*1.1. Motivation*

"Despite twenty-first-century technological advances by Western militaries for demining and the removal of improvised explosive devices, humanitarian demining relies mostly on mid-twentieth-century technology" [1].

Although we share this opinion—at least, regarding aerial survey technologies—we attempt to contribute to advancement by supporting the deployment of hyperspectral surveys by civilian users exposed to explosive device threats. We consider the following explosive devices: unexploded ordnances (UXOs), landmines (LMs), cluster munition (CM), improvised explosive devices (IEDs), homemade explosive (HME) devices, and explosive remnants of war (ERW). The civilian users that we consider are, among others: Single or group ground vehicles of humanitarian demining organizations, traveling from camp to the working area and returning, logistics convoys, medical, humanitarian aid, Red Cross, reconstruction, security forces, civilian VIP travelers, and others. The level of incidents and casualties for civilian vehicles and convoys dominate, when compared to military or security forces [2]. The focus of the technology reviewed and used in this work mostly considers the platforms, sensors, and software available to the civil sector.

There are several new aspects of these topics, and humanitarian mine action cannot be restricted only to the disposal of the landmines by humanitarian demining. Therefore, we briefly consider hazardous explosive threats, non-technical surveys (NTSs) [3], the technologies in use (based on the aerial survey), and advanced survey technologies under a high level of technical readiness. There are several promising sensor technologies, such as hyperspectral, non-linear junction detection (NLJD), LIDAR, longwave infrared, magnetometer, and ground-penetrating radar (GPR); however, in this article, we focus on passive hyperspectral data. This technology is specific, due to a lack of civilian (or public

**Citation:** Baji´c, M., Jr.; Baji´c, M. Modeling and Simulation of Very High Spatial Resolution UXOs and Landmines in a Hyperspectral Scene for UAV Survey. *Remote Sens.* **2021**, *13*, 837. https://doi.org/10.3390/ rs13050837

Academic Editors: Piotr Kaniewski, Mateusz Pasternak and Stefano Mattoccia

Received: 10 January 2021 Accepted: 19 February 2021 Published: 24 February 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

military) hyperspectral data regarding the considered explosive devices in a realistic and non-laboratory environment. A new positive fact is that hyperspectral imaging sensors used on unmanned aerial vehicles (UAVs) can provide pixel resolutions smaller than the explosive devices on the ground surface (very high spatial resolution), which is not practical when using aerial helicopter platforms.

We consider threats caused by several types of explosive devices: IEDs, UXOs, LMs, and ERW. Data about their spatial distribution are limited and, for IEDs, are typically classified. One possible solution is to predict the emplacement of explosive devices by simulation. Generally, several aspects should be considered in simulations: (1) terrain features, (2) explosive devices, (3) objects, and (4) methods of detection of explosive devices from data collected by sensors on remotely piloted aircraft systems.

Our research aims to derive modeling methods and to simulate explosive targets in a hyperspectral scene, through the use of real hyperspectral data of the considered types of explosive devices.

#### *1.2. Possible Terrain Case*

An exciting and valuable example of the situational and spatial behavior of IEDs has been presented in [4] and in a color video acquired from an unmanned aerial vehicle (UAV) [5]. The following photograph (Figure 1) shows a typical large-scale terrain and explosive targets in an arid region in Iraq. It is evident that this explosive hazard scene has a lack of vegetation, and the explosive devices are on the ground surface. The targets in such situations are "ideal" for hyperspectral survey and detection by UAV.

**Figure 1.** Remnants of a cluster munition in South Iraq; "Ideal" targets for hyperspectral detection from UAV [4].

Besides the need for detection and mapping of explosive devices, there exists needs and demands for the non-technical survey (NTS) of larger areas contaminated by various explosive objects. When one considers such areas for NTS, the most critical function of a survey system is the endurance (autonomy) of the UAV. The explosive hazard situation in many afflicted countries is similar to the above description, where the existing differences are mainly in the IED technique and application.

The United Nations peacekeeping forces are exposed to explosive threats; therefore, they have developed guidelines on IED threat mitigation [6]. The European Defense Agency realized the IED Detection Program from 2016 to 2019, in order to improve and to field-test IED detection capabilities to define future Route Clearance and Attack the Network capabilities [7].

#### *1.3. The Civilian Aerial Survey Technologies for Explosive Threats*

We have previously actively participated and contributed to the research, development, and operational deployment of a multisensory and multispectral non-technical survey (NTS) [3], mainly based on the detection of secondary indicators of mine presence (IMP) or indicators of the absence (IMA) of landmines in minefields [8,9].

The IMP and IMA depend on the situation, war history, terrain, climate, and vegetation cover, and are specific for each set of mentioned influencing factors. IMP and IMA have been identified in Croatia, Bosnia, and Herzegovina, [9]; similar IMP and IMA could be expected in Ukraine. However, for countries in the Near East (e.g., Iraq, Afghanistan, and Syria) and North Africa (e.g., Libya), the IMP and IMA will be significantly different. Due to a lack of vegetation in the mentioned countries, there exist chances for the direct detection of targets—that is, the explosive devices (UXO, LM, IED, CM, ERW)—on the ground surface by passive electro-optical sensors (see example from Iraq, Figure 1). With active sensors, these targets also can be detected in the soil.

