Use Of High Resolution Satellite Imagery Research Articles

The Use of High-Resolution Satellite Imagery to Determine the Status of a Large-Scale Outbreak of Southern Pine Beetle

Timely detection of insect infestation (or other disturbance) in a forest is vital for an adequate response plan to be developed. To determine the status of an active infestation of southern pine beetle (Dendroctonus frontalis) in the Bienville National Forest, WorldView-2 imagery was utilized. Principal components analysis (PCA) was performed and correlated with spectral reflectance bands to assess differences between the classification of spectral reflectance bands and principal components. Unsupervised classification of combinations of principal components (e.g., combining principal components 1 and 2, principal component 1 alone, and principal component 2 alone) was performed and compared with combinations of principal component correlations with spectral reflectance bands (e.g., all bands, bands 1–5, bands 6–8, and bands 2, 4, and 5). Combining principal components 1 and 2 was more accurate than other methods, closely followed by spectral bands 1–5. Employing PCA will aid resource managers in quickly detecting areas of active insect infestation and allow them to deploy adequate response measures to prevent or mitigate continued outbreaks.

LANDSCAPE IMPACT ASSESSMENT OF SDG2 DEVELOPMENT PROJECTS USING REMOTE SENSING AND UNSUPERVISED CONTROL SITE SELECTION

Abstract. As part of its objective to achieve Zero Hunger under SDG2 the United Nations World Food Programme, in partnership with Governments, NGOs and other UN agencies, supports food insecure communities to increase natural resource availability and improve their management. This is done mostly through the building and rehabilitation of soil and water conservation assets (e.g., small dams, weirs, landscape restoration) and structures that increase productivity (e.g., vegetable gardens, irrigation canals). To adequately monitor these activities around the globe simultaneously, remote sensing was found to be an adequate tool. This study introduces the use of high-resolution satellite imagery, and more specifically NDVI derived from the Landsat series to verify and quantify the impact of such development projects. In total 121 projects in 10 countries and six different climate zones were analyzed using a pre- and post-implementation comparison and a Before-After Control Impact (BACI) study considering randomly selected control sites. Both approaches were found to show robust results throughout the different countries, project types and climate zones. 67% of all projects showed significant improvements in vegetation conditions during the wet seasons only three years after the implementation. Using the proposed workflow based on Python scripting and cloud computing of satellite data, fast and robust analyses can be achieved, while assuring constant data quality.

Multicriteria Analysis in Apiculture: A Sustainable Tool for Rural Development in Communities and Conservation Areas of Northwest Peru

Apiculture plays a vital role in maintaining a genetically diverse ecosystem and is an economic activity that contributes to the development of rural communities, thereby enhancing the livelihoods of beekeepers. However, despite the presence of over forty thousand beekeepers in Peru, there is currently no cartographic information available on optimal areas for the development of apiculture. Our study focused on assessing the suitability of land for apiculture development in rural and indigenous communities within the Amazonas Department in northwest Peru. We integrated biophysical and socioeconomic criteria using the Multiple Criteria Evaluation (MCE) technique, in conjunction with state-of-the-art geoinformation and earth observation techniques, to model and validate land suitability for supporting apiculture. It was identified that suitability is influenced by biophysical criteria (65%) and socioeconomic criteria (35%), resulting in highly suitable areas covering 315.6 km2 within the territory of peasant communities, 128.4 km2 within native communities, and an additional 41.4 km2 within conserved areas. Furthermore, to validate our results, we combined the use of high-resolution satellite imagery and visits to artisanal producers. This research provides valuable insights for spatiotemporal land use planning, emphasizing apicultural activity as a driver of rural development and biodiversity conservation. Consequently, this study contributes as a management tool to promote apicultural activities as support for rural development and in local-level decision making.

