Land Cover Properties Research Articles

Stochastic modeling of flood peaks using the generalized extreme value distribution

The generalized extreme value (GEV) distribution is a standard tool for modeling flood peaks, both in annual maximum series (AMS) and in partial duration series (PDS). In this paper, combined maximum likelihood estimation (MLE) and L moment (LMOM) procedures are developed for estimating location, shape, and scale parameters of the GEV distribution. Particular attention is given to estimation of the shape parameter, which determines the “thickness” of the upper tail of the flood frequency distribution. Mixed MLE–LMOM methods avoid problems with both MLE (estimator variance) and LMOM (estimator bias) estimators of the shape parameter. The mixed MLE–LMOM procedure is extended to use the two largest flood peaks in a year. This extension is developed in a PDS framework. Estimation procedures are applied to flood peak observations from 104 central Appalachian basins. The estimated values of the shape parameter for the central Appalachian basins are more negative than has been considered physically reasonable, independent of the estimation procedure that is used. Twenty‐eight percent of mixed method estimators of the shape parameter have values less than −0.5, implying that the moments of order 2 and above are infinite. The estimated shape parameters for the central Appalachian basins do not depend on basin morphological parameters (such as drainage area) or land cover properties (such as percent urban, forest, or agricultural land use). Estimated values of the location and scale parameters for the central Appalachian watersheds correspond well with GEV‐based simple scaling theory. Estimated values of the shape parameter for central Appalachian watersheds are shown to differ markedly from those of southern Appalachian watersheds and the difference is shown to be linked to contrasting properties of extreme floods. To conclude the paper, analyses of mixture distribution models are presented to address the question of whether flood peaks really have extreme “heavy tail” behavior or whether the GEV distribution is not the appropriate model for flood peaks.

Quantitative mapping of soil types based on regression kriging of taxonomic distances with landform and land cover attributes

Nowadays, French soil scientists tend to gather new and existing soil data into a common database. The use of this database potentially allows for resolving environmental issues, largely through soil mapping. The purpose of this study is to present a methodology for mapping soil types illustrated by typical observations in the soil database, in this case from the La Rochelle area on the French Mid-Atlantic Coast. The main hypothesis underlying the method is that soil types result from environmental factors such as landform, parent material, and land cover. The method can be divided into four stages. The first step is to construct a local soil type classification from the database by a two-stage continuous classification procedure. The result of this procedure is that at each observation point, the soil is described by a vector of taxonomic distances to each of k centroidal soil types. In the example given, k=18. The second step involves fitting soil–environment equations, one for each centroidal soil type, by regressing taxonomic distances on layers of multivariate environmental data observed on a fine 20-m grid, by multiple linear regression. In this case, the layers are terrain attributes derived from a digital elevation model and land cover attributes derived from three bands of a SPOT image. The third step is to predict k maps or raster GIS layers representing taxonomic distances to soil types on the 20-m grid, using the soil–environment equations and the kriging of the residuals from the regressions. This results in many potential maps: a summary map depicting the nearest centroidal soil type (the soil type for which the taxonomic distance is least) at each location is possibly the most useful, and another one representing the minimum taxonomic distance which, if considered too large, might suggest locations for further field survey to refine the soil types. A map of standard errors of the kriged taxonomic distance residuals to the nearest centroidal soil type can be made to indicate spatial uncertainty. Continuous fuzzy membership maps can also be constructed from the distances. The fourth step involves validation with an independent soil data set allowing discovery of the nature of the actual prediction errors. Thirty-eight percent of sites in a validation sample of 1234 sites was unequivocally validated, 23% was equivocally validated, and the remainder was predicted wrongly by the method.

NASA creates global archive of ortho‐rectified Landsat data

High spatial resolution imagery from the Landsat satellites has provided us with the longest record of terrestrial observations since 1972. Recognizing the need to provide high‐resolution satellite data to the scientific community, NASA's Commercial Remote Sensing Program Office has been working to assemble the first wall‐to‐wall global coverage of ortho‐rectified Landsat Thematic Mapper and Multi Spectral Scanner data to support scientific studies. This database is expected to be of great value to researchers studying a variety of problems.The need for high‐resolution data sets arises from the low spatial autocorrelation of land surface properties [Townshend and Justice, 1988; Townshend and Justice, 1990]. Even in areas with near‐natural land cover, spatial variability can exist at the finest scales due to local terrain variability and associated microclimatic influences on vegetation types and associations. Human‐induced changes, such as deforestation, are the source of many of the finest‐scale alterations and can significantly drive global change. Currently, we have very poor data on where land cover is being changed, what changes are occurring, and the land cover properties of the altered land [Townshend et al., 1991].

