Terra Modis

Mamy ogromną przyjemność oddać do rąk czytelnika długo oczekiwaną publikację prezentującą opracowania użytkowników licencji SITE oprogramowania ArcGIS na Uniwersytecie Warszawskim. Wspólną i spójną tematyką niniejszego wydania jest wykorzystanie technik Systemów Informacji Przestrzennej (GIS) w różnych dziedzinach: zaczynając od nauk przyrodniczych i kończąc na cyfrowej humanistyce. Niniejsza publikacja, choć nieco w innej odsłonie, stanowi kontynuację pomysłu stworzenia forum wymiany informacji na UW prowadzącego do rozwoju i upowszechniania warsztatu badawczego wykorzystującego narzędzia GIS w różnych dziedzinach nauki. W zamyśle ma zachęcać do propagowania interdyscyplinarności
projektów realizowanych na Uczelni. Pierwszy tom serii, pod redakcją Jerzego Lechnio, powstał w 2015 i nosił tytuł „GIS w UW. Pierwsze forum użytkowników licencji edukacyjnej SITE oprogramowania ArcGIS na Uniwersytecie Warszawskim. Materiały pokonferencyjne„. Stanowił bardzo ciekawą relację z postępów prac studentów i doktorantów, którzy wzięli udział w pierwszej ogólnouniwersyteckiej konferencji Forum Użytkowników Licencji SITE oprogramowania ArcGIS na Uniwersytecie Warszawskim. Konferencja ta, w założeniu jako impreza cykliczna,  ostała zainicjowana przez Wydział Geografii i Studiów Regionalnych UW i odbyła się po raz pierwszy 6 lutego 2014 roku. Konwencję „Forum” zaproponował wówczas mgr Jerzy Lechnio i dr Maciej Lenartowicz
Niniejsze wydanie zawiera owoce prac dwóch kolejnych edycji konferencji: drugiej zorganizowanej na Wydziale Geologii UW (w dniu 18 lutego 2015 roku), oraz trzeciej, która odbyła się w Instytucie Archeologii UW (10-12 grudnia 2015 roku). Sprawozdania z wspomnianych konferencji zostały włączone do niniejszego woluminu. Niniejsza publikacja zawiera przede wszystkim artykuły prezentujące wybrane i najciekawsze wystąpienia z dwóch kolejnych konferencji, a stąd  zachowuje porządek chronologiczny, czyli podział na tom II i III.
Wspomniane tomy obejmują ogółem dwanaście artykułów. Ich tematyka koncentruje się na takich zagadnieniach, jak: GIS w badaniach środowiskowych, zróżnicowanie tematyczne i rola danych przestrzennych w nauce i praktyce oraz komunikacji społecznej, analiza zdjęć satelitarnych i jej zastosowania, GIS w archeologii i humanistyce. Szerokie spektrum poruszanych tematów i różnorodność zastosowań technik GIS świadczą o dużych kompetencjach i potencjale absolwentów
UW na rynku pracy.
Artykuły poświęcone zastosowaniu metod i technik GIS w ocenie stanu środowiska poruszają problemy istotne z perspektywy Polski, jak i skali globu. Ich zanieczyszczenia wód podziemnych, ewapotranspiracji (parowanie z powierzchni gruntu), analiz przepuszczalność gruntu w miastach, problematyki globalnego ocieplenia, podatność lasów na uszkodzenia silnym wiatrem, czy też procesów urbanizacji.
Przykłady wykorzystania analiz zdjęć satelitarnych obejmują zarówno analizy bazujące na zastosowaniach wysokiej rozdzielczości zobrazowań panchromatycznych CORONA, jak i multispektralnych z misji Landsat i Worldview-2.
Ważnym zagadnieniem poruszanym przez autorów jest kwestia dostępności danych z zasobów publicznych, w tym Centralnej Bazy Danych Geologicznych, bazy otworów geologicznych PITAKA, Corine Land Cover i Urban Atlas. W wspomnianym nurcie mieści się prezentacja projektu udostępniania danych geograficznych w postaci Regionalizacji geomorfologicznej Karpat.
W publikacji znajdziemy, również przykłady zastosowań technologii GIS w dokumentacji archeologicznej, które rozwijane są z powodzeniem w Uniwersytecie Warszawskim.
Prezentowane opracowania obejmują przede wszystkim wyniki prac magisterskich i licencjackich studentów i absolwentów oraz badań bardziej doświadczonych badaczy z UW. Dowodzą dobitnie, że na naszych oczach dokonuje się rewolucja za sprawą szerokiego i multidyscyplinarnego wykorzystania metod i technik GIS oraz danych przestrzennych, która wpływa na pomnażanie wiedzy o otaczającym świecie, a także rozwój nowych pól badawczych w dziedzinie humanistyki, czy dystrybucję informacji w dobie społeczeństwa  informacyjnego.
Rangę publikacji podnosi fakt, że wszystkie z prezentowanych artykułów podlegały recenzji naukowej i opracowaniu redakcyjnemu.

