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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. [ABSTRACT FROM AUTHOR]

The objective of this study was to understand the need for the preservation of lemurs (V. v. subcincta and E. albifrons) and to provide an updated inventory of the situation and evolution of the dense forest of Nosy Mangabe from 1997 to 2017. The data obtained will be used to strengthen conservation strategies for the lemur population. The study was carried out from January 27th to September 19th 2017 and from January 28th to September 22nd 2017 in the Nosy Mangabe service area. For estimation of the density and abundance of the two species, the line transect method was used. The results obtained in the service area show a density of 5.62 ind/ha for Eulemur albifrons and a density of 2.87 ind/ha for V. v. subcincta. In the core part, the results show a density of 3.62 ind/ha for E. albifrons and a density of 1.25 ind/ha for V. v. subcincta. Land cover conversion over a period of 20 years was mapped using multi-date images from the Landsat satellite. The unsupervised classification method was used using ArcGis 10.4.1 software. A few GPS points were recorded for each type of land use to validate the cartographic results. The results obtained indicate that the dense forest lost an area of 1.47 km² (26%) between the year 1997 and the year 2017. Cyclones and tourism policy are the main natural causes threatening conservation. The landscape of the site is in full transformation and dominated by dense degraded forest. [ABSTRACT FROM AUTHOR]

Context and background: In Cameroon, the pressure on wetlands, which cover nearly 70% of the national territory, appears to be increasing, whether for subsistence needs, firewood, grazing, logging or expansion of development projects. Currently, in terms of land use, forest has decreased by 619 km² and cultivated land has increased by 321 km². The surface area of degraded forests and land is estimated at around 12 million hectares, with a general trend towards an increase in the phenomenon due to both natural and anthropogenic factors. It is obvious that approaches in favour of wetlands are widely engaged in the different basins of Cameroon. However, the management strategies for these areas are based on knowledge that is certainly extensive, but still patchy. There is a serious lack of overview of the location of degraded lands, the intensity of this degradation and the way farmers are addressing this problem through sustainable land management. Goal and objectives: The objective of this study is to characterize the dynamics of land cover from multi)date satellite data in the Noun floodplain of Cameroon. Methodology The methodology relies on the use of remote sensing and GIS to identify spatial units and detect changes over a twenty-two year period (1999 to 2021). The land cover maps were produced from an unsupervised classification with maximum likelihood. Results: The results identified eight classes: herbaceous savannahs with shrubs, forest galleries, fields and plantations, herbaceous tannas, young fallows, mineralized and built-up soils, bare soils and surface waters. It appears that in 1999, the landscape was dominated by natural vegetation (72.6%) located from north to south of the Noun plain. However, since 2004, the landscape has been dominated by agricultural areas (56.8%). Natural formations have been progressively reduced in space over time. The evolution of the Noun floodplain landscape reveals that 14.3% of the space has remained stable. These are fields and plantations, young fallows, mineralized soils and surface water. This space has not migrated to other classes. While about 73.9% of the area has moved to higher classes, of which 35.6% to herbaceous tannas and 26% to fields and plantations. On the other hand, 72.6% of the area (herbaceous savannahs and forests gallery) has been heavily degraded. These results indicate that the landscape of the Noun floodplain is marked by a high level of agricultural activity, which is at the origin of the progressive degradation of the land. They suggest an effective awareness of the level of land degradation and a better integrated management of land at the local level. [ABSTRACT FROM AUTHOR]

SIELETERS is an airborne hyperspectral imaging system that covers the mid- and long-wavelength infrared bands. It is part of the SYSIPHE system that covers bands from 0.4 μm to 11.8 μm. The ground sampling distance of the SIELETERS instrument is 0.5 m when 2000 m above the ground and the spectral resolution is between 6.7 cm-1 and 14.4 cm-1. In this article, we introduce the SYSIPHE project, the SIELETERS system and we show the latest results that we have obtained with the system. Our recent studies led to significant improvements on the quality of the hyperspectral images and of the spectra. The hyperspectral images from the previous airborne campaigns are now compatible with atmospheric compensations, data classifications and anomaly detection. The system is opened to external users. [ABSTRACT FROM AUTHOR]

The objective of this research is to quantify, in a region considered as the most important in terms of date palms, the changes that have affected oases during 30 years and to show the importance of remote sensing as a tool facilitating oasis monitoring. The study of change detection conducted in Zeb El Gherbi oases located near Biskra wilaya, it realized by differentiating images using Normalized Difference Vegetation Index (NDVI), which calculated on three satellite images, Landsat 5TM for 1984 and 2001 as well as Landsat OLI for 2014. Field missions conducted to validate work. The results indicated an increase in the area of date palm plantations with 6123.15 ha between 1984 and 2001 and 6996.78 ha between 2001 and 2014. On the other hand, the study showed a reduction of date palms vigour in the ancient oases, probably caused by urbanisation and abandonment of date palms. [ABSTRACT FROM AUTHOR]

