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The Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, Nunavut (74°55′N, 109°34′W) was established in 2003 to examine Arctic ecosystem processes that would be impacted by climate warming and permafrost degradation. This paper provides a synthesis of how remote sensing has contributed to biogeophysical modelling and monitoring at the CBAWO from 2003 to 2023. Given the location and isolated nature of the CBAWO in the Canadian High Arctic, remote sensing data and derivatives have been instrumental for studies examining ecosystem structure and function at local and landscape scales. In combination with field measurements, remote sensing data facilitated mapping and modelling of vegetation types, % vegetation cover and aboveground phytomass, soil moisture, carbon exchange rates, and permafrost degradation and disturbance. It has been demonstrated that even in an environment with limited vegetation cover and phytomass, spectral vegetation indices (e.g., the normalized difference vegetation index) are able to model various biogeophysical variables. These applications are feasible for research sites such as the CBAWO using high spatial resolution remote sensing data across the visible, infrared, and microwave regions of the electromagnetic spectrum. Furthermore, as the satellite record continues to expand, we will gain a greater understanding of the impacts arising from the expected continued warming at northern latitudes. Although the logistics for research in the Arctic remain challenging, today's technologies (e.g., high spatial resolution satellite remote sensing, automated in situ sensors and data loggers, and wireless communication systems) can support a host of scientific endeavours in the Arctic (and other remote sites) through modelling and monitoring of biogeophysical variables and Earth surface processes with limited but critical field campaigns. The research synthesized here for the CBAWO highlights the essential role of remote sensing of terrestrial ecosystems in the Canadian Arctic.

Various remotely sensed data, including historical aerial photographs, declassified intelligence satellite photographs, optical satellite imagery, and synthetic aperture radar data, were used to undertake the first comprehensive reconstruction of the dynamics of Airdrop Glacier on Axel Heiberg Island, Nunavut. Observations show a continuous terminus advance totalling ∼6 km since 1950 and notably less variability in its surface velocities in comparison to adjacent Iceberg Glacier. This advance is concurrent with relatively high flow rates over its entire surface, resulting in significant thickening near the terminus and thinning at higher elevations. Velocities have more than halved from the mid-2000s to 2021, but without any definitive evidence of previous flow instabilities, we cannot confirm whether Airdrop's behaviour is cyclic in nature and therefore characteristic of a surge. Instead, Airdrop Glacier could be experiencing a delayed response to the positive mass balance conditions of the Little Ice Age, which could also explain the advance of other nearby glaciers. Its recent slowdown could then be indicative of a gradual adjustment to recent climatic conditions. This study highlights the need for comprehensive studies of glacier dynamics in the Canadian Arctic to improve our understanding of the factors triggering dynamic instabilities and causing the observed variety of behaviours.

Thinning sea ice cover and earlier melt in the Arctic impact primary producer (PP) phenology, causing earlier ice algal bloom termination and phytoplankton bloom commencement. However, logistic constraints limit capturing the complete seasonal evolution of PPs and their physical drivers. Here, we combine spectral irradiance data from subsurface oceanographic moorings with synthetic aperture radar backscatter and meteorological variables to study light in Dease Strait, investigating its relation to timing and magnitude of surface PPs for 2017 and 2019. Ice algal blooms in 2017 and 2019 lasted 66 and 84 days, respectively, peaking within 2 days of snow melt onset. In 2019, lower temperatures and a deeper snowpack before snow melt extended the ice algal bloom. Melt pond formation increased light transmission, enabling a short, 6–7-day under-ice phytoplankton bloom in both years that was likely nutrient-limited. The 2019 phytoplankton bloom was less productive, possibly due to the longer ice algal bloom depleting surface nutrients. After ice break-up in 2019, a 31-day late-summer bloom occurred via wind-driven mixing. Our findings suggest that the combined remote sensing technique has novel applicability in other settings, providing insights into the changing state of PP phenology, and the need for long-term Arctic observations to discern regional climate change effects.

River estuaries along western Hudson Bay, Canada, are important summer habitats for beluga whales (Delphinapterus leucus (Pallas, 1776)) and subject to increasing industrial development activities including vessel traffic. The feasibility of establishing a National Marine Conservation Area (NMCA) in western Hudson Bay is under consideration, requiring baseline studies and habitat monitoring. In this study, beluga whale locations were identified using aerial photographs collected during summer 2018 of the Seal, Knife, Churchill, and Nelson River estuaries. Sentinel 2 wavelength bands were used to outline river plume boundaries for the Seal, Knife, and Churchill Rivers. Multiple discriminant analysis was used to differentiate between beluga habitat areas according to their environmental characteristics including concentration of total suspended sediments (TSS), and coloured dissolved organic matter (CDOM). The Seal River estuary, Knife River estuary, Churchill River outer estuary, Churchill River estuary, and Nelson River estuary were identified as distinct habitat areas. Resource selection functions and model selection were used to determine that habitat variables related to prey availability were important for beluga habitat selection, including TSS, CDOM, and the distance to river mouth or river plume. Identification of preferred habitat and habitat areas in this study are imperative for future management decisions including establishment of an NMCA.

