Retrieval of Leaf Area Index (LAI) and Soil Water Content (WC) Using Hyperspectral Remote Sensing under Controlled Glass House Conditions for Spring Barley and Sugar Beet

Leaf area index (LAI) and water content (WC) in the root zone are two major hydro-meteorological parameters that exhibit a dominant control on water, energy and carbon fluxes, and are therefore important for any regional eco-hydrological or climatological study. To investigate the potential for retrieving these parameter from hyperspectral remote sensing, we have investigated plant spectral reflectance (400-2,500 nm, ASD FieldSpec3) for two major agricultural crops (sugar beet and spring barley) in the mid-latitudes, treated under different water and nitrogen (N) conditions in a greenhouse experiment over the growing period of 2008. Along with the spectral response, we have measured soil water content and LAI for 15 intensive measurement campaigns spread over the growing season and could demonstrate a significant response of plant reflectance characteristics to variations in water content and nutrient conditions. Linear and non-linear dimensionality analysis suggests that the full band reflectance information is well represented by the set of 28 vegetation spectral indices (SI) and most of the variance is explained by three to a maximum of eight variables. Investigation of linear dependencies between LAI and soil WC and pre-selected SI's indicate that: (1) linear regression using single SI is not sufficient to describe plant/soil variables over the range of experimental conditions, however, some improvement can be seen knowing crop species beforehand; (2) the improvement is superior when applying multiple linear regression using three explanatory SI's approach. In addition to linear investigations, we applied the non-linear CART (Classification and Regression Trees) technique, which finally did not show the potential for any improvement in the retrieval process

Vegetation Cover Analysis of Hazardous Waste Sites in Utah and Arizona Using Hyperspectral Remote Sensing

This study investigated the usability of hyperspectral remote sensing for characterizing vegetation at hazardous waste sites. The specific objectives of this study were to: (1) estimate leaf-area-index (LAI) of the vegetation using three different methods (i.e., vegetation indices, red-edge positioning (REP), and machine learning regression trees), and (2) map the vegetation cover using machine learning decision trees based on either the scaled reflectance data or mixture tuned matched filtering (MTMF)-derived metrics and vegetation indices. HyMap airborne data (126 bands at 2.3 x 2.3 m spatial resolution), collected over the U. S. Department of Energy uranium processing sites near Monticello, Utah and Monument Valley, Arizona, were used. Grass and shrub species were mixed on an engineered disposal cell cover at the Monticello site while shrub species were dominant in the phytoremediation plantings at the Monument Valley site. Regression trees resulted in the best calibration performance of LAI estimation (R-2 > 0.80. The use of REPs failed to accurately predict LAI (R-2 < 0.2). The use of the MTMF-derived metrics (matched filter scores and infeasibility) and a range of vegetation indices in decision trees improved the vegetation mapping when compared to the decision tree classification using just the scaled reflectance. Results suggest that hyperspectral imagery are useful for characterizing biophysical characteristics (LAI) and vegetation cover on capped hazardous waste sites. However, it is believed that the vegetation mapping would benefit from the use of higher spatial resolution hyperspectral data due to the small size of many of the vegetation patches (<1 m) found on the sites.open111

Retrieval of Leaf Area Index (LAI) and Soil Water Content (WC) Using Hyperspectral Remote Sensing under Controlled Glass House Conditions for Spring Barley and Sugar Beet

Leaf area index (LAI) and water content (WC) in the root zone are two major hydro-meteorological parameters that exhibit a dominant control on water, energy and carbon fluxes, and are therefore important for any regional eco-hydrological or climatological study. To investigate the potential for retrieving these parameter from hyperspectral remote sensing, we have investigated plant spectral reflectance (400–2,500 nm, ASD FieldSpec3) for two major agricultural crops (sugar beet and spring barley) in the mid-latitudes, treated under different water and nitrogen (N) conditions in a greenhouse experiment over the growing period of 2008. Along with the spectral response, we have measured soil water content and LAI for 15 intensive measurement campaigns spread over the growing season and could demonstrate a significant response of plant reflectance characteristics to variations in water content and nutrient conditions. Linear and non-linear dimensionality analysis suggests that the full band reflectance information is well represented by the set of 28 vegetation spectral indices (SI) and most of the variance is explained by three to a maximum of eight variables. Investigation of linear dependencies between LAI and soil WC and pre-selected SI’s indicate that: (1) linear regression using single SI is not sufficient to describe plant/soil variables over the range of experimental conditions, however, some improvement can be seen knowing crop species beforehand; (2) the improvement is superior when applying multiple linear regression using three explanatory SI’s approach. In addition to linear investigations, we applied the non-linear CART (Classification and Regression Trees) technique, which finally did not show the potential for any improvement in the retrieval process

