Detecting animals in African Savanna with UAVs and the crowds

Unmanned aerial vehicles (UAVs) offer new opportunities for wildlife monitoring, with several advantages over traditional field-based methods. They have readily been used to count birds, marine mammals and large herbivores in different environments, tasks which are routinely performed through manual counting in large collections of images. In this paper, we propose a semi-automatic system able to detect large mammals in semi-arid Savanna. It relies on an animal-detection system based on machine learning, trained with crowd-sourced annotations provided by volunteers who manually interpreted sub-decimeter resolution color images. The system achieves a high recall rate and a human operator can then eliminate false detections with limited effort. Our system provides good perspectives for the development of data-driven management practices in wildlife conservation. It shows that the detection of large mammals in semi-arid Savanna can be approached by processing data provided by standard RGB cameras mounted on affordable fixed wings UAVs

Development and application of operational techniques for the inventory and monitoring of resources and uses for the Texas coastal zone. Volume 1: Text

The author has identified the following significant results. Image interpretation and computer-assisted techniques were developed to analyze LANDSAT scenes in support of resource inventory and monitoring requirements for the Texas coastal region. Land cover and land use maps, at a scale of 1:125,000 for the image interpretation product and 1:24,000 for the computer-assisted product, were generated covering four Texas coastal test sites. Classification schemes which parallel national systems were developed for each procedure, including 23 classes for image interpretation technique and 13 classes for the computer-assisted technique. Results indicate that LANDSAT-derived land cover and land use maps can be successfully applied to a variety of planning and management activities on the Texas coast. Computer-derived land/water maps can be used with tide gage data to assess shoreline boundaries for management purposes

Application of remote sensing to selected problems within the state of California

There are no author-identified signficant results in this report

Third ERTS Symposium: Abstracts

Abstracts are provided for the 112 papers presented at the Earth Resources Program Symposium held at Washington, D.C., 10-14 December, 1973

Semi-automatic classification of tree species using a combination of RGB drone imagery and mask RCNN: case study of the Highveld region in Eswatini

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesTree species identification forms an integral part of biodiversity monitoring. Locating at-risk species and predicting their distribution is equally as important as tracing invasive alien plant species distributions. The high prevalence of the latter and their destructive impact on the environment is the focus for this thesis. In areas of the world where technology limitations are restrictive, an approach using low-cost, available RGB drone imagery is proposed to train advanced deep learning models to distinguish individual tree species; three dominant species (Pinus elliotti, Eucalyptus grandis and Syzygium cordatum) providing the bulk of sampling data, of which the first two are highly invasive in the region. This study explored the efficacy of utilizing Mask RCNN, an instance segmentation deep neural network, in identifying multiple classes of trees within the same image. In line with the low-cost approach, Google Colaboratory was utilized which drastically lowers the training time necessary and alleviates the need for high GPU systems. The model was trained on imagery from three study areas which were representative of three distinct landscapes: very dense forest, moderately dense forest with overlapping canopies, and open forest. The results indicate decent performance in open forest landscapes where overlapping tree crowns is infrequent with mean Average Precision of 0.71. On the contrary, in a dense forest landscape with many interlocking tree crowns, a mean Average Precision of 0.43 is highly indicative of the model’s poor performance in such environments. The trained network was also observed to have higher confidence scores of detected objects within the open forest study areas as opposed to dense forest

Lake Catchment Interaction Analysis by Using Remote Sensing and GIS Techniques – the case study of Kolleru Lake, South India

