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Land-cover Map (land-cover + map)
Selected AbstractsA new land-cover map of Africa for the year 2000JOURNAL OF BIOGEOGRAPHY, Issue 6 2004Philippe Mayaux Abstract Aim, In the framework of the Global Land Cover 2000 (GLC 2000), a land-cover map of Africa has been produced at a spatial resolution of 1 km using data from four sensors on-board four different Earth observing satellites. Location, The map documents the location and distribution of major vegetation types and non-vegetated land surface formations for the entire African continent plus Madagascar and the other surrounding islands. Methods, The bulk of these data were acquired on a daily basis throughout the year 2000 by the VEGETATION sensor on-board the SPOT-4 satellite. The map of vegetation cover has been produced based upon the spectral response and the temporal profile of the vegetation cover. Digital image processing and geographical information systems techniques were employed, together with local knowledge, high resolution imagery and expert consultation, to compile a cartographic map product. Radar data and thermal sensors were also used for specific land-cover classes. Results, A total of 27 land cover categories are documented, which has more thematic classes than previously published land cover maps of Africa contain. Systematic comparison with existing land cover data and 30-m resolution imagery from Landsat are presented, and the map is also compared with other pan-continental land cover maps. The map and digital data base are freely available for non-commercial uses from http://www.gvm.jrc.it/tem/africa/products.htm Main conclusions, The map improves our state of knowledge of the land-cover of Africa and presents the most spatially detailed view yet published at this scale. This first version of the map should provide an important input for regional stratification and planning purposes for natural resources, biodiversity and climate studies. Résumé Objet, Dans le cadre du projet Global Land Cover 2000 (GLC 2000), une carte d'Afrique d'occupation du sol a été produite à la résolution spatiale de 1 km à partir de données satellitales de 4 capteurs différents. Localisation, La carte représente la distribution des principaux types de végétation et des surfaces non-végétales du continent africain plus Madagascar et les autres îles voisines du continent. Méthodes, La plupart des données fut acquise durant l'année 2000 par le capteur VEGETATION, embarquéà bord du satellite SPOT-4. La réponse spectrale et le profil temporel des formations végétales ont permis la production de la carte d'occupation du sol. Des techniques de traitement d'image et de systèmes d'information géographique ont été combinées à la consultation d'experts locaux et à l'utilisation de cartes nationales et de données à haute résolution spatiale. Des images radar et thermiques ont servi à cartographier des classes spécifiques. Résultats, Un total de 27 classes est cartographié, ce qui est plus que les précédentes cartes basées sur l'imagerie satellitale. Une comparaison systématique avec les cartes publiées et des images Landsat à 30 m est présentée. Les données sont libres d'accès pour un usage non-commercial à l'adresse http://www.gvm.jrc.it/tem/africa/products.htm Conclusion, Cette carte accroît notre connaissance de l'occupation du sol de l'Afrique et présente la vue la plus détaillée jamais publiée à cette échelle. La première version de la carte devrait fournir une base importante pour une stratification régionale et pour la planification d'études sur les ressources naturelles, la biodiversité et le climat. [source] Assessment of soil erosion hazard and prioritization for treatment at the watershed level: Case study in the Chemoga watershed, Blue Nile basin, EthiopiaLAND DEGRADATION AND DEVELOPMENT, Issue 6 2009W. Bewket Abstract Soil erosion by water is the most pressing environmental problem in Ethiopia, particularly in the Highlands where the topography is highly rugged, population pressure is high, steeplands are cultivated and rainfall is erosive. Soil conservation is critically required in these areas. The objective of this study was to assess soil erosion hazard in a typical highland watershed (the Chemoga watershed) and demonstrate that a simple erosion assessment model, the universal soil loss equation (USLE), integrated with satellite remote sensing and geographical information systems can provide useful tools for conservation decision-making. Monthly precipitation, soil map, a 30-m digital elevation model derived from topographic map, land-cover map produced from supervised classification of a Land Sat image, and land use types and slope steepness were used to determine the USLE factor values. The results show that a larger part of the watershed (>58 per cent of total) suffers from a severe or very severe erosion risk (>80,t,ha,1,y,1), mainly in the midstream and upstream parts where steeplands are cultivated or overgrazed. In about 25 per cent of the watershed, soil erosion was estimated to exceed 125,t,ha,1,y,1. Based on the predicted soil erosion rates, the watershed was divided into six priority categories for conservation intervention and 18 micro-watersheds were identified that may be used as planning units. Finally, the method used has yielded a fairly reliable estimation of soil loss rates and delineation of erosion-prone areas. Hence, a similar method can be used in other watersheds to prepare conservation master plans and enable efficient use of limited resources. Copyright © 2009 John Wiley & Sons, Ltd. [source] Modeling above-ground litterfall in eastern Mediterranean conifer forests using fractional tree cover, and remotely sensed and ground dataAPPLIED VEGETATION SCIENCE, Issue 4 2010Sibel Taskinsu-Meydan Abstract Question: How can we model above-ground litterfall in Mediterranean