Context and background Forest ecosystems play a key role in the regulation of carbon cycle. The sustainability of This ecosystemic service is a necessity in the context of global changes. The spatial distribution of carbon stock is a useful tool of decisionmaking. Which contribute to improve forest management practices. Goal and Objectives: The aim was to model the spatial distribution of the aboveground carbon stock in the Goungoun Forest Reserve and its surrounding lands in northern Benin. Methodology: Systematic stratified sampling was used for the forest inventory. One hundred and fifty circular sampling plots with a radius of 18 m were inventoried. In each plot, all trees with a DBH ≥ 10 cm were identified at species level and measured using compasses. The structural parameters of trees were calculated. The spatial data analysis tool was used to extract spectral indices from remote sensing images. In addition, road density, distance to road network and distance to water stream were calculated. Aboveground biomass was obtained using the allometric model. The conversion factor (CF = 0.50) was used to obtain the carbon stock. The Pearson correlation test was used to select the best environmental variable for carbon distribution modelling. The Radom Forest algorithm was used to predict the spatial distribution of aboveground carbon. The performance of model prediction was evaluated by cross-validation with 100 iterations. The coefficient of determination (R²), root mean square error (RMSE), prediction bias and Akaike Information Criterion (AIC) were used to measure model performance. Results: Results showed that the spatial distribution of carbon stock was strongly influenced by basal area, mean diameter, tree density, forest strats and water stress index. The relative importance of these variables was ranged from 4 to 96%. The model was very accurate (bias = -0.03%, RMSE = 3.24 t/ha and R² = 98.93%). The quantity of carbon observed was ranged from 0.26 to 76.52 t/ha. While, the carbon predicted was varied from 0.24 to 64.66 t/ha for all stands. The carbon stock of forest stands was 2.11 times higher than that of the forest surrounding lands. The sites with high carbon stock were located in savannah woodlands. Anthropogenic pressure triggered the carbon storage potential of the FCGTR. Therefore, we had to strengthen the monitoring of plant species for sustainable forest management. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Accurate and consistent reporting on forest cover and land use/cover changes is crucial in the post-Paris agreement context where countries are obliged to regularly submit their reports on the greenhouse gas balance of emissions and removals. This reporting of changes can have a direct impact on payments through comparisons with national reference (emission) levels in the context of reducing emissions from deforestation and forest degradation, particularly as part of the REDD+ process (Reducing emissions from deforestation and forest degradation). However, before doing so, countries are invited to strengthen their national forest monitoring system and also to produce map products that comply with robust methods for assessing the uncertainty of forest cover change estimates as prescribed by UNFCCC (United Nations Framework Convention on Climate Change). In this study, we present the results of the accuracy of the numerous forest maps available in Congo using a new method developed by SIRS and adapted to the context of the Republic of Congo. The results of the study show an underestimation of nearly 50% of forest losses in the period between 2000 and 2014 either by the direct estimation method or by regression estimates. Comparison of the two methods shows that the estimates of forest cover losses by the sample point method underestimates the estimate of losses over the period 2000-2014 as well as over the period 2014-2016. We conclude that there is a need to strengthen the national teams in charge of forest mapping, but also that the method by Sannier et al. 2014 should be adopted for the evaluation of precision. [ABSTRACT FROM AUTHOR]

This work deals with the evaluation of the potential of multi-temporal and multi-sensor (optical and radar) images of the satellites Sentinel-1 and Sentinel-2 satellites for land cover mapping and coastline evolution monitoring in a tropical ecosystem over the period 2015 to 2020. The study area chosen is the Cameroon Estuary. This area represents a major ecological transition in the sub-region with the presence of protected natural reserves (mangroves, dense forest, wetlands) but also a strong anthropic activity (construction, agriculture, degraded forest). The methodological approach consisted of a chain of pre-processing and visual image analysis, followed by a combination of the bands from each sensor, a supervised Random Forest classification to draft a land use map and finally a digitization of the coastline. Overall, the results show that the classification with the Sentinel- 2 images using 10 bands and adding 4 vegetation indices is slightly more accurate (95.75 %) than the classification with the 13 initial bands (91.78 %). The classification performed with the Sentinel-1A multi-temporal image series (dual polarization (VV, VH) and VV/VH ratio) leads to an accuracy of 78.44 %. The combination of Sentinel-2 A&B bands (10 bands and 4 indices) and Sentinel-1 improves the results and leads to an accuracy of 98.76 %. Our results also show that the use of multi-temporal image time series significantly improves the classification accuracy compared to the use of a single image (mono-date), and this for both sensors, i.e. an additional gain of 13 % and 10 % respectively for Sentinel-2 and Sentinel-1. However, this gain remains small for temporally stable classes. The results of the coastline evolution analysis show that the Cameroon estuary is disturbed by different levels of erosion (Cape Cameroon, North Manoka Island, Sanaga River mouth), and accretion (Limbe, and South Manoka Island) and also by weak internal variations. The fusion of optical and radar remote sensing data in the discrimination of land use classes, has shown that the construction zones are the most vulnerable to coastal erosion. On the other hand, the presence of vegetation (mangrove, forest) stabilizes and protects the coast from possible risks of this nature. [ABSTRACT FROM AUTHOR]

