Showing papers in "International Journal of Remote Sensing in 2002"

An assessment of support vector machines for land cover classification

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

Derivation of a tasselled cap transformation based on Landsat 7 at-satellite reflectance

Abstract: A new tasselled cap transformation based on Landsat 7 at-satellite reflectance was developed. This transformation is most appropriate for regional applications where atmospheric correction is not feasible. The brightness, greenness and wetness of the derived transformation collectively explained over 97% of the spectral variance of the individual scenes used in this study.

Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/topographic correction

Abstract: A method for the radiometric correction of wide field-of-view airborne imagery has been developed that accounts for the angular dependence of the path radiance and atmospheric transmittance functions to remove atmospheric and topographic effects. The first part of processing is the parametric geocoding of the scene to obtain a geocoded, orthorectified image and the view geometry (scan and azimuth angles) for each pixel as described in part 1 of this jointly submitted paper. The second part of the processing performs the combined atmospheric/ topographic correction. It uses a database of look-up tables of the atmospheric correction functions (path radiance, atmospheric transmittance, direct and diffuse solar flux) calculated with a radiative transfer code. Additionally, the terrain shape obtained from a digital elevation model is taken into account. The issues of the database size and accuracy requirements are critically discussed. The method supports all common types of imaging airborne optical instrument...

Land surface temperature and emissivity estimation from passive sensor data: Theory and practice-current trends

Abstract: Land surface temperature (LST) and emissivity for large areas can only be derived from surface-leaving radiation measured by satellite sensors. These measurements represent the integrated effect of the surface and are, thus, for many applications, superior to point measurements on the ground, e.g. in Earth's radiation budget and climate change detection. Over the years, a substantial amount of research was dedicated to the estimation of LST and emissivity from passive sensor data. This article provides the theoretical basis and gives an overview of the current status of this research. Sensors operating in the visible, infrared and microwave range onboard various meteorological satellites are considered, e.g. Meteosat-MVIRI, NOAA-AVHRR, ERS-ATSR, Terra-MODIS, Terra-ASTER and DMSP-SSM/I. Atmospheric effects on measured brightness temperatures are described and atmospheric corrections using radiative transfer models (RTM) are explained. The substitution of RTM with neural networks (NN) for faster fo...

Using a time series of satellite imagery to detect land use and land cover changes in the Atlanta, Georgia metropolitan area

Abstract: A time series of Landsat MSS and TM images was used to extract land use/cover change data of the Atlanta, Georgia metropolitan area in the United States over the past 25 years as a component of Project ATLANTA (ATlanta Land-use ANalysis: Temperature and Air-quality). ATLANTA is funded by NASA EOS Interdisciplinary Science (IDS) program, which has the objective of modelling the impact of land use/cover change on temperature and air quality in Atlanta. This paper describes a suite of techniques that have been used to develop an operational approach, which will ensure high accuracy and compatibility in image classification from the satellite images of different resolutions and varying quality. These techniques include radiometric normalization to establish a common radiometric response among multi-date/multi-sensor data, an unsupervised image classification approach using image clustering and cluster labelling, a GIS-based image spatial reclassification procedure to deal with classification errors caused by ...

Monitoring land-use change in the Pearl River Delta using Landsat TM

Abstract: The Pearl River Delta in the People's Republic ofChina is experiencing rapid rates of economic growth. Government directives in the late 1970s and early 1980s spurred economic development that has led to widespread land conversion. In this study, we monitor land-use through a nested hierarchy of land-cover. Change vectors of Tasseled Cap brightness, greenness and wetness of Landsat Thematic Mapper (TM) images are combined with the brightness, greenness, wetness values from the initial date of imagery to map four stable classes and e ve changes classes. Most of the land-use change is conversion from agricultural land to urban areas. Results indicate that urban areas have increased by more than 300% between 1988 and 1996. Field assessments cone rm a high overall accuracy of the land-use change map (93.5%) and support the use of change vectors and multidate Landsat TM imagery to monitor land-use change. Results cone rm the importance of eeld-based accuracy assessment to identify problems in a land-use map and to improve area estimates for each class.

