著：（意）丹尼艾勒·坎納特拉 譯：李佳琪 校：蔡佳秀

在快速城市化地區(qū)，理解土地覆蓋和土地利用變化的內(nèi)涵是評(píng)估空間政策影響、應(yīng)對(duì)自然災(zāi)害風(fēng)險(xiǎn)和氣候變化的負(fù)面影響、制定實(shí)現(xiàn)可持續(xù)城市發(fā)展戰(zhàn)略的關(guān)鍵任務(wù)，特別是受快速城市化和氣候變化影響的地區(qū)，比如城市三角洲地區(qū)需要采取連貫的、有根據(jù)的、系統(tǒng)性的適應(yīng)和緩解行動(dòng)。氣候變化與土地覆蓋情況存在相互影響的關(guān)系。土地利用/土地覆蓋演變（land use/land cover change, LULC）對(duì)全球氣候的影響體現(xiàn)在大氣中CO2的排放上，而氣候變化影響土地利用和土地管理戰(zhàn)略，需要采取緩解和適應(yīng)對(duì)策，以應(yīng)對(duì)氣候變化的負(fù)面影響[1]。此外，土地覆蓋演變和土地相關(guān)建設(shè)是全球氣候變化的主要因素之一，這改變了土地利用率和可利用水資源量、生態(tài)系統(tǒng)服務(wù)和水文過(guò)程[2]。人類活動(dòng)造成的土地侵蝕可能對(duì)水和土壤等重要自然資源的完整性和質(zhì)量產(chǎn)生重大影響。城市化和人類活動(dòng)可以影響生態(tài)系統(tǒng)的分布及相關(guān)的能量和物質(zhì)流動(dòng)，從而影響其生態(tài)容量。土地利用實(shí)踐與氣候變化在決定流域水文性能的質(zhì)量方面共同發(fā)揮著關(guān)鍵作用[3]。在三角洲地區(qū)，洪水易發(fā)區(qū)域的城市化增加了人類生命財(cái)產(chǎn)遭受自然災(zāi)害的風(fēng)險(xiǎn)，由此導(dǎo)致不透水表面不受控制地增加，削弱了洪泛區(qū)水滲入土壤的能力[4]，同時(shí)改變了徑流方向并增大了峰值流量。土地利用也會(huì)影響城市水分蒸發(fā)、地下徑流和水流排放等基本過(guò)程[5]，從而影響城市水循環(huán)的正常進(jìn)行。這些變化對(duì)城市系統(tǒng)抵御洪水、山體滑坡、風(fēng)暴和干旱等的韌性產(chǎn)生了直接影響[6]，因?yàn)槌鞘兴畡?wù)工程基礎(chǔ)設(shè)施并不是為了應(yīng)對(duì)降水模式改變?cè)斐傻膲毫υ鲩L(zhǎng)而設(shè)計(jì)的。土地利用的變化對(duì)水量和水質(zhì)有負(fù)面影響。作物需要的高營(yíng)養(yǎng)素增加，并且作物的種植面積擴(kuò)大，這將導(dǎo)致地表水中沉積物、硝酸鹽和磷的增加[7-8]。農(nóng)業(yè)擴(kuò)張、工業(yè)活動(dòng)和城市化，將進(jìn)一步消耗地下水供應(yīng)，加劇水的供需失衡[9]。

因此，對(duì)土地覆蓋進(jìn)行歷時(shí)性圖析（mapping）是從空間和定量角度研究城市系統(tǒng)演變內(nèi)涵的重要工作。圖析作為一種方法，是對(duì)正處于城市化進(jìn)程的三角洲地區(qū)的景觀進(jìn)行系統(tǒng)研究的有力工具[10]。使用基于地理信息系統(tǒng)（geographic information systems, GIS）的空間分析方法和工具，可以通過(guò)參考土地覆蓋地圖的指標(biāo)，對(duì)有關(guān)城市景觀的構(gòu)成進(jìn)行量化。比較一個(gè)區(qū)域內(nèi)城市景觀格局的演變，可以從時(shí)間維度更深刻地理解空間演進(jìn)過(guò)程中的相似性與差異性。此外，它有助于分析土地利用政策隨著時(shí)間的推移對(duì)該地區(qū)的影響，從而制定旨在實(shí)現(xiàn)城市可持續(xù)發(fā)展的規(guī)劃。

此類分析可利用全球各個(gè)國(guó)家不同尺度和不同空間分辨率的LULC數(shù)據(jù)。LULC數(shù)據(jù)是基于遙感的重要資源，它們提供了全球和區(qū)域植被覆蓋的信息，被廣泛用于各種大規(guī)模氣候、生態(tài)和水文模型[11]。

本研究以世界上城市化速度最快的三角洲地區(qū)——珠江三角洲（簡(jiǎn)稱珠三角）①為例進(jìn)行研究。在以珠三角LULC為研究對(duì)象的領(lǐng)域中，已經(jīng)開展了多項(xiàng)針對(duì)不同研究目的的項(xiàng)目。例如，Seto等[12]使用Landsat TM衛(wèi)星遙感影像，結(jié)合社會(huì)經(jīng)濟(jì)因素，對(duì)珠江三角洲部分地區(qū)隨時(shí)間演變的土地利用情況進(jìn)行分析。一些學(xué)者專注于預(yù)測(cè)該區(qū)域未來(lái)的土地利用情況[13]，將規(guī)劃政策納入土地利用模擬模型進(jìn)行預(yù)測(cè)[14]，或嘗試探尋不同LULC狀況形成的因素[15]。其他研究側(cè)重于量化LULC對(duì)生態(tài)系統(tǒng)服務(wù)的影響[16-17]。這些分析關(guān)注整個(gè)珠三角地區(qū)，研究時(shí)間區(qū)間3～10年不等。然而，這些研究忽略了珠三角不同地區(qū)的土地利用情況演化和變化強(qiáng)度的差異性。

本研究的目的有2個(gè)方面。一方面，以1年作為時(shí)間顆粒度研究珠三角各城市土地覆蓋演變的不同時(shí)空格局，以了解土地利用政策對(duì)該地區(qū)的空間影響。另一方面，本研究提出了一種完全基于開源數(shù)據(jù)的區(qū)域尺度土地覆蓋時(shí)空演變的研究方法。該方法利用歐洲航天局氣候變化倡議（European Space Agency Land Cover Climate Change Initiative Project, ESA CCI）土地覆蓋圖②和美國(guó)地質(zhì)勘探局（United States Geological Survey, USGS）高程地圖作為基礎(chǔ)數(shù)據(jù)，明確了低海拔海岸帶（low elevation coastal zone, LECZ）的年度土地覆蓋變化強(qiáng)度，并與該地區(qū)其他區(qū)域進(jìn)行比較。LECZ特別容易受到海平面上升、風(fēng)暴潮、濕地退化、地面沉降和洪水淹沒的影響，十分脆弱。ESA CCI數(shù)據(jù)集涵蓋1992—2015年間以年為單位的數(shù)據(jù)。

