The normalized difference water index (NDWI) of McFeeters (1996) was modified by substitution of a middle infrared band such as Landsat TM band 5 for the near infrared band used in the NDWI. The modified NDWI (MNDWI) can enhance open water features while efficiently suppressing and even removing built‐up land noise as well as vegetation and soil noise. The enhanced water information using the NDWI is often mixed with built‐up land noise and the area of extracted water is thus overestimated. Accordingly, the MNDWI is more suitable for enhancing and extracting water information for a water region with a background dominated by built‐up land areas because of its advantage in reducing and even removing built‐up land noise over the NDWI.

Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery

Remotely sensed imagery is ideally used to monitor and detect land cover changes that occur frequently in urban and peri-urban areas as a consequence of incessant urbanization. It is a lengthy process to convert satellite imagery into land cover map using the existing methods of manual interpretation and parametric image classification digitally. In this paper we propose a new method based on Normalized Difference Built-up Index (NDBI) to automate the process of mapping built-up areas. It takes advantage of the unique spectral response of built-up areas and other land covers. Built-up areas are effectively mapped through arithmetic manipulation of re-coded Normalized Difference Vegetation Index (NDVI) and NDBI images derived from TM imagery. The devised NDBI method was applied to map urban land in the city of Nanjing, eastern China. The mapped results at an accuracy of 92.6% indicate that it can be used to fulfil the mapping objective reliably. Compared with the maximum likelihood classification method, t...

Use of normalized difference built-up index in automatically mapping urban areas from TM imagery

Vegetation Indices (VIs) obtained from remote sensing based canopies are quite simple and effective algorithms for quantitative and qualitative evaluations of vegetation cover, vigor, and growth dynamics, among other applications These indices have been widely implemented within RS applications using different airborne and satellite platforms with recent advances using Unmanned Aerial Vehicles (UAV) Up to date, there is no unified mathematical expression that defines all VIs due to the complexity of different light spectra combinations, instrumentation, platforms, and resolutions used Therefore, customized algorithms have been developed and tested against a variety of applications according to specific mathematical expressions that combine visible light radiation, mainly green spectra region, from vegetation, and nonvisible spectra to obtain proxy quantifications of the vegetation surface In the real-world applications, optimization VIs are usually tailored to the specific application requirements coupled with appropriate validation tools and methodologies in the ground The present study introduces the spectral characteristics of vegetation and summarizes the development of VIs and the advantages and disadvantages from different indices developed This paper reviews more than 100 VIs, discussing their specific applicability and representativeness according to the vegetation of interest, environment, and implementation precision Predictably, research, and development of VIs, which are based on hyperspectral and UAV platforms, would have a wide applicability in different areas

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Significant remote sensing vegetation indices: A review of developments and applications

Automated Water Extraction Index: a new technique for surface water mapping using Landsat imagery.

The normalized difference water index (NDWI) has been successfully used to delineate surface water features. However, two major problems have been often encountered: (a) NDWIs calculated from different band combinations [visible, nearinfrared, or shortwave-infrared (SWIR)] can generate different results, and (b) NDWI thresholds vary depending on the proportions of subpixel water/non-water components. We need to evaluate all the NDWIs for determining the best performing index and to establish appropriate thresholds for clearly identifying water features. We used the spectral data obtained from a spectral library to simulate the satellite sensors Landsat ETM, SPOT-5, ASTER, and MODIS, and calculated the simulated NDWI in different forms. We found that the NDWI calculated from (green ‐ SWIR)/(green SWIR), where SWIR is the shorter wavelength region (1.2 to 1.8 mm), has the most stable threshold. We recommend this NDWI be employed for mapping water, but adjustment of the threshold based on actual situations is necessary.

Analysis of Dynamic Thresholds for the Normalized Difference Water Index

The Normalized Difference Water Index (NDWI) is a new method that has been developed to delineate open water features and enhance their presence in remotely-sensed digital imagery. The NDWI makes use of reflected near-infrared radiation and visible green light to enhance the presence of such features while eliminating the presence of soil and terrestrial vegetation features. It is suggested that the NDWI may also provide researchers with turbidity estimations of water bodies using remotely-sensed digital data.

