Remote sensing has had to offer an ever-growing wealth of information to monitor land processes and vegetation. From optical indices that intercept photosynthesis, to thermal sensors that sip out water stress, to microwaves that carve out canopy structure. But stay tuned. THE major operational breakthrough of this decade is, with no doubt… . Without CRISPINESS, you wouldn’t see your cat in your driveway (okay, okay, your car). Without CRISPINESS, Google Earth wouldn’t exist. Without CRISPINESS, geography would remain an academic fantasy. Without CRISPINESS, you cannot relate to the people on the ground. You cannot relate to your neighbors. You cannot relate to yourself… well, wait a minute. Of course you can, but without optical depth. Without a projection. WITHOUT A PERSPECTIVE. Remote sensing today is the unmatched source of spatial inputs to deal with the large, heterogeneous areas associated with agricultural landscapes. Remote sensing today is this other mirror on your wall. The mirror that reflects on how well you spread out. “Mirror, mirror on the wall, what does tomorrow hold for us all?”Doubtful still? Check this out:
Above: Tractor-trailer separation on main Koutiala-Koury highway: 124cm (Sukumba, Mali)
Above: Average hill separation, compound yam field: 153cm (Pisii, Ghana)
Above: Average furrow width, low fertility millet-cowpea field: 204cm (Serkin Hawsa, Niger)
Not yet convinced? Fair enough. Some more food for thought here (please be honest and tell us if you’ve seen these figures elsewhere):
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Site
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FAN1
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NOB1
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PIS1
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SER1
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SUK1
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TEG1
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Estimated space saturation (% cropland)
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31.76
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20.35
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22.70
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61.55
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30.28
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25.20
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Number of smallholder fields extracted
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823
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2031
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2488
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3765
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1548
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826
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Tentative field size, ha (avg ± stdev) 2
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2.5 ± 2.97
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0.73 ± 1.15
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0.59 ± 0.69
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1 ± 0.98
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1.33 ± 1.15
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1.97 ± 1.61
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Tentative field geometry (compacity index)2
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0.07
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0.77
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0.75
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0.77
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0.22
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0.07
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% of smallholder fields by toposequence class (lo/md/hi)3
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To be released soon – please check our blog
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Standardized field-level NDVI anomaly (average)
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0.07
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0.03
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0.04
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0.03
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0.08
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0.10
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Tentative field slope (avg ± stdev) 4
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1.17 ± 3.34
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1.58 ± 0.95
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1 ± 1.29
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1.84 ± 1
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2.45 ± .0.59
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1.77 ± 0.78
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1. FAN = Fansirakoro, Mali; NOB = Nobere, B. Faso; PIS = Pisii, Ghana; SER = Serkin Hawsa, Niger; SUK = Sukumba, Mali; TEG = Tegena, Mali
Above: Illustration of protomap printouts produced for SIBWA partner communities – here, Nobere, Burkina Faso (provisional field limits on top of natural color composite, NDVI anomaly, standardized field-level anomalies)
Okay stop. Let’s step back a moment now. Could there be any reasonable justification that rural communities in Africa (or anywhere BTW) be deprived of access to such key information? Critical metrics to help them inject elements of agricultural landscape DESIGN in their development plans? Meaningful maps to help them DEVISE new development plans from scratch? After all, over 60% of Sub-Saharan Africa’s population is rural. How much longer will they have to wait? How much longer will they have to flight, because we failed to provide one essential tool to slow down rural exodus? You decide and you tell them. Because now Pandora’s box is open. And the news is spreading.
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