A remote sensing study of the urban heat island of Houston, Texas

Abstract: Radiative surface temperature maps of Houston, Texas were derived from satellite sensor data acquired at approximately 0400 LST on 27 separate occasions over a two-year period. Urban-rural temperature differences were determined for 21 of these cases by modelling the urban heat island as a twodimensional Gaussian surface superimposed on a planar rural background. The purpose of this study was to characterise the complete urban heat island in magnitude and spatial extent without the use of in situ measurements and to determine whether a correlation exists between heat island magnitude and rural temperature. The urban heat island magnitude was found to be inversely correlated with rural temperature, while the spatial extent was found to be independent of both heat island magnitude and rural temperature.

Spectral unmixing of vegetation, soil and dry carbon cover in arid regions: comparing multispectral and hyperspectral observations

Abstract: Remote measurements of the fractional cover of photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV) and bare soil are critical to understanding climate and land-use controls over the functional properties of arid and semi-arid ecosystems. Spectral mixture analysis is a method employed to estimate PV, NPV and bare soil extent from multispectral and hyperspectral imagery. To date, no studies have systematically compared multispectral and hyperspectral sampling schemes for quantifying PV, NPV and bare soil covers using spectral mixture models. We tested the accuracy and precision of spectral mixture analysis in arid shrubland and grassland sites of the Chihuahuan Desert, New Mexico, USA using the NASA Airborne Visible and Infrared Imaging Spectrometer (AVIRIS). A general, probabilistic spectral mixture model, Auto-MCU, was developed that allows for automated sub-pixel cover analysis using any number or combination of optical wavelength samples. The model was tested with five different hyperspe...

Mapping of several soil properties using DAIS-7915 hyperspectral scanner data - a case study over clayey soils in Israel

Abstract: The data acquired from the hyperspectral airborne sensor DAIS-7915 over Izrael Valley in northern Israel was processed to yield quantitative soil properties maps of organic matter, soil field moisture, soil saturated moisture, and soil salinity. The method adopted for this purpose was the Visible and Near Infrared Analysis (VNIRA) approach, which yields an empirical model for predicting the soil property in question from both wet chemistry and spectral information of a representative set of samples (calibration set). Based on spectral laboratory data that show a significant capability to predict the above soil properties and populations using the VNIRA strategy, the next step was to examine this feasibility under a hyperspectral remote sensing (HSR) domain. After atmospherically rectifying the DAIS-7915 data and omitting noisy bands, the VNIRA routine was performed to yield a prediction equation model for each property, using the reflectance image data. Applying this equation on a pixel-bypixel basis reve...

GIS-based Landslide Hazard Zonation in the Bhagirathi (Ganga) Valley, Himalayas

Abstract: Landslides cause widespread damage in the Himalayas. Landslide Hazard Zonation is important to take quick and safe mitigation measures and make strategic planning for the future. A part of the Bhagirathi Valley in the Garhwal Himalaya was selected for landslide hazard zonation. The study utilized different types of data including Survey of India topographic maps, geological (lithological and structural) maps, IRS-1B and-1D multispectral and PAN satellite sensor data and field observations. The processing of multi-geodatasets was carried out in a raster GIS environment. The various data layers generated and co-registered were: landuse/landcover, buffer map of thrusts, buffer map of photo-lineaments, lithology, buffer map of drainage, slope angle and relative relief. Data integration was carried out using the ordinal scale (qualitative) relative weighting rating technique to give a Landslide Hazard Index (LHI) value. The breaks in the LHI frequency diagram were used to delineate various landslide hazard zon...

Integration of remote sensing data and GIS for accurate mapping of flooded areas

Abstract: This paper describes a synergetic use of satellite radar images and ancillary information to detect flooded areas at their peak and evaluates its potential with mapping. The procedure was tested on the catastrophic flood that occurred in Regione Piemonte in Italy in November 1994. Two ERS-1 synthetic aperture radar (SAR) images were processed, one acquired one month before the flood and the other acquired three days after the event. Visual interpretation and two different thresholding techniques were performed. The flood map derived shows only a small fraction (20%) of the actually flooded lands because of the time delay between the flood peak and the satellite overpass. To overcome this limitation, the authors developed a new procedure to estimate the flooded area at the peak time by integrating the flooded area from SAR imagery with digital topographic data from a GIS technique. This method allowed inundated areas covering 96.7% of the flooded area officially recorded by the local government to be mappe...