The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features

Mosquito-borne diseases affect millions of people worldwide. In the United States, since 1999, West Nile Virus (WNV) has infected 36,801 people and has caused the deaths of 1,580. In California, since 2002, nearly 3,600 people have been infected with WNV with an additional 124 fatalities. Analyses of remotely- and spatially-based data have proven to facilitate the study of mosquito-borne diseases, including WNV. This study proposes an efficient procedure to identify swimming pools that may serve as potential mosquito habitat. The procedure derives the Normalized Difference Water Index (NDWI) from high resolution, multi-spectral imagery to detect the presence of surface water, and then incorporates vector-based data layers within a GIS to identify residential land parcels with detectable water. This study compared the parcels identified as having water (535) with parcels known to have swimming pools (682) resulting in an accuracy of 78.4%. Nineteen of the 147 land parcels with swimming pools had backyards with enough vegetation to obscure the presence of a swimming pool from the satellite. The remaining 128 parcels lacked enough surface water for the NDWI to indicate them as actually having surface water. It is likely then that swimming pools, associated with such parcels, may have enough water in them to provide adequate habitat for mosquitoes, and so field inspection by mosquito abatement personnel would be justified.

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Using the Normalized Difference Water Index (NDWI) within a Geographic Information System to Detect Swimming Pools for Mosquito Abatement: A Practical Approach

Organic farmers and limited-resource growers in the San Joaquin Valley and other agricultural areas in California—many of whom are ethnic minorities—encounter limited options and environmental constraints when seeking economically viable pest management methods. Over the past 8 years, we have conducted weed research and implementation projects on soil solarization at the UC Kearney Research and Extension Center and on farms in the surrounding San Joaquin Valley. In the Kearney studies, small-scale solarization in parsley reduced weed biomass 94% to 99% over the untreated control. Furthermore, in an on-farm study, solarization provided effective weed control for strawberries at a much lower cost than methyl bromide, with comparable yields. This research has provided guidelines and technical support for growers wishing to implement solarization and related techniques for nonchemical soil disinfestation in a wide variety of specialty crops.

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Methyl bromide alternatives … Soil solarization provides weed control for limited-resource and organic growers in warmer climates

The temporal variability of USA snowfall is investigated for the period 1945–1946 through to 1984–1985 using linear trend and principal components analyses. The results of the linear trend analysis indicate that two regions of the USA evidence significant changes in monthly snowfall over the period. These areas include the Great Lakes/upper mid-west and high plains regions of the USA. In the Great Lakes/upper mid-west sector, positive linear trends are found in monthly snowfall totals for the mid-winter months (December, January, February). For the high plains region, positive linear trends are found for the month of December. Principal components analysis (PCA) is used with seasonal snowfall data in order to better understand the spatial and temporal nature of seasonal snowfall variations across the USA. The PCA isolates six spatially coherent regions in which seasonal snowfall varied similarly over the 40-year period. Only one of these regions, centred on the Great Lakes and upper mid-west, displays any long-term change in seasonal snowfall, a positive trend during the period 1945–1946 through to 1984–1985. These results are discussed in the context of man-induced and natural environmental changes.

Temporal characteristics of USA snowfall 1945–1946 through to 1984–1985

The Landsat-Muitispectral Scanner (MSS) data were used to measure lake area fluctuations (1972–1989) for 130 ground-water dominated lakes in the Western Lakes Region of the Nebraska Sand Hills. In general, the pattern shown in lake area hydrographs was similar to that for in-situ lake elevations. In-situ lake-elevation data verify that remote monitoring of surface-area fluctuations, even at relatively coarse spatial resolution, is not only practical and useful, but also it elucidates the hydrologic characteristics of groundwater-dominated lakes of the Sand Hills. The apparent differences in behavior between lakes in the northern and southern portions of the study area may be related to both their location in the regional ground water system and the substantial local hydrologic complexity.

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Stuart K. McFeeters

Papers

The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features

Using the Normalized Difference Water Index (NDWI) within a Geographic Information System to Detect Swimming Pools for Mosquito Abatement: A Practical Approach

Methyl bromide alternatives … Soil solarization provides weed control for limited-resource and organic growers in warmer climates

Temporal characteristics of USA snowfall 1945–1946 through to 1984–1985

Remote Monitoring of Selected Ground-Water Dominated Lakes in the Nebraska Sand Hills