Spatial data harmonization in the context of INSPIRE directive on the example of hydrographic map of Poland at a scale of 1:10 000

Dyrektywa INSPIRE ustanawiająca ramowe podstawy w zakresie infrastruktury informacji przestrzennej (SDI) definiuje założenia funkcjonowania polityki wspólnotowej w tym zakresie, m.in. odnośnie publicznego dostępu do danych. Ponadto Dyrektywa wprowadza podział zbiorów danych przestrzennych oraz ich klasyfikację zgodnie z tematami załącznika I. W zależności od przynależności do tematu, zaawansowania zasobu oraz dostępności danych, zbiory danych przestrzennych różnicują się w zakresie interoperacyjności. Opracowana Mapa Podziału Hydrograficznego Polski w skali 1:10 000 wpisuje się w założenia i wytyczne Dyrektywy realizując zobowiązania Polski w ramach tematu Hydrografia. Artykuł opisuje uwarunkowania realizacyjne projektu w kontekście zgodności i spójności danych przestrzennych z Dyrektywą INSPIRE. Poddano analizie modele danych MPHP10 oraz INSPIRE, wskazując główne różnice. Następnie opisano główne etapy procesu, poczynając od budowy modeli mapujących obie struktury, a kończąc na migracji danych.The INSPIRE Directive establishes a framework for spatial information infrastructure (SDI) in the European Union and defines the main policy goals across the EU, among others in terms of public access to data. The Hydrographic Map of Poland at the 1:10 000 scale fits the guidelines and framework of the Directive, fulfilling Polish obligations under the theme Hydrography. This paper describes conditions for execution of the MPHP10 project in the context of consistency and compatibility of spatial data with the INSPIRE Directive. The data models of MPHP10 and INSPIRE have been analyzed, indicating major differences. The paper then describes the main stages of the process, starting from construction of models mapping both data structures and ending with data migration

Adapting and using of the Topographic Objects Datebase for Development of Hydrographic Map of Poland AT 1:10 000 scale

Artykuł jest zbiorem wniosków wynikających z doświadczeń zebranych w ramach projektu „Opracowanie Mapy Podziału Hydrograficznego Polski w skali 1:10 000” (MPHP10). Po raz pierwszy do aktualizacji MPHP wykorzystano dostępne dane przestrzenne zgromadzone w CODGiK takie jak: NMT, BDOT (Baza Danych Obiektów Topograficznych), ortofotomapa i mapa topograficzna w skali 1:10 000. Wykorzystanie zasobów Państwowych na cele opracowania mapy hydrograficznej wymagało przygotowania danych wejściowych. W niniejszym artykule omówione zostały prace przygotowawcze z zakresu adaptacji atrybutowej i geometrycznej danych BDOT. Opisane modyfikacje nadają danym kartograficznym cechy typowe dla danych hydrograficznych. Wnioski końcowe mają charakter zaleceń, które mogłyby stanowić uzupełnienie Wytycznych Technicznych do wykonania Bazy Danych Topograficznych (TBD) w zakresie pozyskiwania klas związanych z wodą.This paper is a result of a series of experiments within the project “Development of the Hydrographic Map of Poland at 1:10 000 scale”. For the first time, available spatial data from the resources of CODGiK were used for updating the Hydrographic Map of Poland such as Digital Elevation Model (NMT), Topographic Objects Database, orthophotomap and topographic map at 1:10 000 scale. To use the national resources for development of hydrographic map the input data had to be prepared. This paper describes attribute and geometric adaptation of data from the Topographic Objects Database. Described modifications give cartographic data typical features of hydrographic data. Recommendations in the conclusion may be also considered as complement to the technical guidelines for production works of Topographic Objects Database

Digital geomorphological map of Karpaty Mts

The paper discusses the principles governing the conversion of an analogue, reference geomorphological map into a digital map. This was done using a fragment of the 1:500 000 Geomorphological Map of Poland published in 1984, with topical editorship provided by L. Starkel and cartographic layout by K. Trafas. For the purposes of the paper, the southern part of Poland, situated within the boundaries of the geographic macroregion of the Carpathins, was selected (Olędzki, 2007). The methodology of converting an analogue map into a digital map comprised the process of data collection, encoding and processing. In this process, we used the ArcInfo, ArcView, Arc Map and Erdas Imagine software. In effect, a map was created as well as a spatial database of geomorphological information. The nature of the input data, that is the existing analogue Geomorphological Map of Poland, determined the way the data were compiled. The map’s sheets were scanned, vectorised and encoded. The basic problem was to define the method of encoding and graphic marking of data in the digital map. The geomorphological content of the Digital Geomorphological Map of the Carpathians was expanded by an additional information layer, i.e. the raster underlay of the 1:500 000 Administrative Map of Poland, derived from the Atlas of the Republic of Poland

