resolution map of South African cropland to assess (1) the magnitude of error in several current generation land cover maps, and (2) how these errors propagate in downstream studies. We first quantified pixel-wise errors in the cropland classes of four widely used land cover maps at resolutions ranging from 1 to 100 km, and then calculated errors in several representative "downstream" (map-based) analyses, including assessments of vegetative carbon stocks, evapotranspiration, crop production, and household food security. We also evaluated maps' spatial accuracy based on how precisely they could be used to locate specific landscape features. We found that cropland maps can have substantial biases and poor accuracy at all resolutions (e.g., at 1 km resolution, up to ∼45% underestimates of cropland (bias) and nearly 50% mean absolute error (MAE, describing accuracy); at 100 km, up to 15% underestimates and nearly 20% MAE). National-scale maps derived from higher-resolution imagery were most accurate, followed by multi-map fusion products. Constraining mapped values to match survey statistics may be effective at minimizing bias (provided the statistics are accurate). Errors in downstream analyses could be substantially amplified or muted, depending on the values ascribed to cropland-adjacent covers (e.g., with forest as adjacent cover, carbon map error was 200%-500% greater than in input cropland maps, but ∼40% less for sparse cover types). The average locational error was 6 km (600%). These findings provide deeper insight into the causes and potential consequences of land cover map error, and suggest several recommendations for land

Land degradation mapping based on hyperion data in desertification region of northwest China

Science.gov (United States)

Cheng, Penggen; Wu, Jian; Ouyang, Ping; He, Ting

2008-10-01

Desertification is an alarming sign of land degradation in Henshan county of northwest china. Due to the considerable costs of detailed ground surveys of this phenomenon, remote sensing is an appropriate alternative for analyzing and evaluating the risks of the expansion of land degradation. Degradation features can be detected directly or indirectly by using image data. In this paper, based on the Hyperion images of Hengshan desertification region of northwest china, a new algorithm aimed at land degradation mapping, called Land Degradation Index (LDI), was put forward. This new algorithm is based on the classified process. We applied the linear spectral unmixing algorithm with the training samples derived from the formerly classified process so as to find out new endmembers in the RMS error imagine. After that, using neutral net mapping with new training samples, the classified result was gained. In addition, after applying mask processing, the soils were grouped to 3 types (Kappa =0.90): highly degraded soils, moderately degraded soils and slightly degraded soils. By analyzing 3 mapping methods: mixture-classification, the spectral angle mapper and mixturetuned matched filtering, the results suggest that the mixture-classification has the higher accuracy (Kappa=0.7075) than the spectral angle mapper (Kappa=0.5418) and the mixture-tuned matched filter (Kappa=0.6039). As a result, the mixture-classification is selected to carry out Land Degradation Index analysis.

Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid SWAT Hydrologic Modeling

Science.gov (United States)

Spruce, J.; Bolten, J. D.; Srinivasan, R.

2017-12-01

This presentation discusses research to develop Land Use Land Cover (LULC) maps for the Lower Mekong Basin (LMB). Funded by a NASA ROSES Disasters grant, the main objective was to produce updated LULC maps to aid the Mekong River Commission's (MRC's) Soil and Water Assessment Tool (SWAT) hydrologic model. In producing needed LULC maps, temporally processed MODIS monthly NDVI data for 2010 were used as the primary data source for classifying regionally prominent forest and agricultural types. The MODIS NDVI data was derived from processing MOD09 and MYD09 8-day reflectance data with the Time Series Product Tool, a custom software package. Circa 2010 Landsat multispectral data from the dry season were processed into top of atmosphere reflectance mosaics and then classified to derive certain locally common LULC types, such as urban areas and industrial forest plantations. Unsupervised ISODATA clustering was used to derive most LULC classifications. GIS techniques were used to merge MODIS and Landsat classifications into final LULC maps for Sub-Basins (SBs) 1-8 of the LMB. The final LULC maps were produced at 250-meter resolution and delivered to the MRC for use in SWAT modeling for the LMB. A map accuracy assessment was performed for the SB 7 LULC map with 14 classes. This assessment was performed by comparing random locations for sampled LULC types to geospatial reference data such as Landsat RGBs, MODIS NDVI phenologic profiles, high resolution satellite data from Google Map/Earth, and other reference data from the MRC (e.g., crop calendars). LULC accuracy assessment results for SB 7 indicated an overall agreement to reference data of 81% at full scheme specificity. However, by grouping 3 deciduous forest classes into 1 class, the overall agreement improved to 87%. The project enabled updated LULC maps, plus more specific rice types were classified compared to the previous LULC maps. The LULC maps from this project should improve the use of SWAT for modeling

Removing non-urban roads from the National Land Cover Database to create improved urban maps for the United States, 1992-2011

Science.gov (United States)

Soulard, Christopher E.; Acevedo, William; Stehman, Stephen V.

2018-01-01

Quantifying change in urban land provides important information to create empirical models examining the effects of human land use. Maps of developed land from the National Land Cover Database (NLCD) of the conterminous United States include rural roads in the developed land class and therefore overestimate the amount of urban land. To better map the urban class and understand how urban lands change over time, we removed rural roads and small patches of rural development from the NLCD developed class and created four wall-to-wall maps (1992, 2001, 2006, and 2011) of urban land. Removing rural roads from the NLCD developed class involved a multi-step filtering process, data fusion using geospatial road and developed land data, and manual editing. Reference data classified as urban or not urban from a stratified random sample was used to assess the accuracy of the 2001 and 2006 urban and NLCD maps. The newly created urban maps had higher overall accuracy (98.7 percent) than the NLCD maps (96.2 percent). More importantly, the urban maps resulted in lower commission error of the urban class (23 percent versus 57 percent for the NLCD in 2006) with the trade-off of slightly inflated omission error (20 percent for the urban map, 16 percent for NLCD in 2006). The removal of approximately 230,000 km2 of rural roads from the NLCD developed class resulted in maps that better characterize the urban footprint. These urban maps are more suited to modeling applications and policy decisions that rely on quantitative and spatially explicit information regarding urban lands.

Utilization of Historical Maps in the Land Use Change Impact Studies: A Case Study from Myjava River Basin

Directory of Open Access Journals (Sweden)

Valent P.

2016-12-01

Full Text Available The way land is used has a significant impact on many hydrological processes that determine the generation of flood runoff or soil erosion. Advancements in remote sensing which took place in the second half of the 20th century have led to the rise of a new research area focused on analyses of land use changes and their impact on hydrological processes. This study deals with an analysis of the changes in land use over a period of almost three centuries in the Myjava River catchment, which has an outlet at Šaštín-Stráže. In order to obtain information about the way the land was used in the past, three historical mappings representing various periods were used: the first (1st military mapping (1764-1787, second (2nd military mapping (1807-1869, and a military topographic mapping (1953-1957. The historical mappings have been manually vectorised in an ArcGIS environment to identify various land use categories. The historical evolution of land use was further compared with a concurrent land use mapping, which was undertaken in 2010 and exploited remote sensing techniques. The study also quantifies the impact of these changes on the long-term catchment runoff as well as their impact on flows induced by extreme precipitation events. This analysis was performed using the WetSpa distributed hydrological model, which enables the simulation of catchment runoff in a daily time step. The analysis showed that the selected catchment has undergone significant changes in land use, mainly characterized by massive deforestation at the end of the 18th century and land consolidation in the middle of the 20th century induced by communist collectivisation. The hydrological simulations demonstrated that the highest and lowest mean annual runoffs were simulated in the first (1st military mapping and the last (concurrent land use monitoring time intervals respectively with the smallest and largest percentages of forested areas.

Utilization of Historical Maps in the Land Use Change Impact Studies: A Case Study from Myjava River Basin

Science.gov (United States)

Valent, P.; Rončák, P.; Maliariková, M.; Behan, Š.

2016-12-01

The way land is used has a significant impact on many hydrological processes that determine the generation of flood runoff or soil erosion. Advancements in remote sensing which took place in the second half of the 20th century have led to the rise of a new research area focused on analyses of land use changes and their impact on hydrological processes. This study deals with an analysis of the changes in land use over a period of almost three centuries in the Myjava River catchment, which has an outlet at Šaštín-Stráže. In order to obtain information about the way the land was used in the past, three historical mappings representing various periods were used: the first (1st) military mapping (1764-1787), second (2nd) military mapping (1807-1869), and a military topographic mapping (1953-1957). The historical mappings have been manually vectorised in an ArcGIS environment to identify various land use categories. The historical evolution of land use was further compared with a concurrent land use mapping, which was undertaken in 2010 and exploited remote sensing techniques. The study also quantifies the impact of these changes on the long-term catchment runoff as well as their impact on flows induced by extreme precipitation events. This analysis was performed using the WetSpa distributed hydrological model, which enables the simulation of catchment runoff in a daily time step. The analysis showed that the selected catchment has undergone significant changes in land use, mainly characterized by massive deforestation at the end of the 18th century and land consolidation in the middle of the 20th century induced by communist collectivisation. The hydrological simulations demonstrated that the highest and lowest mean annual runoffs were simulated in the first (1st military mapping) and the last (concurrent land use monitoring) time intervals respectively with the smallest and largest percentages of forested areas.

Land use, forest density, soil mapping, erosion, drainage, salinity limitations

Science.gov (United States)

Yassoglou, N. J. (Principal Investigator)

1973-01-01

The author has identified the following significant results. The results of analyses show that it is possible to obtain information of practical significance as follows: (1) A quick and accurate estimate of the proper use of the valuable land can be made on the basis of temporal and spectral characteristics of the land features. (2) A rather accurate delineation of the major forest formations in the test areas was achieved on the basis of spatial and spectral characteristics of the studied areas. The forest stands were separated into two density classes; dense forest, and broken forest. On the basis of ERTS-1 data and the existing ground truth information a rather accurate mapping of the major vegetational forms of the mountain ranges can be made. (3) Major soil formations are mapable from ERTS-1 data: recent alluvial soils; soil on quarternary deposits; severely eroded soil and lithosol; and wet soils. (4) An estimation of cost benefits cannot be made accurately at this stage of the investigation. However, a rough estimate of the ratio of the cost for obtaining the same amount information from ERTS-1 data and from conventional operations would be approximately 1:6 to 1:10, in favor of the ERTS-1.

An automated land-use mapping comparison of the Bayesian maximum likelihood and linear discriminant analysis algorithms

Science.gov (United States)

Tom, C. H.; Miller, L. D.

1984-01-01

The Bayesian maximum likelihood parametric classifier has been tested against the data-based formulation designated 'linear discrimination analysis', using the 'GLIKE' decision and "CLASSIFY' classification algorithms in the Landsat Mapping System. Identical supervised training sets, USGS land use/land cover classes, and various combinations of Landsat image and ancilliary geodata variables, were used to compare the algorithms' thematic mapping accuracy on a single-date summer subscene, with a cellularized USGS land use map of the same time frame furnishing the ground truth reference. CLASSIFY, which accepts a priori class probabilities, is found to be more accurate than GLIKE, which assumes equal class occurrences, for all three mapping variable sets and both levels of detail. These results may be generalized to direct accuracy, time, cost, and flexibility advantages of linear discriminant analysis over Bayesian methods.

Achieving a Sustainable Urban Form through Land Use Optimisation: Insights from Bekasi City’s Land-Use Plan (2010–2030

Directory of Open Access Journals (Sweden)

Rahmadya Trias Handayanto

2017-02-01

Full Text Available Cities worldwide have been trying to achieve a sustainable urban form to handle their rapid urban growth. Many sustainable urban forms have been studied and two of them, the compact city and the eco city, were chosen in this study as urban form foundations. Based on these forms, four sustainable city criteria (compactness, compatibility, dependency, and suitability were considered as necessary functions for land use optimisation. This study presents a land use optimisation as a method for achieving a sustainable urban form. Three optimisation methods (particle swarm optimisation, genetic algorithms, and a local search method were combined into a single hybrid optimisation method for land use in Bekasi city, Indonesia. It was also used for examining Bekasi city’s land-use-plan (2010–2030 after optimising current (2015 and future land use (2030. After current land use optimisation, the score of sustainable city criteria increased significantly. Three important centres of land use (commercial, industrial, and residential were also created through clustering the results. These centres were slightly different from centres of the city plan zones. Additional land uses in 2030 were predicted using a nonlinear autoregressive neural network with external input. Three scenarios were used for allocating these additional land uses including sustainable development, government policy, and business-as-usual. Future land use allocation in 2030 found that the sustainable development scenario showed better performance compared to government policy and business-as-usual scenarios.

Mapping environmental land use conflict potentials and ecosystem services in agricultural watersheds.

Science.gov (United States)

Kim, Ilkwon; Arnhold, Sebastian

2018-07-15

In mountainous watersheds, agricultural land use cause changes in ecosystem services, with trade-offs between crop production and erosion regulation. Management of these watersheds can generate environmental land use conflicts among regional stakeholders with different interests. Although several researches have made a start in mapping land use conflicts between human activities and conservation, spatial assessment of land use conflicts on environmental issues and ecosystem service trade-offs within agricultural areas has not been fully considered. In this study, we went further to map land use conflicts between agricultural preferences for crop production and environmental emphasis on erosion regulation. We applied an agricultural land suitability index, based on multi-criteria analysis, to estimate the spatial preference of agricultural activities, while applying the Revised Universal Soil Loss Equation (RUSLE) to reflect the environmental importance of soil erosion. Then, we classified the agricultural catchment into four levels of land use conflicts (lowest, low, high and highest) according to preference and importance of farmland areas, and we compared the classes by crop type. Soil loss in agricultural areas was estimated as 45.1thayr, and agricultural suitability as 0.873; this indicated that land use conflicts in the catchment could arise between severe soil erosion (environmental importance) and agricultural suitability (land preferences). Dry-field farms are mainly located in areas of low land use conflict level, where land preference outweighs environmental importance. When we applied farmland management scenarios with consideration of services, conversion to highest-conflict areas (Scenario 1) as 7.5% of the total area could reduce soil loss by 24.6%, while fallow land management (Scenario 2) could decrease soil loss 19.4% more than the current scenario (Business as usual). The result could maximize land management plans by extracting issues of spatial

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

and habitat composition and quality. The focus on essential features of the habitat that can be expressed easily and quantitatively for identification and mapping of small but significant changes at a landscape level has resulted in the reintroduction of Raunkiaers plant life form concept from 1907...... of agricultural land use, general land cover and tree and shrub cover of small biotopes), it has not been difficult to integrate the BioHab framework in the SBMP-monitoring system, thus permitting the monitoring system to deliver an additional important European perspective with only very limited extra resources...

The application of remote sensing in detail land use mapping of RDE site, Puspiptek Serpong

International Nuclear Information System (INIS)

Heni Susiati; Habib Subagio

2016-01-01

Land cover mapping and its development has been performed in a detail scale (1:5000) within the radius of 5 km from the center of Experimental Power Reactor (RDE) site at Kawasan Nuklir Serpong (KNS), PUSPIPTEK Serpong. The objective of this study is to establish land cover database in a detail scale 1:5000 as part of the preparation toward RDE development plan and also to complete the land cover map of a scale 1:10.000. The research method is accomplished in several stages, namely data collection and processing of high-resolution satellite imagery and aerial photographs, field surveys, land use analysis within the radius of 300 - 500 m, 1 km, 2 km, 3 km, 4 km and 5 km from the RDE site as well as analysis of land use change by 2014-2015. Satellite image processing is carried out at Center for Land Mapping and Atlas, Badan Informasi Geospasial (BIG). Data processing is done by using ArcGis and Er Mapper software, whereas the satellite image analysis is executed by using Image Analysis as one of tool in ArcGis software. The result shows that KNS land cover outside the radius of 3 km is a dense residential in many places. Analysis of land use change by year 2014- 2015 shows that vast development of residential has occur which demonstrated by the increase of residential area in North-East of PUSPIPTEK. (author)

UAS Mapping as an alternative for land surveying techniques?

Directory of Open Access Journals (Sweden)

L. Devriendt

2014-03-01

Full Text Available Can a UAS mapping technique compete with standard surveying techniques? Since the boom in different RPAS (remotely piloted air system, UAV (unmanned aerial vehicle, or UAS (unmanned aerial system, this is one of the crucial questions when it comes to UAS mappings. Not the looks and feels are important but the reliability, ease-to-use, and accuracy that you get with a system based on hardware and corresponding software. This was also one of the issues that the Dutch Land Registry asked a few months ago aimed at achieving an effective and usable system for updating property boundaries in new-build districts. Orbit GT gave them a ready-made answer: a definitive outcome based on years of research and development in UAS mapping technology and software.

A Joint Land Cover Mapping and Image Registration Algorithm Based on a Markov Random Field Model

Directory of Open Access Journals (Sweden)

Apisit Eiumnoh

2013-10-01

Full Text Available Traditionally, image registration of multi-modal and multi-temporal images is performed satisfactorily before land cover mapping. However, since multi-modal and multi-temporal images are likely to be obtained from different satellite platforms and/or acquired at different times, perfect alignment is very difficult to achieve. As a result, a proper land cover mapping algorithm must be able to correct registration errors as well as perform an accurate classification. In this paper, we propose a joint classification and registration technique based on a Markov random field (MRF model to simultaneously align two or more images and obtain a land cover map (LCM of the scene. The expectation maximization (EM algorithm is employed to solve the joint image classification and registration problem by iteratively estimating the map parameters and approximate posterior probabilities. Then, the maximum a posteriori (MAP criterion is used to produce an optimum land cover map. We conducted experiments on a set of four simulated images and one pair of remotely sensed images to investigate the effectiveness and robustness of the proposed algorithm. Our results show that, with proper selection of a critical MRF parameter, the resulting LCMs derived from an unregistered image pair can achieve an accuracy that is as high as when images are perfectly aligned. Furthermore, the registration error can be greatly reduced.

Land use maps of the Tanana and Purcell Mountain areas, Alaska, based on Earth Resources Technology Satellite imagery

Science.gov (United States)

Anderson, J. H. (Principal Investigator)

1974-01-01

The author has identified the following significant results. ERTS imagery in photographic format was used to make land use maps of two areas of special interest to native corporations under terms of the Alaska Native Claims Settlement Act. Land selections are to be made in these areas, and the maps should facilitate decisions because of their comprehensive presentation of resource distribution information. The ERTS images enabled mapping broadly-defined land use classes in large areas in a comparatively short time. Some aerial photography was used to identify colors and shades of gray on the various images. The 14 mapped land use categories are identified according to the classification system under development by the U.S. Geological Survey. These maps exemplify a series of about a dozen diverse Alaskan areas. The principal resource depicted is vegetation, and clearly shown are vegetation units of special importance, including stands possibly containing trees of commercial grade and stands constituting wildlife habitat.

A high-resolution land-use map; Nogales, Sonora, Mexico

Science.gov (United States)

Norman, Laura M.; Villarreal, Miguel L.; Wallace, Cynthia S.A.; Gil Anaya, Claudia Z.; Diaz Arcos, Israel; Gray, Floyd

2010-01-01

The cities of Nogales, Sonora, and Nogales, Arizona, are located in the Ambos Nogales Watershed, a topographically irregular bowl-shaped area with a northward gradient. Throughout history, residents in both cities have been affected by flooding. Currently, the primary method for regulating this runoff is to build a series of detention basins in Nogales, Sonora. Additionally, the municipality also is considering land-use planning to help mitigate flooding. This paper describes the production of a 10-meter resolution land-use map, derived from 2008 aerial photos of the Nogales, Sonora Watershed for modeling impacts of the detention basin construction and in support of an ?Early Warning Hazard System? for the region.

Spatial land-use inventory, modeling, and projection/Denver metropolitan area, with inputs from existing maps, airphotos, and LANDSAT imagery

Science.gov (United States)

Tom, C.; Miller, L. D.; Christenson, J. W.

1978-01-01

A landscape model was constructed with 34 land-use, physiographic, socioeconomic, and transportation maps. A simple Markov land-use trend model was constructed from observed rates of change and nonchange from photointerpreted 1963 and 1970 airphotos. Seven multivariate land-use projection models predicting 1970 spatial land-use changes achieved accuracies from 42 to 57 percent. A final modeling strategy was designed, which combines both Markov trend and multivariate spatial projection processes. Landsat-1 image preprocessing included geometric rectification/resampling, spectral-band, and band/insolation ratioing operations. A new, systematic grid-sampled point training-set approach proved to be useful when tested on the four orginal MSS bands, ten image bands and ratios, and all 48 image and map variables (less land use). Ten variable accuracy was raised over 15 percentage points from 38.4 to 53.9 percent, with the use of the 31 ancillary variables. A land-use classification map was produced with an optimal ten-channel subset of four image bands and six ancillary map variables. Point-by-point verification of 331,776 points against a 1972/1973 U.S. Geological Survey (UGSG) land-use map prepared with airphotos and the same classification scheme showed average first-, second-, and third-order accuracies of 76.3, 58.4, and 33.0 percent, respectively.

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.

Analysis of multi-temporal SPOT NDVI images for small-scale land-use mapping

NARCIS (Netherlands)

Bie, de C.A.J.M.; Khan, M.R.; Smakhtin, V.U.; Venus, V.; Weir, M.J.C.; Smaling, E.M.A.

2011-01-01

Land-use information is required for a number of purposes such as to address food security issues, to ensure the sustainable use of natural resources and to support decisions regarding food trade and crop insurance. Suitable land-use maps often either do not exist or are not readily available. This

Modification to the MAPS interview process and electronic form

CERN Multimedia

HR Department

2006-01-01

Based on the first year of experience with e-MAPS and the feedback from departmental users, a number of modifications to the MAPS interview process and the form have been introduced for the 2006 exercise. Definition of signatories The top of the form now also shows the name of the group leader and department head. This is especially useful in cases of detachment. Corrections can be made via the MAPS Coordinator. 'Send back' facility The possibility to send the MAPS report one step backwards is only available to the MAPS coordinators, i.e., from group leader to supervisor, from staff member to group leader, and from group leader to staff member. The form should only be sent back to correct factual errors or oversights, and any send backs will be tracked. Link 'training' part to 'training' application When entering a training objective for 2006, a search menu allows selection from various CERN internal training courses or from conferences. It remains important however to first read the description of the...

Modification to the MAPS interview process and electronic form

CERN Multimedia

HR Department

2006-01-01

Based on the first year of experience with e-MAPS and the feedback from departmental users, a number of modifications to the MAPS interview process and form have been introduced for the 2006 exercise. Definition of signatories The top of the form now also shows the name of the Group Leader and Department Head. This is especially useful in cases of detachment. Corrections can be made via the MAPS Coordinator. 'Send back' facility The possibility to send the MAPS report one step backwards, i.e. from Group Leader to supervisor, from Staff Member to Group Leader, and from Group Leader to Staff Member is only available to the MAPS coordinators. The form should only be sent back to correct factual errors or oversights, and any send- backs will be recorded. Link between 'training' part and 'training' application When entering a training objective for 2006, a search menu allows selection from various CERN internal training courses or from conferences. It is still important, however, to first read the descri...

Mapping Urban Green Infrastructure: A Novel Landscape-Based Approach to Incorporating Land Use and Land Cover in the Mapping of Human-Dominated Systems

Directory of Open Access Journals (Sweden)

Matthew Dennis

2018-01-01

Full Text Available Common approaches to mapping green infrastructure in urbanised landscapes invariably focus on measures of land use or land cover and associated functional or physical traits. However, such one-dimensional perspectives do not accurately capture the character and complexity of the landscapes in which urban inhabitants live. The new approach presented in this paper demonstrates how open-source, high spatial and temporal resolution data with global coverage can be used to measure and represent the landscape qualities of urban environments. Through going beyond simple metrics of quantity, such as percentage green and blue cover, it is now possible to explore the extent to which landscape quality helps to unpick the mixed evidence presented in the literature on the benefits of urban nature to human well-being. Here we present a landscape approach, employing remote sensing, GIS and data reduction techniques to map urban green infrastructure elements in a large U.K. city region. Comparison with existing urban datasets demonstrates considerable improvement in terms of coverage and thematic detail. The characterisation of landscapes, using census tracts as spatial units, and subsequent exploration of associations with social–ecological attributes highlights the further detail that can be uncovered by the approach. For example, eight urban landscape types identified for the case study city exhibited associations with distinct socioeconomic conditions accountable not only to quantities but also qualities of green and blue space. The identification of individual landscape features through simultaneous measures of land use and land cover demonstrated unique and significant associations between the former and indicators of human health and ecological condition. The approach may therefore provide a promising basis for developing further insight into processes and characteristics that affect human health and well-being in urban areas, both in the United

Multi-temporal Land Use Mapping of Coastal Wetlands Area using Machine Learning in Google Earth Engine

Science.gov (United States)

Farda, N. M.

2017-12-01

Coastal wetlands provide ecosystem services essential to people and the environment. Changes in coastal wetlands, especially on land use, are important to monitor by utilizing multi-temporal imagery. The Google Earth Engine (GEE) provides many machine learning algorithms (10 algorithms) that are very useful for extracting land use from imagery. The research objective is to explore machine learning in Google Earth Engine and its accuracy for multi-temporal land use mapping of coastal wetland area. Landsat 3 MSS (1978), Landsat 5 TM (1991), Landsat 7 ETM+ (2001), and Landsat 8 OLI (2014) images located in Segara Anakan lagoon are selected to represent multi temporal images. The input for machine learning are visible and near infrared bands, PCA band, invers PCA bands, bare soil index, vegetation index, wetness index, elevation from ASTER GDEM, and GLCM (Harralick) texture, and also polygon samples in 140 locations. There are 10 machine learning algorithms applied to extract coastal wetlands land use from Landsat imagery. The algorithms are Fast Naive Bayes, CART (Classification and Regression Tree), Random Forests, GMO Max Entropy, Perceptron (Multi Class Perceptron), Winnow, Voting SVM, Margin SVM, Pegasos (Primal Estimated sub-GrAdient SOlver for Svm), IKPamir (Intersection Kernel Passive Aggressive Method for Information Retrieval, SVM). Machine learning in Google Earth Engine are very helpful in multi-temporal land use mapping, the highest accuracy for land use mapping of coastal wetland is CART with 96.98 % Overall Accuracy using K-Fold Cross Validation (K = 10). GEE is particularly useful for multi-temporal land use mapping with ready used image and classification algorithms, and also very challenging for other applications.

A procedure for merging land cover/use data from Landsat, aerial photography, and map sources - Compatibility, accuracy and cost

Science.gov (United States)

Enslin, W. R.; Tilmann, S. E.; Hill-Rowley, R.; Rogers, R. H.

1977-01-01

A method is developed to merge land cover/use data from Landsat, aerial photography and map sources into a grid-based geographic information system. The method basically involves computer-assisted categorization of Landsat data to provide certain user-specified land cover categories; manual interpretation of aerial photography to identify other selected land cover/use categories that cannot be obtained from Landsat data; identification of special features from aerial photography or map sources; merging of the interpreted data from all the sources into a computer compatible file under a standardized coding structure; and the production of land cover/use maps, thematic maps, and tabular data. The specific tasks accomplished in producing the merged land cover/use data file and subsequent output products are identified and discussed. It is shown that effective implementation of the merging method is critically dependent on selecting the 'best' data source for each user-specified category in terms of accuracy and time/cost tradeoffs.

Mapping Deforestation and Land Use in Amazon Rainforest Using SAR-C Imagery

Science.gov (United States)

Saatchi, Sasan S.; Soares, Joao Vianei; Alves, Diogenes Salas

1996-01-01

Land use changes and deforestation in tropical rainforests are among the major factors affecting the overall function of the global environment. To routinely assess the spatial extend and temporal dynamics of these changes has become an important challenge in several scientific disciplines such as climate and environmental studies. In this paper, the feasibility of using polarimetric spaceborne SAR data in mapping land cover types in the Amazon is studied.

Land-Use Mapping in a Mixed Urban-Agricultural Arid Landscape Using Object-Based Image Analysis: A Case Study from Maricopa, Arizona

Directory of Open Access Journals (Sweden)

Christopher S. Galletti

2014-06-01

Full Text Available Land-use mapping is critical for global change research. In Central Arizona, U.S.A., the spatial distribution of land use is important for sustainable land management decisions. The objective of this study was to create a land-use map that serves as a model for the city of Maricopa, an expanding urban region in the Sun Corridor of Arizona. We use object-based image analysis to map six land-use types from ASTER imagery, and then compare this with two per-pixel classifications. Our results show that a single segmentation, combined with intermediary classifications and merging, morphing, and growing image-objects, can lead to an accurate land-use map that is capable of utilizing both spatial and spectral information. We also employ a moving-window diversity assessment to help with analysis and improve post-classification modifications.

Combining land use data acquired from Landsat with soil map data

Science.gov (United States)

Westin, F. C.; Brandner, T. M.

1981-01-01

A method currently used to derive agrophysical units (APUs), i.e., geographical areas having definable/comparable agronomic and physical parameters which reflect a range in agricultural use and management, is discussed with reference to results obtained for South Dakota and an area in China. The method consists of combining agricultural land use data acquired from Landsat with soil map data. The resulting map units are soil associations characterized by cropland use intensity, and they can be used to identify major cropland areas and to develop a rating reflecting the relative potential of the soils in the delineated area for crop production, as well as to update small-scale soil maps.

Identification of land degradation evidences in an organic farm using probability maps (Croatia)

Science.gov (United States)

Pereira, Paulo; Bogunovic, Igor; Estebaranz, Ferran

2017-04-01

Land degradation is a biophysical process with important impacts on society, economy and policy. Areas affected by land degradation do not provide services in quality and with capacity to full-field the communities that depends on them (Amaya-Romero et al., 2015; Beyene, 2015; Lanckriet et al., 2015). Agricultural activities are one of the main causes of land degradation (Kraaijvanger and Veldkamp, 2015), especially when they decrease soil organic matter (SOM), a crucial element for soil fertility. In temperate areas, the critical level of SOM concentration in agricultural soils is 3.4%. Below this level there is a potential decrease of soil quality (Loveland and Weeb, 2003). However, no previous work was carried out in other environments, such as the Mediterranean. The spatial distribution of potential degraded land is important to be identified and mapped, in order to identify the areas that need restoration (Brevik et al., 2016; Pereira et al., 2017). The aim of this work is to assess the spatial distribution of areas with evidences of land degradation (SOM bellow 3.4%) using probability maps in an organic farm located in Croatia. In order to find the best method, we compared several probability methods, such as Ordinary Kriging (OK), Simple Kriging (SK), Universal Kriging (UK), Indicator Kriging (IK), Probability Kriging (PK) and Disjunctive Kriging (DK). The study area is located on the Istria peninsula (45°3' N; 14°2' E), with a total area of 182 ha. One hundred eighty-two soil samples (0-30 cm) were collected during July of 2015 and SOM was assessed using wet combustion procedure. The assessment of the best probability method was carried out using leave one out cross validation method. The probability method with the lowest Root Mean Squared Error (RMSE) was the most accurate. The results showed that the best method to predict the probability of potential land degradation was SK with an RMSE of 0.635, followed by DK (RMSE=0.636), UK (RMSE=0.660), OK (RMSE

The Application of Remote Sensing Data to GIS Studies of Land Use, Land Cover, and Vegetation Mapping in the State of Hawaii

Science.gov (United States)

Hogan, Christine A.

1996-01-01

A land cover-vegetation map with a base classification system for remote sensing use in a tropical island environment was produced of the island of Hawaii for the State of Hawaii to evaluate whether or not useful land cover information can be derived from Landsat TM data. In addition, an island-wide change detection mosaic combining a previously created 1977 MSS land classification with the TM-based classification was produced. In order to reach the goal of transferring remote sensing technology to State of Hawaii personnel, a pilot project was conducted while training State of Hawaii personnel in remote sensing technology and classification systems. Spectral characteristics of young island land cover types were compared to determine if there are differences in vegetation types on lava, vegetation types on soils, and barren lava from soils, and if they can be detected remotely, based on differences in pigments detecting plant physiognomic type, health, stress at senescence, heat, moisture level, and biomass. Geographic information systems (GIS) and global positioning systems (GPS) were used to assist in image rectification and classification. GIS was also used to produce large-format color output maps. An interactive GIS program was written to provide on-line access to scanned photos taken at field sites. The pilot project found Landsat TM to be a credible source of land cover information for geologically young islands, and TM data bands are effective in detecting spectral characteristics of different land cover types through remote sensing. Large agriculture field patterns were resolved and mapped successfully from wildland vegetation, but small agriculture field patterns were not. Additional processing was required to work with the four TM scenes from two separate orbits which span three years, including El Nino and drought dates. Results of the project emphasized the need for further land cover and land use processing and research. Change in vegetation

Soil mapping and process modeling for sustainable land use management: a brief historical review

Science.gov (United States)

Brevik, Eric C.; Pereira, Paulo; Muñoz-Rojas, Miriam; Miller, Bradley A.; Cerdà, Artemi; Parras-Alcántara, Luis; Lozano-García, Beatriz

2017-04-01

Basic soil management goes back to the earliest days of agricultural practices, approximately 9,000 BCE. Through time humans developed soil management techniques of ever increasing complexity, including plows, contour tillage, terracing, and irrigation. Spatial soil patterns were being recognized as early as 3,000 BCE, but the first soil maps didn't appear until the 1700s and the first soil models finally arrived in the 1880s (Brevik et al., in press). The beginning of the 20th century saw an increase in standardization in many soil science methods and wide-spread soil mapping in many parts of the world, particularly in developed countries. However, the classification systems used, mapping scale, and national coverage varied considerably from country to country. Major advances were made in pedologic modeling starting in the 1940s, and in erosion modeling starting in the 1950s. In the 1970s and 1980s advances in computing power, remote and proximal sensing, geographic information systems (GIS), global positioning systems (GPS), and statistics and spatial statistics among other numerical techniques significantly enhanced our ability to map and model soils (Brevik et al., 2016). These types of advances positioned soil science to make meaningful contributions to sustainable land use management as we moved into the 21st century. References Brevik, E., Pereira, P., Muñoz-Rojas, M., Miller, B., Cerda, A., Parras-Alcantara, L., Lozano-Garcia, B. Historical perspectives on soil mapping and process modelling for sustainable land use management. In: Pereira, P., Brevik, E., Muñoz-Rojas, M., Miller, B. (eds) Soil mapping and process modelling for sustainable land use management (In press). Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. 2016. Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274.

ERTS-1 imagery interpretation techniques in the Tennessee Valley. [land use and soil mapping

Science.gov (United States)

Bodenheimer, R. E. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The feasibility of delineating major soil associations and land uses through computerized analyses is discussed. Useful and potential applications in detecting landscape change and land use mapping are described. Recommendations for improving the data processing effort in a multidisciplinary program are presented.

Normal forms for Poisson maps and symplectic groupoids around Poisson transversals.

Science.gov (United States)

Frejlich, Pedro; Mărcuț, Ioan

2018-01-01

Poisson transversals are submanifolds in a Poisson manifold which intersect all symplectic leaves transversally and symplectically. In this communication, we prove a normal form theorem for Poisson maps around Poisson transversals. A Poisson map pulls a Poisson transversal back to a Poisson transversal, and our first main result states that simultaneous normal forms exist around such transversals, for which the Poisson map becomes transversally linear, and intertwines the normal form data of the transversals. Our second result concerns symplectic integrations. We prove that a neighborhood of a Poisson transversal is integrable exactly when the Poisson transversal itself is integrable, and in that case we prove a normal form theorem for the symplectic groupoid around its restriction to the Poisson transversal, which puts all structure maps in normal form. We conclude by illustrating our results with examples arising from Lie algebras.

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

Comparison of satellite imagery and infrared aerial photography as vegetation mapping methods in an arctic study area: Jameson Land, East Greenland

DEFF Research Database (Denmark)

Hansen, Birger Ulf; Mosbech, Anders

1994-01-01

Remote Sensing, vegetation mapping, SPOT, Landsat TM, aerial photography, Jameson Land, East Greenland......Remote Sensing, vegetation mapping, SPOT, Landsat TM, aerial photography, Jameson Land, East Greenland...

Land use mapping and change detection using ERTS imagery in Montgomery County, Alabama

Science.gov (United States)

Wilms, R. P.

