A first assessment of the Sentinel-2 Level 1-C cloud mask product to support informed surface analyses

Abstract Cloud detection in optical remote sensing images is a crucial problem because undetected clouds can produce misleading results in the analyses of surface and atmospheric parameters. Sentinel-2 provides high spatial resolution satellite data distributed with associated cloud masks. In this paper, we evaluate the ability of Sentinel-2 Level-1C cloud mask products to discriminate clouds over a variety of biogeographic scenarios and in different cloudiness conditions. Reference cloud masks for the identification of misdetection were generated by applying a local thresholding method that analyses Sentinel-2 Band 2 (0.490 μm) and Band 10 (1.375 μm) separately; histogram-based thresholds were locally tuned by checking the single bands and the natural color composite (B4B3B2); in doubtful cases, NDVI and DEM were also analyzed to refine the masks; the B2B11B12 composite was used to separate snow. The analysis of the cloud classification errors obtained for our test sites allowed us to get important inferences of general value. The L1C cloud mask generally underestimated the presence of clouds (average Omission Error, OE, 37.4%); this error increased (OE > 50%) for imagery containing opaque clouds with a large transitional zone (between the cloud core and clear areas) and cirrus clouds, fragmentation emerged as a major source of omission errors (R2 0.73). Overestimation was prevalently found in the presence of holes inside the main cloud bodies. Two extreme environments were particularly critical for the L1C cloud mask product. Detection over Amazonian rainforests was highly inefficient (OE > 70%) due to the presence of complex cloudiness and high water vapor content. On the other hand, Alpine orography under dry atmosphere created false cirrus clouds. Altogether, cirrus detection was the most inefficient. According to our results, Sentinel-2 L1C users should take some simple precautions while waiting for ESA improved cloud detection products

Exploring the Use of Sentinel-2 Data to Monitor Heterogeneous Effects of Contextual Drought and Heatwaves on Mediterranean Forests

The use of satellite data to detect forest areas impacted by extreme events, such as droughts, heatwaves, or fires is largely documented, however, the use of these data to identify the heterogeneity of the forests’ response to determine fine scale spatially irregular damage is less explored. This paper evaluates the health status of forests in southern Italy affected by adverse climate conditions during the hot and dry summer of 2017, using Sentinel-2 images (10m) and in situ data. Our analysis shows that the post-event—NDVI (Normalized Difference Vegetation Index) decrease, observed in five experimental sites, well accounts for the heterogeneity of the local response to the climate event evaluated in situ through the Mannerucci and the Raunkiaer methods. As a result, Sentinel-2 data can be effectively integrated with biological information from field surveys to introduce continuity in the estimation of climate change impacts even in very heterogeneous areas whose details could not be captured by lower resolution observations. This integration appears to be a successful strategy in the study of the relationships between the climate and forests from a dynamical perspective

Investigating climate variability and long-term vegetation activity across heterogeneous Basilicata agroecosystems

The Basilicata region summarizes many basic features of the biogeographic complexity characterizing Mediterranean countries. The intricate geomorphology and the long history of human management generated the current landscapes, which include both high-value ecosystems and areas prone to desertification. Preserving goods and services provided by such composite land cover mosaics poses many problems due to the interference/overlap of diverse natural and anthropic factors which make the correct selection of relevant parameters and the interpretation of observational data rather difficult. Here, we study interconnections between local climate and vegetation activity by correlating parameters characterizing the interannual statistics of the NDVI (Normalized Difference Vegetation Index), derived from satellite data, with a recently devised multivariate statistical index of meteoclimatic variability. We used a 15-year sequence of remote images concerning a set of plots located around meteorological ground stations of the central-eastern part of the region to pick up spatial structures in the vegetation–climate relationships. Our analyses were able to correlate spatial heterogeneity to variations in water exchanges between vegetation and atmosphere. This study represents a first step to improve the description of relevant processes to protect natural habitats and quality agriculture, therefore combating land degradation and climate change detrimental effects

L’industrializzazione dell’agricoltura nella Piana del Sele: una prospettiva geografica basata sull’Urban Atlas Copernicus