The mapping of the land use of Gabon in 2010 and 2015 and the changes between these two dates was carried out as part of the OSFACO program (Space observation of Central and Western African Forests) by the Gabonese Agency for Space Studies and Observations (AGEOS). This is the first reference land use map at the national level, including the legend resulting from a consultation of major players in the Gabonese forest sector. This map was obtained by refining the forest cover map of Gabon (forest/non-forest) obtained in the framework of OSFT (Spatial Observation of Tropical Forests) and GEOFORAFRI project (Capacity building and access to earth observation satellite data for monitoring forests in Central and Western Africa). The mapping was based on the use of SPOT 5/7, Sentinel 2 satellite images for the year 2015 and the SPOT 4, ASTER and ALOS 1 images for the year 2010. Semi-automated classification method and Manual enhancement were combined for better accuracy of land use classes. The results obtained highlight ten land use classes representing the country's large landscape groups dominated by forests which occupied 89% of the total area of the country in 2015. The most dynamic land use classes are forests, savannas, agricultural land and artificial surfaces. The main forest losses are linked to the conversion of forests to artificial surfaces, cultivated land and bare soils. The most significant gains in forest are observed at the level of the closure of forest roads. The validation of the product, carried out by an independent expertise from the map production team, was based on a reference data resulting from a sampling plan combining a systematic and random component according to the methodology of Sannier et al. (2016). The analysis of the correspondence between the land use map produced and the reference data gave an overall accuracy of 95%. [ABSTRACT FROM AUTHOR]

Despite the increasing openness and democratisation of satellite data and associated processing tools, the use of these data and the information derived from them remains relatively limited in the Southern countries. For several years now, initiatives have been launched to improve access and use by local actors. This paper presents the results of 3 successive projects funded by the French Development Agency in Central and West Africa between 2010 and 2020. These projects, led by IGN FI and the French National Research Institute for Sustainable Development (IRD), have provided some answers to the main challenges identified by local partners such as: access to data, improving data processing skills, raising awareness among decision-makers and land managers of the information and services that can be derived from it, reference land cover maps production by local teams, and the development and structuring of user networks. This paper presents the actions and results in three areas of intervention, namely (i) the free provision of recent high-resolution data, (ii) the local production of forest cover and land use change maps and (iii) the promotion of the use of images through training and scientific activities. The results of several projects supported within the framework of these actions are published in this special Africa issue. [ABSTRACT FROM AUTHOR]

The role of forests in carbon storage in a climate change context is relevance. In this paper, we will assess the carbon stock in the Libreville area using remote sensing data over a 2001-2018 period. This assessment of carbon stocks in forests is mainly based on Landsat optical imagery. A first analysis aimed at producing a land use mapping between 2001 and 2018 was carried out. These preliminary results were then used as a proxy for the assessment of carbon stocks using terrestrial and mangrove forests. The average value of carbon stock contained in each class comes from the bibliographical work carried out mainly in the same study area. The total value of the carbon stock was estimated at 70 913 018 ± 896 and 68 340 383 ± 927 tons in 2001 and 2018 respectively. [ABSTRACT FROM AUTHOR]

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]

In remote sensing, there is a large number of algorithms to classify a satellite image. Among these classification algorithms, the Random Forest appears to be particularly powerful. The objectives of this study are to evaluate (1) the importance of image selection for the level of accuracy of the training model and (2) the nature of the relationship between the level of accuracy of the model and the overall accuracy of the thematic map resulting from the classification of the satellite image with this algorithm. Based on a Landsat 8 OLI image taken over a tropical mountain area : the West Cameroon region, 35 models were built and tested. Analysis shows that the level of overall accuracy of the Random Forest results are closely dependent on the accuracy of the training model used to classify the satellite image, and on the choice of the images used to train this model. Moreover, the selection of these images is itself dependent on the quality of the Regions of interest (ROI) that will be used to build the model. It is therefore important to place particular emphasis on the quality of the input data in order to guarantee satisfactory results with this algorithm. Otherwise, the performance of this algorithm could be inferior to that of other classification algorithms. [ABSTRACT FROM AUTHOR]

Nowadays, urban sprawl is one of the major problems facing the Algerian Low-Sahara oases. Monitoring and understanding its spatial evolution remains an essential step for any sustainable development project of the oasis city. Local authorities do not have relevant and updated tools for effective management and spatial planning. Remote sensing and Geographic Information Systems (GIS) provide opportunities to overcome these difficulties. The present study consists in application of a change detection technique to map and quantify the spatiotemporal sprawl of Biskra City (Algeria), during the period 1985 - 2000, using three Landsat images acquired in 1985, 2000 and 2015. The post-classification comparison of land use and land cover maps has revealed a remarkable growth in the built-up areas going beyond the municipality's boundaries, in conurbation with the agglomeration of Chetma, against a progressive decline of the palm grove. It has undergone a continue process of fragmentation and conversion of its surface by the uncontrolled urbanisation, leading to the loss of the original oasis identity distinguishing this city. The main aim of this paper is to highlight the urban sprawl process and its spatial land use and land cover modifications. This study also shows the utility of change detection methods and Geographic Information Systems for monitoring the urbanisation patterns and assessing their impacts on oasis ecosystems. [ABSTRACT FROM AUTHOR]