1973-01-01

The feasibility of using remotely sensed data from ERTS-1 for mapping land use and detecting land use change was investigated. Land use information was gathered from 1964 air photo mosaics and from 1972 ERTS data. The 1964 data provided the basis for comparison with ERTS-1 imagery. From this comparison, urban sprawl was quite evident for the city of Montgomery. A significant trend from forestland to agricultural was also discovered. The development of main traffic arteries between 1964 and 1972 was a vital factor in the development of some of the urban centers. Even though certain problems in interpreting and correlating land use data from ERTS imagery were encountered, it has been demonstrated that remotely sensed data from ERTS is useful for inventorying land use and detecting land use change.

Urban Land Cover Mapping Accuracy Assessment - A Cost-benefit Analysis Approach

Science.gov (United States)

Xiao, T.

2012-12-01

One of the most important components in urban land cover mapping is mapping accuracy assessment. Many statistical models have been developed to help design simple schemes based on both accuracy and confidence levels. It is intuitive that an increased number of samples increases the accuracy as well as the cost of an assessment. Understanding cost and sampling size is crucial in implementing efficient and effective of field data collection. Few studies have included a cost calculation component as part of the assessment. In this study, a cost-benefit sampling analysis model was created by combining sample size design and sampling cost calculation. The sampling cost included transportation cost, field data collection cost, and laboratory data analysis cost. Simple Random Sampling (SRS) and Modified Systematic Sampling (MSS) methods were used to design sample locations and to extract land cover data in ArcGIS. High resolution land cover data layers of Denver, CO and Sacramento, CA, street networks, and parcel GIS data layers were used in this study to test and verify the model. The relationship between the cost and accuracy was used to determine the effectiveness of each sample method. The results of this study can be applied to other environmental studies that require spatial sampling.

Using risk maps to link land value damage and risk as basis of flexible risk management for brownfield redevelopment.

Science.gov (United States)

Chen, I-chun; Ma, Hwong-wen

2013-02-01

Brownfield redevelopment involves numerous uncertain financial risks associated with market demand and land value. To reduce the uncertainty of the specific impact of land value and social costs, this study develops small-scale risk maps to determine the relationship between population risk (PR) and damaged land value (DLV) to facilitate flexible land reutilisation plans. This study used the spatial variability of exposure parameters in each village to develop the contaminated site-specific risk maps. In view of the combination of risk and cost, risk level that most affected land use was mainly 1.00×10(-6) to 1.00×10(-5) in this study area. Village 2 showed the potential for cost-effective conversion with contaminated land development. If the risk of remediation target was set at 5.00×10(-6), the DLV could be reduced by NT$15,005 million for the land developer. The land developer will consider the net benefit by quantifying the trade-off between the changes of land value and the cost of human health. In this study, small-scale risk maps can illuminate the economic incentive potential for contaminated site redevelopment through the adjustment of land value damage and human health risk. Copyright © 2012 Elsevier Ltd. All rights reserved.

Deviations of the lepton mapping matrix form the harrison-perkins-scott form

International Nuclear Information System (INIS)

Friedberg, R.; Lee, T.D.

2010-01-01

We propose a simple set of hypotheses governing the deviations of the leptonic mapping matrix from the Harrison-Perkins-Scott (HPS) form. These deviations are supposed to arise entirely from a perturbation of the mass matrix in the charged lepton sector. The perturbing matrix is assumed to be purely imaginary (thus maximally T-violating) and to have a strength in energy scale no greater (but perhaps smaller) than the muon mass. As we shall show,it then follows that the absolute value of the mapping matrix elements pertaining to the tau lepton deviate by no more than O((m μ /m τ ) 2 ) ≅ 3.5 x 10 -3 from their HPS values. Assuming that(m μ /m τ ) 2 can be neglected, we derive two simple constraints on the four parameters θ12, θ23, θ31, and δ of the mapping matrix. These constraints are independent of the details of the imaginary T-violating perturbation of the charged lepton mass matrix. We also show that the e and μ parts of the mapping matrix have a definite form governed by two parameters α and β; any deviation of order m μ /m τ can be accommodated by adjusting these two parameters. (authors)

Applying parcel-specific land-use data to map conflicts and convergences between agriculture and biodiversity in Denmark

DEFF Research Database (Denmark)

Levin, Gregor

2010-01-01

Provision of semi-natural habitats is an important service of agricultural ecosystems. Quality and extent of semi-natural habitats is closely linked with intensity of agricultural management. Grass-dominated habitat types often depend on extensive management in terms of grazing or mowing. Lack...... compositions of semi-natural habitats disappear. For Denmark, we apply parcel-specific data on agricultural land use to map convergences and conflicts between agriculture and biodiversity. We group land-uses into intensive and extensive and overlay these with a map of grass-dominated semi-natural habitats. 61...... % of habitats overlap with extensively managed land, indicating convergence between agriculture and biodiversity. In contrast, 13 % of habitats overlap with intensively managed land, pointing at severe conflicts between agriculture and biodiversity. 27 % of habitats are located outside any agricultural land...

Land cover mapping with emphasis to burnt area delineation using co-orbital ALI and Landsat TM imagery

Science.gov (United States)

Petropoulos, George P.; Kontoes, Charalambos C.; Keramitsoglou, Iphigenia

2012-08-01

In this study, the potential of EO-1 Advanced Land Imager (ALI) radiometer for land cover and especially burnt area mapping from a single image analysis is investigated. Co-orbital imagery from the Landsat Thematic Mapper (TM) was also utilised for comparison purposes. Both images were acquired shortly after the suppression of a fire occurred during the summer of 2009 North-East of Athens, the capital of Greece. The Maximum Likelihood (ML), Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) classifiers were parameterised and subsequently applied to the acquired satellite datasets. Evaluation of the land use/cover mapping accuracy was based on the error matrix statistics. Also, the McNemar test was used to evaluate the statistical significance of the differences between the approaches tested. Derived burnt area estimates were validated against the operationally deployed Services and Applications For Emergency Response (SAFER) Burnt Scar Mapping service. All classifiers applied to either ALI or TM imagery proved flexible enough to map land cover and also to extract the burnt area from other land surface types. The highest total classification accuracy and burnt area detection capability was returned from the application of SVMs to ALI data. This was due to the SVMs ability to identify an optimal separating hyperplane for best classes' separation that was able to better utilise ALI's advanced technological characteristics in comparison to those of TM sensor. This study is to our knowledge the first of its kind, effectively demonstrating the benefits of the combined application of SVMs to ALI data further implying that ALI technology may prove highly valuable in mapping burnt areas and land use/cover if it is incorporated into the development of Landsat 8 mission, planned to be launched in the coming years.

Mapping and quantifying geodiversity in land-water transition zones using MBES and topobathymetric LiDAR

Science.gov (United States)

Brandbyge Ernstsen, Verner; Skovgaard Andersen, Mikkel; Gergely, Aron; Schulze Tenberge, Yvonne; Al-Hamdani, Zyad; Steinbacher, Frank; Rolighed Larsen, Laurids; Winter, Christian; Bartholomä, Alexander

2016-04-01

Land-water transition zones, like e.g. coastal and fluvial environments, are valuable ecosystems which are often characterised by high biodiversity and geodiversity. However, often these land-water transition zones are difficult or even impossible to map and investigate in high spatial resolution due to the challenging environmental conditions. Combining vessel borne shallow water multibeam echosounder (MBES) surveys ,to cover the subtidal coastal areas and the river channel areas, with airborne topobathymetric light detection and ranging (LiDAR) surveys, to cover the intertidal and supratidal coastal areas and the river floodplain areas, potentially enables full-coverage and high-resolution mapping in these challenging environments. We have carried out MBES and topobathymetric LiDAR surveys in the Knudedyb tidal inlet system, a coastal environment in the Danish Wadden Sea which is part of the Wadden Sea National Park and UNESCO World Heritage, and in the Ribe Vesterå, a fluvial environment in the Ribe Å river catchment discharging into the Knudedyb tidal basin. Detailed digital elevation models (DEMs) with a grid cell size of 0.5 m x 0.5 m were generated from the MBES and the LiDAR point clouds, which both have point densities in the order of 20 points/m2. Morphometric analyses of the DEMs enabled the identification and mapping of the different landforms within the coastal and fluvial environments. Hereby, we demonstrate that vessel borne MBES and airborne topobathymetric LiDAR, here in combination, are promising tools for seamless mapping across land-water transition zones as well as for the quantification of a range of landforms at landscape scale in different land-water transition zone environments. Hence, we demonstrate the potential for mapping and quantifying geomorphological diversity, which is one of the main components of geodiversity and a prerequisite for assessing geoheritage. Acknowledgements This work was funded by the Danish Council for

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

Science.gov (United States)

Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Alias, A. N.; Mohd. Saleh, N.; Wong, C. J.; Surbakti, M. S.

2008-03-01

Remote sensing offers an important means of detecting and analyzing temporal changes occurring in our landscape. This research used remote sensing to quantify land use/land cover changes at the Nanggroe Aceh Darussalam (Nad) province, Indonesia on a regional scale. The objective of this paper is to assess the changed produced from the analysis of Landsat TM data. A Landsat TM image was used to develop land cover classification map for the 27 March 2005. Four supervised classifications techniques (Maximum Likelihood, Minimum Distance-to- Mean, Parallelepiped and Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier) were performed to the satellite image. Training sites and accuracy assessment were needed for supervised classification techniques. The training sites were established using polygons based on the colour image. High detection accuracy (>80%) and overall Kappa (>0.80) were achieved by the Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier in this study. This preliminary study has produced a promising result. This indicates that land cover mapping can be carried out using remote sensing classification method of the satellite digital imagery.

Mapping urban environmental noise: a land use regression method.

Science.gov (United States)

Xie, Dan; Liu, Yi; Chen, Jining

2011-09-01

Forecasting and preventing urban noise pollution are major challenges in urban environmental management. Most existing efforts, including experiment-based models, statistical models, and noise mapping, however, have limited capacity to explain the association between urban growth and corresponding noise change. Therefore, these conventional methods can hardly forecast urban noise at a given outlook of development layout. This paper, for the first time, introduces a land use regression method, which has been applied for simulating urban air quality for a decade, to construct an urban noise model (LUNOS) in Dalian Municipality, Northwest China. The LUNOS model describes noise as a dependent variable of surrounding various land areas via a regressive function. The results suggest that a linear model performs better in fitting monitoring data, and there is no significant difference of the LUNOS's outputs when applied to different spatial scales. As the LUNOS facilitates a better understanding of the association between land use and urban environmental noise in comparison to conventional methods, it can be regarded as a promising tool for noise prediction for planning purposes and aid smart decision-making.

Geoportal as a way for monitoring land settlements

Directory of Open Access Journals (Sweden)

Наталя Бубир

2016-10-01

Full Text Available The use of geoportals will improve land monitoring through timely detection of changes in land conditions, mobility access to geospatial data. The result of cadastre geoportals analysis of leading countries, including France, Germany, Great Britain, Austria, USA, Canada, has indicated that their content is correlated to cadastre features in one country and often do not contain complex issues of land monitoring settlements. In Ukraine, there is no public online mapping resource of this topic. It is proposed to establish specialized geoportal monitoring land settlements for public use. The geoportal contents should include an interactive map of each settlement, text information about settlements, laws and regulations, data about existing land use, including land-use violations and carried out or planned environmental activities. An important component of this portal is a personal user panel (Personal office, where he can view, save, print information that is of interest to him, including application forms to the local land management. On this basis we have developed a geoportal monitoring land settlements of Stepnogorsk village council within the student’s research work as part of the relevant geoportals in Zaporizhzhia region. The portal main menu includes: Settlements of Zaporizhzhia region; Monitoring land settlements; Land environmental; Virtual Tour; News. Additional menu contains five tabs: Home (go to home page geoportals; laws; Maps; Photo Gallery; Personal office. Interactive maps of settlements are based on Google maps. Map content includes mapping settlement’s functional areas and distribution of adverse natural and anthropogenic processes. The main map’s advantage is active zone, clicking on which the user is able to see which process is unfavorable in the territory, and which intended purpose is in this land. The user can also edit the map by his personal office. Overall, portal development within student

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.

Improved land use classification from Landsat and Seasat satellite imagery registered to a common map base

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Clark, J.

1981-01-01

In the case of Landsat Multispectral Scanner System (MSS) data, ambiguities in spectral signature can arise in urban areas. A study was initiated in the belief that Seasat digital SAR could help provide the spectral separability needed for a more accurate urban land use classification. A description is presented of the results of land use classifications performed on Landsat and preprocessed Seasat imagery that were registered to a common map base. The process of registering imagery and training site boundary coordinates to a common map has been reported by Clark (1980). It is found that preprocessed Seasat imagery provides signatures for urban land uses which are spectrally separable from Landsat signatures. This development appears to significantly improve land use classifications in an urban setting for class 12 (Commercial and Services), class 13 (Industrial), and class 14 (Transportation, Communications, and Utilities).

Values mapping with Latino forest users: Contributing to the dialogue on multiple land use conflict management

Science.gov (United States)

Kelly Biedenweg; Lee Cerveny; Rebecca J. McLain

2014-01-01

Participatory mapping of landscape values is gaining ground as a method for engaging communities and stakeholders in natural resource management. Socio-spatial mapping allows the public to identify places of economic, social, cultural, or personal importance. In addition to providing data for planning and land management, the mapping process can open dialogue about...

A Remote Sensing Approach for Regional-Scale Mapping of Agricultural Land-Use Systems Based on NDVI Time Series

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Beatriz Bellón

2017-06-01

Full Text Available In response to the need for generic remote sensing tools to support large-scale agricultural monitoring, we present a new approach for regional-scale mapping of agricultural land-use systems (ALUS based on object-based Normalized Difference Vegetation Index (NDVI time series analysis. The approach consists of two main steps. First, to obtain relatively homogeneous land units in terms of phenological patterns, a principal component analysis (PCA is applied to an annual MODIS NDVI time series, and an automatic segmentation is performed on the resulting high-order principal component images. Second, the resulting land units are classified into the crop agriculture domain or the livestock domain based on their land-cover characteristics. The crop agriculture domain land units are further classified into different cropping systems based on the correspondence of their NDVI temporal profiles with the phenological patterns associated with the cropping systems of the study area. A map of the main ALUS of the Brazilian state of Tocantins was produced for the 2013–2014 growing season with the new approach, and a significant coherence was observed between the spatial distribution of the cropping systems in the final ALUS map and in a reference map extracted from the official agricultural statistics of the Brazilian Institute of Geography and Statistics (IBGE. This study shows the potential of remote sensing techniques to provide valuable baseline spatial information for supporting agricultural monitoring and for large-scale land-use systems analysis.

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

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

2017-12-01

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

Mapping soil total nitrogen of cultivated land at county scale by using hyperspectral image

Science.gov (United States)

Gu, Xiaohe; Zhang, Li Yan; Shu, Meiyan; Yang, Guijun

2018-02-01

Monitoring total nitrogen content (TNC) in the soil of cultivated land quantitively and mastering its spatial distribution are helpful for crop growing, soil fertility adjustment and sustainable development of agriculture. The study aimed to develop a universal method to map total nitrogen content in soil of cultivated land by HSI image at county scale. Several mathematical transformations were used to improve the expression ability of HSI image. The correlations between soil TNC and the reflectivity and its mathematical transformations were analyzed. Then the susceptible bands and its transformations were screened to develop the optimizing model of map soil TNC in the Anping County based on the method of multiple linear regression. Results showed that the bands of 14th, 16th, 19th, 37th and 60th with different mathematical transformations were screened as susceptible bands. Differential transformation was helpful for reducing the noise interference to the diagnosis ability of the target spectrum. The determination coefficient of the first order differential of logarithmic transformation was biggest (0.505), while the RMSE was lowest. The study confirmed the first order differential of logarithm transformation as the optimal inversion model for soil TNC, which was used to map soil TNC of cultivated land in the study area.

Regional Geological Mapping in the Graham Land of Antarctic Peninsula Using LANDSAT-8 Remote Sensing Data

Science.gov (United States)

Pour, A. B.; Hashim, M.; Park, Y.

2017-10-01

Geological investigations in Antarctica confront many difficulties due to its remoteness and extreme environmental conditions. In this study, the applications of Landsat-8 data were investigated to extract geological information for lithological and alteration mineral mapping in poorly exposed lithologies in inaccessible domains such in Antarctica. The north-eastern Graham Land, Antarctic Peninsula (AP) was selected in this study to conduct a satellite-based remote sensing mapping technique. Continuum Removal (CR) spectral mapping tool and Independent Components Analysis (ICA) were applied to Landsat-8 spectral bands to map poorly exposed lithologies at regional scale. Pixels composed of distinctive absorption features of alteration mineral assemblages associated with poorly exposed lithological units were detected by applying CR mapping tool to VNIR and SWIR bands of Landsat-8.Pixels related to Si-O bond emission minima features were identified using CR mapping tool to TIR bands in poorly mapped andunmapped zones in north-eastern Graham Land at regional scale. Anomaly pixels in the ICA image maps related to spectral featuresof Al-O-H, Fe, Mg-O-H and CO3 groups and well-constrained lithological attributions from felsic to mafic rocks were detectedusing VNIR, SWIR and TIR datasets of Landsat-8. The approach used in this study performed very well for lithological andalteration mineral mapping with little available geological data or without prior information of the study region.

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

Science.gov (United States)

Pilant, A. N.; Baynes, J.; Dannenberg, M.; Riegel, J.; Rudder, C.; Endres, K.

2013-12-01

US EPA EnviroAtlas is an online collection of tools and resources that provides geospatial data, maps, research, and analysis on the relationships between nature, people, health, and the economy (http://www.epa.gov/research/enviroatlas/index.htm). Using EnviroAtlas, you can see and explore information related to the benefits (e.g., ecosystem services) that humans receive from nature, including clean air, clean and plentiful water, natural hazard mitigation, biodiversity conservation, food, fuel, and materials, recreational opportunities, and cultural and aesthetic value. EPA developed several urban land cover maps at very high spatial resolution (one-meter pixel size) for a portion of EnviroAtlas devoted to urban studies. This urban mapping effort supported analysis of relations among land cover, human health and demographics at the US Census Block Group level. Supervised classification of 2010 USDA NAIP (National Agricultural Imagery Program) digital aerial photos produced eight-class land cover maps for several cities, including Durham, NC, Portland, ME, Tampa, FL, New Bedford, MA, Pittsburgh, PA, Portland, OR, and Milwaukee, WI. Semi-automated feature extraction methods were used to classify the NAIP imagery: genetic algorithms/machine learning, random forest, and object-based image analysis (OBIA). In this presentation we describe the image processing and fuzzy accuracy assessment methods used, and report on some sustainability and ecosystem service metrics computed using this land cover as input (e.g., carbon sequestration from USFS iTREE model; health and demographics in relation to road buffer forest width). We also discuss the land cover classification schema (a modified Anderson Level 1 after the National Land Cover Data (NLCD)), and offer some observations on lessons learned. Meter-scale urban land cover in Portland, OR overlaid on NAIP aerial photo. Streets, buildings and individual trees are identifiable.

Meso(topoclimatic maps and mapping

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Ladislav Plánka

2007-06-01

Full Text Available The atmospheric characteristics can be studied from many points of view, most often we talk about time and spatial standpoint. Application of time standpoint leads either to different kinds of the synoptic and prognostic maps production, which presents actual state of atmosphere in short time section in the past or in the near future or to the climatic maps production which presents longterm weather regime. Spatial standpoint then differs map works according to natural phenomenon proportions, whereas the scale of their graphic presentation can be different. It depends on production purpose of each work.In the paper there are analysed methods of mapping and climatic maps production, which display longterm regime of chosen atmospheric features. These athmosphere features are formed in interaction with land surface and also have direct influence on people and their activities throughout the country. At the same time they’re influenced by anthropogenic intervention to the landscape.

Evaluation of hot forming effects mapping for CAE analyses

Science.gov (United States)

Knoerr, L.; Faath, T.; Dykeman, J.; Malcolm, S.

2016-08-01

Hot forming has grown significantly in the manufacturing of structural components within the vehicle Body-In-White construction. The superior strength of press hardened steels not only guarantee high resistance to deformation, it also brings a significant weight saving compared to conventional cold formed products. However, the benefit of achieving ultrahigh strength with hot stamping, comes with a reduction in ductility of the press hardened part. This will require advanced material modeling to capture the predicted performances accurately. A technique to optically measure and map the thinning distribution after hot stamping has shown to improve numerical analysis for fracture prediction. The proposed method to determine the forming effects and mapping to CAE models can be integrated into the Vehicle Development Process to shorten the time to production.

Mapping project on land use changes in the carboniferous region of Santa Catarina

Science.gov (United States)

Valeriano, D. D.; Pereira, M. D. B.

1983-01-01

The utilization of remote sensing data for monitoring land use changes by means of digital image analysis is described. The following data were utilized: LANDSAT data from September 4, 1975, April 24, 1978, and September 8, 1981; LANDSAT paper photography data; area IV color photographs; IBGE topography maps, and auxiliary data about the Brazilian state of Santa Catarina. Three kinds of analyses of digital images were carried out. The project identified and mapped major classes of land use areas including urban areas, coal deposits, agricultural areas, forests, lakes, and flood plains. Five areas directly affected by coal exploration southeast of Santa Catarina are identified and described. In addition, the classification system used for organizing data about land cover in a hierarchical arrangement is presented. The project made use of two remote sensing data sources: data of MSS spectral (Mulitspectral Scanner System)/LANDSAT on a scale of 1:100,000 with approximately 80 m resolution, and infrared color aerial photographs on a scale of 1:45,000 with approximately 5 m resolution. Therefore, the classification system included three levels, two selected to be compatible with aerial photography data and the third to conform to the resolution of MSS/LANDSAT.

Analysis of Double Meridian Distance for a Closed Traverse Area towards Developing a Contour Map and Land Title

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T. U. Ganiron Jr

2014-07-01

Full Text Available This research aimed to analyze double meridian distance for a closed traverse area in developing a land title for a propose gymnasium in Qassim University. Theodolite, leveling rod and steel tape plays an important role in measuring elevations, bearings and distances of the boundaries of a lot. Contour map is necessary to determine the traces of level surfaces of successive elevation. This will enable to identify the type of contour map and type of contour lines necessary for this project. Corel draw software is used to draw contour map and guide to interpret the significance of the variables. It is essential to check the error of closure for interior angles and for both latitude and departure before applying the Double Meridian Distance (DMD method to obtain the total area of the lot. Technical descriptions of the land such as distance, bearing, boundaries and area are necessary to visualize the shape & exact location of the land. Developing a land title will be obtained using the technical descriptions of the lot in preparation for the type of gymnasium necessary for Qassim University.

Change in land use in the Phoenix (1:250,000) Quadrangle, Arizona between 1970 and 1973: ERTS as an aid in a nationwide program for mapping general land use. [Phoenix Quadrangle, Arizona

Science.gov (United States)

Place, J. L.

1974-01-01

Changes in land use between 1970 and 1973 in the Phoenix (1:250,000 scale) Quadrangle in Arizona have been mapped using only the images from ERTS-1, tending to verify the utility of a standard land use classification system proposed for use with ERTS images. Types of changes detected have been: (1) new residential development of former cropland and rangeland; (2) new cropland from the desert; and (3) new reservoir fill-up. The seasonal changing of vegetation patterns in ERTS has complemented air photos in delimiting the boundaries of some land use types. ERTS images, in combination with other sources of information, can assist in mapping the generalized land use of the fifty states by the standard 1:250,000 quadrangles. Several states are already working cooperatively in this type of mapping.

Grid-based modeling for land use planning and environmental resource mapping.

Energy Technology Data Exchange (ETDEWEB)

Kuiper, J. A.

1999-08-04

Geographic Information System (GIS) technology is used by land managers and natural resource planners for examining resource distribution and conducting project planning, often by visually interpreting spatial data representing environmental or regulatory variables. Frequently, many variables influence the decision-making process, and modeling can improve results with even a small investment of time and effort. Presented are several grid-based GIS modeling projects, including: (1) land use optimization under environmental and regulatory constraints; (2) identification of suitable wetland mitigation sites; and (3) predictive mapping of prehistoric cultural resource sites. As different as the applications are, each follows a similar process of problem conceptualization, implementation of a practical grid-based GIS model, and evaluation of results.

Land Cover Mapping Analysis and Urban Growth Modelling Using Remote Sensing Techniques in Greater Cairo Region—Egypt

Directory of Open Access Journals (Sweden)

Yasmine Megahed

2015-09-01

Full Text Available This study modeled the urban growth in the Greater Cairo Region (GCR, one of the fastest growing mega cities in the world, using remote sensing data and ancillary data. Three land use land cover (LULC maps (1984, 2003 and 2014 were produced from satellite images by using Support Vector Machines (SVM. Then, land cover changes were detected by applying a high level mapping technique that combines binary maps (change/no-change and post classification comparison technique. The spatial and temporal urban growth patterns were analyzed using selected statistical metrics developed in the FRAGSTATS software. Major transitions to urban were modeled to predict the future scenarios for year 2025 using Land Change Modeler (LCM embedded in the IDRISI software. The model results, after validation, indicated that 14% of the vegetation and 4% of the desert in 2014 will be urbanized in 2025. The urban areas within a 5-km buffer around: the Great Pyramids, Islamic Cairo and Al-Baron Palace were calculated, highlighting an intense urbanization especially around the Pyramids; 28% in 2014 up to 40% in 2025. Knowing the current and estimated urbanization situation in GCR will help decision makers to adjust and develop new plans to achieve a sustainable development of urban areas and to protect the historical locations.

Land area change and fractional water maps in the Chenier Plain, Louisiana, following hurricane Rita

Science.gov (United States)

Palaseanu-Lovejoy, M.; Kranenburg, C.; Brock, J. C.

2009-12-01

The objective of this study is to develop a fractional water map at 30-m resolution scale using QuickBird and/or IKONOS high-resolution imagery as dependent variable to investigate the impact of hurricane Rita in the Chenier Plain, Louisiana. Eleven different indices were tested to obtain a high-resolution land / water classification on QuickBird (acquired on 05/23/2003) and IKONOS (acquired on 03/25/2006) images. The percent area covered by water in the high resolution images varied from 22 to 26% depending on the index used , with the simple ratio index (red band / NIR band) accounting for the lowest percent and the blue ratio index (blue band / sum(all bands)) for the highest percent. Using the ERDAS NLCD (National Land Cover Data) Mapping tool module, 100, 000 stratified random sample points with minimum 1000 points per stratum were selected from the high resolution dependent variable as training information for the independent variable layers. The rules for the regression tree were created using the data mining software Rulequest Cubist v. 2.05. This information was used to generate a fractional water map for the entire Landsat scene. The increase in water areas of about 10 - 15% between 2003 to 2006, as well as temporary changes in the water - land configurations are attributed to remnant flooding and removal of aquatic vegetation caused by hurricane Rita, and water level variations caused by tidal and / or meteorological variations between the acquisition dates of the satellite images. This analysis can assist in monitoring post-hurricane wetland recovery and assess trends in land loss due to extreme storm events, although estimation of permanent land loss cannot be made until wetland areas have the opportunity to recover from hurricane impacts.

A methodology for small scale rural land use mapping in semi-arid developing countries using orbital imagery. Part 6: A low-cost method for land use mapping using simple visual techniques of interpretation. [Spain

Science.gov (United States)

Vangenderen, J. L. (Principal Investigator); Lock, B. F.

1976-01-01

The author has identified the following significant results. It was found that color composite transparencies and monocular magnification provided the best base for land use interpretation. New methods for determining optimum sample sizes and analyzing interpretation accuracy levels were developed. All stages of the methodology were assessed, in the operational sense, during the production of a 1:250,000 rural land use map of Murcia Province, Southeast Spain.

Fusion Approaches for Land Cover Map Production Using High Resolution Image Time Series without Reference Data of the Corresponding Period

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Benjamin Tardy

2017-11-01

Full Text Available Optical sensor time series images allow one to produce land cover maps at a large scale. The supervised classification algorithms have been shown to be the best to produce maps automatically with good accuracy. The main drawback of these methods is the need for reference data, the collection of which can introduce important production delays. Therefore, the maps are often available too late for some applications. Domain adaptation methods seem to be efficient for using past data for land cover map production. According to this idea, the main goal of this study is to propose several simple past data fusion schemes to override the current land cover map production delays. A single classifier approach and three voting rules are considered to produce maps without reference data of the corresponding period. These four approaches reach an overall accuracy of around 80% with a 17-class nomenclature using Formosat-2 image time series. A study of the impact of the number of past periods used is also done. It shows that the overall accuracy increases with the number of periods used. The proposed methods require at least two or three previous years to be used.

Comparative analysis of extracted heights from topographic maps ...

African Journals Online (AJOL)

Topographic maps represent the three-dimensional landscape by providing relief information in the form of contours in addition to plan information on which natural and man-made landmarks are quite accurately represented. Height information, extractible from topographic maps, comes in handy for most land use planning.

High resolution population maps for low income nations: combining land cover and census in East Africa.

Directory of Open Access Journals (Sweden)

Andrew J Tatem

2007-12-01

Full Text Available Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas.We examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps.We find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km(2. The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk and are freely available.

High Resolution Population Maps for Low Income Nations: Combining Land Cover and Census in East Africa

Science.gov (United States)

Tatem, Andrew J.; Noor, Abdisalan M.; von Hagen, Craig; Di Gregorio, Antonio; Hay, Simon I.

2007-01-01

Background Between 2005 and 2050, the human population is forecast to grow by 2.7 billion, with the vast majority of this growth occurring in low income countries. This growth is likely to have significant social, economic and environmental impacts, and make the achievement of international development goals more difficult. The measurement, monitoring and potential mitigation of these impacts require high resolution, contemporary data on human population distributions. In low income countries, however, where the changes will be concentrated, the least information on the distribution of population exists. In this paper we investigate whether satellite imagery in combination with land cover information and census data can be used to create inexpensive, high resolution and easily-updatable settlement and population distribution maps over large areas. Methodology/Principal Findings We examine various approaches for the production of maps of the East African region (Kenya, Uganda, Burundi, Rwanda and Tanzania) and where fine resolution census data exists, test the accuracies of map production approaches and existing population distribution products. The results show that combining high resolution census, settlement and land cover information is important in producing accurate population distribution maps. Conclusions We find that this semi-automated population distribution mapping at unprecedented spatial resolution produces more accurate results than existing products and can be undertaken for as little as $0.01 per km2. The resulting population maps are a product of the Malaria Atlas Project (MAP: http://www.map.ox.ac.uk) and are freely available. PMID:18074022

A procedure used for a ground truth study of a land use map of North Alabama generated from LANDSAT data

Science.gov (United States)

Downs, S. W., Jr.; Sharma, G. C.; Bagwell, C.

1977-01-01

A land use map of a five county area in North Alabama was generated from LANDSAT data using a supervised classification algorithm. There was good overall agreement between the land use designated and known conditions, but there were also obvious discrepancies. In ground checking the map, two types of errors were encountered - shift and misclassification - and a method was developed to eliminate or greatly reduce the errors. Randomly selected study areas containing 2,525 pixels were analyzed. Overall, 76.3 percent of the pixels were correctly classified. A contingency coefficient of correlation was calculated to be 0.7 which is significant at the alpha = 0.01 level. The land use maps generated by computers from LANDSAT data are useful for overall land use by regional agencies. However, care must be used when making detailed analysis of small areas. The procedure used for conducting the ground truth study together with data from representative study areas is presented.

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

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.

Detailed forest formation mapping in the land cover map series for the Caribbean islands

Science.gov (United States)

Helmer, E. H.; Schill, S.; Pedreros, D. H.; Tieszen, L. L.; Kennaway, T.; Cushing, M.; Ruzycki, T.

2006-12-01

Forest formation and land cover maps for several Caribbean islands were developed from Landsat ETM+ imagery as part of a multi-organizational project. The spatially explicit data on forest formation types will permit more refined estimates of some forest attributes. The woody vegetation classification scheme relates closely to that of Areces-Malea et al. (1), who classify Caribbean vegetation according to standards of the US Federal Geographic Data Committee (FGDC, 1997), with modifications similar to those in Helmer et al. (2). For several of the islands, we developed image mosaics that filled cloudy parts of scenes with data from other scene dates after using regression tree normalization (3). The regression tree procedure permitted us to develop mosaics for wet and drought seasons for a few of the islands. The resulting multiseason imagery facilitated separation between classes such as seasonal evergreen forest, semi-deciduous forest (including semi-evergreen forest), and drought deciduous forest or woodland formations. We used decision tree classification methods to classify the Landsat image mosaics to detailed forest formations and land cover for Puerto Rico (4), St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines and Grenada. The decision trees classified a stack of raster layers for each mapping area that included the Landsat image bands and various ancillary raster data layers. For Puerto Rico, for example, the ancillary data included climate parameters (5). For some islands, the ancillary data included topographic derivatives such as aspect, slope and slope position, SRTM (6) or other topographic data. Mapping forest formations with decision tree classifiers, ancillary geospatial data, and cloud-free image mosaics, accurately distinguished spectrally similar forest formations, without the aid of ecological zone maps, on the islands where the approach was used. The approach resulted in maps of forest formations with comparable or better detail

Determination of Distribution and Properties of Soil Formed on Different Fluvial Deposit

Directory of Open Access Journals (Sweden)

Orhan DENGİZ

2014-03-01

Full Text Available Alluvial land, formed on accumulated sediment depositions by time, show large variety in their properties at short distances. Therefore, different soils can be form on these lands. The objective of this research was to determine, mapping and classify different soils formed on fluvial land used for intensive cultivation in Örencik village of Samsun Bafra district. Total study area is approximately 407.9 ha. Average annual temperature and precipitation are 13.6 oC and 764.3 mm, respectively. After examination of topographic, land use, geologic and geomorphologic maps and land observation, 9 profile places were excavated in study area. Detailed land observations were done with grid method and auger examinations. The soil samples were taken from each profile and their analyses were done in the laboratory. By assessing the results of analyses and field studies, 7 different soil series were determined and described. Three of them were classified as Entisol due to their young age, three of them were classified as Inceptisol and one is as Vertisol. Whereas Cevizlik series has the largest area (24.7%, Elmacıdede series has the smallest area in the study area (7.8%.

Using remote sensing and GIS to detect and monitor land use and land cover change in Dhaka Metropolitan of Bangladesh during 1960-2005.

Science.gov (United States)

Dewan, Ashraf M; Yamaguchi, Yasushi

2009-03-01

This paper illustrates the result of land use/cover change in Dhaka Metropolitan of Bangladesh using topographic maps and multi-temporal remotely sensed data from 1960 to 2005. The Maximum likelihood supervised classification technique was used to extract information from satellite data, and post-classification change detection method was employed to detect and monitor land use/cover change. Derived land use/cover maps were further validated by using high resolution images such as SPOT, IRS, IKONOS and field data. The overall accuracy of land cover change maps, generated from Landsat and IRS-1D data, ranged from 85% to 90%. The analysis indicated that the urban expansion of Dhaka Metropolitan resulted in the considerable reduction of wetlands, cultivated land, vegetation and water bodies. The maps showed that between 1960 and 2005 built-up areas increased approximately 15,924 ha, while agricultural land decreased 7,614 ha, vegetation decreased 2,336 ha, wetland/lowland decreased 6,385 ha, and water bodies decreased about 864 ha. The amount of urban land increased from 11% (in 1960) to 344% in 2005. Similarly, the growth of landfill/bare soils category was about 256% in the same period. Much of the city's rapid growth in population has been accommodated in informal settlements with little attempt being made to limit the risk of environmental impairments. The study quantified the patterns of land use/cover change for the last 45 years for Dhaka Metropolitan that forms valuable resources for urban planners and decision makers to devise sustainable land use and environmental planning.

Development of an expert analysis tool based on an interactive subsidence hazard map for urban land use in the city of Celaya, Mexico

Science.gov (United States)

Alloy, A.; Gonzalez Dominguez, F.; Nila Fonseca, A. L.; Ruangsirikulchai, A.; Gentle, J. N., Jr.; Cabral, E.; Pierce, S. A.

