This page has only limited features, please log in for full access.

Dr. Ola Hall
Department of Human Geography, Faculty of Social Sciences, Lunds University, 223 62 Lund, Sweden

Basic Info


Research Keywords & Expertise

0 Satellite Imagery
0 Crop Modeling
0 Remote sensing (both satellite and drones)
0 The integration of household surveys
0 Machine learning algorithms in human development studies

Fingerprints

Satellite Imagery

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Preprint content
Published: 18 May 2021
Reads 0
Downloads 0

The standard narrative about inequality is that is ever increasing, but solid evidence to support this claim is often lacking, especially for poor countries and at subnational levels where data are scarce and poor. In this paper we use data from the Demographic and Health Survey for 34 countries in sub-Saharan Africa (SSA) and over 50000 villages surveyed since 1990. We use a wealth index developed by DHS researchers and Gini coefficients drawing on the same source together with remote sensing data. By means of a mixed model we conclude that human development, operationalized by the wealth index has tended to be associated with lower rather than higher inequality in SSA during the period covered.

ACS Style

OlaA Hall; Göran Djurfeldt; Niklas Boke Olén. Gini and wealth in 34 sub-Saharan African countries from 1990. 2021, 1 .

AMA Style

OlaA Hall, Göran Djurfeldt, Niklas Boke Olén. Gini and wealth in 34 sub-Saharan African countries from 1990. . 2021; ():1.

Chicago/Turabian Style

OlaA Hall; Göran Djurfeldt; Niklas Boke Olén. 2021. "Gini and wealth in 34 sub-Saharan African countries from 1990." , no. : 1.

Journal article
Published: 09 October 2020 in Sustainability
Reads 0
Downloads 0

Agricultural intensification based on smallholders is among many economists viewed as a necessary developmental path to ensure food security and poverty reduction in sub-Saharan Africa. Increasingly, a one-sided focus on raising productivity in cereals has been questioned on environmental grounds, with the concept of sustainable agricultural intensification (SAI) emerging from the natural sciences as a way of advancing environmental and social needs simultaneously. SAI approaches have, however, been criticized for being both conceptually and methodologically vague. This study combines socioeconomic survey data with remotely sensed land productivity data and qualitative data from four villages in Tanzania. By triangulating and comparing data collected through ground level surveys and ground-truthing with remote sensing data, we find that this combination of methods is capable of resolving some of the theoretical and methodological vagueness found in SAI approaches. The results show the problems of relying on only one type of data when studying sustainable agricultural intensification and indicate the poor environmental outcomes of cereal monocropping, even when social outcomes may be forthcoming. We identify land use practices that can be considered both socially and environmentally sustainable. Theoretically, we contribute to a further problematization of the SAI concept.

ACS Style

Agnes Andersson Djurfeldt; Ola Hall; Aida Isinika; Elibariki Msuya; Genesis Tambang Yengoh. Sustainable Agricultural Intensification in Four Tanzanian Villages—A View from the Ground and the Sky. Sustainability 2020, 12, 8304 .

AMA Style

Agnes Andersson Djurfeldt, Ola Hall, Aida Isinika, Elibariki Msuya, Genesis Tambang Yengoh. Sustainable Agricultural Intensification in Four Tanzanian Villages—A View from the Ground and the Sky. Sustainability. 2020; 12 (20):8304.

Chicago/Turabian Style

Agnes Andersson Djurfeldt; Ola Hall; Aida Isinika; Elibariki Msuya; Genesis Tambang Yengoh. 2020. "Sustainable Agricultural Intensification in Four Tanzanian Villages—A View from the Ground and the Sky." Sustainability 12, no. 20: 8304.

Review article
Published: 01 September 2020 in Population and Environment
Reads 0
Downloads 0

Human activity is a major driver of change and has contributed to many of the challenges we face today. Detailed information about human population distribution is fundamental and use of freely available, high-resolution, gridded datasets on global population as a source of such information is increasing. However, there is little research to guide users in dataset choice. This study evaluates five of the most commonly used global gridded population datasets against a high-resolution Swedish population dataset on a pixel level. We show that datasets which employ more complex modeling techniques exhibit lower errors overall but no one dataset performs best under all situations. Furthermore, differences exist in how unpopulated areas are identified and changes in algorithms over time affect accuracy. Our results provide guidance in navigating the differences between the most commonly used gridded population datasets and will help researchers and policy makers identify the most suitable datasets under varying conditions.