Northern ecosystems are vulnerable to surface disturbances caused by warming climate and human activities. The Ogilvie Mountains in central Yukon are an important region that should be monitored, as it is a major transportation corridor connecting northern communities. This study aims to characterize 35 years of landscape changes in the Tombstone Territorial Park and the surrounding region of the Ogilvie Mountains by detecting and interpreting landscape changes using a Landsat-derived trend analysis and multilevel image interpretation. Statistically significant spectral changes occurred in 24% of the study area between 1986 and 2021, and most of these changes are gradual and associated with vegetation succession and hydrological processes (i.e., erosion and deposition). Other landscape changes included wildfires, slumps, changes to riverbanks and lake shores, earlier melting of icings in the summer, degradation on the peripheries of some ice-wedge polygonal terrain, and potential insect damage to forests. Our investigation reveals that the extent and magnitude of landscape changes in the study area are influenced by climate, geomorphic setting, ecological succession, and glacial history of the region. Given a varied combination of ecotypes, spatial and temporal variations are to be expected in terms of the response of the landscape to climate and anthropogenic disturbances.

Copyright of Majalat Monazaat Al-Aamal is the property of Majalat Monazaat Al-Aamal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article begins by observing the spatio-temporal heterogeneity of deforestation in Northern Benin over the past four decades. In order to understand the underlying reasons for these spatial disparities, we conducted a thorough inquiry among residents of areas where woody cover has diverged significantly from the regional trend. Utilizing textual statistical methods, our analysis of these interviews has yielded deeper insights into specific local nuances in the population's perceptions of the ongoing environmental changes within their territories. Furthermore, our investigations have underscored a worsening of social and land inequalities that impact the entire region. The persistence of deforestation in Northern Benin, alongside the expression of economic and social vulnerability among the surveyed populations, mirrors situations already observed in several other rural regions of West Africa.

Context and background: In current industrialized world, extremely increase of urbanization, Agriculture land expansion and climate change have led to increase of degradation of wetland in many basins and coastal area, which result to the malfunction of its ecosystem services. However, there are few studies have been conducted to analyze how the historical degradation of wetland will continue in the future especially in most of the developing countries. Goal and objectives: The overall objective of the study intents to provide an integrated method which includes GIS, remote sensing and CA-Markov Chain modelling to analyse the influence of LULC dynamic into wetland degradation. Specifically, is to use historical land use/cover maps of 2000,2010 and 2020 to develop land use simulation model to predict the spatial degradation of wetland for three decades. Methodology: In this study will use historical land use/cover maps of 2000,2010 and 2020 to develop land use simulation model to predict the spatial degradation of wetland in Wami-Ruvu river basin for coming 30 years (2020-2050) under different scenarios using land change modeler (LCM) in Idris-TerrSet. Future land use/cover map of the study area was developed using Markov chain and artificial neural network (ANN) Analysis in LCM modeler. Results: The study found of about 1209.0753Km2 (2%), 949Km2 (1.4%), 521.33Km2 (0.78%) and 213 (0.32%) of wetland was decreasing, which was equal to 1339999, 1055066, 578584and 237199 for the year 2000, 2010, 2020 and 2050 for the individual pixel values respectively, which made a half of the total simulated wetland to have been lost that is 50% of the land in the study region.

As the Arctic is warming, permafrost coasts are eroding faster, threatening coastal communities, habitats, and altering sediment and nutrient budgets. The western Canadian Arctic is eroding at a rapid pace; however, little is known on changes occurring in the Amundsen Gulf area. This study was conducted in the eastern coast of Parry Peninsula, a neglected rock-dominated coastal area. We used orthorectified aerial photos of 1965 and 1993 and very high-resolution satellite imagery of 2020 to manually delineate the shoreline according to backshore and foreshore centered approaches. Shoreline change rates were calculated and sediment and organic carbon transfer from land to sea estimated using digital elevation model, the Northern Circumpolar Soil Carbon Database, and ground ice content. The results show a mean erosion rate of 0.12 m/yr for the backshore zone and 0.16 m/yr for the foreshore zone, with increasing erosion in the Paulatuk Peninsula in recent decades. The average sediment transfer from land to sea was 20 m3/m/yr and the soil organic carbon (SOC) flux was 7 kg C/m/yr. We highlight the importance of using the cliff-top as shoreline reference to accurately estimate sediment and SOC transfers, an approach neglected in automatic shoreline delineation techniques based on remote sensing imagery using the waterline.

