Jakub NowosadAdam Mickiewicz University | UAM · Institute of Geoecology and Geoinformation
Jakub Nowosad
PhD
https://jakubnowosad.com/
About
74
Publications
29,180
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975
Citations
Citations since 2017
Introduction
I am a computational geographer working at the intersection between geocomputation and the environmental sciences.
My research has focused on developing and applying spatial methods to broaden our understanding of processes and patterns in the environment.
Another vital part of my work is to create, collaborate on, and improve geocomputational software.
Additional affiliations
October 2018 - present
August 2016 - July 2018
Education
October 2012 - June 2016
Publications
Publications (74)
Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in g...
Context
Quantitative grouping of similar landscape patterns is an important part of landscape ecology due to the relationship between a pattern and an underlying ecological process. One of the priorities in landscape ecology is a development of the theoretically consistent framework for quantifying, ordering and classifying landscape patterns.
Obj...
Context
Pattern-based spatial analysis provides methods to describe and quantitatively compare spatial patterns for categorical raster datasets. It allows for spatial search, change detection, and clustering of areas with similar patterns.
Objectives
We developed an R package motif as a set of open-source tools for pattern-based spatial analysis....
There is a keen interest in calculating spatial associations between two variables spanning the same study area. Many methods for calculating such associations have been proposed, but the case when both variables are categorical is underdeveloped despite the fact that many datasets of interest are in the form of either regionalizations or thematic...
Spatio-ecological heterogeneity is strongly linked to many ecological processes and functions such as plant species diversity patterns and change, metapopulation dynamics, and gene flow. Remote sensing is particularly useful for measuring spatial heterogeneity of ecosystems over wide regions with repeated measurements in space and time. Besides, de...
![Values of potential insolation [Wh/m 2 ] before and after adding new TBs.](profile/Jakub-Nowosad/publication/368287171/figure/tbl2/AS:11431281118842181@1675879338768/Values-of-potential-insolation-Wh-m-2-before-and-after-adding-new-TBs_Q320.jpg)
Agroforestry systems support all categories of ecosystem services (ESs). In providing the regulating category of ESs, these systems have become an important strategy used to attenuate drought impacts and biodiversity losses on agricultural landscapes. Within the agroforestry design process aimed at ES provision, one of the agroforestry types used i...
Thermokarst lakes are the main components of the vast Arctic and subarctic landscapes. These lakes can serve as geoindicators of permafrost degradation; therefore, proper lake distribution assessment methods are necessary. In this study, we compared four machine learning methods to improve existing lake detection systems. The northern part of Yakut...
Maps represent powerful tools to show the spatial variation of a variable in a straightforward manner. A crucial aspect in map rendering for its interpretation by users is the gamut of colours used for displaying data. One part of this problem is linked to the proportion of the human population that is colour blind and, therefore, highly sensitive...
Geospatial data comes in various forms, including multi and hyperspectral images but also rasters of local composition, local time series, local patterns, etc. Thus, we generalize the SLIC algorithm to work with a library of different data distance measures that are pertinent to geospatial rasters. This contribution includes a description of the ge...
Converting an image to a set of superpixels is a useful preprocessing step in many computer vision applications; it reduces the dimensionality of the data and removes noise. The most popular superpixels algorithm is the Simple Linear Iterative Clustering (SLIC). To use original SLIC with non-imagery data (for example, rasters of discrete probabilit...
Categorical maps of landscape types (LTs) are useful abstractions that simplify spatial and thematic complexity of natural landscapes, thus facilitating land resources management. A local landscape arises from a fusion of patterns of natural themes (such as land cover, landforms, etc.), which makes an unsupervised identification and mapping of LTs...
The quantitative description of the soil surface roughness is necessary for effective monitoring of wind, water and tillage erosion, hydrological processes or greenhouse gas emissions. The aim of this work was to build soil roughness predictive models based on the type of tillage tool, the roughness indices and soil properties. The roughness formed...