Particulate matter (PM) measurements are important in air quality, public health, epidemiological studies and decision making for short and long-term policies implementation. However, only few cities in the word have advance air quality-monitoring networks able to provide reliable information of PM leaves in the ambient air, trends and extent of the pollution. In Colombia, only major cities measure PM concentrations. Available measurements from Bogota, Medel-lin and Bucaramanga show that PM concentration are well above World Health Organization guidelines, but up to now levels and trends of PM in other cities and regions of the country are not well known. Satellite measurements serve as an alternative approach to study air quality in regions were surface measurements are not available. The aim of this study is to perform a spatial and temporal assessment of PM in the ambient air of Colombia. We used Aerosol optical depth (AOD) retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite of NASA and surface measurements from the air quality networks of Bogota, Medellin and Bucaramanga. In a first step, we estimated the correlation between MODIS-AOD and monthly average surface measurements (2000 to 2015) from these three cities, obtaining correlation coefficient R values over 0.4 for the cities under study. After, we used AOD and PM 10 measurements to study the temporal evolution of PM in different cities and regions. Finally, we used AOD measurements to identify cities and regions with the highest AOD levels in Colombia. All the methods presented in this paper may serve as an example for other countries or regions to identify and prioritize locations that require the implementation of more accurate air quality measurements.

Dans le Sud du Chili, de nombreuses plantations forestières remplacent progressivement la plus grande forêt tempérée humide australe, connue pour sa biodiversité. L'objectif est de repérer et de cartographier ces plantations par le biais de données de télédétection : l'indice de végétation NDVI du satellite MODIS. Le profil temporel de cet indice permet de distinguer les coupes forestières et les incendies. Il est cartographié pour une partie montagneuse de cette zone (cordillère et précordillère littorales) et les résultats sont croisés avec diverses sources statistiques et cadastrales, et comparés à des relevés de terrain.
In southern Chile, large forest plantations have progressively replaced the largest temperate rainforest in the southern hemisphere, renowned for its biodiversity. This study aims to detect and map these plantations using remote sensing, MODIS NDVI data. The temporal profile of this vegetation index distinguishes between logging and forest fires. Southern Chile's coastal Cordillera and Precordillera have been mapped and the results compared with various statistical and cadastral data, as well as with field observations.

En el sur de Chile importantes superficies de plantaciones forestales sustituyen al bosque húmedo templado, particularmente rico en biodiversidad y el más extenso en el hemisferio sur. Este estudio busca detectar y cartografiar estas plantaciones utilizando datos de teledetección: el NDVI del satélite MODIS. El perfil temporal de este índice permite discriminar las cortas forestales y los incendios. Se realiza una cartografía sobre la cordillera y precordillera costeras continental del sur del país cuyos resultados son cruzados con diversas estadísticas, catastrales y relevamientos de terreno.

