Camaroptera: A Long-range Image Sensor with Local Inference for Remote Sensing Applications

Batteryless image sensors present an opportunity for pervasive wide-spread remote sensor deployments that require little maintenance and have low cost. However, the reliance of these devices on energy harvesting presents tight constraints in the quantity of energy that can be stored and used, as well as limited, energydependent availability. In this work, we develop Camaroptera, the first batteryless, energy-harvesting image sensing platform to support active, long-range communication. Camaroptera reduces the high latency and energy cost of communication by using nearsensor processing pipelines to identify interesting images and transmit them to a far-away base station, while discarding uninteresting images. Camaroptera also dynamically adapts its processing pipeline to maximize system availability and responsiveness to interesting events in different harvesting conditions. We fully prototype the Camaroptera hardware platform in a compact, 2cm x 3cm x 5cm volume, composed of three adjoined circuit boards. We evaluate Camaroptera demonstrating the viability of a batteryless remote sensing platform in a small package. We show that compared to a system that transmits all image data, Camaropteras processing pipelines and adaptive processing scheme captures and sends 2-5X more images of interest to an application.

This report presents the activities and outcomes to date of the global initiative on remote sensing for water resources management phase two. The Initiative was conceived to help mainstream the use of beneficial remote sensing applications in operational projects of the Bank, as well as to facilitate the adoption of remote sensing applications in World Bank client countries. By bridging the gap between the supply of remote sensing data and the needs from the Bank’s operational projects, Earth Observations can better inform client country agencies by improving monitoring and predictive capabilities and supporting better water-related operations. This report is addressed to technical staff in national water agencies, project leads from development and financing institutions, and water practitioners in general. The goal of the report is to present insights from a range of innovative remote sensing applications developed within the Remote Sensing Initiative, to help address specific water resources management challenges. The results presented here include constraints identified in the adoption of remote sensing, the approaches adopted to make applications functional in different contexts, the project applications themselves, insights on their sustainability, and ways forward. These applications can be replicated, up-scaled, and adapted in many other contexts to address similar challenges. We hope the information contained in this report will help country agencies and project teams in integrating the use of remote sensing in their water resources management practices, as well as in project design, implementation, monitoring and evaluation.

This paper aims to measure and characterise urban sprawl development in Kuala Lumpur city using leapfrog geospatial indices. The researcher utilised remote sensing satellite data such as Landsat and Spot images for two different times. The remote sensing application was subsequently integrated with GIS database to detect changes and analyse the pattern of growth for urban areas in Kuala Lumpur. From the finding of land use change detection, the leapfrog sprawl index was calculated by using geospatial indices formula. The results proved that Kuala Lumpur is the most highly developed city in Malaysia with new development is leapfrogging towards the periphery of the city and infill development pattern seemingly increase vastly filling up the leapt areas cause by leapfrog sprawl. Improper planning will create this type of urban sprawl that is predicted to expand beyond the border towards other states locating adjacent to Kuala Lumpur which is now called Greater Kuala Lumpur. The current scenario has become an absolute threat towards Malaysia planning goal to achieve sustainable urban planning development.

Change Detection is one of the most popular topics in the field of Multi-temporal Remote Sensing (RS) applications. In this paper, a novel approach was introduced for the change detection of the urban area. This approach adopts the Dempster-Shafer(D-S) algorithm for feature fusion of the multi-temporal RS images. It, in the first place,,constructs difference images of pixel and context respectively. These two difference images present the features of changes in different scales. The pixel difference image is obtained by fusing the results of the subtraction operation and the division operation, while the context difference image is obtained by the image context. Secondly, by using the difference images, two evidences could be constructed. These evidences are not certain, but they can give more reliable combination result if considering the average support of the evidence to different subsets in the assignment framework. And based on these evidences, the criterion function could be established by the D-S theory. At last, an improved D-S algorithm is applied to fuse the two different features for detecting the change information of the RS images. An experiment, using the SPOT and TM images of Wuhan urban area, has compared the accuracy of edge detection by using the new fusion algorithm and the existent ones. The result shows that the method of improved D-S is solid and efficacious, which has preferable value in remote sensing applications.

