Evaluating the difference between the normalized difference vegetation index and net primary productivity as the indicators of vegetation vigor assessment at landscape scale

Both the net primary productivity (NPP) and the normalized difference vegetation index (NDVI) are commonly used as indicators to characterize vegetation vigor, and NDVI has been used as a surrogate estimator of NPP in some cases. To evaluate the reliability of such surrogation, here we examined the quantitative difference between NPP and NDVI in their outcomes of vegetation vigor assessment at a landscape scale. Using Landsat ETM+ data and a process model, the Boreal Ecosystem Productivity Simulator, NPP distribution was mapped at a resolution of 90 m, and total NDVI during the growing season was calculated in Heihe River Basin, Northwest China in 2002. The results from a comparison between the NPP and NDVI classification maps show that there existed a substantial difference in terms of both area and spatial distribution between the assessment outcomes of these two indicators, despite that they are strongly correlated. The degree of difference can be influenced by assessment schemes, as well as the type of vegetation and ecozone. Overall, NDVI is not a good surrogate of NPP as the indicators of vegetation vigor assessment in the study area. Nonetheless, NDVI could serve as a fairish surrogate indicator under the condition that the target region has low vegetation cover and the assessment has relatively coarse classification schemes (i.e., the class number is small). It is suggested that the use of NPP and NDVI should be carefully selected in landscape assessment. Their differences need to be further evaluated across geographic areas and biomes.     

Adaptational strategy of a tropical shrub Carissa Carandas L. to urban air pollution

This paper reports the adaptational response of a tropical shrub Carissa Carandas L. to urban air pollution stress in Varanasi, India. Saplings of C. carandas were grown at a density of one per pot and kept for two years at 25 selected sites in the urban environment. Different sites received different levels of air pollution input. Changes in vegetative growth pattern (leafing and branching), in morphological features and in the distribution of biomass to above and below ground structures were considered in relation to the ambient air quality.Different levels of air pollution input produced different sets of harmful effects. Although the air pollution level at Varanasi reduced the plant height, basal diameter, canopy area, leaf area and total plant biomass of C. carandas, this species retained a major fraction of its photosynthate to above-ground plant parts where foliage assumes predominance. Since carbon gain is dependent not only on the rate of carbon acquisition per unit leaf tissue but also on the amount of photosynthetic tissue present, a shift in relative contribution of photosynthate to leaf production and shoot growth appears to be a pollution-induced adaptive response in C. carandas.     

Analysis of agricultural drought using vegetation temperature condition index (VTCI) from Terra/MODIS satellite data

The most commonly used normalized difference vegetation index (NDVI) from remote sensing often fall short in real-time drought monitoring due to a lagged vegetation response to drought. Therefore, research recently emphasized on the use of combination of surface temperature and NDVI which provides vegetation and moisture conditions simultaneously. Since drought stress effects on agriculture are closely linked to actual evapotranspiration, we used a vegetation temperature condition index (VTCI) which is more closely related to crop water status and holds a key place in real-time drought monitoring and assessment. In this study, NDVI and land surface temperature (T _s) from MODIS 8-day composite data during cloud-free period (September–October) were adopted to construct an NDVI–T _s space, from which the VTCI was computed. The crop moisture index (based on estimates of potential evapotranspiration and soil moisture depletion) was calculated to represent soil moisture stress on weekly basis for 20 weather monitoring stations. Correlation and regression analysis were attempted to relate VTCI with crop moisture status and crop performance. VTCI was found to accurately access the degree and spatial extent of drought stress in all years (2000, 2002, and 2004). The temporal variation of VTCI also provides drought pattern changes over space and time. Results showed significant and positive relations between CMI (crop moisture index) and VTCI observed particularly during prominent drought periods which proved VTCI as an ideal index to monitor terminal drought at regional scale. VTCI had significant positive relationship with yield but weakly related to crop anomalies. Duration of terminal drought stress derived from VTCI has a significant negative relationship with yields of major grain and oilseeds crops, particularly, groundnut.     

The potential of biomonitoring of air quality using leaf characteristics of white willow (Salix alba L.)