2016-12-01

Land Subsidence as a result of groundwater extraction in central Mexico's larger urban centers initiated in the 80's as a result of population and economic growth. The city of Celaya has undergone subsidence for a few decades and a consequence is the development of an active normal fault system that affects its urban infrastructure and residential areas. To facilitate its analysis and a land use decision-making process we created an online interactive map enabling users to easily obtain information associated with land subsidence. Geological and socioeconomic data of the city was collected, including fault location, population data, and other important infrastructure and structural data has been obtained from fieldwork as part of a study abroad interchange undergraduate course. The subsidence and associated faulting hazard map was created using an InSAR derived subsidence velocity map and population data from INEGI to identify hazard zones using a subsidence gradient spatial analysis approach based on a subsidence gradient and population risk matrix. This interactive map provides a simple perspective of different vulnerable urban elements. As an accessible visualization tool, it will enhance communication between scientific and socio-economic disciplines. Our project also lays the groundwork for a future expert analysis system with an open source and easily accessible Python coded, SQLite database driven website which archives fault and subsidence data along with visual damage documentation to civil structures. This database takes field notes and provides an entry form for uniform datasets, which are used to generate a JSON. Such a database is useful because it allows geoscientists to have a centralized repository and access to their observations over time. Because of the widespread presence of the subsidence phenomena throughout cities in central Mexico, the spatial analysis has been automated using the open source software R. Raster, rgeos, shapefiles, and rgdal

LAND PRICE MAPPING OF JABODETABEK, INDONESIA

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Adisti Madella Elmanisa

2017-03-01

Full Text Available Land provision is one of the biggest challenges for development in urban area. Most of the available urban land will be the object of speculation to be resold at a higher price when the time is right. In Jabodetabek, where the pace of urban development is faster than other parts of Indonesia, the prices of land show an abnormal increase; they seem to rise too fast. This paper discusses the increasing land prices in Jabodetabek area and argues that the increasing land price has encourages the private developer to bank the land in the area. Based on land price survey in Jabodetabek, urban activity is moving to south Jakarta. The highest land prices were found at East Kuningan, Setiabudi, and South Jakarta. By constrast, the lowest prices were observed in Sumur Batu and Cimuning (Bantar Gebang, Bekasi.It can be concluded that the land price increase also triggered land banking practice in Jabodetabek reaching in total approximately 60% of total area of Jakarta.

The Influence of Built-Form and Land Use on Mode Choice

OpenAIRE

Reilly, Michael; Landis, John

2003-01-01

Although land use planning and urban design are increasingly touted as powerful tools for influencing transportation behavior, only modest empirical evidence for this relationship exists. Here, the results from a two-day activity diary are combined with innovative GIS-based measures of urban form and land use pattern to statistically test potential influences on non-commute home-based mode choice. Local measurement at multiple scales is promoted as a realistic means of quantifying an individu...

Development of a Bi-National Great Lakes Coastal Wetland and Land Use Map Using Three-Season PALSAR and Landsat Imagery

Directory of Open Access Journals (Sweden)

Laura Bourgeau-Chavez

2015-07-01

Full Text Available Methods using extensive field data and three-season Landsat TM and PALSAR imagery were developed to map wetland type and identify potential wetland stressors (i.e., adjacent land use for the United States and Canadian Laurentian coastal Great Lakes. The mapped area included the coastline to 10 km inland to capture the region hydrologically connected to the Great Lakes. Maps were developed in cooperation with the overarching Great Lakes Consortium plan to provide a comprehensive regional baseline map suitable for coastal wetland assessment and management by agencies at the local, tribal, state, and federal levels. The goal was to provide not only land use and land cover (LULC baseline data at moderate spatial resolution (20–30 m, but a repeatable methodology to monitor change into the future. The prime focus was on mapping wetland ecosystem types, such as emergent wetland and forested wetland, as well as to delineate wetland monocultures (Typha, Phragmites, Schoenoplectus and differentiate peatlands (fens and bogs from other wetland types. The overall accuracy for the coastal Great Lakes map of all five lake basins was 94%, with a range of 86% to 96% by individual lake basin (Huron, Ontario, Michigan, Erie and Superior.

Use of multispectral satellite imagery and hyperspectral endmember libraries for urban land cover mapping at the metropolitan scale

Science.gov (United States)

Priem, Frederik; Okujeni, Akpona; van der Linden, Sebastian; Canters, Frank

2016-10-01

The value of characteristic reflectance features for mapping urban materials has been demonstrated in many experiments with airborne imaging spectrometry. Analysis of larger areas requires satellite-based multispectral imagery, which typically lacks the spatial and spectral detail of airborne data. Consequently the need arises to develop mapping methods that exploit the complementary strengths of both data sources. In this paper a workflow for sub-pixel quantification of Vegetation-Impervious-Soil urban land cover is presented, using medium resolution multispectral satellite imagery, hyperspectral endmember libraries and Support Vector Regression. A Landsat 8 Operational Land Imager surface reflectance image covering the greater metropolitan area of Brussels is selected for mapping. Two spectral libraries developed for the cities of Brussels and Berlin based on airborne hyperspectral APEX and HyMap data are used. First the combined endmember library is resampled to match the spectral response of the Landsat sensor. The library is then optimized to avoid spectral redundancy and confusion. Subsequently the spectra of the endmember library are synthetically mixed to produce training data for unmixing. Mapping is carried out using Support Vector Regression models trained with spectra selected through stratified sampling of the mixed library. Validation on building block level (mean size = 46.8 Landsat pixels) yields an overall good fit between reference data and estimation with Mean Absolute Errors of 0.06, 0.06 and 0.08 for vegetation, impervious and soil respectively. Findings of this work may contribute to the use of universal spectral libraries for regional scale land cover fraction mapping using regression approaches.

A regional land use survey based on remote sensing and other data: A report on a LANDSAT and computer mapping project, volume 2

Science.gov (United States)

Nez, G. (Principal Investigator); Mutter, D.

1977-01-01

The author has identified the following significant results. The project mapped land use/cover classifications from LANDSAT computer compatible tape data and combined those results with other multisource data via computer mapping/compositing techniques to analyze various land use planning/natural resource management problems. Data were analyzed on 1:24,000 scale maps at 1.1 acre resolution. LANDSAT analysis software and linkages with other computer mapping software were developed. Significant results were also achieved in training, communication, and identification of needs for developing the LANDSAT/computer mapping technologies into operational tools for use by decision makers.

Highlighting continued uncertainty in global land cover maps for the user community

International Nuclear Information System (INIS)

Fritz, Steffen; See, Linda; McCallum, Ian; Schill, Christian; Obersteiner, Michael; Van der Velde, Marijn; Boettcher, Hannes; Havlík, Petr; Achard, Frédéric

2011-01-01

In the last 10 years a number of new global datasets have been created and new, more sophisticated algorithms have been designed to classify land cover. GlobCover and MODIS v.5 are the most recent global land cover products available, where GlobCover (300 m) has the finest spatial resolution of other comparable products such as MODIS v.5 (500 m) and GLC-2000 (1 km). This letter shows that the thematic accuracy in the cropland domain has decreased when comparing these two latest products. This disagreement is also evident spatially when examining maps of cropland and forest disagreement between GLC-2000, MODIS and GlobCover. The analysis highlights the continued uncertainty surrounding these products, with a combined forest and cropland disagreement of 893 Mha (GlobCover versus MODIS v.5). This letter suggests that data sharing efforts and the provision of more in situ data for training, calibration and validation are very important conditions for improving future global land cover products.

Mapping of the Land Cover Spatiotemporal Characteristics in Northern Russia Caused by Climate Change

Science.gov (United States)

Panidi, E.; Tsepelev, V.; Torlopova, N.; Bobkov, A.

2016-06-01

The study is devoted to the investigation of regional climate change in Northern Russia. Due to sparseness of the meteorological observation network in northern regions, we investigate the application capabilities of remotely sensed vegetation cover as indicator of climate change at the regional scale. In previous studies, we identified statistically significant relationship between the increase of surface air temperature and increase of the shrub vegetation productivity. We verified this relationship using ground observation data collected at the meteorological stations and Normalised Difference Vegetation Index (NDVI) data produced from Terra/MODIS satellite imagery. Additionally, we designed the technique of growing seasons separation for detailed investigation of the land cover (shrub cover) dynamics. Growing seasons are the periods when the temperature exceeds +5°C and +10°C. These periods determine the vegetation productivity conditions (i.e., conditions that allow growth of the phytomass). We have discovered that the trend signs for the surface air temperature and NDVI coincide on planes and river floodplains. On the current stage of the study, we are working on the automated mapping technique, which allows to estimate the direction and magnitude of the climate change in Northern Russia. This technique will make it possible to extrapolate identified relationship between land cover and climate onto territories with sparse network of meteorological stations. We have produced the gridded maps of NDVI and NDWI for the test area in European part of Northern Russia covered with the shrub vegetation. Basing on these maps, we may determine the frames of growing seasons for each grid cell. It will help us to obtain gridded maps of the NDVI linear trend for growing seasons on cell-by-cell basis. The trend maps can be used as indicative maps for estimation of the climate change on the studied areas.

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

Mapping Decadal Land Cover Changes in the Woodlands of North Eastern Namibia from 1975 to 2014 Using the Landsat Satellite Archived Data

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Vladimir R. Wingate

2016-08-01

Full Text Available Woodlands and savannahs provide essential ecosystem functions and services to communities. On the African continent, they are widely utilized and converted to subsistence and intensive agriculture or urbanized. This study investigates changes in land cover over four administrative regions of North Eastern Namibia within the Kalahari woodland savannah biome, covering a total of 107,994 km2. Land cover is mapped using multi-sensor Landsat imagery at decadal intervals from 1975 to 2014, with a post-classification change detection method. The dominant change observed was a reduction in the area of woodland savannah due to the expansion of agriculture, primarily in the form of small-scale cereal and pastoral production. More specifically, woodland savannah area decreased from 90% of the study area in 1975 to 83% in 2004, and then increased to 86% in 2014, while agricultural land increased from 6% to 12% between 1975 and 2014. We assess land cover changes in relation to towns, villages, rivers and roads and find most changes occurred in proximity to these. In addition, we find that most land cover changes occur within land designated as communally held, followed by state protected land. With widespread changes occurring across the African continent, this study provides important data for understanding drivers of change in the region and their impacts on the distribution of woodland savannahs.

A methodology for producing small scale rural land use maps in semi-arid developing countries using orbital imagery

Science.gov (United States)

Vangenderen, J. L. (Principal Investigator); Lock, B. F.

1976-01-01

The author has identified the following significant results. Results have shown that it is feasible to design a methodology that can provide suitable guidelines for operational production of small scale rural land use maps of semiarid developing regions from LANDSAT MSS imagery, using inexpensive and unsophisticated visual techniques. The suggested methodology provides immediate practical benefits to map makers attempting to produce land use maps in countries with limited budgets and equipment. Many preprocessing and interpretation techniques were considered, but rejected on the grounds that they were inappropriate mainly due to the high cost of imagery and/or equipment, or due to their inadequacy for use in operational projects in the developing countries. Suggested imagery and interpretation techniques, consisting of color composites and monocular magnification proved to be the simplest, fastest, and most versatile methods.

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

Using the Landsat Archive to Estimate and Map Changes in Agriculture, Forests, and other Land Cover Types in East Africa

Science.gov (United States)

Healey, S. P.; Oduor, P.; Cohen, W. B.; Yang, Z.; Ouko, E.; Gorelick, N.; Wilson, S.

2017-12-01

Every country's land is distributed among different cover types, such as: agriculture; forests; rangeland; urban areas; and barren lands. Changes in the distribution of these classes can inform us about many things, including: population pressure; effectiveness of preservation efforts; desertification; and stability of the food supply. Good assessment of these changes can also support wise planning, use, and preservation of natural resources. We are using the Landsat archive in two ways to provide needed information about land cover change since the year 2000 in seven East African countries (Ethiopia, Kenya, Malawi, Rwanda, Tanzania, Uganda, and Zambia). First, we are working with local experts to interpret historical land cover change from historical imagery at a probabilistic sample of 2000 locations in each country. This will provide a statistical estimate of land cover change since 2000. Second, we will use the same data to calibrate and validate annual land cover maps for each country. Because spatial context can be critical to development planning through the identification of hot spots, these maps will be a useful complement to the statistical, country-level estimates of change. The Landsat platform is an ideal tool for mapping land cover change because it combines a mix of appropriate spatial and spectral resolution with unparalleled length of service (Landsat 1 launched in 1972). Pilot tests have shown that time series analysis accessing the entire Landsat archive (i.e., many images per year) improves classification accuracy and stability. It is anticipated that this project will meet the civil needs of both governmental and non-governmental users across a range of disciplines.

36 CFR 292.22 - Land category assignments.

Science.gov (United States)

2010-07-01

... land. (iv) Commercial land. (2) Not later than August 12, 1994, a map or maps displaying the privately... availability of this map or maps in the local newspapers of record. (b) Changes in land category assignment.../grazing land so long as the intended use or development is consistent with the standards in § 292.23 and...

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

High spatial resolution mapping of the Cerrado's land cover and land use types in the priority area for conservation Chapada da Contagem, Brazil.

Science.gov (United States)

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

2016-12-01

The Brazilian savanna, Cerrado, is the second largest biome over South America and the most floristically diverse savanna in the world. This biome is considered a conservation hotspot in respect to its biodiversity importance and rapid transformation of its landscape. The Cerrado's natural vegetation has been severely transformed by agriculture and pasture activities. Currently it is the main agricultural frontier in Brazil and one of the most threatened Brazilian biomes. This scenario results in environmental impacts such as ecosystems fragmentation as well as losses in connectivity, biodiversity and gene flow, changes in the microclimate and energy, carbon and nutrients cycles, among others. The Priority Areas for Conservation is a governmental program from Brazil that identifies areas with high conservation priority. One of this program's recommendation is a natural vegetation map including their major ecosystem classes. This study aims to generate more precise information for the Cerrado's vegetation. The main objective of this study is to identify which ecosystems are being prioritized and/or threatened by land use, refining information for further protection. In order to test methods, the priority area for conservation Chapada da Contagem was selected as the study site. This area is ranked as "extremely high priority" by the government and is located in the Federal District and Goias State, Brazil. Satellites with finer spatial resolution may improve the classification of the Cerrado's vegetation. Remote sensing methods and two criteria were tested using RapidEye 3A imagery (5m spatial resolution) collected in 2014 in order to classify the Cerrado's major land cover types of this area, as well as its land use. One criterion considers the Cerrado's major terrestrial ecosystems, which are divided into forest, savanna and grassland. The other involves scaling it down to the major physiognomic groups of each ecosystem. Other sources of environmental dataset such

Identification of soil erosion land surfaces by Landsat data analysis and processing

International Nuclear Information System (INIS)

Lo Curzio, S.

2009-01-01

In this paper, we outline the typical relationship between the spectral reflectance of aileron's on newly-formed land surfaces and the geo morphological features of the land surfaces at issue. These latter represent the products of superficial erosional processes due to the action of the gravity and/or water; thus, such land surfaces are highly representative of the strong soil degradation occurring in a wide area located on the boundary between Molise and Puglia regions (Southern Italy). The results of this study have been reported on thematic maps; on such maps, the detected erosional land surfaces have been mapped on the basis of their typical spectral signature. The study has been performed using Landsat satellite imagery data which have been then validated by means of field survey data. The satellite data have been processed using remote sensing techniques, such as: false colour composite, contrast stretching, principal component analysis and decorrelation stretching. The study has permitted to produce, in a relatively short time and at low expense, a map of the eroded land surfaces. Such a result represents a first and fundamental step in evaluating and monitoring the erosional processes in the study area [it

Agroforestry suitability analysis based upon nutrient availability mapping: a GIS based suitability mapping

Directory of Open Access Journals (Sweden)

Firoz Ahmad

2017-05-01

Full Text Available Agroforestry has drawn the attention of researchers due to its capacity to reduce the poverty and land degradation, improve food security and mitigate the climate change. However, the progress in promoting agroforestry is held back due to the lack of reliable data sets and appropriate tools to accurately map and to have an adequate decision making system for agroforestry modules. Agroforestry suitability being one special form of land suitability is very pertinent to study in the current times when there is tremendous pressure on the land as it is a limited commodity. The study aims for applying the geo-spatial tools towards visualizing various soil and environmental data to reveal the trends and interrelationships and to achieve a nutrient availability and agroforestry suitability map. Using weight matrix and ranks, individual maps were developed in ArcGIS 10.1 platform to generate nutrient availability map, which was later used to develop agroforestry suitability map. Watersheds were delineated using DEM in some part of the study area and were evaluated for prioritizing it and agroforestry suitability of the watersheds were also done as per the schematic flowchart. Agroforestry suitability regions were delineated based upon the weight and ranks by integrated mapping. The total open area was identified 42.4% out of which 21.6% area was found to have high suitability towards agroforestry. Within the watersheds, 22 village points were generated for creating buffers, which were further evaluated showing its proximity to high suitable agroforestry sites thus generating tremendous opportunity to the villagers to carry out agroforestry projects locally. This research shows the capability of remote sensing in studying agroforestry practices and in estimating the prominent factors for its optimal productivity. The ongoing agroforestry projects can be potentially diverted in the areas of high suitability as an extension. The use of ancillary data in GIS

Map showing areas of visible land disturbances caused by two military training operations in the Mojave Desert, California

Science.gov (United States)

Prose, D.V.

1986-01-01

This map shows areas that retain visible land disturbances produced during two military armored-vehicle training operations in the Mojave Desert, California. The map documents the lasting visual effects these operations have on this arid region and provides a data base for monitoring changes in the extent of visual disturbances in the future.

Mapping land cover change over continental Africa using Landsat and Google Earth Engine cloud computing.

Science.gov (United States)

Midekisa, Alemayehu; Holl, Felix; Savory, David J; Andrade-Pacheco, Ricardo; Gething, Peter W; Bennett, Adam; Sturrock, Hugh J W

2017-01-01

Quantifying and monitoring the spatial and temporal dynamics of the global land cover is critical for better understanding many of the Earth's land surface processes. However, the lack of regularly updated, continental-scale, and high spatial resolution (30 m) land cover data limit our ability to better understand the spatial extent and the temporal dynamics of land surface changes. Despite the free availability of high spatial resolution Landsat satellite data, continental-scale land cover mapping using high resolution Landsat satellite data was not feasible until now due to the need for high-performance computing to store, process, and analyze this large volume of high resolution satellite data. In this study, we present an approach to quantify continental land cover and impervious surface changes over a long period of time (15 years) using high resolution Landsat satellite observations and Google Earth Engine cloud computing platform. The approach applied here to overcome the computational challenges of handling big earth observation data by using cloud computing can help scientists and practitioners who lack high-performance computational resources.

High Resolution Urban Land Cover Mapping Using NAIP Aerial Photography and Image Processing for the USEPA National Atlas of Sustainability and Ecosystem Services

Science.gov (United States)

Pilant, A. N.; Baynes, J.; Dannenberg, M.

2012-12-01

The US EPA National Atlas for Sustainability is a web-based, easy-to-use, mapping application that allows users to view and analyze multiple ecosystem services in a specific region. The Atlas provides users with a visual method for interpreting ecosystem services and understanding how they can be conserved and enhanced for a sustainable future. The Urban Atlas component of the National Atlas will provide fine-scale information linking human health and well-being to environmental conditions such as urban heat islands, near-road pollution, resource use, access to recreation, drinking water quality and other quality of life indicators. The National Land Cover Data (NLCD) derived from 30 m scale 2006 Landsat imagery provides the land cover base for the Atlas. However, urban features and phenomena occur at finer spatial scales, so higher spatial resolution and more current LC maps are required. We used 4 band USDA NAIP imagery (1 m pixel size) and various classification approaches to produce urban land cover maps with these classes: impervious surface, grass and herbaceous, trees and forest, soil and barren, and water. Here we present the remote sensing methods used and results from four pilot cities in this effort, highlighting the pros and cons of the approach, and the benefits to sustainability and ecosystem services analysis. Example of high resolution land cover map derived from USDA NAIP aerial photo. Compare 30 m and 1 m resolution land cover maps of downtown Durham, NC.

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

Directory of Open Access Journals (Sweden)

Brian A. Johnson

2018-01-01

Full Text Available The advent of very high resolution (VHR satellite imagery and the development of Geographic Object-Based Image Analysis (GEOBIA have led to many new opportunities for fine-scale land cover mapping, especially in urban areas. Image segmentation is an important step in the GEOBIA framework, so great time/effort is often spent to ensure that computer-generated image segments closely match real-world objects of interest. In the remote sensing community, segmentation is frequently performed using the multiresolution segmentation (MRS algorithm, which is tuned through three user-defined parameters (the scale, shape/color, and compactness/smoothness parameters. The scale parameter (SP is the most important parameter and governs the average size of generated image segments. Existing automatic methods to determine suitable SPs for segmentation are scene-specific and often computationally intensive, so an approach to estimating appropriate SPs that is generalizable (i.e., not scene-specific could speed up the GEOBIA workflow considerably. In this study, we attempted to identify generalizable SPs for five common urban land cover types (buildings, vegetation, roads, bare soil, and water through meta-analysis and nonlinear regression tree (RT modeling. First, we performed a literature search of recent studies that employed GEOBIA for urban land cover mapping and extracted the MRS parameters used, the image properties (i.e., spatial and radiometric resolutions, and the land cover classes mapped. Using this data extracted from the literature, we constructed RT models for each land cover class to predict suitable SP values based on the: image spatial resolution, image radiometric resolution, shape/color parameter, and compactness/smoothness parameter. Based on a visual and quantitative analysis of results, we found that for all land cover classes except water, relatively accurate SPs could be identified using our RT modeling results. The main advantage of our

Census Cities experiment in urban change detection. [mapping of land use changes in San Francisco, Washington D.C., Phoenix, Tucson, Boston, New Haven, Cedar Rapids, and Pontiac

Science.gov (United States)

Wray, J. R. (Principal Investigator); Milazzo, V. A.

1974-01-01

The author has identified the following significant results. Mapping of 1970 and 1972 land use from high-flight photography has been completed for all test sites: San Francisco, Washington, Phoenix, Tucson, Boston, New Haven, Cedar Rapids, and Pontiac. Area analysis of 1970 and 1972 land use has been completed for each of the mandatory urban areas. All 44 sections of the 1970 land use maps of the San Francisco test site have been officially released through USGS Open File at 1:62,500. Five thousand copies of the Washington one-sheet color 1970 land use map, census tract map, and point line identification map are being printed by USGS Publication Division. ERTS-1 imagery for each of the eight test sites is being received and analyzed. Color infrared photo enlargements at 1:100,000 of ERTS-1 MSS images of Phoenix taken on October 16, 1972 and May 2, 1973 are being analyzed to determine to what level land use and land use changes can be identified and to what extent the ERTS-1 imagery can be used in updating the 1970 aircraft photo-derived land use data base. Work is proceeding on the analysis of ERTS-1 imagery by computer manipulation of ERTS-1 MSS data in digital format. ERTS-1 CCT maps at 1:24,000 are being analyzed for two dates over Washington and Phoenix. Anniversary tape sets have been received at Purdue LARS for some additional urban test sites.

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.

Remote sensing in Iowa agriculture. [land use, crop identification, and soil mapping

Science.gov (United States)

Mahlstede, J. P. (Principal Investigator); Carlson, R. E.; Fenton, T. E.

1974-01-01

The author has identified the following significant results. Analysis of 1972 single-date coverage indicated that a complete crop classification was not attainable at the test sites. Good multi-date coverage during 1973 indicates that many of the problems encountered in 1972 will be minimized. In addition, the compilation of springtime imagery covering the entire state of Iowa has added a new dimension to interpretation of Iowa's natural resources. ERTS-1 has provided data necessary to achieve the broad synoptic view not attainable through other means. This should provide soils and crop researchers and land use planners a base map of Iowa. Granted and due to the resolution of ERTS-1, not all details are observable for many land use planning needs, but this gives a general and current view of Iowa.

LANDS CARTOGRAPHY: A MESOAMERICAN HERITAGE

Directory of Open Access Journals (Sweden)

David Pájaro Huertas

2010-05-01

Full Text Available Land maps, like prehispanic mesoamerican maps, do notuse Euclidean projections, which are based on ahumanistic or social projection. The spatial reality inthese maps is defined and structured by socialrelationships. Thus, a land map represents a communityshowing its territory and history, and not only an area likein conventional technical maps. A land map is a“communicentric projection” of the “egocentricperception” of the peasant, and can be defined as theprojection in graphic symbols of the spatial relationshipsabstracted from the knowledge available in cognitivemaps of the environments known by the peasant, ratherthan the result of sophisticated techniques, such as thoseused in soil surveys or remote perception.

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

Science.gov (United States)

Hester, David Barry

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

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

Science.gov (United States)

Daniel, C.C.

1978-01-01

A land use, land cover, and drainage map of the 2,000-square-mile Albermarle-Pamlico peninsula of eastern North Carolina has been prepared, at a scale of 1:125,000, as part of a larger study of the effects of large-scale land clearing on regional hydrology. The peninsula includes the most extensive area of wetland in North Carolina and one of the largest in the country. In recent years the pace of land clearing on the peninsula has accelerated as land is being converted from forest, swamp, and brushland to agricultural use. Conversion of swamps to intensive farming operations requires profound changes in the landscape. Vegetation is uprooted and burned and ditches and canals are dug to remove excess water. What is the impact of these changes on ground-water supplies and on the streams and surrounding coastal waters which receive the runoff This map will aid in answering these and similar questions that have arisen about the patterns of land use and the artificial drainage system that removes excess water from the land. By showing both land use and drainage, this map can be used to identify those areas where water-related problems may occur and help assess the nature and causes of these problems. The map covers the entire area east of the Suffolk Scarp, an area of about 2,000 square miles, for the year 1974 using data from 1974-76. Land use and land cover were compiled and modified from the U.S. Geological Survey 's Rocky Mount and Manteo LUDA maps. Additional information came from U.S. Geological Survey orthophotoquads, Landsat imagery, and field checking. Drainage was mapped from orthophotoquads, some field inspection, and 7-1/2 minute topographic quadrangle maps.

Annual land cover change mapping using MODIS time series to improve emissions inventories.

Science.gov (United States)

López Saldaña, G.; Quaife, T. L.; Clifford, D.

2014-12-01

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 prototype land cover product was created for 2006 to 2008. Several machine learning classifiers were tested as well as different sets of input features going from the BRDF parameters to spectral Albedo. We will present the results of the time series development and the first exercises when creating the prototype land cover product.

Historical Topographic Map Collection bookmark

Science.gov (United States)

Fishburn, Kristin A.; Allord, Gregory J.

2017-06-29

The U.S. Geological Survey (USGS) National Geospatial Program is scanning published USGS 1:250,000-scale and larger topographic maps printed between 1884, the inception of the topographic mapping program, and 2006. The goal of this project, which began publishing the historical scanned maps in 2011, is to provide a digital repository of USGS topographic maps, available to the public at no cost. For more than 125 years, USGS topographic maps have accurately portrayed the complex geography of the Nation. The USGS is the Nation’s largest producer of printed topographic maps, and prior to 2006, USGS topographic maps were created using traditional cartographic methods and printed using a lithographic printing process. As the USGS continues the release of a new generation of topographic maps (US Topo) in electronic form, the topographic map remains an indispensable tool for government, science, industry, land management planning, and leisure.

Toward an operational framework for fine-scale urban land-cover mapping in Wallonia using submeter remote sensing and ancillary vector data

Science.gov (United States)

Beaumont, Benjamin; Grippa, Tais; Lennert, Moritz; Vanhuysse, Sabine; Stephenne, Nathalie; Wolff, Eléonore

2017-07-01

Encouraged by the EU INSPIRE directive requirements and recommendations, the Walloon authorities, similar to other EU regional or national authorities, want to develop operational land-cover (LC) and land-use (LU) mapping methods using existing geodata. Urban planners and environmental monitoring stakeholders of Wallonia have to rely on outdated, mixed, and incomplete LC and LU information. The current reference map is 10-years old. The two object-based classification methods, i.e., a rule- and a classifier-based method, for detailed regional urban LC mapping are compared. The added value of using the different existing geospatial datasets in the process is assessed. This includes the comparison between satellite and aerial optical data in terms of mapping accuracies, visual quality of the map, costs, processing, data availability, and property rights. The combination of spectral, tridimensional, and vector data provides accuracy values close to 0.90 for mapping the LC into nine categories with a minimum mapping unit of 15 m2. Such a detailed LC map offers opportunities for fine-scale environmental and spatial planning activities. Still, the regional application poses challenges regarding automation, big data handling, and processing time, which are discussed.

Mapping the Influence of Land Use/Land Cover Changes on the Urban Heat Island Effect—A Case Study of Changchun, China

Directory of Open Access Journals (Sweden)

Chaobin Yang

2017-02-01

Full Text Available The spatio-temporal patterns of land use/land cover changes (LUCC can significantly affect the distribution and intensity of the urban heat island (UHI effect. However, few studies have mapped a clear picture of the influence of LUCC on UHI. In this study, both qualitative and quantitative models are employed to explore the effect of LUCC on UHI. UHI and LUCC maps were retrieved from Landsat data acquired from 1984, 1992, 2000, 2007, and 2014 to show their spatiotemporal patterns. The results showed that: (1 both the patterns of LUCC and UHI have had dramatic changes in the past 30 years. The urban area of Changchun increased more than four times, from 143.15 km2 in 1984 to 577.45 km2 in 2014, and the proportion of UHI regions has increased from 15.27% in 1984 to 29.62% in 2014; (2 the spatiotemporal changes in thermal environment were consistent with the process of urbanization. The average LST of the study area has been continuously increasing as many other land use types have been transformed to urban regions. The mean temperatures were higher in urban regions than rural areas over all of the periods, but the UHI intensity varied based on different measurements; and (3 the thermal environment inside the city varied widely even within a small area. The LST possesses a very strong positive relationship with impervious surface area (ISA, and the relationship has become stronger in recent years. The UHI we employ, specifically in this study, is SUHI (surface urban heat island.

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

Science.gov (United States)

Bayoudh, Meriam; Roux, Emmanuel; Richard, Gilles; Nock, Richard

2015-03-01

The number of satellites and sensors devoted to Earth observation has become increasingly elevated, delivering extensive data, especially images. At the same time, the access to such data and the tools needed to process them has considerably improved. In the presence of such data flow, we need automatic image interpretation methods, especially when it comes to the monitoring and prediction of environmental and societal changes in highly dynamic socio-environmental contexts. This could be accomplished via artificial intelligence. The concept described here relies on the induction of classification rules that explicitly take into account structural knowledge, using Aleph, an Inductive Logic Programming (ILP) system, combined with a multi-class classification procedure. This methodology was used to monitor changes in land cover/use of the French Guiana coastline. One hundred and fifty-eight classification rules were induced from 3 diachronic land cover/use maps including 38 classes. These rules were expressed in first order logic language, which makes them easily understandable by non-experts. A 10-fold cross-validation gave significant average values of 84.62%, 99.57% and 77.22% for classification accuracy, specificity and sensitivity, respectively. Our methodology could be beneficial to automatically classify new objects and to facilitate object-based classification procedures.

Multiscale mapping of species diversity under changed land use using imaging spectroscopy.

Science.gov (United States)

Paz-Kagan, Tarin; Caras, Tamir; Herrmann, Ittai; Shachak, Moshe; Karnieli, Arnon

2017-07-01

Land use changes are one of the most important factors causing environmental transformations and species diversity alterations. The aim of the current study was to develop a geoinformatics-based framework to quantify alpha and beta diversity indices in two sites in Israel with different land uses, i.e., an agricultural system of fruit orchards, an afforestation system of planted groves, and an unmanaged system of groves. The framework comprises four scaling steps: (1) classification of a tree species distribution (SD) map using imaging spectroscopy (IS) at a pixel size of 1 m; (2) estimation of local species richness by calculating the alpha diversity index for 30-m grid cells; (3) calculation of beta diversity for different land use categories and sub-categories at different sizes; and (4) calculation of the beta diversity difference between the two sites. The SD was classified based on a hyperspectral image with 448 bands within the 380-2500 nm spectral range and a spatial resolution of 1 m. Twenty-three tree species were classified with high overall accuracy values of 82.57% and 86.93% for the two sites. Significantly high values of the alpha index characterize the unmanaged land use, and the lowest values were calculated for the agricultural land use. In addition, high values of alpha indices were found at the borders between the polygons related to the "edge-effect" phenomenon, whereas low alpha indices were found in areas with high invasion species rates. The beta index value, calculated for 58 polygons, was significantly lower in the agricultural land use. The suggested framework of this study succeeded in quantifying land use effects on tree species distribution, evenness, and richness. IS and spatial statistics techniques offer an opportunity to study woody plant species variation with a multiscale approach that is useful for managing land use, especially under increasing environmental changes. © 2017 by the Ecological Society of America.

A Tool for Creating Regionally Calibrated High-Resolution Land Cover Data Sets for the West African Sahel: Using Machine Learning to Scale Up Hand-Classified Maps in a Data-Sparse Environment

Science.gov (United States)

Van Gordon, M.; Van Gordon, S.; Min, A.; Sullivan, J.; Weiner, Z.; Tappan, G. G.

2017-12-01

Using support vector machine (SVM) learning and high-accuracy hand-classified maps, we have developed a publicly available land cover classification tool for the West African Sahel. Our classifier produces high-resolution and regionally calibrated land cover maps for the Sahel, representing a significant contribution to the data available for this region. Global land cover products are unreliable for the Sahel, and accurate land cover data for the region are sparse. To address this gap, the U.S. Geological Survey and the Regional Center for Agriculture, Hydrology and Meteorology (AGRHYMET) in Niger produced high-quality land cover maps for the region via hand-classification of Landsat images. This method produces highly accurate maps, but the time and labor required constrain the spatial and temporal resolution of the data products. By using these hand-classified maps alongside SVM techniques, we successfully increase the resolution of the land cover maps by 1-2 orders of magnitude, from 2km-decadal resolution to 30m-annual resolution. These high-resolution regionally calibrated land cover datasets, along with the classifier we developed to produce them, lay the foundation for major advances in studies of land surface processes in the region. These datasets will provide more accurate inputs for food security modeling, hydrologic modeling, analyses of land cover change and climate change adaptation efforts. The land cover classification tool we have developed will be publicly available for use in creating additional West Africa land cover datasets with future remote sensing data and can be adapted for use in other parts of the world.

Using widely spaced observations of land use, forest attributes, and intrusions to map resource potential and human impact probability

Science.gov (United States)

Victor A. Rudis

2000-01-01

Scant information exists about the spatial extent of human impact on forest resource supplies, i.e., depreciative and nonforest uses. I used observations of ground-sampled land use and intrusions on forest land to map the probability of resource use and human impact for broad areas. Data came from a seven State survey region (Alabama, Arkansas, Louisiana, Mississippi,...

Using widely spaced observations of land use, forest attributes, and intrusions to map resource potential and human impact probability

Science.gov (United States)

Victor A. Rudis

2000-01-01

Scant information exists about the spatial extent of human impact on forest resource supplies, i.e., depreciative and nonforest uses. I used observations of ground-sampled land use and intrusions on forest land to map the probability of resource use and human impact for broad areas. Data came from a seven-state survey region (Alabama, Arkansas, Louisiana, Mississippi,...

A Simple Map Between Fokker-Planck Equation and its Fractional form

International Nuclear Information System (INIS)

Zahran, M.A.; El-Shewy, E.K.

2008-01-01

A simple map between Fokker-Planck Equation (FPE) and its fractional form (FFPE), which recently formulates to describe sub diffusive processes, has been suggested. This connection based on a relation between k-orders for moments of ordinary time domain of FPE and the moments associated with fractional time domain of FFPE . Two classes of special interest of FFPE has been considered to outline this map

Improved failure prediction in forming simulations through pre-strain mapping

Science.gov (United States)

Upadhya, Siddharth; Staupendahl, Daniel; Heuse, Martin; Tekkaya, A. Erman

2018-05-01

The sensitivity of sheared edges of advanced high strength steel (AHSS) sheets to cracking during subsequent forming operations and the difficulty to predict this failure with any degree of accuracy using conventionally used FLC based failure criteria is a major problem plaguing the manufacturing industry. A possible method that allows for an accurate prediction of edge cracks is the simulation of the shearing operation and carryover of this model into a subsequent forming simulation. But even with an efficient combination of a solid element shearing operation and a shell element forming simulation, the need for a fine mesh, and the resulting high computation time makes this approach not viable from an industry point of view. The crack sensitivity of sheared edges is due to work hardening in the shear-affected zone (SAZ). A method to predict plastic strains induced by the shearing process is to measure the hardness after shearing and calculate the ultimate tensile strength as well as the flow stress. In combination with the flow curve, the relevant strain data can be obtained. To eliminate the time-intensive shearing simulation necessary to obtain the strain data in the SAZ, a new pre-strain mapping approach is proposed. The pre-strains to be mapped are, hereby, determined from hardness values obtained in the proximity of the sheared edge. To investigate the performance of this approach the ISO/TS 16630 hole expansion test was simulated with shell elements for different materials, whereby the pre-strains were mapped onto the edge of the hole. The hole expansion ratios obtained from such pre-strain mapped simulations are in close agreement with the experimental results. Furthermore, the simulations can be carried out with no increase in computation time, making this an interesting and viable solution for predicting edge failure due to shearing.