The first UAV for humanitarian mine action appeared in the EU project ARC [8]. In the last 5 to 10 years, the application of UAVs with visible color sensors for humanitarian mine action has increased [4,5,9–12]. The statement made in Use of Aerial Imagery in Urban Survey & Use of UAVs in Mine Action—Lessons Learned from Six Countries, in simple words, generalizes the experience gained since 2019 regarding UAVs with advanced sensors:

"No export restrictions. Platforms as small as possible. We want to operate equipment ourselves, not rely on external personnel. In the short term, detection capabilities are more important than the interface. Need to see real evidence of value before committing to field trials. Detection is only one stage of the clearance process. The combination of sensors and platforms must offer some advantage in terms of reduced false alarms or detection ability, not just the speed of coverage. Vegetation cover will be a major limiting factor in many places usually we cannot remove this in advance because of safety, cost, or environmental damage. The abilities of the sensor/data processing are what matters. Possible sensors: Thermal IR, Hyperspectral, Magnetometers?" [11].

Three essential facts have enabled the stepwise increase in survey efficiency by UAV: (A) The UAV industry (e.g., DJI) has produced very advanced systems which enable computer planning and automated airborne acquisition missions with several sensors. (B) The sensors industry has provided powerful devices matched to UAVs. (C) The software industry has provided tools for processing recordings collected by UAVs, producing the highest quality outcomes. Yet, only color visible cameras have been used in civilian humanitarian domain operations (as of May 2020). The (A), (B), and (C) changes have been finalized in the last several years; now, the average trained deminer-surveyor can use an UAV for their survey tasks, including preparing and planning field missions, preprocessing data into images, and processing these images into valuable and high-quality products for humanitarian mine action, in a short time. There has been an excellent example of the application of the UAV-based survey technology at the level of an entire country [12].

One exciting and challenging possibility is to detect buried explosive devices through spectral changes and derived indicators of the soil surface, as well as plant spectral changes, if exposed to the influence of landmines and explosives. Even if not applicable to arid surfaces, the hyperspectral assessment of plant spectral stress due to landmines and explosives has given promising initial results. Several research projects have been based on this assumption; one of the first was in 1997 [13]. In this project, a hyperspectral imager, named "casi", was used for the detection of buried landmines and blocks of explosive, reporting the probability of detection (in the range from 55% to 94%) and a false alarm rate (from 0.17 m<sup>−</sup><sup>2</sup> to 0.52 m<sup>−</sup>2). Another research direction was to detect the difference of spectra of plants inside of a minefield, compared to the spectra of plants outside the minefield; that is, in areas that were clean of explosive and agricultural fertilizers. In [14–16], airplane platforms have been used, whereas [17] used different hyperspectral sensors

onboard a UAV, helicopter, and ground-based vehicle [18]. This research direction considers changes in vegetation (plants, bushes, and trees) spectra after exposure to contamination with explosives [19,20]. Although the described domain is impressive, our feeling is that its operational potential is not high enough yet.

#### *1.4. The Direct Detection of Explosive Targets and Detection of Their Secondary Indicators*

Current UAV-based operational surveys for the detection of UXO, LM, IED, CM, and ERW only use (visible) color sensors [4,10,11]. Here, we comment on several other sensor technologies in the development or testing phase; although, we thoroughly only consider hyperspectral technology in later sections.

Longwave infrared (LWIR) or thermal infrared (TIR) sensors are now available as dual sensor units, together with a visible color camera (produced by FLIR and DJI) for application onboard UAVs. The dual-sensor delivers TIR and visible color images, either separated or overlapped. TIR sensors are also now available in a version which is optimized for UAV surveys [21,22]. One interesting solution for a long endurance survey is a tethered UAV [23].

For the active detection, via UAV, of targets in the soil or behind obstacles, non-linear junction detectors or harmonic radar (NLJD) can be used [24,25]. A ground-penetrating radar is under development for the detection of buried targets (GPR) from UAV [26–30].

The magnetometer on an UAV enables the automatic survey and detection of ferromagnetic UXO targets [31,32].

In the following chapters, we present the research results regarding the hyperspectral data of explosive targets. The first possible reference for the hyperspectral detection of landmines is from 1997 [13]. According to the best of our knowledge, there are no available/accessible hyperspectral data of explosive targets (UXO, LM, IED, CM, ERW) collected by UAV or, at least, collected by ground-based hyperspectral sensors in the considered afflicted countries. The exceptions are the cases where a limited amount of hyperspectral data of UXO, LM, and minefields were collected in the European environment, in minefields and exploded ammunition depots, by helicopter-, UAV-, and ground-based acquisition systems [9,17,18,33]. Some data collected by fixed-wing plane are available for Africa [14,15] and in Germany [16]. Ground-based hyperspectral data collection of landmines has also been carried out in Lebanon [34–36].

#### *1.5. Hyperspectral Sensors and Platforms*