Slope instability phenomena, by their essentially random nature, generate risks for various elements of mountain heritage. In Man Mountains region of Man, located in the west of Côte d'Ivoire, the manifestation of these phenomena is made more and more because of the rugged terrain and climate change. This study aims to map potential areas of slope instability movements in the Man area to prevent natural damage and/or casualties. The method used in this work, is based on remote sensing, Geographic Information System (GIS) and Saaty's analytic hierarchy process (AHP) method. Six (6) factors involved in the occurrence of landslides such as slope, drainage density, fracturing density, regolith thickness, precipitation, and normalized vegetation index (NDVI) have been mapped. Their integration into a GIS has made it possible to map the region's susceptibility to slope instability movements. Indeed, using Saaty's analytic hierarchy process (AHP) method, a prioritization, a weighting and a classification of the different factors were made. This facilitated the linear combination of the different factors in the GIS. The resulting susceptibility map was field-verified to yield a susceptibility map to slope instability movements of Man area. This map shows classes of very low, low, moderate, high and very high susceptibility. Areas of high and very high instability represent 14.65%. They are located in the West Central of the study area. Majority of these areas are found on the slopes of the Tours and Dan, mountains located between Biankouma and Man, which are characterized by steep slopes and registrate rainfall of more than 1500 mm. [ABSTRACT FROM AUTHOR]

Remote sensing is a particularly suitable tool for monitoring land use but also particularly suited for déforestation monito-ring. By launching the Setinel-1 and Sentinel-2 satellites in the Copernicus program, the community now has free data with important time-revisits allowing the greatest number of people to effectively monitor land cover of a study area. This paper présents a land use monitoring method based on the combination of two approaches computed using Open Source tools (QGIS, Orfeo ToolBox, python). First, we focus on land use monitoring at an annual time scale using Sentinel-1 and Sentinel-2 data, and then, by the use f entienl-1 data, we detect changes in the forest cover due to déforestation at bi-monthly time scale. The results obtained show a very good synergy of thèse approaches allowing the complementary of optical and radar data. In order to make accessible the proposed method, ail the used open source tools are available on this link http ://remotesensing4all.net/index.php/2018/09/11/kit-use-des-donnees-radar-sentinel-1-in-de-latelier-radar-du-FOSS4G-en-2018-2/. [ABSTRACT FROM AUTHOR]

Estimated at 15 million of hectares at the beginning of the 20th century, the surface of dense forests in Côte d'Ivoire was estimated at 2.7 million hectares at the end of the same century. Strong anthmpic 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. [ABSTRACT FROM AUTHOR]

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 Côte d'Ivoire 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). [ABSTRACT FROM AUTHOR]

In Côte d'Ivoire, 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The objective of this study is to develop a comprehensive approach of drought risk management based on indicators calculated from biophysical parameters extracted from NOAA/ AVHRR data over Morocco. Drought early warning requires the use of macrogeographic data generated at national scale and collected daily, decadal or monthly. The calculated indicators in the framework of this study are: Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI). These indicators are used for the characterization of vegetation health and drought monitoring in Morocco. The generated satellite based indicators maps were compared to the maps of Standardized Precipitation Index (SPI) calculated from precipitations derived from satellite. [ABSTRACT FROM AUTHOR]

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]

The recent democratization of drones creates a methodological break for archaeological remote sensing. The first point concerns the ease of use of these vectors, which provide secure flight conditions, thanks to the GPS and the ability to set waypoints for semi-automated flight navigation systems. This flexibility also allows repeated flights over the same area. The second interesting point for archaeological remote sensing is the low flight altitude of drones, allowing documentation of an intermediate level between the site and the micro-region. Low altitude is also a way to gain better information and higher resolution. The last point is the low cost of using, even if the purchase price of the equipment is quite high. The development of UAV for archaeological remote sensing implies to define new uses for traditional sensors. We describe those developed in the framework of the Archeodrones program on airborne photogrammetry and thermography New sensors will probably be adapted on drones in the future, allowing greater access to non-destructive methods of survey. [ABSTRACT FROM AUTHOR]

The recent years have shown a growing interest in low-altitude remote sensing (LARS) for the study of natural areas. But beyond the problematic of access to the study environment, the mapping of these areas on a large scale poses many constraints on acquisition sensors. Indeed, these environments are difficult for traditional image processing algorithms : inherently moving (at observations scales of individuals), composed of hardly distinguishable objects, these environments have varying weather conditions, sometimes hostile (lighting, humidity, temperature, etc.). This mapping is usually up in a thematic study which adds its own operational constraints (need for 3D information as relief or roughness, specific spectral signature, oblique views to simplify visual identification by experts, etc.). Furthermore, the use of low altitude remote sensing lightweight carriers, such as micro-drones, severely limits the available resources for sensors : onboard power calculation, size, weight, etc.. We present in this article two sensors : the tri-cameras sensor and the uEyes stereoscopic rig. The tri-cameras sensor was developed in 2009 for the acquisition of stereoscopic or oblique views at low altitude. By analyzing the experience of ground mission, we will emphasize the crucial importance of a precise synchronization of between the stereoscopic shots. We then present our new amphibious stereoscopic rig that we are developing since 2013. We designed it so it will offer the possibility of acquire perfectly synchronized stereoscopic images, which makes it an ideal tool for the study of coastal areas (for low altitude remote sensing and in situ at low depth). We conclude with a qualitative analysis of the first results obtained. [ABSTRACT FROM AUTHOR]