Research Purpose: Proposes a methodology for space-time analysis of fires/burn on a microregional scale based on free data from the burning program of INPE –National Institute for Space Research and use of free software. Methodology: The methodological referral covered the reference on the subject, the acquisition of accessible vector and matrix data and records from the INPE fires/burn database. The product validation was referenced in the publications of INPE fires and reports. Findings: The results revealed that of the 209 burn detected in the South Coast Microregion of the State of Espírito Santo, Brazil between 2009 and 2019, 60.3% or 126 occurred in land uses of "Pasture" and in "Temporary Crops". It also showed 4 registers inside the Conservation Units -UCs and 26 the damping zone of 3 km of the UCs. The monthly analysis indicated the highest records in the months marked by low rainfall and dry indices, with the highlight for July to September, concentrating 45.9% or 93 of the 209 occurrences. Originality/Value: The use of the methodology offers an important contribution to control and monitoring actions, which can be applied in municipalities or regions that need studies of this nature, because it considered the occurrences in the territory from reference data of accessible fires, charting with free software places most susceptible to disasters of this nature.

The paper is aimed at assessing the associations between the road networks geography and dynamics of wildfire events in the East Siberian boreal forest. We examined the relationship between the function of roads, their use, and management and the wildfire ignition, propagation, and termination during the catastrophic fire season of 2016 in the Irkutsk Region of Russia. Document analysis and interviews were utilized to identify main forest users and road infrastructure functional types and examine wildfire management practices. We combined community observations and satellite remotely sensed data to assess relationships between the location, extent, and timing of wildfires and different types of roads as fire sources, barriers, and suppression access points. Our study confirms a strong spatial relationship between the wildfire ignition points and roads differentiated by their types with the highest probability of fire ignition near forestry roads and the lowest near subsistence roads. Roads also play an important role in wildfire suppression, working as both physical barriers and access points for firefighters. Our research illustrates the importance of local and Indigenous observations along the roads for monitoring and understanding wildfires, including “zombie fires”. It also has practical implications for fire management collectively developed by authorities and local communities.

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.

Abstract On February 6, 2023, two earthquakes shook the southern and central Türkiye causing significant loss of human life and devastating many cities. These are related to the active East Anatolian Fault (EAF). In this study, the digital image correlation (DIC) technique is applied to map the coseismic displacements. For that, a pair of scenes from the Sentinel-2 satellite acquired before and after the seismic events was used. The results showed that the methodological approach can be effectively used to map and monitor large-scale geological phenomena and can assist in seismic risk assessment.

The Boudahar massif is located in the southern part of the eastern belt of the Moroccan High Atlas and it corresponds to a reef mass of about ten kilometers in length. Jbel Boudahar is a district of lead-zinc-barite mineralization, known by a strong artisanal exploitation of its ores. This district is characterized by its topography with a contrast of altitude and an arid environment, which makes the information acquired more valuable. The processing of Landsat 8 OLI data allowed us to extract a lithological and structural map, aiming to make correlations to understand the distribution of lead-zinc mineralization. To this end, several tests were carried out, including the composition of color, principal component analysis and band ratio transformation. The location of the main deposits at Jbel Boudhar coincides well with the lineament derived from band 1 of principal component analysis and with the dolomitic pliensbachian formations mapped by MNF and BR from Landsat Oli8. A remote sensing geological prospecting model has been established for the Jbel Boudhar lead-zinc deposits, providing a basis for future prospecting of new deposits in a similar context.

Increased industrial development in the Arctic has led to a rapid expansion of infrastructure in the region. Localized impacts of infrastructure on snow distribution, road dust, and snowmelt timing and duration feeds back into the coupled Arctic system causing a series of cascading effects that remain poorly understood. We quantify spatial and temporal patterns of snow-off dates in the Prudhoe Bay Oilfield, Alaska, using Sentinel-2 data. We derive the Normalized Difference Snow Index to quantify snow persistence in 2019–2020. The Normalized Difference Vegetation Index and Normalized Difference Water Index were used to show linkages of vegetation and surface hydrology, in relationship to patterns of snowmelt. Newly available infrastructure data were used to analyze snowmelt patterns in relation infrastructure. Results show a relationship between snowmelt and distance to infrastructure varying by use and traffic load, and orientation relative to the prevailing wind direction (up to 1 month difference in snow-free dates). Post-snowmelt surface water area showed a strong negative correlation (up to −0.927) with distance to infrastructure. Results from field observations indicate an impact of infrastructure on winter near-surface ground temperature and snow depth. This study highlights the impact of infrastructure on a large area beyond the direct human footprint and the interconnectedness between snow-off timing, vegetation, surface hydrology, and near-surface ground temperatures.

