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Anthropic pressure and land use dynamics around corridor n°1 of the Pô-Nazinga-Sissili ecological complex in Burkina Faso In Burkina Faso, within the Pô-Nazinga-Sissili ecological complex, known as PONASI in the south-central part of the country, rapid population growth and climatic variability lead to frequent, but generally unplanned, changes in land use. The present study assesses the landscape dynamics around Corridor 1 of the PONASI ecological complex based on the processing of Landsat images from 1996, 2006, 2016 and 2020, complemented by landscape ecology analysis tools. The results reveal that in 24 years (from 1996 to 2020), the areas of pasture, gallery forest and fallow land have regressed by 50 %, 40 % and 98 % respectively through fragmentation and suppression processes. Conversely, the fields have expanded in the landscape, their surface being multiplied by 11, as a consequence of the creation and aggregation of tasks. The landscape dynamics is thus materialized by the replacement of pastures, the matrix of the landscape until 2006, by the fields that constituted the new matrix of the landscape from 2016. Consequently, the anthropization of the landscape induced by agricultural development is illustrated by the level of landscape disturbance that has increased from 0.30 to 1.83, a consequence of the absence of accompanying measures of land use plans in a context of rapid population growth. Our observations imply the need to develop a participatory natural resource management policy taking into account the socio-economic context of the study area.

In Haiti, forest cover is in constant decline and does not exceed 3.5% of the national territory. Parks have been created to preserve the rare forests, including Unit 2 of the Pine Forest National Natural Park (PNN-FP2). However, the meager forest resources of this park are subject to various anthropogenic pressures (agriculture, timber exploitation, urbanization, etc.) leading to the decline of their area in the landscape. This study evaluated the spatio-temporal dynamics of the anthropization of forest ecosystems in PNN-FP2 from four Landsat images dating from 1973, 1986, 1999 and 2018. The cartographic approach combined with the analysis tools of landscape ecology revealed that the natural forest cover has experienced, in 45 years (from 1973 to 2018), a regressive dynamic materialized by a loss of 59.63% of its coverage to the benefit of anthropogenic classes (Fields and fallows, Degraded vegetation and Bare land) The regression of forest cover is underpinned by the dissection and fragmentation of its spots as opposed to the creation of the anthropogenic class spots. Our results justify the urgent need to develop an integrated, adequate and participatory management policy in order to sustainably preserve the forests of PNN-FP2.

How can sustainable agricultural development be reconciled with the fight against climate change and the preservation of biodiversity? To reach such a challenge, political, technical, and socio-economic decision-makers now have access to accurate and valuable environmental information. These include satellite images and environmental data produced from these images. In Guinea, in order to carry out public policies for the sustainable management of territories and natural resources, the government must be in a position to have reliable, consistent, precise, and as recent as possible information on the state and dynamics of its territory (soil artificialisation, agricultural extension, deforestation, mining...) and on the evolution of certain features of the biosphere (forests, savannas, wetlands, mangroves...). To this end, the Guinean Ministry of Agriculture has relied on the French technical expertise to draw up an agroecological zoning for the country, aimed at identifying and quantifying current agricultural areas, assessing agricultural potential, and mapping land cover and land cover change over a 10-year period (2005-2015). This project was implemented over two years in a partnership framework between a team of French thematic experts and a team of Guinean technicians and experts involving a specific organisation and procedure, to ensure a complete transfer of skills on all project activities, from the realisation of a land cover layer to relevant applications in the field of agriculture and the environment, with the aim of providing decision support tools to multiple Guinean actors. [ABSTRACT FROM AUTHOR]

Vegetation Change Analysis in Côte d'Ivoire During Conflicts Using a Phenological Metric and Kendall Correlation of two NDVI Time Series. A multiscale and multisatellite remote sensing approach has been set up in order to study vegetation changes, in particular the forest-savanna limit, first over a region including Ivory Coast and Benin with an 8 km resolution, from 1981 to 2006, then over Ivory Coast only, with a 250 m resolution, from 2002 to 2014. Both two NDVI time series (AVHRR et MODIS) has been studied on the one hand with Kendall correlation and on the other hand, with an original metric which enable to distinguish vegetation which photosynthesis presents a unimodal rhythm (one rainy season and one vegetative activity season) or bimodal rhythm (two rainy seasons and two vegetative activity seasons).

Impact of Anthropogenic Pressures on the Flora of the Haut-Sassandra Classified Forest (Central-West of Côte d'Ivoire). The classified forest of Haut-Sassandra located in the center-west of Ivory Coast is subjected to a strong anthropization since the politico-military conflicts of the year 2002. This study aims to quantify the degradation in the northern, central and southern zones of this domain. To achieve this, a spatiotemporal analysis of the dynamics of the three zones was made based on five Landsat images from 1990, 1997, 2002, 2006 and 2013. It was supplemented by a floristic inventory of each zone. The results show that forest cover conversions of the three zones occurred during the conflict period with regression rates of more than 50 %. At the floristic level, 622 plant species distributed among 410 genera and 104 families were recorded in all three zones. The North and the Center differ significantly from the South by the average specific richness. The inventoried flora generally differs from one zone to another depending on the degradation factors, with a greater diversity in cocoa plantations. However, this flora, although diversified, does not have any similarity with that of the forest relics still present in the classified forest of Haut-Sassandra.