ACS Style

Maria Francisca Archila Bustos; Ola Hall; Thomas Niedomysl; Ulf Ernstson. A pixel level evaluation of five multitemporal global gridded population datasets: a case study in Sweden, 1990–2015. Population and Environment 2020, 42, 1 -23.

AMA Style

Maria Francisca Archila Bustos, Ola Hall, Thomas Niedomysl, Ulf Ernstson. A pixel level evaluation of five multitemporal global gridded population datasets: a case study in Sweden, 1990–2015. Population and Environment. 2020; 42 (2):1-23.

Chicago/Turabian Style

Maria Francisca Archila Bustos; Ola Hall; Thomas Niedomysl; Ulf Ernstson. 2020. "A pixel level evaluation of five multitemporal global gridded population datasets: a case study in Sweden, 1990–2015." Population and Environment 42, no. 2: 1-23.

Journal article
Published: 06 June 2020 in Agriculture
Reads 0
Downloads 0

Yield levels and the factors determining crop yields is an important strand of research on rainfed family farms. This is particularly true for Sub-Saharan Africa (SSA), which reports some of the lowest crop yields. This also holds for Ghana, where actual yields of maize, the most important staple crop, are currently about only a third of achievable yields. Developing a comprehensive understanding of the factors underpinning these yield levels is key to improving them. Previous research endeavours on this frontier have been incumbered by the mono-disciplinary focus and/or limitations relating to spatial scales, which do not allow the actual interactions at the farm level to be explored. Using the sustainable livelihoods framework and, to a lesser extent, the induced innovation theory as inspiring theoretical frames, the present study employs an integrated approach of multiple data sources and methods to unravel the sources of current maize yield levels on smallholder farms in two farming villages in the Eastern region of Ghana. The study relies on farm and household survey data, remotely-sensed aerial photographs of maize fields and photo-elicitation interviews (PEIs) with farmers. These data cover the 2016 major farming season that spanned the period March–August. We found that the factors that contributed to current yield levels are not consistent across yield measures and farming villages. From principal component analysis (PCA) and multiple linear regression (MLR), the timing of maize planting is the most important determinant of yield levels, explaining 25% of the variance in crop cut yields in Akatawia, and together with household income level, explaining 32% of the variance. Other statistically significant yield determinants include level of inorganic fertiliser applied, soil penetrability and phosphorus content, weed control and labour availability. However, this model only explains a third of the yields, which implies that two-thirds are explained by other factors. Our integrated approach was crucial in further shedding light on the sources of the poor yields currently achieved. The aerial photographs enabled us to demonstrate the dominance of poor crop patches on the edges and borders of maize fields, while the PEIs further improved our understanding of not just the causes of these poor patches but also the factors underpinning delayed planting despite farmers’ awareness of the ideal planting window. The present study shows that socioeconomic factors that are often not considered in crop yield analyses—land tenure and labour availability—often underpin poor crop yields in such smallholder rainfed family farms. Labour limitations, which show up strongly in both in the MLR and qualitative data analyses, for example, induces certain labour-saving technologies such as multiple uses of herbicides. Excessive herbicide use has been shown to have negative effects on maize yields.

ACS Style

Ibrahim Wahab; Magnus Jirström; Ola Hall. An Integrated Approach to Unravelling Smallholder Yield Levels: The Case of Small Family Farms, Eastern Region, Ghana. Agriculture 2020, 10, 206 .

AMA Style

Ibrahim Wahab, Magnus Jirström, Ola Hall. An Integrated Approach to Unravelling Smallholder Yield Levels: The Case of Small Family Farms, Eastern Region, Ghana. Agriculture. 2020; 10 (6):206.

Chicago/Turabian Style

Ibrahim Wahab; Magnus Jirström; Ola Hall. 2020. "An Integrated Approach to Unravelling Smallholder Yield Levels: The Case of Small Family Farms, Eastern Region, Ghana." Agriculture 10, no. 6: 206.

