remote sensing

Article Object-Based Mapping of Reef Habitats Using Planet Dove Satellites

Jiwei Li 1, Steven R. Schill 2, David E. Knapp 1 and Gregory P. Asner 1,*

1 Center for Global Discovery and Conservation Science (GDCS), Arizona State University, Tempe, AZ 85281, USA; [email protected] (J.L.); [email protected] (D.E.K.) 2 The Nature Conservancy, Caribbean Division, Coral Gables, FL 33134, USA; [email protected] * Correspondence: [email protected]

 Received: 23 May 2019; Accepted: 15 June 2019; Published: 18 June 2019 

Abstract: High spatial resolution benthic habitat information is essential for protection and coastal environmental management. Satellite-based shallow benthic composition mapping offers a more efficient approach than traditional field measurements, especially given the advancements in high spatial and temporal resolution satellite imagery. The Planet Dove satellite constellation now has more than 150 instruments in orbit that offer daily coverage at high spatial resolution (3.7 m). The Dove constellation provides regularly updated imagery that can minimize cloud in tropical oceans where dense cloud cover persists. Daily image acquisition also provides an opportunity to detect time-sensitive changes in shallow benthic habitats following coral bleaching events, storms, and other disturbances. We developed an object-based coral reef habitat mapping approach for Dove and similar multispectral satellites that provides bathymetry estimation, bottom reflectance retrieval, and object-based classification to identify different benthic compositions in shallow coastal environments. We tested our approach in three study sites in the using 18 Dove images. Benthic composition classification results were validated by field measurements (overall accuracy = 82%). Bathymetry and bottom reflectance significantly contributed to identifying benthic habitat classes with similar surface reflectance. This new object-based approach can be effectively applied to map and manage coral reef habitats.

Keywords: Planet Dove; coral reef; benthic composition; ; coastal; shallow; tropical ocean

1. Introduction Coral reefs and associated shallow coastal ecosystems are among the most productive and vulnerable in the world [1]. Effective protection and management of coral reefs rely heavily on accurate and up-to-date spatially-explicit information on shallow benthic habitats [2]. Traditional labor-intensive field surveys offer point and transect records that can only be applied to small areas [3]. While field-based methods can collect detailed information along coral reef transects, these data are often limited to very small areas and are inadequate for monitoring large areas [4]. However, satellite remote sensing technology, when combined with field survey data, provides a solution to repeatedly map and monitor coral reef benthic habitats over large geographic areas [5]. A common trade-off of remote sensing is its lower accuracy compared to field surveys. Advances in Earth observation offer benefits to coral reef habitat mapping via higher spatial resolution (pixel sizes <5 m) and increasing temporal resolution [6]. High image acquisition frequency (e.g., daily) provides increased likelihood of obtaining cloud-free scenes over tropical regions and delivers time-sensitive data allowing detection of changes to the benthos such as large-scale coral bleaching [2,7]. In NASA MODIS image analyses, a typical portion of the cloud-free satellite images over reef regions ranges from 20% to 30% [8,9]. Previous coral reef studies have been conducted using

Remote Sens. 2019, 11, 1445; doi:10.3390/rs11121445 www.mdpi.com/journal/remotesensing Remote Sens. 2019, 11, 1445 2 of 16 mid-spatial resolution satellite images (e.g., Landsat-8, Sentinel-2) or high-resolution images with low temporal frequency (e.g., IKONOS, Worldview) [3,4,10–13]. Coral reef mapping could benefit from high temporal frequency satellite sensors (e.g., Planet Dove). Mapping benthic composition in shallow coastal environments requires multiple inputs, including sea surface reflectance, bottom (or benthic) reflectance, and bathymetry to identify different habitats using either an object- or a pixel-based approach [2,14]. In particular, bathymetry information is central to identifying different benthic surfaces within distinct coastal geomorphic zones. Moreover, bottom reflectance retrieved from satellite images follows the removal of water column attenuation effects using radiative transfer modeling techniques [15]. Here, we developed a comprehensive object-based mapping approach that provides bathymetry estimation, bottom reflectance retrieval, and object-based classification, all using Planet Dove satellite images. We applied and verified our approach in three coastal sites located in the southeastern Dominican Republic using GPS-referenced underwater video and transducer bathymetry field data. We then performed an accuracy assessment analyzing different benthic habitat types and bathymetric ranges. As part of this research, we also investigated the effects that benthic habitat reflectance, bathymetry, and water column attenuation have on Dove-derived coral reef habitat products.

2. Materials and Methods

2.1. Study Sites Three shallow coastal study sites were selected within a recently declared 8000 km2 marine sanctuary “Arrecifes del Sureste” (Latitude: ~17.5◦–18.8◦ N, Longitude: ~67.8◦–69.35◦ W). This sanctuary covers 120 km of coast and is a primary tourism hub, receiving over 4 million visitors annually (Figure1). With coral reef-based tourism being a major part of the local Dominican Republic economy, a park management plan is currently being developed to monitor and protect these coastal ecosystems. We chose benthic classes to conform to those used by conservation practitioners who manage these habitats within the Dominican Republic. Our research provides an opportunity to test object-based shallow benthic composition mapping across a wide range of benthic types, geomorphic zones, and bathymetric ranges. Such products can provide baseline data, monitor changes, and inform adaptive management actions within the park. Remote Sens. 2019, 11, 1445x FOR PEER REVIEW 33 of of 16