The goal of waterquality is to convert satellite-reflectance imagery to a host of pre-defined water quality algorithms designed for the detection of chlorophyll-a, blue-green algae (Phycocyanin), and Turbidity. This package is able to process the following sensor configurations: WorldView-2, Sentinel-2, Landsat-8, MODIS, and MERIS sensors.
Purpose of Review
Landscape ecology, the study of the complex interactions between landscapes and ecological processes, has hugely benefited from the increase in widely available open-source software in recent years. In particular, the R programming language provides a wealth of community developed tools for landscape ecology.
Recent Findings
In t...
This article focuses on mapping tropical deforestation using time series and machine learning algorithms. Before detecting changes in the time series, we reduced seasonality using Photosynthetic Vegetation (PV) index fractions obtained from Landsat images. Single and multi-temporal filters were used to reduce speckle noise from Synthetic Aperture R...
Soil surveys and mapping with traditional methods are time-consuming and expensive especially in mountainous areas while demand for detailed soil information is steadily increasing. This study tested two spatial hybrid approaches to predict and map basic soil properties using high resolution digital elevation model (DEM) and multispectral satellite...
Ganoderma comprises a common bracket fungal genus that causes basal stem rot in deciduous and coniferous trees and palms, thus having a large economic impact on forestry production. We estimated pathogen abundance using long-term, daily spore concentration data collected in five biogeographic regions in Europe and SW Asia. We hypothesized that path...
Maps of landscape types (LTs) are useful abstractions that facilitate land resources management. However, their creation is difficult as local landscapes arise from a fusion of patterns of many natural themes. This paper introduces the integrated co-occurrence matrix (INCOMA)-a signature for numerical representation of multi-thematic categorical pa...
Categorical maps of landscape types (LTs) are useful abstractions that simplify spatial and thematic complexity of natural landscapes, thus facilitating land resources management. A local landscape arises from a fusion of patterns of natural themes (such as land cover, landforms, etc.), which makes an unsupervised identification and mapping of LTs...
Masz przed sobą skrypt zawierający materiały do ćwiczeń z geostatystyki. Składa się ona z kilkunastu rozdziałów pokazujących jak: wygląda geostatystyczna analiza danych (rozdział 1), dodawać i wizualizować dane przestrzenne w R (rozdział 2), wykonywać wstępną eksplorację danych nieprzestrzennych (rozdział 3), wstępnie analizować dane przestrzenne (...
*Context* Pattern-based spatial analysis provides methods to describe and quantitatively compare spatial patterns for categorical raster datasets. It allows for spatial search, change detection, and clustering of areas with similar patterns. *Objectives* We developed an R package **motif** as a set of open-source tools for pattern-based spatial ana...
Quantifying and effectively communicating the spatio-racial distribution of urban residencies is important for taking the measure of how the multiracial society organizes itself in an urban environment. Most currently used approaches to this problem center around the calculation of segregation metrics; as such, they pertain to only a single pattern...
Entropy is a fundamental concept in thermodynamics that is important in many fields, including image processing, neurobiology, urban planning, and sustainability. As of recently, the application of Boltzmann entropy for landscape patterns was mostly limited to the conceptual discussion. However, in the last several years, a number of methods for ca...
Quantifying and effectively communicating the spatio-racial distribution of urban residencies is important for taking the measure of how the multiracial society organizes itself in an urban environment. Most currently used approaches to this problem center around the calculation of segregation metrics; as such, they pertain to only a single pattern...
Elementarz programisty: Wstęp do programowania używając R ma na celu wprowadzenie do podstaw działania w języku R. W pierwszej części, “Podstawy”, opisuje ona w jaki sposób wykonywać proste operacje w R, czym są obiekty oraz jak tworzyć funkcje, które je przetwarzają. Ta część zawiera także omówienie podstawowych narzędzi pozwalających na sterowani...