Letter
Published: 04 November 2019 in ISPRS International Journal of Geo-Information
Reads 0
Downloads 0

The traditional ways of measuring global sustainable development and economic development schemes and their progress suffer from a number of serious shortcomings. Remote sensing and specifically nighttime light has become a popular supplement to official statistics by providing an objective measure of human settlement that can be used as a proxy for population and economic development measures. With the increased availability and use of the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and data in social science, it has played an important role in data collection, including measuring human development and economic growth. Numerous studies are using nighttime light data to analyze dynamic regions such as expansions of urban areas and rapid industrialization often highlight the problem of saturation in urban centers with high light intensity. However, the quality of nighttime light data and its appropriateness for analyzing areas and regions with low and fluctuating levels of light have rarely been questioned or studied. This study examines the accuracy of DMSP-OLS and VIIRS-DNB by analyzing 147 communities in Burkina Faso to provide insights about problems related to the study of areas with a low intensity of nighttime light during the studied period from 1992 to 2012. It found that up to 57% of the communities studied were undetectable throughout the period, and only 9% of communities studied had a 100% detection rate. Unsurprisingly, the result provides evidence that detection rates in both datasets are particularly low (3%) for settlements with 0–9999 inhabitants, as well as for larger settlements with population of 10,000–24,999 (28%). Cross-checking with VIIRS-DNB for the year 2012 shows similar results. These findings suggest that careful consideration must be given to the use of nighttime light data in research and global comparisons to monitor the progress of the United Nation’s Sustainable Development Goals, especially when including developing countries with areas containing low electrification rates and low population density.

ACS Style

Magnus Andersson; Ola Hall; Maria Francisca Archila. How Data-Poor Countries Remain Data Poor: Underestimation of Human Settlements in Burkina Faso as Observed from Nighttime Light Data. ISPRS International Journal of Geo-Information 2019, 8, 498 .

AMA Style

Magnus Andersson, Ola Hall, Maria Francisca Archila. How Data-Poor Countries Remain Data Poor: Underestimation of Human Settlements in Burkina Faso as Observed from Nighttime Light Data. ISPRS International Journal of Geo-Information. 2019; 8 (11):498.

Chicago/Turabian Style

Magnus Andersson; Ola Hall; Maria Francisca Archila. 2019. "How Data-Poor Countries Remain Data Poor: Underestimation of Human Settlements in Burkina Faso as Observed from Nighttime Light Data." ISPRS International Journal of Geo-Information 8, no. 11: 498.

Data descriptor
Published: 28 October 2019 in Scientific Data
Reads 0
Downloads 0

Knowledge about the past, current and future distribution of the human population is fundamental for tackling many global challenges. Censuses are used to collect information about population within a specified spatial unit. The spatial units are usually arbitrarily defined and their numbers, size and shape tend to change over time. These issues make comparisons between areas and countries difficult. We have in related work proposed that the shape of the lit area derived from nighttime lights, weighted by its intensity can be used to analyse characteristics of the population distribution, such as the mean centre of population. We have processed global nighttime lights data for the period 1992–2013 and derived centroids for administrative levels 0–2 of the Database of Global Administrative Areas, corresponding to nations and two levels of sub-divisions, that can be used to analyse patterns of global or local population changes. The consistency of the produced dataset was investigated and distance between true population centres and derived centres are compared using Swedish census data as a benchmark.

ACS Style

Ola Hall; Maria Francisca Archila Bustos; Niklas Boke Olén; Thomas Niedomysl. Population centroids of the world administrative units from nighttime lights 1992-2013. Scientific Data 2019, 6, 1 -8.

AMA Style

Ola Hall, Maria Francisca Archila Bustos, Niklas Boke Olén, Thomas Niedomysl. Population centroids of the world administrative units from nighttime lights 1992-2013. Scientific Data. 2019; 6 (1):1-8.

Chicago/Turabian Style

Ola Hall; Maria Francisca Archila Bustos; Niklas Boke Olén; Thomas Niedomysl. 2019. "Population centroids of the world administrative units from nighttime lights 1992-2013." Scientific Data 6, no. 1: 1-8.

