New “Snakebot” Could Map Cambodian Minefields

By navigating under dense vegetation, an innovative robot could significantly reduce the monetary, environmental, and human cost of demining Cambodia.

Spatio-temporal pattern of urban forest vegetation density, Medan Baru city, Indonesia

The growth of urban areas and the population generally requires the guarantee of a healthy and comfortable environment. The expansion of physical developments and urban areas, year after year, can no longer support human existence. In Indonesia, the city should have at least 10% of its surface area committed to private urban forest and 20% for public urban forest. Jakarta is Indonesia’s largest city, and has only 9.98% urban forest coverage. Medan Baru city is facing the same issue, as it continues to grow year after year. The population requires a comfortable environment, which includes safe drinking water and clean, fresh air. As a result, vegetation is an important component of Medan Baru sub-district that offers numerous benefits. It is necessary to conduct research on the analysis of vegetation density in the Medan Baru, using vegetation indices such as Normalized Difference Vegetation Index (NDVI). The research aimed to analyze vegetation density change and mapping the vegetation density of Medan Baru city. The research found the largest area was relatively dense vegetation, about 262.00 hectares (47.87%). The research also found a decrease in urban forest quality, indicated by an increase in the sparse density class of 41.90 hectares and a decrease in the relative-dense vegetation class with 51.65 hectares. This reduction of vegetation density will reduce the urban forest quality by influencing urban forest capability in absorbing carbon dioxide and alleviating the oxygen productivity volume. Areas with lower stand density must be considered in future urban development planning. Moreover, decrease in vegetation density and urban forest area should be a primary consideration in Medan urban forest management.

Assessment of Oil Spillage Impact on Vegetation in South-Western Niger Delta, Nigeria

The present study assesses the impact of oil spillage in the Southwestern Niger Delta of Nigeria over the past fifty (50) years. It further sought to find out the driving forces and implications of oil spillage on vegetation, livelihoods and other key parameters. The study employed geospatial techniques and a secondary source of data to achieve the objectives set out in this study. The Global Moran I statistical tool was used to determine the spatial autocorrelation based on feature locations and attribute values. We observed built-up areas, bare land, and less dense vegetation had an overall increment of 1975.98 km2, 1370 km2 and 23805 km2, respectively. Dense vegetation had declension of 22058.33 km2 over the past five decades. Findings depict a declining trend in Normalized Difference Vegetation Index, attributed to oil spillage as the key contributory factor. Occasioned by anthropogenic activities, the driving forces were traced to attacks on oil pipelines during conflicts and illegal means of creating leakages to siphon crude oil for sale. To achieve sustainability in oil spill management in the Delta, the study recommends further research to ascertain the cost of losses incurred apply geospatial techniques to monitor and predict environmental changes that inform decisions of key actors.

Micro-Topography Mapping through Terrestrial LiDAR in Densely Vegetated Coastal Environments

Terrestrial Light Detection And Ranging (LiDAR), also referred to as terrestrial laser scanning (TLS), has gained increasing popularity in terms of providing highly detailed micro-topography with millimetric measurement precision and accuracy. However, accurately depicting terrain under dense vegetation remains a challenge due to the blocking of signal and the lack of nearby ground. Without dependence on historical data, this research proposes a novel and rapid solution to map densely vegetated coastal environments by integrating terrestrial LiDAR with GPS surveys. To verify and improve the application of terrestrial LiDAR in coastal dense-vegetation areas, we set up eleven scans of terrestrial LiDAR in October 2015 along a sand berm with vegetation planted in Plaquemines Parish of Louisiana. At the same time, 2634 GPS points were collected for the accuracy assessment of terrain mapping and terrain correction. Object-oriented classification was applied to classify the whole berm into tall vegetation, low vegetation and bare ground, with an overall accuracy of 92.7% and a kappa value of 0.89. Based on the classification results, terrain correction was conducted for the tall-vegetation and low-vegetation areas, respectively. An adaptive correction factor was applied to the tall-vegetation area, and the 95th percentile error was calculated as the correction factor from the surface model instead of the terrain model for the low-vegetation area. The terrain correction method successfully reduced the mean error from 0.407 m to −0.068 m (RMSE errors from 0.425 m to 0.146 m) in low vegetation and from 0.993 m to −0.098 m (RMSE from 1.070 m to 0.144 m) in tall vegetation.