LUMIS: A Land Use Management Information System for urban planning

Science.gov (United States)

Paul, C. K.

1975-01-01

The Land Use Management Information System (LUMIS) consists of a methodology of compiling land use maps by means of air photo interpretation techniques, digitizing these and other maps into machine-readable form, and numerically overlaying these various maps in two computer software routines to provide land use and natural resource data files referenced to the individual census block. The two computer routines are the Polygon Intersection Overlay System (PIOS) and an interactive graphics APL program. A block referenced file of land use, natural resources, geology, elevation, slope, and fault-line items has been created and supplied to the Los Angeles Department of City Planning for the City's portion of the Santa Monica Mountains. In addition, the interactive system contains one hundred and seventy-three socio-economic data items created by merging the Third Count U.S. Census Bureau tapes and the Los Angeles County Secured Assessor File. This data can be graphically displayed for each and every block, block group, or tract for six test tracts in Woodland Hills, California. Other benefits of LUMIS are the knowledge of air photo availability, flight pattern coverage and frequencies, and private photogrammetry companies flying Southern California, as well as a formal Delphi study of relevant land use informational needs in the Santa Monicas.

Quantitative assessment of the scope of content of selected topographic maps of Polish lands from the 19th and the first half of the 20th century

Directory of Open Access Journals (Sweden)

Panecki Tomasz

2017-12-01

Full Text Available The author presents an overview of the scope of content of selected topographic maps of Polish lands from the 19th and the first half of the 20th century in its quantitative aspect. 19 maps were analysed and a common conceptual model linked to the Database of Topographic Objects (DBTO10k was developed on the basis of catalogues of object types. Quantitative statistics were also prepared for the object types from maps before and after harmonization. Differences between their numbers within the same maps reflect the conceptual variety of said maps. The number of types of objects (before and after harmonization was then juxtaposed with selected thematic layers: water network, transport network, land cover, buildings, structures, and equipment, land use complexes, localities and other objects. Such factors as scales, publication dates and topographic services which created analysed maps were also taken into consideration. Additionally, the analysed maps demonstrate uneven levels of generalization. Inclusion of objects typical for large-scale cartography on topographic and general maps is one of the distinctive features.

Types of Cadastral Maps in Slovak Republic and Accuracy of the Land Area

Directory of Open Access Journals (Sweden)

Seidlová Anna

2017-01-01

Full Text Available The technical progress has affected in all parts of science. This paper is reflecting the changes of creation and accuracy of the maps, used for tax purposes from Austria-Hungary to present. From the precision of coordinates of the break points, which are defining the running of boundary, depends the precision of the parcel area as well. This information is more important because of the prices of land in present.

Single-edition quadrangle maps

Science.gov (United States)

,

1998-01-01

In August 1993, the U.S. Geological Survey's (USGS) National Mapping Division and the U.S. Department of Agriculture's Forest Service signed an Interagency Agreement to begin a single-edition joint mapping program. This agreement established the coordination for producing and maintaining single-edition primary series topographic maps for quadrangles containing National Forest System lands. The joint mapping program saves money by eliminating duplication of effort by the agencies and results in a more frequent revision cycle for quadrangles containing national forests. Maps are revised on the basis of jointly developed standards and contain normal features mapped by the USGS, as well as additional features required for efficient management of National Forest System lands. Single-edition maps look slightly different but meet the content, accuracy, and quality criteria of other USGS products. The Forest Service is responsible for the land management of more than 191 million acres of land throughout the continental United States, Alaska, and Puerto Rico, including 155 national forests and 20 national grasslands. These areas make up the National Forest System lands and comprise more than 10,600 of the 56,000 primary series 7.5-minute quadrangle maps (15-minute in Alaska) covering the United States. The Forest Service has assumed responsibility for maintaining these maps, and the USGS remains responsible for printing and distributing them. Before the agreement, both agencies published similar maps of the same areas. The maps were used for different purposes, but had comparable types of features that were revised at different times. Now, the two products have been combined into one so that the revision cycle is stabilized and only one agency revises the maps, thus increasing the number of current maps available for National Forest System lands. This agreement has improved service to the public by requiring that the agencies share the same maps and that the maps meet a

Soil maps, field knowledge, forest inventory and Ecological-Economic Zoning as a basis for agricultural suitability of lands in Minas Gerais elaborated in GIS

Directory of Open Access Journals (Sweden)

Vladimir Antonio Silva

2013-12-01

Full Text Available Lands (broader concept than soils, including all elements of the environment: soils, geology, topography, climate, water resources, flora and fauna, and the effects of anthropogenic activities of the state of Minas Gerais are in different soil, climate and socio-economics conditions and suitability for the production of agricultural goods is therefore distinct and mapping of agricultural suitability of the state lands is crucial for planning guided sustainability. Geoprocessing uses geographic information treatment techniques and GIS allows to evaluate geographic phenomena and their interrelationships using digital maps. To evaluate the agricultural suitability of state lands, we used soil maps, field knowledge, forest inventories and databases related to Ecological-Economic Zoning (EEZ of Minas Gerais, to develop a map of land suitability in GIS. To do this, we have combined the maps of soil fertility, water stress, oxygen deficiency, vulnerability to erosion and impediments to mechanization. In terms of geographical expression, the main limiting factor of lands is soil fertility, followed by lack of water, impediments to mechanization and vulnerability to erosion. Regarding agricultural suitability, the group 2 (regular suitability for crops is the most comprehensive, representing 45.13% of the state. For management levels A and B, low and moderate technological level, respectively, the most expressive suitability class is the regular, followed by the restricted class and last, the adequate class, while for the management level C (high technological level the predominant class is the restricted. The predominant most intensive use type is for crops, whose area increases substantially with capital investment and technology (management levels B and C.

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

Land Area Change and Fractional Water Maps in the Chenier Plain, Louisiana, following Hurricane Rita (2005)

Science.gov (United States)

Palaseanu-Lovejoy, Monica; Kranenburg, Christine J.; Brock, John C.

2010-01-01

In this study, we estimated the changes in land and water coverage of a 1,961-square-kilometer (km2) area in Louisiana's Chenier Plain. The study area is roughly centered on the Sabine National Wildlife Refuge, which was impacted by Hurricane Rita on September 24, 2005. The objective of this study is twofold: (1) to provide pre- and post-Hurricane Rita moderate-resolution (30-meter (m)) fractional water maps based upon multiple source images, and (2) to quantify land and water coverage changes due to Hurricane Rita.

Land Treatment Digital Library

Science.gov (United States)

Pilliod, David S.; Welty, Justin L.

2013-01-01

The Land Treatment Digital Library (LTDL) was created by the U.S. Geological Survey to catalog legacy land treatment information on Bureau of Land Management lands in the western United States. The LTDL can be used by federal managers and scientists for compiling information for data-calls, producing maps, generating reports, and conducting analyses at varying spatial and temporal scales. The LTDL currently houses thousands of treatments from BLM lands across 10 states. Users can browse a map to find information on individual treatments, perform more complex queries to identify a set of treatments, and view graphs of treatment summary statistics.

Utility of Mobile phones to support In-situ data collection for Land Cover Mapping

Science.gov (United States)

Oduor, P.; Omondi, S.; Wahome, A.; Mugo, R. M.; Flores, A.

2017-12-01

With the compelling need to create better monitoring tools for our landscapes to enhance better decision making processes, it becomes imperative to do so in much more sophisticated yet simple ways. Making it possible to leverage untapped potential of our "lay men" at the same time enabling us to respond to the complexity of the information we have to get out. SERVIR Eastern and Southern Africa has developed a mobile app that can be utilized with very little prior knowledge or no knowledge at all to collect spatial information on land cover. This set of in-situ data can be collected by masses because the tools is very simple to use, and have this information fed in classification algorithms than can then be used to map out our ever changing landscape. The LULC Mapper is a subset of JiMap system and is able to pull the google earth imagery and open street maps to enable user familiarize with their location. It uses phone GPS, phone network information to map location coordinates and at the same time gives the user sample picture of what to categorize their landscape. The system is able to work offline and when user gets access to internet they can push the information into an amazon database as bulk data. The location details including geotagged photos allows the data to be used in development of a lot of spatial information including land cover data. The app is currently available in Google Play Store and will soon be uploaded on Appstore for utilization by a wider community. We foresee a lot of potential in this tool in terms of making data collection cheaper and affordable. Taking advantage of the advances made in phone technology. We envisage to do a data collection campaign where we can have the tool used for crowdsourcing.

Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics

Science.gov (United States)

Pervez, Md Shahriar; Brown, Jesslyn F.

2010-01-01

Accurate geospatial information on the extent of irrigated land improves our understanding of agricultural water use, local land surface processes, conservation or depletion of water resources, and components of the hydrologic budget. We have developed a method in a geospatial modeling framework that assimilates irrigation statistics with remotely sensed parameters describing vegetation growth conditions in areas with agricultural land cover to spatially identify irrigated lands at 250-m cell size across the conterminous United States for 2002. The geospatial model result, known as the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset (MIrAD-US), identified irrigated lands with reasonable accuracy in California and semiarid Great Plains states with overall accuracies of 92% and 75% and kappa statistics of 0.75 and 0.51, respectively. A quantitative accuracy assessment of MIrAD-US for the eastern region has not yet been conducted, and qualitative assessment shows that model improvements are needed for the humid eastern regions where the distinction in annual peak NDVI between irrigated and non-irrigated crops is minimal and county sizes are relatively small. This modeling approach enables consistent mapping of irrigated lands based upon USDA irrigation statistics and should lead to better understanding of spatial trends in irrigated lands across the conterminous United States. An improved version of the model with revised datasets is planned and will employ 2007 USDA irrigation statistics.

The USGS role in mapping the nation's submerged lands

Science.gov (United States)

Schwab, Bill; Haines, John

2004-01-01

The seabed provides habitat for a diverse marine life having commercial, recreational, and intrinsic value. The habitat value of the seabed is largely a function of the geological structure and related geological, biological, oceanologic, and geochemical processes. Of equal importance, the nation's submerged lands contain energy and mineral resources and are utilized for the siting of offshore infrastructure and waste disposal. Seabed character and processes influence the safety and viability of offshore operations. Seabed and subseabed characterization is a prerequisite for the assessment, protection, and utilization of both living and non-living marine resources. A comprehensive program to characterize and understand the nation's submerged lands requires scientific expertise in the fields of geology, biology, hydrography, and oceanography. The U.S. Geological Survey (USGS) has long experience as the Federal agency charged with conducting geologic research and mapping in both coastal and offshore regions. The USGS Coastal and Marine Geology Program (CMGP) leads the nation in expertise related to characterization of seabed and subseabed geology, geological processes, seabed dynamics, and (in collaboration with the National Oceanic and Atmospheric Administration (NOAA) and international partners) habitat geoscience. Numerous USGS studies show that sea-floor geology and processes determine the character and distribution of biological habitats, control coastal evolution, influence the coastal response to storm events and human alterations, and determine the occurrence and concentration of natural resources.

Determination of Some Land and Soil Characteristics of Siirt Province with Geographic Information System Analysis

Directory of Open Access Journals (Sweden)

Mehmet Arif ÖZYAZICI

2014-09-01

Full Text Available The main aim of this research was to determine some land and soil characteristics of Siirt province and to make database using Geographic Information System (GIS. The study area covers about 562619.5 ha. Firstly, digital elevation model was formed using topographic map of the Siirt province and after this process slope, aspect, elevation and hill shade maps were also produced. In addition to that, some data produced General Directory of Rural Services and climate data were used in this study. According to study results, west part of the Siirt province has almost flat area whereas, hilly and mountain area locate in north and east part of it. Therefore, slope degree increase from west to north and east ways. More than half of the study area’s soil types (65% is Brown forest soils. Besides, according to land use and land cover map about 44% and 31% of the study area covers by shrubbery-brush and pastures, respectively. According to erosion maps, approximately %90 of the Siirt province lands has medium, severe and very severe erosion problem. Lands that are suitable for agricultural activities are very limited in Siirt Province. Only about 9% of the total land was classified as I, II and III land capability classes. Moreover, investigated depth map of the study area about 85% of the study area has very shallow and shallow soil depth. Deep soils found on plain and valley located at west part of the study area.

A tale of two land uses in the American West: rural residential growth and energy development

Science.gov (United States)

Assal, Timothy J.; Montag, Jessica M.

2012-01-01

This paper describes a spatiotemporal land use map for a rural county in the western United States. Sublette County, Wyoming has undergone recent land use change in the form of heightened rural residential development on private land and increased energy development on both public and private land. In this study we integrate energy production data, population census data, ownership parcel data, and a series of Landsat Thematic Mapper and Enhanced Thematic Mapper scenes (over a 25-year period) to create a map that illustrates the changing landscape. Spatial change on the landscape is mapped at 30 square meters, congruent with a Landsat pixel. Sublette County has a wealth of wildlife and associated habitat which is affected by both types of growth. While we do not attempt to quantify the effect of disturbance on wildlife species, we believe our results can provide important baseline data that can be incorporated into land use planning and ecological-wildlife research at the landscape scale.

CARETS: A prototype regional environmental information system. Volume 6: Cost, accuracy and consistency comparisons of land use maps made from high-altitude aircraft photography and ERTS imagery

Science.gov (United States)

Alexander, R. H. (Principal Investigator); Fitzpatrick, K. A.

1975-01-01

The author has identified the following significant results. Level 2 land use maps produced at three scales (1:24,000, 1:100,000, and 1:250,000) from high altitude photography were compared with each other and with point data obtained in the field. The same procedures were employed to determine the accuracy of the Level 1 land use maps produced at 1:250,000 from high altitude photography and color composite ERTS imagery. Accuracy of the Level 2 maps was 84.9 percent at 1:24,000, 77.4 percent at 1:100,000 and 73.0 percent at 1:250,000. Accuracy of the Level 1 1:250,000 maps was 76.5 percent for aerial photographs and 69.5 percent for ERTS imagery. The cost of Level 2 land use mapping at 1:24,000 was found to be high ($11.93 per sq km). The cost of mapping at 1:100,000 ($1.75) was about two times as expensive as mapping at 1:250,000 ($.88), and the accuracy increased by only 4.4 percent.

Automated Land Cover Change Detection and Mapping from Hidden Parameter Estimates of Normalized Difference Vegetation Index (NDVI) Time-Series

Science.gov (United States)

Chakraborty, S.; Banerjee, A.; Gupta, S. K. S.; Christensen, P. R.; Papandreou-Suppappola, A.

2017-12-01

Multitemporal observations acquired frequently by satellites with short revisit periods such as the Moderate Resolution Imaging Spectroradiometer (MODIS), is an important source for modeling land cover. Due to the inherent seasonality of the land cover, harmonic modeling reveals hidden state parameters characteristic to it, which is used in classifying different land cover types and in detecting changes due to natural or anthropogenic factors. In this work, we use an eight day MODIS composite to create a Normalized Difference Vegetation Index (NDVI) time-series of ten years. Improved hidden parameter estimates of the nonlinear harmonic NDVI model are obtained using the Particle Filter (PF), a sequential Monte Carlo estimator. The nonlinear estimation based on PF is shown to improve parameter estimation for different land cover types compared to existing techniques that use the Extended Kalman Filter (EKF), due to linearization of the harmonic model. As these parameters are representative of a given land cover, its applicability in near real-time detection of land cover change is also studied by formulating a metric that captures parameter deviation due to change. The detection methodology is evaluated by considering change as a rare class problem. This approach is shown to detect change with minimum delay. Additionally, the degree of change within the change perimeter is non-uniform. By clustering the deviation in parameters due to change, this spatial variation in change severity is effectively mapped and validated with high spatial resolution change maps of the given regions.

Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery

Science.gov (United States)

Castillo, Jose Alan A.; Apan, Armando A.; Maraseni, Tek N.; Salmo, Severino G.

2017-12-01

The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82-0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8-28.5 Mg ha-1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement

Mapping paddy rice planting areas through time series analysis of MODIS land surface temperature and vegetation index data.

Science.gov (United States)

Zhang, Geli; Xiao, Xiangming; Dong, Jinwei; Kou, Weili; Jin, Cui; Qin, Yuanwei; Zhou, Yuting; Wang, Jie; Menarguez, Michael Angelo; Biradar, Chandrashekhar

2015-08-01

Knowledge of the area and spatial distribution of paddy rice is important for assessment of food security, management of water resources, and estimation of greenhouse gas (methane) emissions. Paddy rice agriculture has expanded rapidly in northeastern China in the last decade, but there are no updated maps of paddy rice fields in the region. Existing algorithms for identifying paddy rice fields are based on the unique physical features of paddy rice during the flooding and transplanting phases and use vegetation indices that are sensitive to the dynamics of the canopy and surface water content. However, the flooding phenomena in high latitude area could also be from spring snowmelt flooding. We used land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to determine the temporal window of flooding and rice transplantation over a year to improve the existing phenology-based approach. Other land cover types (e.g., evergreen vegetation, permanent water bodies, and sparse vegetation) with potential influences on paddy rice identification were removed (masked out) due to their different temporal profiles. The accuracy assessment using high-resolution images showed that the resultant MODIS-derived paddy rice map of northeastern China in 2010 had a high accuracy (producer and user accuracies of 92% and 96%, respectively). The MODIS-based map also had a comparable accuracy to the 2010 Landsat-based National Land Cover Dataset (NLCD) of China in terms of both area and spatial pattern. This study demonstrated that our improved algorithm by using both thermal and optical MODIS data, provides a robust, simple and automated approach to identify and map paddy rice fields in temperate and cold temperate zones, the northern frontier of rice planting.

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

Science.gov (United States)

Rokni Deilmai, B.; Ahmad, B. Bin; Zabihi, H.

2014-06-01

Mapping is essential for the analysis of the land use and land cover, which influence many environmental processes and properties. For the purpose of the creation of land cover maps, it is important to minimize error. These errors will propagate into later analyses based on these land cover maps. The reliability of land cover maps derived from remotely sensed data depends on an accurate classification. In this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber. Classification results indicate that SVM was more accurate than MLC. With demonstrated capability to produce reliable cover results, the SVM methods should be especially useful for land cover classification.

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

International Nuclear Information System (INIS)

Deilmai, B Rokni; Ahmad, B Bin; Zabihi, H

2014-01-01

Mapping is essential for the analysis of the land use and land cover, which influence many environmental processes and properties. For the purpose of the creation of land cover maps, it is important to minimize error. These errors will propagate into later analyses based on these land cover maps. The reliability of land cover maps derived from remotely sensed data depends on an accurate classification. In this study, we have analyzed multispectral data using two different classifiers including Maximum Likelihood Classifier (MLC) and Support Vector Machine (SVM). To pursue this aim, Landsat Thematic Mapper data and identical field-based training sample datasets in Johor Malaysia used for each classification method, which results indicate in five land cover classes forest, oil palm, urban area, water, rubber. Classification results indicate that SVM was more accurate than MLC. With demonstrated capability to produce reliable cover results, the SVM methods should be especially useful for land cover classification

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

-based land-use classifications. Aerial photography is typically selected for smaller landscapes (watershed-basin scale), for greater definition of the land-use categories, and for increased spatial resolution. Disadvantages of using photography include time-consuming digitization, high costs for imagery collection, and lack of seasonal data. Recently, the availability of high-resolution satellite imagery has generated a new category of LULC data product. These new datasets have similar strengths to the aerial-photo-based LULC in that they possess the potential for refined definition of land-use categories and increased spatial resolution but also have the benefit of satellite-based classifications, such as repeatability for change analysis. LULC classification based on high-resolution satellite imagery is still in the early stages of development but merits greater attention because environmental-monitoring and landscape-modeling programs rely heavily on LULC data. This publication summarizes land-use and land-cover mapping activities for Alabama and Mississippi coastal areas within the U.S. Geological Survey (USGS) Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project boundaries. Existing LULC datasets will be described, as well as imagery data sources and ancillary data that may provide ground-truth or satellite training data for a forthcoming land-cover classification. Finally, potential areas for a high-resolution land-cover classification in the Alabama-Mississippi region will be identified.

Mapping Impervious Surfaces Globally at 30m Resolution Using Landsat Global Land Survey Data

Science.gov (United States)

Brown de Colstoun, E.; Huang, C.; Wolfe, R. E.; Tan, B.; Tilton, J.; Smith, S.; Phillips, J.; Wang, P.; Ling, P.; Zhan, J.; Xu, X.; Taylor, M. P.

2013-12-01

Impervious surfaces, mainly artificial structures and roads, cover less than 1% of the world's land surface (1.3% over USA). Regardless of the relatively small coverage, impervious surfaces have a significant impact on the environment. They are the main source of the urban heat island effect, and affect not only the energy balance, but also hydrology and carbon cycling, and both land and aquatic ecosystem services. In the last several decades, the pace of converting natural land surface to impervious surfaces has increased. Quantitatively monitoring the growth of impervious surface expansion and associated urbanization has become a priority topic across both the physical and social sciences. The recent availability of consistent, global scale data sets at 30m resolution such as the Global Land Survey from the Landsat satellites provides an unprecedented opportunity to map global impervious cover and urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such a buildings, roads and parking lots. With long term GLS data now available for the 1975, 1990, 2000, 2005 and 2010 time periods, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. In the Global Land Survey - Imperviousness Mapping Project (GLS-IMP), we are producing the first global 30 m spatial resolution impervious cover data set. We have processed the GLS 2010 data set to surface reflectance (8500+ TM and ETM+ scenes) and are using a supervised classification method using a regression tree to produce continental scale impervious cover data sets. A very large set of accurate training samples is the key to the supervised classifications and is being derived through the interpretation of high spatial resolution (~2 m or less) commercial satellite data (Quickbird and Worldview2) available to us through the unclassified

Closed-form expressions for integrals of MKdV and sine-Gordon maps

International Nuclear Information System (INIS)

Kamp, Peter H van der; Rojas, O; Quispel, G R W

2007-01-01

We present closed-form expressions for approximately N integrals of 2N-dimensional maps. The maps are obtained by travelling wave reductions of the modified Korteweg-de Vries equation and of the sine-Gordon equation, respectively. We provide the integrating factors corresponding to the integrals. Moreover we show how the integrals and the integrating factors relate to the staircase method

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

Science.gov (United States)

Strode, Georgianna; Mesev, Victor; Thornton, Benjamin; Jerez, Marjorie; Tricarico, Thomas; McAlear, Tyler

2018-05-01

The terms `land use' and `land cover' typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cover tracts. We believe this is misleading, and feel we need to reiterate the well-established symbiosis of land uses as amalgams of land covers; in other words land covers are subsets of land use. Our paper addresses this spatially complex, and frequently ambiguous relationship, and posits that bivariate cartographic techniques are an ideal vehicle for representing both land use and land cover simultaneously. In more specific terms, we explore the use of nested symbology as ways to represent graphically land use and land cover, where land cover are circles nested with land use squares. We also investigate bivariate legends for representing statistical covariance as a means for visualizing the combinations of land use and cover. Lastly, we apply Sankey flow diagrams to further illustrate the complex, multifaceted relationships between land use and land cover. Our work is demonstrated on data representing land use and cover data for the US state of Florida.

A study of the utilization of ERTS-1 data from the Wabash River Basin. [crop identification, water resources, urban land use, soil mapping, and atmospheric modeling

Science.gov (United States)

Landgrebe, D. A. (Principal Investigator)

1974-01-01

The author has identified the following significant results. The most significant results were obtained in the water resources research, urban land use mapping, and soil association mapping projects. ERTS-1 data was used to classify water bodies to determine acreages and high agreement was obtained with USGS figures. Quantitative evaluation was achieved of urban land use classifications from ERTS-1 data and an overall test accuracy of 90.3% was observed. ERTS-1 data classifications of soil test sites were compared with soil association maps scaled to match the computer produced map and good agreement was observed. In some cases the ERTS-1 results proved to be more accurate than the soil association map.

Effects of Different Forms of Concept-Map Representation on Nursing Students’ Critical Thinking Performances

Directory of Open Access Journals (Sweden)

Chin-Yuan Lai

2015-06-01

Full Text Available Representation is important for problem solving. This study examined the effects of different forms of concept maps on nursing students’ performances of conceptualizing psychiatric patients’ problems. A quasi-experimental research design was adopted to investigate the effects. The participants were two classes of fourth-year students who were enrolled in a psychiatric nursing course in a nursing college. One class with 48 students served as the experimental group, and used web-based concepts map to represent patients’ problem. The other class with 50 students served as the control group, and used the traditional hierarchical concept mapping method. The results indicated that the concept maps drawn by the experimental group showed more nursing problem, supporting evidence, and relationships between nursing problems than those drawn by the control group. The web-based concept maps helped expand students’ thinking and promoted their causality reasoning. Different concept-map representation tools affected the process of students’ problem solving. The experimental learning activities promoted students’ understanding of concepts and ways of psychiatric patients’ care taking. To understand the effects of other types of concept maps, future research may guide students in using different forms of concept maps throughout the stages of nursing process.

Mapping 2000 2010 Impervious Surface Change in India Using Global Land Survey Landsat Data

Science.gov (United States)

Wang, Panshi; Huang, Chengquan; Brown De Colstoun, Eric C.

2017-01-01

Understanding and monitoring the environmental impacts of global urbanization requires better urban datasets. Continuous field impervious surface change (ISC) mapping using Landsat data is an effective way to quantify spatiotemporal dynamics of urbanization. It is well acknowledged that Landsat-based estimation of impervious surface is subject to seasonal and phenological variations. The overall goal of this paper is to map 200-02010 ISC for India using Global Land Survey datasets and training data only available for 2010. To this end, a method was developed that could transfer the regression tree model developed for mapping 2010 impervious surface to 2000 using an iterative training and prediction (ITP) approach An independent validation dataset was also developed using Google Earth imagery. Based on the reference ISC from the validation dataset, the RMSE of predicted ISC was estimated to be 18.4%. At 95% confidence, the total estimated ISC for India between 2000 and 2010 is 2274.62 +/- 7.84 sq km.

Mapping large-area landscape suitability for honey bees to assess the influence of land-use change on sustainability of national pollination services

Science.gov (United States)

Gallant, Alisa L.; Euliss, Ned H.; Browning, Zac

2014-01-01

Pollination is a critical ecosystem service affected by various drivers of land-use change, such as policies and programs aimed at land resources, market values for crop commodities, local land-management decisions, and shifts in climate. The United States is the world's most active market for pollination services by honey bees, and the Northern Great Plains provide the majority of bee colonies used to meet the Nation's annual pollination needs. Legislation requiring increased production of biofuel crops, increasing commodity prices for crops of little nutritional value for bees in the Northern Great Plains, and reductions in government programs aimed at promoting land conservation are converging to alter the regional landscape in ways that challenge beekeepers to provide adequate numbers of hives for national pollination services. We developed a spatially explicit model that identifies sites with the potential to support large apiaries based on local-scale land-cover requirements for honey bees. We produced maps of potential apiary locations for North Dakota, a leading producer of honey, based on land-cover maps representing (1) an annual time series compiled from existing operational products and (2) a realistic scenario of land change. We found that existing land-cover products lack sufficient local accuracy to monitor actual changes in landscape suitability for honey bees, but our model proved informative for evaluating effects on suitability under scenarios of land change. The scenario we implemented was aligned with current drivers of land-use change in the Northern Great Plains and highlighted the importance of conservation lands in landscapes intensively and extensively managed for crops.

Mapping of government land encroachment in Cameron Highlands using multiple remote sensing datasets

International Nuclear Information System (INIS)

Zin, M H M; Ahmad, B

2014-01-01

The cold and refreshing highland weather is one of the factors that give impact to socio-economic growth in Cameron Highlands. This unique weather of the highland surrounded by tropical rain forest can only be found in a few places in Malaysia. It makes this place a famous tourism attraction and also provides a very suitable temperature for agriculture activities. Thus it makes agriculture such as tea plantation, vegetable, fruits and flowers one of the biggest economic activities in Cameron Highlands. However unauthorized agriculture activities are rampant. The government land, mostly forest area have been encroached by farmers, in many cases indiscriminately cutting down trees and hill slopes. This study is meant to detect and assess this encroachment using multiple remote sensing datasets. The datasets were used together with cadastral parcel data where survey lines describe property boundary, pieces of land are subdivided into lots of government and private. The general maximum likelihood classification method was used on remote sensing image to classify the land-cover in the study area. Ground truth data from field observation were used to assess the accuracy of the classification. Cadastral parcel data was overlaid on the classification map in order to detect the encroachment area. The result of this study shows that there is a land cover change of 93.535 ha in the government land of the study area between years 2001 to 2010, nevertheless almost no encroachment took place in the studied forest reserve area. The result of this study will be useful for the authority in monitoring and managing the forest

Mapping of government land encroachment in Cameron Highlands using multiple remote sensing datasets

Science.gov (United States)

Zin, M. H. M.; Ahmad, B.

2014-02-01

The cold and refreshing highland weather is one of the factors that give impact to socio-economic growth in Cameron Highlands. This unique weather of the highland surrounded by tropical rain forest can only be found in a few places in Malaysia. It makes this place a famous tourism attraction and also provides a very suitable temperature for agriculture activities. Thus it makes agriculture such as tea plantation, vegetable, fruits and flowers one of the biggest economic activities in Cameron Highlands. However unauthorized agriculture activities are rampant. The government land, mostly forest area have been encroached by farmers, in many cases indiscriminately cutting down trees and hill slopes. This study is meant to detect and assess this encroachment using multiple remote sensing datasets. The datasets were used together with cadastral parcel data where survey lines describe property boundary, pieces of land are subdivided into lots of government and private. The general maximum likelihood classification method was used on remote sensing image to classify the land-cover in the study area. Ground truth data from field observation were used to assess the accuracy of the classification. Cadastral parcel data was overlaid on the classification map in order to detect the encroachment area. The result of this study shows that there is a land cover change of 93.535 ha in the government land of the study area between years 2001 to 2010, nevertheless almost no encroachment took place in the studied forest reserve area. The result of this study will be useful for the authority in monitoring and managing the forest.

Assessment of the thematic accuracy of land cover maps

DEFF Research Database (Denmark)

Høhle, Joachim

2015-01-01

were applied (‘Decision Tree’ and ‘Support Vector Machine’) using only two attributes (height above ground and normalized difference vegetation index) which both are derived from the images. The assessment of the thematic accuracy applied a stratified design and was based on accuracy measures...... methods perform equally for five classes. Trees are classified with a much better accuracy and a smaller confidence interval by means of the decision tree method. Buildings are classified by both methods with an accuracy of 99% (95% CI: 95%-100%) using independent 3D checkpoints. The average width......Several land cover maps are generated from aerial imagery and assessed by different approaches. The test site is an urban area in Europe for which six classes (‘building’, ‘hedge and bush’, ‘grass’, ‘road and parking lot’, ‘tree’, ‘wall and car port’) had to be derived. Two classification methods...

Development of land data sets for studies of global climate change

International Nuclear Information System (INIS)

Sadowski, F.G.; Watkins, A.H.

1991-01-01

The U.S. Geological Survey has begun a major initiative to organize, produce, and distribute land data sets that will support the land data requirements of the global change science community. Satellite image data sets, produced from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer sensors, will be developed to provide repetitive, synoptic coverage of regional, continental, and global land areas. These data sets, integrated with related land data and supplemented by coregistered Landsat data sets, will enable scientists to quantify the fundamental land surface attributes that are needed to model land surface processes, to detect and monitor land surface change, and to map land cover. These well-structured, consistent land data sets will form the historical record of land observations prior to the era of the National Aeronautics and Space Administration's Earth Observing System sensors

Airborne geoid mapping of land and sea areas of East Malaysia

Science.gov (United States)

Jamil, H.; Kadir, M.; Forsberg, R.; Olesen, A.; Isa, M. N.; Rasidi, S.; Mohamed, A.; Chihat, Z.; Nielsen, E.; Majid, F.; Talib, K.; Aman, S.

2017-02-01

This paper describes the development of a new geoid-based vertical datum from airborne gravity data, by the Department of Survey and Mapping Malaysia, on land and in the South China Sea out of the coast of East Malaysia region, covering an area of about 610,000 square kilometres. More than 107,000 km flight line of airborne gravity data over land and marine areas of East Malaysia has been combined to provide a seamless land-to-sea gravity field coverage; with an estimated accuracy of better than 2.0 mGal. The iMAR-IMU processed gravity anomaly data has been used during a 2014-2016 airborne survey to extend a composite gravity solution across a number of minor gaps on selected lines, using a draping technique. The geoid computations were all done with the GRAVSOFT suite of programs from DTU-Space. EGM2008 augmented with GOCE spherical harmonic model has been used to spherical harmonic degree N = 720. The gravimetric geoid first was tied at one tide-gauge (in Kota Kinabalu, KK2019) to produce a fitted geoid, my_geoid2017_fit_kk. The fitted geoid was offset from the gravimetric geoid by +0.852 m, based on the comparison at the tide-gauge benchmark KK2019. Consequently, orthometric height at the six other tide gauge stations was computed from HGPS Lev = hGPS - Nmy_geoid2017_.t_kk. Comparison of the conventional (HLev) and GPS-levelling heights (HGPS Lev) at the six tide gauge locations indicate RMS height difference of 2.6 cm. The final gravimetric geoidwas fitted to the seven tide gauge stations and is known as my_geoid2017_fit_east. The accuracy of the gravimetric geoid is estimated to be better than 5 cm across most of East Malaysia land and marine areas

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) .

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

International Nuclear Information System (INIS)

Faid, A.M.; Hinz, E.A.; Montgomery, H.

2003-01-01

The impact of land cover/land use on groundwater can be critical. Land cover / land use maps give an early warning for planners and developers to protect groundwater resources from depletion and preserve its sustain ability. These land cover / land use maps can be used for the planning of groundwater development to prevent the deterioration of the aquifer. The Research Institute for Groundwater of Egypt (RIGW) has carried out hydrogeological studies in 1990 to evaluate the potentiality of groundwater in Luxor area in southern Egypt close to the Nile valley. The region is characterized by a rapid and continuous increase in land reclamation and development on the fringes which surround the already heavily cultivated land within the Nile valley. This presented a need for continuous monitoring and information updating over a vast region in a short time and at a reasonable cost. This study illustrates how remote sensing techniques can be effectively used for monitoring changes in land cover / land use in an effort to aid groundwater management. Landsat Thematic Mapper (TM) data collected in 1984 and 2000 were processed and analyzed over the study area to produce land cover/land use maps. The Normalized Difference Vegetation Index (NDVI) technique is used for Landsat TM images of to quantify areas which are covered by vegetation. Results indicated significant increase in cultivated areas. Remote sensing results are compared with iso-piezo metric maps and iso-salinity maps that were produced in 1984 and 2000. Comparison of these maps indicates groundwater depletion and salinity increase from 1984 to 2000. We relate this to the increase of the area being cultivated

Egypt satellite images for land surface characterization

DEFF Research Database (Denmark)

Hasager, Charlotte Bay

images used for mapping the vegetation cover types and other land cover types in Egypt. The mapping ranges from 1 km resolution to 30 m resolution. The aim is to provide satellite image mapping with land surface characteristics relevant for roughness mapping.......Satellite images provide information on the land surface properties. From optical remote sensing images in the blue, green, red and near-infrared part of the electromagnetic spectrum it is possible to identify a large number of surface features. The report briefly describes different satellite...

Mapping tsunami impacts on land cover and related ecosystem service supply in Phang Nga, Thailand

Science.gov (United States)

Kaiser, G.; Burkhard, B.; Römer, H.; Sangkaew, S.; Graterol, R.; Haitook, T.; Sterr, H.; Sakuna-Schwartz, D.

