A multi-temporal phenology based classification approach for Crop Monitoring in Kenya

The SBAM (Satellite Based Agricultural Monitoring) project, funded by the Italian Space Agency aims at: developing a validated satellite imagery based method for estimating and updating the agricultural areas in the region of Central-Africa; implementing an automated process chain capable of providing periodical agricultural land cover maps of the area of interest and, possibly, an estimate of the crop yield. The project aims at filling the gap existing in the availability of high spatial resolution maps of the agricultural areas of Kenya. A high spatial resolution land cover map of Central-Eastern Africa including Kenya was compiled in the year 2000 in the framework of the Africover project using Landsat images acquired, mostly, in 1995. We investigated the use of phenological information in supporting the use of remotely sensed images for crop classification and monitoring based on Landsat 8 and, in the near future, Sentinel 2 imagery. Phenological information on crop condition was collected using time series of NDVI (Normalized Difference Vegetation Index) based on Landsat 8 images. Kenyan countryside is mainly characterized by a high number of fragmented small and medium size farmlands that dramatically increase the difficulty in classification; 30 m spatial resolution images are not enough for a proper classification of such areas. So, a pan-sharpening FIHS (Fast Intensity Hue Saturation) technique was implemented to increase image resolution from 30 m to 15 m. Ground test sites were selected, searching for agricultural vegetated areas from which phenological information was extracted. Therefore, the classification of agricultural areas is based on crop phenology, vegetation index behaviour retrieved from a time series of satellite images and on AEZ (Agro Ecological Zones) information made available by FAO (FAO, 1996) for the area of interest. This paper presents the results of the proposed classification procedure in comparison with land cover maps produced in the past years by other projects. The results refer to the Nakuru County and they were validated using field campaigns data. It showed a satisfactory overall accuracy of 92.66 % which is a significant improvement with respect to previous land cover maps

The desertification context

Desertification is a critical issue for Mediterranean drylands. Climate change is expected to aggravate its extension and severity by reinforcing the biophysical driving forces behind desertification processes: hydrology, vegetation cover and soil erosion. The main objective of this thesis is to assess the vulnerability of Mediterranean watersheds to climate change, by estimating impacts on desertification drivers and the watersheds’ resilience to them. To achieve this objective, a modeling framework capable of analyzing the processes linking climate and the main drivers is developed. The framework couples different models adapted to different spatial and temporal scales. A new model for the event scale is developed, the MEFIDIS model, with a focus on the particular processes governing Mediterranean watersheds. Model results are compared with desertification thresholds to estimate resilience. This methodology is applied to two contrasting study areas: the Guadiana and the Tejo, which currently present a semi-arid and humid climate. The main conclusions taken from this work can be summarized as follows: • hydrological processes show a high sensitivity to climate change, leading to a significant decrease in runoff and an increase in temporal variability; • vegetation processes appear to be less sensitive, with negative impacts for agricultural species and forests, and positive impacts for Mediterranean species; • changes to soil erosion processes appear to depend on the balance between changes to surface runoff and vegetation cover, itself governed by relationship between changes to temperature and rainfall; • as the magnitude of changes to climate increases, desertification thresholds are surpassed in a sequential way, starting with the watersheds’ ability to sustain current water demands and followed by the vegetation support capacity; • the most important thresholds appear to be a temperature increase of +3.5 to +4.5 ºC and a rainfall decrease of -10 to -20 %; • rainfall changes beyond this threshold could lead to severe water stress occurring even if current water uses are moderated, with droughts occurring in 1 out of 4 years; • temperature changes beyond this threshold could lead to a decrease in agricultural yield accompanied by an increase in soil erosion for croplands; • combined changes of temperature and rainfall beyond the thresholds could shift both systems towards a more arid state, leading to severe water stresses and significant changes to the support capacity for current agriculture and natural vegetation in both study areas.Supported by the Portuguese Foundation for Science and Technology and the European Union under Operational Program “Science and Innovation” (POCI 2010), Ph.D. grant ref. SFRH/BD/5059/200