In this study, we assess the potential of white willow (Salix alba L.) as bioindicator for monitoring of air quality. Therefore, shoot biomass, specific leaf area, stomatal density, stomatal pore surface, and stomatal resistance were assessed from leaves of stem cuttings. The stem cuttings were introduced in two regions in Belgium with a relatively high and a relatively low level of air pollution, i.e., Antwerp city and Zoersel, respectively. In each of these regions, nine sampling points were selected. At each sampling point, three stem cuttings of white willow were planted in potting soil. Shoot biomass and specific leaf area were not significantly different between Antwerp city and Zoersel. Microclimatic differences between the sampling points may have been more important to plant growth than differences in air quality. However, stomatal pore surface and stomatal resistance of white willow were significantly different between Zoersel and Antwerp city. Stomatal pore surface was 20% lower in Antwerp city due to a significant reduction in both stomatal length (?11%) and stomatal width (?14%). Stomatal resistance at the adaxial leaf surface was 17% higher in Antwerp city because of the reduction in stomatal pore surface. Based on these results, we conclude that stomatal characteristics of white willow are potentially useful indicators for air quality.     

Using NDVI to Assess Vegetative Land Cover Change in Central Puget Sound

We used the Normalized Difference Vegetation Index (NDVI) in the rapidly growing Puget Sound region over three 5-year time blocks between 1986–1999 at three spatial scales in 42 Watershed Administrative Units (WAUs) to assess changes in the amounts and patterns of green vegetation. On average, approximately 20% of the area in each WAU experienced significant NDVI change over each 5-year time block. Cumulative NDVI change over 15 years (summing change over each 5-year time block) was an average of approximately 60% of each WAU, but was as high as 100% in some. At the regional scale, seasonal weather patterns and green-up from logging were the primary drivers of observed increases in NDVI values. At the WAU scale, anthropogenic factors were important drivers of both positive and negative NDVI change. For example, population density was highly correlated with negative NDVI change over 15 years (r = 0.66, P < 0.01), as was road density (r = 0.71, P < 0.01). At the smallest scale (within 3 case study WAUs) land use differences such as preserving versus harvesting forest lands drove vegetation change. We conclude that large areas within most watersheds are continually and heavily impacted by the high levels of human use and development over short time periods. Our results indicate that varying patterns and processes can be detected at multiple scales using changes in NDVIa values.     

Vegetation NDVI Linked to Temperature and Precipitation in the Upper Catchments of Yellow River

Vegetation in the upper catchment of Yellow River is critical for the ecological stability of the whole watershed. The dominant vegetation cover types in this region are grassland and forest, which can strongly influence the eco-environmental status of the whole watershed. The normalized difference vegetation index (NDVI) for grassland and forest has been calculated and its daily correlation models were deduced by Moderate Resolution Imaging Spectroradiometer products on 12 dates in 2000, 2003, and 2006. The responses of the NDVI values with the inter-annual grassland and forest to three climatic indices (i.e., yearly precipitation and highest and lowest temperature) were analyzed showing that, except for the lowest temperature, the yearly precipitation and highest temperature had close correlations with the NDVI values of the two vegetation communities. The value of correlation coefficients ranged from 0.815 to 0.951 (p?<?0.01). Furthermore, the interactions of NDVI values of vegetation with the climatic indicators at monthly interval were analyzed. The NDVI of vegetation and three climatic indices had strong positive correlations (larger than 0.733, p?<?0.01). The monthly correlations also provided the threshold values for the three climatic indictors, to be used for simulating vegetation growth grassland under different climate features, which is essential for the assessment of the vegetation growth and for regional environmental management.     

Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

Impacts of ecological water conveyance on groundwater dynamics and vegetation recovery in the lower reaches of the Tarim River in northwest China

The ecological water conveyance project (EWCP) in the lower reaches of the Tarim River provided a valuable opportunity to study hydro-ecological processes of desert riparian vegetation. Ecological effects of the EWCP were assessed at large spatial and temporal scales based on 13 years of monitoring data. This study analyzed the trends in hydrological processes and the ecological effects of the EWCP. The EWCP resulted in increased groundwater storage—expressed as a general rise in the groundwater table—and improved soil moisture conditions. The change of water conditions also directly affected vegetative cover and the phenology of herbs, trees, and shrubs. Vegetative cover of herbs was most closely correlated to groundwater depth at the last year-end (R?=?0.81), and trees and shrubs were most closely correlated to annual average groundwater depth (R?=?0.79 and 0.66, respectively). The Normalized Difference Vegetation Index (NDVI) responded to groundwater depth on a 1-year time lag. Although the EWCP improved the NDVI, the study area is still sparsely vegetated. The main limitation of the EWCP is that it can only preserve the survival of existing vegetation, but it does not effectively promote the reproduction and regeneration of natural vegetation.     

