Land Cover Characteristics Database Research Articles

A Global Land Cover Climatology Using MODIS Data

AbstractGlobal land cover data are widely used in weather, climate, and hydrometeorological models. The Collection 5.1 Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type (MCD12Q1) product is found to have a substantial amount of interannual variability, with 40% of land pixels showing land cover change one or more times during 2001–10. This affects the global distribution of vegetation if any one year or many years of data are used, for example, to parameterize land processes in regional and global models. In this paper, a value-added global 0.5-km land cover climatology (a single representative map for 2001–10) is developed by weighting each land cover type by its corresponding confidence score for each year and using the highest-weighted land cover type in each pixel in the 2001–10 MODIS data. The climatology is validated by comparing it with the System for Terrestrial Ecosystem Parameterization database as well as additional pixels that are identified from the Google Earth proprietary software database. When compared with the data of any individual year, this climatology does not substantially alter the overall global frequencies of most land cover classes but does affect the global distribution of many land cover classes. In addition, it is validated as well as or better than the MODIS data for individual years. Also, it is based on higher-quality data and is validated better than the Global Land Cover Characteristics database, which is based on 1 year of Advanced Very High Resolution Radiometer data and represents a widely used first-generation global product.

Malaria resurgence risk in southern Europe: climate assessment in an historically endemic area of rice fields at the Mediterranean shore of Spain.

BackgroundInternational travel and immigration have been related with an increase of imported malaria cases. This fact and climate change, prolonging the period favouring vector development, require an analysis of the malaria transmission resurgence risk in areas of southern Europe. Such a study is made for the first time in Spain. The Ebro Delta historically endemic area was selected due to its rice field landscape, the presence of only one vector, Anopheles atroparvus, with densities similar to those it presented when malaria was present, in a situation which pronouncedly differs from already assessed potential resurgence areas in other Mediterranean countries, such as France and Italy, where many different Anopheles species coexist and a different vector species dominates.MethodsThe transmission risk was assessed analysing: 1) climate diagrams including the minimum temperature for Plasmodium falciparum and Plasmodium vivax development; 2) monthly evolution of the Gradient Model Risk (GMR) index, specifying transmission risk period and number of potential Plasmodium generations; 3) ecological characteristics using remote sensing images with the Eurasia Land Cover characteristics database and the monthly evolution of the Normalized Difference Vegetation Index (NDVI); 4) evaluation of A. atroparvus population dynamics.ResultsClimatological analyses and GMR index show that a transmission risk presently exists, lasting from May until September for P. falciparum, and from May until October for P. vivax. The GMR index shows that the temperature increase does not actually mean a transmission risk increase if accompanied by a precipitation decrease reducing the number of parasite generations and transmission period. Nevertheless, this limitation is offset by the artificial flooding of the rice fields. Maximum NDVI values and A. atroparvus maximum abundance correspond to months with maximum growth of the rice fields.ConclusionsThe Ebro Delta presents the ecological characteristics that favour transmission. The temperature increase has favoured a widening of the monthly potential transmission window with respect to when malaria was endemic. The combined application of modified climate diagrams and GMR index, together with spatial characterization conforms a useful tool for assessing potential areas at risk of malaria resurgence. NDVI is a good marker when dealing with a rice field area.

Statistics and characteristics of permafrost and ground-ice distribution in the Northern Hemisphere