Assessment of different spectral indices in the red-near-infrared spectral domain for burned land discrimination

Abstract: A new spectral index named Burned Area Index (BAI), specifically designed for burned land discrimination in the red-near-infrared spectral domain, was tested on multitemporal sets of Landsat Thematic Mapper (TM) and NOAA Advanced Very High Resolution Radiometer (AVHRR) images. The utility of BAI for burned land discrimination was assessed against other widely used spectral vegetation indices: Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and Global Environmental Monitoring Index (GEMI). BAI provided the highest discrimination ability among the indices tested. It also showed a high variability within scorched areas, which reduced the average normalized distances with respect to other indices. A source of potential confusion between burned land areas and low-reflectance targets, such as water bodies and cloud shadows, was identified. Since BAI was designed to emphasize the charcoal signal in post-fire images, this index was highly dependent on the temporal permanence o...

Global correlation analysis for NDVI and climatic variables and NDVI trends: 1982-1990

Abstract: The relationship between the Normalized Difference Vegetation Index (NDVI) and climatic variables was analysed on a global scale using the Pathfinder AVHRR Land NDVI data set, and observed climate data for the period 1982-1990. A significant correlation between interannual NDVI and temperature variation was recognized in the northern mid- to high latitude areas between spring and autumn. A significant correlation was also identified between the NDVI, temperature and precipitation in northern and southern semiarid regions. A comparison of global NDVI trends show that NDVI increases in the northern mid- and high latitudinal zones are related to temperature rise, and NDVI decreases in southern semiarid regions are due to a precipitation decrease in the survey period. Although the cause of NDVI increases in the equatorial regions remains unclear, the combined effects of forest regrowth, deforestation and fertilization may impact on the NDVI trend.

Monitoring the composition of urban environments based on the vegetation-impervious surface-soil (VIS) model by subpixel analysis techniques

Abstract: The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour l'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Seve...

Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data

Abstract: A unique physical feature of paddy rice fields is that rice is grown on flooded soil. During the period of flooding and rice transplanting, there is a large proportion of surface water in a land surface consisting of water, vegetation and soils. The VEGETATION (VGT) sensor has four spectral bands that are equivalent to spectral bands of Landsat TM, and its mid-infrared spectral band is very sensitive to soil moisture and plant canopy water content. In this study we evaluated a VGT-derived normalized difference water index (NDWI VGT =(B3-MIR)/ (B3+MIR)) for describing temporal and spatial dynamics of surface moisture. Twenty-seven 10-day composites (VGT- S10) from 1 March to 30 November 1999 were acquired and analysed for a study area (175 km by 165 km) in eastern Jiangsu Province, China, where a winter wheat and paddy rice double cropping system dominates the landscape. We compared the temporal dynamics and spatial patterns of normalized difference vegetation index (NDVI VGT ) and NDWI VGT . The NDWI VGT ...

Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research

Abstract: Atmospheric correction is an important preprocessing step required in many remote sensing applications. The authors are engaged in the project 'Human Dimensions of Amazonia: Forest Regeneration and Landscape Structure' in NASA/INPE's Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) programme. This project requires use of corrected Landsat TM data since research foci integrate ground-based data and TM to: (1) measure and model biomass; (2) classify multiple stages of secondary succession; (3) model land cover/land use changes; and (4) derive spectral signatures consistent across different study areas. The 30+ scenes of TM data are historic and lack detailed atmospheric data needed by physically-based atmospheric correction models such as 6S (Second Simulation of the Satellite Signal in the Solar Spectrum). Imagebased DOS models are based on image measurements and explored in this article for application to LBA study areas. Two methods using theoretical spectral radiance and image acquisition d...