Yield and leaf area index estimations for sunflower plants using unmanned aerial vehicle images

Vegetation is commonly monitored to improve efficiency of various agricultural practices. Spatial and temporal changes in plant growth and development can be monitored with the aid of remote sensing techniques employing ground, aerial, and satellite platforms. Unmanned aerial vehicles (UAV) and multi-spectral cameras developed for UAVs have an important potential for agricultural management activities with high-resolution spatial and temporal images. However, UAV images should be assessed based on ground measurements for using these images as a decision-support tool in agriculture. This study was conducted to estimate sunflower leaf area index (LAI) and yield with the aid of Normalized Difference Vegetation Index (NDVI) images generated from raw UAV images. Furthermore, UAV-based NDVI values were compared with NDVI values calculated by using hyper-spectral measurements carried out with a ground-based spectroradiometer. Between July and August of 2017, six flight missions were conducted and spectral measurements were made simultaneously. A significant correlation (R²?=?0.77) was determined between NDVI values that belong to UAV platform and spectroradiometer. Also, regression models developed for sunflower LAI and yield estimation depending UAV-based NDVI have R² values of 0.88 and 0.91, respectively.     

基于RS和GIS技术的贵州省植被生态环境监测分析

为阐明贵州省植被生态环境变化的整体状况，基于RS和GIS技术，应用美国国家航空航天局最新的全球植被指数变化研究数据（GIMMS），通过计算月归一化植被指数（NDVI）变化率，并对研究区一元线性回归模拟，分析了贵州省1982年-2003年的地表植被覆盖。结果表明：22年来，研究区植被覆盖呈增加趋势，表明贵州省植被生态环境向好的方向发展；贵州省平均植被覆盖在春季和秋季呈上升趋势，夏季和冬季呈下降趋势，其中春季对植被覆盖总变化量的贡献最大；植被覆盖程度增减因区域不同而异，变化程度呈增加的区域主要位于贵,ki-I省的中部地区；变化程度呈减小的区域分布在贵州省的四周边缘。     

Vegetation, Soil, and Animal Indicators of Rangeland Health

We studied indicators of rangeland health on benchmark sites with long, well documented records of protection from stress by domestic livestock or histories of environmental stress and vegetation change. We measured ecosystem properties (metrics) that were clearly linked to ecosystem processes. We focused on conservation of soil and water as key processes in healthy ecosystems, and on maintenance of biodiversity and productivity as important functions of healthy ecosystems. Measurements from which indicators of rangeland health were derived included: sizes of unvegetated patches, cover and species composition of perennial grasses, cover and species composition of shrubs and herbaceous perennials, soil slaking, and abundance and species composition of the bird fauna. Indicators that provided an interpretable range of values over the gradient from irreversibly degraded sites to healthy sites included: bare patch index, cover of long-lived grasses, palatability index, and weighted soil surface stability index. Indicators for which values above a threshold may serve as an indicator of rangeland health include: cover of plant species toxic to livestock, cover of exotic species, and cover of increaser species. Several other indicator metrics were judged not sensitive nor interpretable. Examples of application of rangeland health indicators to evaluate the success of various restoration efforts supported the contention that a suite of indicators are required to assess rangeland health. Bird species diversity and ant species diversity were not related to the status of the sample site and were judged inadequate as indicators of maintenance of biodiversity.     

