The use of data from multiple sensors is often required to ensure data coverage and continuity, but differences in the spectral characteristics of sensors result in spectral index values being different. This study investigates spectral response function effects on 48 spectral indices for cultivated grasslands using simulated data of 10 very high spatial resolution sensors, convolved from field...

In red-NIR reflectance space, the Modified Soil Adjusted Vegetation Index (MSAVI) isolines, representing similar vegetation biophysical quantities, are neither convergent to a point nor parallel to each other. Consequently, the treatment of the MSAVI isolines is distinctly different from those of other vegetation index isolines, such as the normalized difference vegetation index (NDVI), the per...

Crop coefficient values are used to estimate crop evapotranspiration (ETc) for determining irrigation scheduling. Many important crop biophysical properties such as Percentage Vegetation Cover and Leaf Area Index can be estimated from remotely sensed Vegetation Index, in order to quantify real time vegetation growth dynamics. The objective of this study was to understand the effectiveness of ba...

Remote sensing of vegetation condition using high resolution digital multispectral imagery (DMSI) is an option for land managers interested in quantifying the distribution and extent of dieback in native forest. Crown condition is assessed as reference to the physical structure and foliage (i.e. density, transparency, extent and in-crown distribution) of a tree crown. At 20 sites in the Yalgoru...

The main goal of this research was to estimate the actual evapotranspiration (ETc) of a drip-irrigated apple orchard located in the semi-arid region of Talca Valley (Chile) using a remote sensing-based soil water balance model. The methodology to estimate ETc is a modified version of the Food and Agriculture Organization of the United Nations (FAO) dual crop coefficient approach, in which the b...

A large number of vegetation indices have been developed and widely applied in terrestrial ecosystem research in the recent decades. However, a certain limitation was observed while applying these indices in research in dry areas due to their low sensitivity to low vegetation cover. In this context, the objectives of this study are to develop a new vegetation index, namely, the Generalized Diff...

Gross primary productivity (GPP) is a key component of ecosystem carbon fluxes and the carbon balance between the biosphere and the atmosphere. Accurate estimation of GPP is essential for quantifying plant production and carbon balance for grasslands. Satellite-derived vegetation indices (VIs) are often used to approximate GPP. The widely used VIs include atmospherically resistant vegetation in...

Vegetation in the Arctic is often sparse, spatially heterogeneous, and difficult to model. Synthetic Aperture Radar (SAR) has shown some promise in above-ground phytomass estimation at sub-arctic latitudes, but the utility of this type of data is not known in the context of the unique environments of the Canadian High Arctic. In this paper, Artificial Neural Networks (ANNs) were created to mode...

Forest ecosystems are among the largest terrestrial carbon reservoirs on our planet earth thus playing a vital role in global carbon cycle. Presently, remote sensing techniques provide proper estimates of forest biomass and quantify carbon stocks. The present study has explored Landsat-8 sensor product and evaluated its application in biomass mapping and estimation. The specific objectives were...

Studies on the resilience of mangrove forest areas are becoming popular in Indonesia, despite implementation Hyper Spectral Remote Sensing method identifying changes vegetation index values based Normalized Difference Vegetation Index (NDVI), Soil Adjusted (SAVI) and Enhanced models (EVI) unreached need to be done add database so that it becomes a reference for further research. Considering thi...