Uncooled FIR-bolometer image sensors are established in many applications like building inspections, cold bridge analyses and predictive maintenance. New fields of application are discovered, like automotive night vision, advanced presence detection, gesture recognition etc. but these require a lower cost, small form factor packaging of the μ-bolometer sensors. Wafer level packaging (WLP) is seen as the enabling housing technology compared to ceramic packages for high volume production. Monolithic integrated μ-bolometer image sensors require a vacuum packaging with vacuum level in the range of mbar or less. The growing demand for reliability especially in automotive applications has also a large impact on the package construction. The overall challenge for high sensitive μbolometer sensors is to create a small package that allows for a maximum IR transmission at minimum cost. The work describes a wafer level technology on 200mm wafers with a hermetic sealing for large evacuated cavity dimensions with the process integration of different antireflective surface treatments. Cavities are created with 90μm thick poly-silicon frames in an additive deposition technology. The IR window region in the caps features different customer specific anti-reflective concepts. One approach is a double side moth eye pattern that can be designed to suppress short wavelength by destructive interference. It is possible to use different geometries of moth eyes inand outside of the cavities to create a low cost filter. To reduce sunlight transmission a combination of moth eyes inside the cavities and a multi-layer filter coating outside can be achieved. The moth eyes patterns are realized in silicon wafers by reactive ion etching. To generate a high vacuum up to mbar a getter with large exposed surface is required. A 3D structured getter solution is presented that generates a maximum getter surface in a small area in the cap. First wafers with a good optical resolution and thermoelectric sensitivity have been achieved by a eutectic wafer bonding process Vacuum WLP construction The hermetic capping of monolithic integrated μbolometer image sensors enables a small package form factor but increases the required development efforts as a seal frame on active CMOS circuits is formed. Beside the fact that special care is needed to prevent CMOS damages due to mechanical overstress, the exposed CMOS area inside the cavity may cause outgassing problems during the high temperature step of the wafer bonding. Considering all pros and cons of alternative hermetic wafer sealing technologies a eutectic AuSn wafer bond process was selected [1,2]. For using μ-bolometer it is necessary to use a cap construction that provides an access for 8-12μm infrared (FIR) radiation but blocks the sunlight. Without an antireflective coating or surface treatment, about 45% of the signal will not pass a silicon cap. Depending on the choice of Anti-reflective coating (ARC) of the silicon IRwindow up to 90% transmission in the range of 8-12 μm can be achieved. Process integration demands for an ARC technology that is fully compatible with all WLP-process steps and vacuum compatible. The choice may be further complicated by the high cost of multi-layer thin film ARC and possible yield loss due to local film defects. The texturing of the surface with special geometries, called moth-eyes, is an alternative approach increase the IRtransmission. The texturing avoids high costs, the need for wafer travelling, and reduces yield loss. Although the demand for a full sun blocking filter cannot be fulfilled, advanced moth-exe pattern can block at least a part of the short wavelength range up to 7 μm. These moth-eyes patterns are realized by reactive ion etching in the silicon surface. So the refractive index n can be changed from 3.4 down to 1.8 by limiting Fresnel reflection [3]. This innovative process is realized in combination with a thick deposited polysilicon distance frame that generates a cavity. The cap wafer construction integrates a double side wafer processing with a high resolved moth eye pattern inside a deep cavity (Fig. 1). Fig.1: Schematic of WLP construction with two different moth eye textures (A), (B) and TIGER3D-Getter (C). The cavity is formed by an additively grown ultra-thick polysilicon distance frame (D), metallized with AuSn for eutectic bonding [4].

Geographic Information Systems (GIS) and Remote Sensing (RS) applications are becoming an important issue for the territorial management, governmental and research projects, and for many fields of our society. A characteristic of such applications is the displaying of successive layers of information that, in some cases, may overlap areas of the displayed images that are eventually never showed to the final user of the application. Even though these overlapped areas are of null interest, the coding of these images considers the complete area of the image, and thus the coding performance of the compression system is penalized. This paper introduces a novel use of the Region Of Interest (ROI) coding techniques to overcome the drawbacks of the map overlapping in GIS and RS applications. The proposed approach is based on a ROI coding method defined for the JPEG2000 standard that efficiently improves the coding performance and keeps JPEG2000 compliance.