Small mammals as indicators of short-term and long-term disturbance in mixed prairie

Disturbance by military maneuvers over short and long time scales may have differential effects on grassland communities. We assessed small mammals as indicators of disturbance by military maneuvers in a mixed prairie in southern Oklahoma USA. We examined sites on two soil series, Foard and Lawton, across a gradient of disturbance intensity. A MANOVA showed that abundance of small mammals was associated (p = 0.03) with short-term (cover of vehicle tracks) disturbance but was not associated (p = 0.12) with long-term (loss of soil organic carbon, SOC) disturbance intensity. At the individual species level, Sigmodon hispidus (cotton rat) and Peromyscus maniculatus (deer mouse) occurred across all levels of disturbance and in both soil types. Only P. maniculatus abundance changed (p < 0.01) with short-term disturbance and increased by about one individual per 5% of additional track-cover. Abundance of P. maniculatus also increased (p = 0.04) by about three individuals per 1% increase in soil carbon. Chaetodipus hispidus (hispid pocket mouse) and Reithrodontomys fulvescens (fulvous harvest mouse) only occurred in single soil types limiting their potential as more general indicators. Abundance of P. maniculatus was positively related to shifts in plant species composition and likely reflected changes in vegetation structure (i.e. litter depth) and forage availability resulting from disturbance. Peromyscus maniculatus may be a useful biological indicator of ecosystem change because it responded predictably to both long-term and short-term disturbance and, when coupled with soil, plant, and disturbance history variables, can reveal land condition trends.     

Evaluation of treatment techniques for increasing the uptake of metal ions from solution by nonliving seaweed algal biomass

The effects of several different treatments on subsequent uptake of several metal ions from solution by six strains of seaweed algae and a sea plant were investigated. Samples of Gracilaria conferta, Eisenia bicyclis, Ulva lactuca, Sargassum fluitans, Cladophora prolitera, Padina pavonica, and Zostera marina were treated with one or more of the following: 1 M HCl, 1 M HNO₃, 0.1 M NaOH, 1 M NaOH, acetone, and 60°C water at times from 15 to 60 min and temperatures of 25 and 60°C. Results obtained demonstrate that a treatment time of 15 or 30 min is usually sufficient to produce maximum subsequent metal uptake. Temperature of treatment had little effect.The percentages of Pb, Cu, Zn, Cd, Cr, Mn, Ni, Co, TI, Hg, Au, and Ag subsequently removed from standard metal solutions at a pH of 2–6 by each treated biomass were compared with the percent removal by untreated biomass under the same conditions. All treatments increased the ability of the biomass types studied to bind metals relative to untreated biomass. In addition, pH binding dependence was altered to some extent with a greater degree of binding observed at low pHs by biomass treated with acid. For certain strains of seaweed algae, 0.1 M NaOH treatment produced subsequent uptake of Pb, Cu, Zn, and Cd at levels reaching 100% of initial metal available. Both acidic and basic treatment increased the uptake of Au, Ag, and Hg by four strains of seaweed to nearly 100%.     

Desertification Evaluated Using an Integrated Environmental Assessment Model

Desertification has been defined as land degradation in arid, semi-arid and dry sub-humid areas resulting from various factors, including climatic variations and human activities (United Nations, 1992). A technique for identifying and assessing areas at risk fordesertification in the arid, semi-arid, and subhumid regionsof the United States was developed by the Desert Research Institute and the U.S. Environmental Protection Agency (EPA), using selected environmental indicators integrated into a Geographic Information System (GIS). Five indicators were selected: potential erosion, grazing pressure, climatic stress (expressed as a function of changesin the Palmer Drought Severity Index [PDSI]), change invegetation greenness (derived from the Normalized DifferenceVegetation Index [NDVI]), and weedy invasives as a percentof total plant cover. The data were integrated over aregional geographic setting using a GIS, which facilitateddata display, development and exploration of data relationships, including manipulation and simulation testing. By combining all five data layers, landscapes having a varying risk for land degradation were identified, providing a tool which could be used to improve landmanagement efficiency.     