2013-12-01

The 2004 Indian Ocean tsunami caused damages to coastal ecosystems and thus affected the livelihoods of the coastal communities who depend on services provided by these ecosystems. The paper presents a case study on evaluating and mapping the spatial and temporal impacts of the tsunami on land use and land cover (LULC) and related ecosystem service supply in the Phang Nga province, Thailand. The method includes local stakeholder interviews, field investigations, remote-sensing techniques, and GIS. Results provide an ecosystem services matrix with capacity scores for 18 LULC classes and 17 ecosystem functions and services as well as pre-/post-tsunami and recovery maps indicating changes in the ecosystem service supply capacities in the study area. Local stakeholder interviews revealed that mangroves, casuarina forest, mixed beach forest, coral reefs, tidal inlets, as well as wetlands (peat swamp forest) have the highest capacity to supply ecosystem services, while e.g. plantations have a lower capacity. The remote-sensing based damage and recovery analysis showed a loss of the ecosystem service supply capacities in almost all LULC classes for most of the services due to the tsunami. A fast recovery of LULC and related ecosystem service supply capacities within one year could be observed for e.g. beaches, while mangroves or casuarina forest needed several years to recover. Applying multi-temporal mapping the spatial variations of recovery could be visualised. While some patches of coastal forest were fully recovered after 3 yr, other patches were still affected and thus had a reduced capacity to supply ecosystem services. The ecosystem services maps can be used to quantify ecological values and their spatial distribution in the framework of a tsunami risk assessment. Beyond that they are considered to be a useful tool for spatial analysis in coastal risk management in Phang Nga.

The Neogene lakes on the Balkan land

Directory of Open Access Journals (Sweden)

Krstić Nadežda

2012-01-01

Full Text Available Palaeogeographic maps of the lacustrine Miocene and Pliocene have been constructed according to all the known geological data. The Lakes of the Balkan Land, depending on the tectonics, migrated due to causes from the deep subsurface. There are several phases of the Miocene lakes: the lowermost Miocene transiting from marine Oligocene, Lower, Middle, Upper Miocene covering, in patches, the main part of the Land. The Pliocene lakes spread mostly to the north of the Balkan Land and covered only its marginal parts. Other lake-like sediments, in fact freshened parts of the Black Sea Kuialnician (Upper Pliocene, stretched along the middle and southern portions of the Balkan Peninsula (to the south of the Balkan Mt.. Subsequently, the Balkan Peninsula was formed.

Embryonic origins of a motor system: motor dendrites form a myotopic map in Drosophila.

Directory of Open Access Journals (Sweden)

Matthias Landgraf

2003-11-01

Full Text Available The organisational principles of locomotor networks are less well understood than those of many sensory systems, where in-growing axon terminals form a central map of peripheral characteristics. Using the neuromuscular system of the Drosophila embryo as a model and retrograde tracing and genetic methods, we have uncovered principles underlying the organisation of the motor system. We find that dendritic arbors of motor neurons, rather than their cell bodies, are partitioned into domains to form a myotopic map, which represents centrally the distribution of body wall muscles peripherally. While muscles are segmental, the myotopic map is parasegmental in organisation. It forms by an active process of dendritic growth independent of the presence of target muscles, proper differentiation of glial cells, or (in its initial partitioning competitive interactions between adjacent dendritic domains. The arrangement of motor neuron dendrites into a myotopic map represents a first layer of organisation in the motor system. This is likely to be mirrored, at least in part, by endings of higher-order neurons from central pattern-generating circuits, which converge onto the motor neuron dendrites. These findings will greatly simplify the task of understanding how a locomotor system is assembled. Our results suggest that the cues that organise the myotopic map may be laid down early in development as the embryo subdivides into parasegmental units.

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.

Potential Land Mapping for Agricultural Extentification in Mengwi Sub-district to Support Food Balance in Badung Regency, Indonesia

Science.gov (United States)

Made Trigunasih, Ni; Lanya, Indayati; Ratna Adi, I. G. P.; Hutauruk, Jeremia; Feronika

2017-12-01

The availability of agricultural land for food crops, especially in Bali, is rapidly declining every year. The availability of rice fields in Badung regency, especially in Mengwi Sub-district until 2040 is no longer exist, this means that Mengwi Sub-district has lost the rice fields. The existence of land conversion will affect food availability for the country, so there will be food deficit. The food balance in Badung Regency in 2015 with Cultivation Index (IP) and initial productivity in each Sub-district showed a food deficit of 32,843.44 tons, then after increasing IP of 2,5 the productivity in Kecamatan Petang and Kuta at 7 tons / ha, and Abiansemal, Mengwi and North Kuta Sub-districts with 8 tons / ha which indicate a surplus in 2020 and 2030 respectively of 25,155.19 tons, and 3,401.79 tons. But in 2040 and 2050 there was a food deficiency of 18,434.78 tons and 11,824.82 tons respectively. Considering that productivity improvement efforts cannot rely solely on intensification approaches, but also need to be done with extensification or expansion of agricultural areas to support food production. This research was conducted in Mengwi Sub-district, Badung Regency. Mengwi Sub-district consists of 20 villages. The objectives of this research are: (1) to map potential land that can be converted to agricultural land of food crops, and (2) to know the amount of food demand to supply food balance in Badung Regency in 2040. Research methodology includes (1) preliminary study, (2) interpretation of satellite images, (3) mapping and measurement of land area, and (4) calculation of additional food availability. The results indicate that the potential land that can be converted to agricultural land for food crops is 132 ha, consists of 128.51 ha of mixed plantation and 3.49 ha of bare land/bush. The result of additional land produced 1601.73 tons of rice that increased the food availability in Mengwi Sub-district to 45425.7 tons. The addition of surplus in 2040 in Mengwi

Effect of land-use on the P forms of an Andisol

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Carlos Henríquez

2015-11-01

Full Text Available The effect of agricultural land use on the forms of P in a Typic Hapludand was evaluated. An area of 8.4 ha composed of 3 adjacent lots, dedicated for over 20 years to secondary forest and plantings of sugarcane and coffee, was chosen at Juan Viñas, Costa Rica. Soil samples were taken using an 8x6 grid layout of sampling points, spaced at 40 m. Soil samples were analyzed with the P fractionation methodology proposed by Hedley et ál. (1982. Total P varied between 936 and 2516 mg.kg-1. Both coffee and sugar cane lots (1934 y 1754 mg.kg-1 respectively, showed the highest values of total-P compared with the forest (1419 mg.kg- 1, suggesting a positive overall balance of P due to its accumulation through the years. The coffee area showed the highest values of P-labile and P-sesquioxides-Fe/Al, which was related to usual higher fertilization compared with areas of sugarcane and forest. The greatest value of P-residual was found in sugarcane with almost 48% of total P. The P-organic varied 27 to 29% of the total suggesting its importance as valuable sink of P. We conclude that the type of land use had a significant effect on the forms of P which was observed in both the quantity and distributionof different forms of P in soil.

Analyzing historical land use changes using a Historical Land Use Reconstruction Model: a case study in Zhenlai County, northeastern China

Science.gov (United States)

Yang, Yuanyuan; Zhang, Shuwen; Liu, Yansui; Xing, Xiaoshi; de Sherbinin, Alex

2017-01-01

Historical land use information is essential to understanding the impact of anthropogenic modification of land use/cover on the temporal dynamics of environmental and ecological issues. However, due to a lack of spatial explicitness, complete thematic details and the conversion types for historical land use changes, the majority of historical land use reconstructions do not sufficiently meet the requirements for an adequate model. Considering these shortcomings, we explored the possibility of constructing a spatially-explicit modeling framework (HLURM: Historical Land Use Reconstruction Model). Then a three-map comparison method was adopted to validate the projected reconstruction map. The reconstruction suggested that the HLURM model performed well in the spatial reconstruction of various land-use categories, and had a higher figure of merit (48.19%) than models used in other case studies. The largest land use/cover type in the study area was determined to be grassland, followed by arable land and wetland. Using the three-map comparison, we noticed that the major discrepancies in land use changes among the three maps were as a result of inconsistencies in the classification of land-use categories during the study period, rather than as a result of the simulation model. PMID:28134342

Land use/land cover study of urban features using spot imagery

International Nuclear Information System (INIS)

Mahmood, S.A.; Qureshi, J.; Abbas, I.

2005-01-01

This study is based on visual interpretation and classification of the urban area of Peshawar. Cloud free satellite image of the French SPOT System in panchromatic mode at 100m/pixel spatial detail was used for this purpose. The coverage area comprised nearly (7.5 x 6)sq. km. on the ground depicting the major portion of the city. Various image interpretation elements were exploited to accomplish the study, thirteen land cover classes were identified and demarcated on a tracing sheet. Having prepared the base map. Satellite image map was constructed by assigning disparate colors to the identified features. Dimensions of some of the prominent, regular and liner features were computed from the image. The results indicate that high-resolution satellite image can be effectively used for mapping and area estimation of urban land use/land cover features. (author)

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.

Lunar Map Catalog

Data.gov (United States)

National Aeronautics and Space Administration — The Lunar Map Catalog includes various maps of the moon's surface, including Apollo landing sites; earthside, farside, and polar charts; photography index maps; zone...

LANDSAFE: LANDING SITE RISK ANALYSIS SOFTWARE FRAMEWORK

Directory of Open Access Journals (Sweden)

R. Schmidt

2012-08-01

Full Text Available The European Space Agency (ESA is planning a Lunar Lander mission in the 2018 timeframe that will demonstrate precise soft landing at the polar regions of the Moon. To ensure a safe and successful landing a careful risk analysis has to be carried out. This is comprised of identifying favorable target areas and evaluating the surface conditions in these areas. Features like craters, boulders, steep slopes, rough surfaces and shadow areas have to be identified in order to assess the risk associated to a landing site in terms of a successful touchdown and subsequent surface operation of the lander. In addition, global illumination conditions at the landing site have to be simulated and analyzed. The Landing Site Risk Analysis software framework (LandSAfe is a system for the analysis, selection and certification of safe landing sites on the lunar surface. LandSAfe generates several data products including high resolution digital terrain models (DTMs, hazard maps, illumination maps, temperature maps and surface reflectance maps which assist the user in evaluating potential landing site candidates. This paper presents the LandSAfe system and describes the methods and products of the different modules. For one candidate landing site on the rim of Shackleton crater at the south pole of the Moon a high resolution DTM is showcased.

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

International Nuclear Information System (INIS)

Bauer, T.B.

2001-08-01

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

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

Science.gov (United States)

Wray, J. R.

1982-01-01

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

The relevance of humus forms for land degradation in Mediterranean mountainous areas

Science.gov (United States)

Sevink, J.; Verstraten, J. M.; Jongejans, J.

1998-06-01

In the Gavarras (NE Spain), a large number of plots on respective schists, leucogranite and granodiorite was studied for their soils and vegetation. Results were used to check conclusions from earlier studies of Mediterranean forest soils (mostly shallow Regosols and Cambisols) on such acidic to intermediate rocks. They confirmed that the humus form depends on catenary position and lithology, and that aggregate stability and infiltration characteristics of the upper mineral soil horizon relate to humus form type. Aggregate stability of the topsoil was found to be relatively high in mor and mull type humus forms, but differences with moder type humus forms were not statistically significant. Differences in aggregate stability are attributed to the presence of stable humus-clay-iron complexes in mulls and to high fungal activity and organic matter content of mors. Low infiltration rates were only encountered in topsoils with mor type humus form, in line with results from the earlier studies. In deeper soil horizons with low organic matter content, aggregate stability will be largely related to soil reaction and base saturation. On leucogranite and granodiorite, these were found to vary strongly, most probably largely due to local differences in fast acid neutralizing capacity (ANC f). These local differences are primarily attributed to differences in the mineralogical composition and texture of the soil material, connected with differences in lithology and/or brought about by erosion, colluviation and soil formation. Consonant with earlier studies, it is concluded that the susceptibility of these forest soils to erosion largely depends on properties of the upper mineral soil horizon, which are controlled by or related with humus form development. General trends in the latter are clear and can be used to predict this susceptibility. In the case of land degradation, which implies a more severe erosion, deeper soil horizons are also involved. Spatial variability in

Mapping Multi-Cropped Land Use to Estimate Water Demand Using the California Pesticide Reporting Database

Science.gov (United States)

Henson, W.; Baillie, M. N.; Martin, D.

2017-12-01

Detailed and dynamic land-use data is one of the biggest data deficiencies facing food and water security issues. Better land-use data results in improved integrated hydrologic models that are needed to look at the feedback between land and water use, specifically for adequately representing changes and dynamics in rainfall-runoff, urban and agricultural water demands, and surface fluxes of water (e.g., evapotranspiration, runoff, and infiltration). Currently, land-use data typically are compiled from annual (e.g., Crop Scape) or multi-year composites if mapped at all. While this approach provides information about interannual land-use practices, it does not capture the dynamic changes in highly developed agricultural lands prevalent in California agriculture such as (1) dynamic land-use changes from high frequency multi-crop rotations and (2) uncertainty in sub-annual crop distribution, planting times, and cropped areas. California has collected spatially distributed data for agricultural pesticide use since 1974 through the California Pesticide Information Portal (CalPIP). A method leveraging the CalPIP database has been developed to provide vital information about dynamic agricultural land use (e.g., crop distribution and planting times) and water demand issues in Salinas Valley, California, along the central coast. This 7 billion dollar/year agricultural area produces up to 50% of U.S. lettuce and broccoli. Therefore, effective and sustainable water resource development in the area must balance the needs of this essential industry, other beneficial uses, and the environment. This new tool provides a way to provide more dynamic crop data in hydrologic models. While the current application focuses on the Salinas Valley, the methods are extensible to all of California and other states with similar pesticide reporting. The improvements in representing variability in crop patterns and associated water demands increase our understanding of land-use change and

Land cover mapping, fire regeneration, and scaling studies in the Canadian boreal forest with 1 km AVHRR and Landsat TM data

Science.gov (United States)

Steyaert, L.T.; Hall, F.G.; Loveland, Thomas R.

1997-01-01

A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km ?? 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within

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

Data.gov (United States)

NSGIC State | GIS Inventory — MoRAP produced and integrated data to map land cover and wetlands for the Upper Silver Creek Watershed in Illinois. LiDAR elevation and vegetation height information...

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

Data.gov (United States)

NSGIC State | GIS Inventory — MoRAP produced and integrated data to map land cover and wetlands for the Meramec River bottomland in Missouri. LiDAR elevation and vegetation height information and...

Mapping and Analysis of Forest and Land Fire Potential Using Geospatial Technology and Mathematical Modeling

International Nuclear Information System (INIS)

Suliman, M D H; Mahmud, M; Reba, M N M; S, L W

2014-01-01

Forest and land fire can cause negative implications for forest ecosystems, biodiversity, air quality and soil structure. However, the implications involved can be minimized through effective disaster management system. Effective disaster management mechanisms can be developed through appropriate early warning system as well as an efficient delivery system. This study tried to focus on two aspects, namely by mapping the potential of forest fire and land as well as the delivery of information to users through WebGIS application. Geospatial technology and mathematical modeling used in this study for identifying, classifying and mapping the potential area for burning. Mathematical models used is the Analytical Hierarchy Process (AHP), while Geospatial technologies involved include remote sensing, Geographic Information System (GIS) and digital field data collection. The entire Selangor state was chosen as our study area based on a number of cases have been reported over the last two decades. AHP modeling to assess the comparison between the three main criteria of fuel, topography and human factors design. Contributions of experts directly involved in forest fire fighting operations and land comprising officials from the Fire and Rescue Department Malaysia also evaluated in this model. The study found that about 32.83 square kilometers of the total area of Selangor state are the extreme potential for fire. Extreme potential areas identified are in Bestari Jaya and Kuala Langat High Ulu. Continuity of information and terrestrial forest fire potential was displayed in WebGIS applications on the internet. Display information through WebGIS applications is a better approach to help the decision-making process at a high level of confidence and approximate real conditions. Agencies involved in disaster management such as Jawatankuasa Pengurusan Dan Bantuan Bencana (JPBB) of District, State and the National under the National Security Division and the Fire and Rescue

Mapping and Analysis of Forest and Land Fire Potential Using Geospatial Technology and Mathematical Modeling

Science.gov (United States)

Suliman, M. D. H.; Mahmud, M.; Reba, M. N. M.; S, L. W.

2014-02-01

Forest and land fire can cause negative implications for forest ecosystems, biodiversity, air quality and soil structure. However, the implications involved can be minimized through effective disaster management system. Effective disaster management mechanisms can be developed through appropriate early warning system as well as an efficient delivery system. This study tried to focus on two aspects, namely by mapping the potential of forest fire and land as well as the delivery of information to users through WebGIS application. Geospatial technology and mathematical modeling used in this study for identifying, classifying and mapping the potential area for burning. Mathematical models used is the Analytical Hierarchy Process (AHP), while Geospatial technologies involved include remote sensing, Geographic Information System (GIS) and digital field data collection. The entire Selangor state was chosen as our study area based on a number of cases have been reported over the last two decades. AHP modeling to assess the comparison between the three main criteria of fuel, topography and human factors design. Contributions of experts directly involved in forest fire fighting operations and land comprising officials from the Fire and Rescue Department Malaysia also evaluated in this model. The study found that about 32.83 square kilometers of the total area of Selangor state are the extreme potential for fire. Extreme potential areas identified are in Bestari Jaya and Kuala Langat High Ulu. Continuity of information and terrestrial forest fire potential was displayed in WebGIS applications on the internet. Display information through WebGIS applications is a better approach to help the decision-making process at a high level of confidence and approximate real conditions. Agencies involved in disaster management such as Jawatankuasa Pengurusan Dan Bantuan Bencana (JPBB) of District, State and the National under the National Security Division and the Fire and Rescue

Geological hazards investigation - relative slope stability map

Energy Technology Data Exchange (ETDEWEB)

Han, Dae Suk; Kim, Won Young; Yu, Il Hyon; Kim, Kyeong Su; Lee, Sa Ro; Choi, Young Sup [Korea Institute of Geology Mining and Materials, Taejon (Korea, Republic of)

1997-12-01

The Republic of Korea is a mountainous country; the mountains occupy about three quarters of her land area, an increasing urban development being taken place along the mountainside. For the reason, planners as well as developers and others must realize that some of the urban areas may be threaten by geologic hazards such as landslides and accelerated soil and rock creeps. For the purpose of environmental land-use planning, a mapping project on relative slope-stability was established in 1996. The selected area encompasses about 5,900 km{sup 2} including the topographic maps of Ulsan, Yongchon, Kyongju, Pulguksa, and Kampo, all at a scale of 1:50,000. Many disturbed and undisturbed soil samples, which were collected from the ares of the landslides and unstable slopes, were tested for their physical properties and shear strength. They were classified as GC, SP, SC, SM, SP-SM, SC-SM, CL, ML, and MH according to the Unified Soil Classification System, their liquid limit and plasticity index ranging from 25.3% to as high as 81.3% and from 4.1% to 41.5%, respectively. X-ray analysis revealed that many of the soils contained a certain amount of montmorillonite. Based on the available information as well as both field and laboratory investigation, it was found out that the most common types of slope failures in the study area were both debris and mud flows induced by the heavy rainfalls during the period of rainy season; the flows mostly occurred in the colluvial deposits at the middle and foot of mountains. Thus the deposits generally appear to be the most unstable slope forming materials in the study area. Produced for the study area were six different maps consisting of slope classification map, soil classification map, lineament density map, landslide distribution map, zonal map of rainfall, and geology map, most of them being stored as data base. Using the first four maps and GIS, two sheets of relative slope-stability maps were constructed, each at a scale of 1

Enhancement of Tropical Land Cover Mapping with Wavelet-Based Fusion and Unsupervised Clustering of SAR and Landsat Image Data

Science.gov (United States)

LeMoigne, Jacqueline; Laporte, Nadine; Netanyahuy, Nathan S.; Zukor, Dorothy (Technical Monitor)

2001-01-01

The characterization and the mapping of land cover/land use of forest areas, such as the Central African rainforest, is a very complex task. This complexity is mainly due to the extent of such areas and, as a consequence, to the lack of full and continuous cloud-free coverage of those large regions by one single remote sensing instrument, In order to provide improved vegetation maps of Central Africa and to develop forest monitoring techniques for applications at the local and regional scales, we propose to utilize multi-sensor remote sensing observations coupled with in-situ data. Fusion and clustering of multi-sensor data are the first steps towards the development of such a forest monitoring system. In this paper, we will describe some preliminary experiments involving the fusion of SAR and Landsat image data of the Lope Reserve in Gabon. Similarly to previous fusion studies, our fusion method is wavelet-based. The fusion provides a new image data set which contains more detailed texture features and preserves the large homogeneous regions that are observed by the Thematic Mapper sensor. The fusion step is followed by unsupervised clustering and provides a vegetation map of the area.

Effects of Land Use on Concentrations and Chemical Forms of Phosphorus in Different-Size Aggregates

Science.gov (United States)

Ahmad, E. H.; Demisie, W.; Zhang, M.

2017-12-01

Land use has been recognized as an important driver of environmental change on all spatial and temporal scales. This study was conducted to determine the effects of land uses on phosphorus concentration in bulk soil and in water-stable aggregates in different soils. The study was conducted on three soil types (Ferrosols, Cambosols, and Primosols), which were collected from three different locations from southeast China and under three land uses (Uncultivated, Vegetable and forest land) the region is characterized as a hill and plain area. Accordingly, a total of 24 soil samples were collected. The results showed that average contents of total P were 0.55-1.55 g/kg, 0.28-1.03 g/kg and 0.14-0.8 g/kg for the soils: Cambosols, Ferrosols and Primosols respectively. Vegetable and forest land led to higher total phosphorus contents in these soils than in the uncultivated land. An aggregate fraction of >2 mm under forest land made up the largest percentage (30 up to 70%), whereas the size fraction phosphorus, organic phosphorus and Olsen P and phosphorus forms in the soils. It implies that the conversion of natural ecosystem to vegetable land increased the phosphorus proportion in the soils, which could have negative impact on the environmental quality.

Disaggregating and mapping crop statistics using hypertemporal remote sensing

Science.gov (United States)

Khan, M. R.; de Bie, C. A. J. M.; van Keulen, H.; Smaling, E. M. A.; Real, R.

2010-02-01

Governments compile their agricultural statistics in tabular form by administrative area, which gives no clue to the exact locations where specific crops are actually grown. Such data are poorly suited for early warning and assessment of crop production. 10-Daily satellite image time series of Andalucia, Spain, acquired since 1998 by the SPOT Vegetation Instrument in combination with reported crop area statistics were used to produce the required crop maps. Firstly, the 10-daily (1998-2006) 1-km resolution SPOT-Vegetation NDVI-images were used to stratify the study area in 45 map units through an iterative unsupervised classification process. Each unit represents an NDVI-profile showing changes in vegetation greenness over time which is assumed to relate to the types of land cover and land use present. Secondly, the areas of NDVI-units and the reported cropped areas by municipality were used to disaggregate the crop statistics. Adjusted R-squares were 98.8% for rainfed wheat, 97.5% for rainfed sunflower, and 76.5% for barley. Relating statistical data on areas cropped by municipality with the NDVI-based unit map showed that the selected crops were significantly related to specific NDVI-based map units. Other NDVI-profiles did not relate to the studied crops and represented other types of land use or land cover. The results were validated by using primary field data. These data were collected by the Spanish government from 2001 to 2005 through grid sampling within agricultural areas; each grid (block) contains three 700 m × 700 m segments. The validation showed 68%, 31% and 23% variability explained (adjusted R-squares) between the three produced maps and the thousands of segment data. Mainly variability within the delineated NDVI-units caused relatively low values; the units are internally heterogeneous. Variability between units is properly captured. The maps must accordingly be considered "small scale maps". These maps can be used to monitor crop performance of

South African National Land-Cover Change Map

African Journals Online (AJOL)

Fritz Schoeman

monitoring land-cover change at a national scale over time using EO data. 2. .... assist with final results reporting and analysis on a sub-national level. ..... South African Land-Cover Characteristics Database: A synopsis of the landscape.

Spatiotemporal Built-up Land Density Mapping Using Various Spectral Indices in Landsat-7 ETM+ and Landsat-8 OLI/TIRS (Case Study: Surakarta City)

Science.gov (United States)

Risky, Yanuar S.; Aulia, Yogi H.; Widayani, Prima

2017-12-01

Spectral indices variations support for rapid and accurate extracting information such as built-up density. However, the exact determination of spectral waves for built-up density extraction is lacking. This study explains and compares the capabilities of 5 variations of spectral indices in spatiotemporal built-up density mapping using Landsat-7 ETM+ and Landsat-8 OLI/TIRS in Surakarta City on 2002 and 2015. The spectral indices variations used are 3 mid-infrared (MIR) based indices such as the Normalized Difference Built-up Index (NDBI), Urban Index (UI) and Built-up and 2 visible based indices such as VrNIR-BI (visible red) and VgNIR-BI (visible green). Linear regression statistics between ground value samples from Google Earth image in 2002 and 2015 and spectral indices for determining built-up land density. Ground value used amounted to 27 samples for model and 7 samples for accuracy test. The classification of built-up density mapping is divided into 9 classes: unclassified, 0-12.5%, 12.5-25%, 25-37.5%, 37.5-50%, 50-62.5%, 62.5-75%, 75-87.5% and 87.5-100 %. Accuracy of built-up land density mapping in 2002 and 2015 using VrNIR-BI (81,823% and 73.235%), VgNIR-BI (78.934% and 69.028%), NDBI (34.870% and 74.365%), UI (43.273% and 64.398%) and Built-up (59.755% and 72.664%). Based all spectral indices, Surakarta City on 2000-2015 has increased of built-up land density. VgNIR-BI has better capabilities for built-up land density mapping on Landsat-7 ETM + and Landsat-8 OLI/TIRS.

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

Fast mapping of novel word forms traced neurophysiologically

Directory of Open Access Journals (Sweden)

Yury eShtyrov

2011-11-01

Full Text Available Human capacity to quickly learn new words, critical for our ability to communicate using language, is well-known from behavioural studies and observations, but its neural underpinnings remain unclear. In this study, we have used event-related potentials to record brain activity to novel spoken word forms as they are being learnt by the human nervous system through passive auditory exposure. We found that the brain response dynamics change dramatically within the short (20 min exposure session: as the subjects become familiarised with the novel word forms, the early (~100 ms fronto-central activity they elicit increases in magnitude and becomes similar to that of known real words. At the same time, acoustically similar real words used as control stimuli show a relatively stable response throughout the recording session; these differences between the stimulus groups are confirmed using both factorial and linear regression analyses. Furthermore, acoustically matched novel non-speech stimuli do not demonstrate similar response increase, suggesting neural specificity of this rapid learning phenomenon to linguistic stimuli. Left-lateralised perisylvian cortical networks appear to be underlying such fast mapping of novel word forms unto the brain’s mental lexicon.

The geo-genic radon potential map of the aspiring 'Buzau Land' Geo-park

International Nuclear Information System (INIS)

Moldovan, M. C.; Burghele, B. D.; Roba, C. A.; Sferle, T. L.; Buterez, C.; Mitrofan, H.

2017-01-01

Mapping the geo-genic radon potential in Buzau County is part of a research project aiming to apply research for sustainable development and economic growth following the principles of geo-conservation in order to support the 'Buzau Land' UNESCO Geo-park initiative. The mapping of geo-genic radon will be used as an overview for planning purposes. The main geological formations of the studied area were identified as Cretaceous and Paleogene flysch, included in a thin-skinned nappes pile and consisting of alternating sandstones, marls, clays and, subordinately, conglomerates, all tightly folded or faulted. Significant variations in the concentration of radon were therefore determined in the ground. However, no high values were determined, the maximum measured activity concentration being 101.6 kBq m -3 . (authors)

Analysis of land stability and land-use change processes in the 19–20th centuries: a case study in Gödöllő Hillside, Hungary

Directory of Open Access Journals (Sweden)

Demény Krisztina

2016-12-01

Full Text Available The manuscript presents land-use change processes based on former military map analyses. Military maps were derived from the 1770s until the 1890s and later from the CORINE Land Cover map. I observed the transition direction of areal distribution of various land uses. Digitalized maps showed 19-20th century land-use conditions; besides them, we created a grouping system which is based on the intensity of land use. We distinguished six land-use types, ranking them according to the anthropogenic influence (1. built-up areas; 2. arable fields; 3. orchards and vineyards; 4. meadows and pastures; 5. forests; 6. wetlands.

MX Siting Investigation. MX System Siting Summary Report. Land Acquisition Application Package Map Sheets. Volume III.

Science.gov (United States)

1982-01-18

Environmental Impact Statement DMA Defense Mapping Agency DOPAA Description of Proposed Actions and Alternatives DTA Designated Training Area DTN Designated...Transportation Network EIS Environmental Impact Statement FLPMA Federal Land Policy Management Act FNI Fugro National, Inc. FSED Full Scale Engineering...CONTRACT OR GRANT NUMBER(s) 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Cr+e wec - r Tniz. Q6 cr-% e rL!: Pktcxim Nat*’v

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

Directory of Open Access Journals (Sweden)

Chandra Giri

2014-10-01

Full Text Available Detailed and accurate land cover and land cover change information is needed for South America because the continent is in constant flux, experiencing some of the highest rates of land cover change and forest loss in the world. The land cover data available for the entire continent are too coarse (250 m to 1 km for resource managers, government and non-government organizations, and Earth scientists to develop conservation strategies, formulate resource management options, and monitor land cover dynamics. We used Landsat 30 m satellite data of 2010 and prepared the land cover database of South America using state-of-the-science remote sensing techniques. We produced regionally consistent and locally relevant land cover information by processing a large volume of data covering the entire continent. Our analysis revealed that in 2010, 50% of South America was covered by forests, 2.5% was covered by water, and 0.02% was covered by snow and ice. The percent forest area of South America varies from 9.5% in Uruguay to 96.5% in French Guiana. We used very high resolution (<5 m satellite data to validate the land cover product. The overall accuracy of the 2010 South American 30-m land cover map is 89% with a Kappa coefficient of 79%. Accuracy of barren areas needs to improve possibly using multi-temporal Landsat data. An update of land cover and change database of South America with additional land cover classes is needed. The results from this study are useful for developing resource management strategies, formulating biodiversity conservation strategies, and regular land cover monitoring and forecasting.

Assessment and mapping of water pollution indices in zone-III of municipal corporation of hyderabad using remote sensing and geographic information system.

Science.gov (United States)

Asadi, S S; Vuppala, Padmaja; Reddy, M Anji

2005-01-01

A preliminary survey of area under Zone-III of MCH was undertaken to assess the ground water quality, demonstrate its spatial distribution and correlate with the land use patterns using advance techniques of remote sensing and geographical information system (GIS). Twenty-seven ground water samples were collected and their chemical analysis was done to form the attribute database. Water quality index was calculated from the measured parameters, based on which the study area was classified into five groups with respect to suitability of water for drinking purpose. Thematic maps viz., base map, road network, drainage and land use/land cover were prepared from IRS ID PAN + LISS III merged satellite imagery forming the spatial database. Attribute database was integrated with spatial sampling locations map in Arc/Info and maps showing spatial distribution of water quality parameters were prepared in Arc View. Results indicated that high concentrations of total dissolved solids (TDS), nitrates, fluorides and total hardness were observed in few industrial and densely populated areas indicating deteriorated water quality while the other areas exhibited moderate to good water quality.

Regional geology mapping using satellite-based remote sensing approach in Northern Victoria Land, Antarctica

Science.gov (United States)

Pour, Amin Beiranvand; Park, Yongcheol; Park, Tae-Yoon S.; Hong, Jong Kuk; Hashim, Mazlan; Woo, Jusun; Ayoobi, Iman

2018-06-01

Satellite remote sensing imagery is especially useful for geological investigations in Antarctica because of its remoteness and extreme environmental conditions that constrain direct geological survey. The highest percentage of exposed rocks and soils in Antarctica occurs in Northern Victoria Land (NVL). Exposed Rocks in NVL were part of the paleo-Pacific margin of East Gondwana during the Paleozoic time. This investigation provides a satellite-based remote sensing approach for regional geological mapping in the NVL, Antarctica. Landsat-8 and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) datasets were used to extract lithological-structural and mineralogical information. Several spectral-band ratio indices were developed using Landsat-8 and ASTER bands and proposed for Antarctic environments to map spectral signatures of snow/ice, iron oxide/hydroxide minerals, Al-OH-bearing and Fe, Mg-OH and CO3 mineral zones, and quartz-rich felsic and mafic-to-ultramafic lithological units. The spectral-band ratio indices were tested and implemented to Level 1 terrain-corrected (L1T) products of Landsat-8 and ASTER datasets covering the NVL. The surface distribution of the mineral assemblages was mapped using the spectral-band ratio indices and verified by geological expeditions and laboratory analysis. Resultant image maps derived from spectral-band ratio indices that developed in this study are fairly accurate and correspond well with existing geological maps of the NVL. The spectral-band ratio indices developed in this study are especially useful for geological investigations in inaccessible locations and poorly exposed lithological units in Antarctica environments.

Three very high resolution optical images for land use mapping of a suburban catchment: input to distributed hydrological models

Science.gov (United States)

Jacqueminet, Christine; Kermadi, Saïda; Michel, Kristell; Jankowfsky, Sonja; Braud, Isabelle; Branger, Flora; Beal, David; Gagnage, Matthieu

2010-05-01

Keywords : land cover mapping, very high resolution, remote sensing processing techniques, object oriented approach, distributed hydrological model, peri-urban area Urbanization and other modifications of land use affect the hydrological cycle of suburban catchments. In order to quantify these impacts, the AVuPUR project (Assessing the Vulnerability of Peri-Urban Rivers) is currently developing a distributed hydrological model that includes anthropogenic features. The case study is the Yzeron catchment (150 km²), located close to Lyon city, France. This catchment experiences a growing of urbanization and a modification of traditional land use since the middle of the 20th century, resulting in an increase of flooding, water pollution and river banks erosion. This contribution discusses the potentials of automated data processing techniques on three different VHR images, in order to produce appropriate and detailed land cover data for the models. Of particular interest is the identification of impermeable surfaces (buildings, roads, and parking places) and permeable surfaces (forest areas, agricultural fields, gardens, trees…) within the catchment, because their infiltration capacity and their impact on runoff generation are different. Three aerial and spatial images were acquired: (1) BD Ortho IGN aerial images, 0.50 m resolution, visible bands, may 5th 2008; (2) QuickBird satellite image, 2.44 m resolution, visible and near-infrared bands, august 29th 2008; (3) Spot satellite image, 2.50 m resolution, visible and near-infrared bands, September 22nd 2008. From these images, we developed three image processing methods: (1) a pixel-based method associated to a segmentation using Matlab®, (2) a pixel-based method using ENVI®, (3) an object-based classification using Definiens®. We extracted six land cover types from the BD Ortho IGN (visible bands) and height classes from the satellite images (visible and near infrared bands). The three classified images are

A Review of the Application of Optical and Radar Remote Sensing Data Fusion to Land Use Mapping and Monitoring

Directory of Open Access Journals (Sweden)

Neha Joshi

2016-01-01

Full Text Available The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral and structural information, for land cover and use assessments. Contrary to our expectations, only 50 studies specifically addressed land use, and five assessed land use changes, while the majority addressed land cover. The advantages of fusion for land use analysis were assessed in 32 studies, and a large majority (28 studies concluded that fusion improved results compared to using single data sources. Study sites were small, frequently 300–3000 km 2 or individual plots, with a lack of comparison of results and accuracies across sites. Although a variety of fusion techniques were used, pre-classification fusion followed by pixel-level inputs in traditional classification algorithms (e.g., Gaussian maximum likelihood classification was common, but often without a concrete rationale on the applicability of the method to the land use theme being studied. Progress in this field of research requires the development of robust techniques of fusion to map the intricacies of land uses and changes therein and systematic procedures to assess the benefits of fusion over larger spatial scales.

Impact of Land Use Land Cover Change on East Asian monsoon

Science.gov (United States)

Chilukoti, N.; Xue, Y.; Liu, Y.; Lee, J.