1 材料與方法

1.1 珠江三角洲

珠江三角洲位于中國(guó)東南部（圖1）。從地貌角度來(lái)看，珠三角是一個(gè)沖積平原，由西江、北江和東江3條主要支流組成。這3條河流在三角洲的中部匯合，然后流入中國(guó)南海。

1 珠江三角洲城市群Pearl River Delta cities

珠三角是由廣州、東莞、佛山、惠州、江門、深圳、肇慶、中山、珠海9個(gè)地級(jí)市和香港、澳門2個(gè)特別行政區(qū)組成的密集城市網(wǎng)絡(luò)，總面積超過(guò)5.5萬(wàn)km2（表1）。

表1 珠江三角洲的城市（按面積排序）Tab.1 The cities of the Pearl River Delta (PRD), ranked by area

1979年改革開放后，珠江三角洲城市群迅速成為中國(guó)乃至世界最具經(jīng)濟(jì)活力的地區(qū)之一。在經(jīng)濟(jì)改革實(shí)施不到10年的時(shí)間里，珠江三角洲的GDP總量占全國(guó)的7.35%[18]。經(jīng)濟(jì)發(fā)展良好，2016年GDP總量占全國(guó)的9.1%[19]。

在經(jīng)濟(jì)增長(zhǎng)的同時(shí)，該地區(qū)也經(jīng)歷了巨大的人口增長(zhǎng)，在2014年超過(guò)東京成為世界上面積和人口最大的城市圈[20]，在2016年人口已近7 200萬(wàn)。

經(jīng)濟(jì)快速發(fā)展與空間結(jié)構(gòu)的劇烈轉(zhuǎn)變同時(shí)發(fā)生，工業(yè)生產(chǎn)大幅增加，農(nóng)業(yè)生產(chǎn)份額急劇下降，直到如今城市化進(jìn)程才開始放緩。

快速城市化、高強(qiáng)度的人類活動(dòng)以及氣候變化帶來(lái)的影響，正在破壞珠三角地區(qū)的微妙平衡，威脅著其可持續(xù)發(fā)展，使其面臨多重挑戰(zhàn)。

一方面，洪水多發(fā)地帶的城市化問(wèn)題、海平面上升以及極端臺(tái)風(fēng)和風(fēng)暴導(dǎo)致珠三角地區(qū)面臨的洪水風(fēng)險(xiǎn)越來(lái)越大。另一方面，灰色基礎(chǔ)設(shè)施的無(wú)序擴(kuò)張會(huì)導(dǎo)致自然系統(tǒng)的破碎化，以及隨之而來(lái)的相關(guān)生態(tài)系統(tǒng)服務(wù)的崩塌[21]。農(nóng)業(yè)和工業(yè)活動(dòng)對(duì)水量和水質(zhì)也有負(fù)面影響，分別占需水量的33%和37%，并造成地表水系統(tǒng)的污染。事實(shí)上，在2015年，珠三角39%的河水被認(rèn)為是“不適合人類接觸的”[22]。

珠三角的城市化進(jìn)程在時(shí)間和空間上是不均衡的。1978年以農(nóng)業(yè)發(fā)展為主的階段結(jié)束后，珠三角的發(fā)展又經(jīng)歷了3個(gè)階段[23]：工業(yè)化階段（1978—2000年）；城市化和大都市化階段（2000—2008年）；城市化背景下的農(nóng)村快速轉(zhuǎn)型階段（2008年至今）。每個(gè)階段的政策不同，這些政策隨著時(shí)間推移對(duì)土地覆蓋產(chǎn)生了不同的影響。此外，城市化最密集的地區(qū)主要分布在珠三角東岸的軸線上，從廣州到香港，途經(jīng)東莞和深圳。相反，珠三角西岸相對(duì)欠發(fā)達(dá)，除廣佛都市圈外，其他城市區(qū)域均散布在洪泛區(qū)。

1.2 數(shù)據(jù)和軟件

珠三角的土地覆蓋演變分析使用了覆蓋全球的開源數(shù)據(jù)集。使用開源數(shù)據(jù)主要基于2個(gè)原因：1）為了測(cè)試可用的免費(fèi)土地覆蓋數(shù)據(jù)在精細(xì)時(shí)間顆粒度上對(duì)區(qū)域尺度土地覆蓋演變分析中的潛力；2）為這種方法在全球其他三角洲地區(qū)應(yīng)用的普適性奠定基礎(chǔ)。

因此，本研究使用了關(guān)于土地覆蓋、海拔和行政單位的3個(gè)主要數(shù)據(jù)集（表2）。

表2 用于土地覆蓋演變分析的源數(shù)據(jù)集Tab.2 Source datasets used in the analysis of land cover change

ESA CCI是在歐洲航天局氣候變化倡議土地覆蓋項(xiàng)目框架內(nèi)提供的全球開放土地覆蓋地圖。這些地圖覆蓋全球，空間分辨率為300 m，1992—2015年地圖每年更新一次。在光柵數(shù)據(jù)集中，每個(gè)像素值代表一個(gè)特定的土地覆蓋類型（表3）。

表3 歐洲航天局氣候變化倡議土地覆蓋類型Tab.3 ESA CCI Land Cover Classification

高程數(shù)據(jù)來(lái)自美國(guó)地質(zhì)勘探局負(fù)責(zé)的航天雷達(dá)地形勘測(cè)任務(wù)。航天飛機(jī)雷達(dá)地形勘測(cè)任務(wù)是美國(guó)國(guó)家航空航天局和美國(guó)國(guó)家圖像和測(cè)繪局的聯(lián)合項(xiàng)目，旨在繪制高水平的地球陸地表面的三維地圖。美國(guó)領(lǐng)土之外的可用數(shù)據(jù)包括3"數(shù)據(jù)，相當(dāng)于90 m。本研究使用了地理參考標(biāo)記圖像文件（georeferenced tagged image files, GeoTIFFs）。

最后，使用行政區(qū)劃邊界③來(lái)裁剪光柵數(shù)據(jù)集。通過(guò)R Studio軟件④對(duì)空間數(shù)據(jù)進(jìn)行重新投影、預(yù)處理和細(xì)化。最終輸出一個(gè)自動(dòng)執(zhí)行整個(gè)過(guò)程的腳本，該腳本之后會(huì)公開發(fā)表。

1.3 數(shù)據(jù)預(yù)處理

在開始分析之前，先將23張ESA CCI光柵圖和高程光柵圖裁剪到珠江三角洲地區(qū)的行政區(qū)劃邊界內(nèi)。裁剪后每個(gè)土地覆蓋地圖都由632 213個(gè)單元格組成，原始分辨率為300 m。隨后將這些單元轉(zhuǎn)換為地理坐標(biāo)，并與高程光柵圖疊加，以確定其中哪些位于LECZ。為了確保其參考性，本研究將LECZ定義為海平面以上、海拔10 m以下的連續(xù)的沿海地區(qū)[24]。這些地區(qū)特別容易受到海平面上升、強(qiáng)風(fēng)暴和氣候變化引發(fā)的其他災(zāi)害的影響，因此與其他高地勢(shì)地區(qū)相比更加脆弱。此外，這些地區(qū)的城市化是對(duì)沿海和三角洲生態(tài)系統(tǒng)的一種傷害，導(dǎo)致為城市住區(qū)提供保護(hù)功能的生態(tài)系統(tǒng)受到侵蝕，從而放大了與氣候相關(guān)的風(fēng)險(xiǎn)。最后，將生成的點(diǎn)網(wǎng)格與行政邊界圖層進(jìn)行空間疊加，以確定珠三角每個(gè)城市的LECZ包含多少單元（表4，圖2），以及1992—2015年每年的土地覆蓋類型和占比。