conifer forests using remotely sensed and ground data, and geographic information systems (GIS)? Location: Eastern Mediterranean conifer forest of Turkey. Methods: Above-ground litterfall from Mediterranean forest stands of Pinus nigra, Cedrus libani, Pinus brutia and Juniperus excelsa and mixed Abies cilicica, C. libani and P. nigra was modeled as a function of fractional tree cover using a regression tree algorithm, based on IKONOS and Landsat TM/ETM+data. Landsat TM/ETM+images for the study area were used to map actual stand patterns, based on a land-cover map of species stands using a supervised classification. Results: Total amount of annual above-ground litterfall for the entire study area (12 260 km2) was estimated at 417.2 Mg ha,1 for P. brutia, 291.1 Mg ha,1 for the mixed stand, 115.5 Mg ha,1 for P. nigra, 54.6 Mg ha,1 for J. excelsa and 45.9 Mg ha,1 for C. libani. The maps generated indicate the distribution of the seasonal amount of total above-ground litterfall for different species and the distribution of species stands in the study area. There was an increase in the amount of above-ground litterfall for P. brutia stand in summer, for J. excelsa in autumn and for C. libani, P. nigra and the mixed stand of A. cilicica, P. nigra and C. libani in winter. Conclusion: Application of this model helps to improve the accuracy of estimated litterfall input to soil organic carbon pools in the Mediterranean conifer forests. [source] Landscape-scale patterns of alien plant species on coastal dunes: the case of iceplant in central ItalyAPPLIED VEGETATION SCIENCE, Issue 2 2010M. Laura Carranza Abstract Question: We investigated the spatial pattern of coastal landscapes invaded by iceplant (Carpobrotus aff. acinaciformis) focusing on two questions: (1) Does the spatial structure of iceplant patches differ from that of native natural costal dune cover types?; (2) Is the distribution of iceplant patches related to other cover types? Location: Tyrrhenian coast of Central Italy. Method: On the basis of a detailed land-cover map, we calculated structural metrics for iceplant patches and for each native coastal dune cover category (mean patch size and patch shape index) and compared them by means of anova. To assess the spatial association between iceplant patches and the different cover types, we implemented an electivity analysis which analyses the frequency of common borders. Results: The mapped coastal dune cover types included beaches, dunes and sand plain variants, related to the typical Tyrrhenian coastal dune vegetation zonation. Iceplant-dominated vegetation presented elongated and irregularly shaped patches, which were not significantly different from most of the natural cover types suggesting a natural spread along the territory analysed. Iceplant patches were positively associated with beach, mobile and inter-dune cover types indicating that these habitats are exposed to further alien spread. Iceplant patches were also positively associated with artificial surfaces highlighting this cover type as a possible source of propagule pressure. Conclusions: The proposed landscape approach combining patch-based metrics with edge-based metrics provided a comprehensive description of the invaded coastal landscape. From an applied research perspective, this landscape approach could be useful in identifying the correct management strategies for alien-invaded areas. [source] Forest Conversion and Degradation in Papua New Guinea 1972,2002BIOTROPICA, Issue 3 2009Phil L. Shearman ABSTRACT Quantifying forest change in the tropics is important because of the role these forests play in the conservation of biodiversity and the global carbon cycle. One of the world's largest remaining areas of tropical forest is located in Papua New Guinea. Here we show that change in its extent and condition has occurred to a greater extent than previously recorded. We assessed deforestation and forest degradation in Papua New Guinea by comparing a land-cover map from 1972 with a land-cover map created from nationwide high-resolution satellite imagery recorded since 2002. In 2002 there were 28,251,967 ha of tropical rain forest. Between 1972 and 2002, a net 15 percent of Papua New Guinea's tropical forests were cleared and 8.8 percent were degraded through logging. The drivers of forest change have been concentrated within the accessible forest estate where a net 36 percent were degraded or deforested through both forestry and nonforestry processes. Since 1972, 13 percent of upper montane forests have also been lost. We estimate that over the period 1990,2002, overall rates of change generally increased and varied between 0.8 and 1.8 percent/yr, while rates in commercially accessible forest have been far higher,having varied between 1.1 and 3.4 percent/yr. These rates are far higher than those reported by the FAO over the same period. We conclude that rapid and substantial forest change has occurred in Papua New Guinea, with the major drivers being logging in the lowland forests and subsistence agriculture throughout the country with comparatively minor contributions from forest fires, plantation establishment, and mining. RESUMEN Sopos long kisim gutpela save long senis i kamak long tropics em i wanpela bik pela samting long wanem, bikpela bus em wanpela hap we wok konsevason na carbon cycle bai inap kirapim gutpela wok. Insait long olgeta hap long world, PNG em wanpela hap we bikpela bus em i stap yet. Insait long dispela wok mipela soim olsem bikpela senis em i kamap long insait long bikpela bus na long hamas bikpela bus yumi gat. Nogat wanpela kain wok painimaut emi painim dispela senis bipo. Mipela lukluk gut long we olgeta bikpela bus i raus na we bus i kisim bagarap insait long, yia 1972 i kamap inap long yia 2002. Long yia 1972 mipela i usim map ol i kolim land cover map na long yia 2002 mipela lukluk long olgeta