Evaluation of Individual Plant Growth Estimation in an Intercropping Field with UAV Imagery

Agriculture practices in monocropping need to become more sustainable and one of the ways to achieve this is to reintroduce intercropping. However, quantitative data to evaluate plant growth in intercropping systems are still lacking. Unmanned aerial vehicles (UAV) have the potential to become a state-of-the-art technique for the automatic estimation of plant growth. Individual plant height is an important trait attribute for field investigation as it can be used to derive information on crop growth throughout the growing season. This study aimed to investigate the applicability of UAV-based RGB imagery combined with the structure from motion (SfM) method for estimating the individual plants height of cabbage, pumpkin, barley, and wheat in an intercropping field during a complete growing season under varying conditions. Additionally, the effect of different percentiles and buffer sizes on the relationship between UAV-estimated plant height and ground truth plant height was examined. A crop height model (CHM) was calculated as the difference between the digital surface model (DSM) and the digital terrain model (DTM). The results showed that the overall correlation coefficient (R2) values of UAV-estimated and ground truth individual plant heights for cabbage, pumpkin, barley, and wheat were 0.86, 0.94, 0.36, and 0.49, respectively, with overall root mean square error (RMSE) values of 6.75 cm, 6.99 cm, 14.16 cm, and 22.04 cm, respectively. More detailed analysis was performed up to the individual plant level. This study suggests that UAV imagery can provide a reliable and automatic assessment of individual plant heights for cabbage and pumpkin plants in intercropping but cannot be considered yet as an alternative approach for barley and wheat.

Mangrove Above-Ground Biomass and Carbon Stock in the Karimunjawa-Kemujan Islands Estimated from Unmanned Aerial Vehicle-Imagery

Blue carbon ecosystems in the Karimunjawa Islands may play a vital role in absorbing and storing the releasing carbon from the Java Sea. The present study investigated mangrove above-ground biomass (AGB) and carbon stock in the Karimunjawa-Kemujan Islands, the largest mangrove area in the Karimunjawa Islands. Taking the aerial photos from an Unmanned Aerial Vehicle combined with Global Navigation Satellite System (GNSS) measurements, we generated Digital Surface Model (DSM) and Digital Terrain Model (DTM) with high accuracy. We calculated mangrove canopy height by subtracting DSM from DTM and then converted it into Lorey’s height. The highest mangrove canopy is located along the coastline facing the sea, ranging from 8 m to 15 m. Stunted mangroves 1 m to 8 m in height are detected mainly in the inner areas. AGBs were calculated using an allometric equation destined for the Southeast and East Asia region. Above-ground carbon biomass is half of AGB. The AGB and carbon biomass of mangroves in the Karimunjawa-Kemujan Islands range from 8 Mg/ha to 328 Mg/ha, and from 4 MgC/ha to 164 MgC/ha, respectively. With a total area of 238.98 ha, the potential above-ground carbon stored in the study area is estimated as 16,555.46 Mg.

Subpixel-Scale Topography Retrieval of Mars Using Single-Image DTM Estimation and Super-Resolution Restoration

We propose using coupled deep learning based super-resolution restoration (SRR) and single-image digital terrain model (DTM) estimation (SDE) methods to produce subpixel-scale topography from single-view ESA Trace Gas Orbiter Colour and Stereo Surface Imaging System (CaSSIS) and NASA Mars Reconnaissance Orbiter High Resolution Imaging Science Experiment (HiRISE) images. We present qualitative and quantitative assessments of the resultant 2 m/pixel CaSSIS SRR DTM mosaic over the ESA and Roscosmos Rosalind Franklin ExoMars rover’s (RFEXM22) planned landing site at Oxia Planum. Quantitative evaluation shows SRR improves the effective resolution of the resultant CaSSIS DTM by a factor of 4 or more, while achieving a fairly good height accuracy measured by root mean squared error (1.876 m) and structural similarity (0.607), compared to the ultra-high-resolution HiRISE SRR DTMs at 12.5 cm/pixel. We make available, along with this paper, the resultant CaSSIS SRR image and SRR DTM mosaics, as well as HiRISE full-strip SRR images and SRR DTMs, to support landing site characterisation and future rover engineering for the RFEXM22.