Forecasting of Gold-Silver Mineralization within the Pepenveem Ore Zone of the Chukchi Peninsula Based on Space Surveys of Resource, Canopus and ASTER

When deciphering the materials of space sensing of the eastern part of the Chukchi Peninsula on a scale of 1 : 50 000, structural elements of tectonic-volcanogenic genesis were revealed, represented by linear, arc, annular, zonal-concentric structural elements of various ranks. Ring structures with a diameter of up to 2 km and their dissecting disjunctiva mainly of the north-eastern and submeridional strike control the localization of gold mineralization of the Pepenveem ore-placer zone. On the basis of computer processing of the ASTER infrared satellite image in the Pepenveem zone, the areas of development of hydrothermally altered rocks (berezites, secondary quartzites, sericite-hydrosluidic-quartz metasomatites) genetically associated with mineralization were identified. The use of high-resolution satellite imagery in conjunction with geophysical data made it possible, on a scale of 1 : 10 000, to identify gold-prospective areas associated with volcanic dome structures, which are characterized by an increased density of lineaments and are associated with the formation of subvolcanic rhyolites.

Assessment of high spatial resolution satellite imagery for monitoring riparian vegetation: riverine management in the smallholding

Riverine habitats are essential ecotones that bridge aquatic and terrestrial ecosystems, providing multiple ecosystem services. This study analyses the potential use of high-resolution satellite imagery, provided by the WorldView-2 satellite, in order to assess its viability for monitoring riparian ecosystems. It is performed by calculating the riparian strip quality index (RSQI) and calibrating it with the riparian quality index (QBR). The methodology was implemented in the Umia River, which is characterised by elevated anthropogenic pressures (located in the northwest of Spain). The results obtained by the method have a 92% of veracity and a kappa coefficient of 0.88. The average quality value obtained for the RSQI index was 71.57, while the average value for the QBR was 55.88. This difference could be attributed to the fact that the former does not differ between autochthonous and non-autochthonous vegetation. The areas with more accurate mapping corresponded to stretches of vegetation with optimal cover (80–50%), with good connectivity with the adjacent forest ecosystem and few or no presence of invasive plants. The worst-scoring sites had the next characteristics: low connectivity (< 10%), low forest cover (< 10%) and a higher presence of invasive plants. The degradation of vegetation could be explained by the presence of agriculture and deficient land use rationing caused by the type of ownership of the study area. The application of this index through satellite images will facilitate the environmental governance of multiple ecosystems and in special riparian ecosystems, obtaining a quick and objective methodology, easily replicable in other basins.Graphical

Use of High-Resolution Satellite Imagery in Prospecting for Coastal Placers and Deposits of Hydrocarbons in the Northern Seas of Russia

Use of High-Resolution Satellite Imagery in Prospecting for Coastal Placers and Deposits of Hydrocarbons in the Northern Seas of Russia

A multi-temporal landslide inventory and hazard zonation using relative effect method along the Mughal road Shopian, India

Landslide inventory and thematic data are of utmost importance in the domain of landslide hazard mapping. The union territory of Jammu and Kashmir, India surrounded by the Himalayan and the Pir-Panjal mountain range is prone to landslides and has already caused havoc at many places. The present study aims to provide the landslide inventory of the Mughal Road, Shopian, which lies in the Pir Panjal range of Kashmir valley. Multidate satellite data of the years 2008 to 2020 are utilized to create an inventory of landslides in this area.The use of high-resolution satellite imagery made it possible to delineate the shallow as well as the deep landslides along the roadside where they occur frequently. To understand the landslide causes, a statistical technique, relative effect method has been implemented in this study. This method helped in mapping the hazard zone areas. The relative effect of each causative factor on landslides is determined by calculating the ratio of coverage and slide which were analyzed in GIS environment. The resulting landslide hazard zone map has been classified as very low, low, moderate, high and very high zones. Out of the total area, 12.62% is critical to landslides, 21.45% is highly prone and 24.84% is moderately prone while 21.94% is low and 19.13% is very low prone to landslides. The outcome of this susceptibility modeling will be beneficial for handling and monitoring the forthcoming landslides as well as the fortification of the general public and environmental hazards of the study area. It will also help the planners in the development around the study area.