The recently published digital version of the International Permafrost Association (IPA) Circum-Arctic Map of Permafrost and Ground Ice Conditions (the IPA map), together with ancillary data sets of the global land cover characteristics data base and the Global Land One-kilometer Base Elevation data base, are used to investigate the distribution of permafrost and ground ice in the Northern Hemisphere. Our study indicates that permafrost underlies approximately 22.79×106 km2 or 23.9% of the exposed land area of the Northern Hemisphere. Permafrost extends from 26°N in the Himalayas to 84°N in northern Greenland. Approximately 70% of the permafrost is distributed between 45 and 67°N. Generally, permafrost with high ice content (>20% by volume) and relatively thick overburden cover (>5 to 10 m) is found at high latitudes, representing approximately 8.57% of the total permafrost area, or 2.02% of the exposed land area of the Northern Hemisphere. Permafrost with low ice content (<10% by volume with either thick or thin overburden cover) occurs mainly in mountainous regions and high plateaus, representing approximately 66.5% of the total permafrost area or 15.8% of the exposed land area. Approximately 62% of the permafrost of the Northern Hemisphere is found below 500 m a.s.l. and about 10% occurs above 3000 m a.s.l. Based on the IPA map categories, the estimated volume of ground ice in the Northern Hemisphere is between 5.63 and 15.12×103 km3, corresponding to ∼2–4 cm sea level equivalent. Based on alternative assumptions, the volume of ground ice may be between 11.37 and 36.55×103 km3, which corresponds to 3-10 cm sea-level equivalent.

How well do we know northern land cover? Comparison of four global vegetation and wetland products with a new ground‐truth database for West Siberia

An unprecedented collection of 2161 geolocated, irregularly spaced field observations of land cover spanning ∼106 km2 throughout West Siberia suggests that currently available land cover classification products are remarkably poor indicators of vegetation type and water body extent in this northern wetland environment. The ground‐truth data are compared with (1) the Global Land Cover Characteristics database derived from Advanced Very High Resolution Radiometer data (GLCC.AVHRR), (2) the Global Land Cover Classification derived from Moderate Resolution Imaging Spectroradiometer data (GLCC.MODIS), (3) the Global Lakes and Wetlands Database (GLWD), and (4) the West Siberian Lowland Peatland Database (WSLPD) using: (1) all land cover categories and (2) permanent wetland and water body categories only. Overall agreement with ground observations of land cover is only 21% for the GLCC.AVHRR database and 11% for the GLCC.MODIS database. However, at a much broader scale (one degree of latitude) there is improved qualitative agreement between vegetation classes, with some notable exceptions: (1) at low latitudes (∼54°N–58°N), both the GLCC.AVHRR and GLCC.MODIS databases underestimate woody savannas in favor of croplands; (2) at midlatitudes (∼58°N–64°N), the GLCC.AVHRR database underestimates evergreen needleleaf forest in favor of mixed forest; and (3) at high latitudes (∼64°N–68°N), both the GLCC.AVHRR and GLCC.MODIS databases underestimate deciduous needleleaf forest in favor of woody savannas or open shrublands, respectively. It is clear that all four data databases significantly underestimate permanent wetlands and water bodies, although those specifically developed for this purpose (GLWD and WSPLD) perform better than the more widely used, multiclass land cover products. For permanent wetlands, agreement with our ground data is only 2% for GLCC.MODIS, 23% for GLCC.AVHRR, 45% for GLWD and 56% for WSLPD. Agreement with open water bodies is even poorer (0–5%). These results raise into question the efficacy of incorporating currently available land cover products into terrestrial ecosystem models in northern wetland environments.