表4 不同城市海拔10 m以上/下的單元格數(shù)及占比Tab.4 Number and percentage of cells above or below 10 meters above sea level by city

從中可以清楚地看出：三角洲的西翼包含大量LECZ，尤其是中山市超過(guò)3/4的區(qū)域位于潛在的脆弱地區(qū)，其次是佛山市（67.70%）和珠海市（61.59%）；在珠三角東部，東莞是LECZ占比最高的城市（44.13%）。

1.4 土地覆蓋重新分類

裁剪土地覆蓋地圖后，對(duì)ESA CCI中的土地利用類型進(jìn)行重新分類和匯總。重新分類是考慮到與水有關(guān)的農(nóng)業(yè)和植被的廣泛存在，例如整個(gè)三角洲地區(qū)的基塘系統(tǒng)。因此，確定了7個(gè)土地覆蓋大類（表5）：森林、農(nóng)業(yè)（農(nóng)田）、農(nóng)業(yè)（灌溉）、森林（水）、草地、灌木林、稀疏植被、裸露地區(qū)、城市化地區(qū)和水。

表5 1992年和2015年用于分析的土地覆蓋大類和各小類的單元格數(shù)量Tab.5 Proposed Aggregated Land Cover Classes for the analysis and number of cells for each class in 1992 and 2015

1.5 時(shí)空矩陣

最后一步是在R Studio中開發(fā)程序來(lái)創(chuàng)建時(shí)空矩陣。在矩陣中，每一行對(duì)應(yīng)一個(gè)點(diǎn)，該點(diǎn)信息包括坐標(biāo)（經(jīng)度和緯度）、海拔（在重新分類中為海拔10 m以上/下）、城市、編碼1～7對(duì)應(yīng)的土地覆蓋大類（表5）。最終時(shí)空矩陣包括坐標(biāo)（顯示為x和y）、城市、海拔以及每年土地覆蓋值的信息，即 1992—2015 年按年份劃分的土地覆蓋類型（表6）。

表6 時(shí)空矩陣樣本Tab.6 Sample of the final spatio-temporal matrix

時(shí)空矩陣是土地覆蓋演變模式分析的起點(diǎn)。矩陣的相關(guān)數(shù)值是生成分析的關(guān)鍵?？v向數(shù)據(jù)展示了按年份劃分的每一類土地覆蓋類型，可按城市和海拔進(jìn)行分組。橫向數(shù)據(jù)可以逐年逐點(diǎn)對(duì)照土地覆蓋演變的強(qiáng)度和差異，或按城市、海拔高度匯總。

此外，這種結(jié)構(gòu)可以很容易地確定每個(gè)城市LECZ內(nèi)外最容易發(fā)生變化的土地覆蓋類型。下面將介紹其中一些分析結(jié)果。

2 分析結(jié)果

對(duì)比1992年和2015年的土地利用地圖，發(fā)現(xiàn)23年間整個(gè)珠三角地區(qū)的城市面積增加了3.5倍以上，從約2 050 km2增加到約6 380 km2（圖3）。而農(nóng)業(yè)地區(qū)（-3.71%）和其他地區(qū)（包括灌木林、草原和裸露地區(qū)，-2.97%）的土地覆蓋率有所下降。灌溉農(nóng)業(yè)面積也大幅減少，從11 252.91 km2減少到10 508.95 km2（-1.34%）。其他土地利用類型基本保持不變。水域面積減少（盡管幅度不大）可能表明，隨著時(shí)間推移一些水域已被填埋造陸。

3 珠江三角洲土地覆蓋總體變化（1992—2015年）Total land cover change in the PRD (years 1992-2015)

除了定量方面之外，土地覆蓋圖（圖4）清楚地顯示了該地區(qū)城市化的空間格局。對(duì)比1992年和2015年的2幅圖，可以看出珠三角的城市化進(jìn)程并不均衡，且可以確定3個(gè)主要演變趨勢(shì)。1）隨著時(shí)間推移，沿入?？跂|岸和廣港航線地區(qū)的建成區(qū)與海岸線相接，形成LECZ。東莞和深圳經(jīng)歷了名副其實(shí)的爆炸式城市化發(fā)展，只是受其領(lǐng)土地形的限制。2）西部軸線從廣州延伸到澳門，廣州和佛山相互融合，城區(qū)總體上發(fā)展更加集中。3）在三角洲地區(qū)更為邊緣的地帶，城市化主要發(fā)生在更集中的城市中心和發(fā)展主軸的沿線。

4 基于ESA CCI的珠江三角洲土地覆蓋地圖（1992—2015年）Land cover maps of the PRD, based on ESA CCI (years 1992-2015)

接下來(lái)對(duì)多年來(lái)土地覆蓋演變的程度和地點(diǎn)進(jìn)行分析。在圖5中，藍(lán)色條表示LECZ的變化，深灰色條表示海拔10 m以上區(qū)域的變化。包含所有土地覆蓋類型的土地覆蓋演變強(qiáng)度在空間上并不均勻。事實(shí)上，這種空間分布不均主要發(fā)生在LECZ，在三角洲內(nèi)有2個(gè)明顯不同的趨勢(shì)。1）從空間維度來(lái)看，深圳和東莞是中國(guó)農(nóng)用地轉(zhuǎn)變?yōu)槌鞘薪ǔ蓞^(qū)最顯著的城市，2001年和2002年分別達(dá)到16.6%和16.5%的峰值；位于珠三角中心地區(qū)的其他沿海城市緊隨其后；江門和肇慶排在后面。2）從時(shí)間維度來(lái)看，1995年是珠三角所有城市土地覆蓋演變首次均勻增加的一年。2001—2002年是演變?cè)龇畲蟮臅r(shí)期，尤其是在深圳和東莞。然而，從2005年開始可以觀察到下降的趨勢(shì)，尤其是在發(fā)展更成熟的城市。

5 各城市低海拔海岸帶的土地覆蓋逐年變化Land Cover Change in LECZ by year, per municipality

3 討論

對(duì)1992—2015年珠江三角洲土地覆蓋演變的分析結(jié)果表明，存在2個(gè)變化速度和強(qiáng)度明顯不同的區(qū)域：一個(gè)是位于珠三角核心區(qū)的沿海城市；另一個(gè)是珠三角外圍的城市，如江門和惠州。特別是在經(jīng)濟(jì)改革實(shí)施初期，位于入?？跂|側(cè)的深圳和東莞土地覆蓋演變速度較快。從圖5可以清楚地看到，這2個(gè)城市的土地覆蓋演變先行發(fā)生，而且強(qiáng)度較大，這主要是由城市化和農(nóng)村向工業(yè)區(qū)轉(zhuǎn)型而推動(dòng)的。其他在歷史上占重要地位的城市如廣州、香港，其土地覆蓋演變強(qiáng)度較低也更穩(wěn)定。