Freely available and reliable meteorological datasets are highly demanded in many scientific and business applications. However, the structure of publicly available databases is often difficult to follow, especially for users who only deal with this kind of dataset on occasion. The "climate" R package aims to fill this gap with an easy-to-use inter...
Land change including deforestation undermines the sustainability of the environment. Using data on 1992‐2015 pattern change in over 1.7 million meso‐scale landscapes worldwide we developed a stochastic model of long‐term landscape dynamics. The model suggests that observed heterogeneous landscapes are short‐lived stages in a transition between qua...
Plain Language Summary
Land change across the world undermines the sustainability of the environment. Understanding the dynamics of landscape change would help to find trade‐offs between the development and sustainability of the environment. We developed a data‐driven model capable of providing plausible scenarios of long‐term evolution of landscap...
Satellite monitoring of cyanobacterial harmful algal blooms in small
freshwater lakes and reservoirs remains challenging. This is partly due to
the configurations and resolutions of commonly utilized satellite
imagers, which are traditionally designed for large terrestrial
applications. The purpose of this report is to provide an efficient
methodol...
Quantifying landscape characteristics and linking them to ecological processes is one of the central goals of landscape ecology. Landscape metrics are a widely used tool for the analysis of patch‐based, discrete land‐cover classes. Existing software to calculate landscape metrics has several constraints, such as being limited to a single platform,...
Landscape metrics are used to characterize landscape patterns and link them to ecological processes. Until now, there is no comprehensive collection of landscape metrics available in R. landscapemetrics is the first R package that includes most of the commonly employed landscape metrics found in the ecological literature. This allows reproducible a...
Monitoring global land cover changes is important because of concerns about their impact on environment and climate. The release by the European Space Agency (ESA) of a set of worldwide annual land cover maps covering the 1992–2015 period makes possible a quantitative assessment of land change on the global scale. While ESA land cover mapping effor...
Soil spectral characteristics from laboratory and in situ measurements are an effective source of information about various soil properties. However, features of scanned surfaces are unified by the drying and grounding of soil samples solely for laboratory measurements. Spectra scanned in situ are perturbed to varying degrees due to spatial variati...
Wydanie drugie "Geostatystyki w R". Aktualne wydanie można znaleźć pod adresem https://bookdown.org/nowosad/Geostatystyka/.
Geostatystyka w R jest skryptem zawierającym materiały do ćwiczeń z geostatystyki. Składa się ona z kilkunastu rozdziałów pokazujących jak:
- wygląda geostatystyczna analiza danych
- dodawać i wizualizować dane przestrzenne...
Airborne fungal spores are prevalent components of bioaerosols with a large impact on ecology, economy and health. Their major socioeconomic effects could be reduced by accurate and timely prediction of airborne spore concentrations. The main aim of this study was to create and evaluate models of Alternaria and Cladosporium spore concentrations bas...
Prediction of allergic pollen concentration is one of the most important goals of aerobiology. Past studies have used a broad range of modeling techniques; however, the results cannot be directly compared owing to the use of different datasets, validation methods, and evaluation metrics. The main aim of this study was to compare nine statistical mo...
Context: Comparing a large number of landscapes calls for using the smallest possible set of landscape metrics. The overall complexity of landscape pattern is the single most important metric, but the standard set of landscape metrics lacks the bona fide indicator of complexity.
Objective: Demonstrate that information theory provides a natural fram...
We present and evaluate a quantitative method for delineation of ecophysiographic regions throughout the entire terrestrial landmass. The method uses the new pattern-based segmentation technique which attempts to emulate the qualitative, weight-of-evidence approach to a delineation of ecoregions in a computer code. An ecophysiographic region is cha...
We present a regionalization of the entire Earth’s landmass into land units of homogeneous landscape patterns. The input to the regionalization is a high resolution Global Land Cover (GLC) dataset. The GLC is first divided into local landscapes – small non-overlapping square blocks of GLC cells. These blocks are agglomerated into much larger land u...