The coasts of our world: Ecological, economic and social importance

We integrated the emerging information of the ecological, economic and social importance of the coasts at a global scale. We defined coastal regions to range from the continental shelf (to a depth of 200 m), the intertidal areas and adjacent land within 100 km of the coastline. We used the 1 km resolution Global Land Cover Characteristics Database and calculated the area covered by 11 different land cover classes (natural and human-altered ecosystems) within the 100 km limit [Burke, L., Kura, Y., Kasem, K., Revenga, C., Spalding, M., McAllister, D., 2001. Coastal Ecosystems. Washington DC World Resource Institute. 93 pp.]. Cover of aquatic ecosystems was calculated based on several world databases. Our results show that the coasts of the world comprise a wide variety of geomorphological characteristics of which mountainous coasts with a narrow shelf are the most abundant. Sandy shores are found on 16% of the coastal countries. The coasts are located in every weather regime and the number of biomes is equally variable. Within the 100 km limit, 72% still is covered by natural ecosystems and 28% have been altered by human activities (urban and croplands). Open shrubs and evergreen broadleaf forests are the most abundant terrestrial ecosystems. Canada has the largest area of natural and relatively well preserved terrestrial ecosystems. Indonesia and China have the largest percentages of cropland area near the shore, and Japan and the US have the largest coastal urban areas. Indonesia, Australia, Brazil, Bahamas and New Caledonia have the largest areas of aquatic ecosystems. The calculated economic value of goods and services provided by coastal ecosystems showed that altogether, coastal ecosystems contribute 77% of global ecosystem-services value calculated by Costanza et al. [Costanza, R., d'Arge, R., de Groot, R., Farber, S., Grasso, M., Hannon, B., Naeem, S., Limburg, K., Paruelo, J., O’Neill, R.V., Raskin, R., Sutton, P., ven den Belt, M., 1997. The value of the world’s ecosystem services and natural capital. Nature 387, 253–260]. According to 2003 data, 2.385 million people live within the coastal limit, which represents 41% of world global population. More than 50% of the coastal countries have from 80 to 100% of their total population within 100 km of the coastline. Twenty-one of the 33 world's megacities are found on the coast. Multivariate analyses grouped coastal countries according to their ecological, economic and social characteristics. Three gradients explained 55% of the variance: degree of conservation, ecosystem service product and demographic trends. Given the current scenario and the climate change prediction, the coastal environments will be confronting serious environmental issues that should be worked in advance, in order to achieve a sustainable development of the most valued locations of the world. Several recommendations are made.

The statistical significance test of regional climate change caused by land use and land cover variation in West China

The West Development Policy being implemented in China is causing significant land use and land cover (LULC) changes in West China. With the up-to-date satellite database of the Global Land Cover Characteristics Database (GLCCD) that characterizes the lower boundary conditions, the regional climate model RIEMS-TEA is used to simulate possible impacts of the significant LULC variation. The model was run for five continuous three-month periods from 1 June to 1 September of 1993, 1994, 1995, 1996, and 1997, and the results of the five groups are examined by means of a student l-test to identify the statistical significance of regional climate variation. The main results are: (1) The regional climate is affected by the LULC variation because the equilibrium of water and heat transfer in the air-vegetation interface is changed. (2) The integrated impact of the LULC variation on regional climate is not only limited to West China where the LULC varies, but also to some areas in the model domain where the LULC does not vary at all. (3) The East Asian monsoon system and its vertical structure are adjusted by the large scale LULC variation in western China, where the consequences are the enhancement of the westward water vapor transfer from the east oast and the relevant increase of wet-hydrostatic energy in the middle-upper atmospheric layers. (4) The ecological engineering in West China affects significantly the regional climate in Northwest China, North China and the middle-lower reaches of the Yangtze River; there are obvious effects in South, Northeast, and Southwest China, but minor effects in Tibet.

A simulation study on the eco-environmental effects of 3N Shelterbelt in North China

Based on the Global Land Cover Characteristics Database (GLCCD) generated by the U.S. Geological Survey (USGS) and University of Nebraska-Lincoln (UNL), a new land cover dataset within a domain of 14.1–49.6°N, 84.6–140.5°E is extracted. This dataset is used to identify the achievements of constructing 3N (Northeast, North and Northwest of China) Shelterbelt in North China and to update the lower boundary conditions of the mesoscale model (MM5), a widely used mesoscale meteorological model. The model is then used to simulate the regional climate effects of the 3N Shelterbelt, the largest forestation engineering in the world. The simulation shows that the construction of the 3N Shelterbelt and the corresponding land use and land cover (LULC) variations in China have changed the roughness length in the cited model domain significantly. Consequently, the surface layer wind speed, air temperature, humidity, and the precipitation are all changed. As compared with the control run without the 3N Shelterbelt, the regional climate in North China is improved shown by the decreased wind speed, increased air humidity and precipitation. The paper also stresses that, in meteorological or climatic simulations, the lower boundary conditions related to the land cover has to be updated frequently by the satellite observed database since the LULC vary fast due to the increasing world population and human activities, this is especially true in developing countries like China.

