THE STUDY OF GLOBAL LAND SUITABILITY EVALUATION: A CASE OF POTENTIAL PRODUCTIVITY ESTIMATION FOR WHEAT

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1 THE STUDY OF GLOBAL LAND SUITABILITY EVALUATION: A CASE OF POTENTIAL PRODUCTIVITY ESTIMATION FOR WHEAT Guoxn TAN, Ryosuke SHIBASAKI, K S RAJAN Insttute of Industral Scence, Unversty of Tokyo Komaba, Meguro-ku,Tokyo JAPAN gxtan@skl.s.u-tokyo.ac.jp shba@skl.s.u-tokyo.ac.jp rajan@skl.s.u-tokyo.ac.jp KEY WORDS: Agrculture, Bomass, Qualty Control, Evaluaton, GIS, Smulaton. ABSTRACT In ths paper, a GIS based global land sutablty evaluaton methodology s ntroduced. Ths methodology s combned GIS spatal analyss technque wth a land evaluaton methodology termed Agro-Ecologcal Zonng (AEZ and a smulaton model developed by FAO for calculatng crop potental maxmum bomass and yeld. It dvdes global area of land nto smaller grds, and calculates crop potental productvty by takng account of the crop characterstcs, the clmatc factors of radaton and temperatures wthn the growth perods together wth the actual photosynthess capacty of wheat and the fracton of the net bomass. Due to the potental maxmum yeld s manly determned by temperature and precptaton characterstcs, a new straghtforward approach to nterpolatng weekly average ar temperature and precptaton aded by monthly clmatologcally at unsampled ponts n space from weather-staton observaton s proposed. Fnally a case of global potental productvty estmaton for wheat s tested. Weekly average temperatures and precptaton are nterpolated wth qualty control model from weather staton network wth tme seres of daly maxmum, mnmum temperature and precptaton. The growth perod n whch clmate wll permt ran-fed crop producton and global wheat potental productvty s determned. The computed values of net bomass producton and yeld show the potental productvty estmaton methodology s actually possble to be used for global land sutablty evaluaton. 1. INSTRUCTION The ablty of the world's natural resources to provde the needs of ts growng populaton s a fundamental ssue for the nternatonal communty. The basc problem s one of mountng pressure on natural resources. Lmts to the productve capacty of land resources are set by clmate, sol and landform condtons and by the use and management appled to the land. Sustanable management of land resources requres sound polces and plannng based on knowledge of these resources, the demands of the use to whch the resources are put, and the nteractons between land and land use. So t s very mportant for agrculture development plannng to take land resources assessment. The Food and Agrculture Organzaton of the Unted Natons (FAO developed a methodologcal framework to assess food producton, whch wdely known as the Agro-ecologcal zonng (AEZ methodology ( FAO, Ths methodology s an approach to determne the ecologcal potental of land resources for crop producton and to estmates land sutablty. It was frst appled to land sutablty estmates for 11 crops at three levels of nputs n fve regons of the developng world. Due to AEZ methodology nvolves many spatal analyss, the applcaton of Geographcal Informaton System (GIS n AEZ can provdes a comprehensve framework for the apprasal and plannng of land resources. Clmate pattern s one of the most mportant components for land productvty assessment. However clmate and ts space-tme varablty contnue to be examned extensvely by many researchers. A wde varety of approaches have been used (Washngton and Meehl, 1986; Spencer and Chrsty, 1990; Drks et al., 1998; Legates and Wllmott, Observatonal bases at the staton locaton are regarded as the most accurate or precse and have been nvestgated extensvely (Karl et al., But weather staton network wth long-term records and good spatal coverage s uncommon (Wllmott Two problems arse from ths paucty of well-condtoned observatonal networks. Estmatng a tme-averaged weather or clmate varable at unsampled locaton by spatal nterpolaton s relatvely unrelable, and n turn, areal averages made from the network observatons can be based. Some approaches have been studed ntendng to solve these problems (Wllmott and Matsuura, 1995, n whch Clmatologcally Aded Interpolaton (CAI s proved the best one. Unfortunately these methods cannot elmnate all the unrelable and bas especally n the felds where sampled statons are very sparely. How to solve these problems s crucal mportant for Internatonal Archves of Photogrammetry and Remote Sensng. Vol. XXXIII, Part B4. Amsterdam