This study evaluated the performances of twenty-nine algorithms that use satellite-based spectral imager data to derive estimates of chlorophyll-a concentrations that, in turn, can be used as an indicator of the general status of algal cell densities and the potential for a harmful algal bloom (HAB). The performance assessment was based on making r...
There is a keen interest in inferring spatial associations between different variables spanning the same study area. We present a method for quantitative assessment of such associations in the case where spatial variables are either in the form of regionalizations or in the form of thematic maps. The proposed index of spatial association – called t...
Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial data can be obtained from airborne sensors and preprocessed gridded meteorological data, not many s...
Understanding of the behavior of atmospheric pollen concentration, as well as developing predictive models, can greatly help allergic sufferers. The aims of this study were (i) to determine mean multi-year characteristics of temporal and space–time autocorrelation of the pollen counts of Corylus, Alnus, and Betula in Poland, (ii) to create and eval...
GeoPAT 2 (Geospatial Pattern Analysis Toolbox) is a standalone suite of modules written in C and dedicated to analysis of large Earth Science datasets in their entirety using spatial and/or temporal patterns. Global scale, high resolution spatial datasets are available but are mostly used in small pieces for local studies. GeoPAT enables studying t...
We present and evaluate a quantitative method for delineation of ecophysigraphic regions throughout the entire terrestrial landmass. The method uses the new pattern-based segmentation technique which attempts to emulate the qualitative, weight-of-evidence approach to a delineation of ecoregions in a computer code. An ecophysiographic region is char...
We present a regionalization of the entire Earth’s landmass into land units of homogeneous landscape patterns. The input to the regionalization is a high resolution Global Land Cover (GLC) dataset. The GLC is first divided into local landscapes – small non-overlapping square blocks of GLC cells. These blocks are agglomerated into much larger land u...
Monitoring global land cover changes is important because of concerns about their impact on environment and climate. To enable such monitoring we present a global, GIS-based database of land cover changes during the 1992–2015 period. The database uses the new ESA global time series of land cover maps at 300m resolution (CCI-LC). The spatial unit of...
Complete global inventory of landscapes (patterns of land cover) is obtained by segmenta-tion/classification of the CCI-LC – a high resolution global land cover dataset. The CCI-LC is first segmented into a large number of small land units. The pattern of CCI-LC categories within each unit is tightly controlled by segmentation algorithm's merging p...
The aim of the study was to create and evaluate models for predicting high levels of daily pollen concentration of Corylus, Alnus, and Betula using a spatiotemporal correlation of pollen count. For each taxon, a high pollen count level was established according to the first allergy symptoms during exposure. The dataset was divided into a training s...
Corylus, Alnus, and Betula trees are among the most important sources of allergic pollen in the temperate zone of the Northern Hemisphere and have a large impact on the quality of life and productivity of allergy sufferers. Therefore, it is important to predict high pollen concentrations, both in time and space. The aim of this study was to create...
Wydanie pierwsze "Geostatystyki w R". Aktualne wydanie można znaleźć pod adresem https://bookdown.org/nowosad/Geostatystyka/.
The aim of the study was to create and evaluate different statistical models for reconstructing and predicting selected phenological phases. This issue is of particular importance in Poland where national-wide phenological monitoring was abandoned in the middle of 1990s and the reactivated network was established in 2006. Authors decided to evaluat...
The aim of the study was to determine the characteristics of temporal and space–time autocorrelation of pollen counts of Alnus, Betula, and Corylus in the air of eight cities in Poland. Daily average pollen concentrations were monitored over 8 years (2001–2005 and 2009–2011) using Hirst-designed volumetric spore traps. The spatial and temporal cohe...