Mapping of the Prosopis-Juliflora (Mesquite) invasion and its effects on pastoralist livelihoods in the Red Sea State, Sudan – a remote sensing approach

Land cover management policies and land use changes are among the risks facing pastoral lands in eastern Sudan. Land use/land cover (LULC) changes play a major role in the study of global change. LULC and human/natural modifications have largely resulted in deforestation, biodiversity loss, global warming, and an increase in natural disaster flooding. This thesis’s investigates vegetation change with a focus on the expansion of Prosopis-Juliflora (Mesquite) and its impact on pastoralist livelihoods in Red Sea State in Sudan. The current study was conducted in three areas of Red Sea State (Sinkat and Jubayt, Ashat, and Salum). Remote sensing and Geographical Information systems (GIS) were used to monitor and map changes in land cover and land use (LULC). Multi-temporal Landsat satellite data from 1984-2020, were used to identify LULC change and study the dynamics of change, the effects of the expansion of the P. juliflora on the livelihoods of pastoralists in the Red Sea region (Sudan), and the identification of possible adaptations therein were studied using interviews. Socioeconomic data were correlated with remote sensing data to analyze the causes and effects of change in LULC and land degradation.Master's Thesis in GeographyGEO350MASV-PHYGMPGEOGRMASV-GEOGMASV-MEH

Land Use Planning for Natural Hazards

Natural hazard events are able to significantly affect the natural and artificial environment. In this context, changes in landforms due to natural disasters have the potential to affect and, in some cases, even restrict human interaction with the ecosystem. In order to minimize fatalities and reduce the economic impact that accompanies their occurrence, proper planning is crucial. Land use planning can play an important role in reducing current and future risks related to natural hazards. Land use changes can lead to natural hazards and vice versa: natural hazards affect land uses. Therefore, planners may take into account areas that are susceptible to natural hazards when selecting favorable locations for land use development. Appropriate land use planning can lead to the determination of safe and non-safe areas for urban activities. This Special Issue focuses on land use planning for natural hazards. In this context, various types of natural hazards, such as land degradation and desertification, coastal hazard, floods, and landslides, as well as their interactions with human activities, are presented

Integrated Applications of Geo-Information in Environmental Monitoring

This book focuses on fundamental and applied research on geo-information technology, notably optical and radar remote sensing and algorithm improvements, and their applications in environmental monitoring. This Special Issue presents ten high-quality research papers covering up-to-date research in land cover change and desertification analyses, geo-disaster risk and damage evaluation, mining area restoration assessments, the improvement and development of algorithms, and coastal environmental monitoring and object targeting. The purpose of this Special Issue is to promote exchanges, communications and share the research outcomes of scientists worldwide and to bridge the gap between scientific research and its applications for advancing and improving society

Climate change and human security: Case studies linking vulnerable populations to increased security risks in the face of the global climate challenge

Climate change has become ubiquitous in today’s socioeconomic and political discourse, being global in scale, climate impacts across ecosystems that cannot be contained by state boundaries. Actions of one country affect regions on the other side of the world, hence the need for a comprehensive and effective global climate regime. In 2015, the Paris Climate Change Agreement was adopted, and in the ensuing years, countries, along with researchers, civil society and industry have been debating how to implement concrete action to address the climate challenge. The link between climate change and human security was first recognised in the early 2000s. This paper examines how climate change has exacerbated uncertainty and instability in vulnerable populations in different regions. It achieves this by looking at diverse national and local experiences through multiple policy lenses, namely, the proliferation of extreme weather events, coastal erosion and sea level rise, internal displacement, cross border migration, and climate change as a threat multiplier. It looks at specific cases in Sub-Saharan Africa, the Pacific Islands and the Levant to understand how human (in)security is being affected by climate change. It also addresses the future of global climate policy by assessing the current state of climate policies in light of the Paris Agreement. Global action on climate change is urgent. While many developed countries like to avoid notions of climate justice and differentiated responsibilities, the reality for the most vulnerable countries is that supranational policy is crucial if they are to tackle the climate challenge at home. This paper emphasises the importance of having meaningful and focused national climate adaptation and mitigation policies in place in order to address both the avoidable and unavoidable impacts of climate change on the economy, the culture and ultimately the security of a country. This study finds that as climate change plays an increasingly important role in discussions of security, comprehensive strategies are needed to respond to climate-induced security threats and geopolitical (in)stability both nationally and around the world. The Paris Agreement was a good first step in driving countries to commit to curbing emissions and drafting climate adaptation action plans. We now need the global climate regime – including countries, industry, and researchers – to step up to the plate and implement effective policies if we are to limit the serious impacts of climate change. The findings in this paper aims to contribute to the global debate around security and climate change