2017-12-01

Humans modify the Earth's terrestrial surface on a continental scale by removing natural vegetation for crops/grazing. The current rates, extents and intensities of Land Use and Land Cover Change (LULCC) are greater than ever in history. The earlier studies of Land-atmosphere interactions used specified land surface conditions without interannual variations. In this study using NCEP CFSv2 coupled with Simplified Simple Biosphere (SSiB) model, biogeophysical impacts of LULCC on climate variability, anomaly, and changes are investigated by using the LULCC map from the Hurtt et al. (2006, 2011), which covered 66 years from 1950-2015 with annual variability. We combined the changes in crop and pasture fractions and consider as LULCC. A methodology had been developed to convert the Hurtt LULCC change map with 1° resolution to the GCM grid points. Since the GCM has only one dominant type, when the crop and pasture frction value at one point was larger than the critical value, that grid was assigned as degraded. Comprehensive evaluation was conducted to ensure the consistence of the trend of land degradation in the Hurtt's map and in the GCM LULCC map. In the degraded point, trees were changed to low vegetation or grasses, and low vegetation to bare soil. A set of surface parameters such as leaf area index, vegetation height, roughness length, and soil parameters, associated with vegetation are changed to show the degradation effects. We integrated the model with the potential vegetation map and the map with LULCC from 1950 to 2015, and the results indicate the LULCC causes precipitation reduction globally, with the strongest signals over monsoon regions. For instance, the degradation in Mexico, West Africa, south and East Asia and South America produced significant precipitation anomalies, some of which are consistent with observed regional precipitation anomalies. Meanwhile, it has also found that the LULCC enhances the surface warming during the summer in monsoon

Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis

Directory of Open Access Journals (Sweden)

F. Xu

2017-08-01

Full Text Available The determination of area-averaged evapotranspiration (ET at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models and general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC sites and four groups of large-aperture scintillometers (LASs, were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this

Area-averaged evapotranspiration over a heterogeneous land surface: aggregation of multi-point EC flux measurements with a high-resolution land-cover map and footprint analysis

Science.gov (United States)

Xu, Feinan; Wang, Weizhen; Wang, Jiemin; Xu, Ziwei; Qi, Yuan; Wu, Yueru

2017-08-01

The determination of area-averaged evapotranspiration (ET) at the satellite pixel scale/model grid scale over a heterogeneous land surface plays a significant role in developing and improving the parameterization schemes of the remote sensing based ET estimation models and general hydro-meteorological models. The Heihe Watershed Allied Telemetry Experimental Research (HiWATER) flux matrix provided a unique opportunity to build an aggregation scheme for area-averaged fluxes. On the basis of the HiWATER flux matrix dataset and high-resolution land-cover map, this study focused on estimating the area-averaged ET over a heterogeneous landscape with footprint analysis and multivariate regression. The procedure is as follows. Firstly, quality control and uncertainty estimation for the data of the flux matrix, including 17 eddy-covariance (EC) sites and four groups of large-aperture scintillometers (LASs), were carefully done. Secondly, the representativeness of each EC site was quantitatively evaluated; footprint analysis was also performed for each LAS path. Thirdly, based on the high-resolution land-cover map derived from aircraft remote sensing, a flux aggregation method was established combining footprint analysis and multiple-linear regression. Then, the area-averaged sensible heat fluxes obtained from the EC flux matrix were validated by the LAS measurements. Finally, the area-averaged ET of the kernel experimental area of HiWATER was estimated. Compared with the formerly used and rather simple approaches, such as the arithmetic average and area-weighted methods, the present scheme is not only with a much better database, but also has a solid grounding in physics and mathematics in the integration of area-averaged fluxes over a heterogeneous surface. Results from this study, both instantaneous and daily ET at the satellite pixel scale, can be used for the validation of relevant remote sensing models and land surface process models. Furthermore, this work will be

Evaluation of the Initial Thematic Output from a Continuous Change-Detection Algorithm for Use in Automated Operational Land-Change Mapping by the U.S. Geological Survey

Directory of Open Access Journals (Sweden)

Bruce Pengra

2016-10-01

Full Text Available The U.S. Geological Survey (USGS has begun the development of operational, 30-m resolution annual thematic land cover data to meet the needs of a variety of land cover data users. The Continuous Change Detection and Classification (CCDC algorithm is being evaluated as the likely methodology following early trials. Data for training and testing of CCDC thematic maps have been provided by the USGS Land Cover Trends (LC Trends project, which offers sample-based, manually classified thematic land cover data at 2755 probabilistically located sample blocks across the conterminous United States. These samples represent a high quality, well distributed source of data to train the Random Forest classifier invoked by CCDC. We evaluated the suitability of LC Trends data to train the classifier by assessing the agreement of annual land cover maps output from CCDC with output from the LC Trends project within 14 Landsat path/row locations across the conterminous United States. We used a small subset of circa 2000 data from the LC Trends project to train the classifier, reserving the remaining Trends data from 2000, and incorporating LC Trends data from 1992, to evaluate measures of agreement across time, space, and thematic classes, and to characterize disagreement. Overall agreement ranged from 75% to 98% across the path/rows, and results were largely consistent across time. Land cover types that were well represented in the training data tended to have higher rates of agreement between LC Trends and CCDC outputs. Characteristics of disagreement are being used to improve the use of LC Trends data as a continued source of training information for operational production of annual land cover maps.

Evaluation of the initial thematic output from a continuous change-detection algorithm for use in automated operational land-change mapping by the U.S. Geological Survey

Science.gov (United States)

Pengra, Bruce; Gallant, Alisa L.; Zhu, Zhe; Dahal, Devendra

2016-01-01

The U.S. Geological Survey (USGS) has begun the development of operational, 30-m resolution annual thematic land cover data to meet the needs of a variety of land cover data users. The Continuous Change Detection and Classification (CCDC) algorithm is being evaluated as the likely methodology following early trials. Data for training and testing of CCDC thematic maps have been provided by the USGS Land Cover Trends (LC Trends) project, which offers sample-based, manually classified thematic land cover data at 2755 probabilistically located sample blocks across the conterminous United States. These samples represent a high quality, well distributed source of data to train the Random Forest classifier invoked by CCDC. We evaluated the suitability of LC Trends data to train the classifier by assessing the agreement of annual land cover maps output from CCDC with output from the LC Trends project within 14 Landsat path/row locations across the conterminous United States. We used a small subset of circa 2000 data from the LC Trends project to train the classifier, reserving the remaining Trends data from 2000, and incorporating LC Trends data from 1992, to evaluate measures of agreement across time, space, and thematic classes, and to characterize disagreement. Overall agreement ranged from 75% to 98% across the path/rows, and results were largely consistent across time. Land cover types that were well represented in the training data tended to have higher rates of agreement between LC Trends and CCDC outputs. Characteristics of disagreement are being used to improve the use of LC Trends data as a continued source of training information for operational production of annual land cover maps.

Landing Site Selection and Surface Traverse Planning using the Lunar Mapping & Modeling Portal

Science.gov (United States)

Law, E.; Chang, G.; Bui, B.; Sadaqathullah, S.; Kim, R.; Dodge, K.; Malhotra, S.

2013-12-01

Introduction: The Lunar Mapping and Modeling Portal (LMMP), is a web-based Portal and a suite of interactive visualization and analysis tools for users to access mapped lunar data products (including image mosaics, digital elevation models, etc.) from past and current lunar missions (e.g., Lunar Reconnaissance Orbiter, Apollo, etc.), and to perform in-depth analyses to support lunar surface mission planning and system design for future lunar exploration and science missions. It has been widely used by many scientists mission planners, as well as educators and public outreach (e.g., Google Lunar XPRICE teams, RESOLVE project, museums etc.) This year, LMMP was used by the Lunar and Planetary Institute (LPI)'s Lunar Exploration internship program to perform lighting analysis and local hazard assessments, such as, slope, surface roughness and crater/boulder distribution to research landing sites and surface pathfinding and traversal. Our talk will include an overview of LMMP, a demonstration of the tools as well as a summary of the LPI Lunar Exploration summer interns' experience in using those tools.

GlobeLand30 as an alternative fine-scale global land cover map

DEFF Research Database (Denmark)

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

2016-01-01

land cover information such as developing countries. In this study, we look at GlobeLand30 of 2010 for Iran in order to find out the accuracy of this dataset as well as its implications. By having looked at 6 selected study sites around larger cities representing dissimilar eco-regions covering rural...

Use of Land Use Land Cover Change Mapping Products in Aiding Coastal Habitat Conservation and Restoration Efforts of the Mobile Bay NEP

Science.gov (United States)

Spruce, Joseph P.; Swann, Roberta; Smooth, James

2010-01-01

The Mobile Bay region has undergone significant land use land cover change (LULC) over the last 35 years, much of which is associated with urbanization. These changes have impacted the region s water quality and wildlife habitat availability. In addition, much of the region is low-lying and close to the Gulf, which makes the region vulnerable to hurricanes, climate change (e.g., sea level rise), and sometimes man-made disasters such as the Deepwater Horizon (DWH) oil spill. Land use land cover change information is needed to help coastal zone managers and planners to understand and mitigate the impacts of environmental change on the region. This presentation discusses selective results of a current NASA-funded project in which Landsat data over a 34-year period (1974-2008) is used to produce, validate, refine, and apply land use land cover change products to aid coastal habitat conservation and restoration needs of the Mobile Bay National Estuary Program (MB NEP). The project employed a user defined classification scheme to compute LULC change mapping products for the entire region, which includes the majority of Mobile and Baldwin counties. Additional LULC change products have been computed for select coastal HUC-12 sub-watersheds adjacent to either Mobile Bay or the Gulf of Mexico, as part of the MB NEP watershed profile assessments. This presentation will include results of additional analyses of LULC change for sub-watersheds that are currently high priority areas, as defined by MB NEP. Such priority sub-watersheds include those that are vulnerable to impacts from the DWH oil spill, as well as sub-watersheds undergoing urbanization. Results demonstrating the nature and permanence of LULC change trends for these higher priority sub-watersheds and results characterizing change for the entire 34-year period and at approximate 10-year intervals across this period will also be presented. Future work will include development of value-added coastal habitat quality

Mapping the global depth to bedrock for land surface modelling

Science.gov (United States)

Shangguan, W.; Hengl, T.; Yuan, H.; Dai, Y. J.; Zhang, S.

2017-12-01

Depth to bedrock serves as the lower boundary of land surface models, which controls hydrologic and biogeochemical processes. This paper presents a framework for global estimation of Depth to bedrock (DTB). Observations were extracted from a global compilation of soil profile data (ca. 130,000 locations) and borehole data (ca. 1.6 million locations). Additional pseudo-observations generated by expert knowledge were added to fill in large sampling gaps. The model training points were then overlaid on a stack of 155 covariates including DEM-based hydrological and morphological derivatives, lithologic units, MODIS surfacee reflectance bands and vegetation indices derived from the MODIS land products. Global spatial prediction models were developed using random forests and Gradient Boosting Tree algorithms. The final predictions were generated at the spatial resolution of 250m as an ensemble prediction of the two independently fitted models. The 10-fold cross-validation shows that the models explain 59% for absolute DTB and 34% for censored DTB (depths deep than 200 cm are predicted as 200 cm). The model for occurrence of R horizon (bedrock) within 200 cm does a good job. Visual comparisons of predictions in the study areas where more detailed maps of depth to bedrock exist show that there is a general match with spatial patterns from similar local studies. Limitation of the data set and extrapolation in data spare areas should not be ignored in applications. To improve accuracy of spatial prediction, more borehole drilling logs will need to be added to supplement the existing training points in under-represented areas.

75 FR 44046 - Noise Exposure Map Acceptance

Science.gov (United States)

2010-07-27

... applicable regulations and which depict non-compatible land uses as of the date of submission of such maps, a... Baseline Noise Exposure Map. Section 1: Appendix C, D and E--Consultation requirements. Section 2: Land Use... the Act. These functions are inseparable from the ultimate land use control and planning...

Geodiversity and land degradation in Hungary

Science.gov (United States)

Őrsi, Anna

2014-05-01

Geodiversity represents a variety of natural values, but they are threatened by a series of anthropogenic activities and land degradation processes. Their effect depends on the intensity of the processes and the sensitivity of the area in question. As a consequence of land degradation processes not only biodiversity but also geodiversity can be damaged and deteriorated. The appearance of the natural landscape changes and natural processes may not have a decisive role in landscape development any more. Some of the damages are irreversible because fundamental changes happen in the landscape, or the processes having created the original forms are no longer in operation. Small scale land degradation processes may be reversible if nature is still capable of reproducing the original state. The most important land degradation processes are desertification and soil erosion. Mining, waste disposal, urbanisation and construction activities, agriculture, inaccurate forest and water management, tourism, unsuitable land use can also lead to severe land degradation problems. The objective of the paper is to show Hungarian examples to all land degradation processes that threaten geodiversity. The results will be shown on a series of maps showing land degradation processes endangering geodiversity in Hungary. A detailed analysis of smaller study sites will be provided to show the effects of certain land degradation processes on landform development and on the changes of geodiversity. This research is supported by the Hungarian Scientific Research Fund (OTKA), project Nr. 10875.

An operational methodology for riparian land cover fine scale regional mapping for the study of landscape influence on river ecological status

Science.gov (United States)

Tormos, T.; Kosuth, P.; Souchon, Y.; Villeneuve, B.; Durrieu, S.; Chandesris, A.

2010-12-01

Preservation and restoration of river ecosystems require an improved understanding of the mechanisms through which they are influenced by landscape at multiple spatial scales and particularly at river corridor scale considering the role of riparian vegetation for regulating and protecting river ecological status and the relevance of this specific area for implementing efficient and realistic strategies. Assessing correctly this influence over large river networks involves accurate broad scale (i.e. at least regional) information on Land Cover within Riparian Areas (LCRA). As the structure of land cover along rivers is generally not accessible using moderate-scale satellite imagery, finer spatial resolution imagery and specific mapping techniques are needed. For this purpose we developed a generic multi-scale Object Based Image Analysis (OBIA) scheme able to produce LCRA maps in different geographic context by exploiting information available from very high spatial resolution imagery (satellite or airborne) and/or metric to decametric spatial thematic data on a given study zone thanks to fuzzy expert knowledge classification rules. A first experimentation was carried out on the Herault river watershed (southern of France), a 2650 square kilometers basin that presents a contrasted landscape (different ecoregions) and a total stream length of 1150 Km, using high and very high multispectral remotely-sensed images (10m Spot5 multispectral images and 0.5m aerial photography) and existing spatial thematic data. Application of the OBIA scheme produced a detailed (22 classes) LCRA map with an overall accuracy of 89% and a Kappa index of 83% according to a land cover pressures typology (six categories). A second experimentation (using the same data sources) was carried out on a larger test zone, a part of the Normandy river network (25 000 square kilometers basin; 6000 km long river network; 155 ecological stations). This second work aimed at elaborating a robust statistical

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).

Mapping of forest types confined to the lay of land

Directory of Open Access Journals (Sweden)

S. K. Farber

2018-04-01

Full Text Available The principles for the formation of forest typological classification and outlines promising areas for development, allowing to solve problems of not only inventory and forest management, but also mapping forest types are discussed in the paper. The analysis is performed by interpreting the concept of «natural regularity» proposed by D. L. Armand (1975. It is shown when the left side of the pattern is a set of indicators of site condition, structure of forest typological constructions will take into account not only the static indicators of the stands, but also their location, the origin and direction of the succession. For relatively similar climatic conditions, the indicators of the lay of land mainly limit the environment of formation of vegetation cover. The method of mapping forest types provides for consideration of site condition and indicators of stands of forest types. Testing is conducted on a test axis West-Sayan forest district, located in the mountains of southern Siberia. Conjugation types of forests, indicators of the topography revealed through the analysis of literary sources and characteristics of forest types accompanying diagnostic table (Smagin et al., 1980. The work is done in a GIS environment using DEM SRTM and Landsat space images. For indexing locations, the inputs are accepted: altitude (gradation 100 m, flat location, slope up to 20° and 20° slopes with northern and southern exposure. Classification of pixels of satellite images is conducted by the method of unsupervised classification separately for each scene, the high-altitude zone and location, which allows increase of the quality of interpretation, because the types of forests are confined to the topography. However completely avoiding mistakes is not possible. The main reasons are an inaccuracy of the DEM and the hit in one class of spectral brightness of different objects of interpretation. The map legend includes characteristics of the terrain, description

Current Application of Remote Sensing Techniques in Land Use ...

African Journals Online (AJOL)

Land use mapping is important for evaluation, management and conservation of natural resources of an area and the knowledge on the existing land use is one of the prime pre-requisites for suggesting better use of land. In this study, we examined four mapping approaches (unsupervised, supervised, fuzzy supervised and ...

Agriculture pest and disease risk maps considering MSG satellite data and land surface temperature

Science.gov (United States)

Marques da Silva, J. R.; Damásio, C. V.; Sousa, A. M. O.; Bugalho, L.; Pessanha, L.; Quaresma, P.

2015-06-01

Pest risk maps for agricultural use are usually constructed from data obtained from in-situ meteorological weather stations, which are relatively sparsely distributed and are often quite expensive to install and difficult to maintain. This leads to the creation of maps with relatively low spatial resolution, which are very much dependent on interpolation methodologies. Considering that agricultural applications typically require a more detailed scale analysis than has traditionally been available, remote sensing technology can offer better monitoring at increasing spatial and temporal resolutions, thereby, improving pest management results and reducing costs. This article uses ground temperature, or land surface temperature (LST), data distributed by EUMETSAT/LSASAF (with a spatial resolution of 3 × 3 km (nadir resolution) and a revisiting time of 15 min) to generate one of the most commonly used parameters in pest modeling and monitoring: "thermal integral over air temperature (accumulated degree-days)". The results show a clear association between the accumulated LST values over a threshold and the accumulated values computed from meteorological stations over the same threshold (specific to a particular tomato pest). The results are very promising and enable the production of risk maps for agricultural pests with a degree of spatial and temporal detail that is difficult to achieve using in-situ meteorological stations.

Dynamic positional fate map of the primary heart-forming region.

Science.gov (United States)

Cui, Cheng; Cheuvront, Tracey J; Lansford, Rusty D; Moreno-Rodriguez, Ricardo A; Schultheiss, Thomas M; Rongish, Brenda J

2009-08-15

Here we show the temporal-spatial orchestration of early heart morphogenesis at cellular level resolution, in vivo, and reconcile conflicting positional fate mapping data regarding the primary heart-forming field(s). We determined the positional fates of precardiac cells using a precision electroporation approach in combination with wide-field time-lapse microscopy in the quail embryo, a warm-blooded vertebrate (HH Stages 4 through 10). Contrary to previous studies, the results demonstrate the existence of a "continuous" circle-shaped heart field that spans the midline, appearing at HH Stage 4, which then expands to form a wide arc of progenitors at HH Stages 5-7. Our time-resolved image data show that a subset of these cardiac progenitor cells do not overlap with the expression of common cardiogenic factors, Nkx-2.5 and Bmp-2, until HH Stage 10, when a tubular heart has formed, calling into question when cardiac fate is specified and by which key factors. Sub-groups and anatomical bands (cohorts) of heart precursor cells dramatically change their relative positions in a process largely driven by endodermal folding and other large-scale tissue deformations. Thus, our novel dynamic positional fate maps resolve the origin of cardiac progenitor cells in amniotes. The data also establish the concept that tissue motion contributes significantly to cellular position fate - i.e., much of the cellular displacement that occurs during assembly of a midline heart tube (HH Stage 9) is NOT due to "migration" (autonomous motility), a commonly held belief. Computational analysis of our time-resolved data lays the foundation for more precise analyses of how cardiac gene regulatory networks correlate with early heart tissue morphogenesis in birds and mammals.

Application of ecological mapping

International Nuclear Information System (INIS)

Sherk, J.A.

1982-01-01

The US Fish and Wildlife Service has initiated the production of a comprehensive ecological inventory map series for use as a major new planning tool. Important species data along with special land use designations are displayed on 1:250,000 scale topographic base maps. Sets of maps have been published for the Atlantic and Pacific coastal areas of the United States. Preparation of a map set for the Gulf of Mexico is underway at the present time. Potential application of ecological inventory map series information to a typical land disposal facility could occur during the narrowing of the number of possible disposal sites, the design of potential disposal site studies of ecological resources, the preparation of the environmental report, and the regulatory review of license applications. 3 figures, 3 tables

Fuzzy Nonnative Phonolexical Representations Lead to Fuzzy Form-to-Meaning Mappings

Directory of Open Access Journals (Sweden)

Svetlana V Cook

2016-09-01

Full Text Available The present paper explores nonnative (L2 phonological encoding of lexical entries and dissociates the difficulties associated with L2 phonological and phonolexical encoding by focusing on similarly sounding L2 words that are not differentiated by difficult phonological contrasts. We test two main claims of the fuzzy lexicon hypothesis: (1 L2 fuzzy phonolexical representations are not fully specified and lack details at both phonological and phonolexical levels of representation (Experiment 1; and (2 fuzzy phonolexical representations can lead to establishing incorrect form-to-meaning mappings (Experiment 2.The Russian-English Translation Priming task (Experiment 1, TJT explores how the degree of phonolexical similarity between a word and its lexical competitor affects lexical access of Russian words. Words with smaller phonolexical distance (e.g., parent - parrot show longer reaction times and lower accuracy compared to words with a larger phonolexical distance (e.g., parent – parchment in lower-proficiency nonnative speakers, and, to a lesser degree, higher-proficiency speakers. This points to a lack of detail in nonnative phonolexical representations necessary for efficient lexical access. The Russian Pseudo-Semantic Priming task (Experiment 2, PSP addresses the vulnerability of form-to-meaning mappings as a consequence of fuzzy phonolexical representations in L2. We primed the target with a word semantically related to its phonological competitor, or a potentially confusable word. The findings of Experiment 2 extend the results of Experiment 1 that, unlike native speakers, nonnative speakers do not properly encode phonolexical information. As a result, they are prone to access an incorrect lexical representation of a competitor word, as indicated by a slowdown in the judgments to confusable words.The study provides evidence that fuzzy phonolexical representations result in unfaithful form-to-meaning mappings, which lead to retrieval of

Geologic map of the Western Grove quadrangle, northwestern Arkansas

Science.gov (United States)

Hudson, Mark R.; Turner, Kenzie J.; Repetski, John E.

2006-01-01

This map summarizes the geology of the Western Grove 7.5-minute quadrangle in northern Arkansas that is located on the southern flank of the Ozark dome, a late Paleozoic regional uplift. The exposed bedrock of this map area comprises approximately 1,000 ft of Ordovician and Mississippian carbonate and clastic sedimentary rocks that have been mildly folded and broken by faults. A segment of the Buffalo River loops through the southern part of the quadrangle, and the river and adjacent lands form part of Buffalo National River, a park administered by the U.S. National Park Service. This geologic map provides information to better understand the natural resources of the Buffalo River watershed, particularly its karst hydrogeologic framework.

Mapping of

Directory of Open Access Journals (Sweden)

Sayed M. Arafat

2014-06-01

Full Text Available Land cover map of North Sinai was produced based on the FAO-Land Cover Classification System (LCCS of 2004. The standard FAO classification scheme provides a standardized system of classification that can be used to analyze spatial and temporal land cover variability in the study area. This approach also has the advantage of facilitating the integration of Sinai land cover mapping products to be included with the regional and global land cover datasets. The total study area is covering a total area of 20,310.4 km2 (203,104 hectare. The landscape classification was based on SPOT4 data acquired in 2011 using combined multispectral bands of 20 m spatial resolution. Geographic Information System (GIS was used to manipulate the attributed layers of classification in order to reach the maximum possible accuracy. GIS was also used to include all necessary information. The identified vegetative land cover classes of the study area are irrigated herbaceous crops, irrigated tree crops and rain fed tree crops. The non-vegetated land covers in the study area include bare rock, bare soils (stony, very stony and salt crusts, loose and shifting sands and sand dunes. The water bodies were classified as artificial perennial water bodies (fish ponds and irrigated canals and natural perennial water bodies as lakes (standing. The artificial surfaces include linear and non-linear features.

Technical procedures for land use, Deaf Smith County site, Texas: Environmental Field Program: Final draft

International Nuclear Information System (INIS)

1987-09-01

This volume contains Technical Procedures pursuant to the Land Use Site Study Plan including land use data acquisition, land use/land cover map compilation, verification of land use/land cover map accuracy, and land use/land cover data analysis. 22 refs., 5 figs

Mapping geogenic radon potential by regression kriging

Energy Technology Data Exchange (ETDEWEB)

Pásztor, László [Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, Hungarian Academy of Sciences, Department of Environmental Informatics, Herman Ottó út 15, 1022 Budapest (Hungary); Szabó, Katalin Zsuzsanna, E-mail: sz_k_zs@yahoo.de [Department of Chemistry, Institute of Environmental Science, Szent István University, Páter Károly u. 1, Gödöllő 2100 (Hungary); Szatmári, Gábor; Laborczi, Annamária [Institute for Soil Sciences and Agricultural Chemistry, Centre for Agricultural Research, Hungarian Academy of Sciences, Department of Environmental Informatics, Herman Ottó út 15, 1022 Budapest (Hungary); Horváth, Ákos [Department of Atomic Physics, Eötvös University, Pázmány Péter sétány 1/A, 1117 Budapest (Hungary)

2016-02-15

Radon ({sup 222}Rn) gas is produced in the radioactive decay chain of uranium ({sup 238}U) which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on the physical and meteorological parameters of the soil and can enter and accumulate in buildings. Health risks originating from indoor radon concentration can be attributed to natural factors and is characterized by geogenic radon potential (GRP). Identification of areas with high health risks require spatial modeling, that is, mapping of radon risk. In addition to geology and meteorology, physical soil properties play a significant role in the determination of GRP. In order to compile a reliable GRP map for a model area in Central-Hungary, spatial auxiliary information representing GRP forming environmental factors were taken into account to support the spatial inference of the locally measured GRP values. Since the number of measured sites was limited, efficient spatial prediction methodologies were searched for to construct a reliable map for a larger area. Regression kriging (RK) was applied for the interpolation using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly, the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Overall accuracy of the map was tested by Leave-One-Out Cross-Validation. Furthermore the spatial reliability of the resultant map is also estimated by the calculation of the 90% prediction interval of the local prediction values. The applicability of the applied method as well as that of the map is discussed briefly. - Highlights: • A new method

Mapping geogenic radon potential by regression kriging

International Nuclear Information System (INIS)

Pásztor, László; Szabó, Katalin Zsuzsanna; Szatmári, Gábor; Laborczi, Annamária; Horváth, Ákos

2016-01-01

Radon ( 222 Rn) gas is produced in the radioactive decay chain of uranium ( 238 U) which is an element that is naturally present in soils. Radon is transported mainly by diffusion and convection mechanisms through the soil depending mainly on the physical and meteorological parameters of the soil and can enter and accumulate in buildings. Health risks originating from indoor radon concentration can be attributed to natural factors and is characterized by geogenic radon potential (GRP). Identification of areas with high health risks require spatial modeling, that is, mapping of radon risk. In addition to geology and meteorology, physical soil properties play a significant role in the determination of GRP. In order to compile a reliable GRP map for a model area in Central-Hungary, spatial auxiliary information representing GRP forming environmental factors were taken into account to support the spatial inference of the locally measured GRP values. Since the number of measured sites was limited, efficient spatial prediction methodologies were searched for to construct a reliable map for a larger area. Regression kriging (RK) was applied for the interpolation using spatially exhaustive auxiliary data on soil, geology, topography, land use and climate. RK divides the spatial inference into two parts. Firstly, the deterministic component of the target variable is determined by a regression model. The residuals of the multiple linear regression analysis represent the spatially varying but dependent stochastic component, which are interpolated by kriging. The final map is the sum of the two component predictions. Overall accuracy of the map was tested by Leave-One-Out Cross-Validation. Furthermore the spatial reliability of the resultant map is also estimated by the calculation of the 90% prediction interval of the local prediction values. The applicability of the applied method as well as that of the map is discussed briefly. - Highlights: • A new method, regression

To the National Map and beyond

Science.gov (United States)

Kelmelis, J.

2003-01-01

Scientific understanding, technology, and social, economic, and environmental conditions have driven a rapidly changing demand for geographic information, both digital and analog. For more than a decade, the U.S. Geological Survey (USGS) has been developing innovative partnerships with other government agencies and private industry to produce and distribute geographic information efficiently; increase activities in remote sensing to ensure ongoing monitoring of the land surface; and develop new understanding of the causes and consequences of land surface change. These activities are now contributing to a more robust set of geographic information called The National Map (TNM). The National Map is designed to provide an up-to-date, seamless, horizontally and vertically integrated set of basic digital geographic data, a frequent monitoring of changes on the land surface, and an understanding of the condition of the Earth's surface and many of the processes that shape it. The USGS has reorganized its National Mapping Program into three programs to address the continuum of scientific activities-describing (mapping), monitoring, understanding, modeling, and predicting. The Cooperative Topographic Mapping Program focuses primarily on the mapping and revision aspects of TNM. The National Map also includes results from the Land Remote Sensing and Geographic Analysis and Monitoring Programs that provide continual updates, new insights, and analytical tools. The National Map is valuable as a framework for current research, management, and operational activities. It also provides a critical framework for the development of distributed, spatially enabled decision support systems.

The National Map: from geography to mapping and back again

Science.gov (United States)

Kelmelis, John A.; DeMulder, Mark L.; Ogrosky, Charles E.; Van Driel, J. Nicholas; Ryan, Barbara J.

2003-01-01

When the means of production for national base mapping were capital intensive, required large production facilities, and had ill-defined markets, Federal Government mapping agencies were the primary providers of the spatial data needed for economic development, environmental management, and national defense. With desktop geographic information systems now ubiquitous, source data available as a commodity from private industry, and the realization that many complex problems faced by society need far more and different kinds of spatial data for their solutions, national mapping organizations must realign their business strategies to meet growing demand and anticipate the needs of a rapidly changing geographic information environment. The National Map of the United States builds on a sound historic foundation of describing and monitoring the land surface and adds a focused effort to produce improved understanding, modeling, and prediction of land-surface change. These added dimensions bring to bear a broader spectrum of geographic science to address extant and emerging issues. Within the overarching construct of The National Map, the U.S. Geological Survey (USGS) is making a transition from data collector to guarantor of national data completeness; from producing paper maps to supporting an online, seamless, integrated database; and from simply describing the Nation’s landscape to linking these descriptions with increased scientific understanding. Implementing the full spectrum of geographic science addresses a myriad of public policy issues, including land and natural resource management, recreation, urban growth, human health, and emergency planning, response, and recovery. Neither these issues nor the science and technologies needed to deal with them are static. A robust research agenda is needed to understand these changes and realize The National Map vision. Initial successes have been achieved. These accomplishments demonstrate the utility of

Decadal changes in the land use/land cover and shoreline along the coastal districts of southern Gujarat, India.

Science.gov (United States)

Misra, A; Balaji, R

2015-07-01

The coastal zone along the districts of Surat, Navsari, and Valsad in southern Gujarat, India, is reported to be facing serious environmental challenges in the form of shoreline erosion, wetland loss, and man-made encroachments. This study assesses the decadal land use/ land cover (LULC) changes in these three districts for the years 1990, 2001, and 2014 using satellite datasets of Landsat TM, ETM, and OLI. The LULC changes are identified by using band ratios as a pre-classification step, followed by implementation of hybrid classification (a combination of supervised and unsupervised classification). An accuracy assessment is carried out for each dataset, and the overall accuracy ranges from 90 to 95%. It is observed that the spatial extents of aquaculture, urban built-up, and barren classes have appreciated over time, whereas the coverage of mudflats has depreciated due to rapid urbanization. The changes in the shoreline of these districts have also been analyzed for the same years, and significant changes are found in the form of shoreline erosion. The LULC maps prepared as well as the shoreline change analysis done for this study area will enable the local decision makers to adopt better land-use planning and shoreline protection measures, which will further aid in sustainable future developments in this region.

National Land Cover Database 2001 (NLCD01)

Science.gov (United States)

LaMotte, Andrew E.

2016-01-01

This 30-meter data set represents land use and land cover for the conterminous United States for the 2001 time period. The data have been arranged into four tiles to facilitate timely display and manipulation within a Geographic Information System (see http://water.usgs.gov/GIS/browse/nlcd01-partition.jpg). The National Land Cover Data Set for 2001 was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. The MRLC Consortium is a partnership of Federal agencies (http://www.mrlc.gov), consisting of the U.S. Geological Survey (USGS), the National Oceanic and Atmospheric Administration (NOAA), the U.S. Environmental Protection Agency (USEPA), the U.S. Department of Agriculture (USDA), the U.S. Forest Service (USFS), the National Park Service (NPS), the U.S. Fish and Wildlife Service (USFWS), the Bureau of Land Management (BLM), and the USDA Natural Resources Conservation Service (NRCS). One of the primary goals of the project is to generate a current, consistent, seamless, and accurate National Land Cover Database (NLCD) circa 2001 for the United States at medium spatial resolution. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer and others (2004), (see: http://www.mrlc.gov/mrlc2k.asp). The NLCD 2001 was created by partitioning the United States into mapping zones. A total of 68 mapping zones (see http://water.usgs.gov/GIS/browse/nlcd01-mappingzones.jpg), were delineated within the conterminous United States based on ecoregion and geographical characteristics, edge-matching features, and the size requirement of Landsat mosaics. Mapping zones encompass the whole or parts of several states. Questions about the NLCD mapping zones can be directed to the NLCD 2001 Land Cover Mapping Team at the USGS/EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov.

Precision Landing and Hazard Avoidance Doman

Science.gov (United States)

Robertson, Edward A.; Carson, John M., III

2016-01-01

The Precision Landing and Hazard Avoidance (PL&HA) domain addresses the development, integration, testing, and spaceflight infusion of sensing, processing, and GN&C functions critical to the success and safety of future human and robotic exploration missions. PL&HA sensors also have applications to other mission events, such as rendezvous and docking. Autonomous PL&HA builds upon the core GN&C capabilities developed to enable soft, controlled landings on the Moon, Mars, and other solar system bodies. Through the addition of a Terrain Relative Navigation (TRN) function, precision landing within tens of meters of a map-based target is possible. The addition of a 3-D terrain mapping lidar sensor improves the probability of a safe landing via autonomous, real-time Hazard Detection and Avoidance (HDA). PL&HA significantly improves the probability of mission success and enhances access to sites of scientific interest located in challenging terrain. PL&HA can also utilize external navigation aids, such as navigation satellites and surface beacons. Advanced Lidar Sensors High precision ranging, velocimetry, and 3-D terrain mapping Terrain Relative Navigation (TRN) TRN compares onboard reconnaissance data with real-time terrain imaging data to update the S/C position estimate Hazard Detection and Avoidance (HDA) Generates a high-resolution, 3-D terrain map in real-time during the approach trajectory to identify safe landing targets Inertial Navigation During Terminal Descent High precision surface relative sensors enable accurate inertial navigation during terminal descent and a tightly controlled touchdown within meters of the selected safe landing target.

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

Science.gov (United States)

Rogan, John

2005-11-01

Land-cover change, manifested as either land-cover modification and/or conversion, can occur at all spatial scales, and changes at local scales can have profound, cumulative impacts at broader scales. The implication of operational land-cover monitoring is that researchers have access to a continuous stream of remote sensing data, with the long term goal of providing for consistent and repetitive mapping. Effective large area monitoring of land-cover (i.e., >1000 km2) can only be accomplished by using remotely sensed images as an indirect data source in land-cover change mapping and as a source for land-cover change model projections. Large area monitoring programs face several challenges: (1) choice of appropriate classification scheme/map legend over large, topographically and phenologically diverse areas; (2) issues concerning data consistency and map accuracy (i.e., calibration and validation); (3) very large data volumes; (4) time consuming data processing and interpretation. Therefore, this dissertation research broadly addresses these challenges in the context of examining state-of-the-art image pre-processing, spectral enhancement, classification, and accuracy assessment techniques to assist the California Land-cover Mapping and Monitoring Program (LCMMP). The results of this dissertation revealed that spatially varying haze can be effectively corrected from Landsat data for the purposes of change detection. The Multitemporal Spectral Mixture Analysis (MSMA) spectral enhancement technique produced more accurate land-cover maps than those derived from the Multitemporal Kauth Thomas (MKT) transformation in northern and southern California study areas. A comparison of machine learning classifiers showed that Fuzzy ARTMAP outperformed two classification tree algorithms, based on map accuracy and algorithm robustness. Variation in spatial data error (positional and thematic) was explored in relation to environmental variables using geostatistical interpolation

GRANULOMETRIC MAPS FROM HIGH RESOLUTION SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

Catherine Mering

2011-05-01

Full Text Available A new method of land cover mapping from satellite images using granulometric analysis is presented here. Discontinuous landscapes such as steppian bushes of semi arid regions and recently growing urban settlements are especially concerned by this study. Spatial organisations of the land cover are quantified by means of the size distribution analysis of the land cover units extracted from high resolution remotely sensed images. A granulometric map is built by automatic classification of every pixel of the image according to the granulometric density inside a sliding neighbourhood. Granulometric mapping brings some advantages over traditional thematic mapping by remote sensing by focusing on fine spatial events and small changes in one peculiar category of the landscape.