Journal article
Published: 11 October 2019 in Agriculture
Reads 0
Downloads 0

Site-specific land management practice taking into account variability in maize yield gaps (the difference between yields in the 90th percentiles and other yields on smallholder farmers’ fields) could improve resource use efficiency and enhance yields. However, the applicability of the practice is constrained by inability to identify patterns of resource utilization to target application of resources to more responsive fields. The study focus was to map yield gaps on smallholder fields based on identified spatial arrangements differentiated by distance from the smallholder homestead and understand field-specific utilization of production factors. This was aimed at understanding field variability based on yield gap mapping patterns in order to enhance resource use efficiency on smallholder farms. The study was done in two villages, Mukuyu and Shikomoli, with high and low agroecology regarding soil fertility in Western Kenya. Identification of spatial arrangements at 40 m, 80 m, 150 m and 300 m distance from the homestead on smallholder farms for 70 households was done. The spatial arrangements were then classified into near house, mid farm and far farm basing on distance from the homestead. For each spatial arrangement, Landsat sensors acquired via satellite imagery were processed to generate yield gap maps. The focal statistics analysis method using the neighborhoods function was then applied to generate yield gap maps at the different spatial arrangements identified above. Socio-economic, management and biophysical factors were determined, and maize yields estimated at each spatial arrangement. Heterogeneous patterns of high, average and low yield gaps were found in spatial arrangements at the 40 m and 80 m distances. Nearly homogenous patterns tending towards median yield gap values were found in spatial arrangements that were located at the 150 m and 300 m. These patterns correspondingly depicted field-specific utilization of management and socio-economic factors. Field level management practices and socio-economic factors such as application of inorganic fertilizer, high frequency of weed control, early land preparation, high proportion of hired and family labor use and allocation of large land sizes were utilized in spatial arrangements at 150 and 300 m distances. High proportions of organic fertilizer and family labor use were utilized in spatial arrangements at 40 and 80 m distances. The findings thus show that smallholder farmers preferentially manage the application of socio-economic and management factors in spatial arrangements further from the homestead compared to fields closer to the homestead which could be exacerbating maize yield gaps. Delineating management zones based on yield gap patterns at the different spatial arrangements on smallholder farms could contribute to site-specific land management and enhance yields. Investigating the value smallholder farmers attach to each spatial arrangement is further needed to enhance the spatial understanding of yield gap variation on smallholder farms.

ACS Style

Munialo Sussy; Hall Ola; Francisca Archila Bustos Maria; Boke-Olén Niklas; Onyango M. Cecilia; Oluoch-Kosura Willis; Marstorp Håkan; Göran Djurfeldt. Micro-Spatial Analysis of Maize Yield Gap Variability and Production Factors on Smallholder Farms. Agriculture 2019, 9, 219 .

AMA Style

Munialo Sussy, Hall Ola, Francisca Archila Bustos Maria, Boke-Olén Niklas, Onyango M. Cecilia, Oluoch-Kosura Willis, Marstorp Håkan, Göran Djurfeldt. Micro-Spatial Analysis of Maize Yield Gap Variability and Production Factors on Smallholder Farms. Agriculture. 2019; 9 (10):219.

Chicago/Turabian Style

Munialo Sussy; Hall Ola; Francisca Archila Bustos Maria; Boke-Olén Niklas; Onyango M. Cecilia; Oluoch-Kosura Willis; Marstorp Håkan; Göran Djurfeldt. 2019. "Micro-Spatial Analysis of Maize Yield Gap Variability and Production Factors on Smallholder Farms." Agriculture 9, no. 10: 219.

Journal article
Published: 16 August 2018 in Drones
Reads 0
Downloads 0

The application of remote sensing methods to assess crop vigor and yields has had limited applications in Sub-Saharan Africa (SSA) due largely to limitations associated with satellite images. The increasing use of unmanned aerial vehicles in recent times opens up new possibilities for remotely sensing crop status and yields even on complex smallholder farms. This study demonstrates the applicability of a vegetation index derived from UAV imagery to assess maize (Zea mays L.) crop vigor and yields at various stages of crop growth. The study employs a quadcopter flown at 100 m over farm plots and equipped with two consumer-grade cameras, one of which is modified to capture images in the near infrared. We find that UAV-derived GNDVI is a better indicator of crop vigor and a better estimator of yields—r = 0.372 and r = 0.393 for mean and maximum GNDVI respectively at about five weeks after planting compared to in-field methods like SPAD readings at the same stage (r = 0.259). Our study therefore demonstrates that GNDVI derived from UAV imagery is a reliable and timeous predictor of crop vigor and yields and that this is applicable even in complex smallholder farms in SSA.

ACS Style

Ibrahim Wahab; Ola Hall; Magnus Jirström. Remote Sensing of Yields: Application of UAV Imagery-Derived NDVI for Estimating Maize Vigor and Yields in Complex Farming Systems in Sub-Saharan Africa. Drones 2018, 2, 28 .

AMA Style

Ibrahim Wahab, Ola Hall, Magnus Jirström. Remote Sensing of Yields: Application of UAV Imagery-Derived NDVI for Estimating Maize Vigor and Yields in Complex Farming Systems in Sub-Saharan Africa. Drones. 2018; 2 (3):28.

Chicago/Turabian Style

Ibrahim Wahab; Ola Hall; Magnus Jirström. 2018. "Remote Sensing of Yields: Application of UAV Imagery-Derived NDVI for Estimating Maize Vigor and Yields in Complex Farming Systems in Sub-Saharan Africa." Drones 2, no. 3: 28.