يركز البحث على كشف وتحليل التغير فى كثافة الغطاء النباتى لروضة خُريم خلال الفترة 1998-2022 بإستخدام تقنية الإستشعار عن بعد ونظم المعلومات الجغرافية، حيث تم استخدام المرئيات الفضائية للقمر الصناعى 5 و8 LandSat، حيث اعتمدت الدراسة على دراسة مؤشر الإختلاف الخضرى (NDVI) Normalized Difference Vegetation Index وعلاقة ذلك بمعدلات التساقط فى نطاق الدراسة حيث يعكس استجابة الغطاء النباتى للتذبذب السنوى فى الأمطار، بناءً على تحليل كشف الغطاء Change Detection وإرتباطها بكميات التساقط إضافة إلى تحليل التطابق Overlay لقياس فروق المساحات فى الغطاء النباتى فى الفترة من 1998-2021م وتحديداً خلال شهرى يناير ويونيو. توصلت الدراسة إلى أن التغطية النباتية بروضة خُريم شهدت تغيراً سلبياً بشكل عام خلال فترة الدراسة، حيث بلغت نسبة التغير بشهر يناير 8.4% ويونيو 49.4% لذلك أوصت الدراسة بضرورة تكامل وتواصل المؤسسات المعنية بالحفاظ على الغطاء النباتى بالمملكة لتبادل الخبرات والمشروعات البحثية بهدف تحقيق الحماية البيئية المستدامة للغطاء النباتى. Abstract The research focuses on detecting and analyzing the change in the density of the vegetation cover of Rawdat Khuraim during the period 1998-2022 using remote sensing technology and geographic information systems, where the satellite visualizations of satellites 5 and 8 LandSat were used. The study relied on the study of the Normalized Difference Vegetation Index (NDVI). Vegetation Index and its relationship to precipitation rates in the scope of the study, as it reflects the response of vegetation to the annual fluctuation in rainfall, based on the change detection analysis and its association with precipitation amounts, in addition to the overlay analysis to measure area differences in vegetation cover in the period from 1998-2021 AD, specifically during the months of January and june. The study concluded that the vegetation coverage in Rawdat Khuraym witnessed a negative change in general during the study period, as the percentage of change in January reached 8.4% and June 49.4%. Therefore, the study recommended the need for integration and communication between institutions concerned with preserving the vegetation cover in the Kingdom to exchange experiences and research projects with the aim of achieving sustainable environmental protection for vegetation.

Nowadays, satellite systems are experiencing noticeable disruptive issues due to the single functionality, high cost of operations, and limited adaptability. This paper presents a satellite mission control system with RF duplex communication, which gives multiple functionalities and health monitoring systems with solar tracking capability. This aims to present a flexible and affordable solution called the Remote Sensing Mission Sentinel Pro Platform. The quantitative approach is used and implemented to trans-receive data from space and pass it to the ground station. Arduino-based prototype uses the nRF24L01 module with an antenna at the ground station to trans-receive satellite data has been developed. Testing and verifications of the developed platform prototype indicated that satellites could monitor key health parameters, including temperature, humidity, and battery charge capacity.

Significant advancements have been made in remote sensing technologies, with increasingly refined applications in creating LULC maps. The integration of Machine Learning-based approaches has been explored to develop LULC maps with varying levels of precision, leveraging diverse satellite imagery. However, the task of producing LULC maps for extensive areas like the Fez-Meknes region, covering an area of approximately 40,075 km2, can be challenging using traditional methodologies. Thus, this study prioritized the major objective of establishing a reference for extracting LULC information. This endeavour involves the comparative assessment of the performance of different LULC classification approaches: Recursive Partitioning (Rpart), k-nearest neighbors (KNN), random forest (RF), Linear Discriminant Analysis (LDA), support vector machine (SVM), and extreme gradient boosting (XGBoost). For map production, remote sensing data and a supervised classification algorithm based on LANDSAT images of the Fez-Meknes region were employed. The accuracy of the generated maps was assessed using overall accuracy and Kappa coefficient. This methodology holds the potential to be replicated in other regions, utilizing a variety of available remote sensing satellite images to generate LULC maps. Essentially, the approach proposed in this study will be a valuable tool for planners, facilitating the acquisition of LULC maps at various time intervals. This will facilitate the classification of land cover types in a faster and more cost-effective manner.

Forest fires are a type of natural catastrophe that poses a risk to the vegetation and fauna of the hill stations. Due to the presence of vast enormous areas of land adorned with aged trees, vegetation, and wild life, safeguarding the ecosystem is both critical and arduous. A Geographic Information System and Remote Sensing assist in resolving this issue through the continuous monitoring of the forest using satellite, aerial, and drone-based imagery gathered from a variety of sources in India and Abroad. Landsat8 series Band 4, Band 5, Band 6 and Band 7 is used for the study. Following the correction and analysis of reflectance values for pre-fire and post-fire imagery, the Normalized Burn Ratio (NBR) is computed and processed. Finally, the difference in NBR based on the pre-fire event and post-fire event for the Yercaud hill station is analyzed and the severity level is classified for the chosen area of interest.

Soil erosion is an important concern due to the steepness of the terrain and the significant elevation differential between the upstream and downstream regions of the basin. Revised Universal Soil Loss Equation (RUSLE) was integrated with Remote Sensing (RS) and Geographic Information System (GIS) in the current work establish the annual soil erosion map in the Bulango Ulu Reservoir basin. The RUSLE model incorporated soil erosion zonation features such as rainfall erosivity, soil erodibility, topographic, vegetation cover, and conservation support practices. The results show that 0 and 110.31 t year−1 are the minimum and maximum soil erosion, with the average rate of soil erosion is 17.30 t year−1 in the present study area. Soil erosion risk regions were divided into five categories: very slight, slight, moderate, severe and extremely severe soil erosion areal extent and area percentages is 229.17 km2 (94.48%), 7.83 km2 (3.23%), 4.25 km2 (1.75%), 1.20 km2 (0.50%), and 0.12 km2 (0.05%), respectively. The Area Under Curve was indicated that RUSLE model had good performance (75.1%). This study demonstrates the utility of GIS and remote sensing for predicting soil erosion, allowing important information to be extracted for implementing soil conservation programs in the Bulango Ulu reservoir basin.