Geo-atmospheric processing of airborne imaging spectrometry data. Part 1: Parametric orthorectification

Abstract: An operational orthorectification solution in support of the combined geometric and radiometric processing of currently available imaging spectrometry data is presented. The described parametric geocoding procedure (PARGE) strictly considers the aircraft and terrain geometry parameters and uses a forward transformation algorithm to create orthorectified imaging spectrometry cubes. The implementation principles, the auxiliary data calibration strategies, and the workflow of the currently applied processor are discussed. The major error sources of the approach are identified, and possibilities are shown how to make the most out of the available auxiliary data Inertial Navigation System/Global Positioning System (INS/GPS) parameters. Results on HyMap and AVIRIS imaging spectrometry data show an absolute accuracy in the range of 1-3 pixels for this kind of imagery. The combination of PARGE with an atmospheric correction procedure is shown in part 2 to this paper. The depicted geo-atmospheric workflow is propo...

A five channel chlorophyll concentration algorithm applied to SeaWiFS data processed by SeaDAS in coastal waters

Abstract: Chlorophyll-a concentration derived from the Sea-viewing Wide Fieldof-view Sensor (SeaWiFS) after applying the current SeaWiFS Data Analysis System (SeaDAS) processing tools appears to be higher than reality in coastal areas, particularly from late summer to early spring when optical properties of water are dominated by yellow substances and suspended matter. As a complement to the SeaWiFS standard procedure addressing clear water, empirical algorithms can bring immediate progress for observing the coastal domain. This paper proposes to modify the SeaWiFS Ocean Colour 4 band algorithm (OC4) by including the 412 and 555 channels. The effect of the suspended matter on the ratios used as inputs in OC4 is revealed by the 555 channel whereas the atmospheric over-correction and the absorption by yellow substances are related to the 412 channel. Based on a dataset located in the English Channel and on the continental shelf of the Bay of Biscay, a parametrization of the relationship between the OC4 ratio and the ...

An efficient method for mapping flood extent in a coastal floodplain using Landsat TM and DEM data

Abstract: An efficient and economical method for mapping flooding extent in a coastal floodplain is described. This method was based on the reflectance features of water versus non-water targets on a pair of Landsat 7 Thematic Mapper (TM) images (before and during the flood event), as well as modelling inundation using Digital Elevation Model (DEM) data. Using limited ground observation, most flooded and non-flooded areas derived from this analysis were verified. Utilizing only TM data, the total flooded areas in Pitt County, North Carolina on 30 September 1999 was 237.9 km 2 or 14.0% of the total county area. This number could be low due to the underestimation of the flooded areas beneath dense vegetation canopies. To further investigate this underestimation, a subset of the area covering the four central topographic quadrangles, the Greenville area, in Pitt County was selected. Through addition of the DEM data into the flood mapping analysis of the Greenville area revealed that the total flooded area was 98.6 km ...

Analytical algorithms for lake water TSM estimation for retrospective analyses of TM and SPOT sensor data

Abstract: Suspended matter in inland waters is related to total primary production and fluxes of heavy metals and micropollutants such as PCBs. Synoptic information on suspended matter cannot be obtained from an in situ monitoring network since suspended matter is a spatially inhomogeneous parameter. This problem can be solved by the integrated use of remote sensing data, in situ data and water quality models. To enable retrospective model and remote sensing data comparison of suspended matter concentration and distribution, a methodology is required for processing satellite images that is independent of in situ measurements. Analytical optical modelling, based on knowledge of the in situ inherent optical properties, leads to reliable multi-temporal algorithms for estimating suspended matter concentration in lakes for the data from the SPOT and Landsat TM sensors. This methodology allows multi-temporal, multi-site and multi-instrument comparison of TSM maps derived from satellite imagery. This means that satellite ...