Il contributo nasce da un approccio interdisciplinare allo studio delle tra-sformazioni territoriali: ne sono autori, infatti, geografi, fisici e ingegneri ambientali esperti di telerilevamento. L’obiettivo è quello di studiare la recente espansione del capitalismo agricolo in una regione strategica per l’economia del Mezzogiorno: la Piana del Sele. In pochi anni, questo territorio a forte vocazione agri-cola ha conosciuto una drastica alterazione della copertura del suolo, che, se nel 2012 registrava un sostanziale equilibrio tra seminativi e serre, nel 2018, in appena sei anni, ha visto una crescita ponderosa delle serre a scapito proprio dei seminativi. È questa la conseguen-za dell’espansione della cosiddetta “quarta gamma” nel mercato or-tofrutticolo - esplosa anche in Italia nelle ultime due decadi – ovvero la produzione in serra di prodotti freschi, lavati e pronti al consumo. Si tratta di un fenomeno che, oltre alla valenza commerciale, ha dei riverberi geo-economici, sociali e ambientali di prim’ordine. In primo luogo, la penetrazione nei mercati locali dei grandi capitalisti agricoli; in secondo luogo, la riduzione della capacità degli ecosistemi di assi-curare beni e servizi; in terzo luogo, il depauperamento del paesaggio e il potenziale aumento del rischio idrogeologico. La metodologia d’indagine prevede l’analisi dei cambiamenti del-la land cover nei comuni di Battipaglia e Bellizzi, nella provincia di Salerno, nel segmento temporale 2012-2018 attraverso l’Urban Atlas Copernicus, realizzato utilizzando dati satellitari ad altissima risolu-zione. Attraverso il software InVEST, ai cambiamenti osservati è stata abbinata la quantificazione della perdita generata dalla riduzione dei beni e servizi ecosistemici.ritorial transformations: in fact, its authors are geographers, physicists and environmental engineers who are experts in remote sensing. The aim is to study the recent expansion of agricultural capitalism in a strategic region for the economy of the South: the Sele Plain. In just a few years, this territory with a strong agricultural vocation has experienced a drastic alteration of the land cover: in 2012 there was a substantial bal-ance between arable land and greenhouses, but in 2018, in just six years, there was a substantial growth of greenhouses own detriment of arable land. This is the consequence of the expansion of the so-called “fourth range” in the fruit and vegetable market - which has also grown up in Italy in the last two decades - or rather the greenhouse production of fresh, washed and ready-to-eat products. It is a phenomenon which, in addition to its commercial value, has first-rate geo-economic, social and environmental effects. First, the penetration of local markets by large ag-ricultural capitalists; secondly, the reduction of the ability of ecosystems to provide goods and services; thirdly, the depletion of the landscape and the potential increase in hydrogeological risk. The survey methodology involves the analysis of land cover changes in the municipalities of Battipaglia and Bellizzi, in the province of Salerno, in the 2012-2018 time span through the Urban Atlas Copernicus, created using very high resolution satellite data. Through the InVEST software, the observed changes were combined with the quantification of the loss generated by the reduction of the ecosystem goods and services

Monitoring the Impact of Rapid Urbanization on Land Surface Temperature and Assessment of Surface Urban Heat Island Using Landsat in Megacity (Lahore) of Pakistan

The present study focused on rapid urbanization due to the change in the existing landforms which has caused substantial adverse impacts on Urban Thermal Environment. In the present study, we have acquired the Landsat data (TM and OLI) for the years 1990, 2000, 2010, and 2020 to observe the land use changes (vegetation cover, built up land, barren land, and water) in Lahore using the supervised image classification method. Later, the impact of urbanization has been examined with Land Surface Temperature (LST) and eventually the Surface Urban Heat Island (SUHI) has been calculated. Accuracy of the classified images revealed an overall accuracy (Kappa co-efficient) of 95.3% (0.929%), 92.05% (0.870%), 89.7% (0.891%), and 85.8% (0.915%) for the years 1990, 2000, 2010, and 2020, respectively. It was found that vegetation cover decreased from 60.5% in 1990 to 47.7% in 2020 at the cost of urbanization. The overall built-up land increased by 23.52% from 1990 to 2020. Urbanization has influenced the LST, and it was examined that maximum LST consistently increased with increase in built-up land. The difference between urban and rural buffer reveals that SUHI has also been increasing over the years. SUHI has been raised from 1.72 C in 1990 to 2.41 C in 2020, and about 0.69 C relative change has been observed. It has also been observed that the Normalized Difference Vegetation Index (NDVI) and LST have an inverse relationship. The research outcomes of this study are useful for urban climatologists, urban planners, architects, and policymakers to devise climate resilient policies, structure, and decisions to balance the urban green spaces for a healthy urban environment

Investigating lost medieval villages using Satellite and Airborne Laser Scanning : the case of Yrsum in Basilicata (Southern Italy)

The phenomenon of lost villages in the late Middle Ages is a topic as complex as it is stimulating for historians and archaeologists. It raises many questions regarding the causes of the abandonment. To answer these questions, systematic studies are required along with detailed surveys of the investigated areas in order to detect the lost villages and to understand the relationships between sites and landscapes. In this context many problems arise, among them, for example, the detection and identification of anthropogenic and geomorphological features. This is a difficult task, especially for complex areas and settlements built on the top of hills and mountains, as in the case of Yrsum, located in the Basilicata Region (Southern Italy). In Yrsum, field work, the study of historical sources, the processing and interpretation of satellite imagery and DTM derived from Lidar survey, allowed us to reconstruct the urban shape of the village in its different functional and spatial components as well as to identify features linked to geomorphological pattern. This opens new investigation perspectives for both the assessment of endangerment of the cultural site and the study of the factors which caused the abandonment of this emblematic study case