Vegetation-related Parameters Research Articles

Unmanned aerial vehicle-based aerial survey of mines in Shanxi Province based on image data

Abstract Accurately monitoring the change of mine area in the mining process is beneficial to mine safety management. This paper briefly introduces the collection of remote sensing images by unmanned aerial vehicles (UAVs) and its application in measuring surface mining subsidence and surrounding vegetation in the mining area. A case study was carried out in some mining areas of Nanshan Mountain, Yuncheng City, Shanxi Province. The surface mining subsidence value and vegetation-related parameters were measured by comparing the digital elevation model and multi-spectral images collected on May 12 and June 12, 2023. The validity experiment verified that the UAV image data could be used to measure the mining subsidence and vegetation parameters. Moreover, it was found that mining underground coal could lead to significant ground subsidence and pollute the surrounding environment, reducing vegetation. The innovation of this article lies in using UAV-collected remote sensing images instead of manually collecting ground elevation data and vegetation distribution data, providing effective references for safe mining in mining areas.

A global 5 km monthly potential evapotranspiration dataset (1982–2015) estimated by the Shuttleworth–Wallace model

Abstract. As the theoretical upper bound of evapotranspiration (ET) or water use by ecosystems, potential ET (PET) has always been widely used as a variable linking a variety of disciplines, such as climatology, ecology, hydrology, and agronomy. However, substantial uncertainties exist in the current PET methods (e.g., empiric models and single-layer models) and datasets because of unrealistic configurations of land surface and unreasonable parameterizations. Therefore, this study comprehensively considered interspecific differences in various vegetation-related parameters (e.g., plant stomatal resistance and CO2 effects on stomatal resistance) to calibrate and parametrize the Shuttleworth–Wallace (SW) model for forests, shrubland, grassland, and cropland. We derived the parameters using identified daily ET observations with no water stress (i.e., PET) at 96 eddy covariance (EC) sites across the globe. Model validations suggest that the calibrated model could be transferable from known observations to any location. Based on four popular meteorological datasets, relatively realistic canopy height, time-varying land use or land cover, and the leaf area index, we generated a global 5 km ensemble mean monthly PET dataset that includes two components of potential transpiration (PT) and soil evaporation (PE) for the 1982–2015 time period. Using this new dataset, the climatological characteristics of PET partitioning and the spatiotemporal changes in PET, PE, and PT were investigated. The global mean annual PET was 1198.96 mm with PT/PET of 41 % and PE/PET of 59 %, controlled moreover by PT and PE of over 41 % and 59 % of the globe, respectively. Globally, the annual PET and PT significantly (p<0.05) increase by 1.26 and 1.27 mm yr−1 over the last 34 years, followed by a slight decrease in the annual PE. Overall, the annual PET changes over 53 % of the globe could be attributed to PT, and the rest to PE. The new PET dataset may be used by academic communities and various agencies to conduct climatological analyses, hydrological modeling, drought studies, agricultural water management, and biodiversity conservation. The dataset is available at https://doi.org/10.11888/Terre.tpdc.300193 (Sun et al., 2023).

Plant functional traits play the second fiddle to plant functional types in explaining peatland CO2 and CH4 gas exchange

Peatlands constitute a significant soil carbon (C) store, yet the C gas flux components show distinct spatial variation both between and within peatlands. Determining the controls on this variability could aid in our understanding of the response of peatlands to global changes. In this study, we assess the usefulness of different vegetation related parameters to explain spatial variation in peatland C gas flux components. We hypothesise that spatial variation is best explained by trait-based indices (similarly to other terrestrial ecosystems), and that the impact of soil physicochemical properties, such as nitrogen (N) content or water level, can be manifested through the traits. Furthermore, we expect that the spatial variability associated with each of the C gas flux components can be explained by a distinct set of traits. To address our aim, we used a successional peatland chronosequence from wet meadows to a bog, along which all variables were recorded with similar methods and under similar climatic conditions.We observed spatial variability with all measured gas fluxes, with carbon dioxide (CO2) fluxes showing significant variability between sites, while within site variability was more important for methane (CH4) fluxes. As expected, our results show that the impacts of physicochemical conditions were directed via vegetation. However, the cover of functional plant types that capture multiple traits proved to be more powerful in explaining gas flux variability compared to functional trait-based indices. Our findings imply that for future gas flux modelling purposes, rather than attempting to use individual traits - as is the ongoing trend in ecology - it might be more useful to refine plant functional groupings and ensure they are based on a set of plant traits relevant for the studied ecosystem process. This could be facilitated by the collation of a large data set of traits measured from peatlands.