Estimation of fuel moisture content from multitemporal analysis of Landsat Thematic Mapper reflectance data: applications in fire danger assessment

Abstract: The objective of this paper was to define indices based on reflectance measurements performed by the Landsat Thematic Mapper (TM) sensor for estimating water content of live Mediterranean fuels for fire danger estimation. Seven Landsat TM images were processed and correlated with fuel moisture content (FMC) of several live species of Mediterranean grassland and shrubland. Raw bands were converted to reflectances, and several indices potentially related to water content were calculated from them. Pearson r correlation coefficients and linear regression analysis were computed in order to estimate FMC. Those indices based on the short wave infrared bands (SWIR: 1.4-2.5 w m) and on the contrast between this band and the near-infrared band offered the best estimations. For grassland, the integral of visible and SWIR bands provided the highest correlation, but also raw reflectances and Normalized Difference Vegetation Indices (NDVIs) provide significant r values ( r 2 above 0.8). For shrub species, indices that...

Urban built-up land change detection with road density and spectral information from multi-temporal Landsat TM data

Abstract: In this article, Landsat TM images acquired during the same season from both 1984 and 1997 were analysed for urban built-up land change detection in Beijing, China, where great changes have taken place during the recent decades. To reduce the spectral confusion between urban 'built-up' and rural 'non built-up' land cover categories, we propose a new structural method based on road density combined with spectral bands for change detection. The road density represents one type of structural information while the multiple Landsat TM bands represent spectral information. Road density maps for both dates were produced using a gradient direction profile analysis (GDPA) algorithm and then integrated with spectral bands. Results from the spectral-structural postclassification comparison (SSPCC) and spectral-structural image differencing (SSID) methods were evaluated and compared with spectral-only change detection methods. The proposed SSPCC method greatly reduced spectral confusion and increased the accuracy of ...

Wheat yield estimates using multi-temporal NDVI satellite imagery

Abstract: We examined seasonal growth profiles developed from AVHRR-NDVI for estimating wheat yield at regional and farm scales in Montana for the years 1989-1997. Both regions and farms showed strong relationships between wheat yields and integrated NDVI over the entire growing season, and with late-season NDVI parameters. The use of AVHRR-NDVI growth profiles at the regional level provided the strongest yield estimates. At the farm scale, the spatial resolution (1 km 2 ) limited the certainty for accurate portrayal of field locations. However, our models provide a basis for further examination of time-series satellite data.

Vegetation and soil lines in visible spectral space: a concept and technique for remote estimation of vegetation fraction

Abstract: The goal of this study is to investigate the information content of reflectance spectra of crops in the visible and near infrared range of the spectrum and develop a technique for remote estimation of vegetation fraction ( VF ). For four wheat species with VF =100% in a wide range of pigment contents and compositions, a high degree of covariance was found for paired reflectances ( R ) at 550 nm versus 700 nm ( R 550 versus R 700) and 500 nm versus 670 nm ( R 500 versus R 670). Both relationships, defined as 'vegetation lines', were linear with determination coefficients r 2 >0.9 and the plotted points were tightly clustered. Using the same coordinates to plot reflectances for a variety of soils, a high degree of covariance ( r 2 >0.94) and a distinct 'soil line' were found. The vegetation and soil lines define a two-dimensional spectral construct within which canopy reflectances, regardless of VF, may be located. Based on these optical properties of vegetation and soils, an attempt was made to estimate VF...

Space-time dynamics of deforestation in Brazilian Amazônia

Abstract: Deforestation maps derived from Landsat Multi-Spectral Scanner (MSS) and Thematic Mapper (TM) imagery were used to analyse spatial patterns of deforestation in the 1970s and the 1991-1997 period in Brazilian Legal Amazonia. Nearly 90% of the deforestation has occurred within 100 km from major roads established under federal development programmes. Clearings larger than 50 ha and 200 ha accounted, respectively, for 74% and 50% of the total deforestation in the 1991-1997 period. Results show that more intense deforestation has been concentrated over some regions, leading to the continuous enlargement of forest clearings and contributing to aggravate deforestation impacts in such areas.