Wetlands belong to the most productive ecosystem on Earth. They provide many essential services to humans. They play an important role and possess ecosystem services, for example, in biodiversity conservation, for the hydrologic cycle, to buffer regional climate change, and for human health. Among the different types of wetlands, lakes (lacustrine wetlands) play a crucial role in maintaining global and regional water balances, natural and socio-economic resources, and habitats. Over the last decades, the lakes have gone through enormous changes derived from both natural processes and anthropogenic activities. Particularly, freshwater lakes are endangered through point and non-point pollutions, and such impacts are coming from agricultural runoff and industrial pollution, domestic waste, through municipal sewage, which may deteriorate the water quality and their ecological integrity. The Kolleru Lake wetland ecosystem in South India has been taken here as a case study, based on a comprehensive data analysis and modeling of Spatio-temporal variability of the pollutant loads, to achieve a better understanding of the man-environmental problems of the lake and its surrounding catchment. This is a necessary requirement for both better management of the agricultural, industrial, and water resources in the whole area and better lake protection and conservation. Kolleru Lake is the largest freshwater lake in India. It is a huge natural flood balancing reservoir and also a wildlife sanctuary. In 2002, the Ramsar Convention recognized the lake as a wetland of international importance. The lake is predominately fed by rivers. Among them, Budameru and Tammileru rivers are contributing to the lake influx substantially, plus supported by 68 minor irrigation (drainage) canals. The Kolleru Lake covers a total area of more than 90,100 hectares and holding approximately 1,350 cubic miles of freshwater. Additionally, Kolleru Lake provides drinking water to the inhabitants of the surrounded villages. The lake area up to 3' ft contour is consistent with water, while the 5' ft contour level of the Kolleru Lake belongs to the wildlife sanctuary. Further, it is mostly occupied by aquacultures followed by paddy cultivation, weed infests, and marshy land. There are many small scales to large scale industries growing steadily in order to support successful aquaculture. Before the 1970s, the lake area up to 5' ft contour was not occupied by any type of economic activity; however, the lake is saturated with water during the rainy season, and it remains dry during summer. Furthermore, it was completely free from contamination by aquaculture and agricultural activities before the 1970s. After the 1970s, the State Government had distributed the Kolleru Lake up to 5'ft contour area the poor people, migrant workers, and local inhabitants in the promise of whenever the government again needs the lake area, and they can take it back by paying compensation to them. Then farmers have started paddy cultivation in and around the lake. All bed villages in the lake region are frequently severely affected by massive flooding in connection with the submersion of paddy fields. Despite the fact that the state Government had encouraged the farmers to convert the paddy fields into fishponds by providing loans in order to overcome the floods. However, the maximum of lake area up to wildlife sanctuary is practiced by the aquaculture in the 1990s. Since 1970 until the current situation, the lake has been facing some severe environmental threats, such as degraded water quality, deteriorated aqua species and birds, and habitat losses, induced by human activities and accelerated by climate change. A major cause of the environmental problems was identified within the lake by the construction of fishponds resulted in pollution by using pesticides and waste food (exposed to bacterial diseases and infection) to enrich the fish growth. As a result, it causes biological magnification diseases, fertility, and respiratory problems to the animals, birds, and humans who live near to the lake. Thereby the ecosystem will become an inhospitable environment for those aqua species and birds. The fish ponds occupied approximately 42% of the lake area while aquaculture had encroached another 8.5%, together covering 50% of the lake region. If the human-induced debasement of the lake will continue, the lake will no longer cease to exist, and the wildlife species soon will disappear. Apart from the aquaculture tradition, the Kolleru Lake catchment is known for its intensive paddy cultivation. However, the massive application of pesticides and chemical fertilizers to agricultural lands across the catchment area is one reason for the eutrophication in Kolleru Lake. In addition to the several factors that influence the lake ecosystem, industrial pollution causes deteriorating water quality and makes them unfit for drinking water for the inhabitants of the villages around the Kolleru Lake. Both point and non-point sources issued threatens to the lake area becomes more sensitive by anthropogenic activities. The main focus of the present research was to analyze the problems related to the lake catchment and give recommendations to the government about the insight view of the land use cover and enlighten the public perception towards the lake degradation. However, sedimentation in a lake is a natural consequence of the inflow of respected tributaries, rivers, and streams. In addition to the natural influence, man-made activities like land use and others are also responsible for erosion in the catchment and the sediment transport and accumulation of the sediments in both the lower sections of the catchment and the lake basin itself, as discussed in the first research objective. Extensive use of land and the indiscriminate rise of embankments for the construction of fishponds as well as agricultural functions has resulted in widespread soil erosion in the catchment and sedimentation over the deltaic part of the Kolleru Lake catchment. In addition, the perennial rivers of Krishna and Godavari drift down to the lake about 68,000 tons/yr of sediments that coming from the whole catchments after passage from the river banks and river beds. The objective of this part was to analyze both the average annual soil loss rate and its change from the catchment and the sediment yields by using the RUSLE model both for the terrestrial part and the semi-aquatic deltaic part of the Kolleru Lake catchment for the years 1972 and 2012. The results indicated that the average annual soil loss was estimated with 13.6 t/ha/yr, classifying the Kolleru Lake Basin under a very high erosion rate category. Whereas, the average annual sediment yield was determined with 7.61 t/ha/yr. The resultant difference of the sediment balance is temporally interbedded within the terrestrial sites and within the river banks and river beds. However, this study has found that tributaries and streamlines of the catchment carry high sediment loads to the lake. This research has proved how intensive agricultural activities in wetland catchments interact with the pollution levels of the lake, causing a deteriorated water quality. Agricultural runoff (runoff from catchment areas dominated by agricultural use) is the main driving factor of accumulated non-point source pollution of the lake water, with side-effects on sediments and silts near the downstream areas of the Kolleru Lake catchment. It primarily caused eutrophication in the lake subsequently that led to proliferating the weeds. However, the second objective of the research was to estimate the tributaries' sub-basin loads and to highlight the diffuse critical sources against the village communities. For this purpose, the Soil and Water Assessment Tool (SWAT) was used to model the diffuse sources in the catchment. The spatial distribution of nitrate-nitrogen (NO3-N) and total phosphorus (TP) emissions were quantified. Some sub-basins contribute more pollutant load to the lake. Alternately, the first and second BMPs (Best Management Practices) level priority areas were identified. Further, suggestions for the implementation of agricultural management practices have been provided for the crucial protection of the lake ecosystem. Consequently, the Kolleru Lake wetland ecosystem is known for its both abundant water availability as well as water scarcity. The river and streams water diverted into the agricultural lands, and still, there is a dire need for groundwater too. When the monsoon rain was weak, and after rainless summer periods, the lake falls more or less dry. Therefore there is a high demand for groundwater, which is continuously increasing. An effective way to analyze groundwater recharge and groundwater availability is a remote sensing and GIS based mapping. The theoretical concepts are involved in this objective is more useful for t further research of the link between surface emission and groundwater contamination. That is why the present research has been investigated as the third objective, the potential groundwater resources in the catchment. A simple mathematical equation was derived from the catchment hydrologic characteristics. The catchment characteristics were analyzed and based on the previous literature sources, and the thematic weight was assigned to evaluate potential groundwater zones. About 13% of the catchment area falls under poor conditions, 38% of the area falls under moderate conditions, 42% of the area falls under good conditions, and about 7% of the area is under excellent condition. These results are a contribution to future groundwater management projects and artificial recharge plans of the Kolleru Lake catchment to maintain sufficient groundwater levels. Due to the still existing lack of observed data of the tributaries, i.e., runoff, sediment, water quality parameters, nutrient load, the used methods are limited and suitable just for an estimation. Sufficient calibration and validation of the results were also limited because the access to the study area and to an onside research institute was not allowed for the Ph.D. candidate, because of its status as a Ph.D. student from Germany. Field investigations on the interaction of pollutant loads with the runoff would be advantageous for a better calculation of the pollutant load and its dynamic. Because of the limited funding capacity, it is challenging to do a field survey to control every remote sensing and GIS result of this research. That is why, without a few exceptions, this study was conducted dominantly based on remote sensing data and accessible weather and soil data. From the research results emphasized that the Kolleru Lake water level and water quality are highly degraded, respectively polluted with metals, agricultural contaminants, which makes the lake water not advisable for human consumption. The erosion and sedimentation loads are also high, and the priority management practices should be targeted already in the middle catchment region. These results give a general understanding of the pollutant levels in the lake, which should be useful for government management plans.