Communication
Published: 22 June 2018 in Drones
Reads 0
Downloads 0

Yield estimates and yield gap analysis are important for identifying poor agricultural productivity. Remote sensing holds great promise for measuring yield and thus determining yield gaps. Farming systems in sub-Saharan Africa (SSA) are commonly characterized by small field size, intercropping, different crop species with similar phenologies, and sometimes high cloud frequency during the growing season, all of which pose real challenges to remote sensing. Here, an unmanned aerial vehicle (UAV) system based on a quadcopter equipped with two consumer-grade cameras was used for the delineation and classification of maize plants on smallholder farms in Ghana. Object-oriented image classification methods were applied to the imagery, combined with measures of image texture and intensity, hue, and saturation (IHS), in order to achieve delineation. It was found that the inclusion of a near-infrared (NIR) channel and red–green–blue (RGB) spectra, in combination with texture or IHS, increased the classification accuracy for both single and mosaic images to above 94%. Thus, the system proved suitable for delineating and classifying maize using RGB and NIR imagery and calculating the vegetation fraction, an important parameter in producing yield estimates for heterogeneous smallholder farming systems.

ACS Style

Ola Hall; Sigrun Dahlin; Håkan Marstorp; Maria Francisca Archila Bustos; Ingrid Öborn; Magnus Jirström. Classification of Maize in Complex Smallholder Farming Systems Using UAV Imagery. Drones 2018, 2, 22 .

AMA Style

Ola Hall, Sigrun Dahlin, Håkan Marstorp, Maria Francisca Archila Bustos, Ingrid Öborn, Magnus Jirström. Classification of Maize in Complex Smallholder Farming Systems Using UAV Imagery. Drones. 2018; 2 (3):22.

Chicago/Turabian Style

Ola Hall; Sigrun Dahlin; Håkan Marstorp; Maria Francisca Archila Bustos; Ingrid Öborn; Magnus Jirström. 2018. "Classification of Maize in Complex Smallholder Farming Systems Using UAV Imagery." Drones 2, no. 3: 22.

Articles
Published: 04 May 2018 in Journal of Land Use Science
Reads 0
Downloads 0

The aim of this paper is to combine remote sensing data with geo-coded household survey data in order to measure the impact of different socio-economic and biophysical factors on maize yields. We use multilevel linear regression to model village mean maize yield per year as a function of NDVI, commercialization, pluriactivity and distance to market. We draw on seven years of panel data on African smallholders, drawn from three rounds of data collection over a twelve-year period and 56 villages in six countries combined with a time-series analysis of NDVI data from the MODIS sensor. We show that, although there is much noise in yield forecasts as made with our methodology, socio-economic drivers substantially impact on yields, more, it seems, than do biophysical drivers. To reach more powerful explanations researchers need to incorporate socio-economic parameters in their models.

ACS Style

Göran Djurfeldt; Ola Hall; Magnus Jirström; Maria Archila Bustos; Björn Holmquist; Sultana Nasrin. Using panel survey and remote sensing data to explain yield gaps for maize in sub-Saharan Africa. Journal of Land Use Science 2018, 13, 344 -357.

AMA Style

Göran Djurfeldt, Ola Hall, Magnus Jirström, Maria Archila Bustos, Björn Holmquist, Sultana Nasrin. Using panel survey and remote sensing data to explain yield gaps for maize in sub-Saharan Africa. Journal of Land Use Science. 2018; 13 (3):344-357.

Chicago/Turabian Style

Göran Djurfeldt; Ola Hall; Magnus Jirström; Maria Archila Bustos; Björn Holmquist; Sultana Nasrin. 2018. "Using panel survey and remote sensing data to explain yield gaps for maize in sub-Saharan Africa." Journal of Land Use Science 13, no. 3: 344-357.

Book
Published: 15 February 2018 in Agrarian Change and Structural Transformation: Drivers and Distributional Outcomes
Reads 0
Downloads 0

This chapter examines agrarian changes triggered by the structural transformation of the overall economy, focusing on their drivers and distributional outcomes. By means of multi-level modelling of three processes—intensification of grain yields, diversification of cropping, and non-farm diversification (pluriactivity)—it concludes that intensification has moderately accelerated and is getting more important than its twin process. Similarly, crop diversification has accelerated, while non-farm diversification seems to be more pull- than push-driven. The most important drivers of the two first-mentioned processes are commercial ones: increasing local and domestic demand for grains and for other crops and institutional changes promoting market participation of smallholders. The chapter concludes that these processes are not pro-poor, but neither are they pro-rich; middling smallholder households tend to be more involved. The gender profile of agricultural diversification seems to involve and benefit male-managed farms, whereas non-farm diversification is gender neutral.