2 weekly average temperature nterpolaton. In ths paper, frstly a Global Land Sutablty Evaluaton methodology and the assessment steps mplemented n global land are bref dscussed n secton 2; then a weekly clmate nterpolaton approach aded by nterpolated monthly clmatologcally s proposed n secton 3; A test of potental productvty estmaton for wheat and conclusons wll gve late. 2. LAND SUITABILITY EVALUATION METHODOLOGY 2.1 Summary Of AEZ Methodology Agro-ecologcal zonng (AEZ dvdes an area of land nto smaller unts, whch have smlar characterstcs related to land sutablty, potental producton and envronmental mpact (FAO/IIASA, It nvolves the nventory, characterstcs, and classfcaton of land resources for assessng the potental of agrcultural producton system. In ts smplest form, the AEZ framework comprses three groups of compound actvtes Inventory of land utlzaton types (LUT and ther ecologcal requrements. LUTs are defned n terms of a product, or a specfed range of products, and the management system, ncludng the operatons and nputs, used to produce these products. Ther ecologcal requrements nvolve the clmatc, sol and landform condtons necessary for the component crops and for the management system Defnton and mappng of agro-ecologcal zones. The land resources nventory s based on combnng dfferent layers of nformaton to defne agro-ecologcal cells (AECs wth a unque combnaton of clmate, sol and other related land attrbutes. It ncludes analyses length of growth perod; defne thermal zones; comple clmatc resource nventory; comple sol and landform resource nventory; and comple present land use nventory Evaluaton of the land sutablty of each agro-ecologcal zone. Assessment of land sutablty s carred out by a combnaton of matchng constrants wth crop requrements, and by modelng of potental bomass producton and yeld under constrant free condtons. Ths actvty s normally carred out n two man stages, n whch frstly the agro-clmatc sutablty s assessed, and secondly the sutablty classes are adjusted accordng to edaphc or sol constrants. 2.2 GIS Based Land Sutablty Evaluaton Methodology The AEZ concept s essentally a smple one. To facltate the storage, manpulaton and dealng of complex spatal nformaton, t s very necessary to nput all spatal data nto a geographcal nformaton system. The nature of the analyss, whch nvolves the data converson, nterpolaton and overlay, can lend tself to the applcaton of GIS. In our examnatons, the spatal database of global land sutablty evaluaton s created and supported by ARC/INFO. Wth the ad of GIS, agro-ecologcal cells can be defned n grd, whch form the basc unt of analyss used n AEZ applcatons, and a program, whch combnng overlad spatal nformaton wth the calculaton of crop productvty, s developed. For estmaton of potental productvty, AEZ uses the concept of a maxmum attanable total bomass and yeld. For a specfed LUT, the potental maxmum yeld s determned by the radaton and temperature characterstcs of a partcular locaton, by the photosynthetc effcency of the crop, and by the fracton of net bomass that the crop can convert to economcally useful yeld. Although some potental land productvty models have been developed, most of these are pad attenton to regonal model development. Here, a potental producton bomass smulaton model (FAO, 1978 s ntroduced to calculate the global potental maxmum bomass and yeld. In ths model the photosynthetc effcency and the maxmum of gross bomass producton are calculated from a very smple photosynthetcally actve radaton (PAR on a perfectly clear day and the daly gross photosynthess rate of crops canopes on very clear and overcast days gven by de Wt. Fgure 1 gves a general overvew of the flow and ntegraton of nformaton mplemented n the global land sutablty evaluaton. In our examnatons, the clmate data s pont dstrbuton data based on whether staton network. In order to nterpolate hgh qualty clmate data, a clmatologcally aded nterpolaton method s proposed, and wll be descrbed late. For each crop type and grd cell, the optmum startng and endng dates of growth cycles are determned automatcally based on ar temperature, precptaton and the calculaton of Potental Evaporaton Transpraton (PET. Usng potental producton bomass smulaton model, photosynthess rate and photosynthetcally actve radaton s calculated, and then gross bomass producton and net bomass producton can be determned. The results are a seres of estmated agronomcally attanable yelds for each land unt (grd. These estmates must be related to some correcton 1046 Internatonal Archves of Photogrammetry and Remote Sensng. Vol. XXXIII, Part B4. Amsterdam 2000.

