Forest canopy moisture content is an important factor in determining forest fire risk and forest fire behaviour. In Dargon 2 project, to develop a suitable regional early warning technique to predict forest fire risk, a Normal Difference Water Index (NDWI), which has been calculated by using the reflectance of SWIR and NIR band of HJ-1B IRS, has been used to retrieve forest canopy moisture cont...

Pan-sharpening is the process of fusing higher spatial resolution panchromatic (PAN) with lower spatial resolution multispectral (MS) imagery to create higher spatial resolution MS images. Here, our overall objective was to pan-sharpen Landsat-8 images and calculate vegetation greenness (i.e., normalized difference vegetation index (NDVI)), canopy structure (i.e., enhanced vegetation index (EVI...

identification of the best vegetation indices (vis) for use in quantitative analyzes of vegetation is one of the important issues for ecologists. the objective of this study was sensitivity evaluation of vegetation indices to a stand volume for identification of the best vegetation index (vi) in stand volume estimation using a statistical sensitivity method. also, another objective of this stud...

This study proposes a method for improving the estimation of surface turbulent fluxes in surface energy balance system (SEBS) model under water stress conditions using MODIS data. The normalized difference water index (NDWI) as an indicator of water stress is integrated into SEBS. To investigate the feasibility of the new approach, the desert-oasis region in the middle reaches of the Heihe Rive...

Several indices, including the normalized difference vegetation index (NDVI), normalized difference build-up index (NDBI), and normalized difference water index (NDWI), were retrieved from the Landsat 5 Thematic Mapper (TM) images, and the land surface temperature (LST) was reversed by the thermal radiation transfer model. Next, with the help of the thermal field variance index from LST, charac...

This study explored the capability of Support Vector Machines (SVMs) and regularised kernel Fisher’s discriminant analysis (rkFDA) machine learning supervised classifiers in extracting flooded area from optical Landsat TM imagery. The ability of both techniques was evaluated using a case study of a riverine flood event in 2010 in a heterogeneous Mediterranean region, for which TM imagery acquir...

Taking LandSat TM/ETM+ images as information source, this paper used the Normalized Difference Water Index (NDWI) to extract mining subsidence-resulted surface water body information in Yanzhou coal mining area. It was found that the extracted water body information would be mixed with solid-waste dumps. Taking DN 40 in band 5 as threshold value, the water bodies and solid-waste dumps were iden...

This study conducts an exploratory evaluation of the performance of the newly available Sentinel-2A Multispectral Instrument (MSI) imagery for mapping water bodies using the image sharpening approach. Sentinel-2 MSI provides spectral bands with different resolutions, including RGB and Near-Infra-Red (NIR) bands in 10 m and Short-Wavelength InfraRed (SWIR) bands in 20 m, which are closely relate...

Building density, as a component of impervious surface fraction, is a significant indicator of population distribution as essentially all humans live and conduct activities in buildings. Because population spatialization usually occurs over large areas, large-scale building density estimation through a proper, time-efficient, and relatively precise way is urgently required. Therefore, this stud...

Abstract There are many traditional methods available for water body extraction based on remote sensing images, such as normalised difference index (NDWI), modified NDWI (MNDWI), and the multi-band spectrum method, but accuracy of these is limited. In recent years, machine learning algorithms have developed rapidly been applied widely. Using Landsat-8 models decision tree, logistic regression, ...