Remote sensing of species diversity using Landsat 8 spectral variables

Evaluation of Dust Effects on Spectral Behavior of Plants Using Remote Sensing Data

Introduction Dust is one of the important climatic phenomena that has occurred in arid and semi-arid regions of the world. In recent years, one of the most important environmental issues in the Middle East and Iran is the occurrence of dust phenomena that affects a variety of factors, including human health, plants and other living organisms, economic conditions, and etc. One of the effective ...

Potential of Landsat-8 spectral indices to estimate forest biomass

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...

Landsat remote sensing of forest windfall disturbance

a r t i c l e i n f o Knowing if a forest disturbance is caused by timber harvest or a natural event is crucial for carbon cycle assessments , econometric analyses of timber harvesting, and other research questions. However, while remote sensing of forest disturbance in general is very well developed, discerning between different types of forest disturbances remains challenging. In this work, w...

Identification of Invasive Species Using Remote Sensing and Vegetation Indices, (Case Study: Vazroud Rangelands, Iran)

Biological invasions form a major threat to the provision of ecosystems productsand services and can affect ecosystems across a wide spectrum of bioclimatic conditions.Therefore, it is important to systematically monitor the spread of species over broad regions. Ithas long been recognized that remote sensing and geographical information system couldcontribute to this capacity. This paper aims t...

Predicting species diversity in agricultural environments using Landsat TM imagery