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4 3.2 Qualty Control In Clmatc Interpolaton In order to reduce the uncertan n ar temperature and precptaton nterpolaton such as no enough sample ponts and ll-dstrbuton sample ponts n external nterpolaton, an nterpolatng qualty control model s T = Ω = 1 n n ( T T ( n 1 (1 = 1 n = 1 T 2 Where T s the clmatc dfference between the lower-resoluton staton temperature or precptaton of nterest T and the clmatologcal clmate average temperature or precptaton T n hgh-resoluton, n s the number of lower-resoluton staton, T s average dfference temperature or precptaton, and Ω s standard devaton. If there are no enough statons n a fx searchng dstance area nearby grd j, then we use T nstead of nterpolaton value T j. If T j s more than T + 3Ω, we thnk nterpolaton n grd j s ll-condton and make T j = T + 3Ω. Otherwse f T < T 3Ω, then make T j = T 3Ω. j 3.3 Monthly Temperature Aded Weekly Ar Temperature Interpolaton Because CAI monthly average temperatures and precptaton have a hgh accuracy, we can nterpolate weekly ar temperature and precptaton more accuracy by the adng of CAI monthly temperature. Ths nterpolaton procedure s termed space-tme nterpolaton. The formula s gven follow T T jw = = k 2 w= k1 m2 m= m1 ( T [ T jw dwm N m + ( T T jw d ] 7 wm (2 Where d wm s the number of days n w th week on m th month, N s the number of days on m th month, k1 and k2 m are the start-week and end-week on m th month, m1 and m2 are the months that w th week spanned, T jw and T are weekly average ar temperature or precptaton and CAI monthly average ar temperature or precptaton at any locaton j correspondngly. 4 A CASE FOR GLOBAL WHEAT POTENTIAL PRODUCTIVITY ESTIMATION Our tests of above-descrbed methodologes are made by estmatng wheat potental productvty. Clmate data wth tme seres of daly maxmum, mnmum temperature, precptaton and elevaton for 6400 avalable terrestral statons over the perod from 1977 to 1991 s our lower-resoluton network. Fgure 2 s the dstrbuton of the global weather staton. A monthly long-term average ar-temperature and precptaton that nterpolated from nearly terrestral statons recorded from 1890 to 1989 by Legates and Wllmott (1990 serves as hgh-resoluton clmatoloy. A DEM at a spatal resoluton of 5 by 5 s also used to obtan the georeferenced heghts for grd networks. The sol data wth dfferent layer bulk-densty, whch provded by The Global Sol Data Task co-ordnatng wth the Data and Informaton System (DIS framework actvty of the Internatonal Geosphere-Bosphere Programme (IGBP, s used. The sol data resoluton s also 5 by 5. The global land resources nventory comprses 4320 by 2160 grd cells wth resoluton of 5 by 5. Fgure 3 are some of the weekly ar temperature nterpolated by CAI and space-tme nterpolaton methods respectvely. In the same way, weekly precptaton was nterpolated. There are many models to estmate evaporaton rate. Here Lnacre model s 1048 Internatonal Archves of Photogrammetry and Remote Sensng. Vol. XXXIII, Part B4. Amsterdam 2000.

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6 1050 Internatonal Archves of Photogrammetry and Remote Sensng. Vol. XXXIII, Part B4. Amsterdam 2000.