— Lithological mapping is a crucial factor in identifying and mapping the spatial distribution of minerals. It aids in accurately defining the most promising primary prospects for local exploration. The differentiation of rock units across a wider region is likely to be attributed to remotely sensed satellite data. Therefore, the research focuses on utilizing remote sensing methods to create a geological map for a specific area in Salem district, Tamil Nadu, by employing HYPERION and ASTER satellite images. Various techniques, such as Band Ratio (BR), Spectral Angle Mapper (SAM), Minimum Noise Fraction (MNF), Mixture Tuned Mapped Filtering (MTMF), Spectral Feature Fitting (SFF), and Support Vector Machines (SVMs), are utilized to classify lithological units, which are crucial for data analysis. The outcomes of these methods will be compared to field-mapped geological boundaries to assess accuracy. In the final phase, a highly precise geological map is produced by combining remote sensing data with on-site investigations. The application of these approaches holds significant potential for enhancing geological mapping and mineral exploration in hard-to-reach areas.

Papua New Guinea has plenty of land with suitable agro-climatic conditions for rice farming, but despite this, the country still needs to import rice to meet the demands of its rapidly growing population and urbanization. To address this issue, a research project was undertaken to create a realistic scope and map of areas within each province of Papua New Guinea that are suitable for rice production, using Remote Sensing (RS) and Geographic Information System (GIS) techniques. The study included nineteen regions of Papua New Guinea. A digital surface model was used to determine the suitability of each area for large-scale rice farming, based on climate, soil factors, and topography. The Erdas Imagine v-11 model builder was used to create a critical model for the suitability of rice mapping. Each province was classified into five classes based on the suitability of the land for rice farming. The results showed that approximately 14% of the land in Papua New Guinea is exceptionally suitable for rice farming. Eight provinces (Central, East Sepik, East New Britain, Morobe, Madang, Milne Bay, West New Britain, and Western Province) were identified as having large-scale land suitable for rice production and were evaluated accordingly.

Context and background: Wheat is one of the oldest crops in the world and has always been one of the most important staple foods for millions of people around the world, especially in North Africa, where wheat is the most dominant crop. The importance of wheat yield estimation is well known in agricultural management and policy making at regional and national levels. In semi-arid areas such as the case of Morocco, an operational cereal yield estimating system that could assist decision makers in planning annual imports is needed. In some developed countries, several effective tools are now available to monitor crops and optimize farm-level decisions by combining crop simulation models with seasonal forecasts. However, few tools are used to effectively manage crops at the farm level to cope with climate variability and risk. Goal and objectives: The following article presents an overview of current methods used for wheat yield estimation in the world and in Morocco Methodology: Various sections describing traditional methods, simulation models, and remote sensing. Then a section is devoted to the estimation methods used in Morocco and their efficiencies. Results: This article is very useful for researchers working on this subject because it brings together all the methods of estimating wheat yields worldwide and classifies them into categories and then situates Morocco, which is a relevant example of a North African country that is a leader in the use of spatial techniques and in the monitoring of crops, and wheat in particular.

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]

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]

Abstract Mass movements naturally occurring along slopes, especially after heavy rains, cause heavy losses of materials and life and affect highways, pipelines, and bridges, among other structures. Among the most common mass movements, landslides and subsequent mass flows especially stand out. Remote sensing and geoprocessing techniques are useful tools for geological and geotechnical analysis, here applied to characterization of mass movements from the analysis of the influence of slopes, lineaments or fractures, and geological-geotechnical at the junction of the Curral homocline and the Moeda syncline, Quadrilátero Ferrífero, Southeast Brazil. The area consists of Archean granitic-gneissic basement and the greenstone belt sequence of the Rio das Velhas Supergroup with Proterozoic metasedimentary rocks of the Minas Supergroup covering these two older successions. Based on satellite images, a preliminary map of lineaments was created, and fractures were grouped according to their direction before being rasterized. Each lineament group was associated with a previously known geological and/or structural feature. Geological units mapped in the area were numerically classified according to their mass movement susceptibility and related geotechnical units. Using a Shuttle Radar Topography Mission (SRTM) image, a terrain slope raster was generated. The objective was to obtain a raster indicating low and high probabilities of mass movements. Four sets of lineaments were identified: the first set associated with the northeast strike stratification of the rocks of the Moeda Formation; the second set related to eastward-trending warp axis lineations; the third set related to the southeast trend of stretch lineaments or mafic dykes directions; and the fourth set evidently associated with the watershed pattern of the Curral Range crest, perpendicular to the strike of the rocks in the area. Simulations with different combinations of parameters produced eight scenarios were generated were constructed to classify the area as to its susceptibility to rupture through changes in slope, lithotype, and lineament density; the first four (1 to 4) were classified by using the slope percentage raster without interval reclassification, so its values in the cartographic algebra were not grouped. The last for (5 to 8), consider the slope percentage classified. This methodology successfully combines mathematical models for predicting mass movements and determining areas in the urban landscape most susceptible to these phenomena. As such, it comprises a useful tool for government planning of preventative actions for areas of high risk.