Monitoring forest state is required to estimate the levels of greenhouse gases emissions from deforestation. The objective of this study was to estimate deforestation trends for 2005-2010 and 2010-2013 periods in the eastern rainforests ecoregion of Madagascar. A supervised classification approach of multi-date Landsat images using the Random Forest algorithm was used. A complete 30 m map of the forest cover change was produced on 20.5 million hectares. The result was validated by photo interpretation of nearly 11 000 points from a regular sampling grid on the basis of SPOTand Landsat satellite images acquired in 2010-2013. The overall mapping accuracy was estimated to be about 90%. The area of Madagascar rainforests has been estimated at 4.5 million hectares in 2005, 4.4 million hectares in 2010 and 4.3 million hectares in 2013. The annual rate of deforestation has increased from 0.5%. to 0.9 % between the two periods. This study could be considered as a reliable cost-effective and reproductible approach for monitoring forests in Madagascar. [ABSTRACT FROM AUTHOR]

Large-scale characterization of tropical rainforest is a challenge for their conservation and management. Very high spatial resolution images as provided by the Pléiades satellites offer new opportunities to study the structural organization of heterogeneous rainforests with limited accessibility. In this study, we have evaluated the potential of Pléiades images to map structural parameters of New Caledonian rainforests by analyzing texture of forest canopies. We have applied the Fourier transform textural ordination (FOTO) method to very high spatial resolution images to compute texture indices of canopy grain (i.e. a combination of size distribution and spatial pattern of tree crowns). The results have showed that this method was promising to isolate the rainforest from other types of vegetation, and to highlight their structural diversity on a large scale. Finally, this case study showed that the use of Pléiades images is promising to predict the structure of rainforests. [ABSTRACT FROM AUTHOR]

Knowing the distribution of vectors of zoonoses is fundamental to understand epidemiological dynamics and characterize risk areas. This distribution can be assessed at different scales: regionally, the range of these species defines the limits of occurrence of pathogen transmission and, locally, niches determine the hazard. This latter scale requires a very precise knowledge of the areas that can be gained through the analysis of very high spatial resolution satellite images. As part of a research project on leptospirosis in La Réunion (LeptOI), this study proposes to measure the potential of a Pleiades image (product resampled to to 50 cm) to characterize the local distribution of various small terrestrial mammals in Saint-Paul swamp area. Three trapping campaigns have led to the capture of 134 animals belonging to four of the five species occurring in Reunion Island (Rattus rattus, R. norvegicus, Suncus murinus and Tenrec ecaudatus). An objectbased image analysis of the Pleiades image allowed discriminating ten land use classes with a total accuracy of 83.6%. Landscape indices were calculated from the classification around each trap (shortest distances to each land use class, edge densities and proportion of each patch within buffers defined by a 50 meters or a 100 meters radius). Three areas ("wet", "urbanized" and "dry") are clearly discriminated by these variables, which can be used as ecological determinants of different epidemiological profiles. The wetland area is known as suitable to leptospirosis whereas the urbanized area is a place of co-occurrence of the four species and thus potentially favorable to the exchange of pathogens. [ABSTRACT FROM AUTHOR]

Segmentation is a widely used operation in very high resolution remote sensing processing such as object based image analysis. Since the available memory resource might be limited, it is often impossible to process a whole satellite image without using piece-wise processing, which in the case of segmentation introduces a huge amount of artifacts. The work presented in this paper introduce a solution to this problem in the case of the Mean-Shift algorithm, which guarantees that piece-wise segmentation results matches exactly those of full image processing at once. First, we define a new property of segmentation algorithms called stability. After proposing a methodology to measure the stability of segmentation algorithms, we demonstrate that among the Mean-Shift, watershed and connected components algorithms, only the latter is stable. Then, we propose a stabilized version of the Mean-Shift algorithm and use it to build a rigorous and exact solution for piece-wise processing of this algorithm. Last, we present some examples demonstrating the usefulness of the proposed method. This method is available in the Orfeo ToolBox free software, and documented in the software guide. [ABSTRACT FROM AUTHOR]

In 2009 a preliminary feasability study on the fourth ring road of Alger was carried out based on SPOT5 images. A comparative study was also conducted with panchromatic (PAN) and multispectral (MS) Pléiades images. The focus of the studies has distinguished six different geological formations. The diversity of terrain encountered has enabled the comparison of parameters such as the resolution and the spectral band. From a geological point of view at macroscopic scale, both satellites enable an aerial sketch mapping of the lineaments. However, a more precise structural mapping was observed with Pléiades PAN images. For SPOT5 and Pléiades MS images, even though their resolution is quite similar (respectively 2,5 m and 2,8 m), a stronger spectral contrast was observed with Pléiades MS which have enabled to highlight the different lithologies. For smaller geological details (1 m), Pléiades PAN images have given good results. Hence, because preliminary studies have to be the most advanced possible, it is clear that Pléiades images are the one that can lead to an exhaustive mapping of the geomorphology encountered. [ABSTRACT FROM AUTHOR]