Assessment of Land Use/Land Cover Change and Morphometric Parameters in the Keta Lagoon Complex Ramsar Site, Ghana

The rapid urbanization, industrialization, agricultural activities, and increasing trend of some natural hazards, such as climate change, particularly in coastal areas, necessitate the continual assessment of critical but fragile ecosystems like that of the Keta Lagoon Complex Ramsar Site (KLCRS). This productive ecosystem in Ghana faces serious threats from intensive exploitation, physical modification, changes in water regime, and water pollution. The current study employed geospatial and intensity analysis to assess the pattern of land use/land cover (LULC) change for almost the past three decades and morphometric parameters of the KLCRS landscape. Landsat Satellite images for 1991, 2007, and 2020 were acquired to uncover the pattern of LULC change, while morphometric changes were assessed using global Advance Space Thermal Emission and Radiometer (ASTER) digital elevation model (DEM) data and the spatial analyst tools in GIS software. The result established that the acceleration of land transformation was intensive between 2007 and 2020, which could be linked to population growth and increased socio-economic activities. There was a net gross gain of built-up that originated largely from the conversion of marsh, dense vegetation, and cultivated land. Prior to this period, cultivated land recorded net gain (125.51 km2) between 1991 and 2007, whereas dense vegetation and marshland showed a net loss of 151.37 km2 and 2.44 km2, respectively. The gain of cultivated land largely targeted marshland in both time intervals. The construction of saltpans contributed largely to the small increase in water extent. The morphometric analysis revealed the groundwater potential of the KLCRS. The low-lying nature of the landscape makes the area susceptible to coastal flooding. The trend of the observed changes could invariably affect the ecological integrity of the landscape, hence suggesting the need for immediate preparation and implementation of marine and coastal spatial plans by relevant stakeholders.

Distribution of ground beetles of the genus Bembidion (Coleoptera, Carabidae) in the agricultural landscape in Northwestern Russia

We have observed seven species of predator beetles of the genus Bembidion in the agricultural landscape of the Leningrad Region (Northwestern Russia) between the years 2008 and 2018. These species reach their highest abundance in sun-exposed areas, especially mesophilic B. quadrimaculatum Linnaeus, 1761, B. properans (Stephens, 1828), B. lampros (Herbst, 1784), and B. femoratum Sturm, 1825. A few mesohygrophilic B. guttula (Fabricius, 1792) and B. gilvipes (Sturm, 1825) live primarily in areas of dense vegetation. Finally, the hygrophilic B. bruxellense (Wesmael, 1835) was only observed on the most humid soils. Assemblages of Bembidion ground beetles were separated in the fields, field boundaries, and adjacent habitats.

Use of Multiplatform SAR Imagery in Mining Deformation Monitoring with Dense Vegetation Coverage: A Case Study in the Fengfeng Mining Area, China

Ground deformation related to mining activities may occur immediately or many years later, leading to a series of mine geological disasters, such as ground fissures, collapses, and even mining earthquakes. Deformation monitoring has been carried out with techniques, such as multitemporal interferometric synthetic aperture radar (MTInSAR). Over the past decade, MTInSAR has been widely used in monitoring mining deformation, and it is still difficult to retrieve mining deformation over dense vegetation areas. In this study, we use multiple-platform SAR images to retrieve mining deformation over dense vegetation areas. The high-quality interferograms are selected by the coherence map, and the mining deformation is retrieved by the MSBAS-InSAR technique. SAR images from TerraSAR-X, Sentinel-1A, Radarsat-2, and PALSAR-2 over the Fengfeng mining area, Heibei, China, are used to retrieve the deformation of mining activities covered with dense vegetation. The results show that the subsidence in the Fengfeng mining area reaches up to 90 cm over the period from July 2015 to April 2016. The root-mean-square error (RMSE) between the results from InSAR and leveling is 83.5 mm/yr at two mining sites, i.e., Wannian and Jiulong Mines.

Utilisation of honey trap method to ensnare a dispersing sub-adult Bengal Tiger Panthera tigris tigris L. in a human dominated landscape

The need to conserve the tiger, an endangered species and avoid interactions with humans is among the main objectives of forest management of tiger reserves in India. The objective of the study is show that male tigers can be trapped by pheromones in urine and feces of tigress for subsequent translocation. A sub-adult male tiger strayed out of Sariska Tiger Reserve into the human dominated areas to look for territory. Attempts to tranquilize the tiger failed due to dense vegetation. Then the urine and feces of a captive tigress was used to trail the tiger, capture him, and release him into his natal area thereby avoiding incidents with humans. Tracking data indicated that the tiger had settled in the northern area part of Sariska and subsequently sired seven cubs with two tigresses.

Vegetation dynamics and climate variability in the Portoviejo river basin

Climate change is currently a global problem, as it significantly affects the dynamics of vegetation. The objective of this research is to analyze the influence of climate variability on the dynamics of vegetation in the Portoviejo river basin. The methodology consisted in the calculation of the NDVI with the use of multispectral images from the Landsat satellite and the analysis of the fluviometric records. The images were downloaded from the Earth Explorer geospatial platform with a spatial resolution of 30 m, images from the period 1998-2019 were selected to analyze their temporal trend. The historical fluviometric records of the Portoviejo station, of the National Institute of Hydrology and Meteorology were used. The results showed that the vegetation experienced a discontinuous greening trend, influenced by the variability of rainfall. A homogeneous trend was found in the spatial distribution of the NDVI, with dense and very dense vegetation cover in the upper part of the basin, as well as little or no cover in the lower part. The area with the greatest coverage corresponded to dense vegetation with a percentage higher than 30%.