Search results for "Land cover"
showing 10 items of 149 documents
Assessment of site-specific drivers of farmland abandonment in mosaic-type landscapes: A case study in Vidzeme, Latvia
2018
Abstract Farmland abandonment, which causes changes in rural life and farming practices, can be observed throughout Europe. Over the last decades natural afforestation has decreased the area of farmland used for agricultural production, thereby leading to landscape homogenization and polarization. This process is explicitly evident in mosaic type landscapes consisting of highly complex land cover patterns, soil composition and topography. The aim of the study was to determine the site-specific driving forces of farmland abandonment at landscape scale in relation to agro-ecological and geographic factors, in a post-Soviet country in Eastern Europe. An extensive field survey approach with sta…
Comparison Between Fractional Vegetation Cover Retrievals from Vegetation Indices and Spectral Mixture Analysis: Case Study of PROBA/CHRIS Data Over …
2009
Abstract: In this paper we compare two different methodologies for Fractional Vegetation Cover (FVC) retrieval from Compact High Resolution Imaging Spectrometer (CHRIS) data onboard the European Space Agency (ESA) Project for On-Board Autonomy (PROBA) platform. The first methodology is based on empirical approaches using Vegetation Indices (VIs), in particular the Normalized Difference Vegetation Index (NDVI) and the Variable Atmospherically Resistant Index (VARI). The second methodology is based on the Spectral Mixture Analysis (SMA) technique, in which a Linear Spectral Unmixing model has been considered in order to retrieve the abundance of the different constituent materials within pixe…
Land cover classification of VHR airborne images for citrus grove identification
2011
Abstract Managing land resources using remote sensing techniques is becoming a common practice. However, data analysis procedures should satisfy the high accuracy levels demanded by users (public or private companies and governments) in order to be extensively used. This paper presents a multi-stage classification scheme to update the citrus Geographical Information System (GIS) of the Comunidad Valenciana region (Spain). Spain is the first citrus fruit producer in Europe and the fourth in the world. In particular, citrus fruits represent 67% of the agricultural production in this region, with a total production of 4.24 million tons (campaign 2006–2007). The citrus GIS inventory, created in…
A novel ensemble computational intelligence approach for the spatial prediction of land subsidence susceptibility.
2020
Land subsidence (LS) is a significant problem that can cause loss of life, damage property, and disrupt local economies. The Semnan Plain is an important part of Iran, where LS is a major problem for sustainable development and management. The plain represents the changes occurring in 40% of the country. We introduce a novel-ensemble intelligence approach (called ANN-bagging) that uses bagging as a meta- or ensemble-classifier of an artificial neural network (ANN) to predict LS spatially on the Semnan Plain in Semnan Province, Iran. The ensemble model's goodness-of-fit (to training data) and prediction accuracy (of the validation data) are compared to benchmarks set by ANN-bagging. A total …
Multitemporal mapping of peri-urban carbon stocks and soil sealing from satellite data.
2017
Abstract Peri-urbanisation is the expansion of compact urban areas towards low-density settlements. This phenomenon directly challenges the agricultural landscape multifunctionality, including its carbon (C) storage capacity. Using satellite data, we mapped peri-urban C stocks in soil and built-up surfaces over three areas from 1993 to 2014 in the Emilia-Romagna region, Italy: a thinly populated area around Piacenza, an intermediate-density area covering the Reggio Emilia-Modena conurbation and a densely anthropized area developing along the coast of Rimini. Satellite-derived maps enabled the quantitative analysis of spatial and temporal features of urban growth and soil sealing, expressed …
Recent trends in solar exergy and net radiation at global scale
2012
Abstract The availability during the last decades of remotely sensed images and global climatic data allow us to analyse the “Earth system” as a whole in order to develop concepts for global environmental management. This system can be considered a complex, dissipative, dynamic entity, far from thermodynamic equilibrium ( Schellnhuber, 1999 ). Energy balance has been considered for many decades to understand the functioning of ecosystems, the biosphere or the Earth planet as a whole, but it is also possible to study our planet from a thermodynamic point of view. In this letter we analyse recent trends in solar exergy and net radiation at global scale during the period 1980–2010, distinguish…
Remote Sensing Image Classification with Large Scale Gaussian Processes
2017
Current remote sensing image classification problems have to deal with an unprecedented amount of heterogeneous and complex data sources. Upcoming missions will soon provide large data streams that will make land cover/use classification difficult. Machine learning classifiers can help at this, and many methods are currently available. A popular kernel classifier is the Gaussian process classifier (GPC), since it approaches the classification problem with a solid probabilistic treatment, thus yielding confidence intervals for the predictions as well as very competitive results to state-of-the-art neural networks and support vector machines. However, its computational cost is prohibitive for…
Cloud detection machine learning algorithms for PROBA-V
2020
This paper presents the development and implementation of a cloud detection algorithm for Proba-V. Accurate and automatic detection of clouds in satellite scenes is a key issue for a wide range of remote sensing applications. With no accurate cloud masking, undetected clouds are one of the most significant sources of error in both sea and land cover biophysical parameter retrieval. The objective of the algorithms presented in this paper is to detect clouds accurately providing a cloud flag per pixel. For this purpose, the method exploits the information of Proba-V using statistical machine learning techniques to identify the clouds present in Proba-V products. The effectiveness of the propo…
A methodology to generate a synergetic land-cover map by fusion of different land-cover products
2012
Abstract The main goal of this study is to develop a general framework for building a hybrid land-cover map by the synergistic combination of a number of land-cover classifications with different legends and spatial resolutions. The proposed approach assesses class-specific accuracies of datasets and establishes affinity between thematic legends using a common land-cover language such as the UN Land-Cover Classification System (LCCS). The approach is illustrated over a large region in Europe using four land-cover datasets (CORINE, GLC2000, MODIS and GlobCover), but it can be applied to any set of existing products. The multi-classification map is expected to improve the performance of indiv…
Simplified methods for spatial sampling: application to first-phase data of Italian National Forest Inventory (INFC) in Sicily
2006
Abstract: Methodological approaches able to integrate data from sample plots with cartographic processes are widely applied. Based on mathematic-statistical techniques, the spatial analysis allows the exploration and spatialization of geographic data. Starting from the punctual information on land use types obtained from the dataset of the first phase of the ongoing new Italian NFI (INFC), a spatialization of land cover classes was carried out using the Inverse Distance Weighting (IDW) method. In order to validate the obtained results, an overlay with other vectorial land use data was carried out. In particular, the overlay compared data at different scales, evaluating differences in terms …