PNG high-resolution satellite imagery. Long yia 2002, 28,251,967 hectares bikpela bus i stap insait long Papua New Guinea. Long namel long 1972 igo inap long 2002, Papua New Guinea i lusim 15 percent long algeta bipela bus belong en. Insait long dispela 15 percent, 8.8 percent em i kamap bikos ol lain i katim diwai long salim. As bilong senisim bikela bus emi stap long ples we igat bikpela diwai long katim. Insait long dispela hap yumi lusim 36 percent, sampela we yumi inap long salim, tasol narapela emi bikos yumi rausim bus long wokim gaden or narapela kainkain pasin yumi wokim. Long 1972 i kamap inap long yia 2002, yumi lusim 13 percent long bikpela bus raonim ol bikpela maunten. Mipela painim olsem, long yia 1990 igo inap long yia 2002, long algeta kantri kain senis i wok long kamap bikpla. Senis istap insait long 0.8 igo inap long 1.8 percent long wan wan yia, tasol insait long wan wan liklik hap some pela i kisim bikpela senis, na ol narapela ino tumas. Long ol hap igat gutpela diwai long katim, senis i stat long 1.1 percent igo inap 3.4 percent. Dispela senis em i winim estimates we ol lain FAO i bin tokaut long em bipo. Long dispela wok painimaut, mipela iken tok olsem, as bilong dispela bikpela senis emi kamap long wanem ol i rausim na bagarapim bikpela bus. Dispela asua i kamap taim yumi rausim planti diwai tumas long salim na sampela taim yumi katim bus long wokim garden. Sampela taim bikpela paia tu i save kukim bikpela bus. [source] Estimating soil carbon fluxes following land-cover change: a test of some critical assumptions for a region in Costa RicaGLOBAL CHANGE BIOLOGY, Issue 2 2004Jennifer S. Powers Abstract Changes in soil carbon storage that accompany land-cover change may have significant effects on the global carbon cycle. The objective of this work was to examine how assumptions about preconversion soil C storage and the effects of land-cover change influence estimates of regional soil C storage. We applied three models of land-cover change effects to two maps of preconversion soil C in a 140 000 ha area of northeastern Costa Rica. One preconversion soil C map was generated using values assigned to tropical wet forest from the literature, the second used values obtained from extensive field sampling. The first model of land-cover change effects used values that are typically applied in global assessments, the second and third models used field data but differed in how the data were aggregated (one was based on land-cover transitions and one was based on terrain attributes). Changes in regional soil C storage were estimated for each combination of model and preconversion soil C for three time periods defined by geo-referenced land-cover maps. The estimated regional soil C under forest vegetation (to 0.3 m) was higher in the map based on field data (10.03 Tg C) than in the map based on literature data (8.90 Tg C), although the range of values derived from propagating estimation errors was large (7.67,12.40 Tg C). Regional soil C storage declined through time due to forest clearing for pasture and crops. Estimated CO2 fluxes depended more on the model of land-cover change effects than on preconversion soil C. Cumulative soil C losses (1950,1996) under the literature model of land-cover effects exceeded estimates based on field data by factors of 3.8,8.0. In order to better constrain regional and global-scale assessments of carbon fluxes from soils in the tropics, future research should focus on methods for extrapolating regional-scale constraints on soil C dynamics to larger spatial and temporal scales. [source] Habitat heterogeneity overrides the species,area relationshipJOURNAL OF BIOGEOGRAPHY, Issue 4 2008András Báldi Abstract Aim, The most obvious, although not exclusive, explanation for the increase of species richness with increasing sample area (the species,area relationship) is that species richness is ultimately linked to area-based increases in habitat heterogeneity. The aim of this paper is to examine the relative importance of area and habitat heterogeneity in determining species richness in nature reserves. Specifically, the work tests the hypothesis that species,area relationships are not positive if habitat heterogeneity does not increase with area. Location, Sixteen nature reserves (area range 89,11,030 ha) in central Hungary. Methods, Four-year faunistic inventories were conducted in the reserves involving c. 70 fieldworkers and 65 taxonomists. CORINE 50,000 land-cover maps were used for calculating the heterogeneity of the reserve landscape (number of habitat types, number of habitat patches and total length of edges). Results, Large reserves were less heterogeneous than small reserves, probably because large reserves were established in large blocks of unproductive land whereas small reserves tended to be in more fertile land. In total, 3975 arthropod species were included in the analysis. The slope of the species,area relationship was positive only for Neuroptera and Trichoptera. There was no significant relationship in the other nine taxa examined (Collembola, Acari, Orthoptera, Thysanoptera, Coleoptera, Araneae, Diplopoda, Chilopoda, Diptera). The density (number of species ha,1) of all species, however, showed a positive correlation with heterogeneity. Main conclusions, The general lack of fit of species,area relationships in this study is inconsistent with most previous published studies. Importantly, and unlike many other studies, habitat heterogeneity was not correlated with reserve area in the studied system. In the absence of this source of covariation, stronger relationships were identified that suggested a fundamental link between species richness and habitat heterogeneity. The results indicate that habitat heterogeneity rather than area per se is the most important predictor of species richness in the studied system. [source] | |||||||||||||