Artificial Neural Network (ANN) is an important Artificial Intelligence (AI) and Machine Learning (ML) method used in various remote sensing applications such as image classification, pattern recognition etc.One of important remote sensing applications is the landuse classification i.e. classification of satellite data into various landuse classes such as forest, waterbody, snowcover etc. Landu...

Abstract Groundwater and its upcoming crisis are the present-day concern of scientist. This research mainly focuses on responses groundwater dynamicity to some important drivers, viz. agricultural yield, irrigated area, draft, landuse/landcover, stage development. The result this study has been done under three sections. In first section, spatiality discussed where it noticed that western side ...

This paper examines characteristics of urban land-use and land-cover (LULC) classes using spectral mixture analysis (SMA), and develops a conceptual model for characterizing urban LULC patterns. A Landsat Enhanced Thematic Mapper Plus (ETM+) image of Indianapolis City was used in this research and a minimum noise fraction (MNF) transform was employed to convert the ETM+ image into principal com...

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about th...

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Clima...

A relevant issue in Remote Sensing (RS) and GIS is related to the analysis and the characterization of Land Use Land Cover (LULC) changes, very useful for a wide range of environmental applications and to efficiently undertake landscape planning and management policies. The methodology described has been applied to a case-study conducted in the area of the Province of Avellino (Southern Italy)....

Landcover change alters not only the surface landscape but also regional carbon and water cycling. The objective of this study was to assess the potential impacts of landcover change across the Kansas River Basin (KRB) by comparing local microclimatic impacts and regional scale climate influences. This was done using a 25-year time series of Normalized Difference Vegetation Index (NDVI) and pre...

This paper describes the development of a 1-km landcover dataset of China by using monthly NDVI data spanning April 1992 through March 1993. The method used combined unsupervised and supervised classification of NDVI data from Ž . AVHRR. It is composed of five steps: a unsupervised clustering of monthly AVHRR NDVI maximum value composites is Ž . performed using the ISOCLASS algorithm; b prelimi...