The average temperature of the world has increased by about 1.5 o C since 1850. This geographical phenomenon, called global warming or climate change, has certain consequences for the ecosystem. Scientists from different disciplines have started to work on this subject, in the last 50 years. Thus, climate change has become a multidisciplinary field in terms of the causes and consequences. Therefore, different methods, perspectives and data collection tools related to climate change have been developed. Remote Sensing systems that was developed after the 1970s provide data in many areas such as plant health, land use, climate events and disasters. By using climate related Remote Sensing data, studies carried out for the specify climate events, climate characteristics, determination of temporal changes, climate analyzes and models on the local and global scale. One of these data is surface temperatures. Surface temperatures are an important parameter used in understanding climate change and/or global warming. With the effect of global warming, surface temperatures are also increasing. Unlike climate stations, surface temperature data is obtained as a continuous surface. Thus, data can be collected in places where climate stations are not available. According to the changes in surface temperatures, climate change presents regional differences in the world. While the warming on Earth varies between 1.5-2 o C on average, this difference can reach 4-5 o C in Polar Regions. With the effect of the increase in surface temperatures in permafrost (frozen soils) regions, problems such as the thawing of the soils

The aim of this study was to evaluate the performance of the Aqua–MODIS (MYD04) Collections 5.1 (C051) and 6 (C006) operational aerosol products over Pakistan. These include the Dark Target (DT) and the Deep Blue (DB) C051/C006 aerosol optical depth (AOD) observations at 10 km spatial resolution, and which were validated using seven years (2007–2013) AOD measurements from two AERONET stations located in Pakistan’s two largest cities, Lahore and Karachi. Lahore is an inland city, consisting of built–up areas and agricultural land and dominated by mainly fine aerosol particles. Karachi is an urban–coastal city with built–up areas and bare land, and mainly affected by coarse aerosol particles. The retrieval uncertainties and accuracy were evaluated using the expected error over land (EE: ± 0.05 + 15%), the root–mean–square error (RMSE), the mean absolute error (MAE), and the relative mean bias (RMB). It was found that the DT C051 AOD retrievals were significantly overestimated over both AERONET sites with mean overestimation of 21% and 31% for Lahore and Karachi respectively. On the other hand, the DB C051 retrievals were underestimated by 10% and 35% for both cities. Similar to the DT C051, the C006 AOD retrievals were overestimated over Lahore, but significantly improved over Karachi as the mean overestimation reduced from 31% (RMB = 1.31) to 4% (RMB = 1.04) and the percentage of retrievals within the EE increased from 38.46% to 63.33%. However, the DB C006 AOD retrievals have similar errors (RMSE and MAE) and the percentage of retrievals within the EE over both cities as C051, but they have more mean underestimations. Spatio–temporal distributions showed that the DT and DB C006 were well correlated with Karachi and Lahore AERONET measurements respectively. Therefore, these results recommend the use of the DT C006 algorithm over Karachi and the DB C006 over Lahore for qualitative regional air quality applications due to differences in land cover characteristics and aerosol types.

Detailed data on land use and land cover constitute important information for Earth system models, environmental monitoring and ecosystem services research. Global land cover products are evolving rapidly; however, there is still a lack of information particularly for heterogeneous agricultural landscapes. We censused land use and land cover field by field in the agricultural mosaic catchment Haean in South Korea. We recorded the land cover types with additional information on agricultural practice. In this paper we introduce the data, their collection and the post-processing protocol. Furthermore, because it is important to quantitatively evaluate available land use and land cover products, we compared our data with the MODIS Land Cover Type product (MCD12Q1). During the studied period, a large portion of dry fields was converted to perennial crops. Compared to our data, the forested area was underrepresented and the agricultural area overrepresented in MCD12Q1. In addition, linear landscape elements such as waterbodies were missing in the MODIS product due to its coarse spatial resolution. The data presented here can be useful for earth science and ecosystem services research. The
data are available at the public repository Pangaea (doi:10.1594/PANGAEA.823677).

