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《景观设计学》2015年第3期
作 者：沈尧（Yao SHEN），龙瀛（Ying LONG），王鹏（Peng WANG）等类 别：景观出 版 社：高等教育出版社有限公司出版时间：2015年6月
俞孔坚
——《景观设计学》2015年第3期“主编寄语”
Landscape in Big Data
By Kongjian Yu
打开手机上的微博，搜索“后滩公园”四个字，屏幕上便立刻出现了很多条关于后滩公园的信息。
6月14日，“@福娃一家亲”写到：“今天宝宝幼儿园春游，游玩后滩公园……”微博上配有9张娃娃们在水边嬉戏的照片—坐在竹木栈道上，在树下捡果子，把手伸到水里……我再点开她的主页，发现这是位热爱生活的母亲，每个周末都会带女儿去公园，她家住上海虹口区。我继续翻看她的其他相册和微博，大部分都是在记录她的宝贝女儿的生活，我甚至可以花一天的时间阅读她的网上日志。
5月23日，“@张青青Vvvictoria”发布了9张她在后滩公园盛开的野花组合中拍摄的写真照片。这是一位毕业于上海华东师范大学的美丽姑娘，她以往的微博透露出，她是一位爱好艺术和社交的校花。
5月23日，“@安安宝贝的小屋”写到：“后滩公园，下次记得带捞网。”微博中配有9张照片：一群小孩在捞水边的蝌蚪……
5月17日，“@ZEAL”写到：“摸鱼行动一天成果。后滩公园比其他公园真是有趣多了，人少景多不收门票、没有各种变异的自行车乱窜……”，照片是其捞鱼的成果。
5月17日，“@麦家的球”写到：“没素质的老太太在后滩公园采摘粽叶。”照片曝光了一位老太太在摘苇叶。
5月12日，“@张小哈-AHHA”写到：“度过宁静的一天，上海最爱的公园，没有之一。”微博中的9张照片都是后滩的风景。这是一位来自西安交通大学设计专业的女生。即将毕业，爱好音乐。
……
如此一页页地翻阅，我看到了后滩公园每时每刻都在不断变幻的风景：出现在人们的照片里的油菜花、向日葵、雏菊、金盏菊交替绽放；我看到人们在芦苇、蒲草、细叶芒丛中的笑容；我看到小孩们在最乐意逗留的水边；我也能看到他们捞上来的小鱼、小虾、蝌蚪—我甚至能辨别出它们的种类；我也可以看到什么鸟最近出没在公园里的什么地方—有观鸟爱好者列出了它们的物种名称。进一步，我也可以知道有什么人、在什么时间使用公园，有时能够了解他们的兴趣爱好与他们所欣赏的景观之间的关系。我甚至可以向公园管理者电话举报（或者并不需要，因为也许此时公园保安也在浏览这些信息）制止正在发生不良行为（比老太太摘苇叶更严重的事）；我也的确曾经通过网友的照片，及时向管理者反映，望尽快修复腐烂的栈道或损毁的栏杆……
地球外围轨道上的遥感卫星、全球定位系统、配有三维激光扫描设备的无人机、无处不在的摄像头、便携的数码相机、全球将近20亿的智能手机用户，加上射频识别技术、移动互联网、云计算……它们在每时每刻地摄取、储藏、传送和处理着海量的景观信息，这些信息包括关于景观系统（包括其格局及过程）、景观服务及其使用。这些信息在几十年前还需要通过昂贵的、系统的调查途径来获得—如通过取样调查来分析生物多样性，通过照片来进行景观的感知评价，通过专业勘察队伍来选择穿越景观的最佳路径，通过现场调查来进行城市公园的使用后评价等—在今天，这些数据正如汹涌的潮水夹杂着大量泥沙和杂物，从各种移动或固定端口涌入我们的办公室、卧室、餐厅、电梯，甚至卫生间。这便是我对大数据时代与景观及其设计和管理之间的联系的体会。
大量来自云端的历史和即时的关于景观和社会文化背景的大数据，为我们有效地设计以及管理景观带来无限的机会。但我们必须清醒地认识到，这样的大数据是一把锋利的双刃剑。首先，因为数据的来源本身并不系统、均衡，而是带有歧视性或偏差性的—如智能手机的使用群体并不能代表我们社会的全部人群—因此，根据这些信息所做的决策必然不是公平公正的；其次，数据如此唾手可得而廉价，海量的数据往往使珍珠被掩埋在泥沙里，没有含义的信息便是噪音，因此，处理这些数据需要超强的系统和巨大的成本；第三，数据和信息都只能告诉我们过去，最多也只能反映当下的状态，并不能告诉我们未来；而只有理论才能告诉我们未来。因此，我们的头脑不能被海量的数据和信息所淤塞，保持头脑有足够的思考余地和清醒的状态，才不致在浩瀚的数据海洋中迷失方向。
译 陈立欣 萨拉•雅各布斯
When I open Weibo (lit. “MicroBlog”) on my cell phone, and enter “Houtan Park”, a great deal of information about the park appears:
June 14, “@福娃一家亲” wrote, “Today, my baby’s kindergarten has a spring outing in Houtan Park....” Nine photos of children playing by the water accompany this text: sitting on the bamboo and wooden plank road; picking fruit under the trees; reaching into the water. I then open her homepage, and find that she is a loving life-mother who lives in Hongkou District, Shanghai, and that every weekend she visits the park with her daughter. I view her other Weibos, mostly her baby daughter in the show. I could spend the whole day reading her online journal.