The use of remote sensing to evaluate and detect desert regions

Die Fernerkundung spielt eine signifikante Rolle bei der Bereitstellung von aktuellen Daten zur Schätzung von empirischen Indizes bei Untersuchungen der Umwelt, insbesondere in Trockengebieten. Spektral- und thermische Kanäle in Satellitenbildern werden auch zur Berechnung von Indizes verwendet, um natürliche Phänomene in Trockengebieten – wie etwa Bodendegradation und Desertifikation – aufzuspüren, zu bestimmen und zu evaluieren. In dieser Arbeit wurden zur Identifikation von Desertifikation in der Kashan-Qom Region im Zentraliran fünf Desertifikationsindikatoren verwendet: Vegetation, Oberflächentemperatur, Erosion, Trockenheit und Überflutungen. Diese Indikatoren wurden dargestellt mit Hilfe von: Vegetationsindex (VCI), Temperaturindex (TCI), Revidierte Universelle Bodenverlustgleichung (RUSLE), standardisierter Niederschlagsindex (SPI) und Abfluss. Multispektrale Bilder des MODIS Satelliten wurden für die Berechnung von VCI und TCI herangezogen. Des Weiteren wurden RUSLE, SPI und Abfluss bestimmt. Schließlich wurden mehrere Desertifikationskarten anhand von zwei Modellen – einem konventionellen Modell und einem unscharfen Modell – erstellt. Die Ergebnisse der Modelle wurden mit Hilfe von Feldproben und der Erstellung einer Fehlermatrix analysiert. Im unscharfen Modell wurde ein regelbasiertes System aufgrund von Expertenwissen und einer induktiven datengetriebenen Methode erstellt. Obwohl das unscharfe Modell weniger genau als die konventionelle Methode ist, zeigt es die Unbestimmtheit in den Desertifikationsklassen der erstellten Karten.Remote sensing plays a significant role in providing up-to-date data for the estimating of empirical indices in studying the environment, especially in drylands. The spectral and thermal bands in satellite images are also applied to calculate the indices to detect, identify, and evaluate the natural phenomena in drylands such as land degradation and desertification. In this project, for the identification of desertification in the Kashan-Qom region in Central Iran, five main indicators of desertification are used as follows: vegetation, land surface temperature, erosion, drought, and flooding; therefore, these indices are selected as Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Revised Universal Soil Loss Equation (RUSLE), and Standardized Precipitation Index (SPI), and runoff (Q), respectively. The multi-spectral satellite images of MODIS are used for the calculation of remotely sensed indices such as Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). Furthermore, the ancillary data-based indices, Revised Universal Soil Loss Equation (RUSLE), and Standardized Precipitation Index (SPI), and runoff (Q), are also estimated. Then several desertification maps are produced in two models: conventional method and fuzzy model. The result of each model is also evaluated, that is, the results are assessed by the supplying of field sampling as ground truth references and the defining of error matrix. In the fuzzy modelling, a rule-based system is built by expert knowledge and data-induction method. According to the obtained results, even though the accuracy of the fuzzy model is lower than the conventional method, the fuzzy model represents the uncertainty in the classes of resulted desertification by providing a map for each class