Sensitivity of Surface Fluxes in the ECMWF Land Surface Model to the Remotely Sensed Leaf Area Index and Root Distribution: Evaluation with Tower Flux Data

The surface-atmosphere turbulent exchanges couple the water, energy and carbon budgets in the Earth system. The biosphere plays an important role in the evaporation process, and vegetation related parameters such as the leaf area index (LAI), vertical root distribution and stomatal resistance are poorly constrained due to sparse observations at the spatio-temporal scales at which land surface models (LSMs) operate. In this study, we use the Carbon Hydrology Tiled European Center for Medium-Range Weather Forecasts (ECMWF) Scheme for Surface Exchanges over Land (CHTESSEL) model and investigate the sensitivity of the simulated turbulent fluxes to these vegetation related parameters. Observed data from 17 FLUXNET towers were used to force and evaluate model simulations with different vegetation parameter configurations. The replacement of the current LAI climatology used by CHTESSEL, by a new high-resolution climatology, representative of the station’s location, has a small impact on the simulated fluxes. Instead, a revision of the root profile considering a uniform root distribution reduces the underestimation of evaporation during water stress conditions. Despite the limitations of using only one model and a limited number of stations, our results highlight the relevance of root distribution in controlling soil moisture stress, which is likely to be applicable to other LSMs.

Neglected but Potent Dry Forest Players: Ecological Role and Ecosystem Service Provision of Biological Soil Crusts in the Human-Modified Caatinga

Biological soil crusts (biocrusts) have been recognized as key ecological players in arid and semiarid regions at both local and global scales. They are important biodiversity components, provide critical ecosystem services, and strongly influence soil-plant relationships, and successional trajectories via facilitative, competitive, and edaphic engineering effects. Despite these important ecological roles, very little is known about biocrusts in seasonally dry tropical forests. Here we present a first baseline study on biocrust cover and ecosystem service provision in a human-modified landscape of the Brazilian Caatinga, South America's largest tropical dry forest. More specifically, we explored (1) across a network of 34 0.1 ha permanent plots the impact of disturbance, soil, precipitation, and vegetation-related parameters on biocrust cover in different stages of forest regeneration, and (2) the effect of disturbance on species composition, growth and soil organic carbon sequestration comparing early and late successional communities in two case study sites at opposite ends of the disturbance gradient. Our findings revealed that biocrusts are a conspicuous component of the Caatinga ecosystem with at least 50 different taxa of cyanobacteria, algae, lichens and bryophytes (cyanobacteria and bryophytes dominating) covering nearly 10% of the total land surface and doubling soil organic carbon content relative to bare topsoil. High litter cover, high disturbance by goats, and low soil compaction were the leading drivers for reduced biocrust cover, while precipitation was not associated Second-growth forests supported anequally spaced biocrust cover, while in old-growth-forests biocrust cover was patchy. Disturbance reduced biocrust growth by two thirds and carbon sequestration by half. In synthesis, biocrusts increase soil organic carbon (SOC) in dry forests and as they double the SOC content in disturbed areas, may be capable of counterbalancing disturbance-induced soil degradation in this ecosystem. As they fix and fertilize depauperated soils, they may play a substantial role in vegetation regeneration in the human-modified Caatinga, and may have an extended ecological role due to the ever-increasing human encroachment on natural landscapes. Even though biocrusts benefit from human presence in dry forests, high levels of anthropogenic disturbance could threaten biocrust-provided ecosystem services, and call for further, in-depth studies to elucidate the underlying mechanisms.