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.

Lands directorate publications

Energy Technology Data Exchange (ETDEWEB)

1981-01-01

The directorate has a lead role in providing advice to the federal government on land use policy in Canada. The Canada Land Inventory (CLI) Program has produced significant amounts of data pertaining to the capability of Canadian lands to support agriculture, forestry, recreation, wildlife and sport fish. A list of CLI reports is presented in this publication. In addition, and capability maps have been compiled for agricultural, forestry, recreation and wildlife and are listed and described in this publication. (KRM)

Geomorphologic characteristic of low-intermediate level radioactive waste disposal land candidate at Lemahabang area

International Nuclear Information System (INIS)

Sucipta

1998-01-01

Geomorphological aspect is a factor should be considered on land evaluation for radioactive wastes disposal purpose. The aspect is important because geomorphological factors contribute on hydrological and erosion condition of the land. The objective of the study is to characterize the geomorphological condition of the land, i.e. land form, geomorphological processes, rock type, soil, surface water, ground water, vegetation and land use. The study was conducted by descriptive analyses from literature study and field geomorphological method, with evaluation as well as developed for terrain analyses. The study area can be divided industry for land from units, I.e. tuff undulating unit (land use: plantation), coastal deposits plain unit, silty sand fluvial plain unit (land use: wet rice field) and unconsolidated sand beach deposits plain unit (opened land without vegetation). Hydrologically, the study area can be divided indus tri three small river stream area (RSA). Detailed description of geomorfological condition is showed by table and geomorphological map. (author)

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.

Mapping and estimating land change between 2001 and 2013 in a heterogeneous landscape in West Africa: Loss of forestlands and capacity building opportunities

Science.gov (United States)

Badjana, Hèou Maléki; Olofsson, Pontus; Woodcock, Curtis E.; Helmschrot, Joerg; Wala, Kpérkouma; Akpagana, Koffi

2017-12-01

In West Africa, accurate classification of land cover and land change remains a big challenge due to the patchy and heterogeneous nature of the landscape. Limited data availability, human resources and technical capacities, further exacerbate the challenge. The result is a region that is among the more understudied areas in the world, which in turn has resulted in a lack of appropriate information required for sustainable natural resources management. The objective of this paper is to explore open source software and easy-to-implement approaches to mapping and estimation of land change that are transferrable to local institutions to increase capacity in the region, and to provide updated information on the regional land surface dynamics. To achieve these objectives, stable land cover and land change between 2001 and 2013 in the Kara River Basin in Togo and Benin were mapped by direct multitemporal classification of Landsat data by parameterization and evaluation of two machine-learning algorithms. Areas of land cover and change were estimated by application of an unbiased estimator to sample data following international guidelines. A prerequisite for all tools and methods was implementation in an open source environment, and adherence to international guidelines for reporting land surface activities. Findings include a recommendation of the Random Forests algorithm as implemented in Orfeo Toolbox, and a stratified estimation protocol - all executed in the QGIS graphical use interface. It was found that despite an estimated reforestation of 10,0727 ± 3480 ha (95% confidence interval), the combined rate of forest and savannah loss amounted to 56,271 ± 9405 ha (representing a 16% loss of the forestlands present in 2001), resulting in a rather sharp net loss of forestlands in the study area. These dynamics had not been estimated prior to this study, and the results will provide useful information for decision making pertaining to natural resources management, land

Mapping Priorities to Focus Cropland Mapping Activities: Fitness Assessment of Existing Global, Regional and National Cropland Maps

Directory of Open Access Journals (Sweden)

François Waldner

2015-06-01

Full Text Available Timely and accurate information on the global cropland extent is critical for applications in the fields of food security, agricultural monitoring, water management, land-use change modeling and Earth system modeling. On the one hand, it gives detailed location information on where to analyze satellite image time series to assess crop condition. On the other hand, it isolates the agriculture component to focus food security monitoring on agriculture and to assess the potential impacts of climate change on agricultural lands. The cropland class is often poorly captured in global land cover products due to its dynamic nature and the large variety of agro-systems. The overall objective was to evaluate the current availability of cropland datasets in order to propose a strategic planning and effort distribution for future cropland mapping activities and, therefore, to maximize their impact. Following a very comprehensive identification and collection of national to global land cover maps, a multi-criteria analysis was designed at the country level to identify the priority areas for cropland mapping. As a result, the analysis highlighted priority regions, such as Western Africa, Ethiopia, Madagascar and Southeast Asia, for the remote sensing community to focus its efforts. A Unified Cropland Layer at 250 m for the year 2014 was produced combining the fittest products. It was assessed using global validation datasets and yields an overall accuracy ranging from 82%–94%. Masking cropland areas with a global forest map reduced the commission errors from 46% down to 26%. Compared to the GLC-Share and the International Institute for Applied Systems Analysis-International Food Policy Research Institute (IIASA-IFPRI cropland maps, significant spatial disagreements were found, which might be attributed to discrepancies in the cropland definition. This advocates for a shared definition of cropland, as well as global validation datasets relevant for the

Mars Exploration Rovers Landing Dispersion Analysis

Science.gov (United States)

Knocke, Philip C.; Wawrzyniak, Geoffrey G.; Kennedy, Brian M.; Desai, Prasun N.; Parker, TImothy J.; Golombek, Matthew P.; Duxbury, Thomas C.; Kass, David M.

2004-01-01

Landing dispersion estimates for the Mars Exploration Rover missions were key elements in the site targeting process and in the evaluation of landing risk. This paper addresses the process and results of the landing dispersion analyses performed for both Spirit and Opportunity. The several contributors to landing dispersions (navigation and atmospheric uncertainties, spacecraft modeling, winds, and margins) are discussed, as are the analysis tools used. JPL's MarsLS program, a MATLAB-based landing dispersion visualization and statistical analysis tool, was used to calculate the probability of landing within hazardous areas. By convolving this with the probability of landing within flight system limits (in-spec landing) for each hazard area, a single overall measure of landing risk was calculated for each landing ellipse. In-spec probability contours were also generated, allowing a more synoptic view of site risks, illustrating the sensitivity to changes in landing location, and quantifying the possible consequences of anomalies such as incomplete maneuvers. Data and products required to support these analyses are described, including the landing footprints calculated by NASA Langley's POST program and JPL's AEPL program, cartographically registered base maps and hazard maps, and flight system estimates of in-spec landing probabilities for each hazard terrain type. Various factors encountered during operations, including evolving navigation estimates and changing atmospheric models, are discussed and final landing points are compared with approach estimates.

Taxonomic classification of world map units in crop producing areas of Argentina and Brazil with representative US soil series and major land resource areas in which they occur

Science.gov (United States)

Huckle, H. F. (Principal Investigator)

1980-01-01

The most probable current U.S. taxonomic classification of the soils estimated to dominate world soil map units (WSM)) in selected crop producing states of Argentina and Brazil are presented. Representative U.S. soil series the units are given. The map units occurring in each state are listed with areal extent and major U.S. land resource areas in which similar soils most probably occur. Soil series sampled in LARS Technical Report 111579 and major land resource areas in which they occur with corresponding similar WSM units at the taxonomic subgroup levels are given.

A fuzzy set approach to assess the predictive accuracy of land use simulations

NARCIS (Netherlands)

van Vliet, J.; Hagen-Zanker, A.; Hurkens, J.; van van Delden, H.

2013-01-01

The predictive accuracy of land use models is frequently assessed by comparing two data sets: the simulated land use map and the observed land use map at the end of the simulation period. A common statistic for this is Kappa, which expresses the agreement between two categorical maps, corrected for

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

Directory of Open Access Journals (Sweden)

Jinshui Zhang

2017-04-01

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

Role of Remote Sensing and Geographyc Information System Mapping for Protected Areas Land Rice Field Subak, Buffer Zones, and Area Conversion (Case Studies In Gianyar Regency, Bali Province)

Science.gov (United States)

Lanya, Indayati; Netera Subadiyasa, N.

2016-11-01

Conversion of rice fields in Bali 2579 ha/year, Law Number 41 of 2009 [1] and five of Government Regulation (GR), mandates the Local Government (LG) has a Regional Regulation (RR) or Rule Regent/Mayor, on the protection of agricultural land sustainable food (PALSF). Yet none provincial government of Bali has PALSF; although Subak as world cultural heritage. Similarly, Gianyar regency development strategy directed to integrate agriculture with tourism. Landsat 8 images, Word View Coverage 2015 Gianyar district and ArcGIS 10.3 software used for of rice field mapping and zoning of land protection Subak. Ten thematic maps (watersheds, land use, irrigation, relief/slope, rainfall, spatial planning, land suitability, productivity, the distance from downtown) as a variable parameter, weighted and balanced numerically. Numerical classification agricultura land using for the overlay menu and reselek. The total value of >125 as rice need to be protected, 100-125 value for buffer zone, and the value of 100, 50-100 and development of the region downstream to the access road Ida Bagus Matera (Jln. Province / national) in the coastal areas of Gianyar.

Federal Lands

Data.gov (United States)

Department of Homeland Security — This map layer consists of federally owned or administered lands of theUnited States, Puerto Rico, and the U.S. Virgin Islands. Only areas of 640 acres or more are...

Possibility of Preparing Thematic Maps Through Developing of the Geographic Information System (GIS

Directory of Open Access Journals (Sweden)

Stjepan Husnjak

2013-04-01

Full Text Available It is a well known fact that nowadays planning of sustainable development and land use requires a lot of reliable and good quality information, which serves as the basis for timely and adequate decision-making. One of the most important forms of information is presented in various maps. Until recently, preparing of such data was, no doubt, a rather complex and time-consuming task. However, at present, thanks to, first of all, the GIS technology it is possible to develop corresponding geographic information systems with databases which then allow comparatively simple and quick preparing of necessary thematic maps. The paper first presents the method of developing the Geographic and Land Information System (GLIS of the Karlovac County which, although developed for the purpose of agricultural development, may also be used in the development of forestry, environment protection, physical planning, water management and for soil conservation and regulation. Several examples illustrate the possibilities of preparing of specialised maps based on this GLIS. The basic data for developing of the geographic and land information system were the data of the Basic Soil Maps and topographic maps of the Republic of Croatia at the scale of 1:50 000 or 1:25 000, and the data from other studies made for the purpose of agricultural development in the area. These data, together with the results of processing and analysing of this data, by digitalisation, generalisation and interpolation, were incorporated into an integrated database of the geographic and land information system by using Microstation, AutoCad, ArcInfo, ArcWiew and Access software and the corresponding hardware. GLIS database consists of two parts. The first part includes the data referring to polygons - pedological contours, and the other part the data on pedological profiles. The base is organised in a way that enable the preparation of different thematic maps, but it can be also used in digital form

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

Science.gov (United States)

Pervez, M.; Seelan, S. K.; Rundquist, B. C.

2006-05-01

The importance of land cover information describing the nature and extent of land resources and changes over time is increasing; this is especially true in Bangladesh, where land cover is changing rapidly. This paper presents research into the land cover dynamics of northwestern Bangladesh for the period 1973-2003 using Landsat satellite images in combination with field survey data collected in January and February 2005. Land cover maps were produced for eight different years during the study period with an average 73 percent overall classification accuracy. The classification results and post-classification change analysis showed that agriculture is the dominant land cover (occupying 74.5 percent of the study area) and is being reduced at a rate of about 3,000 ha per year. In addition, 6.7 percent of the agricultural land is vulnerable to temporary water logging annually. Despite this loss of agricultural land, irrigated agriculture increased substantially until 2000, but has since declined because of diminishing water availability and uncontrolled extraction of groundwater driven by population pressures and the extended need for food. A good agreement (r = 0.73) was found between increases in irrigated land and the depletion of the shallow groundwater table, a factor affecting widely practiced small-scale irrigation in northwestern Bangladesh. Results quantified the land cover change patterns and the stresses placed on natural resources; additionally, they demonstrated an accurate and economical means to map and analyze changes in land cover over time at a regional scale, which can assist decision makers in land and natural resources management decisions.

Land cover mapping at Alkali Flat and Lake Lucero, White Sands, New Mexico, USA using multi-temporal and multi-spectral remote sensing data

Science.gov (United States)

Ghrefat, Habes A.; Goodell, Philip C.

2011-08-01

The goal of this research is to map land cover patterns and to detect changes that occurred at Alkali Flat and Lake Lucero, White Sands using multispectral Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Advanced Land Imager (ALI), and hyperspectral Hyperion and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data. The other objectives of this study were: (1) to evaluate the information dimensionality limits of Landsat 7 ETM+, ASTER, ALI, Hyperion, and AVIRIS data with respect to signal-to-noise and spectral resolution, (2) to determine the spatial distribution and fractional abundances of land cover endmembers, and (3) to check ground correspondence with satellite data. A better understanding of the spatial and spectral resolution of these sensors, optimum spectral bands and their information contents, appropriate image processing methods, spectral signatures of land cover classes, and atmospheric effects are needed to our ability to detect and map minerals from space. Image spectra were validated using samples collected from various localities across Alkali Flat and Lake Lucero. These samples were measured in the laboratory using VNIR-SWIR (0.4-2.5 μm) spectra and X-ray Diffraction (XRD) method. Dry gypsum deposits, wet gypsum deposits, standing water, green vegetation, and clastic alluvial sediments dominated by mixtures of ferric iron (ferricrete) and calcite were identified in the study area using Minimum Noise Fraction (MNF), Pixel Purity Index (PPI), and n-D Visualization. The results of MNF confirm that AVIRIS and Hyperion data have higher information dimensionality thresholds exceeding the number of available bands of Landsat 7 ETM+, ASTER, and ALI data. ASTER and ALI data can be a reasonable alternative to AVIRIS and Hyperion data for the purpose of monitoring land cover, hydrology and sedimentation in the basin. The spectral unmixing analysis and dimensionality eigen

Towards Seamless Validation of Land Cover Data

Science.gov (United States)

Chuprikova, Ekaterina; Liebel, Lukas; Meng, Liqiu

2018-05-01

This article demonstrates the ability of the Bayesian Network analysis for the recognition of uncertainty patterns associated with the fusion of various land cover data sets including GlobeLand30, CORINE (CLC2006, Germany) and land cover data derived from Volunteered Geographic Information (VGI) such as Open Street Map (OSM). The results of recognition are expressed as probability and uncertainty maps which can be regarded as a by-product of the GlobeLand30 data. The uncertainty information may guide the quality improvement of GlobeLand30 by involving the ground truth data, information with superior quality, the know-how of experts and the crowd intelligence. Such an endeavor aims to pave a way towards a seamless validation of global land cover data on the one hand and a targeted knowledge discovery in areas with higher uncertainty values on the other hand.

QUALITY ASSESSMENT AND CONTROL OF OUTPUTS OF A NATIONWIDE AGRICULTURAL LAND COVER MAPPING PROGRAM USING LIDAR: PHIL-LIDAR 2 PARMAP EXPERIENCE

Directory of Open Access Journals (Sweden)

H. M. Pagkalinawan

2017-11-01

Full Text Available The Agricultural Resources Extraction from LiDAR Surveys (PARMAP project component of the Nationwide Detailed Resources Assessment using LiDAR (Phil-LiDAR 2 Program aims to produce detailed agricultural maps using LiDAR. Agricultural land cover at crop level was classified through object based image analysis using Support Vector Machine as classifier and LiDAR derivatives from point cloud (2 points per sq.m. and orthophoto (0.5-meter resolution as inputs. An accuracy of at least 90 %, assessed using validation points from the field and through image interpretation, was required before proceeding to post-processing and map lay-out. Knowledge sharing and capacity development facilitated by the University of the Philippines Diliman (UPD enabled partner universities across the Philippines to produce outputs for their assigned region. Considering output layers were generated by multiple teams working on different landscape complexities with some degree of data quality variability, quality checking is crucial to ensure accuracy standards were met. UPD PARMap devised a centralized and end-to-end scheme divided into four steps – land classification, GIS post-processing, schema application, and map lay-out. At each step, a block is reviewed and, subsequently, either approved or returned with documentation on required revisions. Turnaround time of review is at least one block (area ranging from 10 to 580 sq. km. per day. For coastal municipalities, an additional integration process to incorporate mapped coastal features was applied. Common problems observed during quality checking include misclassifications, gaps between features, incomplete attributes and missing map elements. Some issues are particular to specific blocks such as problematic LiDAR derivatives. UPD addressed these problems through discussion and mentoring visits to partner universities. As of March 2017, a total of 336 municipal agricultural maps have been turned-over to various

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

Science.gov (United States)

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

2016-11-01

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

Oak Ridge reservation land-use plan

Energy Technology Data Exchange (ETDEWEB)

Bibb, W. R.; Hardin, T. H.; Hawkins, C. C.; Johnson, W. A.; Peitzsch, F. C.; Scott, T. H.; Theisen, M. R.; Tuck, S. C.

1980-03-01

This study establishes a basis for long-range land-use planning to accommodate both present and projected DOE program requirements in Oak Ridge. In addition to technological requirements, this land-use plan incorporates in-depth ecological concepts that recognize multiple uses of land as a viable option. Neither environmental research nor technological operations need to be mutually exclusive in all instances. Unique biological areas, as well as rare and endangered species, need to be protected, and human and environmental health and safety must be maintained. The plan is based on the concept that the primary use of DOE land resources must be to implement the overall DOE mission in Oak Ridge. This document, along with the base map and overlay maps, provides a reasonably detailed description of the DOE Oak Ridge land resources and of the current and potential uses of the land. A description of the land characteristics, including geomorphology, agricultural productivity and soils, water courses, vegetation, and terrestrial and aquatic animal habitats, is presented to serve as a resource document. Essentially all DOE land in the Oak Ridge area is being fully used for ongoing DOE programs or has been set aside as protected areas.

Mapping out the regulatory environment and its interaction with land and property markets

International Nuclear Information System (INIS)

Adams, David

2008-01-01

The purpose of this paper is to explain how the regulatory environment created by planning and building regulations interacts with land and property markets. Since this regulatory environment operates as a form of intervention within property markets in general and the development process in particular, it is essential first to understand the nature, structure and operation of land and property markets. These are covered in the first section. The second section identifies the aims and components of the planning system and building regulations. From this basis, four broad types of policy intervention are reviewed in the third section. These cover policies that seek to shape, regulate or stimulate market activity, and those that aim to build state or market capacity to produce desired outcomes. The final section uses the private residential development process as a case study to explore the extent to which state intervention can influence producer-consumer relationships in one important market sector. The paper argues that effective intervention in land and property markets requires the creation of a broad range of policy tools and their appropriate deployment to suit particular market circumstances. (author)

Agent-based land markets: Heterogeneous agents, land proces and urban land use change

NARCIS (Netherlands)

Filatova, Tatiana; Parker, Dawn C.; van der Veen, A.; Amblard, F.

2007-01-01

We construct a spatially explicit agent-based model of a bilateral land market. Heterogeneous agents form their bid and ask prices for land based on the utility that they obtain from a certain location (houte/land) and base on the state of the market (an excess of demand or supply). We underline the

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

Comparison of Desertification Intensity in the Purified Wastewater Irrigated Lands with Normal Lands in Yazd Using of Soil Criterion of the IMDPA Model

Directory of Open Access Journals (Sweden)

M. Yektafar

2016-09-01

Full Text Available Introduction: Desertification, is a complex phenomenon, which as environmental, socio-economical, and cultural impacts on natural resources. According to the United Nations Convention to Combat Desertification defination, desertification is land degradation in arid, semi-arid, and dry sub-humid regions, resulting from climate change and human activities. Because of limiting access to qualified water resources in arid lands, it is necessary to use, all forms of acceptable water resources such as wastewater. Since irrigation with sewages has most effects on soil, in this research, desertification intensity of lands irrigated with sewages and natural lands of the area, where located near Yazd city, has been analyzed considering soil criterion of the Iranian Model for Desertification Potential Assessment (IMDPA. Several studies have done in Iran and in the world in order to provide national, regional or global desertification assessment models. A significant feature of the IMDPA is easily defining and measuring criteria, indicators, and ability of the model to use geometric means for the criteria and indicators. Materials and Methods: In first step, In first step, in a random method, soil samples were taken in each of the defined land units with considering of the size of area. Next, all indices related to the soil criterion such as soil texture index, soil deep gravel percentage, soil depth, and soil electrical conductivity were evaluated in each land use (both irrigated lands and natural lands and weighted considering the present conditions of the lands. Each index was scored according to the standard table of soil that categorized desertification. Then, geometry average of all indices were calculated and map of the desertification intensity of the study area were prepared. Thus, four maps were prepared according to each index. These maps were used to study both quality and effect of each index on desertification. Finally, these maps were

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...

Potential land use planning and assessment in the west part of the Büyük Menderes basin by ILSEN Model

Directory of Open Access Journals (Sweden)

Mustafa Bolca

2013-01-01

Full Text Available This research was planned to investigate the structural properties and soil mapping capability according to rules of the 7. Approximation Soil Taxonomic System of the region western part of the Büyük Menderes Basin by using Landsat satellite images in remote sensing technique. The data gathered from field observation about some soil properties and land requirements of different land use types were correlated and as a result of that the boundaries of land use patterns were carried out. Land use patterns were detected according to suitable land use classes for soil mapping units and potential land use map were done. Land use assessment is likely to be the prediction of land potential for productive land use types. This case is great important in guiding decisions on land uses in terms of potential and conserving natural resources for future generations. The main objective of this study was to determine land resources and to assess potential land use in the west part of the Büyük Menderes Basin of Aegean region. The study area covers about 24.300 km2 and formed on alluvial material deposited by Büyük Menders River. Using Landsat 5 TM satellite images, which cover back and foot slope of mountain and alluvial plains of the western part of Menderes Basin, and taking physiographic units of the region as basis, detailed soil series and phases were determined. Soils of the region were classified as Entisol, Inceptisol as 2 orders, 4 suborders, 4 great groups and 6 sub groups, and 10 series. Twenty-five different land utilization types grouped into 4 major land use groups were evaluated for the studied area’s soils. ILSEN computer model was used to determined potential land use groups and suitable classes for agricultural uses. In addition, ArcGIS software was used to generate their maps and database. Suitability map for agricultural uses results showed that, distributions of the best, relatively good, problematic and restricted agricultural lands

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.

Spatial-area selective retrieval of multiple object-place associations in a hierarchical cognitive map formed by theta phase coding.

Science.gov (United States)

Sato, Naoyuki; Yamaguchi, Yoko

2009-06-01

The human cognitive map is known to be hierarchically organized consisting of a set of perceptually clustered landmarks. Patient studies have demonstrated that these cognitive maps are maintained by the hippocampus, while the neural dynamics are still poorly understood. The authors have shown that the neural dynamic "theta phase precession" observed in the rodent hippocampus may be capable of forming hierarchical cognitive maps in humans. In the model, a visual input sequence consisting of object and scene features in the central and peripheral visual fields, respectively, results in the formation of a hierarchical cognitive map for object-place associations. Surprisingly, it is possible for such a complex memory structure to be formed in a few seconds. In this paper, we evaluate the memory retrieval of object-place associations in the hierarchical network formed by theta phase precession. The results show that multiple object-place associations can be retrieved with the initial cue of a scene input. Importantly, according to the wide-to-narrow unidirectional connections among scene units, the spatial area for object-place retrieval can be controlled by the spatial area of the initial cue input. These results indicate that the hierarchical cognitive maps have computational advantages on a spatial-area selective retrieval of multiple object-place associations. Theta phase precession dynamics is suggested as a fundamental neural mechanism of the human cognitive map.

Policy implications in developing a land use management information systems

Science.gov (United States)

Landini, A. J.

1975-01-01

The current land use map for the city of Los Angeles was developed by the guesstimation process and provides single stage information for each level in the critical geographical hierarchy for land use planning management. Processing and incorporation of LANDSAT data in the land use information system requires special funding; however, computergraphic maps are able to provide a viable information system for city planning and management.

On the spatial and temporal resolution of land cover products for applied use in wind resource mapping

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Badger, Merete; Dellwik, Ebba

as input for modelling the wind conditions over a Danish near-coastal region. The flow model results were compared to alternative use of USGS land cover. Significant variations in the wind speed were found between the two atmospheric flow model results. Furthermore the wind speed from the flow model...... was compared to meteorological observations taken in a tall mast and from ground based remote-sensing wind profiling lidars. It is shown that simulations using CORINE provide better wind flow results close to the surface as compared to those using USGS on the investigated site. The next step towards...... improvement of flow model inputs is to investigate in further detail applied use of satellite maps in forested areas. 75% of new land-based wind farms are planned in or near forests in Europe. In forested areas the near surface atmospheric flow is more challenging to calculate than in regions with low...

Discovering Land Cover Web Map Services from the Deep Web with JavaScript Invocation Rules

Directory of Open Access Journals (Sweden)

Dongyang Hou

2016-06-01

Full Text Available Automatic discovery of isolated land cover web map services (LCWMSs can potentially help in sharing land cover data. Currently, various search engine-based and crawler-based approaches have been developed for finding services dispersed throughout the surface web. In fact, with the prevalence of geospatial web applications, a considerable number of LCWMSs are hidden in JavaScript code, which belongs to the deep web. However, discovering LCWMSs from JavaScript code remains an open challenge. This paper aims to solve this challenge by proposing a focused deep web crawler for finding more LCWMSs from deep web JavaScript code and the surface web. First, the names of a group of JavaScript links are abstracted as initial judgements. Through name matching, these judgements are utilized to judge whether or not the fetched webpages contain predefined JavaScript links that may prompt JavaScript code to invoke WMSs. Secondly, some JavaScript invocation functions and URL formats for WMS are summarized as JavaScript invocation rules from prior knowledge of how WMSs are employed and coded in JavaScript. These invocation rules are used to identify the JavaScript code for extracting candidate WMSs through rule matching. The above two operations are incorporated into a traditional focused crawling strategy situated between the tasks of fetching webpages and parsing webpages. Thirdly, LCWMSs are selected by matching services with a set of land cover keywords. Moreover, a search engine for LCWMSs is implemented that uses the focused deep web crawler to retrieve and integrate the LCWMSs it discovers. In the first experiment, eight online geospatial web applications serve as seed URLs (Uniform Resource Locators and crawling scopes; the proposed crawler addresses only the JavaScript code in these eight applications. All 32 available WMSs hidden in JavaScript code were found using the proposed crawler, while not one WMS was discovered through the focused crawler

SAT-MAP-CLIMATE project results[SATellite base bio-geophysical parameter MAPping and aggregation modelling for CLIMATE models

Energy Technology Data Exchange (ETDEWEB)

Bay Hasager, C.; Woetmann Nielsen, N.; Soegaard, H.; Boegh, E.; Hesselbjerg Christensen, J.; Jensen, N.O.; Schultz Rasmussen, M.; Astrup, P.; Dellwik, E.

2002-08-01

Earth Observation (EO) data from imaging satellites are analysed with respect to albedo, land and sea surface temperatures, land cover types and vegetation parameters such as the Normalized Difference Vegetation Index (NDVI) and the leaf area index (LAI). The observed parameters are used in the DMI-HIRLAM-D05 weather prediction model in order to improve the forecasting. The effect of introducing actual sea surface temperatures from NOAA AVHHR compared to climatological mean values, shows a more pronounced land-sea breeze effect which is also observable in field observations. The albedo maps from NOAA AVHRR are rather similar to the climatological mean values so for the HIRLAM model this is insignicant, yet most likely of some importance in the HIRHAM regional climate model. Land cover type maps are assigned local roughness values determined from meteorological field observations. Only maps with a spatial resolution around 25 m can adequately map the roughness variations of the typical patch size distribution in Denmark. A roughness map covering Denmark is aggregated (ie area-average non-linearly) by a microscale aggregation model that takes the non-linear turbulent responses of each roughness step change between patches in an arbitrary pattern into account. The effective roughnesses are calculated into a 15 km by 15 km grid for the HIRLAM model. The effect of hedgerows is included as an added roughness effect as a function of hedge density mapped from a digital vector map. Introducing the new effective roughness maps into the HIRLAM model appears to remedy on the seasonal wind speed bias over land and sea in spring. A new parameterisation on the effective roughness for scalar surface fluxes is developed and tested on synthetic data. Further is a method for the estimation the evapotranspiration from albedo, surface temperatures and NDVI succesfully compared to field observations. The HIRLAM predictions of water vapour at 12 GMT are used for atmospheric correction of

Status and trends of land change in the Eastern United States—1973 to 2000

Science.gov (United States)

Sayler, Kristi L.; Acevedo, William; Taylor, Janis

2016-09-28

PrefaceU.S. Geological Survey (USGS) Professional Paper 1794–D is the fourth in a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the Eastern United States between 1973 and 2000. Volumes A, B, and C provide similar analyses for the Western United States, the Great Plains of the United States, and the Midwest–South Central United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation.Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Eastern United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Eastern United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of ecological goods and

Low-cost computer classification of land cover in the Portland area, Oregon, by signature extension techniques

Science.gov (United States)

Gaydos, Leonard

1978-01-01

Computer-aided techniques for interpreting multispectral data acquired by Landsat offer economies in the mapping of land cover. Even so, the actual establishment of the statistical classes, or "signatures," is one of the relatively more costly operations involved. Analysts have therefore been seeking cost-saving signature extension techniques that would accept training data acquired for one time or place and apply them to another. Opportunities to extend signatures occur in preprocessing steps and in the classification steps that follow. In the present example, land cover classes were derived by the simplest and most direct form of signature extension: Classes statistically derived from a Landsat scene for the Puget Sound area, Wash., were applied to the Portland area, Oreg., using data for the next Landsat scene acquired less than 25 seconds down orbit. Many features can be recognized on the reduced-scale version of the Portland land cover map shown in this report, although no statistical assessment of its accuracy is available.

Building Land Information Policies

DEFF Research Database (Denmark)

Enemark, Stig

2004-01-01

The paper presents a conceptual understanding in the areas of Cadastre, Land Administration, and Land Management as a basis for building adequate land information policies. To develop this understanding the paper looks at each area as a system or an infrastructure designed for handling specific...... of measurement science, spatial information, management, and land management. (2) To establish national professional associations which accommodate a modern interdisciplinary profile. (3) To assess the capacity needs in land administration and to develop the capacity needed at societal, institutional...... and personal level.    (4) To establish appropriate institutional and organisational infrastructures to manage the integration of topographic mapping and cadastral information into a coherent land administration system for sustainable development. The paper aims to establish the basic understanding for dealing...

Discrimination Of The Land Features In Al Hasa Oasi, Saudi Arabia, Using Color Ratio Technique On Land Sat Tm Data

International Nuclear Information System (INIS)

Al Saud, M.B.M.

2003-01-01

Landsat Thematic Mapper (TM) data for Al Rasa Oasis area was processed for delineating characteristic land features represented mainly by sand dunes, sabkhas, cultivated land and urban areas using procedures that take advantage of distinctive spectral reflectance of these land features. The method employs a color ratio technique based on comprising different ratios 2/3, 2/4, 3/4, 3/5, 4/5, 5/6, and 5/7. A number of ratio triplets were processed using a three colored composite ratio. The ratio images (3/4,3/5,5/6,and 5/7) succeeded to distinguish the main land features in the studied arid region and generate detailed maps over wide area by using quantitative reproducible mapping criteria and helping in identifying the characteristics of the different land features

Land Use Cover Mapping of Water Melon and Cereals in Southern Italy

Directory of Open Access Journals (Sweden)

Costanza Fiorentino

2010-06-01

Full Text Available The new high-resolution images from the satellites as IKONOS, SPOT5, Quickbird2 give us the opportunity to map ground features, which were not detectable in the past, by using medium resolution remote sensed data (LANDSAT. More accurate and reliable maps of land cover can then be produced. However, classification procedure with these images is more complex than with the medium resolution remote sensing data for two main reasons: firstly, because of their exiguous number of spectral bands, secondly, owing to high spatial resolution, the assumption of pixel independence does not generally hold. It is then necessary to have a multi-temporal series of images or to use classifiers taking into account also proximal information. The data in this study were (i a remote sensing image taken by SPOT5 satellite in July 2007 and used to discriminate the water melon cover class and, (ii three multi-temporal remote sensing images taken by SPOT5 satellite in May, June and July 2008 used to discriminate water melon and cereal crop cover classes. For water melon recognition, providing a single image in 2007, an object-oriented technique was applied instead of a traditional, per pixel technique obtaining an increase of overall accuracy of 15%. In 2008, since it was available a multi-temporal data set, a traditional ‘Maximum Likelihood’ technique was applied for both water melon and cereal crop cover class. The overall accuracy is greater than 95%.

Mapping land water and energy balance relations through conditional sampling of remote sensing estimates of atmospheric forcing and surface states

Science.gov (United States)

Farhadi, Leila; Entekhabi, Dara; Salvucci, Guido

2016-04-01

In this study, we develop and apply a mapping estimation capability for key unknown parameters that link the surface water and energy balance equations. The method is applied to the Gourma region in West Africa. The accuracy of the estimation method at point scale was previously examined using flux tower data. In this study, the capability is scaled to be applicable with remotely sensed data products and hence allow mapping. Parameters of the system are estimated through a process that links atmospheric forcing (precipitation and incident radiation), surface states, and unknown parameters. Based on conditional averaging of land surface temperature and moisture states, respectively, a single objective function is posed that measures moisture and temperature-dependent errors solely in terms of observed forcings and surface states. This objective function is minimized with respect to parameters to identify evapotranspiration and drainage models and estimate water and energy balance flux components. The uncertainty of the estimated parameters (and associated statistical confidence limits) is obtained through the inverse of Hessian of the objective function, which is an approximation of the covariance matrix. This calibration-free method is applied to the mesoscale region of Gourma in West Africa using multiplatform remote sensing data. The retrievals are verified against tower-flux field site data and physiographic characteristics of the region. The focus is to find the functional form of the evaporative fraction dependence on soil moisture, a key closure function for surface and subsurface heat and moisture dynamics, using remote sensing data.

Downgrading recent estimates of land available for biofuel production.

Science.gov (United States)

Fritz, Steffen; See, Linda; van der Velde, Marijn; Nalepa, Rachel A; Perger, Christoph; Schill, Christian; McCallum, Ian; Schepaschenko, Dmitry; Kraxner, Florian; Cai, Ximing; Zhang, Xiao; Ortner, Simone; Hazarika, Rubul; Cipriani, Anna; Di Bella, Carlos; Rabia, Ahmed H; Garcia, Alfredo; Vakolyuk, Mar'yana; Singha, Kuleswar; Beget, Maria E; Erasmi, Stefan; Albrecht, Franziska; Shaw, Brian; Obersteiner, Michael

2013-02-05

Recent estimates of additional land available for bioenergy production range from 320 to 1411 million ha. These estimates were generated from four scenarios regarding the types of land suitable for bioenergy production using coarse-resolution inputs of soil productivity, slope, climate, and land cover. In this paper, these maps of land availability were assessed using high-resolution satellite imagery. Samples from these maps were selected and crowdsourcing of Google Earth images was used to determine the type of land cover and the degree of human impact. Based on this sample, a set of rules was formulated to downward adjust the original estimates for each of the four scenarios that were previously used to generate the maps of land availability for bioenergy production. The adjusted land availability estimates range from 56 to 1035 million ha depending upon the scenario and the ruleset used when the sample is corrected for bias. Large forest areas not intended for biofuel production purposes were present in all scenarios. However, these numbers should not be considered as definitive estimates but should be used to highlight the uncertainty in attempting to quantify land availability for biofuel production when using coarse-resolution inputs with implications for further policy development.

A computer-oriented system for assembling and displaying land management information

Science.gov (United States)

Elliot L. Amidon

1964-01-01

Maps contain information basic to land management planning. By transforming conventional map symbols into numbers which are punched into cards, the land manager can have a computer assemble and display information required for a specific job. He can let a computer select information from several maps, combine it with such nonmap data as treatment cost or benefit per...

Quaternary Geologic Map of the Regina 4 Degrees x 6 Degrees Quadrangle, United States and Canada

Science.gov (United States)

Fullerton, David S.; Christiansen, Earl A.; Schreiner, Bryan T.; Colton, Roger B.; Clayton, Lee; Bush, Charles A.; Fullerton, David S.