Distribution and Condition of Intertidal Eastern Oyster (Crassostrea virginica) Reefs in Apalachicola Bay Florida Based on High-Resolution Satellite Imagery

The Eastern Oyster Crassostrea virginica is an important component of the ecology of Apalachicola Bay, Florida, and the economy of the region. Although oyster reefs in the Bay occur in both tidal zones, subtidal reefs have received the most attention because they support most of the oyster fishery. The present study provides new information on the distribution, condition, and ecology of the intertidal reefs, and assessed the general utility of high-resolution satellite imagery for routine monitoring of the extent and condition of intertidal oysters. Using online, freely available color imagery and manual interpretation, a total of 782 individual reefs ranging in size from ∼3 m2 to 3.9 ha (= 9.7 acres) and covering a total of 94 ha (233 ac) of bottom area were mapped. Field inspection and sampling of 100 individual intertidal reefs on November 12–16, 2016, confirmed wide differences in the number and areal coverage of reefs in the three major geographic regions in the Bay: 433 reefs covering a total of 56 ha (139 acres) in the western area (St. Vincent Sound); 113 reefs covering 8 ha (19 acres) in the central area; and 236 reefs covering 30 ha (75 acres) in the eastern area (St. George Sound). Most reefs in the western portion of the bay consisted of recently dead (“box”) oysters in all size classes, suggesting a recent massive mortality event. Mean densities (all size classes combined) of live oysters in the central and eastern areas were 42.9/m2 (±7.39; 1 SE) and 99.3/m2 (±13.22; 1 SE), respectively, with an overall mean shell height of 23.6 mm. Size-frequency histograms indicated only two year classes of live oysters, and the largest oyster collected was 84 mm. Although detailed quantitative comparisons with subtidal reefs were not possible, data from the present study suggest that intertidal reefs cover much less bottom area of the bay, but may contain much higher live oyster densities. The present study also demonstrated the use of high-resolution satellite imagery for mapping reefs as small as a few square meters in surface area, and the potential for estimating relative reef condition measured by live oyster density.

라이다 칩을 이용한 고해상도 위성영상의 자동좌표등록

고해상도 위성영상을 성공적으로 활용하기 위해서는 지상기준점 등을 활용한 좌표등록 및 보정 과정이 필수적이다. 작업자의 수작업을 통한 기준점 획득의 경우 작업 시간이 오래 걸리므로, 자동화된 좌표 등록 방법에 대한 요구가 증대하고 있다. 보정하고자 하는 위성 영상을 정확한 좌표를 가진 참조 데이터에 영상 매칭을 수행하는 기법이 많이 소개 되었는데, 참조 데이터 중 라이다 데이터의 경우 공간 해상도 및 정확도가 높고 무엇보다 3차원 데이터이기 때문에 기복 변위 등을 내포하고 있지 않는 등의 장점을 보인다. 최근 라이다 데이터와 고해상도 위성영상간의 매칭을 위한 기법이 연구, 발표되었으나, 라이다 데이터의 특성상 대용량이기 때문에 처리에 많은 시간이 소요되는 등의 단점이 있었다. 따라서 본 논문에서는 일부의 공간만을 라이다 칩으로 추출 및 저장하여 위성영상의 좌표 등록에 활용하는 연구를 수행하였다. 이를 위해, 전체 라이다 포인트 데이터를 반사강도 정사영상 및 수치표고모델의 두 가지 형태로 변환하고 에지 추출을 통해 의미 있는 양의 에지 정보만을 포함하는 지역을 영상형태의 라이다 칩으로 추출, 저장하였으며, 용량이 현저히 줄어든 것을 확인할 수 있었다. 마지막으로 라이다 칩을 아리랑2호 및 아리랑3호 영상의 자동 좌표등록에 활용 해본 결과 평균 한 픽셀가량의 정확도 또한 확보할 수 있었다. The accurate geo-referencing processes that apply ground control points is prerequisite for effective end use of HRSI (High-resolution satellite imagery). Since the conventional control point acquisition by human operator takes long time, demands for the automated matching to existing reference data has been increasing its popularity. Among many options of reference data, the airborne LiDAR (Light Detection And Ranging) data shows high potential due to its high spatial resolution and vertical accuracy. Additionally, it is in the form of 3-dimensional point cloud free from the relief displacement. Recently, a new matching method between LiDAR data and HRSI was proposed that is based on the image projection of whole LiDAR data into HRSI domain, however, importing and processing the large amount of LiDAR data considered as time-consuming. Therefore, we wmotivated to ere propose a local LiDAR chip generation for the HRSI geo-referencing. In the procedure, a LiDAR point cloud was rasterized into an ortho image with the digital elevation model. After then, we selected local areas, which of containing meaningful amount of edge information to create LiDAR chips of small data size. We tested the LiDAR chips for fully-automated geo-referencing with Kompsat-2 and Kompsat-3 data. Finally, the experimental results showed one-pixel level of mean accuracy.