總的來(lái)說(shuō)，土地覆蓋演變的強(qiáng)度在很大程度上取決于發(fā)生在三角洲這一地區(qū)的城市化進(jìn)程。這主要是由于深圳被劃定為經(jīng)濟(jì)特區(qū)，特別是在經(jīng)濟(jì)改革實(shí)施后的前幾十年里，極大地促進(jìn)了城市化。

珠海經(jīng)濟(jì)特區(qū)的情況似乎有所不同。數(shù)據(jù)分析表明，在20世紀(jì)90年代初，土地覆蓋幾乎沒有變化，只在1995年達(dá)到峰值。這一趨勢(shì)在20世紀(jì)90年代末發(fā)生了變化，在2004年達(dá)到峰值，然后再次下降。在位于珠三角西軸的城市中，佛山和中山的土地利用發(fā)生了最顯著的變化。相反，珠江三角洲邊緣城市的土地覆蓋演變速度較慢。

通過(guò)比較各個(gè)發(fā)展階段中不同城市的變化趨勢(shì)，可以得出2個(gè)結(jié)論。

1）如上所述，有一些城市在各個(gè)階段率先轉(zhuǎn)型，還有一些城市緊隨其后。深圳和東莞是在三角洲工業(yè)化階段以及城市化和大都市化階段土地覆蓋演變迅速的城市。同樣，從2008年開始，這兩座城市的土地覆蓋演變速度放緩，屆時(shí)珠三角進(jìn)入對(duì)已城市化地區(qū)的再開發(fā)階段，并更加重視環(huán)境保護(hù)，這點(diǎn)在發(fā)展更成熟的城市中尤為突出。這一趨勢(shì)與珠江三角洲的西部地區(qū)略有不同，那里的土地覆蓋演變大體保持不變，尤其是在LECZ，以中山市尤為突出。

2）與其他地區(qū)相比，LECZ的土地覆蓋演變強(qiáng)度更高，同時(shí)也更脆弱。城市化的快速進(jìn)程導(dǎo)致人口、重要基礎(chǔ)設(shè)施、服務(wù)和經(jīng)濟(jì)資產(chǎn)的問(wèn)題迅速暴露。

我們需要在珠江三角洲的不同地區(qū)采取有針對(duì)性的措施，以遏制土地覆蓋演變的趨勢(shì)，從而減少與氣候相關(guān)的風(fēng)險(xiǎn)。在土地消耗減緩、致力于更新城市化地區(qū)的城市，應(yīng)優(yōu)先考慮實(shí)施適應(yīng)建筑環(huán)境的干預(yù)措施。

這意味著要恢復(fù)沿海紅樹林等關(guān)鍵生態(tài)系統(tǒng)空間，特別是在入?？跂|岸，恢復(fù)其作為抵御猛烈風(fēng)暴潮和洪水的自然屏障的能力。此外，在正在重建的地區(qū)，應(yīng)盡可能多地推廣基于自然的解決方案（nature-based solutions），以更好地管理地表徑流并改善水質(zhì)。還應(yīng)系統(tǒng)地提高城市地區(qū)的土壤滲透能力，并進(jìn)行植被重建，以恢復(fù)洪泛區(qū)管理地表徑流的自然能力并改善其質(zhì)量。

在入?？谖靼稇?yīng)采用不同的策略。例如中山，或更小尺度的江門和珠海，仍然受到相對(duì)較大的土地覆蓋演變的影響，我們首先需要明確城市化如何導(dǎo)致土地覆蓋演變。我們應(yīng)采取控制城市擴(kuò)張的政策，以避免西江沿岸具有重要文化和生產(chǎn)價(jià)值的農(nóng)業(yè)水產(chǎn)養(yǎng)殖景觀進(jìn)一步破碎化。

4 結(jié)論

圖析三角洲地區(qū)土地覆蓋隨時(shí)間的變化圖，可以揭示其演變的主要模式，輔助識(shí)別穩(wěn)定性特征，并保護(hù)維持其韌性的要素。本研究提出了一種基于ESA CCI土地覆蓋圖、使用時(shí)空矩陣來(lái)量化珠三角城市的土地覆蓋演變模式的方法。該數(shù)據(jù)集涵蓋了1992—2015年的年度數(shù)據(jù)。這種精細(xì)的時(shí)間顆粒度能夠以非常高的精度界定土地覆蓋演變規(guī)律，從而更容易識(shí)別城市區(qū)域內(nèi)經(jīng)濟(jì)政策隨時(shí)間的空間溢出效應(yīng)。

圍繞該數(shù)據(jù)集構(gòu)建的時(shí)空矩陣，有助于了解土地覆蓋演變趨勢(shì)如何在像珠江三角洲這樣有活力的地區(qū)分布，從而比較整個(gè)地區(qū)隨時(shí)間變化的土地覆蓋演變強(qiáng)度的不同。

使用這種全球開源數(shù)據(jù)集的優(yōu)勢(shì)有2個(gè)：一方面，它以精細(xì)時(shí)間顆粒度為單位提供系統(tǒng)化的信息，使定量研究空間演進(jìn)模式成為可能，比如變化發(fā)生在何時(shí)何地，什么類型的土地覆蓋受影響最大，以及變化的主要驅(qū)動(dòng)因素是什么；另一方面，這些數(shù)據(jù)在全球范圍內(nèi)可用，這意味著研究者可比較世界各地不同三角洲地區(qū)的土地覆蓋演變情況，而且在那些國(guó)家或地區(qū)層面的信息不存在或不可用的地區(qū)，這些數(shù)據(jù)依然適用。

當(dāng)然，此數(shù)據(jù)集也有一定局限性。比如，當(dāng)涉及區(qū)域?qū)用娴姆治鰰r(shí)，這個(gè)數(shù)據(jù)集被證明是非常充分的。即使是在城市區(qū)域內(nèi)，300 m的空間分辨率也足以分析土地覆蓋演變趨勢(shì)。然而，當(dāng)縮小規(guī)模或分析更緊湊的地區(qū)時(shí)，例如澳門，這些數(shù)據(jù)可能失去其空間意義。因此，澳門不在本研究范圍內(nèi)，因?yàn)橥恋馗采w數(shù)據(jù)缺乏一致性。

該數(shù)據(jù)集的另一個(gè)局限是，雖然它對(duì)森林和農(nóng)業(yè)地區(qū)的分類足夠全面，但對(duì)建成區(qū)卻不能這樣分析。這說(shuō)明，在分析建成環(huán)境密度變化方面，此數(shù)據(jù)集并不具備顯著性。然而，這個(gè)問(wèn)題可以通過(guò)交叉使用其他來(lái)源的數(shù)據(jù)來(lái)克服，例如通過(guò)遙感圖像的監(jiān)督分類等方法。特別是在珠三角地區(qū)，幾十年來(lái)的城市化進(jìn)程一直是由農(nóng)業(yè)地區(qū)的工業(yè)化推動(dòng)的，農(nóng)業(yè)也是轉(zhuǎn)型政策的主要目標(biāo)之一，因此有必要對(duì)相關(guān)程度最高的工業(yè)地區(qū)進(jìn)行分類，以使其在區(qū)域規(guī)模上與城市地區(qū)區(qū)分開。