In this study, remote sensing and geographic information systems (GIS) are implemented in order to map and assess water erosion using the Universal Soil Loss Equation (USLE) in the Wadi Mina watershed in Algeria. The study area is characterized by great irregularity in rainfall which is mainly generated during storm events. The region is also known for its steep slopes, marly lithology and very sparse vegetation cover, making it more exposed and vulnerable to erosion. The USLE model can be described as the combination of six factors that feature the specific characteristics of the watershed. Data from multi-temporal remote sensing analysis and GIS are used to individually assess and map each factor. Integration of thematic maps for the USLE factors in the GIS is used to identify the impact of each factor on soil loss, as well as to rank the relative importance of the erosion zones, and further to quantify soil loss in the investigated region. [ABSTRACT FROM AUTHOR]

This paper aims to establish a map of the flood risk of the coastal plain of Saïdia located on the Mediterranean coast of north-eastern Morocco. This plain is enclosed between rivers : the Moulouya in the West and the Kiss in the East. It is bordered to the south by the Ouled Mansour Mountains. These are sheared by very steep ravines that empty directly into the plain. The groundwater is very shallow. This background coupled with geomorphic coastal development promotes the current flood risk. In this paper, the methodology is based on the structuring in a geographic information system (GIS), remote sensing data, products derived from a digital elevation model (DEM) and external data (lithology, the groundwater level, etc.). The analytical approach consists of a digital processing of a GeoEye-1 satellite image and aerial photographs to map the surface states, an extraction phase of topographic attributes and geomorphology of the land, represented by the digital elevation model (DEM) and a phase of structuring information for spatial analysis in a GIS. These investigations allowed the construction of two maps : the map of vulnerability to flood and the map of hazards. The vulnerability map shows that very high vulnerability areas represent 57% of the site and correspond to areas of inter-dunes flat formed by deposits of fine clay, and characterized by lowland sector (0-4 m). The hazard map refers to the land cover. The superposition of these two maps helped to establish the map flood risk. This thematic map shows that approximately 43% of the territory considered is located in high to very high flood risk areas, and correspond to the banks of the Moulouya and the kiss rivers and to the marshes of the Moulouya River, and to the sector on which the new Saidia resort is built. [ABSTRACT FROM AUTHOR]

The marshes, wich are potentially suitable for conversion into paddy fields, offer future possibilities for clearness in tropical forest area. A processing chain for multirésolution and multisource satellite images, using Orfeo ToolBox, is put to test in order to discriminate wetlands, water, marshes and paddy fields. This methodology combines radiometric indices extracted from images containing more spectral bands with textural indices from high spatial resolution images. Thus, the spectral information of an image from Landsat 7 ETM+ satellite at 30 m resolution, is used for identifying wetlands and for drawing up their regional mapping. The textural information of 10 m and 2.5 m images from SPOT 5 satellite is used to discriminate wetland types and to map them at the local scale. By combining data from both satellites, the areas of water, wetland and paddy fields were evaluated, with Kappa coefficient (0.8), in two districts of the forested corridor of Fianarantsoa (Madagascar). [ABSTRACT FROM AUTHOR]

Deal with the dual economic and social crisis in the 1980s, many of the Third World farming communities have been able to develop agro-pastoral systems and forestry in order to stamp rural poverty. The case study of Batoufam situated in the western highlands of Cameroon is an edifying illustration. Studies based on surveys and remote sensing data show a dynamic that leads to a gallery forest snacking, isolated groves and alpine meadows in favor of the habitat, communication channels and farms. Despite the increased rate of afforestation in the soils of the range 30, the future of these residual plant formations remains concerned because of population growth and anthropogenic pressures on the lands. [ABSTRACT FROM AUTHOR]

Water erosion is one of the main causes of degradation of the agro-soil assets. This phenomenon is well known in the catchment area of Tlil river sector involved in this study. Located in the north-east of Tunisia, this basin has a hilly terrain with altitudes ranging from 50 m to 420 m and steep slopes ranging from 2 to 25% and sometimes more. It covers an area of 45 km2 drained by a series of river, mainly Tlil river. The application of the universal equation of soil loss has three key objectives: - The parameter estimation of water erosion that is, the aggressiveness of rainfall, soil erodibility, topographic factor, the index of vegetation cover and erosion control practices factor. - The identification of sensitive areas and high risk of erosion and the areas of emergency response in the watershed. - Quantification of soil loss by runoff. The mapping of these areas is done using the remote sensing and geographic information systems. This will guide the various measures of intervention possible water conservation and soil programmed in the region. [ABSTRACT FROM AUTHOR]