Global Forest Cover Mapping for the United Nations Food and Agriculture Organization Forest Resources Assessment 2000 Program

Abstract Many countries periodically produce national reports on the status and changes of forest resources, using statistical surveys and spatial mapping of remotely sensed data. At the global level, the Food and Agriculture Organization (FAO) of the United Nations has conducted a Forest Resources Assessment (FRA) program every 10 yr since 1980, producing statistics and analysis that give a global synopsis of forest resources in the world. For the year 2000 of the FRA program (FRA2000), a global forest cover map was produced to provide spatial context to the extensive survey. The forest cover map, produced at the U.S. Geological Survey (USGS) EROS Data Center (EDC), has five classes: closed forest, open or fragmented forest, other wooded land, other land cover, and water. The first two forested classes at the global scale were delineated using combinations of temporal compositing, modified mixture analysis, geographic stratification, and other classification techniques. The remaining three FAO classes were derived primarily from the USGS global land cover characteristics database (Loveland et al. 1999). Validated on the basis of existing reference data sets, the map is estimated to be 77% accurate for the first four classes (no reference data were available for water), and 86% accurate for the forest and nonforest classification. The final map will be published as an insert to the FAO FRA2000 report. FOR. SCI. 49(3):369–380.

The Regional Climate Effects of Replacing Farmland and Re-greening the Desertification Lands with Forest or Grass in West China

The West Development Policy being implemented in China causes significant land use and land cover (LULC) changes in West China, of which the two most important types of LULC change are replacing farmland and re-greening the desertification land with forest or grass. This paper modifies the prevailing regional climate model (RCM) by updating its lower boundary conditions with the up-to-date satellite database of the Global Land Cover Characteristics Database (GLCCD) created by the United States Geological Survey and the University of Nebraska-Lincoln. The modified RCM is used to simulate the possible regional climate changes due to the LULC variations. The preliminary results can be summarized as that the two main types of LULC variation, replacing farmland and greening the desertification lands with forest or grass in west China, will affect the regional climate mostly in northwest and north China, where the surface temperature will decrease and the precipitation will increase. The regional climate adjustments in South, Southwest China and on the Tibet Plateau are uncertain.

Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data

Researchers from the U.S. Geological Survey, University of Nebraska-Lincoln and the European Commission's Joint Research Centre, Ispra, Italy produced a 1 km resolution global land cover characteristics database for use in a wide range of continental-to global-scale environmental studies. This database provides a unique view of the broad patterns of the biogeographical and ecoclimatic diversity of the global land surface, and presents a detailed interpretation of the extent of human development. The project was carried out as an International Geosphere-Biosphere Programme, Data and Information Systems (IGBP-DIS) initiative. The IGBP DISCover global land cover product is an integral component of the global land cover database. DISCover includes 17 general land cover classes defined to meet the needs of IGBP core science projects. A formal accuracy assessment of the DISCover data layer will be completed in 1998. The 1 km global land cover database was developed through a continent-by-continent unsupervised classification of 1 km monthly Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993. Extensive post-classification stratification was necessary to resolve spectral/temporal confusion between disparate land cover types. The complete global database consists of 961 seasonal land cover regions that capture patterns of land cover, seasonality and relative primary productivity. The seasonal land cover regions were aggregated to produce seven separate land cover data sets used for global environmental modelling and assessment. The data sets include IGBP DISCover, U.S. Geological Survey Anderson System, Simple Biosphere Model, Simple Biosphere Model 2, Biosphere-Atmosphere Transfer Scheme, Olson Ecosystems and Running Global Remote Sensing Land Cover. The database also includes all digital sources that were used in the classification. The complete database can be sourced from the website: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html.