Using remote sensing and GIS to analyse land cover change and its impacts on regional sustainable development

Abstract: Policy and decision making in the context of sustainable development requires rapid, effective and efficient access to and integration of appropriate current information from a wide range of sources and disciplines, including land cover dynamic information derived from remotely sensed data. The analysis of data from high spatial resolution satellite sensors has potential in land cover monitoring. In this paper, a post-classification method is used to detect land cover change from multi-temporal satellite data, and particular attention is given to the selection of an appropriate method for land cover classification. The use of a Geographic Information System (GIS) allows further spatial analysis of the data derived from remotely sensed images and analysis of the impact of land cover change on regional sustainable development. The satellite-derived data used in this study are Thematic Mapper (TM) data acquired by Landsat-5 on 14 May 1985, 20 May 1987, 26 April 1990 and 20 May 1993 in Ansan City, Korea. The ...

Derivation of the red edge index using the MERIS standard band setting

Abstract: Within ESA's Earth Observation programme, the Medium Resolution Imaging Spectrometer (MERIS) is one of the payload components of the European polar platform ENVISAT-1. MERIS will be operated with a standard band setting of 15 bands. The objective of this paper was to study whether the vegetation red edge index can be derived from the MERIS standard band setting. This red edge provides useful information on the physiological status of the vegetation. Two different data sets are explored for simulating the red edge using MERIS spectral bands. Results show that the maximum first derivative and a three-point Lagrangian technique are not appropriate measures for the red edge index. A 'linear method', estimating the inflexion point as the reflectance midpoint between the NIR plateau and the red minimum, is a more robust method. Results also show that the MERIS bands at 665, 705, 753.75 and 775 nm can be used for applying the linear method for red edge index estimation. However, since the band at 753.75 nm is lo...

Interannual variability of NDVI and species richness in Kenya

Abstract: Ecologists have long recognized the spatial variability of species richness. In an attempt to identify the factors responsible for this variability, ecologists have traditionally used environmental data obtained from sparse point samples (such as meteorological stations). However, remotely sensed data also provide a means of estimating relevant environmental factors and thereby improving predictions of species richness. The Advanced Very High Resolution Radiometer Normalized Difference Vegetation Index (AVHRR NDVI) has been shown to be related to net primary productivity (NPP) and actual evapotranspiration (AET) for many vegetation types. NPP and AET have frequently been used as surrogate measures for species richness. Local spatial variability of NPP and AET, indicating habitat heterogeneity, is hypothesized as another influence on species richness. We examined the relationship between interannual maximum NDVI parameters and species richness of vascular plants and mammals. The study was done at a landsca...

A reflectance band ratio used to estimate suspended matter concentrations in sediment-dominated coastal waters

Abstract: This letter presents an empirical relationship that may be used to estimate the suspended particulate matter concentrations in highly turbid waters from remote sensing reflectance measurements. Numerous measurements carried out in the Gironde estuarine waters (France) in 2000 and 2001 are presented and analysed. It was observed that the near-infrared (850 nm) reflectance was weakly correlated with the total suspended matter concentration ( TSMc ) measured in surface waters. A strong correlation ( r =0.91) was obtained between the ratio of the near-infrared and visible (550 nm) reflectance and TSMc, which could provide an accurate calibration curve for data from Systeme Probatoire de l'Observation de la Terre (SPOT), Landsat and Indian Remote Sensing (IRS) satellite sensors. The reflectance ratio reduced the effects of changes in illumination conditions and sediment type (grain-size, refractive index). The calibration function obtained, successfully applied to the Gironde, should be applied in other sedime...

Effects of minimum mapping unit on land cover data spatial configuration and composition

Abstract: A key issue when generating a land cover map from remotely sensed data is the selection of the minimum mapping unit (MMU) to be employed, which determines the extent of detail contained in the map. This study analyses the effects of MMU in land cover spatial configuration and composition, by using simulated landscape thematic patterns generated by the Modified Random Clusters method. This approach allows a detailed control of the different factors influencing landscape metrics behaviour, as well as taking into account a wide range of land cover pattern possibilities. Land cover classes that are sparse and fragmented can be considerably misrepresented in the final map when increasing MMU, while the classes that occupy a large percentage of map area tend to become more dominant. Mean Patch Size and Number of Patches are very poor indicators of pattern fragmentation in this context. In contrast, Landscape Division (LD) and related indices (Splitting Index and Effective Mesh Size) are clearly suitable for com...