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oz1 last won the day on December 6 2012

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  1. To Admin, Please reactivate my account. Thank you
  2. oz1


    Geoimage in Australia claim to supply. We haven't bought from them as yet & they say that the ALOS people are not the easy to deal with so might be worth a try. They close for Christmas soon. https://www.geoimage.com.au/-dems/5m-grid
  3. Creating DEMs from contours commonly produces steps around the contour locations unless the contours are very closely spaced. Try looking at the histogram of your DEM with small bins to see how bad the problem is. One partial solution I have used along streams is as follows: 1. Extract the points along the individual stream segments then interpolate elevations between them. For example, let's say your elevation points are 50 m apart (distance not elevation), then create a set of points 10 m apart. I believe the ET Geowizards let's you create these "station points". Hawth's Tools used to let you do this also for older versions of ARCMAP - not sure about its successor. 2. Since you know the distance of the station points along the stream line, you can interpolate elevations for them from your known elevations along the stream line. Do this outside ARCMAP using data from the dbf file. 3. Convert your contours to points & add your station point elevations. 4. Recreate the DEM raster from the points. This won't fix the step issue elsewhere but it will create stream lines that flow downhill,
  4. Mamadouba is dead right about the need to understand the landscape & the rate of change. Also, you need to be aware of what NDVI actually measures. The following points apply: 1. NDVI or a similar index (they all have pluses & minuses) will tell you something about how green vegetation changes. It is not a good indicator of dry vegetation.Thus, after rain, you will get a strong NDVI signal but after green vegetation dries off, it becomes yellow, brown or grey & your NDVI signal drops off, even though you may have exactly the same amount of ground cover by plants. Essentially, all that happens is that you are swapping green biomass for dry biomass. This is not desertification. Also, a strong NDVI signal may indicate encroachment by woody shrubs at the expense of herbage. In some parts of the world, this is a form of land degradation. 2. NDVI varies in response to rainfall. If your rainfall varies seasonally, you will need to filter out the wet/dry season variation & to extract a longer term trend over time. This will require a time series of data. If your rainfall is variable over longer periods (i.e. subject to ENSO generated wet & dry periods), that will give you substantial NDVI variation over time. Again, to detect true desertification (i.e. loss of the ability of a landscape to produce plant biomass from rainfall), as opposed to short term drought, you will need to filter out the effects of rainfall variability. Hence, the need for a long time series of whatever index you plan to use. The length of the time series needed will depend on the amount of rainfall variability in your environment. 3. Desertification is a term that means different things to different people. I have seen it widely misused & frequently confused with changes in vegetation cover associated with long term changes in rainfall (i.e. confused with the effects of drought). I think what you are after is a loss of landscape resilience, i.e. a capacity to bounce back from imposed stresses, be they natural or man-made. When you develop your methods of analysing a time series of satellite data, you need to show that loss of landscape resilience can be proven. Almost certainly, this will require a long time series of data which forces you to use Landsat or AVHRR. There are exceptions but these are restricted to situations where you have rapid & extreme land degradation. 4. There is loads of this stuff in the literature. Australian researchers probably produced the best developed methods for separating land degradation from rainfall variability & drought using both time series & spatial patterns in remotely sensed data.
  5. Thanks Darksabersan. You're a gentleman.
  6. Would appreciate some help with this as the help section doesn't I have a jpeg RGB image "test.jpg" with some white areas that I want to set to null. The white values are B=251, G=255, R=255. I cannot for the life of me get ARCMAP to do this. Have been trying Set Null from the Spatial Analyst conditional toolbox as follows: Input conditional raster - test.jpg Expression - value>=251 Input false or constant raster - test.jpg Output raster - SetNull_jpg4 Result is an error message: ERROR 010152: Object IRasterStatistics is null. ERROR 010152: Object IRasterStatistics is null. ERROR 010152: Object IRasterStatistics is null. Failed to execute (SetNull). What am I doing wrong?
  7. Does anybody know what's going on? When I search the Glovis website, it is no longer possible to download any Level 1 imagery for Landsat 4 & 5 data. That product is greyed out in the Item basket
  8. What software do people recommend for gridding lidar data. What pros & cons for each software package. Thanks
  9. oz1

    Grid Editor

    thanks Lurker
  10. oz1

    Grid Editor

    Could anyone recommend a grid editor please. I want to modify the values in a floating point tiff file, preferably on screen There used to be a good one in TNTMIPS but I don't have it any more.
  11. Thanks for the veg index info Emperor. Looking at the size of trees suggests a resolution of 1-2 m is needed.
  12. I would like to monitor forest dieback over time using remote sensing. It's happening in scattered small areas & is very patchy so Landsat TM does not have enough resolution. Could anyone help by suggesting which satellite to use (Worldview?) and what is the best vegetation index or data transform please?
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