A Comparison of Three Methods to Collect Submerged Aquatic Vegetation in a Shallow Lake

Two boat-based and one in-water sampling method have been used to collect submerged aquatic vegetation (SAV) as part of a long-term monitoring program in Lake Okeechobee, Florida, USA. The boat-based methods consisted of collecting SAV with a ponar dredge, used only to collect Chara, and an oyster tongs-like rake apparatus, used to collect all SAV. The in-water method involved use of a 0.5 m² PVC quadrat frame deployed by a diver. During summer 2002, SAV biomass samples were collected using all three methods at various sites in the lake to compare between-methods sampling precision. Sites used for these comparisons were selected based on plant type, plant density and sediment type. Statistical comparisons indicated that there were significant (p ≤ 0.05) biomass differences in 8 of 15 possible pairwise comparisons between sampling method biomass means. In four of the eight comparisons, significantly higher biomass mean values were obtained using the quadrat frame. In three of the remaining four comparisons, significantly higher biomass mean values were obtained with the rake apparatus. For the fourth comparison, a significantly higher biomass mean value was obtained with the ponar dredge. Three of the four relationships between SAV biomass collected by the rake and the quadrat and the rake and the quadrat/ponar dredge were statistically significant, linear and explained between 67 and 78% of the biomass variability. There were no significant differences between regression coefficients or elevations for these relationships, therefore these regressions estimated the same population regression. The population regression coefficient was 0.95, suggesting that the quadrat and ponar over-sampled relative to the rake, but the amount of this over-sampling was very small. Since there was no consistent pattern in the sampling method which yielded the significantly different biomass values and there were no significant differences in sampling precision across a range of plant species, plant densities and two sediment types, the boat-based rake method appears to be a suitable replacement for the previously used ponar dredge and quadrat methods, when in-lake measurements are not practical.     

Development and application of a video-mosaic survey technology to document the status of coral reef communities

The recent decline in the condition of coral reef communities worldwide has fueled the need to develop innovative assessment tools to document coral abundance and distribution rapidly and effectively. While most monitoring programs rely primarily on data collected in situ by trained divers, digital photographs and video are used increasingly to extract ecological indicators, provide a permanent visual record of reef condition, and reduce the time that divers spend underwater. In this study, we describe the development and application of a video-based reef survey methodology based on an algorithm for image registration and the estimation of image motion and camera trajectory. This technology was used to construct two-dimensional, spatially accurate, high-resolution mosaics of the reef benthos at a scale of up to 400 m². The mosaics were analyzed to estimate the size and percent cover of reef organisms and these ecological indicators of reef condition were compared to similar measurements collected by divers to evaluate the potential of the mosaics as monitoring tools. The ecological indicators collected by trained divers compared favorably with those measured directly from the video mosaics. Five out of the eight categories chosen (hard corals, octocorals, Palythoa, algal turf, and sand) showed no significant differences in percent cover based on survey method. Moreover, no significant differences based on survey method were found in the size of coral colonies. Lastly, the capability to extract the same reef location from mosaics collected at different times proved to be an important tool for documenting change in coral abundance as the removal of even small colonies (<10 cm in diameter) was easily documented. The two-dimensional video mosaics constructed in this study can provide repeatable, accurate measurements on the reef-plot scale that can complement measurements on the colony-scale made by divers and surveys conducted at regional scales using remote sensing tools.     

Inorganic chemical composition of native trees of the Atlantic Forest

The Atlantic Forest with its exuberant vegetation of high level of biodiversity is classified as one hotspot of the world. Chemical composition of leaves from native trees and underlying soils was evaluated by INAA. The predominant species Euterpe edulis, Bathysa meridionalis, Hyeronima alchorneoides, Marlierea tomentosa, Gomidesia flagellaris, and Gomidesia spectabilis belonging to the diverse plant families were studied. Euterpe edulis, the most abundant understory specie, presented the lowest element concentrations except for Zn. Some variation in chemical composition was noted, however, the chemical specificity of tree species can be more predominant than the soil variability for the obtained leaf concentrations. Factor values obtained through the Monte-Carlo assisted factor analysis were used for species discrimination. The results indicate that chemical investigation of native trees is a quite promising tool for biodiversity studies in the Atlantic Forest.     