This study aims to test the relevance of synthetic aperture radar images of medium and high resolution on the characterization of the types of land use in urban areas. To this end, we relied on textural approaches based on second-order statistics. Specifically, we look for texture parameters most relevant for discriminating urban objects. In this regard, we used Radarsat-1 in fine polarization mode and Radarsat-2 HH fine mode in dual and quad polarization and ultrafine mode HH polarization. The land uses sought were dense buildings, medium density buildings, low density buildings, industrial and institutional buildings, low density vegetation, dense vegetation, and water. We identified nine texture parameters for analysis, grouped into families according to their mathematical definitions in a first step. The parameters of similarity and (or) dissimilarity include homogeneity, contrast, the differential inverse moment, and dissimilarity. The parameters of disorder are entropy and the second angular momentum. Standard deviation and correlation are the dispersion parameters, and the average is a separate group. It is clear from experience that certain combinations of texture parameters from different groups used in classifications yield good results, while others produce kappa values of very little interest. Furthermore, we realize that if the use of several texture parameters improves classifications, its performance reaches a maximum from three parameters. The calculation of correlations between the textures and their principal axes confirms the results. [ABSTRACT FROM AUTHOR]

Abstract: We have mapped the region of Oran, Algeria, using multispectral remote sensing with different resolutions. For the identification of objects on the ground using their spectral signatures, two methods were applied to images from SPOT, LANDSAT, IRS-1C and ASTER. The first one is called Base Rule method (BR method) and is based on a set of rules that must be met at each pixel in the different bands reflectance calibrated and henceforth it is assigned to a given class. The construction of these rules is based on the spectral profiles of popular classes in the scene studied. The second one is called Spectral Angle Mapper method (SAM method) and is based on the direct calculation of the spectral angle between the target vector representing the spectral profile of the desired class and the pixel vector whose components are numbered accounts in the different bands of the calibrated image reflectance. This new method was performed using PCSATWIN software developed by our own laboratory LAAR. After collecting a library of spectral signatures with multiple libraries, a detailed study of the principles and physical processes that can influence the spectral signature has been conducted. The final goal is to establish the range of variation of a spectral profile of a well-defined class and therefore to get precise bases for spectral rules. From the results we have obtained, we find that the supervised classification of these pixels by BR method derived from spectral signatures reduces the uncertainty associated with identifying objects by enhancing significantly the percentage of correct classification with very distinct classes. [Copyright &y& Elsevier]

Abstract: Nowadays, hyperspectral remote sensing is a powerful tool for discrimination and accurate and rapid identification of mineral surfaces, due to the new technique of ground spectrometry. The objective of this article is the spectral identification of carbonate facies that exist in the Moroccan Atlantic High Atlas mountains, to establish a regional spectral library in order to prepare the implementation of regional maps with high spatial resolution. The spectra acquired in the visible-infrared (0.4 to 2.5μm) were used for characterizing and monitoring the evolution of diagenetic dolomite from the Lower Lias of the Arigh Ouzla formation that exists in the anticline Jbel Amsitten. The separation of facies, and the taking into account of the diversity in alteration phenomena, have imposed the normalization of the withdrawal of surface effects of dissolution and the restriction of the spectral window to avoid overlap of information. The characteristic absorption bands vary between 2.319 and 2.323μm and do not change between patina surface and fresh fractures. These values reflect the character totally dolomitic of the facies and can be used to estimate the degree of diagenesis, which gives more details with respect to previous sedimentological and petrographic descriptions. Analysis of the spectra has shown a relationship between the degree of crystallinity and depth of the absorption band could be established. [Copyright &y& Elsevier]

Abstract: The plains of Macta, where the Macta marshes are located, form a wetland with particular ecological characteristics in the Maghreb and are subject to distinct land use dynamics. The plant formations are exposed to multiple forms of degradation, primarily due to climate (period of dryness) and to increasing anthropogenic activities in the area. The new methods of breeding and cultivation contribute to ongoing degradation in this natural ecosystem, with a deterioration of the wetland''s biological potentialities. With the aim of safeguarding Macta''s marshes, a better knowledge of vegetation distribution patterns and dynamics, together with the interpretation of the remote sensing data and GIS, makes it possible to consider programmes of natural environment restoration and sustainable management. The results of land-use dynamics analysis show a decline in agricultural land use from 33,000 ha in 1958 to 21,000 ha in 2005. Halophytic vegetation currently occupies 47,000 ha, while in 1958 it occupied only 27,000 ha. Tamarix, Inula, Joncus and Scirpus species are experiencing a decrease in surface cover, while Salicornia, Suaeda, and Atriplex are extending their area. To cite this article: T. Sitayeb, K. Benabdeli, C. R. Biologies 331 (2008). [Copyright &y& Elsevier]

Abstract: This paper reports on small mountain glacier variations in the northern Belledonne region (French Alps). Between 1926 and 2006, the evolution is surveyed using remote-sensing techniques. Then, it is correlated with climate data for the same period. In the late 1920s and in 1980, there was a maximum extent of the glaciers. The 1980 surge is due to high precipitations during the late 1970s, a similar trend being punctually observed in 1993. Between 1980 and 2003, the Rocher Blanc glaciers have strongly receded, their total surface being divided by ten. From 1997 onward, the large retreat can be explained by the increase of the mean daily temperature, especially the minimum daily temperature. Moreover, unusually high temperatures have been registered during the summer 2003 heat wave. Small mountain glaciers appear to be more sensitive to climate change than larger ones. Their surfaces change within 6 to 12 months. [Copyright &y& Elsevier]

