Savannah ecosystems face significant threats from land degradation, including woody vegetation encroachment. This study introduces a high-resolution method for mapping the fraction of savannah cover by integrating optical (Sentinel-2, S2), radar (Sentinel-1, S1), and auxiliary data. First, comprehensive training dataset fractional (FWC) samples was developed very imagery thousands manually annotated points. Shallow deep learning algorithms were utilised to generate classification masks, with...

In order to exploit remote sensing data operationally for precision agriculture applications, efficient and automated methods are required the accurate detection of vegetation, crops different crop varieties. To this end, we have designed, developed evaluated an object-based classification framework towards vineyards, vine canopy extraction variety discrimination from very high resolution multispectral data. A novel set spectral, spatial textural features, as well rules, segmentation scales...

Mapping water stress in vineyards, at the parcel level, is of significant importance for supporting crop management decisions and applying precision agriculture practices. In this paper, a novel methodology based on aerial Shortwave Infrared (SWIR) data presented, towards estimation vineyards canopy scale entire parcels. particular, broadband spectral were collected from an integrated SWIR multispectral instrumentation, onboard unmanned vehicle (UAV). Concurrently, in-situ leaf stomatal...

Detailed, accurate and frequent land cover mapping is a prerequisite for several important geospatial applications the fulfilment of current sustainable development goals. This paper introduces methodology classification annual high-resolution satellite data into detailed classes. In particular, nomenclature with 27 different classes was introduced based on CORINE Land Cover (CLC) Level-3 categories further analysing various crop types. Without employing cloud masks and/or interpolation...

Abstract. An assessment of the spectral discrimination between different vine varieties was undertaken using non-destructive remote sensing observations at véraison period. During concurrent satellite, aerial and field campaigns, in-situ reflectance data were collected from a spectroradiometer, hyperspectral acquired UAV multispectral high-resolution satellite imaging sensor. Data during three years period (i.e, 2012, 2013 2014) over five wine-growing regions, covering more than 1000ha, in...

Space agencies, international and national organisations institutions recognize the importance of regularly updated homogenized land cover information, in context both nomenclature spatial resolution. Moreover, ensuring credibility to users through validated products with transparent procedures is similarly great importance. To this end, study contributes a systematic accuracy performance evaluation continental global layers. Confidence levels during validation weighted assessment were...

Abstract. In this work, we elaborate on the gained insights from various classification experiments towards detailed land cover mapping over four representative regions of different environmental characteristics in Greece. particular, proposed methodology exploits Sentinel-2 data at an annual basis, for joint 35 and crop type classes. A number pre-processing steps were employed satellite data, order to address atmospheric geometric effects, as well clouds pertinent shadows. Several set-ups...

Abstract. The need for effective crop monitoring in large geographical scales has become increasingly important recent years and constitutes a technological scientific challenge remote sensing applications. In Europe, member states of the European Union collect geospatial data framework Land Parcel Information System (LPIS) agricultural management subsidizing farmers. These can be exploited as training datasets machine learning classifiers crop-type mapping However, way LPIS are being...

In order to exploit operationally remote sensing data for agricultural applications efficient and automated methods are required towards the accurate detection of vegetation, crops different crop varieties. To this end, an object-based classification framework has been developed validated vineyards discrimination vine Very high resolution satellite were collected over four wine-growing regions in Greece during a three-year period, i.e., 2012 2014. A rule-based scheme based on fuzzy logic was...

Savannahs are vital ecosystems whose sustainability is endangered by the spread of woody plants. This research targets accurate mapping fractional cover (FWC) at species level in a South African savannah, using EnMAP hyperspectral data. Field annotations were combined with very high-resolution multispectral drone data to produce land maps that included three species. The labelled then used generate FWC samples for each class 30-m spatial resolution EnMAP. Four machine learning regression...

The detailed, accurate and frequent land cover crop-type mapping emerge as essential for several scientific communities geospatial applications. This paper presents a methodology the semi-automatic production of crop type maps using highly analytic nomenclature more than 40 classes. An intensive manual annotation procedure was carried out reference data. A class based on CORINE Level-3 employed along with additional Multitemporal surface reflectance Landsat-8 data year 2016 were used all...

Savannahs are under threat from land degradation, not least due to woody vegetation encroachment. Here, we target the accurate high-resolution mapping of fractional cover in a South African savannah region, and assess contribution optical (Sentinel-2, S2), radar (Sentinel-1, S1) ancillary data (bioclimatic soils). Firstly, created (FCW) samples based on very high resolution satellite imagery then performed several regression experiments using different combinations S1, S2 auxiliary temporal...

Abstract. Freely available satellite image time-series are currently the most exploited data towards land cover mapping. In this work we assess contribution of spectral and temporal features for detailed, i.e., with more than thirty classes, crop type mapping based on annual Sentinel-2 data. As a baseline employed datacube consisting features, bands indices from one tile Sentinel-2A year 2016. Then formed two different datacubes reduced dimensions, containing either spectrotemporal or...

Across globe and space agencies nations recognize the importance of homogenized land cover information, prone to regular updates, both in context thematic spatial resolutions. Recent sensor advances free distribution policy promote utilization spaceborne products an unprecedented pace into increasingly wider range applications. Ensuring credibility users is a major enabler this process. To end study contributes with systematic accuracy performance measurement continental/global layers'...