The hydrographic map of Poland at a scale of 1:10 000 – new thematic reference data for hydrography

Mapę Podziału Hydrograficznego Polski w skali 1:10 000 (MPHP10) opracowano w ramach projektu Informatyczny System Osłony Kraju przed Nadzwyczajnymi Zagrożeniami (ISOK). MPHP10 to jednolita, ciągła baza danych hydrograficznych obejmująca obszar całego kraju łącznie z częściami dorzecza Wisły i Odry położonymi poza jej granicami. Mapa ta zawiera charakterystykę geometryczną i opisową sieci rzecznej oraz zlewni. MPHP jest jedynym źródłem danych o granicach zlewni. MPHP jest podstawą do tworzenia różnych map tematycznych związanych z gospodarką wodną. Może być pomocna w bilansowaniu wodno gospodarczym, ocenie zasobów wodnych, ocenie przepływów i w konsekwencji symulowaniu ich zmian spowodowanych zmianami klimatu lub działaniami z zakresu gospodarki wodnej. Analizy takie można przeprowadzać w zadanych obszarach takich jak jednolite części wód, zlewnie. regiony wodne oraz dorzecza. Podstawą do utworzenia MPHP10 były warstwy zasobów Bazy Danych Obiektów Topograficznych. Materiał ten został zweryfikowany przez hydrografów. Dzięki temu utworzona mapa numeryczna jest materiałem, który może uzupełnić bądź poprawić zasób geodezyjny w zakresie nazewnictwa cieków i zbiorników wodnych oraz przebiegu, lokalizacji źródeł i ujść cieków. Wymagać to będzie konsultacji między odpowiedzialnymi instytucjami oraz zmiany obowiązujących przepisów. MPHP jest jednym z referencyjnych zbiorów danych tworzących krajową infrastrukturę informacji przestrzennej. Dzięki dostosowaniu MPHP do standardów INSPIRE produkt ten ma taką samą strukturę jak zbiory danych hydrograficznych innych państw Unii Europejskiej. Zharmonizowany zbiór danych MPHP stanie się częścią europejskiej infrastruktury informacji przestrzennej. Pozwoli to dane pochodzące z MPHP10 łączyć z danymi z innych państw i tworzyć opracowania kartograficzne oraz prowadzić analizy przestrzenne o charakterze transgranicznym i paneuropejskim.Hydrographic Map of Poland at a scale of 1:10 000 (MPHP10) was developed under the project “IT System of the Country's Protection Against Extreme Hazards (ISOK)”. MPHP10 is a uniform, continuous hydrographic database covering the whole country, including the river basin of the Vistula and the Oder located outside the borders of Poland. MPHP10 comprises geometrical and descriptive characteristics of river systems and their catchments. It is the only source of data on catchment boundaries for Poland. MPHP10 is a proper basis for creating a variety of thematic maps related to water management. It can assist in carrying out analyses such as economic water balance, water resources assessment, assessment of river flow and, in consequence, simulate changes in the foregoing, caused by climate change or activities in the area of water management. Such an analysis can be performed in selected areas such as water bodies, catchments, water regions and river basins. Geometric basis of MPHP10 provide data sets adopted from the Database of Topographic Objects (BDOT). This material has been analyzed, reviewed and transformed by hydrographers. Therefore MPHP10 is a proper reference to be used for complementing or improving the geodetic data in the following areas: geographic names of rivers, lakes and artificial reservoirs, courses of streams and rivers, location of springs and estuaries. In such cases, additional consultations between responsible bodies and changes in existing law will be required. MPHP10 is one of the reference data sets creating the Spatial Information Infrastructure in Poland. By adopting INSPIRE standards, this product has been structured in the same way as hydrographic data sets of other countries in the European Union. A harmonized set of MPHP data will become a part of the Infrastructure for Spatial Information in Europe. This will allow the data from MPHP10 to be combined with data from other countries to create cartographic products and to conduct cross-border and pan-European spatial analysis