Abstract: Flash-flood events resulting from paroxystic meteorological events concentrated in time and space are insufficiently documented as they produce destructive effects. They are hardly measurable and present single features that are not transposable to another event. In the South of France, the flash flood of November 1999 gives a perfect illustration of these characteristics. The physical complexity of the process and consequently the volume and the variety of the data to take into account are incompatible with the real time constraint allocated to the forecasters confronted to the occurrence of such phenomena. So, we have to make choices to afford acceptable simplifications to the complete mechanical model. MARINE (‘Modélisation de l''Anticipation du Ruissellement et des Inondations pour des évéNements Extrêmes’) is the operational and robust tool we developed for flash-flood forecasting. This model complies with the criterions of real-time simulation. It is a physically based distributed model composed of two parts: first the flood runoff process simulation in the upstream part of the basin modelled from a rainfall–runoff approach, then the flood propagation in the main rivers described by the Saint-Venant equations. It integrates remote sensed data – Digital Elevation Model, land-use map, hydrographic network for the observations from satellites and the rainfall evolution from meteorological radar. The main goal of MARINE is to supply real time pertinent information to the forecasters. Results obtained on the Orbieu River (Aude, France) show that this model is able to supply pertinent flood hydrograph with a sufficient precision for the forecasting service to take the appropriate safety decisions. Furthermore, MARINE has already been tested in the French National Flood Forecasting Service of Haute-Garonne in real conditions. To cite this article: V. Estupina Borrell et al., C. R. Geoscience 337 (2005). [Copyright &y& Elsevier]

In this study, a methodology is presented for elaborating an urban development indicator (UDI). This indicator was designed to describe the optimum conditions for the well-being of urban populations and to allow for efficient comparisons between urban environments — in this case, Abidjan, Côte d'lvoire and Montreal. Seven criteria were used to formalize the indicator, which were estimated from standardized indices and then ranked before joining them together to form one parameter. The composite nature of the UDI thus allowed the researchers to establish that the urban development in the city of Abidjan in 1995 could be characterized as average, but that Montreal Island had a strong state of urban development for the same period. Moreover. by comparing UDls for the two cities, the researchers revealed the need for additional health and educational facilities in Abidjan. The studies carried out on these two urban communities validate the relevance of UDI for quantifying and comparing rates of urban development. Such methods can be used by decision-makers to establish urban policies for sustainable urban development. [ABSTRACT FROM AUTHOR]

The aim of this work is to assess the use of (SPOT) multispectral visible infrared remote sensing to study microphytobentos assemblages in a shellfish ecosystem (Bay of Bourgneuf, France). SPOT satellite images (acquired at low tide in spring or autumn between 1986 and 1998) were calibrated using in situ radiometric data, and the normalised vegetation index (NDVI) obtained from these images showed microphytobenthos on bay mudflats. Proliferation was mainly along a north-south strip, essentially localised around the +2 m isobath and covering a surface area of 19 to 25% of the total mudflat area studied (420 to 550 ha). Three factors seem to be responsible for the spatial structure of the assemblages: bathymetry, nutrient input from the Falleron River and its channel, and the location of oyster-farming areas. Although spatial and spectral resolutions of multispectral remote sensing data have certain limitations, this approach opens up a new field of application for hyperspectral remote sensing, particularly for synoptic mapping of biomass distribution. To cite this article: V. Me´le´der et al., C. R. Biologies 326 (2003). [Copyright &y& Elsevier]

The detection of dense populations of ragweed (Ambrosia artemisiifolia L.) using spatial remote sensing methods seems possible. A sufficiently accurate map of parcels of land infested with ragweed could offer new possibilities to engage in weeding campaigns and to appreciate the space-time evolution of this plant. Obviously, the main difficulties in this approach are related to the heterogeneous floral composition of herbaceous stands and to the risk of confusion of the spectral composition of ragweed with that of other species. On 21 July 2001, we carried out field surveys in zones with abundant ragweed near Lyon (Department of the Rhone), and we used the resulting data in connection with two images of the same area obtained by the Terra ASTER 1B satellite on 26 June and 13 August 2001. A measurement was made in the laboratory on a sample of the plant obtained from the same area to determine its reflectance spectrum. On analysis of the spatial images, we were able to localize herbaceous patches in which ragweed is dominant. When the density of this plant decreases, the reflectance signals of the populations become multiform, requiring further studies. Further progress can be expected when sensors such as the spatial tel IKONOS (operating at a resolution in the order of 1 to 5 m) or the future SPOT 5 (operating at a resolution of 2 to 3 m in the panchromatic mode or at 10 m in a multispectral mode) will be used, allowing us to work at a resolution on the order of one meter. [Copyright &y& Elsevier]

An in-depth knowledge of the three-dimensional geological environment is an important factor in the conservation of rock art in caves because of the beneficial or harmful effects of thermal cycling, water transport, natural or induced tremors, air currents, as well as the presence of visitors. The intermittent or continuous measurement of these parameters, which may be disruptive, necessitates the perfection of specific indirect methods such as microgravimetric, seismic, or electrical prospection and infrared remote sensing. The application of these methods is always difficult in places where access may be limited. [ABSTRACT FROM AUTHOR]