本研究在時(shí)間維度上，通過(guò)量化區(qū)域尺度土地覆蓋演變來(lái)評(píng)估并解讀珠江三角洲的轉(zhuǎn)型。未來(lái)可在3個(gè)方面展開進(jìn)一步研究。1）將這種定量分析與著眼于土地覆蓋空間組構(gòu)的相關(guān)分析相結(jié)合。這類分析考量了景觀空間，包括但不限于通過(guò)景觀生態(tài)學(xué)領(lǐng)域的指標(biāo)來(lái)測(cè)度。在珠三角的研究背景下，意味著要了解珠三角各城市之間的空間組構(gòu)關(guān)系，不同景觀類型是如何破碎的，以及三角洲不同城市是如何發(fā)展的。2）可將這類分析與生態(tài)系統(tǒng)服務(wù)分析相結(jié)合，來(lái)衡量后者隨時(shí)間推移的變化及受到人類活動(dòng)的影響。3）開發(fā)預(yù)測(cè)模型，利用時(shí)空土地覆蓋演變圖預(yù)測(cè)未來(lái)的變化和土地利用政策的影響。

注釋：

① 本文中的珠江三角洲是指大珠江三角洲，包括珠三角和香港、澳門2個(gè)特別行政區(qū)。

② www.esa-landcover-cci.org。

③ 采用全球行政區(qū)域數(shù)據(jù)庫(kù)的行政邊界（gadm.org/download_v4.html），該數(shù)據(jù)庫(kù)為學(xué)術(shù)和非商業(yè)用途提供免費(fèi)可用的空間數(shù)據(jù)。

④ R Studio是一款免費(fèi)的數(shù)據(jù)科學(xué)開源軟件（www.rstudio.com）。它使用了R語(yǔ)言——一種用于統(tǒng)計(jì)計(jì)算的編程語(yǔ)言。

圖表來(lái)源：

文中圖表均由作者使用表2中的地理空間數(shù)據(jù)繪制，圖1審圖號(hào)GS（2019）4342號(hào)。

（編輯 / 王一蘭）

著者簡(jiǎn)介：

（意）丹尼艾勒·坎納特拉 / 男 / 博士 / 代爾夫特理工大學(xué)建筑與建成環(huán)境學(xué)院助理教授 / 研究方向?yàn)閺?fù)雜適應(yīng)系統(tǒng)理論、區(qū)域設(shè)計(jì)、氣候變化應(yīng)對(duì)戰(zhàn)略

譯者簡(jiǎn)介：

李佳琪 / 女 / 哈爾濱工業(yè)大學(xué)（深圳）建筑學(xué)院在讀碩士研究生 / 研究方向?yàn)閳D析與城市設(shè)計(jì)

校者簡(jiǎn)介：

蔡佳秀 / 女 / 博士 / 香港中文大學(xué)建筑學(xué)院助理教授 / 本刊特約編輯 / 研究方向?yàn)槌鞘性O(shè)計(jì)理論與方法、城市形態(tài)學(xué)、建筑模式語(yǔ)言、設(shè)計(jì)思維與設(shè)計(jì)過(guò)程

CANNATELLA D.Mapping Land Cover Change Through the Implementation of a Spatio-Temporal Matrix: The Case of the Pearl River Delta (China)[J].Landscape Architecture, 2023, 30(11): 70-86.DOI: 10.12409/j.fjyl.202208170491.

Mapping Land Cover Change Through the Implementation of a Spatio-Temporal Matrix: The Case of the Pearl River Delta (China)

Author:(ITA) Daniele Cannatella Translator: LI Jiaqi Proofreader: CAI Jiaxiu

Abstract:[Objective] In rapidly urbanizing deltas, the impacts of climate change and land cover transformation are highly interconnected.Therefore, mapping land cover change (LCC) over time is a relevant research objective to investigate both the impacts of human activities on these urban systems and to assess their degree of vulnerability to natural disasters.[Methods] This paper presents a systematic analysis of LCC patterns in the Pearl River Delta (PRD) in both space and time to shed light on spatial impacts of land-use policies on this deltaic megaregion and map out recommendations for responses to climate change mitigation and sustainable urban development.[Results] This paper presents a methodology for mapping LCC at the regional scale over time using R Studio and entirely based on open data, through the implementation of a spatiotemporal matrix.It uses ESA CCI land cover maps and USGS elevation maps to analyze patterns of change in the PRD, one of the fastest urbanizing regions in the world, over years 1992-2015.Through the quantification of LCC patterns at a fine temporal grain, the study reveals how the stages of development in PRD correspond to different trends in the intensity of change in different areas of the delta.In addition, LCC rates are higher in the low elevation coastal zone (LECZ), particularly prone to sea-level rise, stronger storms and other hazards induced by climate change.[Conclusion] The proposed matrix can help decision makers to better understand the spatial and temporal variation of LCC across deltaic regions, that can aid in the formulation of targeted planning strategies to increase resilience in vulnerable coastal areas.

Keywords:land cover change; open-source data; mapping; deltaic regions;Pearl River Delta; ESA CCI land cover maps; R

?BeijingLandscape ArchitectureJournal Periodical Office Co., Ltd.Published byLandscape ArchitectureJournal.This is an open access article under the CC BY-NC-ND license.

In fast urbanising areas, understanding the implication of change in land cover and land use is a crucial task to assess the impact of spatial policies, respond to risks posed by natural disasters,deal with the negative impacts of climate change and develop strategies aiming for sustainable urban development.This is especially relevant for regions where growing urbanisation and the new climate regime have a greater impact, and therefore coherent, informed and systemic adaptation and mitigation actions are needed, as in the case of urban deltas.Climate change and land cover are connoted by a deep and mutual relationship, in which one affects the other.The impacts of land use/land cover change (LULC) on global climate reveal themselves in the flux of CO2in the atmosphere, whereas climate change affects land use and land management strategies, and calls for mitigation and adaptation responses to tackle the negative effects of climate change[1].Furthermore,land cover change and related use are one of the main drivers of global change, altering land and water resources availability, ecosystem services, and hydrological processes[2].Land erosion as a consequence of human activities can have major impacts on the integrity and quality of vital natural resources, such as water and soil.Urbanisation and anthropogenic action can alter the distribution of ecosystems and their associated fluxes of energy and matter, affecting their capacity to support and sustain humans and other living beings.Land use practices, in conjunction with climate change, play a key role in determining the quality of the hydrological performance of watersheds[3].In deltaic areas, urbanisation in flood-prone areas increases the exposure of human lives and assets to natural disasters, and the resulting uncontrolled increase of impervious surfaces affects the capacity of floodplains to attenuate water infiltration into soils[4], while simultaneously redirecting water runoff and magnifying peak discharges.Fundamental processes such as evapotranspiration,groundwater flow and stream discharge regime are also affected by land use[5], influencing the correct functioning of the water cycle in urban areas.These alterations generate direct consequences on the vulnerability of urban systems to floods[6],landslides, storms and droughts among others, as the engineered infrastructure for water management is not designed to deal with the growing stress caused by the altered patterns of precipitation.Changes in land use have negative impacts on water quantity and quality.The expansions of crop areas requiring high inputs of nutrients can lead to higher sediments, nitrates and phosphorus loads in surface waters[7-8].Agricultural expansion, together with industrial activities and urbanisation, will further deplete groundwater supplies, leading to growing imbalances between water supply and demand[9].