La realizzazione della carta delle formazioni naturali e semi-naturali e della carta forestale su basi tipologiche della regione Lazio

Abstract: The paper presents the main methodological aspects and the most important results achieved in the implementation of the “Map of natural and semi-natural environments” and of the “Forest types map” in Lazio region at a scale of 1:10.000. The project was carried out for the Agenzia dei Parchi and for the Area Foreste of Regione Lazio through a collaboration between e-GEOS , the University of Rome La Sapienza, the University of Tuscia and Forestlab Centre , a spin- off of the University of Molise . The project is based on the integrated use of high-resolution satellite imagery and ADS40 false-color infrared digital orthophotos and led to the creation of two maps geometrically and thematically consistent with each other. The “Map of natural and semi-natural environments” is integrated with the pre-existing land use map of the Lazio region deepening the thematic detail up to the 6th Corine level. The “Forest types map” is based on a typological system organized in 17 categories and 36 forest types .

Use of high-resolution satellite imagery for investigating acid mine drainage from artisanal coal mining in North-Eastern India

Acid mine drainage (AMD) is one of the major environmental problems in coalmining districts. The present study explores the potential of high-resolution satellite (HRS) imagery, combined with field-based geochemical sampling, for investigating the AMD-related issues arising from artisanal coal mining activity in a part of North-Eastern India. The HRS imagery available from Indian remote sensing satellites (CARTOSAT-1 and RESOURCESAT-1) and QuickBird are used for this purpose. The study demonstrates that (1) the artisanal ‘rat-hole' type coal mines prevalent in the study area can be mapped to a fair extent through merged CARTOSAT-1 PAN and RESOURCESAT-1 LISS-IV imagery; (2) coal mining-induced enhanced dissolution of pyrites appears to be the main mechanism for the occurrence of AMD exacerbating the problem of acid rock drainage (ARD); and (3) HRS imagery can be used to detect iron precipitates on streambeds indicating the presence of AMD.

Use of high-resolution satellite imagery in an integrated model to predict the distribution of shade coffee tree hybrid zones

In New Caledonia (21°S, 165°E), shade-grown coffee plantations were abandoned for economic reasons in the middle of the 20th century. Coffee species ( Coffea arabica, C. canephora and C. liberica) were introduced from Africa in the late 19th century, they survived in the wild and spontaneously cross-hybridized. Coffee species were originally planted in native forest in association with leguminous trees (mostly introduced species) to improve their growth. Thus the canopy cover over rustic shade coffee plantations is heterogeneous with a majority of large crowns, attributed to leguminous trees. The aim of this study was to identify suitable areas for coffee inter-specific hybridization in New Caledonia using field based environmental parameters and remotely sensed predictors. Due to the complex structure of tropical vegetation, remote sensing imagery needs to be spatially accurate and to have the appropriate bands for monitoring vegetation cover. Quickbird panchromatic (black and white) imagery at 0.6 to 0.7 m spatial resolutions and multispectral imagery at 2.4 m spatial resolution were pansharpened and used for this study. The two most suitable remotely sensed indicators, canopy heterogeneity and tree crown size, were acquired by the sequential use of tree crown detection (neural network), image processing (such as textural analysis) and classification. All models were supervised and trained on learning data determined by human expertise. The final model has two remotely sensed indicators and three physical parameters based on the Digital Elevation Model: elevation, slope and water flow accumulation. Using these five predictive variables as inputs, two modelling methods, a decision tree and a neural network, were implemented. The decision tree, which showed 96.9% accuracy on the test set, revealed the involvement of ecological parameters in the hybridization of Coffea species. We showed that hybrid zones could be characterized by combinations of modalities, underlining the complexity of the environment concerned. For instance, forest heterogeneity and large crown size, steep slopes (> 53.5%) and elevation between 194 and 429 m asl, are favourable factors for Coffea inter-specific hybridization. The application of the neural network on the whole area gave a predictive map that distinguished the most suitable areas by means of a nonlinear continuous indicator. The map provides a confidence level for each area. The most favourable areas were geographically localized, providing a clue for the detection and conservation of favourable areas for Coffea species neo-diversity.