Remote sensing of the land surface for studies of global change: Models — algorithms — experiments

The ISLSCP Workshop was held in Columbia, Maryland, 23–26 June 1992 with over 240 scientists and science managers attending. The goal was to assess the progress of the last decade in the areas of modeling, satellite data algorithm development, and field experiments. This article includes: 1. 1. A review of the state and direction of biosphere-atmosphere model development and an assessment of the data needs of the models. Models covering a large range of timescales were considered: energy-water-carbon (seconds to seasons); carbon cycles and biogeochemistry (days to years); and ecological structure and function (years to millennia). 2. 2. A reference to current satellite data algorithms and other global data sources. The areas covered in the workshop were: near-surface meteorology, surface radiation budget, precipitation, runoff, snow and ice, soils and soil moisture, and land cover type and land cover attributes. These are discussed in detail in other articles in this issue. 3. 3. A review of completed and planned major field experiments. The major experiments of the last decade are summarized and the lessons noted. The participating scientists agreed on the need to rapidly assemble and circulate global data sets of variables and parameters required to initialize, force, and validate the global biosphere-atmosphere models. A prioritized list of data sets required to meet this need is set out and discussed. Lastly, initiatives taken by ISLSCP to satisfy these requirements are reviewed: Initiative I. Immediate Generation of High Priority Global Data Sets Some essential global data sets are to be put together within 2 years and released to the community by mid-1994. These data sets will be mapped to a common spatial resolution (1° × 1°) and will cover the period 1987–1988. 1. 1. Vegetation: Global sets of vegetation-related parameters are to be generated with a monthly time resolution. Available AVHRR data sets are to be used as the basis for this effort, and algorithms will be applied to calculate fields of cover type, phenology, FPAR, and leaf area index. These fields can then in turn be used to infer other surface parameters such as roughness, albedo, biomass, etc. 2. 2. Hydrometeorology: Global meteorological fields retrieved from numerical reanalysis will be manipulated to provide near-surface forcing data sets for temperature, humidity, windspeed, etc. Observations of precipitation, runoff, and snow cover are to be worked up into easily accessible forms. 3. 3. Radiation Budget: A closer interface with the International Satellite Cloud Climatology Project (ISCCP) and related projects will be pursued to obtain surface radiation budget components at higher spatial resolutions, as well as fields of incident PAR. 4. 4. Soils: A small project was set in place with the goal of providing a useful soil type and properties data set for use by global modelers. Initiative II: Improved, Follow-on Data Sets The data sets specified in Initiative I are to be generated within a 2-year period. However, it is clear that great improvements could be made over this first data release which must rely on preexisting data sets and robust, available algorithms. Work was started to scope out what needs to be done to produce improved versions of all the Initiative I data sets within 5 years, by mid-1997. Initiative III: Improved Communications within the Land Science Community Future discussions within ISLSCP and between ISLSCP and other bodies will focus on the need to coordinate different research thrusts within the land science community, particularly the modeling, algorithm and field experiment work.

Studies of optical and biological properties of landcover employing shuttle flights of a multispectral linear array radiometer

Studies to characterize optical and biological properties of land cover as observed from space are planned using a six channel, imaging spectroradiometer employing newly developed multispectral linear array (MLA) detector technology. These studies are to take place by mounting the radiometer on the Shuttle and observing areas with dynamic and diverse types of land cover condition. The radiometer will have 15 meter spatial resolution for four, 20 nanometer bands in the visible and near infrared and 30 meter resolution for similarily narrow bands in the shortwave infrared bands. The instrument will scan ± 45 degrees along the Shuttle orbital path. The principle objective of this experiment is to obtain observations that augment knowledge of the distribution of basic land cover types in regions that are known to be key to questions of biogeochemical cycles, energy balance and climatic change. Another key objective is to quantify the bidirectional reflectance of key land cover conditions in major portions of the visible, near infrared and shortwave infrared as they are observed from space. The initial execution of this experiment is presently scheduled for late 1987.