Retrieval of DTM under Complex Forest Stand Based on Spaceborne LiDAR Fusion Photon Correction

The new generation of satellite-borne laser radar Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) data has been successfully used for ground information acquisition. However, when dealing with complex terrain and dense vegetation cover, the accuracy of the extracted understory Digital Terrain Model (DTM) is limited. Therefore, this paper proposes a photon correction data processing method based on ICESat-2 to improve the DTM inversion accuracy in complex terrain and high forest coverage areas. The correction value is first extracted based on the ALOS PALSAR DEM reference data to correct the cross-track photon data of ICESat-2. The slope filter threshold is then selected from the reference data, and the extracted possible ground photons are slope filtered to obtain accurate ground photons. Finally, the impacts of cross-track photon and slope filtering on fine ground extraction from the ICESat-2 data are discussed. The results show that the proposed photon correction and slope filtering algorithms help to improve the extraction accuracy of forest DTM in complex terrain areas. Compared with the forest DTM extracted without the photon correction and slope filtering methods, the MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) are reduced by 51.90~57.82% and 49.37~53.55%, respectively. To the best of our knowledge, this is the first study demonstrating that photon correction can improve the terrain inversion ability of ICESat-2, while providing a novel method for ground extraction based on ICESat-2 data. It provides a theoretical basis for the accurate inversion of canopy parameters for ICESat-2.

COMPARISON ASSESSMENT OF DIGITAL 3D MODELS OBTAINED BY DRONE-BASED LIDAR AND DRONE IMAGERY

The purpose of this study is to assess the potential of drone airborne LiDAR technology in Morocco in comparison with drone photogrammetry. The cost and complexity of the equipment which includes a laser scanner, an inertial measurement unit, a positioning system and a platform are among the causes limiting its use. Furthermore, this study was motivated by the following reasons: (1) Limited number of studies in Morocco on drone-based LiDAR technology applications, (2) Lack of study on the parameters that influence the quality of drone-based LiDAR surveys as well as on the evaluation of the accuracy of derived products. In this study, the evaluation of LiDAR technology was carried out by an analysis of the geometric accuracy of the 3D products generated: Digital Terrain Model (DTM), Digital Surface Model (DSM) and Digital Canopy Model (DCM). We conduct a comparison with the products generated by drone photogrammetry and GNSS surveys. Several tests were carried out to analyse the parameters that influence the mission results namely height, overlap, drone speed and laser pulse frequency. After data collection, the processing phase was carried out. It includes: the cleaning, the consolidation then the classification of point clouds and the generation of the various digital models. This project also made it possible to propose and validate a workflow for the processing, the classification of point clouds and the generation of 3D digital products derived from the processing of LiDAR data acquired by drone.

How Can Remote Sensing Reduce Required Human Intervention in Robotic Forest Regeneration

In this article, we introduce an alternative solution for forest regeneration based on unmanned ground vehicles (UGV) and describe requirements for external data, which could significantly increase the level of automation. Over the past few decades, the global forested area has decreased, and there is a great need to restore and regenerate forests. Challenges such as the lack of labor and high costs demand innovative approaches for forest regeneration. Mechanization has shown satisfactory results in terms of time-efficient planting, although its usage is limited by high operational costs. Innovative technologies must be cost-efficient and profitable for large scale usage. Automation could make mechanized forest regeneration feasible. Forest regeneration operations can be automated using a purpose built unmanned platform. We developed a concept to automate forest planting operations based on mobility platform. The system requires external data for efficient mobility in clear-cut areas. We developed requirements for external data, analyzed available solutions, and experimented with the most promising option, the SfM (structure from motion) technique. Earth observation data are useful in the planning phase. A DEM (digital terrain model) for UGV planter operations can be constructed using ALS (airborne laser scanning), although it may be restricted by the cost. Low-altitude flights by drones equipped with digital cameras or lightweight laser scanners provided a usable model of the terrain. This model was precise (3–20 cm) enough for manually planning of the trajectory for the planting operation. This technique fulfilled the system requirements, although it requires further development and will have to be automated for operational use.

