{ "docId": "019dd923-5e88-73ef-bd58-0a90f274909d", "docSlug": "53b53a981c0ad9b0", "documentTitle": "COPERNICUS Market report February 2019", "authorId": "PwC", "authorName": "PwC", "documentKindSlug": "consulting-deck", "documentKindLabel": "Consulting deck", "sourceTypeSlug": "strategy_consulting", "sourceTypeLabel": "Strategy consulting", "presentationDate": null, "orientation": "landscape", "aspectRatio": 1.778, "pageNumber": 53, "pageCount": 164, "prevPage": 52, "nextPage": 54, "slideType": "industry_trends", "function": "establish_context", "density": "overcrowded", "nDataPoints": 0, "notes": null, "elementsJson": [ "paragraph", "icon_grid" ], "metadataConfidence": 1, "imagePath": null, "slideHref": "/slides/019dd923-5e88-73ef-bd58-0a90f274909d/53", "deckHref": "/decks/019dd923-5e88-73ef-bd58-0a90f274909d", "deckJsonHref": "/decks/019dd923-5e88-73ef-bd58-0a90f274909d.json", "deckAnchorHref": "/decks/019dd923-5e88-73ef-bd58-0a90f274909d#slide-53", "components": [ { "bbox": { "h": 0.18, "w": 0.4, "x": 0.54, "y": 0.21 }, "kind": "list", "text": "DRIVER 1: Cost reduction in monitoring compliance to forest management best practices (for national forest agencies)\nDRIVER 2: Improve and preserve forest ecosystems and green infrastructures\nDRIVER 3: Improved yields in forest industry thanks to sustainable management (increasing volume and quality of timber in the long term)", "attrs": null, "subkind": "bullet", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "a694c3c6-a99c-4082-9363-7dab3b6fe4c1", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.2, "w": 0.44, "x": 0.06, "y": 0.68 }, "kind": "list", "text": "CHALLENGE 1: For some parameters, the methodologies for producing maps at scale have not been developed or validated\nCHALLENGE 2: EO data from satellites, manned aircraft, or UAVs still need major enhancements to map given characteristics\nCHALLENGE 3: The change in the signal detected by the EO instrument(s) over time is not necessarily related to changes in the forest characteristics", "attrs": null, "subkind": "bullet", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "c5f58049-1751-4cdb-bb94-f5faafd78e63", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.12, "w": 0.44, "x": 0.06, "y": 0.21 }, "kind": "paragraph", "text": "EO data is mostly used by national forest agencies to monitor the compliance of the forest owners to the law. Indeed, rules have been implemented to prevent private owners of forests from depleting this national asset. In these regards, the development of clear-cut maps will enable the authorities to enforce the rules in the forestry sector. Forest agencies in other European countries use commercial satellite imagery to prepare their maps.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "74f39d87-21cb-40c3-bc57-abf41d73d428", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.25, "w": 0.4, "x": 0.54, "y": 0.68 }, "kind": "paragraph", "text": "One of the main challenges of using EO data for forest mapping is constructing time series on given characteristics. Large budgets do not guarantee the quality of forest variation maps; for many aspects (e.g. biodiversity) there is still a need to develop or validate methodologies for producing maps at scale, not to mention the impossibility to retroactively collect new data from past data gathering. Mapping variations over time still relies on the analysis of suboptimal historical satellite datasets, while mapping certain parameters may involve extensive ground research and data.\n\nSecondly, there seems to be a gap between users' expectations on actual quality of data, and what this data can actually accurately map, especially within a reasonable budget for the users.\n\nMoreover, the change in the signal over time detected by EO sensors does not necessarily reflect variations in the forest features, but may indicate changes in atmospheric conditions, vegetation seasonal changes or humidity conditions, or even the actual calibration of the sensor itself. The accuracy of such maps thus needs to be assessed through further ground data or independent EO products, and to rely on EO data and methods that are least likely to cause misconception in the resulting map.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "bef9a0e0-f4d3-4067-bc66-c29c9a1716f0", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.15, "w": 0.44, "x": 0.06, "y": 0.34 }, "kind": "paragraph", "text": "Preserving forest ecosystems and green infrastructure is crucial for peoples' well-being. They are hosting global biodiversity, and they provide benefits to society and the economy via the provision of ecosystem services (soils erosion protection, watershed regulation, climate regulation, carbon storage and water/air purification). EO data provides forest authorities accurate forest mapping. Thanks to time series of satellite images, forest authorities are able to detect change in the land cover/land use in forest areas, such as illegal clear cut.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "f2ca8e1a-722c-4ae7-9962-ccfaf58f93ad", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.15, "w": 0.44, "x": 0.06, "y": 0.5 }, "kind": "paragraph", "text": "Lastly, sustainable management of forests requires activities like replanting within 3 years after the clear-cut and one or even two pre-commercial thinning within the 10 years after replanting. These are costly investments for private owners if they only looked at short term optimization of returns. However, in the long term (approximately 80 years) the profitability of the forest is improved as this sound asset management results in more wood for the final clear cut. EO leads to improved yields in the forest sector, by monitoring forest owners compliance to sustainable practices.", "attrs": null, "subkind": "paragraph", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "f5d2ba7b-5c1e-4180-9f4f-953c9d481218", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.03, "w": 0.18, "x": 0.06, "y": 0.09 }, "kind": "title", "text": "FORESTRY", "attrs": null, "subkind": "headline", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "48273979-c4f3-4335-b9cd-5162353fc778", "frameworkName": null, "frameworkSlug": null }, { "bbox": { "h": 0.03, "w": 0.78, "x": 0.06, "y": 0.13 }, "kind": "title", "text": "DRIVERS AND CHALLENGES FOR THE UPTAKE OF EO BY FOREST MANAGERS", "attrs": null, "subkind": "subtitle", "toolName": null, "toolSlug": null, "confidence": null, "componentId": "01bb548a-fb95-4aa7-a276-e2b03f7685c7", "frameworkName": null, "frameworkSlug": null } ], "metrics": [], "tools": [ { "name": "List presentation", "slug": "list-presentation", "agent": null, "layer": "slide", "matchId": "26fd4fc7-307f-46c4-b4bc-95e9406c2901", "evidence": "list/bullet: CHALLENGE 1: For some parameters, the methodologies for producing maps at scale have not been developed or validated", "confidence": 0.5 } ], "frameworks": [], "arcBeats": [ { "to": 164, "from": 21, "beatId": "b6675433-9953-41fa-b682-77766fc26089", "arcName": "Monroe's Motivated Sequence", "arcSlug": "monroes-sequence", "beatName": "Action", "beatSlug": "monroes-sequence-action", "evidence": "Industry-specific benefits, case studies, and conclusions", "position": 4, "confidence": 0.8, "parentBeatName": "Resolution", "parentBeatSlug": "resolution" } ], "loops": [], "imagePathAlt": null, "thumbSrc": null, "thumbSrcAlt": null, "locked": true }