Using high-resolution satellite imagery and double sampling as a cost-effective means of collecting forest inventory data – the case of Hans Kanyinga Community Forest, Namibia

The present study deals with the use of high-resolution satellite imagery in forest inventory of the open savanna woodlands of southern Africa. The study was carried out in Hans Kanyinga Community Forest, north-eastern Namibia. A two-phase (double) sampling design was used to estimate the variables of interest, namely stand volume, stand density and diameter distribution. QuickBird satellite images were used to extract auxiliary variables (image data), such as photogrammetric crown diameter and number of stems, using visual interpretation and measuring tools offered by Erdas 8.7 geographic imaging software. Field inventory data (terrestric data) collected in 2002 were used to obtain the terrestric data. Stepwise regression and correlation analysis between satellite imagery and field data was carried out and the results were moderate. The stand volume model explained 56%, the stand density model 81% and the diameter distribution model 43% of the variation. Cost-efficiency assessment of double sampling with regression estimators showed a considerable reduction in inventory costs by up to 24% compared to a traditional forest inventory method in Hans Kanyinga Community Forest. Double sampling was found to be cost-efficient when the proportion of variability of the models was higher than 27%. The inventory concept showed potential in providing information required both at the higher and lower levels of forest management. Follow up research is required.

Remote Sensing Observations of Landslides and Ground Deformation from the 2004 Niigata Ken Chuetsu Earthquake

In recent years, major developments in remote sensing have made it possible to use these technologies to document the effects of earthquakes. Specifically, high-resolution satellite imagery and three-dimensional laser scanning (LIDAR) can provide important observations of earthquake damage that supplement traditional observations from field reconnaissance. The 2004 Niigata Ken Chuetsu earthquake provided an opportunity to use remote sensing to document the distribution of landslides in the epicentral region through the use of high-resolution satellite imagery and to document the detailed three-dimensional geometries of several failures using LIDAR. The satellite imagery was acquired the day after the earthquake, but at very large acquisition angles that resulted in image distortion. Nonetheless, the satellite imagery accurately identified the landslide distribution in the epicentral region, although the total area of landslides was underestimated by about 25% as compared with traditional aerial reconnaissance because of the large acquisition angle for the satellite imagery. Terrestrial LIDAR was used to collect three-dimensional data at several failure sites, including two large rock slides and a railroad tunnel portal affected by ground deformation. The LIDAR data allowed for precise measurement of failure deformations and geometries, and provided digital terrain models that could be archived and used in future analyses. In the future, satellite imagery and LIDAR, as well as other remote sensing technologies, will play an increasing role in documenting and understanding the effects of earthquakes.

A simple visualization method for distinguishing subglacial-bed and side-wall returns in radio-echo records from outlet and valley glaciers

AbstractRadar returns from valley side-walls may complicate the identification of the glacier bed when examining airborne radio-echo sounding (RES) records. We describe simple visualization techniques for aiding analysis of RES data with the aim of resolving these ambiguities, making use of high-resolution satellite imagery. An application of the technique is illustrated using RES data obtained from part of Stygge Glacier, Ellesmere Island, Nunavut, Canada.

Brazilian Amazonia: Industrial development and environmental monitoring

After a critical analysis of the strategies for conservation of the environment in Latin America and of large-scale development projects (agriculture and livestock raising, mining and electrical power plants) in the Amazon region of Brazil, this paper deals with the use of high-resolution satellite imagery for environmental monitoring. Two areas were considered in the study, Tucurui and Altamira. Spot/XS and Landsat/TM multispectral images were used, together with color aerial photographs of these areas. A computer-assisted visual interpretation procedure was employed to analyze images, and linear multispectral transformation was applied in selected subscenes in order to improve information extraction. The results indicate that high-resolution satellite imagery is generally compatible with the scale of the environmental problems in Amazonia and is a very efficient source of detailed information at a local scale on many aspects of the environment, in particular for monitoring changes over time in selected areas. Therefore, commercial satellite imagery, processed by specialized software, can accommodate a variety of analysis needs for decision makers and can also be an effective means of verification of international agreements on conservation of the environment in Amazonia.