Mapping the change in land cover over time is therefore a key activity to investigate the implications of the evolution of urban systems both from a spatial and a quantitative point of view.Mapping as a method is a powerful tool for carrying out a systematic study of deltaic landscapes undergoing urbanisation[10].In particular, using spatial analysis methods and tools based on geographic information systems (GIS)can support the quantification of certain aspects regarding the composition and the configuration of the urban landscape through the development or use of metrics that refer to land cover maps.Comparing the evolution of urban landscape patterns within a region can help to provide more insightful information on the similarities and dissimilarities of processes of spatial transformation from a temporal perspective.Moreover, it assists in analysing the impact of land use policies on the territory over time, and consequently formulate planning choices aimed at sustainable urban development.

To carry out this type of analysis, it is possible to make use of numerous LULC products that are produced at different scales, from global to national, and different spatial resolution.LULC is a significant resource based on remote sensing that provides information on global and regional vegetation cover, and is widely used in various largescale climatic, ecological, and hydrological models[11].

This research makes use of the Pearl River Delta (PRD)①, the fastest urbanizing deltaic region in the world, as a case study.Several studies with different purposes have been conducted to analyse LULC in the PRD.For example, Seto et al.[12]estimated land-use change over time for a part of the PRD incorporating the estimates in a socioeconomic analysis of the factors influencing such change using Landsat TM imagery.Some scholars focused on the prediction of future land-use in the region[13], incorporating planning policies into a land-use simulation model[14]or identifying the contribution of different LULC driving factors[15].Other studies focus on the quantification of LULC impacts on ecosystem services[16-17].These analyses focus mainly on the PRD region as a whole, and are characterised by timeframe ranging from three years to ten years.Furthermore, they overlook the diversity of intensity and variation of transformation in different parts of this megaregion.

1 Pearl River Delta cities

The aim of this paper is twofold.On the one hand, it investigates the different spatial and temporal patterns of land cover change (LCC)across PRD’s cities at a fine temporal grain (1 year)to understand the spatial impacts of land-use policies on the region.On the other hand, it proposes a methodology for the spatio-temporal mapping of land cover change at the regional scale based entirely on open-source data.It utilises ESA CCI (European Space Agency Land Cover Climate Change Initiative Project)②land cover maps and USGS elevation maps as base data, to define the intensity of annual land cover variation in the low elevation coastal zone (LECZ), comparing it with the rest of the region.The LECZ is used as a proxy to identify vulnerable areas, particularly prone to inundation from sea level rise, storm surge, wetland degradation, land subsidence and flooding.The ESA CCI dataset covers the period 1992-2015 with maps produced on a yearly base.

1 Materials and Methods

1.1 The Pearl River Delta

The Pearl River Delta is located in the south-eastern part of China (Fig.1).From a geomorphological perspective, the PRD is an alluvial plain formed by three main tributaries, the Xi Jiang (West River), Bei Jiang (North River), and Dong Jiang (East River).The three rivers converge in the central part of the delta before flowing into the South China Sea.

The PRD is home to a thick network of cities formed by nine prefectures located on the mainland — namely, Guangzhou, Dongguan,Foshan, Huizhou, Jiangmen, Shenzhen, Zhaoqing,Zhongshan, and Zhuhai — and the two Special Administrative Regions of Hong Kong and Macao.Altogether, the nine prefectures and the two Special Administrative Regions cover a total area of over 55 thousand square kilometres (Tab.1).

Tab.1 The cities of the Pearl River Delta (PRD), ranked by area

After the launch of the open door policy in 1979, the PRD rapidly became one of the most economically dynamic regions in China and the world.In less than ten years since the implementation of the economic reforms, the PRD’s total GDP accounted for 7.35% of the country’s total[18].This trend has never suffered any major setbacks, reaching 9.1% of China in 2016[19].

Concurrently with this economic growth, the region has experienced tremendous demographicgrowth, surpassing Tokyo to be the world’s largest urban area in both size and population in 2014[20],and reaching a population of nearly 72 million inhabitants in 2016.

This abrupt economic development coincided with a dramatic structural and spatial transformation that saw a large increase in industrial production and a simultaneous drastic decline in the share of agricultural production, but also a process of urbanisation that only today seems to be slowing down.

Relentless urbanisation and uncontrolled anthropogenic activities, together with the impacts generated by climate change, have been undermining the delicate balance of this deltaic region, threatening its sustainable development and confronting it with multiple challenges.

On the one hand, the region is exposed to growing flood risks, due to urbanisation in floodprone areas, rising sea levels, and extreme typhoons and storms.On the other hand, increasing soil sealing contributes to the fragmentation of natural systems and the subsequent erosion of related ecosystem services[21].Agriculture and industry also have a negative influence on water quantity and quality, representing respectively 33% and 37% of water demand and contributing to the pollution of the surface water system.In fact, in 2015, 39% of its river waters were considered “unfit for human touch”[22].

The urbanisation process in the PRD has been uneven in space and time.After a phase characterised mainly by agricultural development,which ended in 1978, the development of the PRD went through three further stages[23]: the industrialisation stage (1978-2000); the urbanisation and metropolitanism stage(2000-2008); and the rapid rural transformation under urbanisation stage (2008-present).Each of these stages is characterised by different policies which in turn have had equally different impacts on land cover over time.In addition, the most intense urbanisation has occurred mainly along the eastern axis of the delta, which runs from Guangzhou to Shenzhen, and continues to Hong Kong, and through Dongguan and Shenzhen.Conversely, the western axis is relatively less developed, with a metropolitan cluster consisting of the conurbation of Guanzhou and Foshan, and more compact urban areas dotting the floodplain.

1.2 Data and Software

The LCC analysis of the PRD was carried out using open-source datasets with global coverage.The choice of employing open-source data is due to two main reasons.Firstly, to test the potential of available free datasets on land cover having a finegrained temporal resolution in LCC analysis at the regional scale.Secondly, to set the basis for its replicability in other deltaic regions around the globe.

For this reason, three main datasets on land cover, elevation, and administrative units were used(Tab.2).

Tab.2 Source datasets used in the analysis of land cover change

The ESA CCI Land Cover Maps are openaccess Global Land Cover maps provided within the framework of the European Space Agency(ESA) Land Cover Climate Change Initiative Project.The maps have global coverage and are available at 300 m spatial resolution.In addition,they are produced on a yearly base, covering the years from 1992 to 2015.In the raster dataset, each pixel value represents a specific land cover class(Tab.3).