2007-01-01

For scientific purposes, the map differentiates Quaternary surficial deposits and materials on the basis of clast lithology or composition, matrix texture or particle size, structure, genesis, stratigraphic relations, engineering geologic properties, and relative age, as shown on the correlation diagram and indicated in the 'Description of Map Units'. Deposits of some constructional landforms, such as end moraines, are distinguished as map units. Deposits of erosional landforms, such as outwash terraces, are not distinguished, although glaciofluvial, ice-contact, fluvial, and lacustrine deposits that are mapped may be terraced. Differentiation of sequences of fluvial and glaciofluvial deposits at this scale is not possible. For practical purposes, the map is a surficial materials map. Materials are distinguished on the basis of lithology or composition, texture or particle size, and other physical, chemical, and engineering characteristics. It is not a map of soils that are recognized and classified in pedology or agronomy. Rather, it is a generalized map of soils as recognized in engineering geology, or of substrata or parent materials in which pedologic or agronomic soils are formed. As a materials map, it serves as a base from which a variety of maps for use in planning engineering, land-use planning, or land-management projects can be derived and from which a variety of maps relating to earth surface processes and Quaternary geologic history can be derived.

Land use planning for forest catchment of Arasbaran

International Nuclear Information System (INIS)

Dehdar Dargahi, M.; Makhdoum, M.F.

2001-01-01

In this study, land use planning for six hydrological units (296690 ha) of Arasbaran forest catchment (N W of Iran in Azerbaijan) has been conducted. The main objectives of the plan were to promote sustainable use, to increase living conditions, and enhance environmental conservation in the region. First, ecological and socio-economic resources were surveyed and mapped (scale 1:50000). Then data analysis and integration with system analysis approach were performed. As a result, 3556 micro-ecosystems were mapped. Ecological capability of mapping unit (MU) was evaluated for: agriculture, range management, forestry, eco tourism and conservation with the aid of specified ecological models. Finally with coordination of socioeconomic data and ecological capability of MU, priority of land uses with qualitative-analogous method was established. At the end, map of land use planning for six hydrological units was depicted for management purposes. The results show that %5.38 of allocated land use is suitable for irrigation farming, %1.32 for dry farming, %17.43 for range management, %15.17 for protected forestry, %2.13 for forest plantation, %28.47 for extensive eco tourism, %0.01 for intensive eco tourism and finally %30.09 for conservation

Archetypical patterns and trajectories of land systems in Europe

DEFF Research Database (Denmark)

Levers, Christian; Müller, Daniel; Erb, Karlheinz

2018-01-01

-system change, there is a need to develop approaches to reduce this complexity. Using Europe as a case study, we applied a clustering approach based on self-organising maps and 12 land-use indicators to map (1) land-system archetypes for the year 2006, defined as characteristic patterns of land-use extent...... and intensity, and (2) archetypical change trajectories, defined as characteristic changes in these indicators between 1990 and 2006. Our analysis identified 15 land-system archetypes, with low-intensity archetypes dominating (ca. 55 % coverage) followed by high-intensity archetypes (ca. 26 %). In terms...... of change, we identified 17 archetypical change trajectories, clustered in four broad categories. Stable land systems were most widespread (ca. 40 % of the EU27), followed by land systems characterised by land-use conversions (ca. 26 %), de-intensification trends (ca. 18 %), and intensification trends (ca...

The evolving Alaska mapping program.

Science.gov (United States)

Brooks, P.D.; O'Brien, T. J.

1986-01-01

This paper describes the development of mapping in Alaska, the current status of the National Mapping Program, and future plans for expanding and improving the mapping coverage. Research projects with Landsat Multispectral Scanner and Return Vidicon imagery and real- and synthetic-aperture radar; image mapping programs; digital mapping; remote sensing projects; the Alaska National Interest Lands Conservation Act; and the Alaska High-Altitude Aerial Photography Program are also discussed.-from Authors

Simultaneous comparison and assessment of eight remotely sensed maps of Philippine forests

Science.gov (United States)

Estoque, Ronald C.; Pontius, Robert G.; Murayama, Yuji; Hou, Hao; Thapa, Rajesh B.; Lasco, Rodel D.; Villar, Merlito A.

2018-05-01

This article compares and assesses eight remotely sensed maps of Philippine forest cover in the year 2010. We examined eight Forest versus Non-Forest maps reclassified from eight land cover products: the Philippine Land Cover, the Climate Change Initiative (CCI) Land Cover, the Landsat Vegetation Continuous Fields (VCF), the MODIS VCF, the MODIS Land Cover Type product (MCD12Q1), the Global Tree Canopy Cover, the ALOS-PALSAR Forest/Non-Forest Map, and the GlobeLand30. The reference data consisted of 9852 randomly distributed sample points interpreted from Google Earth. We created methods to assess the maps and their combinations. Results show that the percentage of the Philippines covered by forest ranges among the maps from a low of 23% for the Philippine Land Cover to a high of 67% for GlobeLand30. Landsat VCF estimates 36% forest cover, which is closest to the 37% estimate based on the reference data. The eight maps plus the reference data agree unanimously on 30% of the sample points, of which 11% are attributable to forest and 19% to non-forest. The overall disagreement between the reference data and Philippine Land Cover is 21%, which is the least among the eight Forest versus Non-Forest maps. About half of the 9852 points have a nested structure such that the forest in a given dataset is a subset of the forest in the datasets that have more forest than the given dataset. The variation among the maps regarding forest quantity and allocation relates to the combined effects of the various definitions of forest and classification errors. Scientists and policy makers must consider these insights when producing future forest cover maps and when establishing benchmarks for forest cover monitoring.

Status and trends of land change in the Midwest–South Central United States—1973 to 2000

Science.gov (United States)

Auch, Roger F.; Karstensen, Krista A.; Auch, Roger F.; Karstensen, Krista A.

2015-12-10

U.S. Geological Survey (USGS) Professional Paper 1794–C is the third in a four-volume series on the status and trends of the Nation’s land use and land cover, providing an assessment of the rates and causes of land-use and land-cover change in the Midwest–South Central United States between 1973 and 2000. Volumes A, B, and D provide similar analyses for the Western United States, the Great Plains of the United States, and the Eastern United States, respectively. The assessments of land-use and land-cover trends are conducted on an ecoregion-by-ecoregion basis, and each ecoregion assessment is guided by a nationally consistent study design that includes mapping, statistical methods, field studies, and analysis. Individual assessments provide a picture of the characteristics of land change occurring in a given ecoregion; in combination, they provide a framework for understanding the complex national mosaic of change and also the causes and consequences of change. Thus, each volume in this series provides a regional assessment of how (and how fast) land use and land cover are changing, and why. The four volumes together form the first comprehensive picture of land change across the Nation.Geographic understanding of land-use and land-cover change is directly relevant to a wide variety of stakeholders, including land and resource managers, policymakers, and scientists. The chapters in this volume present brief summaries of the patterns and rates of land change observed in each ecoregion in the Midwest–South Central United States, together with field photographs, statistics, and comparisons with other assessments. In addition, a synthesis chapter summarizes the scope of land change observed across the entire Midwest–South Central United States. The studies provide a way of integrating information across the landscape, and they form a critical component in the efforts to understand how land use and land cover affect important issues such as the provision of

Design and analysis for thematic map accuracy assessment: Fundamental principles

Science.gov (United States)

Stephen V. Stehman; Raymond L. Czaplewski

1998-01-01

Land-cover maps are used in numerous natural resource applications to describe the spatial distribution and pattern of land-cover, to estimate areal extent of various cover classes, or as input into habitat suitability models, land-cover change analyses, hydrological models, and risk analyses. Accuracy assessment quantifies data quality so that map users may evaluate...

BAC-HAPPY mapping (BAP mapping: a new and efficient protocol for physical mapping.

Directory of Open Access Journals (Sweden)

Giang T H Vu

2010-02-01

Full Text Available Physical and linkage mapping underpin efforts to sequence and characterize the genomes of eukaryotic organisms by providing a skeleton framework for whole genome assembly. Hitherto, linkage and physical "contig" maps were generated independently prior to merging. Here, we develop a new and easy method, BAC HAPPY MAPPING (BAP mapping, that utilizes BAC library pools as a HAPPY mapping panel together with an Mbp-sized DNA panel to integrate the linkage and physical mapping efforts into one pipeline. Using Arabidopsis thaliana as an exemplar, a set of 40 Sequence Tagged Site (STS markers spanning approximately 10% of chromosome 4 were simultaneously assembled onto a BAP map compiled using both a series of BAC pools each comprising 0.7x genome coverage and dilute (0.7x genome samples of sheared genomic DNA. The resultant BAP map overcomes the need for polymorphic loci to separate genetic loci by recombination and allows physical mapping in segments of suppressed recombination that are difficult to analyze using traditional mapping techniques. Even virtual "BAC-HAPPY-mapping" to convert BAC landing data into BAC linkage contigs is possible.

Land-use impact on selected forms of arsenic and phosphorus in soils of different functions

Science.gov (United States)

Plak, Andrzej; Bartmiński, Piotr; Dębicki, Ryszard

2017-10-01

The aim of the study was to assess the impact of technosols and geomechanically unchanged soils of the Lublin agglomeration on the concentrations of arsenic and phosphorus, and on selected forms of these elements. Arsenic and phosphorus concentrations were determined in the urban soils of Lublin (Poland), and the relationship between their degree of contamination and different types of land use was estimated. The samples collected were subjected to sequential analysis, using ammonium sulphate, acid ammonium phosphate, oxalate buffer (also with ascorbic acid) and aqua regia for arsenic, and ammonium chloride, sodium hydroxide, hydrochloric acid and aqua regia for phosphorus. The influence of the land use forms was observed in the study. The greatest amount of arsenic (19.62 mg kg-1) was found in the industrial soils of Lublin, while the greatest amount of phosphorus (580.4 mg kg-1) was observed in non-anthropogenic soils (mainly due to the natural accumulation processes of this element). Fractions of arsenic and phosphorus obtained during analysis showed strong differentiation. Amorphic and crystalline fractions of arsenic, bound with iron oxides, proved to have the highest share in the total arsenic pool. The same situation was noted for phosphorus.

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

Science.gov (United States)

Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K.

2018-01-01

Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type–semi-natural, vegetated land surfaces with varying degrees of management practices–for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area– 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and

Clustering of Multi-Temporal Fully Polarimetric L-Band SAR Data for Agricultural Land Cover Mapping

Science.gov (United States)

Tamiminia, H.; Homayouni, S.; Safari, A.

2015-12-01

Recently, the unique capabilities of Polarimetric Synthetic Aperture Radar (PolSAR) sensors make them an important and efficient tool for natural resources and environmental applications, such as land cover and crop classification. The aim of this paper is to classify multi-temporal full polarimetric SAR data using kernel-based fuzzy C-means clustering method, over an agricultural region. This method starts with transforming input data into the higher dimensional space using kernel functions and then clustering them in the feature space. Feature space, due to its inherent properties, has the ability to take in account the nonlinear and complex nature of polarimetric data. Several SAR polarimetric features extracted using target decomposition algorithms. Features from Cloude-Pottier, Freeman-Durden and Yamaguchi algorithms used as inputs for the clustering. This method was applied to multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Canada, during June and July in 2012. The results demonstrate the efficiency of this approach with respect to the classical methods. In addition, using multi-temporal data in the clustering process helped to investigate the phenological cycle of plants and significantly improved the performance of agricultural land cover mapping.

Methods for Delineating Degraded Land at Citarum Watershed, West Java, Indonesia

Directory of Open Access Journals (Sweden)

Suria Darma Tarigan

2012-09-01

Full Text Available Accurate information on the extent and spatial location of degraded lands is very important to plan their rehabilitation.So far, various institutions issue different estimation on the extent of degraded land in Indonesia led to big confusion for rehabilitation planning. Ministry of Forestry estimates around 30.2 million ha of degraded land both inside and outside forestry area throughout Indonesia based on data released in 2007. Ministry of Forestry implementes the socalled scoring method in delineating degraded land. Criteria used in the scoring methods are: land cover, slope steepness, erosion, and management. Scoring method applies different weight to each of those criteria. This study aimed to analyze accuracy of scoring method and to compare it to propose alternative methods in delineating degraded land such as: a Inconsistency of land use, and b Combination of Inconsistency of land use and scoring method. The accuracy of these methods were obtained by comparing to the field observation. The slope map was derived from SRTM 30 m, soil map was obtained from Soil Research Institute and land cover/land use from Ministry for Environment. Using GIS analysis, those maps were used to compose land capability classification (LCC and inconsistency of land use. The study showed that scoring method had 66% accuracy in delineating degraded land. When scoring method was combined with Inconsistency method the accuracy increased about 7%.

Direct sensor orientation of a land-based mobile mapping system.

Science.gov (United States)

Rau, Jiann-Yeou; Habib, Ayman F; Kersting, Ana P; Chiang, Kai-Wei; Bang, Ki-In; Tseng, Yi-Hsing; Li, Yu-Hua

2011-01-01

A land-based mobile mapping system (MMS) is flexible and useful for the acquisition of road environment geospatial information. It integrates a set of imaging sensors and a position and orientation system (POS). The positioning quality of such systems is highly dependent on the accuracy of the utilized POS. This limitation is the major drawback due to the elevated cost associated with high-end GPS/INS units, particularly the inertial system. The potential accuracy of the direct sensor orientation depends on the architecture and quality of the GPS/INS integration process as well as the validity of the system calibration (i.e., calibration of the individual sensors as well as the system mounting parameters). In this paper, a novel single-step procedure using integrated sensor orientation with relative orientation constraint for the estimation of the mounting parameters is introduced. A comparative analysis between the proposed single-step and the traditional two-step procedure is carried out. Moreover, the estimated mounting parameters using the different methods are used in a direct geo-referencing procedure to evaluate their performance and the feasibility of the implemented system. Experimental results show that the proposed system using single-step system calibration method can achieve high 3D positioning accuracy.

An investigation of the sensitivity of a land surface model to climate change using a reduced form model

Energy Technology Data Exchange (ETDEWEB)

Lynch, A.H.; McIlwaine, S. [PAOS/CIRES, Univ. of Colorado, Boulder, CO (United States); Beringer, J. [Inst. of Arctic Biology, Univ. of Alaska, Fairbanks (United States); Bonan, G.B. [National Center for Atmospheric Research, Boulder, CO (United States)

2001-05-01

In an illustration of a model evaluation methodology, a multivariate reduced form model is developed to evaluate the sensitivity of a land surface model to changes in atmospheric forcing. The reduced form model is constructed in terms of a set of ten integrative response metrics, including the timing of spring snow melt, sensible and latent heat fluxes in summer, and soil temperature. The responses are evaluated as a function of a selected set of six atmospheric forcing perturbations which are varied simultaneously, and hence each may be thought of as a six-dimensional response surface. The sensitivities of the land surface model are interdependent and in some cases illustrate a physically plausible feedback process. The important predictors of land surface response in a changing climate are the atmospheric temperature and downwelling longwave radiation. Scenarios characterized by warming and drying produce a large relative response compared to warm, moist scenarios. The insensitivity of the model to increases in precipitation and atmospheric humidity is expected to change in applications to coupled models, since these parameters are also strongly implicated, through the representation of clouds, in the simulation of both longwave and shortwave radiation. (orig.)

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

Science.gov (United States)

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

2018-01-01

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

Application of ASTER SWIR bands in mapping anomaly pixels for Antarctic geological mapping

International Nuclear Information System (INIS)

Beiranvand Pour, Amin; Hashim, Mazlan; Park, Yongcheol

2017-01-01

Independent component analysis (ICA) was applied to shortwave infrared (SWIR) bands of ASTER satellite data for detailed mapping of alteration mineral zones in the context of polar environments, where little prior information is available. The Oscar II coast area north-eastern Graham Land, Antarctic Peninsula (AP) was selected to conduct a remote sensing satellite-based mapping approach to detect alteration mineral assemblages. Anomaly pixels in the ICA image maps related to spectral features of Al-O-H, Fe, Mg-O-H and CO3 groups were detected using SWIR datasets of ASTER. ICA method provided image maps of alteration mineral assemblages and discriminate lithological units with little available geological data for poorly mapped regions and/or without prior geological information for unmapped regions in northern and southern sectors of Oscar II coast area, Graham Land. The results of this investigation demonstrated the applicability of ASTER spectral data for lithological and alteration mineral mapping in poorly exposed lithologies and inaccessible regions, particularly using the image processing algorithm that are capable to detect anomaly pixels targets in the remotely sensed images, where no prior information is available. (paper)

USGS Topo Base Map Service from The National Map

Data.gov (United States)

U.S. Geological Survey, Department of the Interior — USGS Topo is a topographic tile cache base map that combines the most current data (Boundaries, Names, Transportation, Elevation, Hydrography, Land Cover, and other...

Land use inventory of Salt Lake County, Utah from color infrared aerial photography 1982

Science.gov (United States)

Price, K. P.; Willie, R. D.; Wheeler, D. J.; Ridd, M. K.

1983-01-01

The preparation of land use maps of Salt Lake County, Utah from high altitude color infrared photography is described. The primary purpose of the maps is to aid in the assessment of the effects of urban development on the agricultural land base and water resources. The first stage of map production was to determine the categories of land use/land cover and the mapping unit detail. The highest level of interpretive detail was given to the land use categories found in the agricultural or urbanized portions of the county; these areas are of primary interest with regard to the consumptive use of water from surface streams and wells. A slightly lower level of mapping detail was given to wetland environments; areas to which water is not purposely diverted by man but which have a high consumptive rate of water use. Photos were interpreted on the basis of color, tone, texture, and pattern, together with features of the topographic, hydrologic, and ecological context.

A method for mapping corn using the US Geological Survey 1992 National Land Cover Dataset

Science.gov (United States)

Maxwell, S.K.; Nuckols, J.R.; Ward, M.H.

2006-01-01

Long-term exposure to elevated nitrate levels in community drinking water supplies has been associated with an elevated risk of several cancers including non-Hodgkin's lymphoma, colon cancer, and bladder cancer. To estimate human exposure to nitrate, specific crop type information is needed as fertilizer application rates vary widely by crop type. Corn requires the highest application of nitrogen fertilizer of crops grown in the Midwest US. We developed a method to refine the US Geological Survey National Land Cover Dataset (NLCD) (including map and original Landsat images) to distinguish corn from other crops. Overall average agreement between the resulting corn and other row crops class and ground reference data was 0.79 kappa coefficient with individual Landsat images ranging from 0.46 to 0.93 kappa. The highest accuracies occurred in Regions where corn was the single dominant crop (greater than 80.0%) and the crop vegetation conditions at the time of image acquisition were optimum for separation of corn from all other crops. Factors that resulted in lower accuracies included the accuracy of the NLCD map, accuracy of corn areal estimates, crop mixture, crop condition at the time of Landsat overpass, and Landsat scene anomalies.

Simulation of boreal Summer Monsoon Rainfall using CFSV2_SSiB model: sensitivity to Land Use Land Cover (LULC)

Science.gov (United States)

Chilukoti, N.; Xue, Y.

2016-12-01

The land surface play a vital role in determining the surface energy budget, accurate representation of land use and land cover (LULC) is necessary to improve forecast. In this study, we have investigated the influence of surface vegetation maps with different LULC on simulating the boreal summer monsoon rainfall. Using a National Centres for Environmental Prediction (NCEP) Coupled Forecast System version 2(CFSv2) model coupled with Simplified Simple Biosphere (SSiB) model, two experiments were conducted: one with old vegetation map and one with new vegetation map. The significant differences between new and old vegetation map were in semi-arid and arid areas. For example, in old map Tibetan plateau classified as desert, which is not appropriate, while in new map it was classified as grasslands or shrubs with bare soil. Old map classified the Sahara desert as a bare soil and shrubs with bare soil, whereas in new map it was classified as bare ground. In addition to central Asia and the Sahara desert, in new vegetation map, Europe had more cropped area and India's vegetation cover was changed from crops and forests to wooded grassland and small areas of grassland and shrubs. The simulated surface air temperature with new map shows a significant improvement over Asia, South Africa, and northern America by some 1 to 2ºC and 2 to 3ºC over north east China and these are consistent with the reduced rainfall biases over Africa, near Somali coast, north east India, Bangladesh, east China sea, eastern Pacific and northern USA. Over Indian continent and bay of Bengal dry rainfall anomalies that is the only area showing large dry rainfall bias, however, they were unchanged with new map simulation. Overall the CFSv2(coupled with SSiB) model with new vegetation map show a promising result in improving the monsoon forecast by improving the Land -Atmosphere interactions. To compare with the LULC forcing, experiment was conducted using the Global Forecast System (GFS) simulations

Spectral mixture analysis (SMA and change vector analysis (CVA methods for monitoring and mapping land degradation/desertification in arid and semiarid areas (Sudan, using Landsat imagery

Directory of Open Access Journals (Sweden)

Abdelrahim A.M. Salih

2017-04-01

Full Text Available The severe Sahel catastrophe in 1968–1974 as well as repeated famines and food shortage that have hit many African countries during the 1970s have highlighted the need for further research concerning land degradation and environmental monitoring in arid and semi-arid areas. Land degradation, and desertification processes in arid and semi-arid environment were increased in the last four decades, especially in the developing countries like Sudan. To test to what extent remote sensing and geographical information science (GIS methodologies and techniques could be used for monitoring changes in arid and semi-arid regions and environment, these methodologies have long been suggested as a time and cost-efficient method. In this frame, spectral Mixture Analysis (SMA, Object-based oriented classification (Segmentation, and Change Vector Analysis are recently much recommended as a most suitable method for monitoring and mapping land cover changes in arid and semi-arid environment. Therefor the aim of this study is to use these methods and techniques for environmental monitoring with emphasis on desertification and to find model that can describe and map the status and rate of desertification processes and land cover changes in semi-arid areas in White Nile State (Sudan by using multi-temporal imagery of the Landsat satellite TM (1987, TM (2000, and ETM+ (2014 respectively. The paper also discusses and evaluates the efficiency of the adapted methodologies in monitoring the land degradation processes and changes in the arid and semi-arid regions.

Testing the accuracy of remote sensing land use maps

Science.gov (United States)

Vangenderen, J. L.; Lock, B. F.; Vass, P. A.

1977-01-01

Some of the main aspects that need to be considered in a remote sensing sampling design are: (1) the frequency that any one land use type (on the ground) is erroneously attributed to another class by the interpreter; (2) the frequency that the wrong land use (as observed on the ground) is erroneously included in any one class by the remote sensing interpreter; (3) the proportion of all land (as determined in the field) that is mistakenly attributed by the interpreter; and (4) the determination of whether the mistakes are random (so that the overall proportions are approximately correct) or subject to a persistent bias. A sampling and statistical testing procedure is presented which allows an approximate answer to each of these aspects. The concept developed and described incorporates the probability of making incorrect interpretations at particular prescribed accuracy levels, for a certain number of errors, for a particular sample size. It is considered that this approach offers a meaningful explanation of the interpretation accuracy level of an entire remote sensing land use survey.

Historical changes in dispersed kopanitse land type and changes in use of agricultural land on Kysuce region example

Directory of Open Access Journals (Sweden)

Barančok Peter

2016-12-01

Full Text Available Territory of Kysuce is characterised by a high proportion of the traditional agricultural landscape (TAL, which occupy almost 12% of the area. Two types of TAL were allocated here. The first type is represented by TAL with dispersed settlement. The second type is represented by TAL of arable land and grassland landscape. The largest representation has typical forms of anthropogenic relief (FAR. TALs represent the most diverse mosaic of man-made habitats and natural habitats too. In the past, there were the largest representations of arable land and regularly mown meadows. Currently, these areas are dominated by abandoned meadows (fallow meadows, occasionally grazed pastures and meadows. Arable land is represented only minimally. The large part of areas is overgrown by non-forest woody vegetation or passes to the forest vegetation. In this process of landscape changes, significant changes in biodiversity of the areas are realised. Successively, the species of segetal and ruderal vegetation are less represented and species of forest vegetation obtained greater representation. In the process of mapping and evaluation, FAR - shape and orientation of plots, types of balks and some of their basic characteristics - were monitored.

Assessing urban vacant land ecosystem services: Urban vacant land as green infrastructure in the City of Roanoke, Virginia

Science.gov (United States)

Gunwoo Kim; Patrick A. Miller; David J. Nowak

2015-01-01

The research reported here quantifies the ecosystem services and values of vacant land using the City of Roanoke, Virginia as a study site. Aerial photo interpretation with ground-truthing was used to identify and catalog vacant parcels of land within the city limits and the results mapped using the i-Tree Canopy and i-Tree Eco models to define land cover classes and...

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

Science.gov (United States)

Land-cover maps are often used to compute land-cover composition (i.e., the proportion or percent of area covered by each class), for each unit in a spatial partition of the region mapped. We derive design-based estimators of mean deviation (MD), mean absolute deviation (MAD), ...

Method for estimating potential wetland extent by utilizing streamflow statistics and flood-inundation mapping techniques: Pilot study for land along the Wabash River near Terre Haute, Indiana

Science.gov (United States)

Kim, Moon H.; Ritz, Christian T.; Arvin, Donald V.

2012-01-01

Potential wetland extents were estimated for a 14-mile reach of the Wabash River near Terre Haute, Indiana. This pilot study was completed by the U.S. Geological Survey in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service (NRCS). The study showed that potential wetland extents can be estimated by analyzing streamflow statistics with the available streamgage data, calculating the approximate water-surface elevation along the river, and generating maps by use of flood-inundation mapping techniques. Planning successful restorations for Wetland Reserve Program (WRP) easements requires a determination of areas that show evidence of being in a zone prone to sustained or frequent flooding. Zone determinations of this type are used by WRP planners to define the actively inundated area and make decisions on restoration-practice installation. According to WRP planning guidelines, a site needs to show evidence of being in an "inundation zone" that is prone to sustained or frequent flooding for a period of 7 consecutive days at least once every 2 years on average in order to meet the planning criteria for determining a wetland for a restoration in agricultural land. By calculating the annual highest 7-consecutive-day mean discharge with a 2-year recurrence interval (7MQ2) at a streamgage on the basis of available streamflow data, one can determine the water-surface elevation corresponding to the calculated flow that defines the estimated inundation zone along the river. By using the estimated water-surface elevation ("inundation elevation") along the river, an approximate extent of potential wetland for a restoration in agricultural land can be mapped. As part of the pilot study, a set of maps representing the estimated potential wetland extents was generated in a geographic information system (GIS) application by combining (1) a digital water-surface plane representing the surface of inundation elevation that sloped in the downstream

Smartphones Based Mobile Mapping Systems

Science.gov (United States)

Al-Hamad, A.; El-Sheimy, N.

2014-06-01

The past 20 years have witnessed an explosive growth in the demand for geo-spatial data. This demand has numerous sources and takes many forms; however, the net effect is an ever-increasing thirst for data that is more accurate, has higher density, is produced more rapidly, and is acquired less expensively. For mapping and Geographic Information Systems (GIS) projects, this has been achieved through the major development of Mobile Mapping Systems (MMS). MMS integrate various navigation and remote sensing technologies which allow mapping from moving platforms (e.g. cars, airplanes, boats, etc.) to obtain the 3D coordinates of the points of interest. Such systems obtain accuracies that are suitable for all but the most demanding mapping and engineering applications. However, this accuracy doesn't come cheaply. As a consequence of the platform and navigation and mapping technologies used, even an "inexpensive" system costs well over 200 000 USD. Today's mobile phones are getting ever more sophisticated. Phone makers are determined to reduce the gap between computers and mobile phones. Smartphones, in addition to becoming status symbols, are increasingly being equipped with extended Global Positioning System (GPS) capabilities, Micro Electro Mechanical System (MEMS) inertial sensors, extremely powerful computing power and very high resolution cameras. Using all of these components, smartphones have the potential to replace the traditional land MMS and portable GPS/GIS equipment. This paper introduces an innovative application of smartphones as a very low cost portable MMS for mapping and GIS applications.

Geoinformatics for the Mapping of Nexus Between Poverty and Land Degradation in Drylands of Thar Desert

Science.gov (United States)

Gaur, Mahesh

2012-07-01

contributes to the relatively low Human Development Index (HDI) indicators. Besides the extreme deprivations in the normal course of life, the poor become particularly vulnerable at the time of recurrent drought induced crisis. (MPOWER, 2010) The present study demonstrates application of earth observations for the mapping of nexus between poverty and land degradation. The empirical study carried out by the investigator in the Pali district highlights that such technological inputs could be applied in support of the poor and marginal farming community in the different parts of State and the country at cadastral level.

Mapping earthworm communities in Europe

DEFF Research Database (Denmark)

Rutgers, Michiel; Orgiazzi, Alberto; Gardi, Ciro

Existing data sets on earthworm communities in Europe were collected, harmonized, modelled and depicted on a soil biodiversity map of Europe. Digital Soil Mapping was applied using multiple regressions relating relatively low density earthworm community data to soil characteristics, land use...

Mapping earthworm communities in Europe

NARCIS (Netherlands)

Rutgers, M.; Orgiazzi, A.; Gardi, C.; Römbke, J.; Jansch, S.; Keith, A.; Neilson, R.; Boag, B.; Schmidt, O.; Murchie, A.K.; Blackshaw, R.P.; Pérès, G.; Cluzeau, D.; Guernion, M.; Briones, M.J.I.; Rodeiro, J.; Pineiro, R.; Diaz Cosin, D.J.; Sousa, J.P.; Suhadolc, M.; Kos, I.; Krogh, P.H.; Faber, J.H.; Mulder, C.; Bogte, J.J.; Wijnen, van H.J.; Schouten, A.J.; Zwart, de D.

2016-01-01

Existing data sets on earthworm communities in Europe were collected, harmonized, collated, modelled and depicted on a soil biodiversity map. Digital Soil Mapping was applied using multiple regressions relating relatively low density earthworm community data to soil characteristics, land use,

Long-term agricultural land-cover change and potential for cropland expansion in the former Virgin Lands area of Kazakhstan

DEFF Research Database (Denmark)

Kraemer, Roland; Prishchepov, Alexander; Müller, Daniel

2015-01-01

of Northern Kazakhstan. Further, we assessed the potential of currently idle cropland for re-cultivation. We reconstructed the cropland extent before and after the Virgin Lands Campaign using archival maps, and we mapped the agricultural land cover in the late Soviet and post-Soviet period using multi...... until 1990, as well as cropland contraction after 1990, occurred mainly in areas that were less favorable for agriculture. Cropland re-cultivation after 2000 was occurring on lands with relatively favorable agro-environmental conditions in comparison to remaining idle croplands, albeit with much lower...... agro-environmental endowment compared to stable croplands from 1990 to 2010. In sum, we found that cropland production potentials of the currently uncultivated areas are much lower than commonly believed, and further cropland expansion is only possible at the expense of marginal lands. Our results...

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

Directory of Open Access Journals (Sweden)

Elizabeth Ferreira

2013-03-01

Full Text Available This study identified, quantified and analyzed changes in land use and cover on the campus of Federal University of Lavras campus, located in Lavras city (Minas Gerais State. The 2009 QuickBird satellite imagery and 1985, 1979, 1971, 1964 vertical aerial photographs were used to produce a set of land use and land cover maps. The work started with the orthorectification of the QuickBird satellite imagery and vertical aerial photographs. The identification and definition of land cover and land use classes were obtained from field surveys in 2009. First, the land cover and land use maps were made from that information. Finally, the quantification and analysis of changes were performed at the imagery time range. The results showed that in 2009 the "urbanized area class" of the campus reached 65.79 ha and that the most significant increase of this class occurred between the years 1964 (6.24 ha and 1971 (24.4 ha. The smallest area of "forest land class" found on the campus was 38.38 ha in 1971, and from 1979 on this situation has been improved reaching 113.18 ha of "forest land class" in 2009. For the "water class" there was not any dam constructed yet in the campus before 1971. Most of the campus area, previously used for "agricultural land class" had a significant reduction within this category, from 384.19 ha in 1964 to 271.16 ha in 2009.

76 FR 60962 - Noise Exposure Map Update for Buffalo Niagara International Airport, Buffalo, NY

Science.gov (United States)

2011-09-30

... ``2008 Noise Exposure Map with Land Use'' and Figure 9 ``2013 Noise Exposure Map & Affected Land Uses... meet applicable regulations and which depict non-compatible land uses as of the date of submission of... land use control and planning responsibilities of local government. These local responsibilities are...

LANDSAT-8 OPERATIONAL LAND IMAGER CHANGE DETECTION ANALYSIS

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W. Pervez

2017-05-01

Full Text Available This paper investigated the potential utility of Landsat-8 Operational Land Imager (OLI for change detection analysis and mapping application because of its superior technical design to previous Landsat series. The OLI SVM classified data was successfully classified with regard to all six test classes (i.e., bare land, built-up land, mixed trees, bushes, dam water and channel water. OLI support vector machine (SVM classified data for the four seasons (i.e., spring, autumn, winter, and summer was used to change detection results of six cases: (1 winter to spring which resulted reduction in dam water mapping and increases of bushes; (2 winter to summer which resulted reduction in dam water mapping and increase of vegetation; (3 winter to autumn which resulted increase in dam water mapping; (4 spring to summer which resulted reduction of vegetation and shallow water; (5 spring to autumn which resulted decrease of vegetation; and (6 summer to autumn which resulted increase of bushes and vegetation . OLI SVM classified data resulted higher overall accuracy and kappa coefficient and thus found suitable for change detection analysis.

Revisiting Kappa to account for change in the accuracy assessment of land-use models

NARCIS (Netherlands)

Vliet, van J.; Bregt, A.K.; Hagen-Zanker, A.

2011-01-01

Land-use change models are typically calibrated to reproduce known historic changes. Calibration results can then be assessed by comparing two datasets: the simulated land-use map and the actual land-use map at the same time. A common method for this is the Kappa statistic, which expresses the

Study on temporal and spatial variations of urban land use based on land change data

Science.gov (United States)

Jiang, Ping; Liu, Yanfang; Fan, Min; Zhang, Yang

2009-10-01

With the rapid development of urbanization, demands of urban land increase in succession, hence, to analyze temporal and spatial variations of urban land use becomes more and more important. In this paper, the principle of trend surface analysis and formula of urban land sprawl index ( ULSI) are expatiated at first, and then based on land change data of Jiayu county, the author fits quadratic trend surface by choosing urban land area as dependent variable and urbanization and GDP as independent variables from 1996 to 2006, draws isoline of trend surface and residual values; and then urban land sprawl indexes of towns are calculated on the basis of urban land area of 1996 and 2006 and distribution map of ULSI is plotted. After analyzing those results, we can conclude that there is consanguineous relationship between urban land area and urbanization, economic level etc.

Scientific Collaboration Along the Trinational Frontier of Brazil-Bolivia-Peru: Implications for Regional Land-Use in the MAP Region of Southwestern Amazonia

Science.gov (United States)

Brown, I.

2002-12-01

High-speed road systems are connecting southwestern Amazonia (~1.5 million km2) to Pacific and Atlantic ports as well as providing greater access to Brazilian, Bolivian and Peruvian urban markets. Coupled with this increased accessibility are ambitious governmental plans to expand production of timber, non-timber forest products, and beef, all of which are likely to modify human migrations in the region. The heart of southwestern Amazonia lies in the trinational frontier region of Madre de Dios Department/Peru, eastern Acre State/Brazil and Pando Department/Bolivia (MAP region: ~200,000 km2, ~500,000 inhabitants). The MAP region composes a global hot spot of terrestrial biodiversity and has become an axis of integration for the three countries. Faced with rapid change in socioeconomic trends, regional environmental scientists and professionals have promoted collaborative projects to analyze land use trends and their forcing functions and to supply these results to local and regional societies. In addition, they have begun to develop a regional scientific community that bridges different nationalities and specialties. The projects are both international - as they involve three countries - and local/regional as they involve institutions that are within a radius of 300 km of the border. In the past two years, LBA-sponsored activities have helped bring over 100 professionals together in the region in five MAP-oriented workshops. The research results are now influencing public policy and are being incorporated into the regional school systems with the objective of maximizing the benefits and minimizing the adverse impacts of the changing socio-economic trends on land-use and development in the MAP region.

Landslide inventory map as a tool for landscape planning and management in Buzau Land Geopark