Statistics and characteristics of permafrost and ground‐ice distribution in the Northern Hemisphere1

The recently published digital version of the International Permafrost Association (IPA) Circum‐Arctic Map of Permafrost and Ground Ice Conditions (the IPA map), together with ancillary data sets of the global land cover characteristics data base and the Global Land One‐kilometer Base Elevation data base, are used to investigate the distribution of permafrost and ground ice in the Northern Hemisphere. Our study indicates that permafrost underlies approximately 22.79 × 106 km2 or 23.9% of the exposed land area of the Northern Hemisphere. Permafrost extends from 26°N in the Himalayas to 84°N in northern Greenland. Approximately 70% of the permafrost is distributed between 45°N and 67°N. Generally, permafrost with high ice content (>20% by volume) and relatively thick overburden cover (>5 to 10 m) is found at high latitudes, representing approximately 8.57% of the total permafrost area, or 2.02% of the exposed land area of the Northern Hemisphere. Permafrost with low ice content (<10% by volume with either thick or thin overburden cover) occurs mainly in mountainous regions and high plateaus, representing approximately 66.5% of the total permafrost area or 15.8% of the exposed land area. Approximately 62% of the permafrost of the Northern Hemisphere is found below 500 m a.s.l. and about 10% occurs above 3000 m a.s.l. Based on the IPA map categories, the estimated volume of ground ice in the Northern Hemisphere is between 5.63 and 15.12 × 103 km3, corresponding to ∼2–4 cm sea level equivalent. Based on alternative assumptions, the volume of ground ice may be between 11.37 and 36.55 × 103 km3, which corresponds to 3–10 cm sea‐level equivalent.

Applications of the U.S. Geological Survey's global land cover product

The U.S. Geological Survey (USGS), in partnership with several international agencies and universities, has produced a global land cover characteristics database. The land cover data were created using multitemporal analysis of advanced very high resolution radiometer satellite images in conjunction with other existing geographic data. A translation table permits the conversion of the land cover classes into several conventional land cover schemes that are used by ecosystem modelers, climate modelers, land management agencies, and other user groups. The alternative classification schemes include Global Ecosystems, the Biosphere Atmosphere Transfer Scheme, the Simple Biosphere, the USGS Anderson Level 2, and the International Geosphere Biosphere Programme. The distribution system for these data is through the World Wide Web (the web site address is: http://edcwww.cr.usgs.gov/landdaac/glcc/glcc.html) or by magnetic media upon special request The availability of the data over the World Wide Web, in conjunction with the flexible database structure, allows easy data access to a wide range of users. The web site contains a user registration form that allows analysis of the diverse applications of large-area land cover data. Currently, applications are divided among mapping (20 percent), conservation (30 percent), and modeling (35 percent).

Sensitivity of ISODATA to changes in sampling procedures and processing parameters when applied to AVHRR time-series NDV1 data

Abstract In recent years significant effort has gone into collecting, processing, and analysing normalized difference vegetation index (NDVI) data derived from the National Oceanic and Atmospheric Administration's (NOAA) 1-km advanced very high resolution radiometer (AVHRR) for environmental applications. The ISODATA clustering procedure has been employed using time-series AVHRR maximum NDVI composites to produce a land cover characteristics data base. This study examines the sensitivity of the ISODATA clustering results to changes in sampling procedures and processing parameters when applied to NOAA NDVI time-series data. The effects of varying the sampling strategy, sampling intensity, clustering parameters, and number of iterations have been evaluated. The ISODATA clustering procedure was most sensitive to variations in sampling intensity and clustering parameters.

Development and validation of AVHRR-derived regional forest cover data for the north-eastern U.S.

Abstract As part of developing the geographic information system (GIS) to support a north-eastern U.S. regional forest change modelling effort, we investigated the utility of several sources of AVHRR data in regional forest cover mapping. Single-date classified Advanced Very High Resolution Radiometer (AVHRR) imagery in combination with existing USGS Land Use/Land Cover data was used to create a forest cover database that encompassed eastern New York state and all of New England. The USGS EROS Data Center Conterminous U.S. Land Cover Characteristics database was also evaluated for comparison. Statistical analysis showed that the AVHRR-derived regional land cover datasets provided estimates of total forest area that were comparable to U.S. Forest Service county level estimates. The AVHRR imagery recorded after leaf fall appeared to enhance the discrimination of coniferous vs. deciduous forests.