Copyright of VertigO is the property of La Revue Electronique en Sciences de l'Environnement VertigO and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

The Bathurst caribou (Rangifer tarandus groenlandicus (Borowski, 1780)) herd declined from ∼349 000 animals in 1996 to ∼8200 in 2018. Climate-driven changes to tundra and boreal vegetation is one hypothesis for the decline. We modelled and mapped annual productivity and phenology across the herd’s range using enhanced vegetation index (EVI) data derived from a Moderate Resolution Imaging Spectroradiometer (MODIS) time series spanning 2000–2017. Maximum annual EVI, growing season length, and time-integrated EVI increased significantly on 16%, 18%, and 49% of the core annual range, respectively. Trends toward longer growing seasons were driven entirely by earlier spring green-up and, along with time-integrated EVI, were most prevalent in tundra regions. Trends in forested regions were overwhelmingly related to the influence of forest fires, which burned more than half of the range below the forest–tundra ecotone since 1965. These trends suggest that climate-driven changes in production and phenology have occurred in the tundra and forest–tundra portions of the range and could have contributed to the recent herd decline. However, the trends may also be a result of herd decline itself, given the loss of this large herbivore from the landscape. Elucidating cause and effect will require comprehensive analysis of interactions between climatic variables, herd dynamics, and vegetation change, complemented by targeted field investigations.

Abstract The study adopts a number of soil salinity indices by applying geoinformatics techniques in the northeast of the Nile River Delta, based on the different spectral reflectance of soil salinity. The field investigation is carried out by collecting soil samples, and chemically analyzing them in order to compare them with the results of the indices (8 indices), relying on field review so as to capture images indicative of soil salinity and its impact on the land use that is most vulnerable to it, and this is vegetation. This is mainly for the sake of supporting the accuracy of the spectral resolution. It is found that each index relies on different variables of spectral reflectance. Accordingly, the study identifies the most appropriate and effective indices for assessing salinity, both spatially and temporally, in the northeast of the Nile River Delta. This is done through determining the highest degree of correlation between the results of the indices and the results of the chemical analysis of soil samples. Moreover, the study relies on the best indices in determining vegetation, which is EVI, so as to find out the degree to which the vegetation density is affected by soil salinity. This is carried out with the aim of coming up with results that help decision-makers in addressing the problems resulting from soil salinity with the least effort, the lowest cost, and the highest accuracy and realism. المستخلص باللغة العربية اعتمدت الدراسة عدد من أدلة ملوحة التربة عن طريق تطبيق تقنيات الجيوانفورماتيکس شمال شرق دلتا نهر النيل، مستندة على الانعکاسات الطيفية المختلفة لملوحة التربة. وتم التحقق الميداني عن طريق تجميع عينات من التربة وتحليلها کيميائياً، بغرض مقارنتها بنتائج الأدلة (8 مؤشرات)، مع الاعتماد على المراجعة الحقلية لالتقاط الصور المعبرة عن ملوحة التربة وأثارها على أکثر استخدامات الأرض حساسية لها وهو الغطاء النباتي، وذلک لتدعيم دقة التمييز الطيفي. وقد تبين أن کل مؤشر يعتمد على متغيرات مختلفة من الانعکاسات الطيفية، ومن ثم لجأت الدراسة إلى تحديد أفضل المؤشرات المناسبة والفعالة في تقييم الملوحة زمانياً ومکانياً شمال شرق دلتا النيل، وذلک عن طريق تحديد أعلى درجة ارتباط بين نتائج المؤشرات ونتائج التحليل الکيميائي لعينات التربة، کما اعتمدت الدراسة على أفضل المؤشرات في تحديد الغطاء النباتي وهوEVI لمعرفة درجة تأثر کثافة الغطاء النباتي بملوحة التربة، وذلک بهدف الخروج بنتائج تساعد صناع القرار في معالجة المشاکل الناتجة عن ملوحة التربة بأقل جهد وأقل تکلفة وتکون أکثر دقة وواقعية.