URBAN FLOOD IMPACTS, FLOOD WATER QUALITY AND RISK MAPPING OF OLODO AREA, IBADAN, NIGERIA

This study assessed urban flood impact, flood water quality and vulnerability around Olodo area of Ibadan region, Nigeria. The study employed remote sensing and GIS techniques in creating vulnerability and risk maps. Digital terrain model (DTM) was used to get the topography of the study area. Footprints of buildings along the Egberi riverbank and flood plain in Olodo were created in the GIS environment from high resolution satellite imagery. Buffering operation was conducted to classify the buildings into risk zones based on closeness to the riverbank using ArcGIS 10.0. The study revealed that 326 buildings were within the very vulnerable and vulnerable zones because they were less than 15.2m away from the riverbank. The characteristics of water quality change during the flood and non-flood periods. TSS, DO, NOD, and COD were all higher during the flood event. Microbial analysis showed that water quality levels in the floodwater exceeded water quality standards (e.g., the coliform excess from 10 to 10,000 times), and thus this may be a health risk for local people during flood events. Concentration of Escherichia coli (E. coli) ranged from 484 to 1290 cfu/100 mL during flooding compared to 192 to 295 cfu/100 mL after flood. Salmonella was found to be high ranging from 659 to 1840 cfu/100 mL during flooding compared to 530 to 1034 cfu/100 mL after flooding.

Možnosti srovnávací analýzy plužiny zaniklých středověkých vsí. Vypovídací hodnota vybraných lokalit a role digitálního modelu reliéfu z dat leteckého laserového skenování

The paper deals with the plowlands of deserted medieval villages (DMVs) representing a specific data source of medieval settlement research. Its basic priorities are based on the needs of archaeological heritage protection for a better definition of DMVs’ hinterlands, which are significantly less distinguishable in comparison with villages’ intravilans. At the same time, not much attention was paid to this area, even in known or well-surveyed sites. These issues are important especially in the context of what exactly we are looking for within the DMVs, how we define it and where we can find the best examples worthy of protection or further study. The basis of the presented work is the processing of a digital terrain model derived from airborne laser scanning data. The primary procedure consists of the ALS data processing into a DEM, its subsequent visualization, and classification of objects in DMVs’ hinterlands, which is further supplemented by selected examples of field verification. The informative value of the hinterlands is also discussed on the example of several differently preserved sites.

Comparative Analysis of DTM Results with Hydro Enforcement LiDAR Data Method and Interferometric Synthetic Aperture Radar (InSAR) from Radar Satellite Imagery (Case Study of Kebumen Regency)

Data containing information on the terrain elevation model is necessary for several uses related to human activities, such as development planning, spatial planning, disaster modeling, disaster mitigation planning, land productivity estimation, etc. Information about the ground elevation can be presented in a 3-dimensional topographical model such as Digital Terrain Model (DTM). There are several technologies used to form DTM data, including by using LiDAR and radar satellites (Sentinel-1). The hydro enforcement method is used to process DTM with LiDAR data by modifying the elevation value of LiDAR data in water areas during data processing. The height of this feature is modified digitally to achieve hydrological connectivity. This method aims to produce a DTM according to the principles of hydro enforcement and hydro flatten. While for processing DTM radar data, the InSAR method is used. InSAR is a remote sensing technique to extract three-dimensional information from the earth’s surface with the phase of radar waves. Additional data of morphological information and break lines were added to provide more representative information on the actual situation. The result of this research is the value of vertical geometry accuracy (LE90) of DTM to RBI data with a scale of 1:25,000. In this research, 5 kinds of DTM have been successfully formed with LE90 vertical accuracy values are as follows: LiDAR DTM with LE90 of 4.614 m; InSAR DTM with LE90 of 9.583 m; InSAR breakline with LE90 of 9.433 m; InSAR RBI assimilation with LE90 of 2.532 m; and InSAR DTM-LiDAR assimilation with LE90 of 4.077 m. DTM with the highest accuracy based on Topographic Map (RBI) 1:25,000 is InSAR DTM RBI assimilation and the lowest accuracy is DTM InSAR without breakline and assimilation data.

Nově objevené hradiště Čerťák u obce Sovolusky v kontextu halštatského osídlení regionu

This paper presents a new hillfort site which is situated on top of „Čerťák“ Hill (651 m n. m.), Sovolusky municipality, Karlovy Vary district. It has been identified with the help of a digital terrain model based on Airborne Laser Scanning (LiDAR). Two separate lines of stone ramparts have been confirmed on top of the Čerťák Hill, formed by a significant right bank meander in the upper course of the river Střela. The inner area reaches 1.4 ha and the external enclosed area spreads to 2.3 ha. Subsequent field research yielded a collection of more than 500 pottery fragments from the Late Hallstatt period. The dispersion of finds shows relatively intensive settlement. The paper also discusses other sites in the surrounding region which date to the same period. The Hallstatt settlement seems to have been a structurally connected complex in the presented area.