Tab.3 ESA CCI Land Cover Classification

Data on elevation was derived from the USGS SRTM (Shuttle Radar Topography Mission).The SRTM is a joint project between NASA and NIMA aiming at mapping the planet’s land surface in three dimensions at a high level of detail.Data available over non-U.S.territory include 3-arcsecond data, corresponding to approximately 90 m.For this analysis, georeferenced tagged image files(GeoTIFFs) were used.

Lastly, administrative boundaries③were used to clip the raster datasets.Spatial data were reprojected, preprocessed, and elaborated through R Studio software④.The final output is a script that automates the entire process, which will later be made publicly available.

1.3 Data Preprocessing

Before starting the analysis, it was necessary to clip the 23 ESA CCI raster maps and the elevation raster map to the administrative limits of the PRD.Each of the resulting land cover maps iscomposed of a total of 632,213 cells, having the original resolution of 300 m.The cells were subsequently converted into georeferenced points and cross-referenced with the elevation raster to determine which of them were located in the LECZ.For the sake of reproducibility of this study in other contexts, The LECZ is defined in this study as the contiguous areas along the coast that is less than 10 metres above sea level[24].These areas are particularly prone to sea-level rise, stronger storms and other hazards induced by climate change, and therefore more vulnerable than other areas lying on higher ground.Furthermore,urbanisation in these areas represents a treat to coastal and deltaic ecosystems, contributing to the erosion of ecosystem services delivering protection functions for urban settlements, thus amplifying climate-related risk.Lastly, the next step was the spatial intersection of the resulting point grid with the municipal boundaries layer.This made it possible to determine how many cells were located in the LECZ for each city in the PRD (Tab.4, Fig.2), and what type and share of land cover characterised them year by year, from 1992 to 2015.

Tab.4 Number and percentage of cells above or below 10 meters above sea level by city

From the map, it is clear that the western wing of the delta is characterized by a large presence of LECZ.In particular, more than threequarters of the territory of Zhongshan is located in potentially vulnerable areas, followed by Foshan(67.70%) and Zhuhai (61.59%).On the eastern side of the PRD, Dongguan is the city with the highest percentage of territory in the LECZ (44.13%).

2 Map of areas in the LECZ

1.4 Land Cover Reclassification

After land cover maps were clipped, the next step entailed the reclassification and aggregation of land use classes proposed by the ESA CCI.The reclassification was made keeping in mind the widespread presence of water-related agriculture and vegetation, such as the dyke-pond system that characterises the whole deltaic region.For this reason, seven aggregate land cover classes were identified (Tab.5).These classes are: forest;agriculture (cropland); agriculture (irrigated); forest(water); grassland, shrubland, sparse vegetation and bare areas; urbanized areas; and water.

Tab.5 Proposed Aggregated Land Cover Classes for the analysis and number of cells for each class in 1992 and 2015

1.5 Spatio-Temporal Matrix

The final step involved the creation of a spatio-temporal matrix by developing a script in R Studio environment.In the matrix, each row corresponds to a point marked by coordinates(longitude and latitude), elevation (reclassified as above/below 10 m above sea level), city, and finally, a series of numerical values from 1 to 7,corresponding to the land cover categories per as described in Tab.5.Tab.6 shows a sample of the final matrix, including information on coordinates(displayed asxandy), city, elevation, and land cover values per year.The latter represent the land cover categories by year, from 1992 to 2015.Tab.6 shows a sample of the matrix containing the first 20 rows.

Tab.6 Sample of the final spatio-temporal matrix

The spatio-temporal matrix is the starting point for the land cover change pattern analysis.The relevant aspect of this matrix is that it yields several keys to interpretation.A “vertical” reading provides quantification of each aggregate class of land cover by year, groupable by city and elevation.A “horizontal” reading, on the other hand, returns the intensity and variability of land cover change year by year by point, or aggregated by city and/or elevation.

In addition, this structure makes it easy to identify the land cover categories most subject to transformation, inside or outside the LECZ, for each city.The next section presents the results of some of these analyses.

2 Results

Comparing land use maps from 1992 and 2015, we see that throughout the whole PRD region, in the span of twenty-three years, urban areas have increased more than three and half times, from about 2,050 km2to about 6,380 km2(Fig.3).On the other hand, a decrease in land cover is found in agricultural areas (-3.71%) and those classified as others (including shrublands,grasslands, and bare areas, -2.97%).Irrigated agricultural areas also decreased significantly, from11,252.91 km2to 10,508.95 km2(-1.34%).Other land use types remained essentially unchanged.The decrease in areas classified as water, however not substantial, may indicate that some areas have been reclaimed over time.

3 Total land cover change in the PRD (years 1992-2015)

Beyond the quantitative aspects, the land cover maps in Fig.4 clearly show the spatial patterns of urbanization in the region.A comparison of the two maps in 1992 and 2015 shows how urbanization in the PRD has not happened at all evenly.On the contrary, it is possible to identify three major trends.1) The first is along the east coast of the estuary, along the Guangzhou - Hong Kong route.In this area, builtup areas have welded together along the coast over time, thickening right into the LECZ belt.In addition, Dongguan and Shenzhen have witnessed a veritable explosion of urbanization, limited only by the topographical conformation of their territories.2) The western axis, running from Guangzhou to Macao, saw the merging of the cities of Guangzhou and Foshan and generally a more concentric development of urban settlements.3) In the more peripheral areas of the delta, urbanization took place mainly around the more consolidated urban centres, and along the main connecting axes.

4 Land cover maps of the PRD, based on ESA CCI (years 1992-2015)

5 Land Cover Change in LECZ by year, per municipality

The second part of the analysis investigates how much and where land cover change has occurred over the years.In Fig.5, the blue bars indicate the change in the LECZs, and the dark grey bars express the change in the areas above 10 m a.s.l.The first thing that stands out is that the intensity of land cover change, which here takes into account all land cover categories, does not happen uniformly in space.In fact, it occurs mainly in the LECZ, and has two clearly distinct paces across the Delta.1) Looking at the temporal dimension, Shenzhen and Dongguan are the municipalities where the conversion of land to urban areas ihas occurred most significantly, with peaks of 16.6% in 2001 and 16.5% in 2002 respectively.Other cities along the coast follow,located in the central area of the delta.Jiangmen and Zhaoqing take the back seat.2) Looking at the temporal dimension, 1995 is the year in which the first increase in land cover change is recorded in all cities homogeneously.The 2001-2002 period is the one in which the largest increases in change are recorded, especially in Shenzhen and Dongguan.From 2005 onwards, however, a decline in transformation can be observed, especially in more mature cities.

3 Discussion

The results on the analyses conducted on land cover change in the PRD over the years 1992-2015 show the existence of two distinct geographies, each characterised by very different pace and intensity of transformation.The first is represented by the cities located in the PRD core area, along the coast; The second is the outermost cities, such as Jiangmen and Huizhou.In particular,Shenzhen and Dongguan, located on the eastern side of the estuary, are characterized by a high rate of land cover change, especially in the early stages of the implementation of economic reforms.When looking at Fig.5, it becomes clear that it is these two cities where land cover change occurs first and with greater intensity, driven primarily by urbanization and the transformation of the countryside into industrial areas.Other major and historically more important cities such as Guangzhou and Hong Kong have significantly lower, but also steadier, transformation intensities.