ACS Style

Agnes Andersson Djurfeldt; Göran Djurfeldt; Ola Hall; Maria Archila Bustos. Agrarian Change and Structural Transformation: Drivers and Distributional Outcomes. Agrarian Change and Structural Transformation: Drivers and Distributional Outcomes 2018, 1 .

AMA Style

Agnes Andersson Djurfeldt, Göran Djurfeldt, Ola Hall, Maria Archila Bustos. Agrarian Change and Structural Transformation: Drivers and Distributional Outcomes. Agrarian Change and Structural Transformation: Drivers and Distributional Outcomes. 2018; ():1.

Chicago/Turabian Style

Agnes Andersson Djurfeldt; Göran Djurfeldt; Ola Hall; Maria Archila Bustos. 2018. "Agrarian Change and Structural Transformation: Drivers and Distributional Outcomes." Agrarian Change and Structural Transformation: Drivers and Distributional Outcomes , no. : 1.

Journal article
Published: 15 February 2017 in Annals of the American Association of Geographers
Reads 0
Downloads 0
ACS Style

Thomas Niedomysl; Ola Hall; Maria Francisca Archila Bustos; Ulf Ernstson. Using Satellite Data on Nighttime Lights Intensity to Estimate Contemporary Human Migration Distances. Annals of the American Association of Geographers 2017, 107, 591 -605.

AMA Style

Thomas Niedomysl, Ola Hall, Maria Francisca Archila Bustos, Ulf Ernstson. Using Satellite Data on Nighttime Lights Intensity to Estimate Contemporary Human Migration Distances. Annals of the American Association of Geographers. 2017; 107 (3):591-605.

Chicago/Turabian Style

Thomas Niedomysl; Ola Hall; Maria Francisca Archila Bustos; Ulf Ernstson. 2017. "Using Satellite Data on Nighttime Lights Intensity to Estimate Contemporary Human Migration Distances." Annals of the American Association of Geographers 107, no. 3: 591-605.

Dataset
Published: 17 January 2017 in Scientific Data
Reads 0
Downloads 0

For its fifth assessment report, the Intergovernmental Panel on Climate Change divided future scenario projections (2005-2100) into two groups: Socio-Economic Pathways (SSPs) and Representative Concentration Pathways (RCPs). Each SSP has country-level urban and rural population projections, while the RCPs are based on radiative forcing caused by greenhouse gases, aerosols and associated land-use change. In order for these projections to be applicable in earth system models, SSP and RCP population projections must be at the same spatial scale. Thus, a gridded population dataset that takes into account both RCP-based urban fractions and SSP-based population projection is needed. To support this need, an annual (2000-2100) high resolution (approximately 1km at the equator) gridded population dataset conforming to both RCPs (urban land use) and SSPs (population) country level scenario data were created

ACS Style

Niklas Boke-Olén; Abdulhakim M. Abdi; Ola Hall; Veiko Lehsten. High-resolution African population projections from radiative forcing and socio-economic models, 2000 to 2100. Scientific Data 2017, 4, 160130 .

AMA Style

Niklas Boke-Olén, Abdulhakim M. Abdi, Ola Hall, Veiko Lehsten. High-resolution African population projections from radiative forcing and socio-economic models, 2000 to 2100. Scientific Data. 2017; 4 (1):160130.

Chicago/Turabian Style

Niklas Boke-Olén; Abdulhakim M. Abdi; Ola Hall; Veiko Lehsten. 2017. "High-resolution African population projections from radiative forcing and socio-economic models, 2000 to 2100." Scientific Data 4, no. 1: 160130.