One of the goals of geomorphometry is an automatic classification of terrain. Automatic classification is much faster than manual mapping and the results are based on clearly defined rules. On the other hand automatic algorithm does not possess human " knowledge " about numerous hidden relations between entities in the data which leads to classific...
We present the results of a numerical experiment aiming at explaining reasons for classification errors when using an automatic pattern-based terrain classifications algorithm proposed by Jasiewicz et. al. [3]. We use composition of landform elements from incorrectly classified areas, and we use texture pattern from example areas to synthesize a ne...
The basic aim of this study was to find relations between the dates of occurrence and characteristics of exten-sive extreme daily (24-h) precipitation totals (EEDPTs) and pressure systems. The analysis was conducted on the basis of precipitation data from the multi-year period 1956-1980 and the Grosswetterlagen classification of circulation situa-t...
Projects
Projects (4)
The subject of the project is to carry out R&D works on a product that is innovative on a national scale - an IT service for the optimization of agricultural crop productivity management using satellite imagery, based on personalized GIS services generated autonomously on the basis of artificial intelligence, available on a dedicated agricultural portal.
As a result of this R&D works, a prototype system will be developed at the IX TRL. The solution will operate on the basis of artificial intelligence and will be intended primarily for farmers, fertilizer producers, seed breeders and agricultural advisory centers.
The main goal of the project is to develop a new product - an IT service, the implement. of which will increase the competitiveness of the Project Leader - Poldrone Sp. z o.o. This goal will be achieved through the implementation by the Consortium, stages of the project (parameterized with milestones) and increasing the R&D
potential of the company through not only employment of R&D employees but, above all, cooperation with experienced research units.
As part of the project, industrial research will be carried out by the research workers of the Project Leader and members of the Consortium, aimed at acquiring new knowledge in many areas, including determining the potential of cultivation sites, controlling the production potential of the crop, diagnosing the state of plant nutrition with nitrogen, determining nitrogen doses and forecasting yields. Then, experimental, development works will be carried out aimed at using the acquired new knowledge and its implementation in a market solution - an innovative IT service, available on a dedicated agricultural portal. As a result of the project, a prototype of the system will be developed at the IX technological readiness level.
The implement. of the project results will take place through the sale of an annual license, the size of which will depend on the number of hectares covered by the service.
This project was designed to better detect and quantify water quality parameters (Chl-a, PC, Turbidity) through the following a variety of software tools and options to conduct the following:
1. Explore relationships between remote sensing imagery and in situ measurements.
2. Test & validate remote sensing algorithms
3. Develop tools and approaches to better automate workflows
The main challenge of modern agriculture is increasing production while reducing the pressure on the environment. This can be achieved by improving the management of water and nitrogen which are the main factors of agricultural production. Taking up this challenge would require a quick and effective diagnosis of the nitrogen nutrition status of plants in the principal stages of crop formation. Accomplishing this task requires using effective diagnostic tools in order to assess the nutritional status of plants during the growing season, as well as determining the corrective doses of nitrogen and performing the task.
The diagnostic tools used to assess the nitrogen nutrition status that are currently available are not effective. Fundamental errors arise from the point sampling (low spatial representativeness) and long analysis time, and are in fact affected by the forecast error. Such limitations can be eliminated through the use of remote sensing techniques. These methods consist of registering the electromagnetic radiation (solar radiation) reflected from the surface of the soil and plants.
The aim of the research is to develop and validate methods and tools that increase the efficiency of the means of production, mainly nitrogen, maintaining the established level or/and increase in crop yields, while improving the quality of the environment, in regard not only to nitrogen, but also the increase of CO2 in the biomass of plants (physiological sequestration). The results of industrial research will be compiled in a consolidated set of guidelines and methodological approaches to be implemented in the dedicated IT system prototype at the development stage. This will allow to use the developed algorithms in a subsequent commercial solution which will disseminate the use of knowledge about the growth rate control and the needs of crops at critical phases of growth, available so far only to scientific research institutes.