Estimating and mapping forest biomass using regression models and Spot-6 images (case study: Hyrcanian forests of north of Iran)

Hyrcanian forests of North of Iran are of great importance in terms of various economic and environmental aspects. In this study, Spot-6 satellite images and regression models were applied to estimate above-ground biomass in these forests. This research was carried out in six compartments in three climatic (semi-arid to humid) types and two altitude classes. In the first step, ground sampling methods at the compartment level were used to estimate aboveground biomass (Mg/ha). Then, by reviewing the results of other studies, the most appropriate vegetation indices were selected. In this study, three indices of NDVI, RVI, and TVI were calculated. We investigated the relationship between the vegetation indices and aboveground biomass measured at sample-plot level. Based on the results, the relationship between aboveground biomass values and vegetation indices was a linear regression with the highest level of significance for NDVI in all compartments. Since at the compartment level the correlation coefficient between NDVI and aboveground biomass was the highest, NDVI was used for mapping aboveground biomass. According to the results of this study, biomass values were highly different in various climatic and altitudinal classes with the highest biomass value observed in humid climate and high-altitude class.     

Invasive species and coal bed methane development in the Powder River Basin, Wyoming

One of the fastest growing areas of natural gas production is coal bed methane (CBM) due to the large monetary returns and increased demand for energy from consumers. The Powder River Basin, Wyoming is one of the most rapidly expanding areas of CBM development with projections of the establishment of up to 50,000 wells. CBM disturbances may make the native ecosystem more susceptible to invasion by non-native species, but there are few studies that have been conducted on the environmental impacts of this type of resource extraction. To evaluate the potential effects of CBM development on native plant species distribution and patterns of non-native plant invasion, 36 modified Forest Inventory and Analysis plots (each comprised of four 168-m² subplots) were established in the Powder River Basin, Wyoming. There were 73 168-m² subplots on control sites; 42 subplots on secondary disturbances; 14 on major surface disturbances; eight on well pads; and seven on sites downslope of CBM wells water discharge points. Native plant species cover ranged from 39.5 ± 2.7% (mean ± 1 SE) in the secondary disturbance subplots to 17.7 ± 7.5% in the pad subplots. Non-native plant species cover ranged from 31.0 ± 8.4% in the discharge areas to 14.7 ± 8.9% in the pad subplots. The control subplots had significantly less non-native species richness than the combined disturbance types. The combined disturbance subplots had significantly greater soil salinity than the control sites. These results suggest that CBM development and associated disturbances may facilitate the establishment of non-native plants. Future research and management decisions should consider the accumulative landscape-scale effects of CBM development on preserving native plant diversity.     

Using NOAA AVHRR data to assess flood damage in China

The article used two NOAA-14 Advanced Very High ResolutionRadiometer (AVHRR) datasets to assess flood damage in the middleand lower reaches of China's Changjiang River (Yangtze River) in 1998. As the AVHRR is an optical sensor, it cannot penetratethe clouds that frequently cover the land during the flood season, and this technology is greatly limited in flood monitoring. However the widely used normalized difference vegetation index (NDVI) can be used to monitor flooding, sincewater has a much lower NDVI value than other surface features.Though many factors other than flooding (e.g. atmospheric conditions, different sun-target-satellite angles, and cloud) can change NDVI values, inundated areas can be distinguished fromother types of ground cover by changes in the NDVI value beforeand after the flood after eliminating the effects of other factors on NDVI. AVHRR data from 26 May and 22 August, 1998 wereselected to represent the ground conditions before and after flooding. After accurate geometric correction by collecting GCPs,and atmospheric and angular corrections by using the 6S code, NDVI values for both days and their differences were calculatedfor cloud-free pixels. The difference in the NDVI values betweenthese two times, together with the NDVI values and a land-use map, were used to identify inundated areas and to assess the arealost to the flood. The results show a total of 358 867 ha, with 207 556 ha of cultivated fields (paddy and non-irrigated field) inundated during the flood of 1998 in the middle and lower reaches of the Changjiang River Catchment; comparing with the reported total of 321 000 and 197 000 ha, respectively. The discrimination accuracy of this method was tested by comparing the results from two nearly simultaneous sets of remote-sensingdata (NOAA's AVHRR data from 10 September, 1998, and JERS-1 synthetic aperture radar (SAR) data from 11 September, 1998, with a lag of about 18.5 hr) over a representative flooded regionin the study area. The results showed that 67.26% of the total area identified as inundated using the NOAA data was also identified as inundated using the SAR data.