Journal article
Published: 29 July 2015 in Geographical Research
Reads 0
Downloads 0

It has been 10 years since the Indian Ocean Tsunami caused serious damage to the coastal areas in South and Southeast Asia. The effects on vegetation and human settlements in the affected areas were enormous. This study presents the results of an analysis estimating the long‐term recovery using two longitudinal remotely sensed dataset: 1. Moderate Resolution Imaging Spectroradiometer enhanced vegetation index (MODIS EVI), a dataset accounting for change in the landscape and vegetation; and 2. Defense Meteorological Satellite Program‐Optical Line Scanner (DMSP‐OLS) night‐time light data in order to estimate the effects on human and economic activities. It is evident from the results of this study that the night‐time light and vegetation index datasets can both be beneficial in identifying changes caused by natural disasters and can be used to track recovery. The results using night‐time light indicates a large loss of lighted area but also a rapid recovery of night‐time light after the tsunami. Already in year 2005–2006, the levels of lighted area and sum of the lighting (SOL) intensity reached the same levels as pre‐tsunami. For MODIS vegetation index, a drop can be observed in 2005/2006 on locations close to the coastline using 1 year temporal resolution; however, when utilizing the 16 day temporal resolution, the impact of the tsunami is illustrated as a dramatic drop, mostly in pixels located within 3km from the coast. Following the drop in vegetation index due to the tsunami, it was observed that most pixels exhibited at least some level of recovery in 2 years after the event.

ACS Style

Magnus Andersson; Ola Hall; Maria Francisca Archila Bustos. Assessing Recovery from the 2004 Indian Ocean Tsunami: An Application of Night-time Light Data and Vegetation Index. Geographical Research 2015, 53, 436 -450.

AMA Style

Magnus Andersson, Ola Hall, Maria Francisca Archila Bustos. Assessing Recovery from the 2004 Indian Ocean Tsunami: An Application of Night-time Light Data and Vegetation Index. Geographical Research. 2015; 53 (4):436-450.

Chicago/Turabian Style

Magnus Andersson; Ola Hall; Maria Francisca Archila Bustos. 2015. "Assessing Recovery from the 2004 Indian Ocean Tsunami: An Application of Night-time Light Data and Vegetation Index." Geographical Research 53, no. 4: 436-450.

Journal article
Published: 14 March 2015 in Ambio
Reads 0
Downloads 0

Nighttime satellite photographs of Earth reveal the location of lighting and provide a unique view of the extent of human settlement. Nighttime lights have been shown to correlate with economic development and population but little research has been done on the link between nighttime lights and population change over time. We explore whether population decline is coupled with decline in lighted area and how the age structure of the population and GDP are reflected in nighttime lights. We examine Europe between the period of 1992 and 2012 using a Geographic Information System and regression analysis. The results suggest that population decline is not coupled with decline in lighted area. Instead, human settlement extent is more closely related to the age structure of the population and to GDP. We conclude that declining populations will not necessarily lead to reductions in the extent of land development.

ACS Style

Maria Francisca Archila Bustos; Ola Hall; Magnus Andersson. Nighttime lights and population changes in Europe 1992–2012. Ambio 2015, 44, 653 -665.

AMA Style

Maria Francisca Archila Bustos, Ola Hall, Magnus Andersson. Nighttime lights and population changes in Europe 1992–2012. Ambio. 2015; 44 (7):653-665.

Chicago/Turabian Style

Maria Francisca Archila Bustos; Ola Hall; Magnus Andersson. 2015. "Nighttime lights and population changes in Europe 1992–2012." Ambio 44, no. 7: 653-665.

Journal article
Published: 01 February 2015 in World Development
Reads 0
Downloads 0
ACS Style

Souknilanh Keola; Magnus Andersson; Ola Hall. Monitoring Economic Development from Space: Using Nighttime Light and Land Cover Data to Measure Economic Growth. World Development 2015, 66, 322 -334.

AMA Style

Souknilanh Keola, Magnus Andersson, Ola Hall. Monitoring Economic Development from Space: Using Nighttime Light and Land Cover Data to Measure Economic Growth. World Development. 2015; 66 ():322-334.

Chicago/Turabian Style

Souknilanh Keola; Magnus Andersson; Ola Hall. 2015. "Monitoring Economic Development from Space: Using Nighttime Light and Land Cover Data to Measure Economic Growth." World Development 66, no. : 322-334.

Book chapter
Published: 31 July 2014 in State and Environment
Reads 0
Downloads 0

This chapter examines the causes and consequences of stakeholder participation in natural resource management by presenting evidence from 143 biosphere reserves (BR) in fifty-five countries. In particular, it considers whether stakeholder participation in natural resource management programs leads to better management of ecosystems, and how the quality of democratic institutions and levels of corruption affects stakeholders' likelihood of participating in natural resource programs. After an overview of the possible reasons why stakeholders participate in the management of natural resources, the discussion shifts to political rights, with emphasis on the right to form associations and organizations. The chapter then explains the data and methods used in the survey of 143 BRs and analyzes patterns of stakeholder involvement in BR activities to the BR's management performance. The results show that institutional guarantees for political rights are about as important as a BR policy prioritizing combined social, economic, and ecological development in persuading non-governmental organizations and locals to get involved in BR implementation activities.