Program on State Agency Remote Sensing Data Management (SARSDM)

A planning study for developing a Missouri natural resources information system (NRIS) that combines satellite-derived data and other information to assist in carrying out key state tasks was conducted. Four focal applications -- dam safety, ground water supply monitoring, municipal water supply monitoring, and Missouri River basin modeling were identified. Major contributions of the study are: (1) a systematic choice and analysis of a high priority application (water resources) for a Missouri, LANDSAT-based information system; (2) a system design and implementation plan, based on Missouri, but useful for many other states; (3) an analysis of system costs, component and personnel requirements, and scheduling; and (4) an assessment of deterrents to successful technological innovation of this type in state government, and a system management plan, based on this assessment, for overcoming these obstacles in Missouri

Airborne and Terrestrial Laser Scanning Data for the Assessment of Standing and Lying Deadwood: Current Situation and New Perspectives

LiDAR technology is finding uses in the forest sector, not only for surveys in producing forests but also as a tool to gain a deeper understanding of the importance of the three-dimensional component of forest environments. Developments of platforms and sensors in the last decades have highlighted the capacity of this technology to catch relevant details, even at finer scales. This drives its usage towards more ecological topics and applications for forest management. In recent years, nature protection policies have been focusing on deadwood as a key element for the health of forest ecosystems and wide-scale assessments are necessary for the planning process on a landscape scale. Initial studies showed promising results in the identification of bigger deadwood components (e.g., snags, logs, stumps), employing data not specifically collected for the purpose. Nevertheless, many efforts should still be made to transfer the available methodologies to an operational level. Newly available platforms (e.g., Mobile Laser Scanner) and sensors (e.g., Multispectral Laser Scanner) might provide new opportunities for this field of study in the near future

Application of remote sensing to state and local government (ARSIG)

Progress of ARSIG projects is reported and the impact of the projects upon policy decision within Arizona is discussed

Internet of things

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth