The process of cartographic generalization is used to produce a harmonized picture at different scales of geospatial features.

噸他處理製圖綜合的用於產生在地理空間特徵的不同尺度一個統一圖片。

Generalization is an essential part of any cartographic production process and is, generally, a process that is still at least partly, manually driven. The move to

泛化是任何製圖生產過程中必不可少的部分，並且通常是至少部分仍由手動驅動的過程。 通過開發用於管理“與比例有關的”功能的功能，向ENC製圖的轉變使不同比例的圖表建立具有一定程度的自動化。

Database driven production systems, able to store the data for multiple charts in a single database instance, are then able to reuse features for different charts reducing the need for manual intervention.

由資料庫驅動的生產系統能夠在一個數據庫例項中儲存多個圖表的資料，然後能夠為不同的圖表重用功能，從而減少了人工干預的需求。

The issue remains though, that many features require extensive manual editing in order to produce generalized products which are acceptable to both cartographer and end-user.

但是，問題仍然存在，許多功能需要大量的手動編輯才能生成製圖師和終端使用者都可以接受的通用產品。

There is, therefore, a large potential to increase the efficiency of any data production system by automating generalization into the chart production process as far as possible.

因此，通過儘可能地將歸納自動化到圖表生成過程中，有很大的潛力提高任何資料生成系統的效率。

From a generalization point of view, bathymetric content is probably the most challenging as it is both one of the most (if not, THE most) important and safety-critical elements of the navigational chart and also one of the most complex and subtle in the practice of marine cartography.

從一般的角度來看，測深內容可能是最具挑戰性的內容，因為它既是導航圖中最重要(如果不是，最重要)且對安全性至關重要的元素之一，也是導航圖中最複雜，最微妙的元素之一。海洋製圖的實踐。

Bathymetric content is composed primarily of the following features and attributes:

測深內容主要由以下功能和屬性組成：

1. Individual soundings along with attribution containing various quality parameters

   包含不同質量引數的單個聲音以及歸因

2. Areas delimiting specified ranges of depths

   劃定指定深度範圍的區域

3. Contours denoting lines of equal-depth (in practice these are the perimeters of the depth area features in the previous point)

   等高線表示等深線(實際上，這是上一點中深度區域特徵的周長)

4. Value of sounding attributes on individual features, rocks, wrecks, etc
   各個要素，岩石，殘骸等上的測深屬性的價值

The collection, processing, and compilation of bathymetry data are the most labor-intensive and safety-critical of all phases of marine cartography and the resultant surface of depth areas and sounding arrays forms the essential surface for navigation which is presented to the chart’s end user.

航海圖資料的收集，處理和彙編是海洋製圖各個階段中勞動強度最大，最安全的關鍵 ，深度區域和測深陣列的結果表面構成了導航的基本表面，並向海圖的終端使用者呈現。

Bathymetric source data is obtained from the raw, dense, survey information gathered by sensors from survey vessels and aircraft. Raw survey data is cleaned, validated, and harmonized into a large, dense set of candidate source depths soundings.

測深源資料是從感測器，調查船和飛機收集的原始，密集的調查資訊中獲得的。 原始的調查資料將被清理，驗證並統一為大量密集的候選源深度測深。

From these surfaces, contours and a large set of candidate spot soundings are derived. Features are selected from the available source and sub-processes such as thinning, critical sounding designation and deconfliction with existing sources all take place and are and used to compile the resultant chart, whether by new edition (replacement) or update. From a generalization point of view, the selection of “appropriate” depth vectors from the available source, and the adaptation of large scale line-work are the core tasks.

從這些表面可以得出輪廓和大量的候選點測深。 從可用的源中選擇功能，然後進行子流程(例如細化，關鍵的聲音指定以及與現有源的衝突)，無論是通過新版本(替換)還是更新，這些功能都將用於編譯結果圖表。 從一般的角度來看，從可用資源中選擇“適當的”深度向量，以及適應大規模的線路工作是核心任務。

This selection must be clear, consistent, and safe for the end-user of the chart.