Abstract. The ISPRS Technical Commission I Midterm Symposium on "Intelligent Sensing and Remote Sensing Application" was held in Changsha, China, during May 13–17, 2024, aiming to provide a platform to share the latest researches, advanced technologies and application experience, to discuss the future development and to seek international cooperation in various forms. The Symposium has received 229 full paper and abstract s, among them 45 double-blind peer-reviewed full papers were published in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information, and 165 papers accepted through abstract review were published in the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. These papers are mostly dedicated to topics of the 8 TC I Working Groups, 3 Inter-commission Working Groups, including Satellite Missions and Constellations for Remote Sensing, Mobile Mapping Technology, Multispectral, Hyperspectral and Thermal Sensors, LiDAR, Laser Altimetry and Sensor Integration, Microwave and InSAR Technology for Earth Observation, Orientation, Calibration and Validation of Sensors, Data Quality and Benchmark of Sensors, Multi-sensor Modelling and Cross-modality Fusion, Robotics for Mapping and Machine Intelligence, Autonomous Sensing Systems and their Applications, Digital Construction: Reality Capture, Automated Inspection and Integration to BIM, Point Cloud Generation and Processing, Artificial Intelligence Technology Related to Sensor Systems, Multi-sensor Remote Sensing Applications.. These papers presented the latest trends of sensor systems. The full papers and abstracts were reviewed by the members of the Symposium Scientific Committee comprised of Working Group officers and invited experts. We would like to take this opportunity to express our great gratitude to the Scientific Committee, Local Organizing Committee, Sponsors, Exhibitors and all those who have contributed to this successful Symposium. We also want to express our thanks to the authors for their excellent papers and presentations. Tang Xinming, Antonio Maria Garcia Tommaselli, Zhang Tao, Xie JunfengISPRS Technical Commission I on Sensor SystemsMay 2024, Changsha, China

Abstract. The ISPRS Technical Commission I Midterm Symposium on "Intelligent Sensing and Remote Sensing Application" was held in Changsha, China, during May 13–17, 2024, aiming to provide a platform to share the latest researches, advanced technologies and application experience, to discuss the future development and to seek international cooperation in various forms. The Symposium has received 229 full paper and abstract s, among them 45 double-blind peer-reviewed full papers were published in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information, and 165 papers accepted through abstract review were published in the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. These papers are mostly dedicated to topics of the 8 TC I Working Groups, 3 Inter-commission Working Groups, including Satellite Missions and Constellations for Remote Sensing, Mobile Mapping Technology, Multispectral, Hyperspectral and Thermal Sensors, LiDAR, Laser Altimetry and Sensor Integration, Microwave and InSAR Technology for Earth Observation, Orientation, Calibration and Validation of Sensors, Data Quality and Benchmark of Sensors, Multi-sensor Modelling and Cross-modality Fusion, Robotics for Mapping and Machine Intelligence, Autonomous Sensing Systems and their Applications, Digital Construction: Reality Capture, Automated Inspection and Integration to BIM, Point Cloud Generation and Processing, Artificial Intelligence Technology Related to Sensor Systems, Multi-sensor Remote Sensing Applications.. These papers presented the latest trends of sensor systems. The full papers and abstracts were reviewed by the members of the Symposium Scientific Committee comprised of Working Group officers and invited experts. We would like to take this opportunity to express our great gratitude to the Scientific Committee, Local Organizing Committee, Sponsors, Exhibitors and all those who have contributed to this successful Symposium. We also want to express our thanks to the authors for their excellent papers and presentations. Tang Xinming, Antonio Maria Garcia Tommaselli, Zhang Tao, Xie JunfengISPRS Technical Commission I on Sensor SystemsMay 2024, Changsha, China