In general, the intensity of land cover change is largely determined by urbanization processes that mainly have been taking place in this part of the delta.This is mainly due to Shenzhen’s designation as a Special Economic Zone (SEZ), which has given an incredible boost to urbanization especially in the first decades since the implementation of economic reforms.

For Zhuhai’s SEZ, the situation seems to be different.Data analysis shows that in the early 1990s LCC was almost absent, except for a peak in 1995.This trend changes towards the end of the 1990s, with a steady increase culminating in a peak in 2004, before declining again.Of the cities located along the western axis of the delta, Foshan and Zhongshan are those whose territory has undergone the most significant transformation.The more peripheral cities in the PRD are the ones that have slower LCC rates instead.

When looking at temporal patterns, two relevant aspects emerge from comparing trends by city.

The first is that, as mentioned above, there are some cities that lead the transformation tendencies at various stages, and others that follow.Again, Shenzhen and Dongguan are the cities where it is possible to detect an acceleration in LCC in the industrialization stage of the delta, as well as in the urbanization and metropolitanism stage.Similarly, these are the first cities where there is a dramatic slowdown in LCC from 2008 onward,when the PRD enters a further phase characterized by the redevelopment of already urbanized areas and an increased focus on environmental protection, especially in more mature cities.This trend is slightly different for the western delta zone, particularly for Zhongshan, where the LCC still remains constant, especially in the LECZ.

Lastly, when comparing LCC intensity in LECZ and other areas, it is striking to see that it happened mostly in the former, which coincides with the most vulnerable areas.As urbanisation is the main driver of change, this resulted in a dramatic increase of exposure of people, critical infrastructure, services and economic assets.

This is clearly a trend that needs to be curbed to avoid increasing climate-related risk in the PRD by taking targeted action in its different parts.In cities where land consumption has slowed and efforts are devoted to regeneration of already urbanized areas, interventions dedicated to adapting the built environment should be prioritized.

This means identifying spatial opportunities to reinstate key ecosystems such as mangrove forests along the coasts, and restore their capacity to act as natural barriers against violent storm surges and floods, especially along the eastern side of the estuary.In addition, in areas undergoing redevelopment, nature-based solutions should be promoted more wherever possible to be able to better manage excess water and improve its quality.In addition, nature-based solutions should be promoted more in areas undergoing redevelopment, where possible.Systemic soil permeabilization and revegetation interventions in urban areas should also be encouraged, to restore the natural ability of floodplain to manage excess water and improve its quality.

A different logic should apply to the western side of the estuary.As Zhongshan, and to a lesser extent Jiangmen and Zhuhai, are still subject relatively high LCC trends, the question that needs to be asked is how this transformation should take place, especially with regard to urbanization.Policies to curb urban sprawl should be pursued to avoid further fragmentation of the agri-aquacultural landscape along the Xi Jiang, which is of great cultural as well as productive value.

4 Conclusions

Mapping deltaic regions’ land cover change over time can shed light on the main patterns that characterise their evolution, supporting the identification of those traits that resist modification as well as those that must be preserved to safeguard resilience.This paper proposed a methodology based on the use of ESA CCI land cover maps to quantify patterns of land cover change in the PRD cities through the use of a spatiotemporal matrix.This dataset covers the period from 1992 to 2015, on an annual basis.This fine temporal grain makes it possible to detect LCC rhythms at a very high level of accuracy,which in turn can more easily identify spatial spillovers over time of economic policies within an urban region.

Structuring the spatiotemporal matrix around this dataset also helps to understand how LCC trends are distributed in a region as dynamic as the PRD, making it possible to compare LCC intensities and temporal variations across the region.

The advantage of using such global open dataset is twofold: on the one hand, it allows to systematize information produced at a fine temporal grain to quantitatively investigate these patterns — where and when these changes occurred, what types of land cover are most affected, and what are the major drivers of change).On the other, this data is available at a global coverage, which means that it makes it easy to compare different deltaic regions across the world,but also that it can be used in areas where information at the national or local level is not present or not available.

This methodology has some limitations.When it comes to conducting a regional-level analysis, this dataset proves to be extremely adequate.A spatial resolution of 300 m is more than enough to analyze LCC trends even within an urban region.However, when scaling down or working on more limited areas, as in the case of Macao, these data may lose their spatial significance.For this reason, Macao was kept out in this study because there was little consistency in the LCC data.

Another limitation of this dataset is that while the classification it proposes on forest and agricultural areas is sufficiently broad, the same cannot be said for built-up areas.this implies that it is not significant when it comes to analysing the variation in density of the built environment.However, this problem can be overcome by crossreferencing it with other sources, for example by using methods such as supervised classification of remote sensing images.In the case of the PRD, in particular, where the urbanization process for decades has been driven by the industrialization of agricultural areas with the same being one of the main objects of transformation policy, a categorization becomes necessary to diversify the most relevant industrial areas from urban ones at the regional scale.

This study focuses on quantifying land cover change at the regional scale through a temporal assessment of the transformative dynamics that have occurred in the PRD.this type of study represents an essential preliminary analysis for subsequent analyses, which can be developed in three different directions.The first is the coupling of this quantitative analysis with an analysis that instead looks at aspects related to the spatial configuration of land cover.This type of analysis allows the exquisitely spatial aspects of the landscape to be taken into account, including by measuring them through metrics such as those belonging to the field of Landscape Ecology.Applied in the context of the PRD, this means understanding what kind of spatial configuration is emerging in the various cities of the PRD, how different landscape types are actually fragmenting,and how urban development is taking place in the different municipalities of the delta.The second aspect is the integration of this type of analysis with that on ecosystem services, to measure how the latter vary over time and are impacted by human activities.The third is related to the development of predictive models that make use of spatiotemporal land cover change maps to forecast future transformations and the impacts of land-use policies.

Notes:

① PRD in this paper refers to the Greater Pearl River Delta,which include PRD and the two Special Administrative Regions of Hong Kong and Macao.

② www.esa-landcover-cci.org.

③ Administrative boundaries from GADM (gadm.org/download_v4.html), which provides freely available spatial data for academic and non-commercial use, were employed.

④ R studio is a free and open-source software for data science (www.rstudio.com).It makes use of R, a programming language used for statistical computing.

Sources of Figures and Tables:

All maps and tables are made by the author, using the geospatial data mentioned in Tab.2, approval number of Fig.1 is No.GS(2019)4342.

(Editor / WANG Yilan)

Author:

(ITA) Daniele Cannatella, Ph.D., is an assistant professor at the Faculty of Architecture and the Built Environment, Delft University of Technology.His research focuses on complex adaptive systems theory, regional design, and adaptation strategies to climate change.

Translator:

LI Jiaqi is a master student in the School of Architecture,Harbin Institute of Technology, Shenzhen.Her research focuses on mapping and urban design.

Proofreader:

CAI Jiaxiu, Ph.D., is an assistant professor in the School of Architecture, The Chinese University of Hong Kong, and a contributing editor of this journal.Her research focuses on urban design theory and methods, urban morphology,pattern languages, and design thinking and design process.