Abstract The floor of Wadi An-Natrun Depression has a high level of salinity and occupies by a shallow salt lakes, which are characteristic geomorphologic landforms. In general, Wadi An-Natrun Depression is characterized by very arid climate. The geological formations of Wadi An-Natrun Depression range from lower Miocene, lower Pliocene and Quaternary deposits. This study attempts to determine the effectiveness of using remote sensing indicators in deducing sabkhas in the Wadi El-Natrun depression utilizing Landsat 8 OLI satellite images based on field data of laboratory analyzes of sabkhas soil samples collected through the field study. To achieve this, linear and multiple regression models were applied between soil salinity and electrical conductivity (ECe) on the one hand and remote sensing indices on the other hand, where the NDSI index had the highest correlation coefficient of 0.872. This was followed by the derivation of the Enhanced soil salinity index from (NIR), (SWIR) 2 and the NDVI index, which had higher correlation than NDSI with electrical conductivity (ECe) of 0.918 . المستخلص باللغة العربية يتميز قاع منخفض وادي النطرون بمستوى عالٍ من الملوحة وتحتله بحيرات ملحية ضحلة والتي تعد من أهم المظاهر الجيمورفولوجية بالمنخفض ، وبصفة عامة فإن مناخ منخفض وادي النطرون يتسم بشدة الجفاف ، تتراوح التکوينات الجيولوجية بالمنخفض بين الميوسين الأسفل والبليوسين الاسفل بالإضافة إلي رواسب البليستوسين والحديث . تحاول هذه الدراسة تحديد فاعلية استخدام مؤشرات الاستشعار عن بعد في استنباط السبخات بمنخفض وادي النطرون باستخدام صور القمر الصناعي لاندسات 8 OLI إرجاعاً إلي بيانات فعلية للتحليلات المعملية لعينات تربة السبخات والتي تم جمعها من خلال الدراسة الميدانية . ولتحقيق ذلک ، تم تطبيق نماذج الانحدار الخطي والمتعدد بين ملوحة التربة والتوصيل الکهربائي (ECe) من ناحية ومؤشرات الاستشعار عن بعد من ناحية اخري ، حيث کان لمؤشر NDSI أعلى معامل ارتباط قدره 0.872. ، تبي ذلک اشتقاق مؤشر ملوحة التربة المحسن بالاعتماد علي النطاقات الطيفية (NIR) و (SWIR) 2ومؤشر NDVI ، و کان لهذا المؤشر ارتباط أعلى من NDSI مع التوصيل الکهربائي (ECe) بلغ 0.918.

The urban pattern has changed significantly in Latin American cities over the last decades. Since the 1980s, urban policies have increased the periphery land value, promoting suburbanization that restricted spaces for informal settlers. The study used Landsat imagery to analyze if urban pattern changes in Bogota, Colombia and Sao Paulo, Brazil forced informal settlements to move closer to environmental risk areas or areas with limited mobility. This research used a stratified supervised classification to locate formal and informal developments in 2000 and 2018, followed by multiple criteria evaluation to categorize environmental risk and mobility in the study area. The results revealed that segregation in the periphery of cities is not a generalized pattern in the city periphery but a localized phenomenon encouraged by urban policies.

IN THE CURRENT STUDY, THE UNIVERSEL SOIL LOSS EQUATION (USLE) IS APPLIED TO MODELING THE SOIL WATER EROSION IN OUED CHERRAT WATERSHED LOCATED IN THE WEST OF MOROCCO. USLE MODEL TAKES IN CONSIDERATION THE MAIN FACTORS THAT INFLUENCE WATER EROSION : RAINFALL, TOPOGRAPHY, SOIL PROPERTIES, THE CONDITIONS OF CROP MANAGEMENT AND CONSERVATION PRACTICES. MANY DATA, FROM VARIOUS SOURCES WAS USED THROUGH THE SPATIAL TOOLS, GIS (GEOGRAPHIC INFORMATION SYSTEMS) AND REMOTE SENSING, TO ASSESS THE RISK OF WATER EROSION. THE RESULTS SHOW THAT 65.7% OF THE STUDY AREA HAS A VERY LOW RISK OF EROSION, 7.7% LOW RISK, 9.9% MEDIUM RISK, 5.4% HIGH RISK AND 11.3% A VERY HIGH RISK. THE SOIL LOSS VARY BETWEEN 0 AND 524.15 T/HA/YR. THE AVERAGE RATE OF EROSION FOR THE ENTIRE WATERSHED IS ESTIMATED TO 12.16 T/HA/YR. PRIORITY AREAS FOR EROSION MANAGEMENT REPRESENT 16.7%. GENERALLY CHARACTERIZED BY HIGH SLOPES, THEY ARE MAINLY LOCATED IN THE UPSTREAM OF THE WATERSHED AND ON THE BANKS OF OUED CHERRAT AND ITS STREAMS. [ABSTRACT FROM AUTHOR]

Copyright of Algerian Journal of Arid Environment (AJAE) is the property of University of Kasdi Merbah Ouargla and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Nouvelles Perspectives en Sciences Sociales is the property of Editions Prise de parole and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of VertigO is the property of La Revue Electronique en Sciences de l'Environnement VertigO and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Urban heat zone are the major problem affecting human health through the microclimatological effect. Green Spaces are like a natural air conditioners that can cool dense urban environments from hot air. The cooling effect of urban heat from the presence of Green Space is called the Urban Cooling Effect (UCE) while the cool air produced is called Urban Cooling Island (UCI). This research aims to analyze the extent to which UCI is able to neutralize UHI by urban cooling. This study of this research was conducted in Kapanewon Depok around the North Ringroad zone. In the research, the Remote Sensing method was used utilizing Landsat-8 and processed with ArcGIS to determine the patterns and dynamics of UCI and UHI and was equipped with field data measurement and interviews data using questionnaires. The results obtained were that the coldest and largest UCI Spot was at Babarsari Camping Ground, 27,777°C in 159,218 m2, with green space types consisting of shrubs, grass, plants, mixed trees and flowing river. Questionnaire results show that the majority of residents still feel hot. It was concluded that although Green Space is useful in cooling cities, but UCI VS UHI is still dominated by UHI’s influence.