There has been significant expansion in the functionality and differentiation of modern remote sensing applications due to the exponential growth in adoption of Unmanned Aerial Vehicles (UAVs). With recent advancements of new technologies such as Artificial Intelligence - Machine Learning (AI-ML) and Cloud Computing, many opportunities have emerged to significantly evolve UAV based remote sensing applications. This paper presents a novel approach to evolve remote sensing application as a System-of-Systems (SoS). Bringing in the SoS perspective provides additional insights into the dynamics of the interactions between the various constituent systems (e.g. swarm UAVs, Ground stations) and the impact on the overall remote sensing application. Systematically analyzing the relationships between the various Measures-of-Effectiveness (MOEs) of the SoS vis-a-vis the constituent systems, in tandem with the evolution of the MOEs, would enable optimal leverage of the recent technology advancements for remote sensing applications

Essential Image Processing and GIS for Remote Sensing

AN ASSESSMENT OF SPATIAL VARIATION OF LAND SURFACE CHARACTERISTICS OF MINNA, NIGER STATE NIGERIA FOR SUSTAINABLE URBANIZATION USING GEOSPATIAL TECHNIQUES

Remote sensing applications often concern very large volumes of spatio-temporal data, the emerging Grid computing technologies bring an effective solution to this problem. The Open Grid Services Architecture (OGSA) treats Grid as the aggregate of Grid service, which is extension of Web Service. It defines standard mechanisms for creating, naming, and discovering transient Grid service instances; provides location transparency and multiple protocol bindings for service instances; and supports integration with underlying native platform facilities. It is not effective used in data-intensive computing such as remote sensing applications because its foundation, Web Service, is not efficient in scientific computing. How to increase the efficiency of the grid services for a scientific computing? This paper proposes a mechanism Grid service spread (GSS), which dynamically replant a Grid service from a Grid node to the others. We have more computers to provide the same function, so less time can be spent completing a problem than original Grid system. This paper also provides the solution how to adept the service duplicate for the destination node’s Grid environment; how each service duplicate communicates with each other; how to manage the lifecycle of services spread etc. The efficiency of this solution through a remote sensing application of NDVI computing is demonstrated. It shows that this method is more efficient for processing huge amount of remotely sensed data.

We propose two lossless archiving methods for the light field (LF) array of views created by plenoptic cameras, when the camera sensor images (also called lenslet images) are available. The two archiving methods are based on generative mechanisms, where we encode all information needed to run the processing pipeline that generates the LF array of views starting from source sensor images. The first archiving method starts by encoding the two sensor images needed as input in the processing pipeline: one scene sensor image, and one white image (available from the camera database of white images). The second archiver encodes a single lenslet-like image obtained by devignetting and debayering the scene sensor image and the white image. After encoding the input lenslet images both methods proceeds to encode all additional meta-information necessary for running the processing chain, starting from sensor image to the final LF array of views, and any needed corrections due to possible quantization along the processing chain, finally creating a lossless archive of the light field array of views. We exemplify the performance for a database of plenoptic camera images that was extensively used in the light field lossless compression literature, obtaining competitive archive file sizes.

An overview of current and potential applications of thermal remote sensing in precision agriculture

As a relatively new remote sensing means, unmanned aerial vehicle (UAV) remote sensing has been widely used in the fields of agriculture, forestry, and urban construction surveying and mapping because of its low cost, high efficiency, and flexibility. This paper introduces UAV remote sensing sensor technology and its applications in different fields. First, the core role of sensors in UAV remote sensing systems is introduced, including the development of multispectral, hyperspectral, and LiDAR sensor technologies and their applications in UAV remote sensing. Then, the working principles, technical characteristics, and application scenarios of multispectral, hyperspectral, and LiDAR sensors are discussed. Then, multi-sensor integration techniques in UAV remote sensing are discussed in terms of their importance and challenges. Finally, through the application cases of agricultural monitoring, forestry resource management, and urban construction mapping, the practicality and potential of UAV remote sensing technology are shown. This paper provides a reference for the research and application of UAV remote sensing and its sensor technology in several fields. With the continuous progress and innovation of technology, UAV remote sensing technology is expected to play a key role in more fields and promote the sustainable development of related industries.