High spatio-temporal resolution optical remote sensing data provide unprecedented opportunities to monitor
and detect forest disturbance and loss. To demonstrate this potential, a 12-year time series (2000 to 2011)
with an 8-day interval of a 30 m spatial resolution data was generated by the use of the Spatial and Temporal
Adaptive Reflectance Fusion Model (STARFM) with Landsat sensor observations and Moderate Resolution Imaging
Spectroradiometer (MODIS) data as input. The time series showed a close relationship over homogeneous
forested and grassland sites, with r2 values of 0.99 between Landsat and the closest STARFM simulated data;
and values of 0.84 and 0.94 between MODIS and STARFM. The time and magnitude of clearing and re-clearing
events were estimated through a phenological breakpoint analysis, with 96.2% of the estimated breakpoints of
the clearing event and 83.6% of the re-clearing event being within 40 days of the true clearing. The study highlights
the benefits of using these moderate resolution data for quantifying and understanding land cover change
in open forest environments.

In the past decade, West Asia has witnessed more frequent and intensified dust storms affecting Iran and Persian Gulf countries. Employing a varying threshold that takes into account systematic differences between TOMS and OMI data, TOMS-OMI Aerosol Index data are used to identify long-term changes in the horizontal distribution of dust storms in West Asia from 1980 to present. The northwest of Iraq and east of Syria are identified as emerging dusty areas, whereas east of Saudi Arabia and southeast of Iraq are identified as permanent dusty areas, including both dust sources and affected areas. Whereas the frequency of dust events increased slightly in the permanent dusty areas, it increased markedly in the emerging dusty areas. As expected, the frequency of dust events is highest in June and July. The dust source areas are identified as the Iraq-Saudi Arabia boundary region and (recently) the northwest of Iraq, using MODIS deep blue aerosol optical depth data. Subsequently, a lagged correlation was implemented between identified dust sources and whole West Asia to determine the main paths and receptors of intense dust storms. Accordingly, southwest of Iran and Persian Gulf countries were determined as main receptors of summertime dust storms in West Asia. During spring, dust storms mostly hit the northern half of the region and reach to the Caspian Sea. Analyzing atmospheric patterns, Shamal and Frontal patterns were found as dominant atmospheric circulations simultaneous with summertime and springtime dust storms, respectively.

The Mekong Delta, located in Southern Vietnam, is one of the most affected areas in the world by climate change and sea level rises, especially flooding. Therefore, flood mapping is essential for understanding the flood regime and mitigating its impacts. Remote sensing and GIS can support the accurate and area wide evaluation of floods. In this study, high spatial resolution synthetic aperture radar (SAR) and optical data were used to generate a dense satellite data time series for analysing the spatio-temporal patterns of flooding in the Mekong Delta. To derive water masks, a total of 777 Sentinel-1, 515 Sentinel-2 and 57 Landsat-8 scenes were used to generate cloud free water masks at a 10m spatial resolution in regular 10-day intervals throughout the observation period of hydrological years 2016-2017. The results show a spatial explicit information on the core zones of the seasonal flooding processes for the entire Mekong Delta and their effect of using floodwater for rice cultivation. The outcome maps provide an overall understanding of Mekong Delta flood patterns and many valuable information for policymakers and water resources managers.

This paper presents a paddy growth stages classification using MODIS remote sensing images with support vector machines (SVMs). We collected the paddy growth stages data samples from a series of MODIS mages acquired from March to July 2012 along paddy field area only. The data are collected based on growth stages phenology of paddy using spectral profile which consists of at least 9 classes for growth stages and 2 classes for dominated soil and cloud. We apply SVMs to build a binary classifier for each class with one against all strategy of multiclass approach. One important issue needed to address is unbalanced prior probability that should be solved by each SVM. In this study, we evaluate the effectiveness of balanced branches strategy that is applied to one against all SVMs learning. Our result shows that the balanced branches strategy does improves in average around 10% classification accuracy during training and validation, and in average around 50% during testing. Index Terms-Remote sensing, MODIS images, classification, support vector machines (SVMs).