A Generic First-Order Radiative Transfer Modelling Approach for the Inversion of Soil and Vegetation Parameters from Scatterometer Observations

We present the application of a generic, semi-empirical first-order radiative transfer modelling approach for the retrieval of soil- and vegetation related parameters from coarse-resolution space-borne scatterometer measurements ( σ 0 ). It is shown that both angular- and temporal variabilities of ASCAT σ 0 measurements can be sufficiently represented by modelling the scattering characteristics of the soil-surface and the covering vegetation-layer via linear combinations of idealized distribution-functions. The temporal variations are modelled using only two dynamic variables, the vegetation optical depth ( τ ) and the nadir hemispherical reflectance (N) of the chosen soil-bidirectional reflectance distribution function ( B R D F ). The remaining spatial variabilities of the soil- and vegetation composition are accounted for via temporally constant parameters. The model was applied to series of 158 selected test-sites within France. Parameter estimates are obtained by using ASCAT σ 0 measurements together with auxiliary Leaf Area Index ( L A I ) and soil-moisture ( S M ) datasets provided by the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land-surface model within the SURFEX modelling platform for a time-period from 2007–2009. The resulting parametrization was then used used to perform S M and τ retrievals both with and without the incorporation of auxiliary L A I and S M datasets for a subsequent time-period from 2010 to 2012.

The Impact of Land-Surface Parameter Properties and Resolution on the Simulated Cloud-Topped Atmospheric Boundary Layer

Sensitivity tests using the ‘Consortium for Small Scale Modeling’ model in large-eddy simulation mode with a grid spacing of 100 m are performed to investigate the impact of the resolution of soil- and vegetation-related parameters on a cloud-topped boundary layer in a real-data environment. The reference simulation uses the highest land-surface parameter resolution available for operational purposes (300 m). The sensitivity experiments were conducted using spatial averaging of about $$2.5\,\hbox {km}\times 2.5\,\hbox {km}$$ and $$10\,\hbox {km} \times 10\,\hbox {km}$$ for the land-surface parameters and a completely homogeneous distribution for the whole model domain of about $$70\,\hbox {km} \times 70\,\hbox {km}$$ . Additionally, one experiment with a higher mean soil moisture and another with six mesoscale patches of enhanced or reduced soil moisture are performed. Boundary-layer clouds developed in all simulations. To assess the deviations of cloud cover on different scales within the model domain, we calculated the root-mean-square deviation (RMSD) between the sensitivity experiments and the reference simulation. The RMSD depends strongly on the spatial resolution at which cloud fields are compared. Different spatial resolutions of the cloud fields were generated by applying a low-pass filter. For all sensitivity experiments, large RMSD values occur for cut-off wavelengths $${<}1$$ km, reflecting the stochastic nature of convection, but they decrease rapidly for wavelengths between 1 and 5 km. For cut-off wavelengths $${>}5\,\hbox {km}$$ , the RMSD is still pronounced for the simulation with higher mean soil moisture. Additionally, for cut-off wavelengths between 5 and 30 km, considerable differences can be found for the experiment with mesoscale patches and for that with homogeneous land-surface parameters. Spatial averaging of land-surface parameters for areas of $$2.5\,\hbox {km} \times 2.5\,\hbox {km}$$ and $$10\,\hbox {km} \times 10\,\hbox {km}$$ results in larger patch sizes but simultaneously in reduced amplitudes of land-surface parameter anomalies and shows the lowest RMSD for all cut-off wavelengths.