對於圖表的終端使用者，此選擇必須清晰，一致且安全。

Generalization in terms of marine charts is often used to define cartographic generalization, the stage of viewing the underlying geospatial data. In this model, the representation of the chart features is transformed via a set of fixed generalization operators into viewable representations, the chart symbols. In 1988 McMaster and Shea defined a conceptual model of generalization grouped into:

在海圖，以g eneralization通常用來定義製圖綜合，檢視基礎地理空間資料的階段。 在此模型中，統計圖特徵的表示通過一組固定的歸納運算子轉換為可視表示(統計圖符號)。 1988年，McMaster和Shea定義了概化的概念模型，歸納為 ：

1. Why — the basis for understanding why generalization takes place

1. 為什麼-理解為什麼進行概括的基礎

2. When — establishing when particular features require generalization

2.何時—確定何時需要概括特定功能

3. How — the exact process of generalization, such as simplification, aggregation, displacement, and elimination.

3.如何—概括的確切過程，例如簡化，聚合，置換和消除。

The process of generalization of marine geospatial data making up charts and ENC data can be viewed in this light and used to then define where in the compilation process Artificial Intelligence and Machine Learning (AI/ML) can make a positive contribution, for example, should AI/ML define “when” a sounding, contour or obstruction is generalized or “how” it is generalized in terms of its representation in each chart?

可以從這個角度檢視組成圖表和ENC資料的海洋地理空間資料的一般化過程，然後將其用於定義在編譯過程中人工智慧和機器學習(AI / ML)可以在哪些方面做出積極貢獻，例如， AI / ML定義了“何時”對聲音，輪廓或障礙物進行概括，或者“如何”根據每個圖表中的表示進行概括？

The primary difficulty of generalizing depths is the subjective nature of what constitutes a “safe” and informative selection of depth information for use by the end-user. According to IHO S-4, a generalization of depth information should result in a blend of an informative, shoal-biased, and context-sensitive selection of depths at a smaller scale. There are two critical tests referenced in IHO S-4 (B-410) which are crucial to any consideration of the quality of a generalization process, the triangle test and edge test which define a shoal-biased triangulation of soundings (and, potentially, depth areas and other features with bathymetric content) which the mariner can use to interpolate depths in relation to their individual vessel draught and safety margins.

歸納深度的主要困難是構成“安全”和內容豐富的深度資訊供終端使用者使用的主觀性。 根據IHO S-4 ，深度資訊的一般化應導致在更小範圍內混合深度資訊，淺灘偏向和上下文相關的深度選擇。 在IHO S-4(B-410)中引用了兩個關鍵測試，這些測試對於綜合處理質量的任何考慮都至關重要，即三角形測試和邊緣測試，它們定義了測深的三角偏測(並且可能深度區域和具有測深內容的其他特徵)，海員可以使用這些深度來插補相對於其個人船隻吃水深度和安全裕度的深度。

The IHO mechanism described in IHO S-4 assures the mariner safe passage between soundings by eliminating shoal source soundings between, or on the edge of geodesics joining adjacent soundings (recent work by the University of New Hampshire expanded on these tests’ implementation heavily by adding linear contours and some contextual features to the test’s domain — this does not change the test in principle but enhances its applicability). The following image shows an example triangulation of multiple usage band data together with depth contours and illustrates some of the generalization techniques and the constraints placed upon them by the triangle/edge tests. In it, coastal and approach soundings are in blue and red and the triangulation shows the consistent validation of the triangle test in the soundings selected for inclusion in the generalized coastal chart. The green depth contours are generalized from the approach chart and show how the simplified geometry harmonizes with the selected soundings and simplify the detail of the approach ENC data.

IHO S-4中描述的IHO機制通過消除與相鄰測深點相連的大地測量學之間或之間的淺灘源測深，確保了測深之間的航海安全通道( 新罕布什爾大學的最新工作通過增加以下內容極大地擴充套件了這些測試的實現)線性輪廓和測試領域的某些上下文特徵-原則上不會改變測試，但會增強其適用性 。 下圖顯示了多個使用帶資料與深度輪廓的三角剖分示例，並說明了一些泛化技術以及三角形/邊緣測試對它們施加的約束。 在該圖中，沿海和進近測深為藍色和紅色，並且三角剖分顯示了在選定要包含在廣義沿海圖表中的測深中對三角檢驗的一致驗證。 綠色進深輪廓線是從進近圖概括而來的，顯示出簡化的幾何形狀如何與選定的測深相協調，並簡化進近ENC資料的細節。

The other points in S-4 (and which may be enhanced/reflected in individual member state guidance) are the requirement to take into account the density of soundings in respect of seabed morphology and proximity to other contextual features such as hazards and shorelines, all within the constraints of feature/vertex density to reduce the clutter of the resulting chart.

S-4中的其他要點(可能會在各個成員國的指南中得到增強/體現)是要求考慮到海床形態以及與其他背景特徵(如危險和海岸線)的接近程度，測深的密度。在要素/頂點密度的約束範圍內，以減少結果圖表的混亂情況。

The interconnected nature of bathymetric elements can be seen in the following diagram which highlights just two of the key features making up the complex interrelationships in a navigational chart:

下圖顯示了測深元素的相互聯絡的性質，該圖中僅著重了構成導航圖中複雜相互關係的兩個關鍵特徵：

Generalization of depth is not dealt with exhaustively in IHO S-4, nor in other cartographic guidance within the existing standards base which leaves member state producers to develop their own detailed guidance and styles. Indeed many ENC datasets are digitized from historical paper charts and therefore retain the generalization styles and features in place for many years.

深度G的eneralization不處理詳盡IHO S-4 ，也沒有在現有標準的基礎葉成員國生產商制定自己的詳細指導和風格，其內的其他製圖指導。 實際上，許多ENC資料集都是從歷史紙質圖表中數字化的，因此保留了多年的概括樣式和功能。

Although, as previously stated, a large body of knowledge exists inland mapping in respect of generalization, little has been written specifically on the topic of marine cartographic generalization, nor of the bathymetric element of that process. Measurements like Topfer’s ratio equating feature density at different resolutions are useful and processes such as the Douglas-Peucker algorithm for smoothing linear features require extensive adaptation for use within the safety-critical processes in marine charting.

儘管如前所述，在內陸製圖方面存在大量的知識，但是關於海洋製圖泛化或該過程的測深要素的論述很少。 諸如Topfer比率等於不同解析度下的特徵密度之類的測量非常有用，並且諸如Douglas-Peucker演算法(用於平滑線性特徵)之類的過程需要廣泛的適應性，才能在海洋製圖的安全關鍵過程中使用。

So, the difficulties of automating generalization (and specifically bathymetric generalization) have traditionally been :

因此，自動進行概括(尤其是測深綜合)的困難傳統上是：

1. Some aspects of generalization can be highly subjective and resist rigid rules-based formulation. Within marine cartography decluttering of charts is of prime importance and aesthetic judgments have played a strong role in the creation of high-quality products for many years.

1.概括的某些方面可能是高度主觀的，並且會抵制基於規則的嚴格表述。 在海洋製圖學中，圖表的雜亂化是至關重要的，多年來，美學判斷在建立高質量產品中發揮了重要作用。

2. Marine cartography places strict safety-related rulesets around generalization due to the extraordinary amount of legal liability inherent in the product. Some examples of this are the generalization of obstructions and hazards relevant to IMO functions in the ECDIS and generalization of coastline/depth areas to ensure safety margins are maintained and reproduced. This requirement impacts on the ability to reuse many terrestrial mapping generalization techniques. Bathymetric data, shoals, obstructions, and contours are features on which navigational decisions are made and where mistakes and omissions can result in profound safety issues, carrying large liabilities for producing nations.

2.由於產品固有的大量法律責任，航海製圖圍繞泛化制定了嚴格的安全相關規則集。 例如，在ECDIS中推廣與IMO功能有關的障礙物和危害，並推廣海岸線/深度地區以確保維持和再現安全裕度。 此要求影響重用許多地面對映概括技術的能力。 水深資料，淺灘，障礙物和等高線是進行航行決策的地方，錯誤和遺漏會導致嚴重的安全問題，對生產國承擔重大責任。

3. How new / changed information is harmonized with existing information is a characteristic specific to marine cartography because of the large amount of uncertainty involved and the cost of acquisition of raw data.

3.由於涉及的大量不確定性和獲取原始資料的成本，如何將新的/更改的資訊與現有資訊相協調是海洋製圖的一個特定特徵。

4. There is an implicit spatial and semantic interaction between features in a chart. So, for instance, lateral buoyage close to shore should not be absorbed by the seaward generalization of coastline (via its underlying depth areas and land areas). Bathymetric generalization must take into account seabed morphology when determining the appropriate density of included soundings, it must also take into account proximity to the coastline, significant hazards, and navigational context (e.g. when determining critical soundings in confined approaches). At all times the topology and relationships between features in the datasets need to be maintained.

4.圖表中的要素之間存在隱式的空間和語義互動。 因此，例如，靠近海岸的橫向浮標不應被海岸線向海的泛濫所吸收(通過其下伏的深度區域和陸地區域)。 在確定包括的測深的適當密度時，測深綜合必須考慮海床的形態，還必須考慮到海岸線的接近性，重大危害和航行環境(例如，在密閉進近中確定關鍵測深時)。 任何時候都需要維護資料集中的拓撲和要素之間的關係。

5. The selection of appropriate bathymetric data from the survey for use in multiple scales must be consistent with neighboring charts and meet the concrete tests defined in procedures (and IHO standards).

5.從勘測中選擇合適的測深資料以用於多種尺度，必須與附近的海圖一致，並符合程式( 和IHO標準 )中定義的具體測試。

ENC, the primary cartographic product under SOLAS refines the concept of charts somewhat. ENC is a database of geospatial features used to render a chart image on an ECDIS dependent on a number of user-defined parameters according to fixed international standards for content and portrayal. ENC also has a very rigid topological structure and tight validation rules which only permit certain geospatial relationships and feature/attribute combinations. Real-world features are encoded from a number of sources and expressed via the S-57 object/attribute catalogs using a style derived mainly from the IHO Use of the Object Catalogue. This language of features and attributes is symbolized by an ECDIS for display but also for alarm and indication behavior, the safety-critical functions of the navigation system. Bathymetric data is the most important feature class within the chart with many of the IMO mandated safety-critical functions determined from features with bathymetric content.

ENC是SOLAS下的主要製圖產品，在某種程度上完善了圖表的概念。 ENC是一個地理空間資料庫，用於根據固定的內容和刻畫國際標準，根據許多使用者定義的引數在ECDIS上繪製圖表影象。 ENC還具有非常嚴格的拓撲結構和嚴格的驗證規則，僅允許某些地理空間關係和要素/屬性組合。 現實世界的功能從許多來源進行編碼，並通過S-57物件/屬性目錄使用主要源自IHO使用物件目錄的樣式來表示。 功能和屬性的這種語言由ECDIS表示，用於顯示，但也用於警報和指示行為，即導航系統的安全關鍵功能。 測深資料是圖表中最重要的要素類，其中許多IMO強制性的安全關鍵功能是根據具有測深內容的要素確定的。

From an ENC perspective, bathymetric data is held within

從ENC角度來看，測深資料儲存在

· Sounding Arrays (SOUNDG)

·探測陣列( SOUNDG )

· Depth Areas (DEPARE) (+Dredged Areas DRGARE) with (DRVAL1/DRVAL2) attributes. Associated depth contours (DEPCNT) are linked with DEPARE features. Additionally routing measures such as deepwater routes and fairways have depth attribution within them which should be considered.

·具有( DRVAL1 / DRVAL2 )屬性的深度區域( DEPARE )(+挖泥區域DRGARE)。 關聯的深度輪廓(DEPCNT)與DEPARE要素連結。 另外，深水路線和航道等路線測量方法在其中應具有深度歸因。

· VALSOU attributes on hazards, subsurface obstructions, and wrecks.

·有關危險，地下障礙物和沉船的VALSOU屬性。

All these features make up the bathymetric picture of the ENC and are relevant to generalization processes. Bathymetric cartographic generalization, therefore, in ENC terms needs to preserve the safety-critical nature of certain features as well as delivering a de-cluttered and intuitive presentation of the bathymetric features at all scales. For presentation at smaller scales, therefore, a harmonized approach across all relevant feature types is called for.