May 23, “@张青青Vvvictoria” posted nine portraits among the blooming wild flowers in Houtan Park. This is a beautiful girl, a graduate from East China Normal University in Shanghai, whose other Weibos reveal that she is a campus belle who loves art and the social scene.
May 23, “@安安宝贝的小屋” wrote: “Houtan Park, next time remember to bring a fishing net.” Accompanied by nine photographs: a group of children at the water fishing for tadpoles….
May 17, “@ZEAL” wrote: “A day of fishing achievements. Houtan Park is really much more interesting than the other parks, fewer people, more scenery, no tickets, no worries about bike scurries…”, some photos show his fishing achievements.
May 17,” @麦家的球” wrote: “An old lady who lacks quality is picking reed leaves in Houtan Park.” A photo shows that an old lady is being caught picking reed leaves.
May 12, “@张小哈-AHHA” wrote: “A restful day, my favorite park in Shanghai, none can be compared to it”. Nine photos in this Weibo are scenes of Houtan Park. This is a girl from Xi’an Jiaotong University whose major is design. She is about to graduate, she is also a music fan.
….
I read page after page to see the changing landscape of Houtan Park in different moments: field mustard, sunflower, daisy, pot marigold... all emerge in people’s photos, blooming alternately. I see people’s joy in the reeds, and the bushes of narrowleaf cattail and maiden grass. I see kids by the water, where they like it most. I see fish, shrimp, tadpoles, which are just out of the water — I can even identify their species. I can see what kind of birds have been spotted recently — some bird watchers list their species, I can see who, and at what time, uses the park, and sometimes I can understand the relationship between their interests and their favorable landscapes. I can even report to the local administrators (or might not, because the park security also browse this information) to stop bad behavior taking place as I browse (more serious matters than picking reed leaves). I have also reported to the park administrators, helped by netizens’ photos, in time to have a rotten plank road and a damaged railing repaired.
Remote sensing satellites orbit of the Earth’s periphery, the Global Positioning System (GPS), unmanned aerial vehicles (UAVs) with three-dimensional lasers canning equipment; Below, there are ubiquitous digital cameras and nearly 20 billion smart phones, Radio Frequency Identification (RFID) technology, mobile Internet and Cloud computing. They incessantly generate / download, store, transmit and process vast amounts of landscape information, including landscape systems (patterns and processes), landscape services and their uses. A few decades ago such information could only be gained through expensive, systematic surveys, for example, analyzing an area’s biological diversity based on a sample survey, making evaluations of landscape perception through photographs, selecting optimal paths throughout the landscape by professional exploration crew, making post occupancy evaluation (POE) for a city park through field investigation and so on. Today, data, like a surging tide saturated with sediment and debris swarms into our offices, bedrooms, restaurants, elevators. Even into the bathroom.
A large amount of ordinary big data from the Cloud concerns landscape and socio-cultural background. This brings landscape architects and urban planners limitless opportunities to effectively design and manage landscapes. Yet, we must recognize that big data is a double-edged sword. First, the source of the data is not balanced, but has a discriminatory or biased nature — people who use smart phones are not representative of the general population — meaning that decisions made according to such information are not always fair and equitable. Second, the data is so readily available and inexpensive that the pearl often becomes buried in the sand: meaningless information is nothing but noise. Besides, this big data processing requires powerful systems and can incur huge costs. Third, data and information can only tell us the past, or reflect the state of the moment. It cannot predict the future: only theory can. Therefore, we must avoid a situation where our minds are silted up by vast amounts of data and information. We must keep enough thinking room and remain awake. Otherwise we may become lost in these vast oceans of data, rendering them without use.
TRANSLATED BY Qing DONG Jago RACKHAM