Evaluating a spatially-explicit and stream power-driven erosion and sediment deposition model in Northern Vietnam

Land use change and unsustainable farm management practises have led to increased soil erosion with severe consequences on the natural resource base in mountainous Northern Vietnam. Given the often prevailing data-limited situations in these regions, simulation models can be used to evaluate alternative land use trajectories or provide decision support for soil conservation planning. In this study, we present a newly developed dynamic and spatially-explicit EROsion and sediment DEPosition model (ERODEP), which simulates soil erosion by stream power principles, sediment deposition based on texture-specific settling velocity classes, and sediment re-entrainment to move previously deposited particles back into runoff flow. ERODEP runs on a daily basis and was linked with the Land Use Change Impact Assessment model (LUCIA) building on its hydrological and vegetation growth routines. The combined modelling framework was employed for a period of four years using field datasets of a small case study watershed. ERODEP-LUCIA simulated reasonably well soil erosion and sediment deposition patterns following the annual variations in land use and rainfall regimes. Output validation (i.e. modelling efficiency=EF) revealed satisfying to good simulation results, i.e. plot-scale soil loss under upland swiddening (EF: 0.60–0.86) and sediment delivery rates in monitored streamflow (EF: 0.44–0.93). Cumulative sediment deposition patterns in lowland paddy fields were simulated fairly well (EF: 0.66), but showed limitations in adequately predicting silt fractions along a spatial gradient in a lowland monitoring site. Findings of a sensitivity analysis demonstrated the interplay of soil erosion and sediment deposition by superimposed variations in stream power, sediment velocity and vegetation related parameters. Results highlighted the potential of ERODEP-LUCIA as an integrated biophysical assessment tool for mountainous ecosystems with moderate data availability.

Modeling response of soil erosion and runoff to changes in precipitation and cover

Global climate has changed over the past century. Precipitation amounts and intensities are increasing. In this study we investigated the response of seven soil erosion models to a few basic precipitation and vegetation related parameters using common data from one humid and one semi-arid watershed. Perturbations were made to inputs for rainfall intensities and amounts, and to ground surface cover and canopy cover. Principal results were that: soil erosion is likely to be more affected than runoff by changes in rainfall and cover, though both are likely to be significantly impacted; percent erosion and runoff will likely change more for each percent change in rainfall intensity and amount than to each percent change in either canopy or ground cover; changes in rainfall amount associated with changes in storm rainfall intensity will likely have a greater impact on runoff and erosion than simply changes in rainfall amount alone; changes in ground cover have a much greater impact on both runoff and erosion than changes in canopy cover alone. The results do not imply that future changes in rainfall will dominate over changes in land use, since land use changes can often be drastic. Given the types of precipitation changes that have occurred over the last century, and the expectations regarding changes over the next century, the results of this study suggest that there is a significant potential for climate change to increase global soil erosion rates unless offsetting conservation measures are taken.

A 10-Year Study on Techniques for Vegetation Restoration in a Desertified Salt Lake Area

Vegetation restoration is one of the most common and effective ways to combat desertification and prevent adjacent areas from sand encroachment in many of the desertified regions of the world. However, vegetation restoration in desertified regions is very difficult because of low rainfall, the mobile ground surface, and cost. An effective, low-cost method of afforestation is urgently required. To determine such a method, a 10-year study was carried out in the Jilantai Salt Lake area. Five different afforestation areas were established: a ‘comparison area,’ a ‘land enclosure area,’ a ‘land enclosure + irrigation area,’ a ‘leveled-afforestation area’ (the dune areas were leveled and then planted with seedlings with added irrigation), and a ‘protected afforestation area’ (the dune areas were planted with seedlings, and the surviving natural vegetation was protected as much as possible). Vegetation-related parameters (survival rate, height, trunk diameter, coverage, canopy size, and density) and environment-related factors (relative humidity, wind velocity, and amount of sand encroachment) were measured by standard methods. Results show that the protected afforestation method had the following advantages: (1) the survival rate was higher for seedlings planted in the protected afforestation area than in the leveled afforestation area; (2) vigor (height, trunk diameter, coverage, and canopy size) was better in seedlings planted in the protected afforestation area than in the leveled afforestation area, especially in the beginning period of revegetation; (3) coverage (of individual species, of all planted vegetation, and of all vegetation) was larger in the protected afforestation area than in the leveled afforestation area; (4) density of naturally germinated plant species was higher in the protected afforestation area than in the other areas, showing that the protected afforestation method provided a suitable growing environment not only for planted species but also for naturally growing species; (5) in the protected vegetation area, relative humidity of air increased and wind velocity was greatly reduced; (6) after the establishment of vegetation by the protected afforestation method, sand encroachment into the salt lake area was significantly reduced. These results suggest that protected afforestation is an effective method of vegetation rehabilitation that has the potential not only to be applied to arid lands in China but also to desertified areas throughout the world; (7) cost-effective calculation shows that the leveled afforestation area costs much more than other areas.