ACS Style

Andreas Duit; Ola Hall. Causes and Consequences of Stakeholder Participation in Natural Resource Management: Evidence from 143 Biosphere Reserves in Fifty-Five Countries. State and Environment 2014, 293 -320.

AMA Style

Andreas Duit, Ola Hall. Causes and Consequences of Stakeholder Participation in Natural Resource Management: Evidence from 143 Biosphere Reserves in Fifty-Five Countries. State and Environment. 2014; ():293-320.

Chicago/Turabian Style

Andreas Duit; Ola Hall. 2014. "Causes and Consequences of Stakeholder Participation in Natural Resource Management: Evidence from 143 Biosphere Reserves in Fifty-Five Countries." State and Environment , no. : 293-320.

Journal article
Published: 23 January 2012 in The Open Geography Journal
Reads 0
Downloads 0

From Census to Grids: Comparing Gridded Population of the World with Swedish Census Records

ACS Style

Ola Hall; Emilie Stroh; Fredy Paya. From Census to Grids: Comparing Gridded Population of the World with Swedish Census Records. The Open Geography Journal 2012, 5, 1 -5.

AMA Style

Ola Hall, Emilie Stroh, Fredy Paya. From Census to Grids: Comparing Gridded Population of the World with Swedish Census Records. The Open Geography Journal. 2012; 5 (1):1-5.

Chicago/Turabian Style

Ola Hall; Emilie Stroh; Fredy Paya. 2012. "From Census to Grids: Comparing Gridded Population of the World with Swedish Census Records." The Open Geography Journal 5, no. 1: 1-5.

Journal article
Published: 06 July 2010 in The Open Remote Sensing Journal
Reads 0
Downloads 0

Since the early days of satellite remote sensing in the 1950’s, accessibility, quality, and scope of remote sensing image data has been continuously improving, making it a rich data source with a wide range of applications. Today, the use of remote sensing techniques and data is commonplace within many disciplines in the natural sciences. Although there are quite a few examples of remote sensing to be found in the social sciences, developments here have, on the whole, been less pronounced. This paper investigates 1) how remote sensing data has been put to use in social science studies, and 2) how social science could better utilize the huge potential of remote sensing data. The first part of the paper gives an overview of existing types of remote sensing techniques and data collection. The second part consistsof a review of social science applications of remote sensing data. In the conclusions it is argued that remote sensing data is at its most valuable in the social sciences when used in combination with traditional methods such as surveys, public records, interviews and direct observation

ACS Style

Ola Hall. Remote Sensing in Social Science Research~!2009-12-28~!2010-03-26~!2010-06-25~! The Open Remote Sensing Journal 2010, 3, 1 -16.

AMA Style

Ola Hall. Remote Sensing in Social Science Research~!2009-12-28~!2010-03-26~!2010-06-25~! The Open Remote Sensing Journal. 2010; 3 (1):1-16.

Chicago/Turabian Style

Ola Hall. 2010. "Remote Sensing in Social Science Research~!2009-12-28~!2010-03-26~!2010-06-25~!" The Open Remote Sensing Journal 3, no. 1: 1-16.

Journal article
Published: 01 March 2009 in The Journal of Environment & Development
Reads 0
Downloads 0

This article investigates if higher levels of social capital, better governance structures, and a more ambitious conservation policy are positively linked to the ability of states to address biodiversity loss. Serving this purpose is a data set containing estimates of woodpecker diversity in 20 European countries. These data are argued to be a more valid indicator of biodiversity than most other available cross-national measures of environmental quality. A seemingly unrelated regression analysis reveals that none of the indicators are linked to higher levels of woodpecker diversity, which in turn leads to the conclusion that present institutions, environmental policies, and social structures have negligible effects on biodiversity compared to long-term landscape transformations.

ACS Style

Andreas Duit; Ola Hall; Grzegorz Mikusinski; Per Angelstam. Saving the Woodpeckers. The Journal of Environment & Development 2009, 18, 42 -61.

AMA Style

Andreas Duit, Ola Hall, Grzegorz Mikusinski, Per Angelstam. Saving the Woodpeckers. The Journal of Environment & Development. 2009; 18 (1):42-61.

Chicago/Turabian Style

Andreas Duit; Ola Hall; Grzegorz Mikusinski; Per Angelstam. 2009. "Saving the Woodpeckers." The Journal of Environment & Development 18, no. 1: 42-61.