Earth Observation Strategies for Degradation Monitoring in South Africa with Sentinels - Results from the Spaces 2 Saldi-Project Year 1

Author(s):  
C. Schmullius ◽  
M. Urban ◽  
A. Hirner ◽  
C. Berger ◽  
K. Schellenberg ◽  
...  
2021 ◽  
Vol 4 ◽  
Author(s):  
Charlotte E. Wheeler ◽  
Edward T. A. Mitchard ◽  
Hugo E. Nalasco Reyes ◽  
Gloria Iñiguez Herrera ◽  
Jose Isaac Marquez Rubio ◽  
...  

Forest degradation leads to the gradual reduction of forest carbon stocks, function, and biodiversity following anthropogenic disturbance. Whilst tropical degradation is a widespread problem, it is currently very under-studied and its magnitude and extent are largely unknown. This is due, at least in part, to the lack of developed and tested methods for monitoring degradation. Due to the relatively subtle and ongoing changes associated with degradation, which can include the removal of small trees for fuelwood or understory clearance for agricultural production, it is very hard to detect using Earth Observation. Furthermore, degrading activities are normally spatially heterogeneous and stochastic, and therefore conventional forest inventory plots distributed across a landscape do not act as suitable indicators: at best only a small proportion of plots (often zero) will actually be degraded in a landscape undergoing active degradation. This problem is compounded because the metal tree tags used in permanent forest inventory plots likely deter tree clearance, biasing inventories toward under-reporting change. We have therefore developed a new forest plot protocol designed to monitor forest degradation. This involves a plot that can be set up quickly, so a large number can be established across a landscape, and easily remeasured, even though it does not use tree tags or other obvious markers. We present data from a demonstration plot network set up in Jalisco, Mexico, which were measured twice between 2017 and 2018. The protocol was successful, with one plot detecting degradation under our definition (losing greater than 10% AGB but remaining forest), and a further plot being deforested for Avocado (Persea americana) production. Live AGB ranged from 8.4 Mg ha–1 to 140.8 Mg ha–1 in Census 1, and from 0 Mg ha–1 to 144.2 Mg ha–1 Census 2, with four of ten plots losing AGB, and the remainder staying stable or showing slight increases. We suggest this protocol has great potential for underpinning appropriate forest plot networks for degradation monitoring, potentially in combination with Earth Observation analysis, but also in isolation.


2021 ◽  
Author(s):  
Insa Otte ◽  
Nosiseko Mashiyi ◽  
Pawel Kluter ◽  
Steven Hill ◽  
Andreas Hirner ◽  
...  

<p>Global biodiversity and ecosystem services are under high pressure of human impact. Although avoiding, reducing and reversing the impacts of human activities on ecosystems should be an urgent priority, the loss of biodiversity continues. One of the main drivers of biodiversity loss is land use change and land degradation. In South Africa land degradation has a long history and is of great concern. The SPACES II project SALDi (South African Land Degradation Monitor) aims for developing new, adaptive and sustainable tools for assessing land degradation by addressing the dynamics and functioning of multi-use landscapes with respect to land use change and ecosystem services. SPACES II is a German-South African “Science Partnerships for the Adaptation to Complex Earth System Processes”. Within SALDi ready-to-use earth observation (EO) data cubes are developed. EO data cubes are useful and effective tools using earth observations to deliver decision-ready products. By accessing, storing and processing of remote sensing products and time-series in data cubes, the efficient monitoring of land degradation can therefore be enabled. The SALDi data cubes from optical and radar satellite data include all necessary pre-processing steps and are generated to monitor vegetation dynamics of five years for six focus areas. Intra- and interannual variability in both, a high spatial and temporal resolution will be accounted to monitor land degradation. Therefore, spatial high resolution earth observation data from 2016 to 2021 from Sentinel-1 (C-Band radar) and Sentinel-2 (multispectral) will be integrated in the SALDi data cube for six research areas of 100 x 100 km. Additionally, a number of vegetation indices will be implemented to account for explicit land degradation and vegetation monitoring. Spatially explicit query tools will enable users of the system to focus on specific areas, like hydrological catchments or blocks of fields.</p>


2015 ◽  
Vol 10 (2) ◽  
Author(s):  
Michael T. Gebreslasie ◽  
Ides Bauwens

The aim of this study is to assess the capacity gaps and requirements of Earth observation (EO) and related technologies for malaria vector control and management in the Lubombo Spatial Development Initiative regions of South Africa, Swaziland and Mozambique. In order to achieve the core objective of this study, available EO data (including main characteristics and resources required to utilize them) and their potential applications for malaria epidemiology are reviewed. In addition, a survey was conducted to assess the availability of human and facility resources to operate EO and related technologies for control and management of the malaria control programs in these countries resulting in an analysis of capacity gaps, priorities and requirements. Earth observation in malaria vector control and management has two different applications: i) collection of relevant remotely sensed data for epidemiological use; and ii) direct support of ongoing malaria vector control activities. All malaria control programs and institutions recognize the significance of EO products to detect mosquito vector habitats, to monitor environmental parameters affecting mosquito vector populations as well as house mapping and distribution of information supporting residual spray planning and monitoring. It was found that only the malaria research unit (MRU) of the medical research council (MRC) in South Africa and the national malaria control program (MCP) in Swaziland currently have a fully functional geographic information systems (GIS), whereas the other surveyed MCPs in South Africa and Mozambique currently do not have this in place. Earth observation skills only exist in MRU of MRC, while spatial epidemiology is scarce in all institutions, which was identified as major gap. The survey has also confirmed that EO and GIS technologies have enormous potential as sources of spatial data and as analytical frameworks for malaria vector control. It is therefore evident that planning and management require capacity building with respect to GIS, EO and spatial epidemiology.


Author(s):  
Maria Ferentinou ◽  
Wojciech Witkowski ◽  
Ryszard Hejmanowski ◽  
Hennie Grobler ◽  
Agnieszka Malinowska

Abstract. Sinkholes are alarming and dangerous events, they have a worldwide occurrence, and are imposing a potential risk to urban communities and the widely developed built environment. Losses due to catastrophic sinkhole collapse, foundation, pavement and structural repairs, occur more often, due to the increased pressure to develop even on sinkhole prone land, and the aging of existing water supply infrastructure in the majority of cities. Remote sensing earth observation methods have proved to be valuable tools during the last two decades in long-term sinkhole hazard assessment. Satellite air borne and ground earth observation methods have primarily facilitated the wide detection of continuous displacement on the earth's crust. National sinkholes catalogues are necessary for town planers decision makers, and government authorities. In many instances the ground collapse is the result of water ingress from old poorly maintained leaking pipelines, or extensive dewatering activities. In the current study a comprehensive review of the current literature is presented in order to show experiences from South Africa and present recent mapping using PSInSAR methodology in Centurion South Africa.


2013 ◽  
Vol 21 (5) ◽  
pp. 1053-1070 ◽  
Author(s):  
Zahn Műnch ◽  
Julian E. Conrad ◽  
Lesley A. Gibson ◽  
Anthony R. Palmer ◽  
Denis Hughes

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