Impact of field-calibrated vegetation parameters on GCM climate simulations

This paper describes a study in which, for the first time, advanced systems-engineering parameter-estimation techniques were applied to data from several field studies to estimate the preferred set of parameters for some of the most common biomes represented in an advanced Soil-Vegetation-Atmosphere Transfer (SVAT) scheme (BATS2, a recent version of the Biosphere-Atmosphere Transfer Scheme); the effect on modelled climate was also investigated. Observational data from field sites in Brazil, Canada, Arizona and Kansas/Oklahoma in the USA, and the Netherlands were chosen as representative of tropical rain forest, coniferous forest, semi-arid vegetation, agricultural crops, and grassland biomes, respectively. Together, these five biomes make up 50% of the land area represented in BATS2. Multi-criteria calibration algorithms do not produce a unique set of model parameters and, when different combinations of the available objective functions at each site are considered, the number of solutions increases substantially. The need for a single parameter-set for each site (biome) is an important practical issue that was necessarily addressed in this study. A procedure was defined in which optimized parameter-sets were successively discarded by successively applying a cut-off threshold to single observable objective functions following a preference hierarchy. In this study, only the vegetation-related parameters are calibrated for each of the five biomes and implemented into BATS2; however, in a separate experiment, the effect of including soil parameters in the optimization was investigated. When the calibrated parameters are adopted and used in BATS2, there are significant changes between the climates calculated in an eight-year run with Version 3 of the Community Climate Model and in an equivalent eight-year run in which the original default parameters were used. The overall conclusion of this exploratory study is that advanced parameter-estimation techniques and appropriate field data can be used successfully to improve representation of surface exchanges and the modelled climate given by a GCM, by defining appropriate values for vegetation-related parameters in an advanced SVAT scheme.

Impact of field‐calibrated vegetation parameters on GCM climate simulations

AbstractThis paper describes a study in which, for the first time, advanced systems‐engineering parameter‐estimation techniques were applied to data from several field studies to estimate the preferred set of parameters for some of the most common biomes represented in an advanced Soil‐Vegetation‐Atmosphere Transfer (SVAT) scheme (BATS2, a recent version of the Biosphere‐Atmosphere Transfer Scheme); the effect on modelled climate was also investigated. Observational data from field sites in Brazil, Canada, Arizona and Kansas/Oklahoma in the USA, and the Netherlands were chosen as representative of tropical rain forest, coniferous forest, semi‐arid vegetation, agricultural crops, and grassland biomes, respectively. Together, these five biomes make up 50% of the land area represented in BATS2. Multi‐criteria calibration algorithms do not produce a unique set of model parameters and, when different combinations of the available objective functions at each site are considered, the number of solutions increases substantially. The need for a single parameter‐set for each site (biome) is an important practical issue that was necessarily addressed in this study. A procedure was defined in which optimized parameter‐sets were successively discarded by successively applying a cut‐off threshold to single observable objective functions following a preference hierarchy. In this study, only the vegetation‐related parameters are calibrated for each of the five biomes and implemented into BATS2; however, in a separate experiment, the effect of including soil parameters in the optimization was investigated. When the calibrated parameters are adopted and used in BATS2, there are significant changes between the climates calculated in an eight‐year run with Version 3 of the Community Climate Model and in an equivalent eight‐year run in which the original default parameters were used. The overall conclusion of this exploratory study is that advanced parameter‐estimation techniques and appropriate field data can be used successfully to improve representation of surface exchanges and the modelled climate given by a GCM, by defining appropriate values for vegetation‐related parameters in an advanced SVAT scheme.

A Climate Version of the Regional Atmospheric Modeling System

The Regional Atmospheric Modeling System (RAMS) has been widely used to simulate relatively short-term atmospheric processes. To perform full-year to multi-year model integrations, a climate version of RAMS (ClimRAMS) has been developed, and is used to simulate diurnal, seasonal, and annual cycles of atmospheric and hydrologic variables and interactions within the central United States during 1989. The model simulation uses a 200-km grid covering the conterminous United States, and a nested, 50-km grid covering the Great Plains and Rocky Mountain states of Kansas, Nebraska, South Dakota, Wyoming, and Colorado. The model’s lateral boundary conditions are forced by six-hourly NCEP reanalysis products. ClimRAMS includes simplified precipitation and radiation sub-models, and representations that describe the seasonal evolution of vegetation-related parameters. In addition, ClimRAMS can use all of the general RAMS capabilities, like its more complex radiation sub-models, and explicit cloud and precipitation microphysics schemes. Thus, together with its nonhydrostatic and fully-interactive telescoping-grid capabilities, ClimRAMS can be applied to a wide variety of problems. Because of non-linear interactions between the land surface and atmosphere, simulating the observed climate requires simulating the observed diurnal, synoptic, and seasonal cycles. While previous regional climate modeling studies have demonstrated their ability to simulate the seasonal cycles through comparison with observed monthly-mean temperature and precipitation data sets, this study demonstrates that a regional climate model can also capture observed diurnal and synoptic variability. Observed values of daily precipitation and maximum and minimum screen-height air temperature are used to demonstrate this ability.

Combining remotely sensed data using aggregation algorithms

Abstract. This paper describes a strategic approach for providing documentation of the surface energy exchange for heterogeneous land surfaces via the simultaneous, four-dimensional assimilation of several streams of remotely sensed data into a coupled land surface-atmosphere model. The basic concepts and underlying theory behind this proposed approach are presented with the intent that this will guide, facilitate, and stimulate future research focused on its practical implementation when appropriate data from the Earth Observing System (EOS) become available. The theoretical concepts that underlie the approach are derived from relationships between the values of parameters which control surface exchanges at pixel (or patch) scale and the area-average value of equivalent parameters applicable at larger, grid scale. A three-step implementation method is proposed which involves (a) estimating grid-average surface radiation fluxes from appropriate remotely sensed data; (b) absorbing these radiation flux estimates into a four-dimensional data assimilation model in which grid-average values of vegetation-related parameters are calculated from pertinent remotely sensed data using the equations that link pixel and grid scales; and (c) improving the resulting estimate of the surface energy balance-again using scale-linking equations by estimating the effect of soil-moisture availability, perhaps assuming that cloud-free pixels are an unbiased subsample of all the pixels in the grid square.

Linear spectral mixture modelling to estimate vegetation amount from optical spectral data

Abstract Spectral mixture modelling has developed in recent years as a suitable remote sensing tool for analysing the biophysical and compositional character of ground surfaces. In this paper the potentiality of the linear spectral mixture model to extract vegetation related parameters from 0·4-2·5 μm reflectance data has been tested. High spectral resolution reflectance measurements of soil-plant mixtures with different soil colour and plant densities were carried out in a laboratory experiment. The constrained least-squares and the factor analysis unmixing procedures were applied to generate endmember fractions of the components present in the mixtures and to test the validity of the model. It is concluded that the derived fraction of the vegetation endmember is less sensitive to soil background than the NDV[. The accuracy attainable by this modelling approach can be considered sufficient for many practical purposes, being operational in the monitoring of vegetation from satellite data.

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.