Figure 1. Planet Dove mosaic imagery (shown in RGB true color) covering three study sites within Figurethe Arrecifes 1. Planet del Dove Sureste mosaic marine imagery sanctuary (show in southeasternn in RGB true Dominican color) covering Republic three (DR): study Catalina sites with Islandin the(a), Arrecifes eastern Dominican del Sureste Republic marine sanctuary (b), and Saona in southeastern Island (c). FieldDominican data transects Republic are (DR) shown: Catalina as red Island lines. (Thea), eastern general Dominican location of Republic the study ( regionb), andis Saona provided Island in ( thec). Field lower data right transects panel. are shown as red lines. The general location of the study region is provided in the lower right panel. 2.2. Field Data Collection 2.2. FieldFrom D 30ata AprilCollection to 4 May 2018, a total of six field transects were generated to measure and assess a diverseFrom array 30 April of benthic to 4 May compositions 2018, a total withinof six field the threetransects study were sites generated (Catalina to Island, measure Saona and Island,assess aand diverse Eastern array Dominican of benthic Republic, compositions Figure with1). Bathymetricin the three study field measurements sites (Catalina wereIsland, collected , using anda Lowrance Eastern Elite7TiDominican® (Tulsa, Republic, OK, Figure USA) system1). Bathymetric with a xSonic field measurements P319 (50/200 kHz) were transducer collected using and 10 a LowranceHz GPS receiver Elite7Ti that ® ( collectedTulsa, OK continuous, USA) system depth with readings a xSonic at 3P319 pts/ sec(50/200kHz) along each transducer transect. Inand parallel, 10Hz GPSa GPS-referenced receiver that SeaViewercollected continuous Sea-Drop 6000 depth HD readings (Tampa, at FL, 3 USA)pts/sec underwater along each video transect. camera In parallel, with 30 ma GPSvertical-referenced cable was SeaView used toer record Sea-Drop benthic 6000 habitat HD (Tampa, types along FL,each USA) transect underwater (Table 1video). A total camera of 152.4 with km 30 mof vertical bathymetric cable measurements was used to record and122 benthic benthic habitat video types samples along were each recorded transect (Table along all1). transects.A total of From152.4 kmthese of data, bathymetric we generated measurements 5300 bathymetric and 122 measurement benthic video points samples at a 15were m interval.recorded Benthic along all habitat transects. types (coralFrom reefthese crest, data, coral we patchgenerated deep, 5,300 coral bathymetric back-reef/flat, measurement coral fore-reef, points gorgonian at a 15/soft m coral,interval hardbottom. Benthic withhabitat algae, types seagrass (coral reef dense, crest, seagrass coral patch sparse, deep, sand coral shallow, back and-reef/flat, sand coral deep withfore-reef, sparse gorgonian/soft macroalgae) werecoral, classifiedhardbottom for with each videoalgae, sampleseagrass (Table dense,1). seagrass A total ofsparse, 3000 pointssand shallow, were applied and sand as the deep training with sparsesamples macroalgae for the object-based) were classified classification. for each The video remaining sample 2300 (Table points 1). were A usedtotal for of 3,000 model points verification. were Weapplied selected as the the training training samples and verification for the object points-based based classification. on depths and The habitat remaining types. 2,300 points were used for model verification. We selected the training and verification points based on depths and habitat types.

Remote Sens. 2019, 11, x FOR PEER REVIEW 4 of 16

Table 1. Benthic composition classification scheme.

Benthic Description [16] Field Video Example Habitat type Remote Sens. 2019, 11, x FOR PEER REVIEW 4 of 16 Coral Reef Crest is found in shallow water break zones. Table 1. Benthic composition classification scheme. Remote Sens. 2019, 11, x FOR PEERThe REVIEWbenthic cover consists of 4 of 16 Remote Sens. 2019, 11, 1445 Benthic coral build up and 4 of 16 Remote Sens. Coral2019, 11 Reef, x FOR PEER REVIEWDescription [16] Field Video Example 4 of 16 Habitat type turf/calcareousTable 1. Benthic algae. composition Large classification scheme. Crest Coralfleshy Reef macroalgae Crest is found are in Benthic Table 1. Benthic composition classification scheme. Table 1. BenthicshallowlargelyDescription composition water absent break and [16] onlyzones. classification scheme.Field Video Example Habitat type Benthic Thesmall benthic coral cover colonies consists were of Coral DescriptionReef Crest is [16] found in Field Video Example Benthic Habitat TypeHabitat type Descriptioncoralobserved. build [16] up and Field Video Example Coral Reef shallow water break zones. Coralturf/calcareousCoral Patch Reef CrestDeep algae. isis foundtypically Large in Crest The benthic cover consists of coveredshallowfleshy with water macroalgae a veneerbreak zones. areof turf coral build up and CoralCoral Reef Reef CrestThealgae islargely foundbenthic and absent in acover shallowsparse and consists (<5 only water %) of turf/calcareous algae. Large breakCrest zones. Thecoversmall benthiccoral of coral scleractinian build cover colonies up consists and werecoral, of Coralcoral Reef build up andfleshy turf/ calcareousmacroalgae algae. are Coral Reef Crest turf/calcareoushydrocoral,observed. gorgonians, algae. Large LargeCrest fleshy macroalgaelargely areabsent largely andabsent only Coral Patch Coralspongesfleshy Patch ,macroalgae and Deep macroalgae. is typically are and only smallsmall coral coral colonies colonies were were Deep coveredlargelyTypically with absent found a ven