Cocoa Expansion Dynamics in the Forest-Savanna Contact Zones: Case Study of the Sub-prefecture of Kokumbo (Côte d'Ivoire). In Ivory Coast, forests-savannah transition areas have been considered from the 1970s as unfavorable to cocoa cultivation. In recent years, however, there has been a comeback to the cocoa economy in these areas. This study carried out in the sub-prefecture of Kokumbo, aimed to map and to follows the spatial and temporal evolution of this crop using Landsat images of 1990, 2002 and 2016. In order to better understand the fundamentals of the peasant practices, surveys were carried out in different villages in the area. Treatment shows that the influence of cocoa culture is becoming increasingly important in the region. This cocoa crop is set up to the detriment of forests and savannahs, which have lost 25% and 58.1% of their initial area respectively. The surveys identified four types of cocoa farms, of which 65% of the plots were created between 2002 and 2014. Facing this relatively recent expansion, the issue of the sustainability of cocoa production systems in this region arises. Their agronomic and economic performances and their value for biodiversity conservation should be analyzed in future studies.

Dynamics of Settlement and Landscape Modifications in the Southern Rural Area of the Bonon City (Marahoué Region, Côte d'Ivoire). Estimated at 15 million of hectares at the beginning of the 20th century, the surface of ​​dense forests in Ivory Coast was estimated at 2.7 million hectares at the end of the same century. Strong anthropic pressure led to a reduction of forest surface in this country. This is the case in the Bonon area, a sub-prefecture in Marahoué region, where cash crops were developed in the early 1970s. Field data collected in 2000 on settlement and landscape were compared with those from 2015. Changes in population density, spatial organization of the territory and rural communications were described. Within 15 years, the rural population density has increased from 75 inhabitants / km² in 2000 to 134 inhabitants / km² in 2015. This increase in human population densities, despite the socio-political crisis from 2002 to 2011, has profoundly changed the landscape in this area. The analysis of the landscape shows a considerable increase in cultivation surface. Agricultural surface have risen from 3818 hectares in 2000 to 5250 hectares in 2015, so an increase of 31% over 15 years. The original forest has almost disappeared.

The Deforestation Radius Around Lubumbashi City (Upper Katanga, DR Congo): Synthesis. The Miombo woodland is a type of vegetation widely distributed in Zambezian Africa where it provides timber and non-timber forest products to millions of inhabitants. In Lubumbashi, the causes of its degradation, supported by rapid population growth, are mainly: (i) agricultural development, (ii) charcoal production, (iii) urban expansion, and (iv) mining activities. We present a meta-analysis of the studies that have defined the deforestation radius around Lubumbashi. This radius, used both to express the area (circular area), intensity and the magnitude (distance to the city) of deforestation, was determined through in situ charcoal production and remote sensing. Although the city's ecological footprint is illustrated, estimates of the resulting deforested area do not appear to be consistent because of the variability of methodological protocols within and between approaches. While studies focusing on charcoal production suggest complete Miombo woodland suppression around the city, those based on remote sensing mention the persistence of Miombo patches relatively close to the city and sometimes confuse the different levels of Miombo degradation. These observations prevent the development of an appropriate policy for the conservation and sustainable use of the concerned ecosystem.

The organic matter (OM) is an important element of the fertility of cultivated soils. Reflectance measurements have been successfully used to predict soil organic carbon (OC) content of agricultural soils, measured in the laboratory on samples of dried soil or directly in the field using field spectro-radiometer or satellite imagery. This study proposes a method for spatial prediction of soil OC, from UAV imagery. An agricultural plot of 13 ha "Grande Borne" located in the plain of Versailles (78) was analysed in April 2013, shortly before sowing while it was still bare soil. The AIRINOV® UAV used was equipped with a four channels multispectral camera MultiSPEC 4C® (550nm, 660nm, 735 nm and 790 nm) and flying at an altitude of 150m. Twenty three ground control points, distributed in the plot were delineated by target located with a centimetric DGPS and different measures have been made synchronously with the drone flight: Spectral Measurements (spectroradiometer ASD FieldSpec 3®), roughness measurements by photogrammetric method, samples of soil samples for analysis of chemical composition and water content. The images obtained with a resolution of 15cm have been georeferenced with an infra-pixel accuracy. The field spectra were aggregated on the spectral bands of the Multispec 4C for validation by linear regression. The obtained R2, between 0.8 and 0.9 by band, with an error between 1 and 3%, have shown good reliability of the Multispec 4C® sensor. The OC content was then estimated by partial least squares regression (PLSR) from spectral measurements of the 23 plots. The mean squared error of cross validation (RMSECV) by LOO (Leave One Out) method was 1.97 g of OC per kg of soil. A second correction of the model incorporating the effects of moisture and roughness on reflectance, has improved the quality of the prediction by 18% and a RMSECV of 1.61 g / kg. The model was finally spatialized in GIS and compared to simple spatial interpolations of soil analyses. [ABSTRACT FROM AUTHOR]