所有這些功能構成了ENC的測深圖，並且與泛化過程有關。 因此，以ENC術語表示，測深製圖一般化需要保留某些要素的安全性至關緊要的性質，並以各種尺度提供整潔而直觀的測深要素表示。 因此，為了以較小的比例顯示，需要在所有相關要素型別上採用統一的方法。

There is much work on automated cartographic generalization already established within the terrestrial mapping domain, mainly concerned with the definition of symbology generalization operators, rule-based transformations of feature representation, and their integration together. Symbology generalization for ENC however is restricted to the S-52 visual library (so, for instance, line weights cannot be adjusted, nor colors).

Ť這裡是自動化製圖綜合多工作的地面測繪領域內已經建立，主要關心的符號泛化運營商，特徵表示的基於規則的轉變的定義，以及它們整合到一起。 但是，ENC的符號系統化僅限於S-52視覺庫(因此，例如，線寬不能調整，顏色也不能調整)。

This places a tight vocabulary around what generalization processes are definable and how they should be implemented and suggests an approach based on the vector content of the features and attributes rather than from their appearance on screen

這圍繞可定義的概化過程以及應如何實施這些概論，並提出了一種基於特徵和屬性的向量內容而不是根據其在螢幕上的外觀的方法。

The proposed system platform is shown in the following diagram:

下圖顯示了建議的系統平臺：

In the proposed system the following steps take place:

在建議的系統中，執行以下步驟：

1. The input training ENC data is split into its component features. Other input data that may be relevant, such as source bathymetric surfaces and soundings and chart metadata will be digitized into the schema within the system. At this point, an automated process determines the extent and content of the existing generalization within the input cells. This is used to form the generalization labels according to the model configuration.

1.輸入的培訓ENC資料分為其組成特徵。 其他可能相關的輸入資料，例如源測深曲面和測深以及圖表元資料，將被數字化到系統內的模式中。 此時，自動化過程將確定輸入像元中現有概括的程度和內容。 這用於根據模型配置形成概括標籤。

2. Features that are linked (for instance coastline (COALNE) which is coincident with Land Areas and 0m Depth Areas) are represented as single instances with combined attribution to maintain their validity (e.g. to avoid a depth area being generalized and not matching the appropriate depth contour). From a generalization perspective, it is the underlying skin of the earth features and points soundings/bathymetric attribution which require generalization, not the coastline features.

2.連結的要素(例如，與陸地區域和0m深度區域重合的海岸線(COALNE))被表示為具有合併屬性的單個例項，以保持其有效性(例如，避免深度區域被概括且與適當的區域不匹配)深度輪廓)。 從一般化的角度來看，需要綜合性的是地球要素和點測深/測深屬性的潛在表皮，而不是海岸線特徵。

3. A model (selected from a number of candidates) is trained, tuned, and used to predict generalized forms of the input features. These are formed from the predictions by using values generated by the models (i.e. selections of soundings from source or inclusion/exclusion instructions based on chart context (e.g. controlling depths)) and parameters that can drive line smoothing algorithms.

3.對模型(從許多候選項中選擇)進行訓練，調整並用於預測輸入特徵的廣義形式。 這些是通過使用模型生成的值(即，基於圖表上下文(例如，控制深度)從源或包含/排除指令中選擇測深)和可以驅動線平滑演算法的引數從預測中形成的。

4. A subset of the component features is used to test the model predictions.

4.元件特徵的子集用於測試模型預測。

5. The features are re-assembled into a candidate generalized ENC.

5.將特徵重新組合成候選的通用ENC。

6. This ENC can then be evaluated against

6.然後可以根據該ENC進行評估

a. Validation rules, IHO S-58, and IHO S-57 UOC.

一個。 驗證規則 IHO S-58 和IHO S-57 UOC。

b. IHO S-4 triangle/edge test, national policy tests.

b。 IHO S-4 三角形/邊緣測試，國家政策測試。

c. Feature density and compilation scale assessments

C。 特徵密度和編譯比例評估

d. Safety criteria, safety-critical features as defined under IMO SOLAS

d。 安全標準，IMO SOLAS定義的關鍵安全功能

e. The cartographic judgment of the effectiveness of the generalization

e。 製圖判斷的有效性

7. Feedback from the outputs is used to tune the model parameters and modify the feature data designs and labels.

7.來自輸出的反饋用於調整模型引數並修改特徵資料設計和標籤。

As noted in this section, a loss function defining a measure of generalization based on the many algorithms specific to bathymetric data and attribution and factors relevant to bathymetric generalization is used by the system to progressively improve the generalization processes used to form the results.

如本節所述，系統會使用損失函式，基於特定於測深資料和歸因的許多演算法以及與測深泛化相關的因素來定義泛化度量，以逐步改善用於形成結果的泛化過程。

It is crucial to ensure as large a training dataset as possible is available to the system — in bathymetry terms, this should also contain the processed source data from which soundings/contours are derived and which form the decision space for the majority of the soundings/contours.

確保系統可以使用盡可能大的訓練資料集至關重要-以測深法而言，它還應包含處理後的源資料，從中得出測深/等高線，並形成大多數測深/輪廓。

The success of such a system will be heavily dependent on the availability of a critical mass of representative training data at all scales and the generalization processes defining the input ENC cells.

這種系統的成功將在很大程度上取決於在所有規模上是否有關鍵數量的代表性訓練資料，以及定義輸入ENC單元的概括過程。

This pipeline technology has the following benefits:

這種管道技術具有以下優點：

1. It is platform neutral and uses only open source components, Java, Python, PostgreSQL/PostGIS and can be adapted to other spatial database solutions.

1.它是平臺無關的，僅使用Java，Python，PostgreSQL / PostGIS等開源元件，並且可以適應其他空間資料庫解決方案。

2. It allows any AI/ML model to be interfaced with its open schema without any proprietary restrictions whatsoever. This allows for maximum flexibility in choice, tuning, and configuration of the machine learning model, crucial given the number and variation available to the project.

2.它允許任何AI / ML模型與其開放式架構介面，而沒有任何專有限制。 這就給機器學習模型的選擇，調整和配置提供了最大的靈活性，這在給定專案可用數量和變化的情況下至關重要。

3. The open architecture allows for multiple algorithms to be engineered to generate line features (and associated polygons). This means that depth contour/depth area generalization can be accomplished by using machine learning to learn “parameters” such as offsets from existing contours, inclusion/exclusion of shoals, and identification of critical depths, and then the actual algorithms generating the features can be deterministic rather than defined by the machine learning model.

3.開放式體系結構允許設計多種演算法以生成線要素(和關聯的多邊形)。 這意味著深度輪廓/深度區域的概括可以通過使用機器學習來學習“引數”，例如從現有輪廓偏移，淺灘的包含/排除以及關鍵深度的識別，然後生成特徵的實際演算法可以完成。確定性的，而不是由機器學習模型定義的。

4. The system would not be limited to feature generalization only. Assessment of for example SCAMIN application (e.g. selection of SCAMIN values on safety-critical soundings) and safety classification of changes to ENCs would be alternative use cases for such an AI/ML adapted system.

4.該系統將不僅限於特徵概括。 對於這樣的AI / ML適應系統，評估SCAMIN應用(例如，選擇對安全至關重要的SCAMIN值)以及對ENC進行更改的安全分類將是替代用例。

5. These components also allow “hybrid” ENCs to be created where some elements are generalized whereas others are untouched. This has the advantage of allowing the project to progress iteratively with more complex generalization included when simple cases are initially proven.

5.這些元件還允許在某些元素被概括而其他元素未被修改的情況下建立“混合” ENC。 這樣做的好處是，當最初證明簡單的情況時，專案就可以以更復雜的概括來迭代進行。

6. The Nautilus process preserves the relationships between the features and their topology so that a standards conformant ENC can be built for full validation/inspection after the prediction processes have run. The system allows for training validation to take place for the classification process to complete.

6. Nautilus流程保留了要素及其拓撲之間的關係，因此可以在執行預測流程後構建符合標準的ENC，以進行全面的驗證/檢查。 該系統允許進行培訓驗證，以完成分類過程。

7. The maximum flexibility of the input data and its labels is achievable.

7.可以實現輸入資料及其標籤的最大靈活性。