The dynamic development of modern cities requires new solutions to urban planning and management by local regional authorities. The paper focuses on ecological indicators based on Earth Remote Sensing Data (ERSD) of the snow cover with the purpose to evaluate the city and to plan ecological environment protection strategy. The paper deals with the method of using space images to assess the snow cover pollution of Chelyabinsk, a large Russian industrial city. The assessment of the snow cover of Chelyabinsk was carried out by comparing the heavy metals concentrations with the Landsat 8 data. The spectral indices were calculated for fourteen sites evenly distributed over the urban area of four types: courtyards, car parks, industrial zones and roads. We found a statistically significant difference between the Swirl/Green index and the site type and a correlation with the concentrations of dissolved and suspended forms of heavy metals in snow cover. Snow cover indices can be used as ecological indicators of urban environment.

This document is produced as part of a project of mapping, monitoring and prediction of urban sprawl in the city of Rabat, using algorithms of machine Learning, remote sensing and geographic information system. It therefore aims to determine and monitor the urban sprawl of the city of Rabat, using new Geo-spatial technologies, this socio-economic mechanism is theoretically based on the increase in the horizontal area of the city, and a decrease in population density. On the contrary, the city of Rabat is characterized by a negative growth rate between the years 2004-2014 at about -0.79% different from 1.2% at the national level, and defined by a higher population density of 255 inhabitants per km2, these statistics were directed to a hypothesis that indicates a horizontal confinement of the city of Rabat and reverse immigration to per-urban territories. In addition, this project is mainly aimed at the implementation of a computerized simulation model for the characterization and prediction of the urban expansion of the city of Rabat for 40 years (1990, 2000, 2010, 2020, 2030). To conclude, the city of Rabat has experienced a very slow urban sprawl, thanks to the green belt put in 1971, and the modernization strategy that has been adapted in recent years to eliminate informal housing, in addition to the development of roads and the new TGV railway line, and also to the lack of land use, of which many large villas of several hectares were built. Although this mechanism is moving very slowly, the city of Rabat has had negative consequences on the territory and the environment. So, local authorities need a creative, innovative and intelligent urban planning programme to both eliminate the effects of this mechanism, and build the pillars of the functional city (smart city).

Surface water plays a vital role in the living environment. The shrinking surface water area in urban areas is one of the main culprits causing serious environmental problems such as flooding, ecosystem imbalance, etc. In Vietnam, surface water area in the urban center is rapidly declining due to urbanization, especially in the capital - Hanoi, where the urbanization rate is highest. This study examines the mutation in surface water area in several central districts in Hanoi through the period of 1993-2020 using remote sensing images and GIS. The result shows that the surface water area in the research region decreased gradually over the years from 5881.2 hectares to 4328.7 hectares. This parameter dropped more steeply in recently established districts and those adjacencies namely Thanh Tri, Gia Lam, and Dong Anh than in central districts, Hoan Kiem and Hai Ba Trung for instance. Especially, In 2000 and 2007 the rate of reduction was highest. This finding is useful for urban planners, managers, and policymakers involved in Vietnam's sustainable urban development process.

The study describes a case study from an ecologically fragile region of Kerala, India, in which GIS and remote sensing techniques were used to identify groundwater potential zones (GWPZ). The study area has been adversely affected by pollution from various sources, and residents have become reliant on groundwater for their drinking water needs. Here, the Weighted Index Overlay Analysis method was used to identify the potential groundwater zones to assign ranking values to different classes of individual thematic maps based on their mediating and moderating influence on groundwater potentiality. Twelve thematic layers were used. The results of the GWPZ were validated by overlaying samples on the potential zones in the GIS environment. The study emphasizes the importance of GWPZ mapping for planning new abstraction well locations to meet increasing water demand and improve the awareness of groundwater availability for sustainable development.

Based on remote sensing data, it is possible to create a real-time database of agricultural sectors of the study area, in particular, types of crops, fisheries, arable land, and other sectors of agriculture. Remote sensing techniques can also be used to help determine crop yields, parasite spread, increased damage, and soil conditions using satellite imagery and aerial photography. In agricultural mapping, a classification algorithm is required that ensures the reliability and accuracy of the data extracted from the remote sensing data. Research and experiments have shown that increasing the accuracy of classification results requires not only the selection of a perfect algorithm but also a high level of knowledge and skills in the field in which the research is conducted. The mapping of agricultural sectors, in particular the classification of crops, also requires close acquaintance with the existing types of crops in the region, their dependence on natural and climatic conditions, and their development trends.